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The 'neuropunk revolution' represents an innovative approach focused on the integration of human–machine interfaces through nerve and neural pathways. This cutting-edge concept seeks to push the boundaries of human–machine interaction by exploring the intricate connections between the human nervous system and artificial technologies. Neuropunk delves into the realm of cyborg technologies, blurring the lines between humans and machines and opening up new possibilities for augmenting human capabilities. By tapping into nerve and neural pathways, neuropunk envisions a future where individuals can seamlessly interface with technology, leading to enhanced sensory perception, cognitive abilities, and physical performance. This concept encapsulates a rebellious and unconventional spirit, challenging traditional notions of the human body and its relationship with technology. This paper discusses the challenges and potential of neuropunk, exploring the fusion of scientific exploration, technological innovation, and a punk-inspired ethos in advancing human–machine integration. It highlights the emergence of real-time neurosimulations and neuromorphic computing as key tools to achieve these aspirations. Additionally, the integration of neurological and hormonal bioinspiration is examined as a promising approach to the design of neural interfaces, fostering more efficient and effective technologies that align better with the human body. Finally, the paper addresses ethical considerations and research tasks to responsibly navigate the neuropunk revolution, ensuring a future that maximizes the benefits of neural interfaces while mitigating potential risks and promoting ethical principles. [ABSTRACT FROM AUTHOR]

We have developed environment-adaptive software that enables high-performance operation by automatically converting application code in accordance with the deployed environment and setting appropriate amounts of resources. We only considered conversions and settings before the start of operation. In this paper, we verify that the logic is reconfigured in accordance with the usage characteristics during operation. We propose a FPGA reconfiguration method during operation and confirm that the application running on the FPGA is reconfigured into another application in accordance with the usage characteristics. Through confirmation, performance improvement and break time are checked, and the effectiveness of method is shown. [ABSTRACT FROM AUTHOR]

In this paper, we prove that there is a strongly universal cellular automaton on the heptagrid with five states under the relaxation of the assumption of rotation invariance for the rules. The result is different from that of a previous paper of the author with six states but with rotationally invariant rules. Here, the structures is more constrained than in the quoted paper with six states and rotation invariance of the rules. [ABSTRACT FROM AUTHOR]

In this paper, we construct a weakly universal cellular automaton in the heptagrid, the tessellation $ \{7,3\} $ { 7 , 3 } which takes place in the hyperbolic plane. The cellular automation is not rotation invariant but which is truly planar. This result, under these conditions, cannot be improved for the tessellations $ \{p,3\} $ { p , 3 } of the hyperbolic plane. [ABSTRACT FROM AUTHOR]

Due to the widespread penetration of wind energy, large-capacity wind turbines (WTs) are becoming more conspicuous. In this paper, a linear control-oriented large-capacity wind turbine (WT) model is redesigned based on the 15 MW WT in openFAST. Compared with the original model, the redesigned model is more efficient and conducive to the design of linear controllers. To verify the validity of the redesigned WT model, we design a distributed control scheme with deloading operation of the wind farm (WF) to fairly share the load. Simulations are performed to verify the effectiveness of the application in the WF. [ABSTRACT FROM AUTHOR]

Aspect-based sentiment analysis (ABSA) aims to analyze the emotional color contained in sentences or documents in more detail by classifying and evaluating different aspects and emotions in the text. However, the current research methods cannot effectively analyze the relationship between aspect words and context and extract grammatical information about sentences. Additionally, the extracted syntactic information is insufficient, and the combination of syntactic and semantic information is inefficient, leaving the model unable to correctly determine aspects' emotional orientations. This paper proposes an aspect-level sentiment analysis based on Fusion Graph Double Convolutional Neural Networks (FGD-GCN) to address these issues. Firstly, FGD-GCN proposes a multi-feature extraction module. Using BERT and bidirectional long-short-term memory models, this module extracts the hidden context between words. In addition, the positional attention module is used to capture important features in sentences, reducing noise and bias. Then, a semantic enhancement module is proposed, which fuses attention-focused information and feature information extracted from graphs to emphasize aspect words and context, and uses CNN model to classify on feature vectors. According to experiment results on three benchmark datasets, the model outperforms previous GCN methods for context-based aspect-level sentiment analysis. [ABSTRACT FROM AUTHOR]

