International Journal of Information and Communication Technology (19 papers in press)

Regular Issues

• Open Access

  Real time monitoring system for power distribution network faults based on deep learning technology ( Free Full-text Access )

  by Qiaoni Zhao, Li Yang 
  Abstract: This article aims to propose a reliable real-time monitoring system for distribution network defects, improve intelligent monitoring technology by combining deep learning technology, and analyse the drawbacks of traditional real-time monitoring of distribution network defects in real-time, by improving the algorithm, the basic structure of the algorithm model is constructed. Based on experimental analysis, the data processing of this system is based on deep learning technology. Multiple monitoring modules are used in the system to improve the accuracy and real-time performance of data collection, providing more reliable data support for fault detection. From the simulation experiment, it can be seen that the real-time monitoring system for distribution network defects based on deep learning proposed in this article can play an important role in fault diagnosis and troubleshooting in the distribution network.
  Keywords: deep learning; distribution network; defects; real-time monitoring.
  
  

• Open Access

  Design and research of red-blue confrontation training system based on virtual reality ( Free Full-text Access )

  by Song Yong, Haili Yin 
  Abstract: In order to show the scene of military confrontation more truly and enhance the immersion of soldiers in confrontation, the behaviour generation of virtual soldiers is added. In order to solve the problem of red-blue confrontation system, this paper constructs a red-blue confrontation training system combined with virtual reality technology, simulates virtual soldiers with motion editing and motion redirection technology, uses motion redirection algorithm based on forward kinematics for kinematics simulation calculation, uses frame-by-frame solution method to process motion number, and uses surface model as collision detection model. Through simulation example images, it can be seen that the virtual reality technology proposed in this paper can realise interactive simulation of red-blue confrontation. At the same time, from the victory rate test of both sides of red-blue confrontation, it can be seen that the theoretical victory rate and the test victory rate are very close, so the red-blue confrontation training system based on virtual reality has obvious effect and can effectively improve the simulation effect of subsequent red-blue confrontation.
  Keywords: virtual reality; red-blue confrontation; training; military.
  
  

• Open Access

  Enhancing oral English self-study: a speech knowledge recognition algorithm approach ( Free Full-text Access )

  by Yuanyuan Zhang 
  Abstract: In today’s globally connected world, English proficiency is vital for effective communication. This paper introduces a novel approach utilising a speech knowledge recognition algorithm to evaluate oral English self-study. Through a comprehensive analysis comparing self-study with standard oral English, aspects such as acoustics, rhythm, and perception are assessed. By integrating both subjective and objective evaluations, the proposed algorithm provides a robust framework for assessing oral English proficiency. The ultimate goal is to improve the efficiency and efficacy of English self-study. Simulation results affirm the effectiveness of the speech knowledge recognition algorithm in evaluating oral English proficiency.
  Keywords: speech knowledge recognition algorithm; oral English score; error detection; prosodic correction.
  
  
• Cost-effective cryptographic architecture in quantum dot cellular automata for secured nano-communication  
  by S. Senthilnathan, S. Kumaravel 
  Abstract: Quantum dot cellular automata (QCA) provide rapid computational efficiency, high density and low power consumption, which is an alternative for CMOS technology. In digital world, cryptography is an important feature to protect digital data. To ensure the data protection in nano-communication, a QCA-based cryptographic architecture is proposed in this article. In the proposed design, the encryption and decryption is done with the help of random keys which is produced by the pseudo random number generator (PRNG). In this paper, architectural component of cryptographic architecture includes XOR block, 1 to 4 de-multiplexer and PRNG, which are realised using QCA. Finally, an integration of the individual components through clock zone-based crossover, lead to the generation of a novel cryptographic architecture. This design achieves low cost compared to the existing literature, as it uses minimum number of majority gate and inverters with clock zone-based crossover.
  Keywords: quantum dot cellular automata; QCA; clock zone-based crossover; CZBC; cryptographic architecture; pseudo random number generator; PRNG; demultiplexer; nano-router.
  DOI: 10.1504/IJICT.2022.10051962
   
