International Journal of Information and Communication Technology (32 papers in press)

Regular Issues

• Open Access

  Based on fuzzy mathematics multi-level comprehensive evaluation of physical education teaching quality and improvement ( Free Full-text Access )

  by Yan Liang 
  Abstract: At present, in the information work of different colleges and universities, fuzzy mathematics multi-level comprehensive assessment applied to schools, have received good results. At present, when the physical education teaching teachers set up the physical education teaching hall, due to the number of students, location, time, teachers and many other reasons, resulting in the complexity of the physical education teaching. Based on fuzzy mathematics multi-level comprehensive evaluation method, this paper studies the adaptability of intelligent physical education course teaching. In colleges and universities, due to the increase of the number of schools, the arrangement of teaching content is more difficult and complicated. Moreover, once there are problems in the arrangement, it will have a great impact on the whole teaching process, so as to promote the teaching effect of the classroom to a certain extent.
  Keywords: fuzzy mathematics; multi-level comprehensive evaluation; physical education curriculum; the quality of teaching.
  DOI: 10.1504/IJICT.2024.10062478
   
  

• Open Access

  Improved DeepLabv3+ connected augmented reality technology for building target extraction in urban environmental design ( Free Full-text Access )

  by Jie Chen, Qian Wu 
  Abstract: Aiming at the problem of inaccurate segmentation of building edges in remote sensing images, the imprecise segmentation of building edges in remote sensing images by deep learning models is an important research direction for remote sensing intelligence applications. This paper proposes a lightweight remote sensing image building extraction method based on DeepLabv3. The skeleton network uses DeepLabv3 to connect the IEU-Net structure. Secondly, in order to solve the problem of limited feature richness of the model, the morphological construction index MBI is introduced to participate in the classification process of the model together with the RGB band of the remote sensing image. Finally, in the model prediction, corresponding to IELoss, a strategy of ignoring edge prediction is adopted to obtain the best building extraction results. Our proposed method can effectively overcome the problem of insufficient edge pixel features of samples, suppress the influence of road and building shadows on the results, and improve the extraction accuracy of houses and buildings in remote sensing images.
  Keywords: building extraction; boundary perception; DeepLabv3+.
  DOI: 10.1504/IJICT.2024.10062708
   
  

• Open Access

  Mathematical modelling of multi-UAV scenario planning based on 3D LiDAR ( Free Full-text Access )

  by Ruishuai Chai 
  Abstract: In order to improve the operation efficiency of multi-UAV groups, this paper studies the mathematical modelling of multi-UAV scene planning, takes 3D LiDAR technology as the base navigation technology, and uses the bacterial foraging algorithm as the multi-objective optimisation algorithm. Moreover, this paper appropriately improves the defects of the algorithm, and introduces the bacterial population in the algorithm into the log-linear model to improve the two basic behaviours of the algorithm, the trend and the migration, so that the local search of the algorithm is more accurate. In addition, this paper introduces Gauss-Cauchy variation to ensure the diversity of bacterial populations and ensure that the algorithm results are close to the global optimal value. Through experimental research, it is known that the algorithm proposed in this paper can drive the drone to conform to the flight trajectory as a whole, achieve the expected fusion positioning accuracy, and meet the requirements of autonomous cruising. The average registration time is 120 milliseconds, which meets the real-time perception of the scene and pose estimation requirements during cruising. The experimental study shows that the multi-UAV scene planning method based on 3D LiDAR can effectively improve the optimal control effect of multi-UAV.
  Keywords: 3D LiDAR; multi-UAV; scene planning; mathematical modelling.
  DOI: 10.1504/IJICT.2024.10063064
   
  

• Open Access

  The application of geometric form in architectural interior environment design ( Free Full-text Access )

  by Nan Yin 
  Abstract: In the traditional interior design realm, limitations in conveying spatial concepts led to the emergence of virtual reality (VR) and artificial intelligence (AI) integration. These technologies aim to offer enhanced user experiences and meet personalised demands by simulating indoor environments. The contemporary approach emphasises a harmonious blend of art and science to streamline design processes, aiming for efficiency. However, despite efforts to simplify and automate design, reliance on specialised designers persists, elongating design cycles and increasing costs. Presently, manual furniture selection involves a cumbersome process, impacting design outcomes and elevating building expenses. This paper explores geometric and mathematical optimisation strategies for interior environmental design in buildings, aiming to address inefficiencies in design and bridge the gap between professional expectations and user preferences.
  Keywords: geometric form; architectural design; indoor environment; spatial planning.
  DOI: 10.1504/IJICT.2024.10063139
   
