Forthcoming and Online First Articles

International Journal of Information and Communication Technology

International Journal of Information and Communication Technology (IJICT)

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International Journal of Information and Communication Technology (26 papers in press)

Regular Issues

  •   Free full-text access Open AccessSentiment classification model for student teaching evaluation based on deep learning technology
    ( Free Full-text Access ) CC-BY-NC-ND
    by Cen Li 
    Abstract: In order to improve the effect of emotion classification of students’ teaching evaluation, this paper studies the emotion classification of students’ teaching evaluation combined with deep learning technology. This paper presents a sentiment analysis method based on the sentiment dictionary of teaching evaluation as a cold start solution when the marking data is insufficient. This method builds a collocation dictionary for teaching evaluation, solves the polar context-related problems of emotion words, introduces parallel relation and similarity calculation, and designs multi-level polarity recognition strategies for emotion words, so as to improve the performance of emotion analysis. The research shows that the classification model of student teaching evaluation based on deep learning proposed in this paper has a good effect on emotion classification, and has a certain effect on promoting interaction between teachers and students.
    Keywords: student; teaching evaluation sentiment; classification model; deep learning.
    DOI: 10.1504/IJICT.2024.10063748
  •   Free full-text access Open AccessResearch on intelligent teaching curriculum of preschool education majors in universities based on artificial intelligence technology support
    ( Free Full-text Access ) CC-BY-NC-ND
    by Yabo Yang 
    Abstract: Using the PopBots toolbox, children can construct, design, experiment, and play with their very own social machine, all while learning basic AI concepts. However, children have not been taught whether to use or develop this modern technology. This article developed PopBots to assist children aged 4 to 7 in their education by integrating constructionist principles into an AI-based programme. Early childhood education is one area where the use of robotics (AI) in the classroom has recently garnered significant attention. The aim of the research was to explore how schools can better prepare their early childhood learners with AI-based intelligence learning programmes. The research findings demonstrated that AI technology can provide students with more personalised learning experiences and enhance the overall quality of education. This research contributes to the development of an intelligent teaching curriculum for university-level pre-kindergarten education majors.
    Keywords: artificial intelligence; technology; preschool education; virtual reality; knowledge-based system; supervised machine learning; SML.

  • Which people are loyal followers of influencers? An exploratory study   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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
  • A rapid elimination of communication signal interference in complex electromagnetic environment   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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.   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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   Order a copy of this article
    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
  • A data tamper-proof method of cloud computing platform based on blockchain   Order a copy of this article
    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
  • Analysing the Algerian social movement through Twitter   Order a copy of this article
    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
  • Improving college ideological and political education based on deep learning   Order a copy of this article
    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
  • Received signal strength-based power map generation in a 2-D obstructed wireless sensor network   Order a copy of this article
    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 testbed.
    Keywords: noisy channel; node deployment; power map; channel frequency; obstructed network.
    DOI: 10.1504/IJICT.2022.10046848
  • Study on detection of attacking nodes in power communication network based on non-parametric CUSUM algorithm   Order a copy of this article
    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 secret sharing scheme based on integer decomposition and hexagonal structure   Order a copy of this article
    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