A study on major overhaul or replacement decision of a pendulum ride (Gyro Swing - Claw) at theme park
- Authors: Madawala, Senarath , Chattopadhyay, Gopinath , Chundhoo, Vickram , Kandra, Harpreet , Summers, Adrian
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022, Anand, India, 12-15 December 2022, 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022
- Full Text: false
- Reviewed:
- Description: Routine maintenances are useful for reducing downtimes of rides in theme parks. Breakdown maintenances impact on the maintenance budget and customer experience and there is a possibility to minimize the unnecessary down time with the right decision on maintenance and replacements. Gyro swing is one of the oldest rides in the park studied in this paper. It will complete the 20 years of service life by 2024. Organization will have to allocate significant time, cost, and manpower for annual maintenance, shutdown for twenty-year overhaul or replacement. Cost for overhaul is estimated close to 2.23M AUD for the components, manpower, spare and services and 3.42M AUD for a replacement. This paper is on analysis and findings from a study conducted to evaluate the feasible economic decision on whether to overhaul or replace. © 2022 IEEE.
A systematic literature review on the evaluation of business simulation games using PRISMA
- Authors: Faisal, Nadia , Chadhar, Mehmood , Goriss-Hunter, Anitra , Stranieri, Andrew
- Date: 2022
- Type: Text , Conference paper
- Relation: 33rd Australasian Conference on Information Systems: The Changing Face of IS, ACIS 2022, Melbourne, 4-7 December 2022, ACIS 2022 - Australasian Conference on Information Systems, Proceedings
- Full Text:
- Reviewed:
- Description: In recent years, organisational software process education has seen a considerable uptick in interest in adopting business simulation games (BSGs) as a novel learning resource. However, the lack of reliable and valid instruments to evaluate simulation learning outcomes inhibits the adoption and progress of simulation in Information System education. To fill this need, we performed a systematic review of 33 empirical studies using the PRISMA declaration approach to identify the different evaluation methods used to analyse BSG learning outcomes. We created a concept matrix using a didactic framework that categorised these assessment methodologies into three game stages (pre-game, in-game and post-game). We established a comprehensive evaluation strategy using this concept matrix, which teachers and researchers may use to choose the best appropriate evaluation method to analyse a wide range of learning outcomes of business simulation games. Copyright © 2022 Faisal, Chadhar, Goriss-Hunter & Stranieri.
Abnormal entity-aware knowledge graph completion
- Authors: Sun, Ke , Yu, Shuo , Peng, Ciyuan , Li, Xiang , Naseriparsa, Mehdi , Xia, Feng
- Date: 2022
- Type: Text , Conference paper
- Relation: 22nd IEEE International Conference on Data Mining Workshops, ICDMW 2022, Orlando USA, 28 November to 1 December 2022, Proceedings: 22nd IEEE International Conference on Data Mining Workshops Vol. 2022-November, p. 891-900
- Full Text: false
- Reviewed:
- Description: In real-world scenarios, knowledge graphs remain incomplete and contain abnormal information, such as redundan-cies, contradictions, inconsistencies, misspellings, and abnormal values. These shortcomings in the knowledge graphs potentially affect service quality in many applications. Although many approaches are proposed to perform knowledge graph completion, they are incapable of handling the abnormal information of knowledge graphs. Therefore, to address the abnormal information issue for the knowledge graph completion task, we design a novel knowledge graph completion framework called ABET, which specially focuses on abnormal entities. ABET consists of two components: a) abnormal entity prediction and b) knowledge graph completion. Firstly, the prediction component automati-cally predicts the abnormal entities in knowledge graphs. Then, the completion component effectively captures the heterogeneous structural information and the high-order features of neighbours based on different relations. Experiments demonstrate that ABET is an effective knowledge graph completion framework, which has made significant improvements over baselines. We further verify that ABET is robust for knowledge graph completion task with abnormal entities. © 2022 IEEE.