  

• Open Access

  A health prediction method for new energy vehicle power batteries based on AACNN-LSTM neural network ( Free Full-text Access )

  by Jijun Zhang, Wenjian Feng, Yisong Tan, Hanping Pan 
  Abstract: Battery pack is an important part of the energy system of electric vehicles, and ensuring its safety is of great significance to the intelligent development of electric vehicles and human life and property. Detecting and ensuring the safety of battery pack in the energy system has become a research hotspot in the field of power batteries. Proposes a new composite deep neural network attention after CNN-LSTM (AACNN-LSTM) based on the characteristics and limitations of long- and short-term memory (LSTM) neural network, one-dimensional convolution neural network (1D-CNN) and other methods. We have carried out comparative experiments such as data division of different life stages, ablation experiments of multiple architecture combinations, and comparison with different types of algorithms. The results show that compared with other methods, the precision is significantly improved and the operation efficiency is maintained. Finally, the proposed health state estimation method is verified by three different battery accelerated aging test datasets. The experimental results show that the proposed method shows excellent battery health state estimation performance and good robustness under different working conditions and different number of training cycles.
  Keywords: life prediction; attention mechanism; time series prediction; long and short time memory neural network.
  DOI: 10.1504/IJICT.2024.10063210
   
  

• Open Access

  Deconstruction of the influence of entrepreneurial orientation on innovation performance based on logistic regression model ( Free Full-text Access )

  by Dong Li 
  Abstract: In the dynamic landscape of innovation and entrepreneurship, the challenge lies in fostering survival and innovation in entrepreneurial ventures amid evolving markets. Investigating how entrepreneurial orientation (EO) influences innovation performance (IP) is a crucial research focus. Leveraging logistic regression analysis, this study examines the impact of EO on IP. By exploring the relationship between corporate EO traits and utilising logistic regression models, it highlights the substantial positive influence of innovation, proactiveness, and risk-taking aspects of EO on IP. Notably, the innovation factor demonstrates a significant impact, with a score of 0.794, indicating its pivotal role. Understanding this relationship provides valuable guidance for enterprises, emphasising the significance of EO in enhancing future innovation performance.
  Keywords: enterprise EO; IP; logistic regression model; enterprise innovation; entrepreneurship.
  DOI: 10.1504/IJICT.2024.10063249
   
  

• Open Access

  Integration of Fourth Industrial Revolution in teaching and learning during COVID-19 pandemic ( Free Full-text Access )

  by Awelani V. Mudau, Lettah Sikhosana 
  Abstract: The aim of this paper was to explore how Fourth Industrial Revolution shaped teaching and learning during the COVID-19 pandemic in some schools located in Gauteng and Mpumalanga provinces, South Africa. This paper employed a qualitative interpretative multiple case study design. We selected four teachers who separately taught in early childhood development, intermediate phase, senior phase and further education and training phases purposefully. Data was collected telephonically through semi-structured interview and analysed using a typology approach. We inferred from the results that teachers had challenges with teaching and learning resources, unlimited access to internet and socio-economic background. There were also challenges related to teachers’ background on the usage of Fourth Industrial Revolution and the lack of support from the School Management Teams. Therefore, we recommended that the relevant stakeholders within the education sector to provide resources such as smart-boards, computers, and unlimited internet access in schools lacking such facilities.
  Keywords: Fourth Industrial Revolution; 4IR; COVID-19; School Management Teams; SMTs; integration; blended learning.
  DOI: 10.1504/IJICT.2024.10063468
   
  

• Open Access

  Research on high-precision time synchronization technology for sea mobile platforms ( Free Full-text Access )

  by Dao Peng Dong, Hong Shuo Wu, Qing Feng Guo, Jin Wei Yang, Xi Li 
  Abstract: Under static conditions, at present, mature technologies for long-distance and high-precision time synchronisation include satellite common view (CV) and two way satellite time and frequency transfer (TWSTFT) and so on. However, under dynamic conditions, research on high-precision time synchronisation technology is relatively lack such as mobile platforms on the sea. Considering the dynamic conditions of mobile platforms on the sea, a method of position’s smooth filtering with velocity is proposed to improve the accuracy of position measurement, reducing the time measurement error introduced by position error. And proposed method improves ultimately the CV comparison accuracy between sea surface mobile platforms. The simulation and actual test results show that by using the method of position’s smooth filtering with velocity, the CV comparison accuracy between mobile platforms on the sea can reach 10 ns.
  Keywords: mobile platform; time and frequency synchronisation; spaceon electronics; common view; CV.
  DOI: 10.1504/IJICT.2024.10063506
   