  
• Diabetic retinopathy detection using curvelet and retina analyser  
  by Manas Saha, Biswa Nath Chatterji 
  Abstract: The diabetic retinopathy (DR) is a clinical disorder of retina caused due to diabetes mellitus. This work presents an automated detection of DR images using curvelet and retina analyser. Like Fourier transform, curvelet is a mathematical transform. It is deployed here to trace the directional field of the curve singularities of the retina images. This helps to segment the retinal vasculature of the fundus images. The change in retinal morphology like length, diameter, tortuosity due to the ophthalmoscopic changes are computed by retina analyser. Feedforward neural network (FNN) is implemented to detect DR images with sensitivity: 79%, specificity: 94% and accuracy: 88% which is better than the contemporary works. The proposed system is a smart integration of three modules - curvelet, retina analyser and FNN. It is simple, less time consuming and easily implementable. In future the same system can be extended to detect exact stage of DR.
  Keywords: diabetic retinopathy; retinal vasculature; tortuosity; optic fundus; single layer perceptron.
  DOI: 10.1504/IJICT.2022.10052060
   
  
• Study on enterprise financial information management system based on big data analysis.  
  by Li Zhang 
  Abstract: In order to improve the accuracy of enterprise financial information management and reduce management time, this paper proposes to design an intelligent enterprise financial information management system. Stm32f103zet6 single chip microcomputer was selected in this hardware, and TC1782 is the main controller; in the software, this system login module, authority management module, financial subject information module and financial database module are designed; in the financial information database management module, the confidence of data is determined with the help of big data analysis method, and the effective financial information data is defined through the fuzzy theory in big data analysis to complete this design. The comparison shows that the proposed system can increase this accuracy of financial data management, and the data processing time is short.
  Keywords: big data analysis; financial information; Stm32f103zet6; Tc1782 microcontroller; authority management module; financial information database management module.
  DOI: 10.1504/IJICT.2022.10052061
   
  
• Fuzzy-based weighted fair queue scheduling technique for internet of things networks  
  by Harpreet Kaur, Manoj Kumar, Sukhpreet Kaur Sidhu, Sukhwinder Singh Sran 
  Abstract: In an IoT enabled network, a variety of devices are interconnected to each other and communicate by using ultra low power communication technology known as time slotted channel hopping mechanism. To transmit information accurately, efficiently and in collision free manner, a scheduling window is implemented for the devices deployed in the network. The priority scheduling is one of the solutions implemented recently in which nodes have high priority to transmit data first. Such algorithms can block low priority communication channels indefinitely that may leave some events unreported. In order to achieve fairness, efficiency in scheduling, we used fuzzy-based weighted fair queue scheduling algorithm. So, the fuzzy-based weighted fair queue scheduling suppresses the unfairness in the scheduling mechanism for communication paths having little information. The weighted fair queue scheduling algorithm belongs to a class of scheduling algorithms that are used in network schedulers. To implement this algorithm and compare the performance with the existing technique, the MATLAB platform is used. The results reveal the improvements in network throughput, end-to-end delay, energy consumption rate, network lifetime, congestion rate and packet loss ratio as compared to existing work in the similar scenarios.
  Keywords: fair queue scheduling; priority scheduling; data transmissions; fuzzy logic; sensors.
  DOI: 10.1504/IJICT.2022.10052800
   
  
• Interactive decision support system with machine intelligence for augmentative communication  
  by Ruiwei Chen, C.B. Sivaparthipan 
  Abstract: Many augmentative communication technologies help physically challenged people to communicate with others in the present world. Augmentative communication system integrates components that include symbols, strategies, and aids that enhance communication abilities. Augmentative communication technology’s significant challenge for physically challenged people is the lack of speech expression and depression. Interactive decision support system integrated machine intelligence framework (DSS-MIF) supports augmentative communication proposed to express the physically challenged expression and depression. DSS has multiple sensors, which monitor the heartbeat rate, vocal cord vibration, body temperature, and muscle contraction. The related data are calibrated using MIF, in which the expression of the person is recognised. Based on the DSS-MIF output, physically challenged people could express themselves to others using the augmentative communication system. The experimental analysis shows that the proposed DDS-MIF for augmentative communication improves performance rate to 98.66% and shows physically challenged people’s expression effectively.
  Keywords: augmentative communication; machine intelligence; decision support; multiple sensors.
  DOI: 10.1504/IJICT.2023.10056637
   