An effective traffic management approach for decentralized BSNs
- Authors: Zahid, Noman , Alkhayyat, Ahmed , Ismail, Muhammad , Sodhro, Ali
- Date: 2022
- Type: Text , Conference paper
- Relation: 96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022, London, 26-29 September 2022, 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Proceedings Vol. 2022-September
- Full Text: false
- Reviewed:
- Description: Wireless technology and sensing devices are playing an important role in healthcare, known as Body Sensor Networks (BSNs). Existing wearable technologies process vast amounts of data with critical quality of service (QoS) requirements in terms of delay, reliability, and throughput. This study provides a traffic prioritizing strategy that ensures synchronization, optimal traffic control, and resource optimization. It includes a method for reducing delay and enhancing throughput, and the energy efficiency of BSNs. In addition, we investigated that implementation of access periods improves the channel accessing strategy for high priority nodes with increased starvation for high data rates in low priority nodes. M/G/1/K queue with finite buffer is implemented to overcome poor resource utilization. Simulation results showed that implementing a finite buffer had enhanced resource utilization in terms of higher throughput and bandwidth efficiency. © 2022 IEEE.
An ensemble of machine learning and clinician set thresholds for vital signs alarms
- Authors: Mai, Shenhan , Balasubramanian, Venki , Arora, Teena
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Australasian Computer Science Week, ACSW 2022, Virtual, Online, 14-17 February 2022, ACM International Conference Proceeding Series p. 232-234
- Full Text:
- Reviewed:
- Description: High false alarm rates is a common issue in patient vital sign monitoring systems and may result in alarm fatigue for medical workers and even cause alarm-related patient deaths. In this study, the research toward the use of ensemble learning that combines a feed forward back propagation neural network, a random forest and manually set threshold based alarms is used. A method for estimating the false alarm rate using the machine learning, to help clinicians set thresholds is also proposed. Experimental results to date on a small dataset are promising. © 2022 ACM.
An interpretive study of stakeholders privacy issues in blockchain : a healthcare context
- Authors: Singh, Supreet , Firmin, Sally , Chadhar, Mehmood
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Australasian Computer Science Week, ACSW 2022, Virtual, Online, 14-17 February 2022, ACM International Conference Proceeding Series p. 235-238
- Full Text: false
- Reviewed:
- Description: Ever-growing and rapidly changing healthcare information systems (HIS) encourage many new technologies to integrate with it to enrich the treatment and facilitate patients. Blockchain, a decentralised digital ledger, is legitimately disrupting traditional HIS due to its characteristics such as immutability, interoperability, decentralise, and security. Blockchain' applications in healthcare industries are attracting investors and organisations to develop platforms for future. However, security and privacy concerns hinder blockchain adoption in the health sector. Therefore, there is a need to develop deeper understandings about these issues and require strategies to address these issues so that the desired values can be obtained. Besides, privacy could mean different to different people such as patients, doctors, and admin staff. Therefore, there is a need to explore it from various stakeholder perspectives too. Using interpretive qualitative research approach, this research-in-progress will extend the body of knowledge by scrutinising the stakeholders' perception of privacy concerns and its relationship in blockchain based HIS. The findings of this study will contribute to address privacy issues emerged from the research and help to eliminate them before implementing blockchain. This paper supplies an appropriate research approach for multidimensional research in healthcare. In addition, this research-in progress will formulate a framework which provide awareness to stakeholders about privacy issues when they use blockchain based HIS in future. © 2022 ACM.
An overview of demand response opportunities for commercial and industrial customers in the Australian NEM
- Authors: Amin, B.M. Ruhul , Shah, Rakibuzzaman , Hasan, Kaz , Tayab, Usman , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 14th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2022, Melbourne, 20-23 November 2023, 2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC) Vol. 2022-November
- Full Text: false
- Reviewed:
- Description: Different demand response (DR) mechanisms available in the Australian national electricity market (NEM), such as wholesale, ancillary, emergency, and network DR could provide significant flexibility to maintain and enhance power system security and reliability. Australian Energy Market Operator (AEMO) is continually reviewing global practices working with different states and territories, and revising the legislative and technical requirements for integrating more DR participants into the national electricity market (NEM). Commercial and Industrial (CandI) customers have a higher potential to participate in DR with flexible larger loads and onsite distributed energy resources (DERs). The CandI customers can reduce their energy bills and earn incentives from operators through DR participation. This paper provides a comprehensive review of different types of DR mechanisms that have been used in the Australian NEM. Technical and legislative requirements to participate in DR for CandI customers have been identified and summarised. Furthermore, the challenges for DR participation and potential benefits have been highlighted. Finally, a look-up table is prepared to identify the suitability of CandI customers to participate in one or multiple DR mechanisms potentially. The findings of this paper can be used as a guiding tool for CandI customers to understand technical and legislative requirements for participating in different DR mechanisms in Australia and select the most appropriate DR mechanisms for maximising their benefits. © 2022 IEEE.