  

• Open Access

  Chinese character style transfer based on improved StarGAN v2 network ( Free Full-text Access )

  by Ruohao Wang, Yilihamu Yaermaimaiti 
  Abstract: Chinese character generation has attracted a lot of attention due to its wide range of applications. Mainstream methods for generating Chinese character fonts are mainly based on generative adversarial networks, however, the structure of Chinese characters is more complex than other fonts and the problem of font structure change and style loss occurs when generating complex fonts and the mainstream methods require paired datasets, which is difficult and time-consuming to collect paired datasets. This paper proposes Trans-StarGAN v2 network for the above problems, which is based on StarGAN v2, introduces the Transformer structure for spatial feature extraction and channel feature extraction, which improves the feature extraction and generation ability of the network, and secondly, introduces the perceptual loss to strengthen the model training process. The experimental results show that compared with other Chinese character generation networks, the proposed network can generate multiple styles of fonts at the same time, improve the quality of the generated characters, preserve the structure of the fonts and make the style more complete in the face of complex fonts, and improve the FID and LPIPS indexes of the generated Chinese character content.
  Keywords: transformer; generative adversarial network; GAN; style migration; StarGAN v2.
  DOI: 10.1504/IJICT.2024.10063507
   
  
• Analysing the Algerian social movement through Twitter  
  by Meriem Laifa, Djamila Mohdeb, Mouhoub Belazzoug 
  Abstract: Technology has altered collective actions guidance resulting in a new regulatory frame for action. For the sake of being successful in a social movement, people plan and advertise in advance to encourage and gather greater participation to strengthen the influence of crowds. For this, social media offers exceptional opportunities to organise masses of people into actions with lower participation expenses, and to foster new repositories of information and actions that go beyond communities offline. While most contemporary social movements have been studied from different perspectives, the Algerian social movement (i.e., Hirak) was overlooked in the literature. This paper presents a distinctive foundation for understanding the Algerian Hirak through analysing Twitter data. The used approach is established mainly at the intersection of sociology and data analysis, with the intention to generate an improved discernment of this movement. Promising future research directions are also discussed in this paper.
  Keywords: social movements; social media; Algerian Hirak; natural language processing; Twitter; Algerian Social Movement.
  DOI: 10.1504/IJICT.2022.10046232
   
  
• Received signal strength-based power map generation in a 2-D obstructed wireless sensor network  
  by Mrinmoy Sen, Indrajit Banerjee, Tuhina Samanta 
  Abstract: This paper analyses the effect of received signal strength (RSS) in efficient deployment, in presence of obstacles. We consider RSS based power values, so that x-y plane represents the spatial coordinates within a target field and z coordinates denote power values over the field. We plot the power values on the x-y coordinates, addressed as power map, having some peaks and falls: the peaks represent strong signals and the falls represent weak signals at the co-ordinates. It is intuitive that locations with strong signals are more suitable for communications. The falls in the power strength indicates that more sensor nodes are to be put for successful communications. We validate the proposed scheme via simulations as well as small-scale indoor and outdoor experiments with XBee sensor motes. We propose an algorithm to estimate the received power and analyse the estimated results with the results generated through the hardware test-bed.
  Keywords: noisy channel; node deployment; power map; channel frequency; obstructed network.
  DOI: 10.1504/IJICT.2022.10046848
   
  
• Which people are loyal followers of influencers? An exploratory study  
  by Javier A. Sánchez-Torres, Juan Sebastían Roldan-Gallego, Francisco-Javier Arroyo-Cañada, Ana María Argila-Irurita 
  Abstract: Influencers are tools implemented in digital marketing as a communication mechanism between the brand and its target; however, there are few studies that observe the relationship between the personality of the follower and their attitude towards the influencer. The objective of this study is to explore whether personality traits influence positive attitudes towards influencers. An empirical study was carried out in Spain and Colombia with a sample of 381 individuals and cause-effect relationships were analysed using the partial least squares methodology. The results show that extroversion and disordered personality traits are related to positive attitudes towards influencers and there could be some differences between genders, specifically men with a calm personality and women with a sympathetic personality
  Keywords: influencers; personality; followers; social network analysis; internet marketing; digital marketing; partial least squares methodology; extroversion; disordered personality; calm personality; sympathetic personality.
  DOI: 10.1504/IJICT.2022.10047160
   
