JournalTOCs

International Journal of Wireless and Mobile Computing
Journal Prestige (SJR): 0.233

Citation Impact (citeScore): 1
Number of Followers: 8

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1741-1084 - ISSN (Online) 1741-1092
Published by Inderscience Publishers

[439 journals]

Penevector marine multifunctional geological sampling/testing
integrated equipment
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  Authors: Wei Zhang, Qi Chen, Linqi Xia, Tao Li
  Pages: 211 - 219
  Abstract: An integrated seabed geological sampling/testing system is developed for marine geological survey. The system has the functions of static pressure penetration sampling, vibration penetration sampling and in-situ test. The static pressure penetration sampling function adopts the fuzzy control algorithm to control the speed and torque of the friction wheel to ensure the synchronism of the two friction wheels. The double friction wheel holds the sampling pipe to penetrate into the stratum for sampling, which has high fidelity. In the sand layer, the sand can be liquefied and sampled by the function of vibration penetration sampling. In situ testing, multi-functional static cone penetration is used to obtain the mechanical properties, resistivity and geothermal gradient of the seabed directly.
  Keywords: geological survey; seabed type; static pressure sampling; vibration sampling; static cone penetration
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 211 - 219
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127580
  Issue No: Vol. 23, No. 3/4 (2022)
Narrowband internet of things: performance analysis of coverage
enhancement in uplink transmission
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  Authors: Rasveen, Shilpy Agrawal, Khyati Chopra
  Pages: 220 - 230
  Abstract: Narrowband Internet of Things (NB-IoT) is a wireless standard and a novel technology for the IoT devices and applications. The extended coverage, low cost and long battery life make NB-IoT an excellent candidate for IoT applications. One of the primary goals of NB-IoT is to enhance coverage beyond the existing cellular technologies like General Packet Radio Service and Long-Term Evolution (GPRS and LTE). To accomplish this, the NB-IoT system utilises a repetition technique in which the same signal is repeated several times with different sub-carrier spacing in the uplink. We propose the repetition model with the optimisation algorithm, i.e., Moth Flame Optimisation (MFO). The optimisation reduces the Block Error Rate (BLER) even in the worst channel condition, which increases the performance evaluation in a single-tone and multi-tone transmission with sufficient transmission time, eventually increasing the radio coverage. The conducted evaluation showed that signal could be recovered even in low S/N, thereby providing better coverage.
  Keywords: repetition; RU; resource unit; single-tone; multi-tone; coverage enhancement
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 220 - 230
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127583
  Issue No: Vol. 23, No. 3/4 (2022)
Targeted sentiment classification with multi-attention network
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  Authors: Xiao Tian, Peiyu Liu, Zhenfang Zhu
  Pages: 231 - 238
  Abstract: Targeted sentiment classification aims at recognising the sentiment polarity of specific targets. However, existing methods mainly depend on a crude attention mechanism, while neglecting the mutual effects between target and context. In order to solve this problem, this paper introduces a Multi-Attention Network (MAN) for aspect level sentiment classification. We jointly modelled intra-level and inter-level attentional components to capture the interaction between target and context. The former attention mechanism pays attention to the context relation, whereas the latter attention mechanism considers important parts in a sentence. The experimental conducted on laptop, restaurant and Twitter data sets indicate that our model surpasses the baseline model.
  Keywords: attention mechanism; self-attention; targeted sentiment analysis; emotion analysis; neural network
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 231 - 238
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127585
  Issue No: Vol. 23, No. 3/4 (2022)
Remaining useful life prediction for lithium-ion battery using a
data-driven method
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  Authors: Zhiyang Jin, Chao Fang, Jingjin Wu, Jinsong Li, Wenqian Zeng, Xiaokang Zhao
  Pages: 239 - 249
  Abstract: Accurate prediction of the remaining useful life (RUL) of Li-ion batteries is one of the key technologies in the Battery Management System (BMS). To boost the prediction accuracy of Li-ion battery RUL, a data-driven approach is developed, through the combination of Long and Short-Term Memory (LSTM) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). First and foremost, the battery capacity extracted from the National Aeronautics and Space Administration (NASA) battery data set is used as original data and the CEEMDAN is utilised to deal with original data into components of dissimilar frequencies. Then, the LSTM model is used to predict components of different frequencies. Finally, the CEEMDAN-LSTM prediction result is efficaciously integrated to acquire the final prediction of the Li-ion battery RUL. The results show that the proposed method is superior for Li-ion battery RUL prediction.