For a set M of vertices and an edge e of a graph G, let $ P_G(M, e) $ P G (M , e) be the set of the pair $ (x, y) $ (x , y) with a vertex x of M and a vertex y of $ V(G) $ V (G) such that $ d_G(x, y)\neq d_{G-e}(x, y) $ d G (x , y) ≠ d G − e (x , y). For a vertex x, let $ EM(x) $ EM (x) be the edge set e such that there exists a vertex v in G with $ (x, v) \in P(\{x\}, e) $ (x , v) ∈ P ({ x } , e). A set M of vertices of a graph G is distance-edge-monitoring set if every edge e of G is monitored by some vertex $ v\in M $ v ∈ M , that is, for any $ e \in E(G) $ e ∈ E (G) , we have $ P_G(M, e)\neq \emptyset $ P G (M , e) ≠ ∅. The distance-edge-monitoring number of a graph G, denoted by $ \operatorname {dem}(G) $ dem ⁡ (G) , is defined as the smallest size of distance-edge-monitoring sets of G. In this paper, we study the distance edge monitoring number of pseudo wheel graphs, that is, some variants of wheel graph. [ABSTRACT FROM AUTHOR]

Given a graph G and an edge $ e\in E(G) $ e ∈ E (G) , let S be a vertex set of G. For any two vertices x, $ y\in S $ y ∈ S , if e belongs to all the shortest paths between x and y, then x and y can monitor the edge e. For each edge e of G, if there exists x and y in S such that x and y can monitor e, then the set S can be called a monitoring-edge-geodetic ( $ \operatorname {MEG} $ MEG for short) set of G. The $ \operatorname {MEG} $ MEG number, denoted by $ \operatorname {meg}(G) $ meg ⁡ (G) , is the size of the smallest $ \operatorname {MEG} $ MEG set of G. In this paper, we obtain the exact values of the $ \operatorname {MEG} $ MEG numbers for radix triangular mesh networks, Sierpiński graphs, Sierpiński gasket graphs and Sierpiński generalized graphs. [ABSTRACT FROM AUTHOR]

The interplanetary File system (IPFS) provides data communication using plaintext over distributed and decentralized systems. Up till now, the security of data has mostly been established using keys. To facilitate classified data communication within a Closed User Group (CUG), services of IPFS private swarm are required to render additional content encryption. Currently, there is no inherent security built into IPFS. This paper presents an application DMaya on IPFS to provide keyless encryption on IPFS based on the Quasigroup-based Secret Sharing Scheme (QSS). IPFS is used as a storage medium, irrespective of the nature of data. Data security in decentralized mode with IPFS is provided with DMaya. The classified data of all types (i.e. video data, audio data, text data, and image data) when subjected to DMaya application, are fragmented into smaller fragments then processed by the probabilistic Quasigroup-based Secret Sharing (QSS) Scheme. DMaya keyless encryption generates the metadata tag file at the source node. The recipient node within the same private IPFS swarm, on receipt of metadata tag file reconstructs the original data with DMaya application. [ABSTRACT FROM AUTHOR]

The fault tolerability of the network is usually measured by the classical or generalized connectivity of the graph. For any subset $ S \subseteq V\left (G \right) $ S ⊆ V (G) with $ \left | S \right | \ge 2 $ | S | ≥ 2 , a tree T is called an S-tree if $ S \subseteq V\left (T \right) $ S ⊆ V (T) . Furthermore, any two S-tree $ T_1 $ T 1 and $ T_2 $ T 2 are internally disjoint if $ E\left ({{T_1}} \right) \cap E\left ({{T_2}} \right) = \emptyset $ E ( T 1 ) ∩ E ( T 2 ) = ∅ and $ V\left ({{T_1}} \right) \cap V\left ({{T_2}} \right) = S $ V ( T 1 ) ∩ V ( T 2 ) = S. We denote by $ {\kappa _G}\left (S \right) $ κ G (S) the maximum number of pairwise internally disjoint S-trees in G. For an integer $ k \ge 2 $ k ≥ 2 , the generalized k-connectivity of a graph G is defined as $ {\kappa _k}\left (G \right) = \min \left \{ {{\kappa _G}\left (S \right) | S \subseteq V\left (G \right)} \right. $ κ k (G) = min { κ G (S) | S ⊆ V (G) and $ \left. {\left | S \right | = k} \right \} $ | S | = k } . In this paper, we establish the generalized 4-connectivity of the Cayley graph $ CT_n $ C T n generated by complete graphs. [ABSTRACT FROM AUTHOR]