  
• A secure and integrated ontology-based fusion using multi-agent system  
  by Tarek Salah Sobh 
  Abstract: This study aims to handle ontology-based fusion and use multi-agent systems to obtain information fusion from multiple sources/sensors in a secure and integrated manner. Therefore, our objective is to produce a secure and integrated ontology-based fusion framework by using multi-agent. The agent system gets different props from using ontologies such as interoperability, reusability, and support. Here, fusion levels vary from the signal level that is low to the high knowledge level. Securing a multi-agent platform was introduced through a security system called 'SMASP'. The performance results show that the framework is almost idle while the user is composing the query. The workload is low on CPU and memory. This framework receives multiple data sources through cloudlet. Ontologies support a secure multi-agent system with different operations such as reasoner agents and query agents. Using the cloudlet architecture gives the flexibility to overcome intensive computing and sensitivity to latency.
  Keywords: information fusion; multiple data sources; integrated framework; ontology; reasoning; cloudlet; agent security.
  DOI: 10.1504/IJICT.2022.10048013
   
  
• An efficient single unit for virtual-machine placement in cloud data centres  
  by Salam Ismaeel, Ali Miri, Ayman Al-Khazraji 
  Abstract: There are numerous energy minimisation plans are adopted in today’s data centres (DCs). The highest important ones are those that depend on switching off unused physical machines (PMs). This is usually done by optimal distribution and/or reallocating of virtual machines (VMs) on the selected servers. While maintaining the quality of service (QoS) to ensure the performance of a DC. In this work, a novel server machine condition index (MCI) has been proposed, which includes all resources related to servers available in the DC using a single unit. The MCI represents a dynamic tool to compare services, increase effectiveness, reflect PM adequation, and ensure the optimal management of heterogeneous DC resources. The MCI will be used to convert the multi-objective VM allocation optimisation problem into a single-objective problem. This work will identify the MCI components and the way that can be used as a cloud resource unit, and modified VMP algorithms.
  Keywords: power consumption; virtual-machine placement; cloud data centre; closed loop system; sustainable energy systems; task scheduling.
  DOI: 10.1504/IJICT.2022.10048372
   
  
• 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
   
  
• Information integration method of English teaching resources based on artificial intelligence  
  by Jin Guo 
  Abstract: In this paper, an information integration method of English teaching resources based on artificial intelligence is proposed. The generalised fuzzy C-means clustering algorithm was used to construct the Arduino device image dataset, and the convolutional neural network model of Arduino device was designed. The image data input model in TFRecord format was designed, and multiple Arduino device resource feature maps were output through convolution, pooling and other operations to establish the English teaching resource library and complete the information integration of English teaching resources. The experimental results show that this method has fast convergence speed, with a recognition success rate of 96.7% and can improve the academic performance to more than 90 points, and the actual evaluation value of it in the 5th and 6th academic year is close to 1. Therefore, it can improve the information integration efficiency of English teaching resources and English performance.
  Keywords: artificial intelligence; English teaching; resource information integration; Arduino device; convolution neural network; clustering algorithm.
  DOI: 10.1504/IJICT.2022.10048588
   
  
• 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
   
  
• A key feature mining method of online teaching behavior based on k-kernel decomposition  
  by Wei Wang 
  Abstract: In view of the poor effect of online teaching behaviour key feature mining, an online teaching behaviour key feature mining method based on k-kernel decomposition is designed. Firstly, the adjacent data of the key features of network teaching behaviour are interpolated to determine the key features, and the singular distance function is normalised to complete the feature preprocessing; Then, the key characteristics of network teaching behaviour are transformed into weighted network, and the key characteristics are divided according to the centrality of nodes; Finally, the online behaviour feature k-kernel after classification is assigned, the feature k-kernel value index after assignment is calculated, the correlation of feature data is calculated, the probability of feature data belonging to k-clustering is determined, and the key feature mining of network teaching behaviour is completed. The results show that the mining effect of this method is good.
  Keywords: K-kernel decomposition; weighted network; online teaching behaviour; key feature mining.
  DOI: 10.1504/IJICT.2022.10049157
   
