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By harnessing fundamental quantum properties, a large-scale quantum computer could undermine currently deployed public-key algorithms. The post-quantum, code-based cryptosystem Classic McEliece (CM) addresses this security concern. However, its large ...

Spike timing-dependent plasticity (STDP) is crucial for training neural networks (SNNs), offering a hardware-compatible and energy-efficient alternative to backpropagation. Current STDP hardware platforms encounter significant challenges, such as ...$$$$$$

In recent years, unmanned aerial vehicles (UAVs) have been broadly employed as a data collection platform to assist in efficiently collecting data from IoT devices. However, the deployment optimization of UAVs has been challenged due to the need ...

Fourier PlenOctrees have shown to be an efficient representation for real-time rendering of dynamic neural radiance fields (NeRF). Despite its many advantages, this method suffers from artifacts introduced by the involved compression when ...

This paper explores the problem of determining which classes of Petri nets can be encoded into behaviourally-equivalent CCS processes. Most of the existing related literature focuses on the inverse problem (i.e., encoding process calculi belonging ...$$

Participatory data physicalizations allow people to physically participate in the creation of visualizations. In this work, we present four categories of data physicalization concepts that were tested with public event visitors in a university context. ...

Many Boolean functions that need to be encoded as CNF in practice, have only exponential size CNF representations. To avoid this effect, one usually introduces nondeterministic variables. For example, whereas the minimum number of clauses in a CNF ...${}_{\mathrm{}}{}_{\mathrm{}}{}_{}$${\mathrm{}}^{\mathrm{}}$$\mathrm{}$

The ρ-calculus (Reflective Higher-Order Calculus) of Meredith and Radestock is a π-calculus-like language with unusual features, notably, structured names, runtime generation of free names, and the lack of a scoping operator. These features pose ...

The Gate Level Information Flow Tracking (GLIFT) is an effective method to uphold the information security for high-assurance digital circuits. The GLIFT method associates a security label with each data bit and monitors these labels to expose ...

The enhancements made to an earlier proposed combination of spectral subtraction using voice activity detection (SS-VAD) and linear predictive coding (LPC) system under uncontrolled environments are demonstrated in this work. In the earlier ...

Understanding and reading an unstructured text to answer queries on it, also called Machine Reading Comprehension (MRC), has been a hot topic amongst researchers worldwide in the past few years. There are many ways in which this problem has been ...

Shellcode is a critical element in computer security that exploits vulnerabilities within software systems. Shellcode is written in machine code and often designed to be compact in size, evading detection by security software. Printable shellcode, ...

In this work, we introduce the random fault model - a more advanced fault model inspired by the random probing model, where the adversary can fault all values in the algorithm but the probability for each fault to occur is limited. The new ...

This paper studies the problem of stabilizing a self-triggered control system with quantized output. Employing a standard observer-based state feedback control law, a self-triggering mechanism that dictates the next sampling time based on ...

Polynomial based secret sharing is the art of protecting information and a tool used in areas where a secret has to be distributed among multiple parties. In this method, secret is encrypted into noisy shares and transferred to participants in the ...

Acoustic features, in the examination of emotions occurring in pronouncing English and Chinese Mandarin words, are investigated in this study, then different emotion recognition experiments are presented. To this end, the sound recordings for 91 ...

(Non)-Deterministic finite automata are one of the simplest models of computation studied in automata theory. Here we study them through the lens of succinct data structures. Towards this goal, we design a data structure for any ...

Decoding and encoding models are popular multivariate approaches used to study representations in functional neuroimaging data. Encoding approaches seek to predict brain activation patterns using aspects of the stimuli as features. Decoding models,...

Cognitive brain mapping is enjoying its growth with the availability of large open data sharing efforts as well as the application of modern machine learning and deep learning methods. In this article, we review some of the current practices in ...

Cloud storage represents a cloud delivered-service model which draws the attention of organizations and individuals due to its uncounted attractive advantages. Cloud Service Providers (CSPs) supply storage facilities while the cloud user has the ...