List of Titles

Quick View

An adaptive and flexible brain energized full body exoskeleton with IoT edge for assisting the paralyzed patients

- Jacob, Sunil, Alagirisamy, Mukil, Menon, Varun, Kumar, B. Manoj, Balasubramanian, Venki

Authors: Jacob, Sunil , Alagirisamy, Mukil , Menon, Varun , Kumar, B. Manoj , Balasubramanian, Venki
Date: 2020
Type: Text , Journal article
Relation: IEEE Access Vol. 8, no. (2020), p. 100721-100731
Full Text:
Reviewed:
Description: The paralyzed population is increasing worldwide due to stroke, spinal code injury, post-polio, and other related diseases. Different assistive technologies are used to improve the physical and mental health of the affected patients. Exoskeletons have emerged as one of the most promising technology to provide movement and rehabilitation for the paralyzed. But exoskeletons are limited by the constraints of weight, flexibility, and adaptability. To resolve these issues, we propose an adaptive and flexible Brain Energized Full Body Exoskeleton (BFBE) for assisting the paralyzed people. This paper describes the design, control, and testing of BFBE with 15 degrees of freedom (DoF) for assisting the users in their daily activities. The flexibility is incorporated into the system by a modular design approach. The brain signals captured by the Electroencephalogram (EEG) sensors are used for controlling the movements of BFBE. The processing happens at the edge, reducing delay in decision making and the system is further integrated with an IoT module that helps to send an alert message to multiple caregivers in case of an emergency. The potential energy harvesting is used in the system to solve the power issues related to the exoskeleton. The stability in the gait cycle is ensured by using adaptive sensory feedback. The system validation is done by using six natural movements on ten different paralyzed persons. The system recognizes human intensions with an accuracy of 85%. The result shows that BFBE can be an efficient method for providing assistance and rehabilitation for paralyzed patients. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**

Quick View

Reduced switch multilevel inverter topologies for renewable energy sources

- Sarebanzadeh, Maryam, Hosseinzadeh, Mohammad, Garcia, Cristian, Babaei, Ebrahim, Islam, Syed, Rodriguez, Jose

Authors: Sarebanzadeh, Maryam , Hosseinzadeh, Mohammad , Garcia, Cristian , Babaei, Ebrahim , Islam, Syed , Rodriguez, Jose
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 120580-120595
Full Text:
Reviewed:
Description: This article proposes two generalized multilevel inverter configurations that reduce the number of switching devices, isolated DC sources, and total standing voltage on power switches, making them suitable for renewable energy sources. The main topology is a multilevel inverter that handles two isolated DC sources with ten power switches to create 25 voltage levels. Based on the main proposed topology, two generalized multilevel inverters are introduced to provide flexibility in the design and to minimize the number of elements. The optimal topologies for both extensive multilevel inverters are derived from different design objectives such as minimizing the number of elements (gate drivers, DC sources), achieving a large number of levels, and minimizing the total standing voltage. The main advantages of the proposed topologies are a reduced number of elements compared to those required by other existing multilevel inverter topologies. The power loss analysis and standalone PV application of the proposed topologies are discussed. Experimental results are presented for the proposed topology to demonstrate its correct operation. © 2013 IEEE.

Trustworthiness of self-driving vehicles for intelligent transportation systems in industry applications

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Islam, Syed

Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Islam, Syed
Date: 2021
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 2 (2021), p. 961-970
Full Text: false
Reviewed:
Description: To enhance industrial production and automation, rapid and faster transportation of raw materials and finished products to and from distributed factories, warehouses and outlets are essential. To reduce cost with increased efficiency, this will increasingly see the use of connected and self-driving commercial vehicles fitted with industrial grade sensors on roads, shared with normal and self-driving passenger vehicles. For its wide adoption, the trustworthiness of self-driving vehicles in the intelligent transportation system (ITS) is pivotal. In this article, we introduce a novel model to measure the overall trustworthiness of a self-driving vehicle considering on-Board unit (OBU) components, GPS data and safety messages. In calculating the trustworthiness of individual OBU components, CertainLogic and beta distribution function (BDF) are used. Those trust values are fused using both the dempster-Shafer Theory (DST) and a logical operator of CertainLogic. Results of our simulation show that our proposed method can effectively determine the trust of self-driving vehicles. © 2005-2012 IEEE.