  
• Investigating the effect of TEC variability on a dual-band GNSS receiver’s geographic location using carrier phase measurement  
  by Udaya Kumar Sahoo, Bijayananda Patnaik, Srinivasarao Chintagunta, Shyam Sundar Kundu, Shiv Prasad Aggarwal 
  Abstract: Satellite navigation is affected significantly by the ionospheric plasma bubbles and characterised using total electron content (TEC) of the ionosphere. To determine TEC, Global Navigation Satellite System (GNSS) based method has been prevailed. In this work, dual-band multi-constellation GNSS receivers were used to acquire the navigation signal of a satellite constellation in carrier phase mode. An experimental study was conducted in north-eastern tropical zone of India to correlate the position error of the dual-band GNSS receiver with the variability of TEC in the ionosphere. The study shows that the concentration of TEC in the ionosphere fluctuates throughout the day, viz., the peak value of TEC during morning, noon-time, and evening is 30.43 TECU, 65.37 TECU, and 28.32 TECU, respectively. At the TEC variability of 23.913 TECU during the September equinox, position accuracy of dual-band GNSS receiver was affected by 13.8477 cm, 3.3950 cm, and 4.9583 cm in latitude, longitude, and altitude, respectively.
  Keywords: TEC variability; ionospheric perturbation; dual-band GNSS receiver; positioning accuracy; geospatial measurement.
  DOI: 10.1504/IJICT.2023.10056906
   
  
• A novel approach for an energy-efficient traffic monitoring system using wireless sensor network and CupCarbon simulator (V 5.0) for a smart city  
  by Hanshita Prabhakar, Asna Furqan 
  Abstract: Internet network is contributing to the Traffic monitoring system so that people get more advantages and less delay from traffic updates as the number of automobiles widens and daily congestion increases. To manage delays and congestion in the proposed work, we have implemented an intelligent traffic monitoring system using a wireless sensor network for the smart city. The shortest path sensor nodes are active, and the rest of the sensors are not due to the inactiveness of other sensor’s energy saved. The results have shown that the sensor node has the highest energy and battery life for the shortest path detection process concerning time. Highest point taken by the sensor is 0.040 J at a time of 0.10 s, and the battery life of a sensor node varies between (19,159.995 and 19,160.005) it has examined and estimated the errors, transmission/reception happens between the sensor nodes with the help of console output messages.
  Keywords: CupCarbon simulator (V 5.0); internet of things; IoT; smart city; wireless sensor network; WSN; intelligent traffic monitoring.
  DOI: 10.1504/IJICT.2024.10061724
   
  
• Performance modelling and estimation of multi-user CDMA wireless technology with evolving spreading gain and noise density  
  by Ridhima Mehta 
  Abstract: The efficient signal processing techniques for spread-spectrum code division multiple access (CDMA) systems necessitate data delivery with higher quality-of-service support, diminished error rates and improved channel capacity. In this paper, the impact of interference regulation is explored on various channel-based unique attributes in the wireless multi-user CDMA networks. The enhanced performance of these networks with increasing spreading gains to accomplish wider communication spectrum is analysed while accommodating a larger number of subscribers. Moreover, the performance comparison between synchronous and asynchronous CDMA techniques is implemented for different number of users and noise spectral density. As the order of the employed phase shift keying modulation scheme increases, the average signal-to-interference plus noise ratio (SINR) per information bit transmitted scales up for accurate channel detection and data decoding at the receiver. Finally, it is demonstrated that our proposed model outperforms other existing methods in terms of SINR, average bit error rate, and throughput.
  Keywords: bit error rate; code division multiple access; CDMA; interference power; signal-to-interference plus noise ratio; SINR; spreading gain.
  DOI: 10.1504/IJICT.2024.10063749
   
  
• GSKTM: efficient of query search for spatial keyword in text mining  
  by Ramya R.S., Darshan Manu, G. Naveen Raju, Sejal Santosh Nimbhorkar, Venugopal Kuppanna Rajuk, S.S. Iyengar, L.M. Patnaik 
  Abstract: In today’s world, geo-positioning technologies, location-based services have attracted many researchers due to the increasing amount of spatio textual objects in various applications like social networks, geo location services. Each spatial object consists of spatial locations and a set of query terms. In this paper, an efficient group of query search for spatial keyword in text mining is proposed that retrieves both spatial and textual keyword objects to effectively reduce the search space. The clusters and subclusters are constructed based on the calculated range of the objects location and categories in the dataset. Further, categorylist is constructed that identifies the category of interest (CoI) of users query. Experiments are conducted on two real dataset namely Euro and geographic names. It is observed that GSKTM outperforms inverted linear quad-tree (ILQ) with improved response time and provides groupwise top-k results.
  Keywords: Group; Keyword; Query Search; Spatial Text Feature Selection.
  
