In the rapidly evolving pharmaceutical industry, optimizing supply chain management is critical for enhancing efficiency and customer satisfaction. This research focuses on a data-driven approach to improving supply c...
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The prime focus of this Agro-Predictor system which relies on the key learnings of the Internet of Things and Deep Learning Approach, to benefit the agricultural sector, placing its undivided attention on critical are...
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One of themost prominent research areas in information technology is the Internet of Things (IoT) as its applications are widely used, such as structural monitoring, health care management systems, agriculture and bat...
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One of themost prominent research areas in information technology is the Internet of Things (IoT) as its applications are widely used, such as structural monitoring, health care management systems, agriculture and battlefield management, and so on. Due to its self-organizing network and simple installation of the network, the researchers have been attracted to pursue research in the various fields of IoTs. However, a huge amount of work has been addressed on various problems confronted by IoT. The nodes densely deploy over critical environments and those are operated on tiny batteries. Moreover, the replacement of dead batteries in the nodes is almost impractical. Therefore, the problem of energy preservation and maximization of IoT networks has become the most prominent research area. However, numerous state-of-The-Art algorithms have addressed this issue. Thus, it has become necessary to gather the information and send it to the base station in an optimized method to maximize the network. Therefore, in this article, we propose a novel quantum-informed ant colony optimization (ACO) routing algorithm with the efficient encoding scheme of cluster head selection and derivation of information heuristic factors. The algorithm has been tested by simulation for various network scenarios. The simulation results of the proposed algorithm show its efficacy over a few existing evolutionary algorithms using various performance metrics, such as residual energy of the network, network lifetime, and the number of live IoT nodes. Impact Statement-Toward IoT-based applications, here we presented the Quantum-inspired ACO clustering algorithm for network lifetime. IoT nodes in the clustering phase choose theirCH through the distance between cluster member IoT nodes and the residual energy. Thus, CH selection reduces the energy consumption of member IoT nodes. Therefore, our significant contributions are summarized as follows. i. Developing Quantum-informed ACO clustered routing algor
Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic pa...
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Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic patternmining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodicpatterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequencesis more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences isimportant. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To addressexisting problems, three new measures are defined: the utility, high support, and high-utility period sequenceratios. Further, a new upper bound, upSeqRa, and two new pruning properties were proposed. MHUPFPS usesa newly defined HUPFPS-list structure to significantly accelerate the reduction of the search space and improvethe overall performance of the algorithm. Furthermore, the proposed algorithmis evaluated using several *** experimental results indicate that the algorithm is accurate and effective in filtering several non-high-utilityperiodic frequent patterns.
The Internet of Things (IoT) has emerged as a promising technology for connecting physical objects and enabling communication between them. However, IoT faces several challenges such as security, privacy, and interope...
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The internet has become a part of every human ***,various devices that are connected through the internet are ***,the Industrial Internet of things(IIoT)is an evolutionary technology interconnecting various industries...
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The internet has become a part of every human ***,various devices that are connected through the internet are ***,the Industrial Internet of things(IIoT)is an evolutionary technology interconnecting various industries in digital platforms to facilitate their ***,IIoT is being used in various industrial fields such as logistics,manufacturing,metals and mining,gas and oil,transportation,aviation,and energy *** is mandatory that various industrial fields require highly reliable security and preventive measures against *** detection is defined as the detection in the network of security threats targeting privacy information and sensitive *** Detection Systems(IDS)have taken an important role in providing security in the field of computer *** of intrusion is completely based on the detection functions of the *** an IIoT network expands,it generates a huge volume of data that needs an IDS to detect intrusions and prevent network *** research works have been done for preventing network *** day,the challenges and risks associated with intrusion prevention are increasing while their solutions are not properly *** this regard,this paper proposes a training process and a wrapper-based feature selection With Direct Linear Discriminant Analysis LDA(WDLDA).The implemented WDLDA results in a rate of detection accuracy(DRA)of 97%and a false positive rate(FPR)of 11%using the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)dataset.
Addressing the global challenges of water resource depletion and efficient agricultural water management has led to the emergence of an innovative solution - the integration of Internet of Things (IoT) technology into...
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Breast cancer poses a significant global health challenge, affecting millions of women each year and leading to substantial cancer-related deaths. Early detection is crucial, particularly in regions with limited resou...
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With the rapid growth and adoption of web-based technologies, more and more service providers offer various services on the web. This can facilitate the organizations to develop business applications using web service...
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A comparative analysis of deep learning techniques for the prediction of genetic disease - cystic fibrosis. Cystic fibrosis (CF) is a complex genetic disorder that needs early and accurate diagnosis for effective trea...
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