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Power module for integration of renewable hydrogen storage with bioethanol production from non-food biowastes

  • Authors: Ghayur, Adeel
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Wollongong, 3-6 December 2023, 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
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  • Description: Sustainable biofuels that do not compromise food security will play an integral role in the world's transition to renewable and circular economies. Integration of their production with surplus renewable electricity offers significant potential to improve overall system efficiencies. One such pathway is integration of bioethanol production with surplus renewable power via a power module modelled in this study. This module comprises of an electrolyzer, a Solid Oxide Fuel Cell (SOFC), a Magnesium Hydride (MgH2) Tank and two reactor columns. This module is then connected to the Carbon Negative Biorefinery, which produces bio-acetate from non-food biowastes. Simulations are carried out wherein the module converts surplus/off-peak renewable grid power to hydrogen, storing 25% in the MgH2 Tank. The MgH2 Tank releases waste heat during the storage process which is used with 75% of the electrolytic hydrogen to hydrogenate Carbon Negative Biorefinery's bio-acetate into bioethanol. Simulation results show that 15 kg of hydrogen is able to produce 120 kg of ethanol. This equates to a 77% increase in the lower heating value when compared with 15 kg of hydrogen. Simulation results also reveal that waste heat from the SOFC is enough to preheat oxygen and hydrogen, and desorb hydrogen from the MgH2 Tank during fuel cell's electricity generation. These results are encouraging, warranting further investigation into the co-production of hydrogen and ethanol as electrochemical and biochemical energy vectors. © 2023 IEEE.

Radiative heat transfer in solar particle receivers

Real-time distributed trajectory planning for mobile robots

  • Authors: Nguyen, Binh , Nghiem, Truong , Nguyen, Linh , Nguyen, Anh , Nguyen, Thang
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 22nd IFAC World Congress Vol. 56, p. 2152-2157
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  • Description: Efficiently planning trajectories for nonholonomic mobile robots in formation tracking is a fundamental yet challenging problem. Nonholonomic constraints, complexity in collision avoidance, and limited computing resources prevent the robots from being practically deployed in realistic applications. This paper addresses these difficulties by modeling each mobile platform as a nonholonomic motion and formulating trajectory planning as an optimization problem using model predictive control (MPC). That is, the optimization problem is subject to both nonholonomic motions and collision avoidance. To reduce computing costs in real time, the nonholonomic constraints are convexified by finding the closest nominal points to the nonholonomic motion, which are then incorporated into a convex optimization problem. Additionally, the predicted values from the previous MPC step are utilized to form linear avoidance conditions for the next step, preventing collisions among robots. The formulated optimization problem is solved by the alternating direction method of multiplier (ADMM) in a distributed manner, which makes the proposed trajectory planning method scalable. More importantly, the convergence of the proposed planning algorithm is theoretically proved while its effectiveness is validated in a synthetic environment. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Scalar reward is not enough JAAMAS Track

Secure-and privacy-preserving policies for distributed cooperative control of multiple vehicle systems

  • Authors: Nguyen, Binh , Nghiem, Truong , Nguyen, Linh , Nguyen, Tuy , Nguyen, Thang
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023, Orlando USA, 2-4 May 2023, Proceedings of SPIE - The International Society for Optical Engineering Vol. 12540
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  • Description: Conventional distributed formation control of multiple vehicle systems (MVSs) has two drawbacks: inflexible formation changes and explicit-value exchanges of vehicles' information such as position and velocity among all vehicles. Since formation changes are needed, each vehicle is required to update its relative position which is quite difficult in large spatial applications. Firstly, the explicit-value exchanges possibly result in two critical issues. When each vehicle policy needs to keep its information confidential from another unexpected listener, the explicit-value exchanges are invalid for the privacy policies. Additionally, the explicit-value storing or exchanging signals or parameters are much more vulnerable and dangerous to security threats. This work proposes an approach to overcome the above challenges by taking advantage of model predictive control-consensus algorithms to achieve desired formations. We will also allow the computation to be effectively distributed among the vehicle agents according to their computational capabilities. Secondly, we use the highly secure encryption scheme that empowers all computations carried out in encrypted forms, including system parameters and signals. Our results are verified by the formation control of multiple vehicles working in large-scale environments where a ground station does not touch all vehicles due to limited communication ranges and security problems. Compared to cutting-edge studies, the formation of vehicles is still able to be changed securely by the ground station without updating new formations to all vehicles. Besides, the data privacy of each vehicle is preserved by encrypting all physical signals. © 2023 SPIE. All rights reserved.