  
• A new fast DBSCAN using dual-space analysis and colour integral volume for document image segmentation  
  by Zakia Kezzoula, Djamel Gaceb 
  Abstract: The segmentation of the colour document images is an essential step allowing facilitating and improving the stages of characterisation and interpretation of the information contained in these documents. Recent systems of automatic processing and recognition of document images, which use separation of colouremric layers, are more efficient compared to conventional systems, only based on binary or grey levels images. This task requires non-supervised pixel segmentation or clustering techniques to separate the document image to a variable and unknown number of colour layers. The methods based on density are widely used in this context at pixel level, such as the DBSCAN method and its different variants, very robust to the noise and more adapted to the degradations present on document images, but who suffer from a great complexity. In this context, we propose a new faster DBSCAN variant using the volume integral in colourimitric space for the first time to significantly reduce calculation time. The combination of the two spaces, Cartesian and colorimetric has also accelerated the method and improved its performance on document images with different challenges. The results obtained show the effectiveness of the proposed approach, which was marked by significant improvement in the quality of segmentation and reduction in computed time.
  Keywords: clustering; DBSCAN; region growing; document image segmentation; fast I2SDBSCAN; 3D colour histogram; integral volume.
  DOI: 10.1504/IJICT.2024.10065387
   
  
• Community detection of trajectory data for location-based facility recommendation system  
  by B.A. Sabarish, R. Karthi, T. Gireesh Kumar 
  Abstract: Trajectory contains spatial-data generated from traces of moving objects like people, animals, etc. Community generated from trajectories portrays common behaviour. Trajectory clustering based on community-detection involves region-graph generation and community-detection. In region-graph generation, trajectories are projected to spatial grid to transform GPS representation into string representation. Sequential graph is generated from string representation. Edge-based similarity is calculated between trajectories to create an adjacency matrix representing relationship and represent entire region. In community-detection phase, region-graph is divided into communities using various algorithms and validated using modularity values. Based on analysis, Louvain, fast-greedy, leading-eigenvector, and edge-betweenness algorithms provide the optimum modularity value for better community detection. Analysing the community can be used as a pre-processing step in identifying location for location-based services (LBS), including hotspots, delay-tolerant-networks, and mobile antenna placements for better coverage. Design and capacity planning of the network based on the size and pattern of the community improves quality of LBS.
  Keywords: trajectory; community; delay tolerant networks; quality of service; clustering; representation.
  DOI: 10.1504/IJICT.2022.10048405
   
  
• A Huffman-based short message service compression technique using adjacent distance array  
  by Pranta Sarker, Mir Lutfur Rahman 
  Abstract: The short message service (SMS) is a wireless medium of transmission that allows you to send brief text messages. Cell phone devices have an uttermost SMS capacity of 1,120 bits in the traditional system. Moreover, the conventional SMS employs seven bits for each character, allowing the highest 160 characters for an SMS text message to be transmitted. This research demonstrated that an SMS message could contain more than 200 characters by representing around five bits each, introducing a data structure, namely, adjacent distance array (ADA) using the Huffman principle. Allowing the concept of lossless data compression technique, the proposed method of the research generates character's codeword utilising the standard Huffman. However, the ADA encodes the message by putting the ASCII value distances of all characters, and decoding performs by avoiding the whole Huffman tree traverse, which is the pivotal contribution of the research to develop an effective SMS compression technique for personal digital assistants (PDAs). The encoding and decoding processes have been discussed and contrasted with the conventional SMS text message system, where our proposed ADA technique performs outstandingly better from every aspect discovered after evaluating all outcomes.
  Keywords: data compression; SMS compression; Huffman coding; data structure; adjacent distance array; ADA.
  DOI: 10.1504/IJICT.2022.10052558
   