Quick View

Improved method to obtain the online impulse frequency response signature of a power transformer by multi scale complex CWT

- Zhao, Zhongyong, Tang, Chao, Yao, Chenguo, Zhou, Qu, Xu, Lingna, Gui, Yingang, Islam, Syed

Authors: Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Zhou, Qu , Xu, Lingna , Gui, Yingang , Islam, Syed
Date: 2018
Type: Text , Journal article
Relation: IEEE Access Vol. 6, no. (2018), p. 48934-48945
Full Text:
Reviewed:
Description: Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method.

Quick View

A new data driven long-term solar yield analysis model of photovoltaic power plants

- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed

Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
Date: 2020
Type: Text , Journal article
Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
Full Text:
Reviewed:
Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.

Quick View

Dual cost function model predictive direct speed control with duty ratio optimization for PMSM drives

- Liu, Ming, Hu, Jiefeng, Chan, Ka, Or, Siu, Ho, Siu, Xu, Wenzheng, Zhang, Xian

Authors: Liu, Ming , Hu, Jiefeng , Chan, Ka , Or, Siu , Ho, Siu , Xu, Wenzheng , Zhang, Xian
Date: 2020
Type: Text , Journal article
Relation: IEEE Access Vol. 8, no. (2020), p. 126637-126647
Full Text:
Reviewed:
Description: Traditional speed control of permanent magnet synchronous motors (PMSMs) includes a cascaded speed loop with proportional-integral (PI) regulators. The output of this outer speed loop, i.e. electromagnetic torque reference, is in turn fed to either the inner current controller or the direct torque controller. This cascaded control structure leads to relatively slow dynamic response, and more importantly, larger speed ripples. This paper presents a new dual cost function model predictive direct speed control (DCF-MPDSC) with duty ratio optimization for PMSM drives. By employing accurate system status prediction, optimized duty ratios between one zero voltage vector and one active voltage vector are firstly deduced based on the deadbeat criterion. Then, two separate cost functions are formulated sequentially to refine the combinations of voltage vectors, which provide two-degree-of-freedom control capability. Specifically, the first cost function results in better dynamic response, while the second one contributes to speed ripple reduction and steady-state offset elimination. The proposed control strategy has been validated by both Simulink simulation and hardware-in-the-loop (HIL) experiment. Compared to existing control methods, the proposed DCF-MPDSC can reach the speed reference rapidly with very small speed ripple and offset. © 2013 IEEE.
Description: This work was supported in part by the Research Grants Council of the Hong Kong Special Administrative Region (HKSAR) Government under Grant R5020-18, and in part by the Innovation and Technology Commission of the HKSAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center under Grant K-BBY1.

Quick View

Continuous patient monitoring with a patient centric agent : A block architecture

- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki

Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
Date: 2018
Type: Text , Journal article
Relation: IEEE Access Vol. 6, no. (2018), p. 32700-32726
Full Text:
Reviewed:
Description: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including continuous remote patient monitoring (RPM). However, the complexity of RPM architectures, the size of data sets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier-based End to End architecture for continuous patient monitoring that has a patient centric agent (PCA) as its center piece. The PCA manages a blockchain component to preserve privacy when data streaming from body area sensors needs to be stored securely. The PCA based architecture includes a lightweight communication protocol to enforce security of data through different segments of a continuous, real time patient monitoring architecture. The architecture includes the insertion of data into a personal blockchain to facilitate data sharing amongst healthcare professionals and integration into electronic health records while ensuring privacy is maintained. The blockchain is customized for RPM with modifications that include having the PCA select a Miner to reduce computational effort, enabling the PCA to manage multiple blockchains for the same patient, and the modification of each block with a prefix tree to minimize energy consumption and incorporate secure transaction payments. Simulation results demonstrate that security and privacy can be enhanced in RPM with the PCA based End to End architecture.

Time-delay analysis of wide area voltage control considering smart grid contingences in real-time environment

- Musleh, Ahmed, Muyeen, S., Al-Durra, Ahmed, Kamwa, Innocent, Masoum, Mohammad, Islam, Syed

Authors: Musleh, Ahmed , Muyeen, S. , Al-Durra, Ahmed , Kamwa, Innocent , Masoum, Mohammad , Islam, Syed
Date: 2018
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 14, no. 3 (2018), p. 1242-1252
Full Text: false
Reviewed:
Description: IEEE This paper addresses the time delay effects of the wide area monitoring and control systems (WAMCS) in smart power grids which may critically impact system stability. The main purpose is to conduct a detailed delay analysis of the WAMCS in case of grid contingences. This analysis is performed via an advanced WAMCS testbed where a wide area controller (WAC) for a flexible AC transmission system (FACTS) device is implemented. The real-time measurements for the WAC are collected using phasor measurements units (PMU). The testbed is resulted from an interface of four main segments known as the WAC, the actual FACTS device, the local area controller, and the power grid system along with the PMUs are simulated via real time digital simulator (RTDS). To mimic the real case scenario both hardware-in-the-loop (HIL) and software-in-the-loop (SIL) schemes are adopted in the experimental testbed, considering time delay effects. The results obtained clarify the effect of delay in WAMCS in case of smart grid contingences.

