Shuying Xu¹, Chin-Chen Chang¹, Ji-Hwei Horng^2,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 721-739, 2023, DOI:10.32604/csse.2023.026046

Abstract Hiding secret data in digital images is one of the major research fields in information security. Recently, reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services. This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique (OMTBL-RDHEI). In our scheme, the content owner encrypts the cover image with block permutation, pixel permutation, and stream cipher, which preserve the in-block correlation of pixel values. After uploading to the cloud service, the data hider applies the prediction error rearrangement (PER), the optimal threshold selection… More >

Nguyen Tu Trung^1,*, Tran Thi Ngan¹, Tran Manh Tuan¹, To Huu Nguyen²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 535-544, 2023, DOI:10.32604/csse.2023.026011

Abstract Fusing medical images is a topic of interest in processing medical images. This is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis accuracy. This fusion aims to improve the image quality and preserve the specific features. The methods of medical image fusion generally use knowledge in many different fields such as clinical medicine, computer vision, digital imaging, machine learning, pattern recognition to fuse different medical images. There are two main approaches in fusing image, including spatial domain approach and transform domain approachs. This paper proposes a new algorithm to fusion multimodal images.… More >

Son-Lam VU, Quang-Hung LE^*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 471-483, 2023, DOI:10.32604/csse.2023.025897

Abstract Recommender systems are similar to an information filtering system that helps identify items that best satisfy the users’ demands based on their preference profiles. Context-aware recommender systems (CARSs) and multi-criteria recommender systems (MCRSs) are extensions of traditional recommender systems. CARSs have integrated additional contextual information such as time, place, and so on for providing better recommendations. However, the majority of CARSs use ratings as a unique criterion for building communities. Meanwhile, MCRSs utilize user preferences in multiple criteria to better generate recommendations. Up to now, how to exploit context in MCRSs is still an open issue. This paper proposes a… More >

Moeiz Miraoui^1,2,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799

Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the door for visitors after their… More >

Fawaz Alassery¹, Ahmed Alzahrani², Asif Irshad Khan², Kanika Sharma³, Masood Ahmad⁴, Raees Ahmad Khan^4,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 859-872, 2023, DOI:10.32604/csse.2023.025796

Abstract In recent years, it has been observed that the disclosure of information increases the risk of terrorism. Without restricting the accessibility of information, providing security is difficult. So, there is a demand for time to fill the gap between security and accessibility of information. In fact, security tools should be usable for improving the security as well as the accessibility of information. Though security and accessibility are not directly influenced, some of their factors are indirectly influenced by each other. Attributes play an important role in bridging the gap between security and accessibility. In this paper, we identify the key… More >

Moonseong Kim¹, Woochan Lee^2,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 663-675, 2023, DOI:10.32604/csse.2023.025615

Abstract The occurrence of ‘sensing holes’ not only hinders seamless data collection but also leads to misinterpretation of information in certain areas under extensive data analysis. In order to overcome this, various sensor relocation strategies have been proposed, but the existing relocation strategies revealed problems such as the ping-pong, shaded area, network disconnection, etc. This paper conducted research on relocation protocols in a distributed environment that is very suitable for real-world situations and efficiently recovering the problem of sensing holes. First, a simulation was performed on the distribution of the shaded area for data collection, which is a problem with the… More >

D. Banumathy^1,*, Osamah Ibrahim Khalaf², Carlos Andrés Tavera Romero³, P. Vishnu Raja⁴, Dilip Kumar Sharma⁵

Computer Systems Science and Engineering, Vol.44, No.1, pp. 595-612, 2023, DOI:10.32604/csse.2023.025611

Abstract The most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient for the early identification of… More >

M. Geetha^1,*, R. Vijayabhasker², Suresh Seetharaman¹

Computer Systems Science and Engineering, Vol.44, No.1, pp. 813-832, 2023, DOI:10.32604/csse.2023.025575

Abstract A basic 7-level MLI topology is developed and the same is extended to the 9-level then further increased to 17-levels. The developed structure minimizes the component’s count and size to draw out the system economy. Despite the various advantages of MLIs, efficiency and reliability play a major role since the usage of components is higher for getting a low Total Harmonics Distortion (THD) value. This becomes a major challenge incorporated in boosting the efficiency without affecting the THD value. Various parametric observations are done and realized for the designed 9-level and 17-level MLI, being the Total Standing Voltage (TSV), efficiency,… More >

Muhammad Shahzeb Ali¹, Ali Alqahtani^2,*, Ansar Munir Shah¹, Adel Rajab², Mahmood Ul Hassan³, Asadullah Shaikh², Khairan Rajab², Basit Shahzad⁴

Computer Systems Science and Engineering, Vol.44, No.1, pp. 845-858, 2023, DOI:10.32604/csse.2023.025449

Abstract Throughout the use of the small battery-operated sensor nodes encourage us to develop an energy-efficient routing protocol for wireless sensor networks (WSNs). The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN. Many routing protocols are available, but the issue is still alive. Clustering is one of the most important techniques in the existing routing protocols. In the clustering-based model, the important thing is the selection of the cluster heads. In this paper, we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining… More >

M. Manikandakumar^1,*, P. Karthikeyan²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 913-927, 2023, DOI:10.32604/csse.2023.025434

Abstract Weed is a plant that grows along with nearly all field crops, including rice, wheat, cotton, millets and sugar cane, affecting crop yield and quality. Classification and accurate identification of all types of weeds is a challenging task for farmers in earlier stage of crop growth because of similarity. To address this issue, an efficient weed classification model is proposed with the Deep Convolutional Neural Network (CNN) that implements automatic feature extraction and performs complex feature learning for image classification. Throughout this work, weed images were trained using the proposed CNN model with evolutionary computing approach to classify the weeds… More >