SMGKM : an efficient incremental algorithm for clustering document collections

The ethics of point of care devices and the need for AI policy frameworks in resources limited settings

  • Authors: Watts, Mimmie , Imahi, Ismaila , Gebrehiwet, Tesfay , Gmira, Maha , Cross, Wendy , Rouse, Ian
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 17th World Congress on Public Health, Italy, Rome, 2-6 May 2023, Population Medicine Vol. 5, p. 191-191
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  • Description: Access to quality healthcare is a fundamental human right and one of the Sustainable Development Goals (SDGs), as adopted by the United Nations in 2015. Thus, so is the maintenance of high ethical standards in providing healthcare. An important requirement for healthcare practitioners is the practice of the concept of avoiding harm while doing good. Advances in technology, global industrialization, and more recently Artificial Intelligence (AI) have undoubtedly led to significant improvements and advances in healthcare delivery, including the Introduction of Point-Of-Care Testing (POCT) devices that can instantly provide data about measures of a patient’s health. Unfortunately, these advances have inadvertently affected the ethical standards in the field and there are calls for appropriate structures to ensure that all healthcare beneficiaries, especially the vulnerable ones in society continue to enjoy high ethical standards expected in receiving healthcare. This article drawing on the TAM and UTAUT theories, provides comprehensive analysis on the need to develop policy and ethical framework for AI technologies in healthcare. We believe that this has great potential to accelerate scientific discovery in medicine and to improve health care services. © (2023), (European Publishing). All Rights Reserved.

Time-minimum motion handling of open liquid-filled objects using sparse sequential quadratic programming

  • Authors: Le, Hieu , Appuhamillage, Gayan , Nguyen, Linh
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023, Sivas, Turkey, 11-13 October 2023, 2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023
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  • Description: The paper presents an efficient approach to minimize motion time of an industrial robot so that it can successfully manipulate an open and liquid-filled object in pick-and-place operations. It is first proposed a motion planning optimization problem, where the total motion duration is considered as a cost function. Moreover, the robot physical limits such as its joint positions, velocities and accelerations are used as the optimization constrains. On the other hand, to ensure an open and liquidfilled object always upright, orientation constraints of the robot end-effector are taken into account. More specifically, roll and pitch of the end-effector are proposed to be fixed during the transportation, which ensures there is no tipping over in the object. The formulated motion planning optimization problem is then efficiently solved by using the sparse sequential quadratic programming method. Our approach excels in optimizing the motion trajectory by leveraging its flexibility, accommodating various trajectory shapes that satisfy the kinematic conditions. The optimization leads to more efficient and effective motion execution, resulting in a substantial reduction in the overall motion profile duration. Extensive evaluation of the proposed approach on a KUKA robot model demonstrates its effectiveness. © 2023 IEEE.

Whose data are reliable : sensor declared data reliability

  • Authors: Shafin, Sakib , Karmakar, Gour , Mareels, Iven , Balasubramanian, Venki , Kolluri, Ramachandra
  • Date: 2023
  • Type: Text , Conference paper
  • Relation: 19th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2023, Montreal, Canada, 21-23 June 2023, International Conference on Wireless and Mobile Computing, Networking and Communications Vol. 2023-June, p. 249-254
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  • Description: Sensor data is susceptible to faults, noise, and malicious attacks, posing a significant operational and security threat. Therefore, ensuring reliability of sensor data is critical for real-time monitoring systems. Prior research on sensor data reliability relies on edge or upper-layer devices for data fusion from multiple sensors, employing architectures with major overheads and latency due to transmission and storage demands. An alternative approach is to have the sensor estimate and declare its own reliability. While some methods involve sensors computing data confidence and including it in payloads, limitations arise in the absence of neighboring sensor data, and communication overheads are incurred. To address this problem, this paper proposes an innovative approach to enhance the reliability of sensor data using an intelligent self-declaration process. Proposed reliability estimation is evaluate with three lightweight estimation algorithms, namely, Kalman Filter, Holt-Winters Method, and Mahalanobis Distance using sensor's historical data. The reliability level is then added to the three reserved bits of a TCP packet header which results in zero additional overhead. Experiments conducted using real-world sensor data (from water quality monitoring systems) obtained from our IoT lab demonstrate the effectiveness of our proposal and the potential for application in real-world sensor-based applications. © 2023 IEEE.