Notes on feasibility and optimality conditions of small-scale multifunction robotic cell scheduling problems with pickup restrictions

- Foumani, Mehdi, Gunawan, Indra, Smith-Miles, Kate, Ibrahim, Yousef

Authors: Foumani, Mehdi , Gunawan, Indra , Smith-Miles, Kate , Ibrahim, Yousef
Date: 2015
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 11, no. 3 (2015), p. 821-829
Full Text: false
Reviewed:
Description: Optimization of robotic workcells is a growing concern in automated manufacturing systems. This study develops a methodology to maximize the production rate of a multifunction robot (MFR) operating within a rotationally arranged robotic cell. An MFR is able to perform additional special operations while in transit between transferring parts from adjacent processing stages. Considering the free-pickup scenario, the cycle time formulas are initially developed for small-scale cells where an MFR interacts with either two or three machines. A methodology for finding the optimality regions of all possible permutations is presented. The results are then extended to the no-wait pickup scenario in which all parts must be processed from the input hopper to the output hopper, without any interruption either on or between machines. This analysis enables insightful evaluation of the productivity improvements of MFRs in real-life robotized workcells. ©2014 IEEE.

Quick View

Time is on my side : How do engineering academics spend their days - an international study

- Aarrevaara, Timo, Dobson, Ian

Authors: Aarrevaara, Timo , Dobson, Ian
Date: 2012
Type: Text , Journal article
Relation: World Transactions on Engineering and Technology Education Vol. 10, no. 3 (2012), p. 184-191
Full Text:
Reviewed:
Description: This article uses empirical data from the international Changing Academic Profession (CAP) survey to establish similarities and differences in work patterns among the world's academic engineers. Overall working hours and the distribution of work between teaching, research and other activities are examined. Summary results indicate that in periods when classes are in session, engineering academics from South Korea and Hong Kong reported a longer working week than equivalent staff from other countries. Engineering academics from Mexico and South Africa spent the highest proportion of their time on teaching, whereas those from Argentina, China and Italy spent the highest proportion on research. The most likely reason for international differences in the length of the working week is that national systems (such as higher education) have been constructed from the individual histories and cultures in each country. © 2012 WIETE.
Description: 2003010832

A distributed and anonymous data collection framework based on multilevel edge computing architecture

- Usman, Muhammad, Jan, Mian, Jolfaei, Alireza, Xu, Min, He, Xiangjian, Chen, Jinjun

Authors: Usman, Muhammad , Jan, Mian , Jolfaei, Alireza , Xu, Min , He, Xiangjian , Chen, Jinjun
Date: 2020
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 9 (2020), p. 6114-6123
Full Text: false
Reviewed:
Description: Industrial Internet of Things applications demand trustworthiness in terms of quality of service (QoS), security, and privacy, to support the smooth transmission of data. To address these challenges, in this article, we propose a distributed and anonymous data collection (DaaC) framework based on a multilevel edge computing architecture. This framework distributes captured data among multiple level-one edge devices (LOEDs) to improve the QoS and minimize packet drop and end-to-end delay. Mobile sinks are used to collect data from LOEDs and upload to cloud servers. Before data collection, the mobile sinks are registered with a level-two edge-device to protect the underlying network. The privacy of mobile sinks is preserved through group-based signed data collection requests. Experimental results show that our proposed framework improves QoS through distributed data transmission. It also helps in protecting the underlying network through a registration scheme and preserves the privacy of mobile sinks through group-based data collection requests. © 2005-2012 IEEE.