As distributed and multi-organization Machine Learning emerges, new challenges must be solved, such as diverse and low-quality data or real-time delivery. In this paper, we use a distributed learning environment to analyze the relationship between block size, parallelism, and predictor quality. Specifically, the goal is to find the optimum block size and the best heuristic to create distributed Ensembles. We evaluated three different heuristics and five block sizes on four publicly available datasets. Results show that using fewer but better base models matches or outperforms a standard Random Forest, and that 32 MB is the best block size. [ABSTRACT FROM AUTHOR]

This paper investigates the coordination control of large-scale systems (LSSs) with unknown external disturbances. The disturbances exist in the channels from the controllers to the actuators. To compensate the impact of disturbances, an extended observer using the output states is constructed, and an observer-based event-triggered controller is designed to save communication resources. Moreover, based on the event-triggering strategy, a controller using dynamic information estimation is designed, and Zeno behavior is further excluded. Finally, a DC micro-grid model is used for simulations to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Let G be a graph with vertex set $ V(G) $ V (G) and edge set $ E(G) $ E (G). For any $ e \in E(G) $ e ∈ E (G) and $ u,v\in V(G) $ u , v ∈ V (G) , the edge e is monitored by two vertices u and v in graph G if $ d_G(u, v) \neq d_{G-e}(u, v) $ d G (u , v) ≠ d G − e (u , v). A set M of vertices of G is a monitoring-edge-geodetic set of G if for any edge $ e \in E(G) $ e ∈ E (G) there exists a pair $ u, v\in M $ u , v ∈ M such that e is monitored by u, v. The monitoring-edge-geodetic number $ \operatorname {meg}(G) $ meg ⁡ (G) is the cardinality of the minimum MEG-set in G. In this paper, we obtain the exact values or bounds for the MEG numbers of graph products, including join, corona, cluster, lexicographic products and direct products. [ABSTRACT FROM AUTHOR]

This paper proposes an unconventional architecture and algorithm for implementing reservoir computing on FPGA. An architecture-oriented algorithm with improved throughput and architecture designed to reduce memory and hardware resource requirements are presented. The proposed architecture exhibits good performance in terms of benchmarks for reservoir computing. A prediction accelerator for reservoir computing that operates on 55.45 mW at 450 K fps with <3000 LEs is realized by implementing the architecture on FPGA. The proposed approach presents a novel FPGA implementation of reservoir computing focussing on both algorithms and architecture that may serve as a basis for applications of AI at network edge. [ABSTRACT FROM AUTHOR]

Analog computing is often considered to be an outdated technology only to be found and cared for in museums but not as the basis of modern cutting edge computing. Nothing could be further from reality. Together with quantum computers, analog computers complement today's stored program digital computers, acting as co-processors for certain types of computationally intensive tasks. They are highly energy efficient and exhibit a degree of parallelism that by far surpasses classic digital computers. In contrast to quantum computers, analog computers do not require exotic technologies, no intricate cooling systems, no elaborate shielding systems, etc. In addition to this there already exists a plethora of proven programs for analog computers to solve a wide variety of problems. This paper describes the necessity of analog computing for the twenty-first century, gives a short introduction to the structure and programming of analog computers, before discussing future application areas. Analog computing will drastically alter the way we think about computing in the years to come as it will become an integral part of every high performance computer. It will be an indispensable technology for future AI systems, it will revolutionize many medical applications, it might even replace or at least complement, certain types of quantum computers, etc. [ABSTRACT FROM AUTHOR]

This paper reports a special class of cellular automata machines that can solve graph theoretic problems, such as spanning tree problem and single source shortest path problem. The machine deals with planar graphs only. We first develop two-dimensional cellular automata to solve the graph theoretic problems for planar graphs. Next, we design the hardware for implementation of those cellular automata. [ABSTRACT FROM AUTHOR]

This paper presents efficient data structures for the implementation of matrix-free finite element methods on block-structured, hybrid tetrahedral grids. It provides a complete categorization of all geometric sub-objects that emerge from the regular refinement of the unstructured, tetrahedral coarse grid and describes efficient iteration patterns and analytical linearization functions for the mapping of coefficients to memory addresses. This foundation enables the implementation of fast, extreme-scalable, matrix-free, iterative solvers, and in particular geometric multigrid methods by design. Their application to the variable-coefficient Stokes system subject to an enriched Galerkin discretization and to the curl-curl problem discretized with Nédélec edge elements showcases the flexibility of the implementation. Finally, the solution of a curl-curl problem with $ 1.6\cdot 10^{11} $ 1.6 ⋅ 10 11 (more than one hundred billion) unknowns on more than 32,000 processes with a matrix-free full multigrid solver demonstrates its extreme-scalability. [ABSTRACT FROM AUTHOR]

