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Fundamentals of Internet of Things
Published in Bhawana Rudra, Anshul Verma, Shekhar Verma, Bhanu Shrestha, Futuristic Research Trends and Applications of Internet of Things, 2022
Sarthak Srivastava, Anshul Verma, Pradeepika Verma
Vision of Mark Weiser: Mark D. Weiser, a very well-known computer scientist and chief technology officer (CTO) at Xerox PARC, California, is also one the greatest visionaries of the interlinked physical world and considered to be the father of ubiquitous computing (coined the term in 1988) [16], which actually is a type of computing that can be done by any device, anywhere, anytime, and in any format and includes all the paradigms of what we call today IoT. Weiser, in 1991, in his essay [17] ‘The Computer for the 21st Century’, expressed his vision of an interconnected and computerized physical world which was going to be proven so helpful for mankind in its work in a self-effacing way, where the common computationally augmented artifact would interact almost naturally with our senses and spoken words and the most remarkable thing would be their meddlesomeness for users.
Smart Healthcare in Smart Cities
Published in Lavanya Sharma, Towards Smart World, 2020
Smart city enhancements become the largest global challenge. Growing requests for pervasive and personalized healthcare with diminished risks and price require mobile cloud computing to fulfill the healthcare requests by providing fast analyses of patients' data. Ubiquitous healthcare firm, Ube Health, has the most advanced approach to s-healthcare, including advanced data processing, machine learning, big data, high-performance computing (HPC), and IoT. They serve to optimize network circulation, which consecutively over cloudlet and net sheets adjusts data speeds and storing, and daily outcomes. Advancements in s-healthcare ICT—cloud computing, IoT, broadcasting communications, WSN, WBAN, big data, robotics, artificial intelligence, and 4G/5G networks—has a significant impact in the advancement of healthcare because these techniques can provide anywhere, anytime connectivity, initiating the new generation of healthcare paradigms and services [43–48].
Implications of World Mega Trends for MCDM Research
Published in Sarah Ben Amor, Adiel Teixeira de Almeida, João Luís de Miranda, Emel Aktas, Advanced Studies in Multi-Criteria Decision Making, 2019
Hannele Wallenius, Jyrki Wallenius
The envisioned changes will bring about (1) digital connectivity, independent of time and place, and (2) tools for quickly analyzing vast amounts of digital data. In the World Economic Forum’s report, the changes are grouped into six “mega-trends.” We borrow freely from the report. The Internet—world’s access to the Internet will continue improving; people’s interaction with it will become more ubiquitousFurther enhancements in computing power, communications technologies, and data storage, and the ability to interface with digital technology, anytime using multiple devicesThe “Internet of Things”Big data and Artificial Intelligence (AI)—the ability to access and analyze huge amounts of data; coupled with the “ability” of computers to make decisions based on this dataThe sharing (or platform) economy and distributed trust (based on, for example, the block chain technology)3D-printing
An exact approach for the constrained two-dimensional guillotine cutting problem with defects
Published in International Journal of Production Research, 2023
Hao Zhang, Shaowen Yao, Qiang Liu, Lijun Wei, Libin Lin, Jiewu Leng
Several papers discuss other cutting problems with defects, and the number of papers has increased recently. Neidlein, Scholz, and Wäscher (2016) introduced a problem generator for the two-dimensional rectangular single large object placement problem with defects. Durak and Tuzun Aksu (2017) suggested the online glass cutting problem with defects and proposed dynamic programming and mixed-integer programming-based online algorithms. Recently, Parreño, Alonso, and Alvarez-Valdes (2020) studied the glass cutting problem with defects by Saint Gobain for the 2018 ROADEF challenge and developed a beam search algorithm. The same problem has been studied by Libralesso and Fontan (2021) and an anytime tree search algorithm was introduced to solve this problem. Goncalves and Wäscher (2020) addressed the two-dimensional non-guillotine cutting problem with defects and proposed a MIP model and a biased random-key genetic algorithm. Martin, Morabito, and Munari (2022) addressed the two-stage and one-group two-dimensional guillotine cutting problems with defects and proposed a constraint programming-based algorithm as well as integer linear programming formulations.
An adaptive patch approximation algorithm for bicriteria convex mixed-integer problems
Published in Optimization, 2022
In this paper, we develop an algorithm which is designed contrarily to the above characteristics. We pose the following goals to achieve with our method: The approximation returned by the algorithm in each step should be an inner approximation, i.e. all points in the approximation should correspond to feasible solutions that can be directly computed.The algorithm should provide an approximation of the Pareto frontier with a clearly quantified approximation guarantee at every step. In particular, the algorithm can be stopped at every moment and we still obtain a result with a clear approximation guarantee, i.e. the algorithm should be an anytime algorithm [25]. The approximation quality obtained until each given time limit should be competitive with every other algorithm that requires a similar amount of time.The approximation quality obtained by the algorithm, respectively, the needed number of iterations to reach some given accuracy, should be bounded with respect to some intrinsic property of the problem we solve. In particular, the performance of the algorithm should be not too far away from a theoretical optimum that is given by the number of patches minimally needed to describe an approximation to the Pareto frontier.
Anytime clustering of data streams while handling noise and concept drift
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2022
Jagat Sesh Challa, Poonam Goyal, Ajinkya Kokandakar, Dhananjay Mantri, Pranet Verma, Sundar Balasubramaniam, Navneet Goyal
To address this issue, anytime stream clustering algorithms were proposed, which perform anytime online maintenance of micro-clusters for streams that have varying inter-arrival rate of objects. They can handle objects arriving at any stream speed, deliver a result at any given point in time, and use more time if available, to refine the result to the highest possible degree. Figure 1 depicts the characteristic of an anytime algorithm where the accuracy of the result improves with increase in time allowance. Only a few anytime stream clustering algorithms exist in literature, which include ClusTree (Kranen et al., 2011), LiarTree (Hassani et al., 2011) and SubClusTree (Hassani et al., 2014). However, there are a few drawbacks associated with them. ClusTree’s (Kranen et al., 2011) algorithm for insertion of incoming objects, uses distance computations performed from each object to the mean of the existing micro-clusters, which leads to a reduction in overall purity of the micro-clusters indexed especially for high dimensional data. Moreover, ClusTree does not handle noise and concept drift. LiarTree (Hassani et al., 2011) is a variation of ClusTree that handles noise & concept drift. However, its method builds new sub-trees for each noise-to-concept transition, which distorts spatial locality and thus hampers purity of the micro-clusters produced. SubClusTree is an extension of ClusTree for anytime subspace clustering. Also, all of the above are proposed for single-port data streams only.