  
• Improving college ideological and political education based on deep learning  
  by Youwu Zhang, Yongquan Yan, R. Lakshmana Kumar, Sapna Juneja 
  Abstract: The rapid development of information and technology results in the involvement of technology channels like communication devices, and simultaneously it acts as a vital part of life. It emerged as a significant concern in the student’s educational progress both physically and mentally. It is essential to maintain the teaching quality in the teaching field, and more concentration is needed for the college ideological political education. For successive enhancement, a novel multimedia assisted ideological and political education system using deep learning techniques (MIPE-DLT) is introduced. The model analyses the characteristics and the capability of higher education students in gathering information and realising the effects of propagating novelties in ideological and political education. The proper flow of protocols has been executed in implementing multimedia techniques towards ideological and political education. It bridges the gap efficiently with a higher accuracy rate and processing rate. Compared with previous techniques, the MIPE-DLT achieves a high-order performance ratio with a minimal delay rate.
  Keywords: multimedia; political; ideology; education; college learning; quality; teaching.
  DOI: 10.1504/IJICT.2022.10049249
   
  
• A rapid elimination of communication signal interference in complex electromagnetic environment  
  by Cao Chai 
  Abstract: To solve the problems of low recognition accuracy, high noise amplitude and long time consuming of traditional methods, a rapid elimination method of communication signal interference in 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 10dB, and the average time of interference elimination is 0.73s.
  Keywords: complex electromagnetic environment; communication signal; time spectrum; FMNN; LMS algorithm; low recognition accuracy; long time consuming.
  DOI: 10.1504/IJICT.2022.10050728
   
  
• A secret sharing scheme based on integer decomposition and hexagonal structure  
  by Zender Rouia, Noui Lemnouar, Abdessemed Mohamed Rida 
  Abstract: Security is a major challenge in storage and transmission of digital data. Secret sharing scheme is a fundamental primitive used in multiparty computations, access control and key management, which is based here on two concepts, namely: hexagonal structure and integer decomposition. Use of hexagonal structure is common in biological modelling. For integer decomposition, the oldest known method is Fermat’s factorisation, while for the proposed decomposition, the factorisation uniqueness of positive integer into two factors is exploited. Experimental results obtained from the applied scheme to digital images reveal interesting properties; this scheme turns out to be lossless, ideal, flexible, extensible, and even can detect and identify cheater; in sum, it has a good security.
  Keywords: secret sharing; quasi-square decomposition; bio-inspired hexagonal structure; isoperimetry.
  DOI: 10.1504/IJICT.2022.10051892
   
  
• 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
   
  
• 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
   
  
• A data tamper-proof method of cloud computing platform based on blockchain  
  by Dongying Gao, Renjie Su, Helin Zhang, Jie Fu, Hang Zhang 
  Abstract: In order to solve the problems existing in traditional methods such as low tamper-proof success rate, high tamper-proof time and high resource occupation, a data tamper-proof method of cloud computing platform based on blockchain is designed. The differences of data features are obtained according to the number of data spatial dimensions to determine the importance of data features. According to the importance of data features, on the basis of cloud computing platform data denoising processing, the data feature set is constructed to complete feature extraction. Combined with the result of feature extraction, blockchain is used to construct block structure, and the tamper-proof algorithm of cloud computing platform data is designed to ensure the data security of cloud computing platform. The experimental results show that the tamper-proof method designed has a high success rate, low tamper-proof time, low resource occupation, and good practical application effect.
  Keywords: blockchain; cloud computing; data tamper-proofing; platform data; realtime.
  DOI: 10.1504/IJICT.2022.10052225
   
  
• Study on detection of attacking nodes in power communication network based on non-parametric CUSUM algorithm  
  by Mengxiang Liang, Wenlong Yao, Changqi Wei 
  Abstract: In order to improve the detection accuracy and time-consuming of traditional attack node detection methods, the paper proposes a new method for power communication network attack node detection based on non-parametric CUSUM algorithm. First, according to the similarity evaluation results, the suspicious nodes in the power communication network are collectively processed. Secondly, in order to make the node sequence meet the calculation requirements of the non-parametric CUSUM algorithm, the node sequence is preprocessed. Finally, the non-parametric CUSUM algorithm is used to calculate the threshold of the attacking node detection, and the attacking node decision function is constructed to complete the detection of the attacking node. Through experimental verification, it is found that the detection method proposed in this study can effectively detect attacking nodes, the detection accuracy is basically maintained above 95%, and the maximum detection time does not exceed 4 s.
  Keywords: non-parametric CUSUM algorithm; power communication network; attack node detection.
  DOI: 10.1504/IJICT.2022.10052226
   
  
• 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
   
  
• 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