The connectivity and diagnosability are two important parameters to evaluate the fault-tolerability of network. The enhance hypercube is a variant of the hypercube which not only retains some of the favorable properties of the hypercube, but also possesses some embedding properties that the hypercube does not have. In this paper, we obtain the connectivity and the conditional diagnosability of enhanced hypercube based on structure faults. [ABSTRACT FROM AUTHOR]

Quadratic Unconstrained Binary Optimization (QUBO) is a combinatorial optimization problem defined by an energy function that consists of a quadratic formula involving multiple binary variables. We propose the method of combing bit reduction and duplication technique that can generate hard instances of QUBO problems from any original QUBO problem without changing the size. The idea is to reduce the original QUBO problem for a specified number of bits and duplicate the same number of bits while ensuring all duplicated pair of bits take the same binary values. Experimental results show that generated QUBO instances are much hard for solving. [ABSTRACT FROM AUTHOR]

We propose a novel blockchain-based academic degree verification system. The system relies on a smart contract deployed on the Ethereum blockchain platform. The system protects the privacy of the students who have been verified without the need of encryption, and hence, avoid the complexity of security key management and the potential disaster if the keys are stolen or revealed. The amount of degree data is also designed to be minimum for proper verification. All operations on the critical path of the system are automated without any human intervention. However, the system does assume that the organization would stand behind the proposed system to ensure the system's integrity. The system is open to anyone who wishes to verify the degree of a student. To prevent spamming and to support the long-term sustainability of the system, a small fee is charged for each verification request. A portion of the fees collected is immediately credited to the participating schools. To facilitate automated school enrollment into the system, any school may request to enroll by placing a significant amount of stake in ETH. The stake can be refunded when the school decides to leave the system. However, if the school is blacklisted due to misbehavior, the stake is confiscated. This design strongly discourages adversaries from abusing the system. The performance of the system is fully characterized with regard to the gas consumption of key operations in various use cases. We demonstrate that the system is conducive for long-term sustainability. [ABSTRACT FROM AUTHOR]

We present a paradigm for access control to typed objects logically connected to form a hierarchy, whereby each object has a single parent, and may have children. Protection domains are divided into three classes. A vertical domain includes authorizations for the objects in a subhierarchy. A horizontal domain includes authorizations for the children of a given object. A simple domain includes an authorization for a single object. We introduce the hierarchical capability concept as a generalization of the classical password capability concept. A hierarchical capability references an entire domain instead of a single object. [ABSTRACT FROM AUTHOR]

For scientific software, especially those used for large-scale simulations, achieving good performance and efficiently using the available hardware resources is essential. It is important to regularly perform benchmarks to ensure the efficient use of hardware and software when systems are changing and the software evolves. However, this can become quickly very tedious when many options for parameters, solvers, and hardware architectures are available. We present a continuous benchmarking strategy that automates benchmarking new code changes on high-performance computing clusters. This makes it possible to track how each code change affects the performance and how it evolves. [ABSTRACT FROM AUTHOR]

This article develops a new control-oriented linear parameter varying (LPV) model, which is a linear state-space model with varying parameters aimed at efficiently representing large-scale offshore wind turbines (LOWTs). Firstly, the LPV model is constructed by the mechanism analysis of a 15-MW direct-drive permanent magnet wind turbine. Subseuently, based on the operational data from FAST, the parameters with unknown values in the LPV model are determined by gain scheduling and parameter estimation. Furthermore, a deloading operation for the active output power regulation of LOWTs is proposed based on coordinating the rotor over-speed control (ROC) and the pitch angle control (PAC). [ABSTRACT FROM AUTHOR]

Public and permissionless blockchain systems are challenged by Sybil attacks, in which attackers use multiple identities to gain control. Traditionally, such attacks are prevented by consensus mechanisms relying on resource expenditure. However, such mechanisms (e.g. proof of work) face criticism for being wasteful. To address this and other concerns, novel blockchain systems backed by new consensus mechanisms have recently emerged. We formalise three key characteristics pursued by these systems: permissionlessness, Sybil attack resistance, and freeness. We demonstrate that no blockchain protocol can simultaneously achieve all three characteristics within the paradigm established by our formalisation. Thus, a trilemma emerges for distributed ledger technology designers, who must balance these characteristics thoughtfully. [ABSTRACT FROM AUTHOR]

