Tsu-Yang Wu¹, Qian Meng¹, Lei Yang¹, Saru Kumari², Matin Pirouz^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 317-341, 2023, DOI:10.32604/cmes.2022.019595 - 24 August 2022

Abstract The development of the Internet of Things has facilitated the rapid development of various industries. With the improvement in people’s living standards, people’s health requirements are steadily improving. However, owing to the scarcity of medical and health care resources in some areas, the demand for remote surgery has gradually increased. In this paper, we investigate remote surgery in the healthcare environment. Surgeons can operate robotic arms to perform remote surgery for patients, which substantially facilitates successful surgeries and saves lives. Recently, Kamil et al. proposed a secure protocol for surgery in the healthcare environment. However, More >

Saima Kanwal¹, Feng Tao^1,*, Ahmad Almogren², Ateeq Ur Rehman³, Rizwan Taj¹, Ayman Radwan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 201-219, 2023, DOI:10.32604/cmes.2022.020255 - 24 August 2022

Abstract The authenticity and integrity of healthcare is the primary objective. Numerous reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection. A trade-off between robustness, imperceptibility, and embedded capacity is difficult to achieve with current algorithms due to limitations in their ability. Keeping this purpose insight, an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern. A key is generated by a… More >

C. Santhosh Kumar¹, K. Vishnu Kumar^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2893-2907, 2023, DOI:10.32604/iasc.2023.029669 - 17 August 2022

Abstract Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare system. Online patient data processing from remote places may lead to severe privacy problems. Moreover, the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to offloading of live patient data to remote cloud servers. Solve the privacy problem. The proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption schemes. It can help maintain the privacy preservation and confidentiality of patients’ medical data during diagnosis of Parkinson’s disease. In addition, the energy More >

Zhengshu Zhou^*, Yutaka Matsubara, Hiroaki Takada

Computer Systems Science and Engineering, Vol.45, No.1, pp. 35-50, 2023, DOI:10.32604/csse.2023.030848 - 16 August 2022

Abstract Since entering the era of Industry 4.0, the concept of Healthcare 4.0 has also been put forward and explored by researchers. How to use Information Technology (IT) to better serve people’s healthcare is one of the most featured emerging directions in the academic circle. An important field of Healthcare 4.0 research is the reliability engineering of healthcare service. Because healthcare systems often affect the health and even life of their users, developers must be very cautious in the design, development, and operation of these healthcare systems and services. The problems to be solved include the More >

Mariem Belhor^1,2,3, Adnen El-Amraoui^1,*, Abderrazak Jemai², François Delmotte¹

Computer Systems Science and Engineering, Vol.45, No.1, pp. 1-19, 2023, DOI:10.32604/csse.2023.029058 - 16 August 2022

Abstract This research focuses on the home health care optimization problem that involves staff routing and scheduling problems. The considered problem is an extension of multiple travelling salesman problem. It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon. Thus, a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint. Nevertheless, when the time horizon become large, practical-sized instances become very difficult to More >

S. Siamala Devi¹, K. Venkatachalam², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1869-1880, 2023, DOI:10.32604/csse.2023.025505 - 01 August 2022

Abstract The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using… More >

D. Doreen Hephzibah Miriam¹, Deepak Dahiya², Nitin³, C. R. Rene Robin^4,*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1889-1906, 2023, DOI:10.32604/iasc.2023.028850 - 19 July 2022

Abstract Blockchain technology is critical in cyber security. The most recent cryptographic strategies may be hacked as efforts are made to build massive electronic circuits. Because of the ethical and legal implications of a patient’s medical data, cyber security is a critical and challenging problem in healthcare. The image secrecy is highly vulnerable to various types of attacks. As a result, designing a cyber security model for healthcare applications necessitates extra caution in terms of data protection. To resolve this issue, this paper proposes a Lionized Golden Eagle based Homomorphic Elapid Security (LGE-HES) algorithm for the… More >

Nithya Rekha Sivakumar^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2383-2398, 2023, DOI:10.32604/iasc.2023.028574 - 19 July 2022

Abstract Internet of things (IoT) has brought a greater transformation in healthcare sector thereby improving patient care, minimizing treatment costs. The present method employs classical mechanisms for extracting features and a regression model for prediction. These methods have failed to consider the pollution aspects involved during COVID 19 prediction. Utilizing Ensemble Deep Learning and Framingham Feature Extraction (FFE) techniques, a smart healthcare system is introduced for COVID-19 pandemic disease diagnosis. The Collected feature or data via predictive mechanisms to form pollution maps. Those maps are used to implement real-time countermeasures, such as storing the extracted data… More >

Farzana Kausar Gondal^1,*, Syed Khuram Shahzad², Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1369-1386, 2023, DOI:10.32604/iasc.2023.028407 - 19 July 2022

Abstract Cities are facing challenges of high rise in population number and consequently need to be equipped with latest smart services to provide luxuries of life to its residents. Smart integrated solutions are also a need to deal with the social and environmental challenges, caused by increasing urbanization. Currently, the development of smart services’ integrated network, within a city, is facing the barriers including; less efficient collection and sharing of data, along with inadequate collaboration of software and hardware. Aiming to resolve these issues, this paper recommended a solution for a synchronous functionality in the smart… More >

K. Saranya^*, K. Premalatha

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2029-2042, 2023, DOI:10.32604/iasc.2023.027949 - 19 July 2022

Abstract Medical data mining has become an essential task in healthcare sector to secure the personal and medical data of patients using privacy policy. In this background, several authentication and accessibility issues emerge with an intention to protect the sensitive details of the patients over getting published in open domain. To solve this problem, Multi Attribute Case based Privacy Preservation (MACPP) technique is proposed in this study to enhance the security of privacy-preserving data. Private information can be any attribute information which is categorized as sensitive logs in a patient’s records. The semantic relation between transactional More >