  
• Research on reversible information hiding in image encryption domain based on multilayer perceptron  
  by Zhiqiang Yue, Weijia Chai 
  Abstract: To solve the problems of large mean square error, low peak signal-to-noise (PSNR) ratio and low embedding rate of traditional methods, a reversible information hiding in image encryption domain based on multilayer perceptron is proposed. Image blocks are encrypted sequentially, and the encrypted information is embedded into the image to complete the construction of the image encryption domain. Reversible information in the image encryption domain is extracted, the weight of the extracted information is calculated by multilayer perceptron, and the sender and receiver models are built according to the calculation results. Reversible information hiding in the image encryption domain is realised by using these two models. Experimental results show that the maximum and minimum mean square error of the encrypted image and the original image are 0.254 and 0.482 respectively, the maximum and minimum PSNR ratio are 56dB and 50dB respectively, and embedding rate is always above 91%.
  Keywords: multilayer perceptron; images; encrypted domain; reversible information hiding; dimensionality reduction; sender model; receiver model.
  DOI: 10.1504/IJICT.2022.10049147
   
  
• Exploring the possibilities of integration of cyber-psychology for human behaviour in a smart city  
  by Liping Wen, Zhou Ting, Huang Zheng, J. Alfred Daniel, A. Antonidoss 
  Abstract: The smart city idea differs between cities and nations. In all meanings and characteristics of a smart city, public involvement is the only thing that remains common. Therefore, it is a very significant field to study human behaviour and development in smart cities. This paper presents a framework for identifying qualities necessary for people to be classified as intelligent persons and to integrate these human behavioural characteristics in cyber technology. Human behaviour in a smart city has been analysed using the machine learning algorithm and big data analytics. The integrated machine learning and big data analytics framework (iML-BD) classifies the cyber behaviour of intelligent persons in a smart city by observing the cyber activities performed by the individuals. Furthermore, this paper handles the risk factors for cyber-acquired and cyber-dependant crime violence and abuse that vulnerable internet and public access devices using blockchain technology. Blockchain is a method of storing data that takes too long to alter, modify, or manipulate. A blockchain is an electronic accounting system that is reproduced and spread through the Bitcoin protocol's entire communication network. The case study performed on iML-BD has resulted in the highest performance in terms of prediction accuracy of 94.98%.
  Keywords: cyber crime; human behaviour; machine learning; smart city; vulnerability.
  DOI: 10.1504/IJICT.2024.10065162
   
  
• A rapid elimination of communication signal interference in complex electromagnetic environment  
  by Cao Chai 
  Abstract: In order to solve the problems of low recognition accuracy and the long-time consumption of the signal interference elimination method, a rapid elimination method of communication signal interference in a complex electromagnetic environment is studied. Short-time Fourier transform (STFT) algorithm is used to calculate the time spectrum of mixed signals in complex electromagnetic environment. According to frequency and amplitude characteristics, fuzzy minimum-maximum neural network (FMNN) is used to classify and identify the interference signals. According to the transverse filter, least mean square (LMS) algorithm is constructed to calculate the tap weight coefficient and filter coefficient, which is combined with the filter coefficient to separate the normal communication signal from the interference signal to achieve the rapid elimination of interference. Experimental results show that the maximum recognition accuracy of the proposed method is 97%, the signal noise amplitude is between 3 and 10 dB, and the average time of interference elimination is 0.73 s.
  Keywords: complex electromagnetic environment; communication signal; time spectrum; FMNN; LMS algorithm; low recognition accuracy; long time consuming.
  DOI: 10.1504/IJICT.2022.10050728
   
  
• Research on accurate estimation of energy consumption of new energy vehicles based on improved Kalman filter  
  by Fangling Zhang 
  Abstract: Because the previous traditional methods have a series of obstacles in data acquisition, such as low accuracy, large error and long calculation time, an accurate estimation method of energy consumption of new energy vehicles based on improved Kalman filter is proposed. Taking TC275 chip as the core, a set of energy vehicle energy consumption data acquisition architecture is designed to filter the collected data. After changing the estimation calculation method, finally, the latest consumption estimates result is obtained by using the Kalman filter. The result is 88%, the maximum is 93%, the average energy consumption estimation error rate is 6.8%, and the estimation time fluctuates between 0.3 s and 0.7 s.
  Keywords: improved Kalman filtering; new energy vehicles; accurate energy consumption estimation; data acquisition architecture; filtering.
  DOI: 10.1504/IJICT.2022.10052062