  Keywords: Li-ion battery; remaining useful life long and short-term memory; CEEMDAN; complete ensemble empirical mode decomposition with adaptive noise
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 239 - 249
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127586
  Issue No: Vol. 23, No. 3/4 (2022)
Research on remote sensing image classification method using two-stream
convolutional neural network
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  Authors: Kai Peng, Juan Hu, Siyu Liu, Fang Qu, Houqun Yang, Jing Chen
  Pages: 250 - 255
  Abstract: Owing to the lack of remote sensing image data set and no regional pertinence in terms of characteristics for classification, we have published the remote sensing image of some areas in Haikou City, Hainan Province, and made a HN-7 dataset, which has the regional characteristics specific of Hainan Province. The HN-7 dataset consists of seven classes, of which the construction site and dirt road categories appear in the public remote sensing dataset for the first time. Owing to the limited quantity of the HN-7 dataset, we decided to train a small convolutional neural network from scratch for the classification task, by using a three-layer two-stream network for improving the accuracy of the neural network model. Our model achieved 98.57% accuracy on the test set. We compared the accuracy of four common networks trained on HN-7, and the results showed that our model achieves the best performance.
  Keywords: classification method; remote sensing image; two-stream convolutional; neural network
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 250 - 255
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127587
  Issue No: Vol. 23, No. 3/4 (2022)
Study of the monitoring system for double row steel sheet pile cofferdam
engineering
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  Authors: Jianjun Wang, Guiqin Liu
  Pages: 256 - 260
  Abstract: The construction monitoring and control standard of the steel sheet pile cofferdam is still the standard of the foundation pit of the civil structure. In this paper, by referring to the literature related to double-wall steel sheet pile cofferdam, the detection content, structure calculation method and error analysis of double-wall steel sheet pile cofferdam project are summarised systematically. To ensure the safety of the cofferdam structure, the automatic monitoring system of steel cofferdam is established to realise the organic combination of real-time monitoring and control of steel cofferdam, so as to take timely measures to ensure the smooth progress of the project and analyse the error which will be used to improve the model and algorithm. Finally, the calculation error between the model and algorithm will shrink and be smaller, making the results more reliable.
  Keywords: cofferdam; real-time monitoring; safety
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 256 - 260
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127589
  Issue No: Vol. 23, No. 3/4 (2022)
Energy-efficient sink relocation using whale optimisation technique in
virtual grid-based wireless sensor networks
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  Authors: A. Keerthika, V. Berlin Hency
  Pages: 261 - 271
  Abstract: Wireless Sensor Network (WSN) is an efficient network for monitoring and recording the physical environment and transfers the monitored data into the central location using widely distributed sensor nodes. One of the main problems in WSN is the issue of developing an energy-efficient routing protocol that achieves less energy consumption and enhances the lifetime of the network. During the past decades, researchers have used the mobile sink to reduce the energy problem and hotspot problems. In this work, Virtual Grid Based Energy Efficient Sink Relocation (VGESR) is proposed to solve these issues. The grid clustering is achieved by employing K-means clustering. After clustering, the Leader Node (LN) selection is done by calculating the Acceptability Factor (AF). Acceptability factor is calculated based on the nodes residual energy, Available bandwidth and Received Signal Strength (RSS). Whale Optimisation Algorithm (WOA) technique is employed for the optimal sink relocation based on the fitness value of the nodes. The results obtained from the simulation prove that the proposed VGESR performs well in terms of life span and energy utilisation. The proposed VGESR simulation is performed using the OMNet++ tool.
  Keywords: acceptability factor; clustering; network lifetime; sink relocation; whale optimisation; wireless sensor networks
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 261 - 271
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127590
  Issue No: Vol. 23, No. 3/4 (2022)
Direction-of-arrival estimation for partially polarised signals with
switch-based multi-polarised uniform linear array
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  Authors: Yujian Pan, Jingke Zhang, Zongfeng Qi
  Pages: 272 - 280
  Abstract: In this paper, a new switch-based multi-polarised receiver architecture and two compatible Direction-of-Arrival (DOA) estimation algorithms are proposed for the partially polarised signals. In the receiver, each polarised element in an antenna is connected to a common Radio Frequency (RF) chain via a switch, which reduces the number of RF chains. For DOA estimation, an ESPRIT-based algorithm and a joint annihilation-based algorithm are proposed. The ESPRIT-based algorithm is based on summing the covariance matrices of different polarised outputs, and the joint annihilation-based algorithm is based on annihilating different polarised outputs by a common filter. Compared with other algorithms, the ESPRIT-based algorithm, which only takes about 91 us to perform one estimation, is more efficient and the joint annihilation-based algorithm, which can approach the Cramer-Rao Lower Bound (CRLB), is more accurate. It is also concluded that the tri-polarised Uniform Linear Array (ULA) can offer more accurate estimation than the dual-polarised ULA.