Quick View

Robust image classification using a low-pass activation function and DCT augmentation

- Hossain, Md Tahmid, Teng, Shyh, Sohel, Ferdous, Lu, Guojun

Authors: Hossain, Md Tahmid , Teng, Shyh , Sohel, Ferdous , Lu, Guojun
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 86460-86474
Full Text:
Reviewed:
Description: Convolutional Neural Network's (CNN's) performance disparity on clean and corrupted datasets has recently come under scrutiny. In this work, we analyse common corruptions in the frequency domain, i.e., High Frequency corruptions (HFc, e.g., noise) and Low Frequency corruptions (LFc, e.g., blur). Although a simple solution to HFc is low-pass filtering, ReLU - a widely used Activation Function (AF), does not have any filtering mechanism. In this work, we instill low-pass filtering into the AF (LP-ReLU) to improve robustness against HFc. To deal with LFc, we complement LP-ReLU with Discrete Cosine Transform based augmentation. LP-ReLU, coupled with DCT augmentation, enables a deep network to tackle the entire spectrum of corruption. We use CIFAR-10-C and Tiny ImageNet-C for evaluation and demonstrate improvements of 5% and 7.3% in accuracy respectively, compared to the State-Of-The-Art (SOTA). We further evaluate our method's stability on a variety of perturbations in CIFAR-10-P and Tiny ImageNet-P, achieving new SOTA in these experiments as well. To further strengthen our understanding regarding CNN's lack of robustness, a decision space visualisation process is proposed and presented in this work. © 2013 IEEE.

Quick View

Impact of load ramping on power transformer dissolved gas analysis

- Cui, Huize, Yang, Liuging, Li, Shengtao, Qu, Guanghao, Wang, Hao, Abu-Siada, Ahmed, Islam, Syed

Authors: Cui, Huize , Yang, Liuging , Li, Shengtao , Qu, Guanghao , Wang, Hao , Abu-Siada, Ahmed , Islam, Syed
Date: 2019
Type: Text , Journal article
Relation: IEEE Access Vol. 7, no. (2019), p. 170343-170351
Full Text:
Reviewed:
Description: Dissolved gas in oil analysis (DGA) is one of the most reliable condition monitoring techniques, which is currently used by the industry to detect incipient faults within the power transformers. While the technique is well matured since the development of various offline and online measurement techniques along with various interpretation methods, no much attention was given so far to the oil sampling time and its correlation with the transformer loading. A power transformer loading is subject to continuous daily and seasonal variations, which is expected to increase with the increased penetration level of renewable energy sources of intermittent characteristics, such as photovoltaic (PV) and wind energy into the current electricity grids. Generating unit transformers also undergoes similar loading variations to follow the demand, particularly in the new electricity market. As such, the insulation system within the power transformers is expected to exhibit operating temperature variations due to the continuous ramping up and down of the generation and load. If the oil is sampled for the DGA measurement during such ramping cycles, results will not be accurate, and a fault may be reported due to a gas evolution resulting from such temporarily loading variation. This paper is aimed at correlating the generation and load ramping with the DGA measurements through extensive experimental analyses. The results reveal a strong correlation between the sampling time and the generation/load ramping. The experimental results show the effect of load variations on the gas generation and demonstrate the vulnerabilities of misinterpretation of transformer faults resulting from temporary gas evolution. To achieve accurate DGA, transformer loading profile during oil sampling for the DGA measurement should be available. Based on the initial investigation in this paper, the more accurate DGA results can be achieved after a ramping down cycle of the load. This sampling time could be defined as an optimum oil sampling time for transformer DGA.

Development of flexible haptic forceps based on the electrohydraulic transmission system

- Ogawa, Kenji, Ibrahim, Yousef, Ohnishi, Kouhei

Authors: Ogawa, Kenji , Ibrahim, Yousef , Ohnishi, Kouhei
Date: 2018
Type: Text , Journal article
Relation: IEEE Transactions on Industrial Informatics Vol. 14, no. 12 (2018), p. 5256-5267
Full Text: false
Reviewed:
Description: Minimally invasive surgery (MIS) has many benefits, e.g., unnecessary trauma and blood loss can be minimized by opening tiny surgery scars, recovery process of patients can be lessened, and the possibilities of complications can be decreased. The natural orifice transluminal surgery (NOTES) is one of the MIS surgical methodologies. NOTES surgery is performed using an endoscope. This methodology does not rely on making holes to patients' body to insert the medical instruments. Although some medical robots for NOTES have been proposed, current robots mainly suffer from the absence/limitation of haptic feedback to the surgeon's hands. In order to overcome this problem, this paper proposes electro hydraulic transmission system (EHTS) based forceps. The EHTS is a remote actuation system using fluid energy. By using the EHTS, the classical position and force transmission losses will not be influenced by the tube's shape. The validity of the proposal and its advantages have been experimentally verified and presented in this paper.

