A 'peer reviewed' journal indexed on Cabell's Directory, and also distributed by EBSCO and Proquest Database
It is a quarterly journal that publishes research papers on state-of-the-art Computing techniques and Encryption techniques; Computational problems; Artificial Intelligence; Cloud Computing; Databases; Algorithms and data structures; Cybernetics; Firewall techniques; Chip designing, Logic circuits and Software engineering; Programming techniques; Computer architecture; Neural networks, Machine Learning etc.
"It Is Going to Kill Us!" and Other Myths About the Future of Artificial Intelligence
When it comes to Artificial Intelligence (AI), myths are spreading faster than the technology itself is advancing. Left unchecked, they could inspire fears that undermine the technology's progress to the detriment of economic growth and social progress. AI is a branch of computer science that overlaps with other areas of study, including robotics, natural language processing, and computer vision. While AI has become commonplace, the public still has a poor understanding of the technology. As a result, a diverse cast of critics, driven by fear, opportunism or ignorance, has jumped into the intellectual vacuum to warn policymakers that, sooner than we think, AI will produce a parade of horribles. Indeed, these voices have grown so loud that their narratives may soon be accepted as truth. Needless to say, when AI is so demonized, there is a real risk that policymakers will seek to retard its progress. The truth is that AI systems are tools in the service of humans, and we can use them to make our lives vastly better. Given the promise that innovation in AI holds for economic growth and societal advancement, it is critical that policymakers actively support its further development and use. The paper provides a primer on AI and debunks five prevailing myths that, if accepted, threaten to slow or undermine its progress.
Detection of Intruder in Wireless Sensor Networks
Various attacks observed in Wireless Sensor Networks (WSNs) result in limiting or spoiling the ability of the networks in carrying out the expected work. WSNs have finite resources, can be deployable in uncontrollable environments and can be smoothly accessed by an intruder or rather attacker. When an attacker attacks a network layer, it can also affect the other layers. In suggested algorithm, local sensor action on many layers is supervised and evaluated to detect the possible attacker. A general approach of an anomaly-based Intrusion Detection System (IDS) is modified (mIDS). mIDS uses the OTP (One-Time Password) concept, which can find out the presence of the attacker inside the network. The results show that the suggested approach has better end-to-end delay, throughput and packet delivery ratio.
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