International Journal of Information and Communication Technology (12 papers in press)

Regular Issues

• Open Access

  Application of image colour matching algorithm based on visual perception model in clothing design ( Free Full-text Access )

  by Wenzhe Hu, Yuan Zhang 
  Abstract: This study examines an image colour matching algorithm based on visual perception models, utilising the interactive genetic algorithm (IGA) to improve colour exploration in fashion design. The algorithm’s performance was evaluated across various scenarios, focusing on colour matching accuracy, perceptual quality, and computational efficiency. Results show an average accuracy of 87.5% and a perceptual quality score of 4.2 on a Likert scale. The algorithm operates with an average execution time of 0.25 seconds per design image, demonstrating efficient performance. These findings highlight the algorithm’s potential to enhance creativity and streamline workflows in clothing design. While promising, further research is needed to refine the algorithm and expand its applications in the fashion industry, offering designers a more reliable and precise tool for their work.
  Keywords: image colour matching; visual perception models; clothing design; interactive genetic algorithm; IGA; computational intelligence.
  
  

• Open Access

  Method of target damage probability distribution simulation and evaluation based on GPU parallel computing ( Free Full-text Access )

  by Xiaoyun Lei, Yaping Tan, Lihua Zhu 
  Abstract: For the projectiles with proximity-fused warheads used to destroy the target, the most vulnerable information is vital to destroy targets efficiently. So, it is important to quickly locate the most vulnerable position of the target in combat. An algorithm combining GPU parallel computing and numerical simulation is proposed. For a specific target, a slicing processing method is used to define the spatial position parameters, and the damage probability distribution in the space near the target is established to determine the most vulnerable position. In the example, the computation speed of the method is about 3.6 times higher than that of the CPU serial calculation method. It could quickly locate the most vulnerable position of a certain ballistic missile, namely, when the projectile was situated in the plane of 1/5 projectile length from the bottom of the target, the target would be damaged with the highest probability of 90%.
  Keywords: damage probability; vulnerable position; GPU parallel computing; numerical simulation.
  
  

• Open Access

  Edge detection algorithm of insulator hydrophobic image in CPS system considering deconvolution and deblurring algorithm ( Free Full-text Access )

  by Junchao Wei 
  Abstract: Through experiments, this paper verifies the practicability and effectiveness of the deconvolution deblurring algorithm. Through fuzzy kernel estimation and sharp edge recovery, we have effectively improved the defects of traditional edge detection algorithms, which also solve the clear hydrophobic image under CPS. The experimental data show that, compared with the traditional edge detection algorithm, the comprehensive PSNR value of the edge detection algorithm of insulator hydrophobic image based on deconvolution and deblurring algorithm in CPS environment is 27.02, and the improvement range is about 0.3 dB to 1.9 dB. In terms of operation time, the average operation time of this algorithm is reduced by about two-thirds. Therefore, the following conclusions are drawn in this paper. The edge detection accuracy of insulator hydrophobic image considering deconvolution deblurring algorithm is very high, and the convergence performance is also very good.
  Keywords: image edge detection algorithm; deconvolution deblurring algorithm; insulator water repellency; image processing; CPS.
  
  

• Open Access

  Optimisation of news propagation path in media convergence era under interactive digital media technology ( Free Full-text Access )

  by Yizhou Gong, Zhihu Shi 
  Abstract: With the development of digital media technology, data sharing has become the main theme of the new media era of big data, so the news industry is facing new opportunities and challenges. As a new form of data news, the transmission path of data news is very important to its transmission effect. By the news propagation path as the research object, from the theoretical level discusses the communication content, the influence of the platform and digital news propagation path the main body, on the basis of social network analysis and the theory of the virus, analyses the related data of representative, studied three kinds of the difference of the path, find the data of news communication path mainly includes three types: the communication effect is affected by communication platform, communication node, news nature, external interference factors and so on. In the production and dissemination of data news using various operating platforms, attention should be paid to strengthening technology construction, maintaining user relations and paying fees.
  Keywords: adaptive recommendation system; multi-media information environment; data analysis.
  
  

• Open Access

  Chaotic colour image encryption based on differential evolutionary deep learning ( Free Full-text Access )

  by Zhengbao Cai 
  Abstract: Traditional chaotic image encryption methods have certain limitations in terms of processing high-dimensional data, computational complexity and attack resistance, which limits their widespread promotion and use in practical applications. To solve these problems, this paper proposes a chaotic colour image encryption method based on differential evolutionary deep learning. Firstly, the security and stability of the image encryption algorithm is enhanced by introducing a six-dimensional cellular neural network (CNN). Secondly, the parameters of the six-dimensional CNN are optimised using differential evolutionary algorithms to improve the complexity and randomness of the chaotic sequences. The experimental results show that compared with the traditional CNN, AES and Chaotic Encryption Algorithm, this paper's method shows significant improvement in NPCR and UACI indicators.
  Keywords: chaotic image encryption; differential evolutionary algorithm; six-dimensional cellular neural network; CNN; NPCR; unified average changing intensity; UACI.
  
  
• 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
   
  
• A new fast DBSCAN using dual-space analysis and colour integral volume for document image segmentation  
  by Zakia Kezzoula, Djamel Gaceb 
  Abstract: The segmentation of the colour document images is an essential step allowing facilitating and improving the stages of characterisation and interpretation of the information contained in these documents. Recent systems of automatic processing and recognition of document images, which use separation of colouremric layers, are more efficient compared to conventional systems, only based on binary or grey levels images. This task requires non-supervised pixel segmentation or clustering techniques to separate the document image to a variable and unknown number of colour layers. The methods based on density are widely used in this context at pixel level, such as the DBSCAN method and its different variants, very robust to the noise and more adapted to the degradations present on document images, but who suffer from a great complexity. In this context, we propose a new faster DBSCAN variant using the volume integral in colourimitric space for the first time to significantly reduce calculation time. The combination of the two spaces, Cartesian and colorimetric has also accelerated the method and improved its performance on document images with different challenges. The results obtained show the effectiveness of the proposed approach, which was marked by significant improvement in the quality of segmentation and reduction in computed time.
  Keywords: clustering; DBSCAN; region growing; document image segmentation; fast I2SDBSCAN; 3D colour histogram; integral volume.
  DOI: 10.1504/IJICT.2024.10065387
   
  
• 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
   
  
• Keyword extraction method based on complex network  
  by Zhen Yang, Huajian Gong, Weiyun Ma, Chunlin Yin, Jie Li, Siyang Liu, Hua Zhu, Na Zhao 
  Abstract: Keyword extraction has a wide range of applications in the field of natural language processing. Many research results on keyword extraction at present. Among them, keyword extraction methods are based on complex networks do not require a lot of data training in advance and are simple to implement. This paper analyses and realises the application of complex network theory in the Chinese news keyword extraction task. We collected and analysed 2,061 news texts from Sina website as experimental data, and found that the number of keywords extracted affected the performance of keyword extraction method. We also compared the performance of our algorithm with other keyword extraction algorithms. The experiments verify the accuracy and effectiveness of complex networks in keyword extraction of Chinese news texts. Based on PyQt and TextRank, a news text keyword analysis platform is constructed to realise the visualisation of text network and the extraction of Chinese news keywords.
  Keywords: complex network; keyword extraction; text network; TextRank.
  DOI: 10.1504/IJICT.2024.10066685
   
  
• 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
   
  
• GSKTM: efficient of query search for spatial keyword in text mining  
  by Ramya Rayacherlu Sambasadasiva Reddy, 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 researcher's 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.
  DOI: 10.1504/IJICT.2024.10066679
   
  
• 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