Search results for "Theoretical Computer Science"
showing 10 items of 1151 documents
Investigating Novice Developers’ Code Commenting Trends Using Machine Learning Techniques
2023
Code comments are considered an efficient way to document the functionality of a particular block of code. Code commenting is a common practice among developers to explain the purpose of the code in order to improve code comprehension and readability. Researchers investigated the effect of code comments on software development tasks and demonstrated the use of comments in several ways, including maintenance, reusability, bug detection, etc. Given the importance of code comments, it becomes vital for novice developers to brush up on their code commenting skills. In this study, we initially investigated what types of comments novice students document in their source code and further categoriz…
An automatic method for metabolic evaluation of gamma knife treatments
2015
Lesion volume delineation of Positron Emission Tomography images is challenging because of the low spatial resolution and high noise level. Aim of this work is the development of an operator independent segmentation method of metabolic images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Twenty-four cerebral tumors are segmented to evaluate the functional follow-up after Gamma Knife radiotherapy treatment. Experimental results show that the segmentation algorithm is accurate and has real-time performance. In addition, it can reflect metabolic changes useful to evaluate radiotherapy response in treated patients.
Neuro-radiosurgery treatments: MRI brain tumor seeded image segmentation based on a cellular automata model
2016
Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most promi-nent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and op-erator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, is only obtained by using computer-assisted appr…
Organizational Learning from Cybersecurity Performance: Effects on Cybersecurity Investment Decisions
2023
AbstractIS literature has identified various economic, performance, and environmental factors affecting cybersecurity investment decisions. However, economic modeling approaches dominate, and research on cybersecurity performance as an antecedent to investments has taken a backseat. Neglecting the role of performance indicators ignores real-world concerns driving actual cybersecurity investment decision-making. We investigate two critical aspects of cybersecurity performance: breach costs and breach identification source, as antecedents to cybersecurity investment decisions. We use organizational learning to theorize how performance feedback from these two aspects of cybersecurity breaches …
Increasing stability in the linearized inverse Schrödinger potential problem with power type nonlinearities
2022
We consider increasing stability in the inverse Schr\"{o}dinger potential problem with power type nonlinearities at a large wavenumber. Two linearization approaches, with respect to small boundary data and small potential function, are proposed and their performance on the inverse Schr\"{o}dinger potential problem is investigated. It can be observed that higher order linearization for small boundary data can provide an increasing stability for an arbitrary power type nonlinearity term if the wavenumber is chosen large. Meanwhile, linearization with respect to the potential function leads to increasing stability for a quadratic nonlinearity term, which highlights the advantage of nonlinearit…
Kohn-Sham Decomposition in Real-Time Time-Dependent Density-Functional Theory An Efficient Tool for Analyzing Plasmonic Excitations
2017
The real-time-propagation formulation of time-dependent density-functional theory (RT-TDDFT) is an efficient method for modeling the optical response of molecules and nanoparticles. Compared to the widely adopted linear-response TDDFT approaches based on, e.g., the Casida equations, RT-TDDFT appears, however, lacking efficient analysis methods. This applies in particular to a decomposition of the response in the basis of the underlying single-electron states. In this work, we overcome this limitation by developing an analysis method for obtaining the Kohn-Sham electron-hole decomposition in RT-TDDFT. We demonstrate the equivalence between the developed method and the Casida approach by a be…
Linear Types for Higher Order Processes with First Class Directed Channels
1995
Abstract We present a small programming language for distributed systems based on message passing processes. In contrast to similar languages, channels are one-to-one connections between a unique sender and a unique receiver process. Process definitions and channels are first class values and the topology of process systems can change dynamically. The operational semantics of the language is defined by means of graph rewriting rules. A static type system based on the notion of linear types ensures that channels are always used as one-to-one connections.
Novel qutrit circuit design for multiplexer, De-multiplexer, and decoder
2022
AbstractDesigning conventional circuits present many challenges, including minimizing internal power dissipation. An approach to overcoming this problem is utilizing quantum technology, which has attracted significant attention as an alternative to Nanoscale CMOS technology. The reduction of energy dissipation makes quantum circuits an up-and-coming emerging technology. Ternary logic can potentially diminish the quantum circuit width, which is currently a limitation in quantum technologies. Using qutrit instead of qubit could play an essential role in the future of quantum computing. First, we propose two approaches for quantum ternary decoder circuit in this context. Then, we propose a qua…
Some Investigations on Similarity Measures Based on Absent Words
2019
In this paper we investigate similarity measures based on minimal absent words, introduced by Chairungsee and Crochemore in [1]. They make use of a length-weighted index on a sample set corresponding to the symmetric difference M(x)ΔM(y) of the minimal absent words M(x) and M(y) of two sequences x and y, respectively. We first propose a variant of this measure by choosing as a sample set a proper subset (x, y) of M(x)ΔM(y), which appears to be more appropriate for distinguishing x and y. From the algebraic point of view, we prove that (x, y) is the base of the ideal generated by M(x)ΔM(y). We then remark that such measures are able to recognize whether the sequences x and y share a common s…
SparseHC: A Memory-efficient Online Hierarchical Clustering Algorithm
2014
Computing a hierarchical clustering of objects from a pairwise distance matrix is an important algorithmic kernel in computational science. Since the storage of this matrix requires quadratic space with respect to the number of objects, the design of memory-efficient approaches is of high importance to this research area. In this paper, we address this problem by presenting a memory-efficient online hierarchical clustering algorithm called SparseHC. SparseHC scans a sorted and possibly sparse distance matrix chunk-by-chunk. Meanwhile, a dendrogram is built by merging cluster pairs as and when the distance between them is determined to be the smallest among all remaining cluster pairs. The k…