Quick View

Green underwater wireless communications using hybrid optical-acoustic technologies

- Islam, Kazi, Ahmad, Iftekhar, Habibi, Daryoush, Zahed, M., Kamruzzaman, Joarder

Authors: Islam, Kazi , Ahmad, Iftekhar , Habibi, Daryoush , Zahed, M. , Kamruzzaman, Joarder
Date: 2021
Type: Text , Journal article
Relation: IEEE Access Vol. 9, no. (2021), p. 85109-85123
Full Text:
Reviewed:
Description: Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology - underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe absorption of light in the medium, the communication range is short in underwater optics. Conversely, acoustics suffers from low data rate and high power consumption, but provides longer communication ranges. Since most underwater equipment relies on battery power, energy-efficient communication is critical for reliable underwater communications. In this work, we derive analytical models for both underwater acoustics and optics, and calculate the required transmit power for reliable communications in various underwater communication environments. We then formulate an optimization problem that minimizes the network power consumption for carrying data from underwater nodes to surface sinks under varying traffic loads and weather conditions. The proposed optimization model can be solved offline periodically, hence the additional computational complexity to find the optimum solution for larger networks is not a limiting factor for practical applications. Our results indicate that the proposed technique yields up to 35% power savings compared to existing opto-acoustic solutions. © 2013 IEEE.

Quick View

A secured framework for SDN-based edge computing in IoT-enabled healthcare system

- Li, Junxia, Cai, Jinjin, Khan, Fazlullah, Rehman, Ateeq, Balasubramanian, Venki

Authors: Li, Junxia , Cai, Jinjin , Khan, Fazlullah , Rehman, Ateeq , Balasubramanian, Venki
Date: 2020
Type: Text , Journal article
Relation: IEEE Access Vol. 8, no. (2020), p. 135479-135490
Full Text:
Reviewed:
Description: The Internet of Things (IoT) consists of resource-constrained smart devices capable to sense and process data. It connects a huge number of smart sensing devices, i.e., things, and heterogeneous networks. The IoT is incorporated into different applications, such as smart health, smart home, smart grid, etc. The concept of smart healthcare has emerged in different countries, where pilot projects of healthcare facilities are analyzed. In IoT-enabled healthcare systems, the security of IoT devices and associated data is very important, whereas Edge computing is a promising architecture that solves their computational and processing problems. Edge computing is economical and has the potential to provide low latency data services by improving the communication and computation speed of IoT devices in a healthcare system. In Edge-based IoT-enabled healthcare systems, load balancing, network optimization, and efficient resource utilization are accurately performed using artificial intelligence (AI), i.e., intelligent software-defined network (SDN) controller. SDN-based Edge computing is helpful in the efficient utilization of limited resources of IoT devices. However, these low powered devices and associated data (private sensitive data of patients) are prone to various security threats. Therefore, in this paper, we design a secure framework for SDN-based Edge computing in IoT-enabled healthcare system. In the proposed framework, the IoT devices are authenticated by the Edge servers using a lightweight authentication scheme. After authentication, these devices collect data from the patients and send them to the Edge servers for storage, processing, and analyses. The Edge servers are connected with an SDN controller, which performs load balancing, network optimization, and efficient resource utilization in the healthcare system. The proposed framework is evaluated using computer-based simulations. The results demonstrate that the proposed framework provides better solutions for IoT-enabled healthcare systems. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramaniam” is provided in this record**

Quick View

Mobility based network lifetime in wireless sensor networks: A review

- Nguyen, Linh, Nguyen, Hoc

Authors: Nguyen, Linh , Nguyen, Hoc
Date: 2020
Type: Text , Journal article
Relation: Computer Networks Vol. 174, no. (2020), p.
Full Text:
Reviewed:
Description: Increasingly emerging technologies in micro-electromechanical systems and wireless communications allows mobile wireless sensor networks (MWSNs) to be a more and more powerful mean in many applications such as habitat and environmental monitoring, traffic observing, battlefield surveillance, smart homes and smart cities. Nevertheless, due to sensor battery constraints, energy-efficiently operating an MWSN is paramount importance in those applications; and a plethora of approaches have been proposed to elongate the network longevity at most possible. Therefore, this paper provides a comprehensive review on the developed methods that exploit mobility of sensor nodes and/or sink(s) to effectively maximize the lifetime of an MWSN. The survey systematically classifies the algorithms into categories where the MWSN is equipped with mobile sensor nodes, one mobile sink or multiple mobile sinks. How to drive the mobile sink(s) for energy efficiency in the network is also fully reviewed and reported. © 2020