Anomaly detection on health data
- Authors: Samariya, Durgesh , Ma, Jiangang
- Date: 2022
- Type: Text , Conference paper
- Relation: 11th International Conference on Health Information Science, HIS 2022, Virtual, Online, 28- 30 October 2022, Health Information Science, 11th International Conference, HIS 2022, Virtual Event, October 28–30, 2022, Proceedings Vol. 13705 LNCS, p. 34-41
- Full Text: false
- Reviewed:
- Description: The identification of anomalous records in medical data is an important problem with numerous applications such as detecting anomalous reading, anomalous patient health condition, health insurance fraud detection and fault detection in mechanical components. This paper compares the performances of seven state-of-the-art anomaly detection algorithms to do detect anomalies in healthcare data. Our experimental results in six datasets show that the state-of-the-art method of isolation based method iForest has a better performance overall in terms of AUC and runtime. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Application of slope mass rating and kinematic analysis along road cut slopes in the Himalayan terrain
- Authors: Siddique, Tariq , Sazid, Mohammed , Khandelwal, Manoj , Varshney, Harsh , Irshad, Sayem
- Date: 2022
- Type: Text , Conference paper
- Relation: International Conference on Geotechnical challenges in Mining, Tunneling and Underground structures, ICGMTU 2021, Virtual, Online, 20-21 December 2021, Lecture Notes in Civil Engineering Vol. 228, p. 697-708
- Full Text: false
- Reviewed:
- Description: Hundreds of fatalities are being reported every year due to rampant slope failures along road-cut engineered slopes in the Himalayan region. Prevailing perilous conditions of cut slopes are mainly due to adverse geological attributes and ever-rising anthropogenic factors. To procure a landslide resilient design along roads in mountainous regions, a systematic geotechnical investigation is required. In this regard, the characterization of vulnerable slopes through empirical classification systems is of paramount importance for geotechnical appraisal. Eleven vulnerable road cut slopes along national highway-5 (NH-5), from Solan to Shimla have been studied herein. The present study incorporates the application of Slope Mass Rating (SMR) and its extensions, including Continuous Slope Mass Rating (CSMR) and Chinese Slope Mass Rating (ChSMR) to study various slopes. The outcomes of SMR and its extensions are used to classify cut slopes into different stability grades. In addition, prevailing structurally controlled failures have also been assessed by kinematic analysis. The majority of slopes are liable to undergo planar and wedge failures. The outcomes obtained by kinematic analysis, SMR and its extensions are used to propose adequate remedial measures. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Attractiveness based conference ranking
- Authors: Zhang, Chen , Febrinanto, Falih , Liu, Mujie , Kong, Xiangjie , Zhang, Dongyu , Islam, Sardar
- Date: 2022
- Type: Text , Conference paper
- Relation: 37th ACM/SIGAPP Symposium on Applied Computing, SAC 2022, Virtual, online, 25-29 April 2022, Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing p. 803-806
- Full Text: false
- Reviewed:
- Description: Conferences have a significant impact on the academic world. Academic conferences aim to exchange information about research results with others. The quality of the conference is highly considered because it involves the credibility of the research papers produced. Creating a ranking system is an effective way to measure conference quality and compare it with other venues. The existing conference ranking systems do not have a unified index or are still manually evaluated by humans, so there is a gap to create an academic conference evaluation system that is objective, comprehensive, and universal. To further improve the ranking system, we propose two new indicators in this work. In these two indicators, we quantify the attractiveness of conferences and combine them with the traditional three indicators to calculate the scores of 10 conferences in the field of data science through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. The proposed new evaluation system can help authors understand conferences more comprehensively and screen conferences more sensibly. © 2022 ACM.
