V. Sridhar¹, K.V. Ranga Rao², Saddam Hussain^3,*, Syed Sajid Ullah⁴, Roobaea Alroobaea⁵, Maha Abdelhaq⁶, Raed Alsaqour⁷

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1693-1708, 2023, DOI:10.32604/cmc.2023.028129

Abstract Nonorthogonal Multiple Access (NOMA) is incorporated into the wireless network systems to achieve better connectivity, spectral and energy effectiveness, higher data transfer rate, and also obtain the high quality of services (QoS). In order to improve throughput and minimum latency, a Multivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access (MRRWPBA-NOMA) technique is introduced for network communication. In the downlink transmission, each mobile device's resources and their characteristics like energy, bandwidth, and trust are measured. Followed by, the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different… More >

Xiaoyun Lu¹, Jiuying Dong^2,3,*, Hecheng Li¹, Shuping Wan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 881-907, 2022, DOI:10.32604/cmes.2022.020598

Abstract Based on the analyses of existing preference group decision-making (PGDM) methods with intuitionistic fuzzy preference relations (IFPRs), we present a new PGDM framework with incomplete IFPRs. A generalized multiplicative consistent for IFPRs is defined, and a mathematical programming model is constructed to supplement the missing values in incomplete IFPRs. Moreover, in this study, another mathematical programming model is constructed to improve the consistency level of unacceptably multiplicative consistent IFPRs. For group decisionmaking (GDM) with incomplete IFPRs, three reliable sources inuencing the weights of experts are identified. Subsequently, a method for determining the weights of experts is developed by simultaneously considering… More >

Ahmed M. Mostafa^*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4125-4142, 2022, DOI:10.32604/cmc.2022.024676

Abstract Many businesses have experienced difficulties in selecting a cloud service provider (CSP) due to the rapid advancement of cloud computing services and the proliferation of CSPs. Many independent criteria should be considered when evaluating the services provided by different CSPs. It is a case of multi-criteria decision-making (MCDM). This paper presents an integrated MCDM cloud service selection framework for determining the most appropriate service provider based on the best only method (BOM) and technique for order of preference by similarity to ideal solution (TOPSIS). To obtain the weights of criteria and the relative importance of CSPs based on each criterion,… More >

Wanni Xu^1,*, Huasen Xu², Xingyu Guo³

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1171-1192, 2022, DOI:10.32604/cmes.2022.017824

Abstract Color language has important meaning for children’s picture books. Understanding children’s preferences in terms of color language will be helpful when designers model computerized picture books in order to adapt to children’s visual senses and effectively stimulate children’s interest in reading. In this study, we aimed to further explore the general characteristics of children’s preference for colors, color depth and color matching forms in picture books. For the study, 256 children between the ages of three and six were selected and divided into four groups. According to the implementation needs of the children’s color preference test, these children were asked… More >

Mohanad Al-Ghobari¹, Amgad Muneer^2,*, Suliman Mohamed Fati³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1553-1570, 2021, DOI:10.32604/cmc.2021.016348

Abstract Many tourists who travel to explore different cultures and cities worldwide aim to find the best tourist sites, accommodation, and food according to their interests. This objective makes it harder for tourists to decide and plan where to go and what to do. Aside from hiring a local guide, an option which is beyond most travelers’ budgets, the majority of sojourners nowadays use mobile devices to search for or recommend interesting sites on the basis of user reviews. Therefore, this work utilizes the prevalent recommender systems and mobile app technologies to overcome this issue. Accordingly, this study proposes location-aware personalized… More >

Hai Yang Zhu^1,∗,†, Xiaobo Yin^1,∗,‡, Shunxiang Zhang^1,∗,§, Zhongliang Wei^1,¶, Guangli Zhu^1,II, Meng-Yen Hsieh^2,*,**

Computer Systems Science and Engineering, Vol.35, No.6, pp. 399-410, 2020, DOI:10.32604/csse.2020.35.399

Abstract A large number of new words in product reviews generated by mobile terminals are valuable indicators of the privacy preferences of customers. By clustering these privacy preferences, sufficient information can be collected to characterize users and provide a data basis for the research issues of privacy protection. The widespread use of mobile clients shortens the string length of the comment corpus generated by product reviews, resulting in a high repetition rate. Therefore, the effective and accurate recognition of new words is a problem that requires an urgent solution. Hence, in this paper, we propose a method for discovering new words… More >

Yi-Chih Hsieh¹, Peng-Sheng You^2,*

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 703-713, 2020, DOI:10.32604/iasc.2020.010104

Abstract In this study we present a generalized museum visitor routing problem considering the preferences and congestion of multiple groups with each group having its own must-see and select-see exhibition rooms based on their preferences in exhibits. The problem aims to minimize the makespan of all groups. An effective encoding scheme is proposed to simultaneously determine the scheduling of exhibition rooms for all groups and an immune-based algorithm (IBA) is developed. Numerical results, compared with those of a genetic algorithm and particle swarm optimization, on a museum in Taiwan are reported and discussed to show the performance of the IBA. More >

Mohammad Reza Ghotbi-Ravandi¹, Davoud Hassanvand², Sajad Zare^3,*, Milad Beytollahi⁴

Sound & Vibration, Vol.54, No.3, pp. 201-213, 2020, DOI:10.32604/sv.2020.08651

Abstract Undoubtedly, noise has become a major hazardous issue in today’s industrial world, with a lot of people suffering from exposure to excessive noise in their work environments. This study was conducted to weigh and prioritize noise control methods in an Iranian tire manufacturing complex in Iran. The Delphi method and the Technique for Order Preference by Similarity and an Ideal Solution (TOPSIS) were utilized for this purpose. This cross-sectional, descriptive study was conducted in the baking hall of an Iranian tire manufacturing factory in 2016. To weigh and prioritize noise control methods, Analytic Hierarchy Process (AHP) and TOPSIS were applied.… More >

Chunjing Xiao^1,∗, Yongwei Qiao², Kewen Xia¹, Yuxiang Zhang³

Computer Systems Science and Engineering, Vol.33, No.2, pp. 95-103, 2018, DOI:10.32604/csse.2018.33.095

Abstract Tourist routes recommendation is a way to improve the tourist experience and the efficiency of tourism companies. Session-based methods divide all users’ interaction histories into the same number sessions with fixed time window and treat the user preference as time sequences. There have few or even no interaction in some sessions for some users because of the high sparsity and temporal characteristics of tourist data. That lead to many session-based methods can not be applied to routes recommendation due to aggravate the sparsity. In order to better adapt and apply the characteristics of tourism data and alleviate the sparsity, a… More >

Qing Yang¹, Shengjie Zhou¹, Heyong Li¹, Jingwei Zhang^{2, 3, *}

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1691-1704, 2020, DOI:10.32604/cmc.2020.010256

Abstract Group recommendations derive from a phenomenon in which people tend to participate in activities together regardless of whether they are online or in reality, which creates real scenarios and promotes the development of group recommendation systems. Different from traditional personalized recommendation methods, which are concerned only with the accuracy of recommendations for individuals, group recommendation is expected to balance the needs of multiple users. Building a proper model for a group of users to improve the quality of a recommended list and to achieve a better recommendation has become a large challenge for group recommendation applications. Existing studies often focus… More >