Consider the empirical laws established in the History of Science. The process of scientific discovery can be roughly explained by (Popper-Kuhn's) cycle which starts with collecting evidence, introducing a model to explain observations, predicting further observations, and confronting them with experimentation, reinforcing or disproving the model. We attempt to prove that the empirical evidence modeled by arithmetical operations can be automatically discovered with a small amount of information, i.e. with very short Blums' locking sequences, due to the suitable enumerations of arithmetical functions. [ABSTRACT FROM AUTHOR]

CAMP proposes a hierarchical cache subsystem for multi-core mixed criticality processors, focusing on ensuring worst-case execution time (WCET) predictability in automotive applications. It incorporates criticality-aware locked L1 and L2 caches, reconfigurable at mode change intervals, along with criticality-aware last level cache partitioning. Evaluation using CACOSIM, Moola Multicore simulator, and CACTI simulation tools confirms the suitability of CAMP for keeping high-criticality jobs within timing budgets. A practical case study involving an automotive wake-up controller using the sniper v7.2 architecture simulator further validates its usability in real-world mixed criticality applications. CAMP presents a promising cache architecture for optimized multi-core mixed criticality systems. [ABSTRACT FROM AUTHOR]

Each generation of CPU provides more resources and new features. These increase the ability to perform algorithms faster and with a higher degree of parallelism. The article discusses methods used to optimise CRC generation algorithms for long data blocks with consideration of the capabilities of contemporary systems. We analysed known software CRC algorithms and combined all known principles into a solution scalable in multiple CPU cores on single and multi-socket systems. Various algorithms were evaluated on contemporary multicore systems with 1 × 4, 1 × 64, 2 × 12, and 4 × 26 cores. The results show how the performance is affected by the architecture of the memory subsystem. Compared to the original sequential Sarwate algorithm, our algorithms are 48.0, 51.1, 38.0, and 28.8 times faster. [ABSTRACT FROM AUTHOR]

This study addresses the problem of 'Circle Formation on an Infinite Grid by Fat Robots' ( $ CF\_FAT\_GRID $ CF _FAT _GRID). Unlike prior work focused solely on point robots in discrete domain, it introduces fat robots to circle formation on an infinite grid, aligning with practicality as even small robots inherently possess dimensions. The algorithm, named $ CIRCLE\_FG $ CIRCLE _FG , resolves the $ CF\_FAT\_GRID $ CF _FAT _GRID problem using a swarm of fat luminous robots. Operating under an asynchronous scheduler, it achieves this with five distinct colors and by leveraging one-axis agreement among the robots. [ABSTRACT FROM AUTHOR]

The reliability of consensus protocols establishes the basis for cryptocurrency cybersecurity. Formal and simulation techniques are appreciated for the verification of proof-of-work agreement protocols, because the formal techniques development process frequently requires a series of assumptions, leading to somewhat unrealistic models. A conventional colored Petri net model, presented by the authors in a previous study, allowed us to refine the Keller and Böhme consensus protocol by applying the simulation technique. In this study, we developed a reenterable colored Petri net model representing a general construct for model-driven development and refinement of consensus protocols and the corresponding software. A considerable benefit of a reenterable model is the invariance of its structure with respect to the net topology, number of attached nodes, and parameters of their software and hardware, which are represented as the marking of dedicated places. Switching of topology tags associated with dynamic objects represents the basic principle of reenterable model functioning. It is shown that, having the same characteristics, in bounds of admissible error of some 2-3%, the reenterable model results in 6 times speed-up of the simulation process and a drastic decrease in time for model editing, especially when the number of nodes exceeds a hundred. Thus, a reenterable model is a valuable complement to possible formal models that allows us to obtain express-evaluations of characteristics in a rather short time and with an acceptable level of adequacy. [ABSTRACT FROM AUTHOR]

Survivability of Elastic Optical Networks (EONs) from a link failure is an important problem. Shared Backup Path Protection (SBPP) is widely used for protection against a link failure. Backup Spectrum Reservation with Multi Path Protection (BSR-MPP) was introduced to increase backup spectrum sharing by reserving backup spectrum and employing protection with multiple backup paths. We propose a new polynomial-time strategy, Blocking Aware Survivable Path Provisioning (BASPP) that shares backup resources like SBPP and BSR-MPP but can reduce request blocking when opportunity of sharing resources does not exist. Since we address the offline problem of Survivable Routing, Modulation and Spectrum Allocation in EONs, we also propose an Integer Linear Program formulation. Results show appreciable reduction in bandwidth blocking ratio by using BASPP over existing strategies. [ABSTRACT FROM AUTHOR]