Behavioral modeling and cognitive assessment in smart textiles
- Authors: Oatley, Giles , Choudhury, Tanveer , Buckman, Paul
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Australasian Computer Science Week, ACSW 2022, Virtual, Online, 14-17 February 2022, ACM International Conference Proceeding Series p. 229-231
- Full Text: false
- Reviewed:
- Description: Smart textiles can be used as innovative solutions to amuse, meaningfully engage, comfort, entertain, stimulate, and to overall improve the quality of life for people living in care homes with dementia or its precursor mild cognitive impairment (MCI). We have developed a prototype smart textile system that uses capacitive sensing to loosely couple the textile overlay from the underlying technology layer. This inclusion of technology adds to the user experience and quality of life is increased. Additionally, by using microelectronics, light-emitting diodes (LEDs) and capacitive touch sensors we can represent and design a range of sophisticated memory and reasoning diagnostic/ assessment tools, which are detailed in this paper. © 2022 ACM.
Blockchain based smart auction mechanism for distributed peer-to-peer energy trading
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, Virtual, online, 3-7 January 2022, Proceedings of the Annual Hawaii International Conference on System Sciences Vol. 2022-January, p. 6013-6022
- Full Text:
- Reviewed:
- Description: Blockchain based framework provides data immutability in a distributed network. In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading. Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare. We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment. The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts. Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods. © 2022 IEEE Computer Society. All rights reserved.
Collision-free minimum-time trajectory planning for multiple vehicles based on ADMM
- Authors: Nguyen, Thanh , Nguyen, Thang , Nghiem, Truong , Nguyen, Linh , Baca, Jose , Rangel, Pablo , Song, Hyoung-Kyu
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022, Kyoto, Japan, 23-27 October 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Vol. 2022-October, p. 13785-13790
- Full Text: false
- Reviewed:
- Description: The paper presents a practical approach for planning trajectories for multiple vehicles where both collision avoidance and minimum travelling time are simultaneously considered. It is first proposed to exploit the mixed-integer programming (MIP) approach to formulate the collision avoidance paradigm, where the linear dynamic models are utilized to derive the linear constraints. Moreover, travelling time of each vehicle is compromised among them and set to be minimized so that all the vehicles can practically reach the expected destinations at the shortest time. Unfortunately, the formulated optimization problem is NP-hard. In order to effectively address it, we propose to employ the alternating direction method of multipliers (ADMM), which can share the computational burdens to distributive optimization solvers. Thus, the proposed method can enable each vehicle to obtain an expected trajectory in a practical time. Convergence of the proposed algorithm is also discussed. To verify effectiveness of our approach, we implemented it in a numerical example, where the obtained results are highly promising. © 2022 IEEE.
Community capacity to envisage a post-mine future: rehabilitation options for Latrobe Valley brown coal mines
- Authors: Reeves, Jessica , Baumgartl, Thomas , Morgan, D. , Reimers, Vaughan , Green, Michael
- Date: 2022
- Type: Text , Conference paper
- Relation: 15th International Conference on Mine Closure, Mine Closure 2022, Brisbane, Australia, 4-6 October 2022, Proceedings of the International Conference on Mine Closure Vol. 1, p. 173-185
- Full Text:
- Reviewed:
- Description: Since closure of the Hazelwood Power Station in 2017, and the associated Morwell open cut mine, the community of the Latrobe Valley have largely come to terms with the coming end of an industry that for almost a century defined their region. However, the capacity for the community to envisage what comes next has been limited. This is in part due to uncertainty of the viability of options for rehabilitation, future ownership and responsibility for the sites, and a challenging policy framework. It is also related to systemic social issues, such as mistrust of both government and energy companies, as well as over-consultation fatigue. We draw here on findings from a recent study, commissioned by AGL Loy Yang, on the community perspectives on the final void forms and future land and water uses of the three Latrobe Valley open cut brown coal mines - and surrounding lands. The data were obtained through a series of focus groups with key stakeholders, including community organisations, environmental groups, government authorities, business groups, primary producers and Traditional Owners; and a web-based survey, completed by over 560 participants. From this we found a common theme concerning a desire to have the land returned to the community and to leave a positive legacy for the sites. Options that were visually attractive and enabled either recreation and/or tourism were preferred to future industrial uses; environmental benefit was also a strong priority. Authentic community consultation necessitates that the community be empowered to make an informed contribution to the discussion, and that they are made aware of how their input will be utilised. The community of the Latrobe Valley are invested in having a positive outcome for their region, which future generations can benefit from. To achieve this, the community must be actively engaged in the process. © 2022 Australian Centre for Geomechanics, Perth.
