Abhilash Kancharla

This computational study investigates dynamic self-healing processes in nanomaterials driven by neuronal spike activity. We developed a multiscale simulation framework that integrates neuronal dynamics, quantum mechanical effects, and material science principles. Our model incorporates a time-dependent neuron spike voltage equation coupled with a nanomaterial health update function, including quantum probability terms, to capture nanoscale effects. We employ reliability engineering concepts to assess system performance. Simulations reveal that neuronal spike patterns significantly influence self-healing dynamics, exhibiting non-linear behavior with quantum effects crucial to healing efficiency. Statistical analysis demonstrates a strong correlation between spike frequency and healing rate, identifying an optimal range for maximum recovery. Integrating quantum probabilities yields more accurate nanoscale behavior predictions than classical approaches alone. This study provides a foundation for understanding and optimizing neuronal spike-induced recovery in nanomaterials with potential applications in neural interfaces, intelligent materials, and biomedical devices.

This study investigates the integration of quantum computing, classical methods, and deep learning techniques for enhanced image processing in dynamic 6G networks, while also addressing essential aspects of copyright technology and detection. Our findings indicate that quantum methods excel in rapid edge detection and feature extraction but encounter difficulties in maintaining image quality compared to classical approaches. In contrast, classical methods preserve higher image fidelity but struggle to satisfy the real-time processing requirements of 6G applications. Deep learning techniques, particularly CNNs, demonstrate potential in complex image analysis tasks but demand substantial computational resources. To promote the ethical use of AI-generated images, we introduce copyright detection mechanisms that employ advanced algorithms to identify potential infringements in generated content. This integration improves adherence to intellectual property rights and legal standards, supporting the responsible implementation of image processing technologies. We suggest that the future of image processing in 6G networks resides in hybrid systems that effectively utilize the strengths of each approach while incorporating robust copyright detection capabilities. These insights contribute to the development of efficient, high-performance image processing systems in next-generation networks, highlighting the promise of integrated quantum-classical–classical deep learning architectures within 6G environments.

This paper proposes a quantitative model for a new blockchain technology that distributes public ledger in a decentralized manner, referred to as Distributed Decentralized chain (DDC). A clique of k nodes in the P2P network participates in storing a complete copy of blockchain instead of having every node carry an entire copy. The proposed model is k-Queue Variable Bulk Arrival and Static Bulk Service queueing model (k-VBASBS), in which the state is defined by (i,k), where i is the number of slots from 0 upto n in a block on the current node, and k is the number of distributed nodes to store a complete copy of a chain of blocks. Without loss of generality and practicality, it is assumed that there are two different transaction posting rates assumed to take into account the overhead of inter-node (i.e., μ(inter-node)) control-hopping versus the one of the original intra-node posting rate (i.e., μ(intra-node)), and μ(inter-node)μ<<(intra-node). Based on the proposed k-VBASBS model, the average waiting time, space requirement, and throughput of the transactions will be simulated for the performance, and the dependability will be also modeled and simulated by the vulnerability to 51% attack.

This paper proposes a new hybrid chain, and a double-tuple variable bulk arrival and static bulk service (VBASBS) model to assess its performance. The proposed hybrid chain consists of a permissioned chain (e.g. Hyperledger) and a permission-less chain (e.g., Ethereum) with the double-tuple VBASBS-type queues, one per each chain, respectively. The hybrid chain may be realized in two different approaches such that API-API approach coordinates the context switching across hybrid chains through a script as an API to the API's to hybrid chains sitting on a central server; or CHAIN-API through an independent chain as an interface to the API's to hybrid chains. The proposed double-tuple model is built based on the top of single-tuple model such that the single-tuple model is extended to a double-tuple to address the two chains into account in a Markovian manner, through which the effectiveness, efficiency and versatility of the VBASBS model will be demonstrated in this paper. A few performances, such as the transaction execution time and the block spatial requirement, will be analyzed under various assumptions on the transaction arrival and service (i.e., block posting process) through extensive numerical methods on Matlab. The expected benefits of the proposed hybrid chain are: an inter-operability across hybrid chains, a seamless and thereby sustained crypto-trust, and ultimately an open chain, to mention a few. A crypto payment system using HTML as a frontend is developed as a testbed to demonstrate the effectiveness and efficiency of the proposed hybrid chain.

The slim chain is proposed in this paper in an effort to address and resolve the scalability issue of blockchain-based crypto computing by managing the volume of the blockchain itself. An adequate balancing of computation across on/off-chain is expected to relieve the spatial and temporal overhead of managing the otherwise exponentially growing size of the blockchain by making the blockchain slimmer as much as the volume migrated and kept off-chain than the conventional, as referred to as a slim chain in this paper. As an initial design, a novel theoretical model is proposed to assure the efficacy of the proposed slim chain with specific respect to the dependability from a single transaction's standpoint in a stochastic manner. It is demonstrated that the dependability can be traced with respect to whether the transaction of concern is to write off the chain or read back from off the chain to on-chain, as the transactions writing off the chain are more dependable than reading from off the chain without loss of practicality, as well as the crypto rate and the IPFS rate as IPFS (Inter-Planetary File System) is an off-chain storage considered in this research.

This paper proposes a novel embedded Markovian queueing model of the M(1,n)/Mn/1 type in order to establish a theoretical foundation to design a blockchain-based system with specific interest in Ethereum. The model assumes variable bulk arrivals of transactions in Poisson distribution, i.e., M(1,n), where n the number of slots across all the mined transactions and static bulk service of transactions in exponential time, i.e., Mn, for posting in the current block, namely, VBASBP. The primary performance measurements to be taken are the average number of slots no matter how many transactions are mined under the assumption of the maximum number of slots per block as specified by n; the average waiting time per slot; and the throughput in terms of the average number of slots to be processed per time. The variable bulk arrival rate is assumed to vary linearly proportional to the size of the transactions in a multiple of per slot, and the static bulk service is assumed to take place when the number of slots in the mined transactions reaches at n, i.e., a bulk processing of multiple transactions in multiple slots for posting in a block. Numerical simulations are conducted on Matlab to demonstrate the efficacy of the model.

The hybrid chain is proposed in this paper to investigate on a new blockchain network that is to be built across private and main nets, namely, a hybrid chain. Note that the hybrid chain is distinguished from the on/off-balanced chain such that the hybrid chain is across two different (e.g., Hypercubes private net vs. Ethereum main net) while the on/off-balanced chain across on-chain and off-chain (e.g., Ethereum main net vs. cloud). It is essential to build a dependable interface in between private and main nets if business to consumer (or vice versa) transactions are demanded for instance. In the course of interfacing across private and main nets, dependability is to be considered as one of the most critical design factors in order to ensure private transactions stay within the private territory and publicized transactions stay public in the main net, and further in order to facilitate a seamless yet dependable execution of transactions across the border. In this context, the efficacy of the privacy of the private net side and the publicity of the main net side will be addressed and modeled by tracing a transaction's stochastic process at a steady state. A protype for an isolated testing across the Ethereum and Hypercubes open source for validation purpose is proposed along with extensive parametric simulations.