  Keywords: direction-of-arrival estimation; ESPRIT; joint annihilation; multi-polarised array; partially polarised signal
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 272 - 280
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127591
  Issue No: Vol. 23, No. 3/4 (2022)
Computation offloading using K-nearest neighbour time critical
optimisation algorithm in fog computing
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  Authors: Ashwini Kumar Jha, Minal P. Patel, Tanmay D. Pawar
  Pages: 281 - 292
  Abstract: The wide range of IoT devices and wireless devices used in healthcare, hospitals and enterprises generates a large volume of digital data that must be processed, analysed and stored. Owing to the small processing capacity of these devices, the data generated cannot be processed on-board. Therefore, we suggest offloading this data to an efficient server. Time-critical applications cannot rely on the availability of cloud servers since they are in a remote location. The paper examines algorithms such as Deep Reinforcement Learning for Online Computation Offloading (DROO), coordinate descent, adaptive boosting, and then implements the <em>K</em>-nearest neighbour time critical optimisation algorithm as a fog offloading network topology. The offloading decision is based on the cost function, which includes latency, memory consumption and model accuracy. The topology implementing <em>K</em>-NN can be trained quickly and offers almost 99% accuracy when it comes to data offloading. Based on the comparative analysis, it excels over other machine learning approaches.
  Keywords: fog computing; edge computing; computation offloading; cloud computing; K-nearest neighbour
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 281 - 292
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127593
  Issue No: Vol. 23, No. 3/4 (2022)
Pattern recognition of surface electromyography based on multi-scale
convolutional neural network with attention mechanism
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  Authors: Beibei Wang, Hui Zheng, Jing Jie, Miao Zhang, Yintao Ke, Yang Liu
  Pages: 293 - 301
  Abstract: Natural control methods based on Surface Electromyography (sEMG) pattern recognition have been widely applied in the field of hand prostheses. However, the control robustness and accuracy are difficult to meet many real-life applications. This paper proposes a Multi-Scale Convolutional Neural Network (MSCNN) model based on the attention mechanism, which can automatically learn gesture features through convolution. The model generates features through convolution kernels of different sizes to achieve the fusion of features of different degrees firstly. After that, the attention mechanism is used to calculate the weights of different scales, and then the fused comprehensive features are obtained. The proposed model has been verified on the SIA_delsys_16_movement and NinaPro data sets. The experimental results showed that the proposed model has better classification accuracy, and the attention mechanism can validly improve the classification performance of the convolutional neural network.
  Keywords: surface electromyography; convolutional neural network; gesture recognition; machine learning; attention mechanism
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 293 - 301
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127594
  Issue No: Vol. 23, No. 3/4 (2022)
Hardware implementation of approximate multipliers for signal processing
applications
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  Authors: E. Konguvel, I. Hariharan, R. Sujatha, M. Kannan
  Pages: 302 - 309
  Abstract: Multiplication is a complex and substantial arithmetic task involved in signal processing applications. The hardware complexity of the multiplier is always high when compared with any other arithmetic operation. Approximate multiplication is a common operation used in many signal processing applications for improved performance and low-power computation. The proposed approximate multiplier design is based on the approximate 4-2 compressor and self-error recovery technique. A small modification of the truth table entries in the approximate 4-2 compressor shows performance improvement at a small cost of accuracy. The designed multiplier promises to have improved performance when compared with the earlier approximate designs. The computational errors arising because of this multiplication approximation can be considered as trade-off for the significant gains in power and area.
  Keywords: approximate computing; adders; multipliers; hardware; error analysis; VLSI design
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 302 - 309
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127595
  Issue No: Vol. 23, No. 3/4 (2022)
DstNet: deep spatial-temporal network for real-time action recognition and
localisation in untrimmed video
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  Authors: Zhi Liu, Junting Li, Xian Wang
  Pages: 310 - 317
  Abstract: Action recognition is a hot research direction of computer vision. How to deal with human action in untrimmed video in real time is a very significant challenge. It can be widely used in fields such as real-time monitoring. In this paper, we propose an end-to-end Deep Spatial-Temporal Network (DstNet) for action recognition and localisation. First of all, the untrimmed video is clipped into segments with fixed length. Then, the Convolutional 3 Dimension (C3D) network is used to extract highly dimensional features for each segment. Finally, the extracted feature sequences of several continual segments are input into Long Short-Term Memory (LSTM) network to find the intrinsic relationship among clipped segments to take action recognition and localisation simultaneously in the untrimmed video. While maintaining good accuracy, our network has the function of real-time video processing and has achieved good results in the standard evaluation performance of THUMOS14.