Comparison between wired versus wireless mode of digital protection scheme leveraging on PRP topology
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 4th IEEE Sustainable Power and Energy Conference, iSPEC 2022, Virtual, online, 4-7 December 2022, Proceedings - 2022 IEEE Sustainable Power and Energy Conference, iSPEC 2022
- Full Text: false
- Reviewed:
- Description: Applications of Digital communication in power systems have undergone revolutionary changes in the last decade due to the advancement in technology encompassing substation automation system (SAS). The reasons for veering away from traditional copper based secondary wiring for protection schemes to Ethernet and fiber optic (FO) include economic gains, faster project delivery, ease of diagnostics, less engineering and design efforts. However, digital systems still comprise some challenges such as latencies, data losses, and packet clogging during high traffic. Errors in packets transmission and associated difficulties in publication and subscription of generic object-oriented substation events (GOOSE) and sampled value (SV) packets in a Wide Area Network (WAN) substation based on IEC 62439-3 protocol call for a detailed investigation. This paper compares the performance of wired and wireless mode of digital secondary scheme based on simulation and physical set up leveraging on Parallel Redundancy Protocol (PRP) topology. It presents different scenarios for SV packets in a process bus and provides analysis to the data packet transmission due to traffic and network clogging in wired and wireless topologies. © 2022 IEEE.
Contrastive GNN-based traffic anomaly analysis against imbalanced dataset in IoT-based ITS
- Authors: Wang, Yang , Lin, Xi , Wu, Jun , Bashir, Ali , Yang, Wu , Li, Jianhua , Imran, Muhammad
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 IEEE Global Communications Conference, GLOBECOM 2022, Virtual, online, 4-8 December 2022, 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings p. 3557-3562
- Full Text: false
- Reviewed:
- Description: The traffic anomaly analysis in IoT-based intelligent transportation system (ITS) is crucial to improving public transportation safety and efficiency. The issue is also challenging due to the unbalanced distribution of anomaly data in IoT-based ITS, which may cause overfitting or underfitting in the training phase. However, some research on traffic anomaly analysis injected limited data to address the shortage of anomaly samples or even neglects this issue, which overlooks the potential representation of nodes in graph neural networks. In this paper, we propose an improved contrastive GNN-based learning framework for traffic anomaly analysis that alleviates the problem of imbalanced datasets in the training phase. In this framework, we provide a graph augmentation approach with coupled features to learn different views of graph data. Besides, we design an effective training method based on the contrastive loss for our framework, which can learn the better performance of latent representations utilized in the downstream tasks. Finally, we conduct extensive experiments to evaluate the performance of our proposed frame-works based on real-world datasets. We demonstrate that our framework achieves as high as 6.45% precision improvement compared to the state-of-the-art. © 2022 IEEE.
Coordinated hierarchical control strategy for islanded ac/dc hybrid microgrids
- Authors: Shan, Yinghao , Ma, Liqian , Liu, Huashan , Hu, Jiefeng
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Asia Power and Electrical Technology Conference, APET 2022, Virtual, online, 11-13 November 2022, 2022 Asia Power and Electrical Technology Conference, APET 2022 p. 132-137
- Full Text: false
- Reviewed:
- Description: To meet future practical needs of smart grids, constructing hybrid ac&dc microgrids with the two-type sub-grids becomes more realistic and urgent. However, in the existing literature, it is rare to see the joint controls of these sub-grids in islanded hierarchical control architecture. To this end, a coordinated hierarchical control strategy for this kind of hybrid microgrid has been presented in this paper, where both sub-grids are equipped with primary and secondary controllers. Using the proposed strategy, the power flows can be autonomously shared and deviated bus voltages can be fully restored. The control performance and stability of the overall microgrid system have been ensured to address different ac/dc load changes. Comprehensive simulation studies have verified the validity of the proposed strategy for hybrid microgrids. © 2022 IEEE.
