International Journal of Information and Communication Technology (25 papers in press)

Regular Issues

• Open Access

  Multimedia interactive creative dance choreography design integrating hybrid density network algorithms ( Free Full-text Access )

  by Di Wu, Qian Zhao 
  Abstract: With the continuous development of society and economy, dance has changed from traditional individual movements to group and interactive movements. Although computers have been introduced for multimedia interactive dance choreography, there are still insufficient simulation accuracy, large calculations, and real-time Poor performance and other limitations, and relatively difficult to model. In the realm of multimedia interactive dance choreography, the industry is plagued by issues of simulation inaccuracy, high computational demand, and inadequate real-time responsiveness. These limitations impede the seamless integration of dance movements with multimedia elements, demanding a sophisticated solution. This paper introduces a hybrid density network algorithm to address these challenges by integrating a myriad of influencing factors into the choreographic design process to achieve creative interactive dance choreographer. Practice has proved that the algorithm is effective and can effectively support multimedia interactive creative dance choreography.
  Keywords: inverse kinematics; hybrid density network algorithm; creative dance choreography design; multimedia interaction.
  
  

• Open Access

  Analysis of control characteristics of intelligent digital pump combined with discrete variables ( Free Full-text Access )

  by Jinyan Shi, Kechang Zhang 
  Abstract: In order to improve the control effect and operation effect of intelligent digital pump, this paper analyses the control characteristics of intelligent digital pump with discrete variable method, and obtains the transfer function of the control system of digital pump through the establishment and analysis of mathematical model. The variable mechanism of digital pump can be simplified as a mechanical-hydraulic servo system in which two-sided slide valves control differential cylinders. The digital pump system based on discrete variable technology is a parallel digital discrete system, which is composed of digital pump and control valve group. The control valve logic topology relation is adopted to realise the combined control of displacement through coded signals. Moreover, the proposed control configuration can significantly improve the displacement control accuracy under the same number of control units, and then reduce the variable impact amplitude. Based on the experimental bench and loader prototype, the digital pump steering system and control strategy are tested and analysed, which verifies the feasibility of this method proposed by this paper.
  Keywords: discrete change; intelligent digital pump; intelligent control; control characteristics.
  
  

• Open Access

  Analysis and assessment of multimedia-assisted physical education quality based on graded score algorithm ( Free Full-text Access )

  by Chuncheng Wu 
  Abstract: In the modern educational landscape, multimedia integration in physical education (PE) has become a pivotal tool for enhancing teaching quality. This study introduces a novel graded score algorithm designed to analyse and consolidate various factors that influence the effectiveness of multimedia-assisted PE. The algorithm employs a weight analysis approach to assess and optimise the quality of teaching, offering insights for curriculum development and multimedia content enhancement. Our simulation results indicate that the algorithm is adept at identifying key factors that impact teaching quality, thus supporting a comprehensive evaluation framework for student progress. This research not only advances multimedia technology but also contributes to the development of grade-score algorithms, aiming for continuous refinement in educational practices.
  Keywords: differential score algorithm; multimedia technology; physical education; PE; teaching quality analysis; multimedia-assisted teaching.
  
  

• Open Access

  Design and implementation method of immersive IoT teaching platform based on virtual reality technology ( Free Full-text Access )

  by Dafei Wu 
  Abstract: With societal and economic advancements, teaching methods have evolved from traditional single-directional approaches to interactive models utilising diverse online resources. However, certain limitations persist. Addressing these, this paper introduces virtual reality (VR) technology, merging it with internet of things (IoT) teaching platforms to create immersive classroom experiences. By integrating interactive design and learning within surreal VR environments, we establish a novel teaching paradigm. Furthermore, we explore the rationality of interactive design application in teaching. Simulation results demonstrate VRs extensive applicability, offering a broader and more open educational platform. Future endeavours should focus on effectively combining immersive IoT with higher education to enhance educational outcomes.
  Keywords: virtual reality; VR; teaching platform; internet of things; IoT; immersive.
  
  
• 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
   
  
• 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 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
   
  
• 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 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
   
  
• 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.
  
  
• 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 protocols 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.
  
  
• 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 that 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
   
  
• 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
   
  
• Chinese and Vietnamese cross-lingual topic discovery based on word similarity of comparable corpus  
  by Zhengtao Yu, Linjie Xia, Peili Tang, Xiaocong Wang, Shengxiang Gao 
  Abstract: In order to solve the problem of the scarcity of Chinese-Vietnamese comparable corpus and limited scale of bilingual dictionaries, we propose a method for cross-language topic discovery based on the similarity between Chinese and Vietnamese. Firstly, we use the Chinese-Vietnamese comparable corpus to train to get the word vectors representing the bilingual texts, and calculate the similarity between the Chinese query words and Vietnamese words. Then, we select out readily extended words from Vietnamese which are similar to the Chinese words. Subsequently, the Chinese-Vietnamese translation model is constructed from the similarity between the Chinese-Vietnamese words, to search the Vietnamese word from the translation model and return the related Vietnamese document. Finally, the AP algorithm is used to obtain the Vietnamese documents related to the Chinese text. The experimental results show that the proposed method has achieved good results in accuracy and recall rate.
  Keywords: Chinese and Vietnamese; cross-language topic discovery; comparable corpus; word similarity; cross-language query translation model.
  DOI: 10.1504/IJICT.2024.10065007
   
  
• 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
   
  
• 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
   
  
• A key feature mining method of online teaching behaviour 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