  Keywords: action recognition; action localisation; LSTM; C3D; untrimmed video
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 310 - 317
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127597
  Issue No: Vol. 23, No. 3/4 (2022)
Research on a safety evaluation method based on ANP-fuzzy decision for
coal mine ventilation system
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  Authors: Hongjuan Cai, Hengqiang Gao
  Pages: 318 - 328
  Abstract: Aiming at the ambiguity and randomness of the indicators in the comprehensive evaluation of the safety of the mine ventilation system, a two-level fuzzy comprehensive evaluation model of safety is established. In this paper, to calculate the indicators which have enhanced the objectivity and scientific of the safety evaluation of the mine ventilation system, network analytic method (ANP) is used. By utilising this ANP method, the obtained results indicated that the safety level of the mine was only 'general safety'. Through single-factor evaluation and analysis of the weights of various indicators, the system can be based on the employees' physical fatigue (A3), employees' attendance (A7), volume fraction of gas and toxic gas (C3), dust mass concentration (C5), air volume supply-demand ratio (C7), ventilation system hole volume ratio (C8) and regular inspection (B1) to improve the safety of the mine ventilation system.
  Keywords: ANP; fuzzy comprehensive decision; coal mine ventilation system; safety evaluation
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 318 - 328
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127599
  Issue No: Vol. 23, No. 3/4 (2022)
A novel primary user detection using OFDM internal structures on Raspberry
Pi
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  Authors: Mobin Alizadeh, Javad Kazemitabar
  Pages: 329 - 337
  Abstract: Using autocorrelation-based techniques for detecting (Orthogonal Frequency Division Multiplexing) OFDM signals in cognitive radio systems is well studied. Correlating the cyclic prefix with its replica provides a means to distinguish an OFDM signal from noise as shown in previous research. A subtle yet crucial shortcoming of this autocorrelation-based method is that it may mistake a sinusoidal for an OFDM signal. All for that to happen is for the sinusoid to have the proper period; the algorithm would then find a repeating pattern and declare OFDM signal detection. In this paper, we modify the conventional autocorrelation-based method to avoid generating false-alarms in the presence of sinusoidal signals. We test our algorithm on a custom-built Raspberry Pi.
  Keywords: cognitive radio; primary user detection; OFDM; spectrum sensing; Raspberry Pi
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 329 - 337
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127602
  Issue No: Vol. 23, No. 3/4 (2022)
A statistical model checking approach to analyse the random access
protocol
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  Authors: Ahmed Roumane, Bouabdellah Kechar
  Pages: 338 - 349
  Abstract: Mobile cellular networks are becoming the most important technology in the telecom industry, and this made them a preferred subject for research and development of new hardware and software systems. In order to check the validity of these systems, one can use either a simulation or formal methods. Recently, new emerging methods have been proposed as alternative solutions, such as Statistical Model Checking (SMC). In this paper, we present a comprehensive framework based on SMC that could be used to analyse the cellular network protocol Random-Access Procedure (RAP), by using UPPAAL. We model the system using a simplified network of timed automata, we check the validity of our model by running some concrete simulations and after that we perform a formal verification of some properties of the protocol. Finally, the statistical approach, SMC, is used to study the performance of the system.
  Keywords: mobile network; cellular network; formal verification; model checking; statistical model checking; random access procedure
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 338 - 349
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127603
  Issue No: Vol. 23, No. 3/4 (2022)
A survey on trends on mobile app development and applications
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  Authors: Mazen Lahham, Hussein Hazimeh, Mohammad Malli
  Pages: 350 - 360
  Abstract: The widespread use of smart-phones and the increasing demand for mobile users to have similar desktop functionality and performance have resulted in better and faster mobile innovation technology. We present, in this survey, an overview of the body of the literature that deals with the latest emerging mobile technologies and examines its impact on the current mobile app ecosystem. To the best of our knowledge, this is the first work that combines the most significant mobile advancements while showing the futuristic potentials and challenges faced by the mobile app industry. Therefore, the paper defines the criteria for selecting these latest mobile developments since it cannot incorporate all of them due to the magnitude of the subject.
  Keywords: mobile app development; smartphone applications; mobile technologies
  Citation: International Journal of Wireless and Mobile Computing, Vol. 23, No. 3/4 (2022) pp. 350 - 360
  PubDate: 2022-12-12T23:20:50-05:00
  DOI: 10.1504/IJWMC.2022.127604
  Issue No: Vol. 23, No. 3/4 (2022)