A cloud-based IoMT data sharing scheme with conditional anonymous source authentication

  • Authors: Wang, Yan-Ping , Wang, Xiao-Fen , Dai, Hong-Ning , Zhang, Xiao-Song , Su, Yu , Imran, Muhammad , Nasser, Nidal
  • 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. 2915-2920
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  • Description: As a rapidly growing subset of the Internet of Thing (IoT), the cloud-based Internet of Medical Thing (IoMT) has been widely applied in remote healthcare industries, which allows the physicians to monitor patients' body parameters remotely to offer continuous and timely healthcare. These healthcare parameters usually contain sensitive information, such as heart rates, glucose levels and etc., and the exposure of them may pose serious threats to the patients' health and lives. To guarantee security and privacy, many IoMT data sharing schemes have been proposed. However, most of these schemes either exhibit a one-to-one data sharing structure or fail to protect the patients' privacy. Since the data usually needs to be shared to different physicians, patients may want to be assisted without revealing their identities. To meet these requirements in healthcare systems, we propose a multi-receiver secure healthcare data sharing scheme, in which the patients are allowed to share their IoMT data to multiple physicians simultaneously for a multidisciplinary treatment, and the conditional anonymity is achieved where data source authentication is provided without revealing the patient's identity. When the patient health condition is abnormal, the hospital can correctly and quickly trace the patient's identity and inform him/her immediately. Our scheme is formally proved to achieve multiple security properties including confidentiality, unforgeability and anonymity. Simulation results demonstrate that the proposed scheme is efficient and practical. © 2022 IEEE.

A generative adversarial active learning method for effective outlier detection

  • Authors: Bah, Mohamed , Zhang, Ji , Yu, Ting , Xia, Feng , Li, Zhao , Zhou, Shuigeng , Wang, Hongzhi
  • Date: 2022
  • Type: Text , Conference paper
  • Relation: 34th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2022, Virtual, online, 31 October-2 November 2022, Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI Vol. 2022-October, p. 131-139
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  • Description: Outlier detection is an important data mining task, and developing effective methods to detect outliers is challenging in cases where there is insufficient labeled data. Manually labeling the data is labor-intensive and time-consuming. Because of a limited number of labeled samples, the classes are unbalanced, resulting in a class-imbalance problem. Existing methods fail to address these aforementioned issues holistically and fall short in generating quality outlier samples for effective outlier detection accuracy. In this paper, we propose a new solution that tackles these problems. We propose a. Generative Adversarial Active Learning method (DIR-GAAL), which generates Diverse, Informative, and Representative outlier samples through active learning, and employs the mini-max game between the generator and discriminator in a generative adversarial network. We conducted extensive experiments on several benchmark datasets to evaluate the performance of our method. When compared to other benchmark methods, our method consistently demon-strates better outlier detection accuracy without being negatively affected by the class-imbalance problem. © 2022 IEEE.

A new modulation technique for H6 transformerless inverter to minimize leakage current with reduced power loss

