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                <text>The need for vigorous security methods becomes a great concern as container-based virtualization continues to gain close attention in modern edge computing environments. This study proposed a novel hybrid security algorithm designed specifically for containerized virtualization technology, leveraging the distinctive capabilities of Residue Number Systems (RNS). The proposed algorithm integrates the strengths of the bits permutation technique with the efficiency and parallelism inherent in RNS to enhance data security in containerized systems. The proposed algorithm combines RNS-based encryption and decryption processes with the bits permutation technique to form an adaptable security scheme. This proposed hybrid technique leverages an RNS's ability to perform modular arithmetic operations in parallel, offering data protection against certain attacks. The proposed security algorithm unlike the risk …</text>
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                <text>In Wireless Sensor Networks (WSNs), an efficient clustering technique is critical in optimizing the energy level of networked sensors and prolonging the network lifetime. While the traditional bee colony optimization technique has been widely used as a clustering technique in WSN, it mostly suffers from energy efficiency and network performance. This study proposes a Bee Colony Optimization that synergistically combines K-mean algorithms (referred to as K-BCO) for efficient clustering in heterogeneous sensor networks. This is to develop a robust and efficient clustering algorithm that addresses the challenges of energy consumption and network performance in WSNs. The K-BCO algorithm outperformed comparative clustering algorithms such as H-LEACH, DBCP, and ABC-ACO in average error rate (AER), average data delivery rate (ADDR), and average energy consumption (AEC) for transmitting data packets from sensors to cluster heads. The K-BCO outperformed other algorithms in terms of ADDR at 95.00% against H-LEACH (75.86%), DBCP (72.07%) and ABC-ACO (90.08%). The findings indicate that the K-BCO not only optimizes energy consumption but also guarantees more stable and robust solutions, thereby extending the network lifetime of WSNs. Thus, K-BCO is recommended to practitioners in wireless sensor networks as it paves the way for more efficient and sustainable wireless communication.</text>
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                <text>Improved Residue Number System Reverse Conversion Algorithm for [[Equation]] Three Moduli Set Implementation in Sensor Networks</text>
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                <text>PRINCE MODEY, Gaddafi Adbdul-Salaam, Alimatu Sadia Shirazu, Mohammad Hossein Anisi, Emmanuel Freeman</text>
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                <text>Residue Number System (RNS) is a number system providing borrow-free subtraction, carry-free addition, parallel operations, and one-step multiplication. These capabilities make RNS applications in Digital Signal Processing and Wireless Networks a good choice. Although RNS has proven to solve the problem of carry propagation in binary number systems, it has the problem of reverse conversion, which limits its implementation in digital systems likewise sensor nodes. In this paper, we proposed an RNS reverse converter based on the moduli set {[[EQUATION]]} and the residue number [[EQUATION]]. The proposed scheme re-grouped the moduli set into two sub-moduli sets with their corresponding residue representations. The proposed method in this study requires [[EQUATION]] bit hardware resources for its implementation and also imposed [[EQUATION]] delay in its performance. The proposed RNS reverse converter needs lesser hardware resources for its implementation compared to other state of the art, making it suitable for hardware implementation in sensor networks. The proposed scheme demonstrates reliable and secure data transmission in Wireless Sensor Networks (WSNs) by using the RRNS QC encoder/decoder scheme.</text>
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                <text>STRATEGIC COLLABORATIONSATATECHNOLOGY RESEARCH AND INNOVATION CENTRE IN GHANA</text>
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                <text>Nearly five years ago, the Ghana Technology University College (GTUC) responded to a call for proposals by the Council for Technical and Vocational Education and Training (COTVET) and the Ministry of Environment, Science, Technology and Innovation (MESTI) under Component 2 of the Ghana Skills and Technology Development Project (GSTDP). Funding received was used in the establishment of the Technology Research and Innovation Centre (TRIC) for technology and market-oriented research with an overarching goal of transferring technology to the public and industry. Ghana Technology University College is committed to bridging the gap between academia and industry, and the establishment of TRIC transformed this vision into reality. Nine projects were selected from presentations made at workshops by researchers from our academic faculties (ie, Faculty of Computing and Information Systems, Faculty of IT Business and Faculty of Engineering) in collaboration with their private industry partners. Thus, the implementation of the projects entailed cross-institutional collaborations between GTUC, COTVET and MESTI with the involvement of the private sector. This paper discusses the processes and outcomes of the implementation of the TRIC projects with recommendations for the sustainability of TRIC.</text>
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