Cyber resilience modelling for the operations of hybrid network
- Authors: Ur-Rehman, Attiq , Kamruzzuman, Joarder , Gondal, Iqbal , Jolfaei, Alireza
- Date: 2022
- Type: Text , Conference paper
- Relation: 20th IEEE International Conference on Dependable, Autonomic and Secure Computing, 20th IEEE International Conference on Pervasive Intelligence and Computing, 7th IEEE International Conference on Cloud and Big Data Computing, 2022 IEEE International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2022, Falerna, Italy, 12-15 September 2022, Proceedings 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
- Full Text: false
- Reviewed:
- Description: Cyber resilience is referred to as the ability to resist cyber-attacks and it has several dimensions to evaluate. This study focuses on cyber resilience evaluation of nodes in hybrid network operations. This paper proposes a framework to evaluate cyber resilience and its integration with the CVSS (Common Vulnerability Scoring System) framework. CVSS is an industry standard to assess node vulnerabilities. The integration of cyber resilience with the CVSS framework will help cyber industry to standardise the node resilience capabilities for their operations. The proposed modelling is assessed and compared with our previous work on CVSS-based vulnerability evaluation for IoT and industrial integrated systems called CVSSIoT-ICS. The comparison results validate that the proposed model better evaluates the node vulnerabilities by incorporating the resilience capability of that nodes. © 2022 IEEE.
Deep learning model to empower student engagement in online synchronous learning environment
- Authors: Godly, Cinthia , Balasubramanian, Venki , Stranieri, Andrew , Saikrishna, Vidya , Mohammed, Rehena , Chackappan, Godly
- Date: 2022
- Type: Text , Conference paper
- Relation: 19th IEEE India Council International Conference, INDICON 2022, Kochi India, 24-26 November 2022, INDICON 2022 - 2022 IEEE 19th India Council International Conference
- Full Text:
- Reviewed:
- Description: Following the start of the pandemic, online synchronous learning has grown significantly. The higher education sector is searching for new creative ways to provide the information online because of the switch from face-to-face to online synchronous course delivery. Students are also becoming accustomed to studying online, and research has shown that synchronous online learning has a variety of effects on student engagement. For instance, according to statistics from the National Survey of Student Engagement, students are less likely to participate in collaborative learning, studentfaculty interactions, and conversations when learning online if they use quantitative reasoning during face-to-face instruction. Additionally, studies suggest that because they depend on their devices to take online classes, students feel more alienated from their lecturers. This has been linked to a drop in contacts with peers and teachers as a result. By using a cutting-edge deep learning model to predict learner engagement behaviour in a synchronous teaching environment, our research intends to improve online engagement. The model with a clever trigger will encourage the disengaged pupils to communicate with the teachers online. Smart triggers will be built around factors that have been found, focusing on disengaged students to engage them in real-time with automatic, personalized feedback. © 2022 IEEE.
Design of hybrid power system stabilizer for dynamic stability improvement using cultural algorithm
- Authors: Patel, Jasmeen , Das, Narottam , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 4th IEEE Sustainable Power and Energy Conference, iSPEC 2022, Virtual, online, 4-7 December 2022, Proceedings - 2022 IEEE Sustainable Power and Energy Conference, iSPEC 2022
- Full Text: false
- Reviewed:
- Description: In power system the stability is an important property that varies on the operational condition and the interruption to which it is exposed. The power system network endangered to the similar disruption can be stable at one operational situation (e.g., in off-peak hours) and not stable at another (e.g., at peak times). Similarly, a network at one operational situation can be stable to one disturbance and not stable to another. Consequently, stability reports generally involve the analysis of several cases, in order to cover various disruptions of interest and the key points of operation of the system. This research recommends various stabilizers such as, Power system stabilizers (PSS), Proportional Integration Differentiation (PID) and Fractional Order PID (FOPID) to decrease oscillations due to small signal disruption. The PSS-Voltage stabilizer generates impulses at the time of speed-change which usually results in positive PSS output. Using the FOPID procedure in relation with PSS, this approach can decrease these impulses. Using this approach, the generated impulses are finally decreased. Genetic Algorithm, particle swarm optimization and cultural algorithm are used for parameter fine-tuning of all the stabilizers. All these algorithms will help to tune parameters at soft computing level and then again tuned by two stabilizers which are FOPID and PSS. Now, again two stabilizers will tune and provide output needs to compare and average output to get required tuned values. Finally, the average of two stabilizers will field circuit and drive rotor according to the value given to it. © 2022 IEEE.