  • Authors: Mondal, Sudipto , Biswas, Shuvra , Islam, Md Rabiul , Shah, Rakibuzzaman
  • Date: 2022
  • Type: Text , Conference paper
  • Relation: 1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022, Kharagpur, India, 9-11 December 2022, 1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022
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  • Description: Solar energy has a significant role to play in supplying the world's growing energy needs, while transformerless inverters (TLIs) are effectively used in photovoltaic (PV) applications due to their high efficiency, small size, and lower cost. Though transformer-based inverter is frequently employed to offer galvanic isolation and voltage ratio conversions between input and output, they're getting less popular due to high iron and copper loss. Among various types of single-phase transformerless inverters, most of their switching techniques are based on the unipolar pulse width modulation (UPPWM) or bipolar pulse width modulation (BPPWM) method. Due to some unbalanced gate pulses in both UPPWM and BPPWM techniques, total harmonic distortion (THD) of output voltage (without filter) increases significantly. The leakage current also increases due to high harmonics content in the output power of TLI systems. The asymmetrical switching of the power semiconductor switches leads to a substantial increase in power loss due to unbalanced gate pulses. In this paper, a new modulation technique is proposed to reduce the output voltage THD, leakage current, as well as the total power losses compared to mostly used UPPWM and BPPWM techniques employing in PV fed TLI system. The mostly used H6 transformerless inverter topology is chosen here for performance evaluation. The simulation is carried out in MATLAB/Simulink and PLECS simulation environments to validate the proposed claim. By using the H6 transformerless inverter topology, 12.2 mA of common mode current is achieved by maintaining a steady common mode voltage via the proposed modulation technique. The output voltage (without filter) THD is found to be 37.5% with the proposed modulation technique, while BPPWM and UPPWM show 98.7% and 53.8% THD, respectively. A reduced-scaled laboratory prototype is built and tested to verify the simulated claim. © 2022 IEEE.

A new transformer-less common grounded nine-level grid-connected boost inverter

  • Authors: Kurdkandi, Naser , Marangalu, Milad , Haghighian, Saiedeh , Islam, Md Rabiul , Mehrizi-Sani, Ali , Shah, Rakibuzzaman
  • Date: 2022
  • Type: Text , Conference paper
  • Relation: 1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022, Kharagpur, India, 9-11 December 2022, 1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022
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  • Description: In this paper, a new single-source switched-capacitor-based 9-level structure that is applied to grid systems is presented. In this presented circuit, the null of the grid and input source has the common ground point. As a result, the leakage current is suppressed completely. The introduced solution can provide a nine-level output voltage waveform and boost the input voltage amplitude using a single input source. The high step-up factor of the introduced inverter is 2. In this topology, the switched capacitors are fixed to input the dc power supply and provide the voltage boosting feature. The mathematical analysis of the output filter is expressed. A peack current control method is applied to generate the gate pulses and control both active and reactive powers. A thorough comparison has been made to highlight the proposed structure's features and show the difference between the proposed structure and other structures. Finally, to confirm the correct operation of the proposed structure, its electrical circuit was simulated using MATLAB/Simulink software, and the results were extracted considering different operational conditions. © 2022 IEEE.

A review of cascade water supply systems

  • Authors: Pathberiyage, Githmi , Barton, Andrew , Kandra, Harpreet , Dassanayake, Kithsiri
  • Date: 2022
  • Type: Text , Conference paper
  • Relation: 40th Hydrology and Water Resources Symposium, HWRS 2022, Brisbane, Australia, 30 November to 2 December 2022, Hydrology and Water Resources Symposium, HWRS 2022 p. 679-694
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  • Description: Cascade Water Supply Systems (CWSS) are a type of rural water supply system used in many parts of the world such as India, China, Sri Lanka, South America, Iran, Iraq, Saudi Arabi, Korea, Peru, Egypt, Rome, Turkey, Greece, and Thailand. They are also known as Village Tank Cascade Systems (VTCS) & Cascade Systems (CS). CWSS is typically designed to collect runoff from upper forested catchment areas to provide to downstream areas and consists of a network of linearly inter-connected 'tanks' or storages, with the supply of water often supplemented from additional catchments downstream, along with groundwater resources and diversions from other sources such as rivers. As water flows from the upper regions to the downstream segments of the system, water is utilised for various purposes such as irrigation, drinking, bathing, and other household activities. The inflows and outflows result in changes in water quality in different stretches of these systems. This paper reviews the international literature surrounding CWSS, with a particular focus on water quality and associated issues. It has been found that despite the significant social, environmental, and economic importance of CWSS, and their existence for many centuries, there is limited information on water quality characteristics over space and time. Pressures such as population growth, intensification of agricultural practices, and changing climate, affect these systems as well. This review reveals that water quality is comparatively better in the upstream sections of CWSSs and progressively worsens downstream, with the data showing that the water quality in downstream systems clearly exceeds the WHO drinking and irrigation water standards. © Hydrology and Water Resources Symposium, HWRS 2022. All rights reserved.

A study on major overhaul or replacement decision of a pendulum ride (Gyro Swing - Claw) at theme park

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
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  • 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
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  • 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
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  • 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

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
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  • 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.