Quick View

A machine vision based automatic optical inspection system for measuring drilling quality of printed circuit boards

- Wang, Wei, Chen, Shang-Liang, Chen, Liang-Bi, Chang, Wan-Jung

Authors: Wang, Wei , Chen, Shang-Liang , Chen, Liang-Bi , Chang, Wan-Jung
Date: 2017
Type: Text , Journal article
Relation: IEEE Access Vol. 5, no. (2017), p. 10817-10833
Full Text:
Reviewed:
Description: In this paper, we develop and put into practice an automatic optical inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device, and charge-coupled device cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5 mu m could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole, and the incorrect location of the holes. However, previous work only focuses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes, and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users to analyze the causes of errors and immediately correct the problems. In addition, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1-mm image resolution, which is better than others used in industry. We set a detecting standard based on 2-mm diameter of circles to diagnose the quality of the holes within 10 s.

Wifi-based localisation datasets for No-GPS open areas using smart bins

- Nassar, Mohamed, Hasan, Mahmud, Khan, Md, Sultana, Mirza, Hasan, Md, Luxford, Len, Cole, Peter, Oatley, Giles, Koutsakis, Polychronis

Authors: Nassar, Mohamed , Hasan, Mahmud , Khan, Md , Sultana, Mirza , Hasan, Md , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis
Date: 2020
Type: Text , Journal article , Data article
Relation: Computer Networks Vol. 180, no. (2020), p. 1-5
Full Text: false
Reviewed:
Description: In recent years, Wifi-based localisation systems have gained significant interest because of the lack of Global Positioning System (GPS) signal in indoor and certain open areas. Over the past decade, many datasets have been introduced to enable researchers to compare different localisation techniques. Existing datasets, however, have failed to cover open areas such as parks in cases where GPS is still unavailable, and there is a lack of Wifi access points. Also, the existing datasets only focus on getting Wifi fingerprint collected and labelled by users. To the best of our knowledge, no dataset provides Received Signal Strengths (RSS) collected by Wireless Access Points (APs). In this work, we offer two datasets publicly. The first is the Fingerprint dataset in which four users generated 16,032 accurate and consistently labelled WiFi fingerprints for all available Reference Points (RPs) in a central and busy area of Murdoch University, known as Bush Court. The second is the APs dataset that includes 2,450,865 auto-generated records received from 1000 users' devices, including the four users, associated with Wifi signal strengths. To overcome the Wifi coverage problem for the Bush Court, we attached our previously designed Wireless Sensor Nodes (WSNs) to existing garbage bins, enabling them to provide real-time environmental sensing and act as soft APs that sense MAC addresses and Wifi signals from surrounding devices.

Quick View

Rectified softmax loss with all-sided cost sensitivity for age estimation

- Li, Daxiang, Ma, Xuan, Ren, Yaqiong, Teng, Shyh

Authors: Li, Daxiang , Ma, Xuan , Ren, Yaqiong , Teng, Shyh
Date: 2020
Type: Text , Journal article
Relation: IEEE Access Vol. 8, no. (2020), p. 32551-32563
Full Text:
Reviewed:
Description: In Convolutional Neural Network (ConvNet) based age estimation algorithms, softmax loss is usually chosen as the loss function directly, and the problems of Cost Sensitivity (CS), such as class imbalance and misclassification cost difference between different classes, are not considered. Focus on these problems, this paper constructs a rectified softmax loss function with all-sided CS, and proposes a novel cost-sensitive ConvNet based age estimation algorithm. Firstly, a loss function is established for each age category to solve the imbalance of the number of training samples. Then, a cost matrix is defined to reflect the cost difference caused by misclassification between different classes, thus constructing a new cost-sensitive error function. Finally, the above methods are merged to construct a rectified softmax loss function for ConvNet model, and a corresponding Back Propagation (BP) training scheme is designed to enable ConvNet network to learn robust face representation for age estimation during the training phase. Simultaneously, the rectified softmax loss is theoretically proved that it satisfies the general conditions of the loss function used for classification. The effectiveness of the proposed method is verified by experiments on face image datasets of different races. © 2013 IEEE.

Showing items 1 - 20 of 51