Applications In Computer Science Research Articles

Perceptual Quality Assessment of Colored 3D Point Clouds.

3D point clouds have found a wide variety of applications in multimedia processing, remote sensing, and scientific computing. Although most point cloud processing systems are developed to improve viewer experiences, little work has been dedicated to perceptual quality assessment of 3D point clouds. In this work, we build a new 3D point cloud database, namely the Waterloo Point Cloud (WPC) database. In contrast to existing datasets consisting of small-scale and low-quality source content of constrained viewing angles, the WPC database contains 20 high quality, realistic, and omni-directional source point clouds and 740 diversely distorted point clouds. We carry out a subjective quality assessment experiment over the database in a controlled lab environment. Our statistical analysis suggests that existing objective point cloud quality assessment (PCQA) models only achieve limited success in predicting subjective quality ratings. We propose a novel objective PCQA model based on an attention mechanism and a variant of information content-weighted structural similarity, which significantly outperforms existing PCQA models. The database has been made publicly available at https://github.com/qdushl/Waterloo-Point-Cloud-Database.

Technical Note—On Adaptivity in Nonstationary Stochastic Optimization with Bandit Feedback

Optimal Nonstationary Optimization Without Knowing Function Changes Nonstationary stochastic optimization plays a vital role in a number of computer science and operations research applications. It is known how to design and analyze algorithms that optimize a sequence of strongly convex/concave and smooth functions with access to only one-point noisy function values with the underlying function sequence subject to maximum magnitude of function changes. In recent work from Wang titled “Technical Note: On Adaptivity in Nonstationary Stochastic Optimization with Bandit Feedback,” an optimization algorithm is designed and analyzed without assuming the magnitude of function changes is known in advance. Optimality of the designed algorithm is demonstrated.

Enhanced Effectiveness in Various Ladder Graphs Based on the F-Centroidal Meanness Criterion

Graph labeling allows for the representation of additional attributes or properties associated with the vertices, edges, or both of graphs. This can provide a more comprehensive and detailed representation of the system being modeled, allowing for a richer analysis and interpretation of the graph. Graph labeling in ladder graphs has a wide range of applications in engineering, computer science, physics, biology, and other fields. It can be applied to various problem domains, such as image processing, wireless sensor networks, VLSI design, bioinformatics, social network analysis, transportation networks, and many others. The versatility of ladder graphs and the ability to apply graph labeling to them make them a powerful tool for modeling and analyzing diverse systems. If a function Υ is an injective vertex assignment in {1,2,…q+1} and the inductive edge assignment function Υ* in {1,2,…q} is expressed as a graph with q edges, defined as Υ*(uv)=2[Υ(u)2+Υ(u)Υ(v)+Υ(v)2]3[Υ(u)+Υ(v)], then the function is referred to as F-centroidal mean labeling. This is known as the F-centroidal mean criterion. Here, we have determined the F-centroidal mean criteria of the graph ladder, slanting ladder, triangular ladder, TLn∘Sm, SLn∘Sm for m≤2, double-sided step ladder, Dn*, and diamond ladder.

Proximal algorithm with quasidistances for multiobjective quasiconvex inimization in Riemannian manifolds

We introduce a proximal algorithm using quasidistances for multiobjective minimization problems with quasiconvex functions defined in arbitrary Riemannian manifolds. The reason of using quasidistances instead of the classical Riemannian distance comes from the applications in economy, computer science and behavioral sciences, where the quasidistances represent a non symmetric measure. Under some appropriate assumptions on the problem and using tools of Riemannian geometry we prove that accumulation points of the sequence generated by the algorithm satisfy the critical condition of Pareto-Clarke. If the functions are convex then these points are Pareto efficient solutions.

Socialist AI? Societal Use, Economic Implementation, and the Tensions of Applied Computer Science in Late Socialist GDR

Socialist AI? Societal Use, Economic Implementation, and the Tensions of Applied Computer Science in Late Socialist GDR

Asymptotic normality for the size of graph tries built from M-ary tree labelings

Graph tries are a new and interesting data structure proposed by Jacquet in 2014. They generalize the classical trie data structure which has found many applications in computer science and is one of the most popular data structure on words. For his generalization, Jacquet considered the size (or space requirement) and derived an asymptotic expansion for the mean and the variance when graph tries are built from n independently chosen random labelings of a rooted M-ary tree. Moreover, he conjectured a central limit theorem for the (suitably normalized) size as the number of labelings tends to infinity. In this paper, we verify this conjecture with the method of moments.

Discrete Analogue of Fishburn’s Fractional-Order Stochastic Dominance

A stochastic dominance (SD) relation can be defined by two different perspectives: One from the view of distributions, and the other one from the view of expected utilities. In the early days, Fishburn investigated SD from the view of distributions, and we refer this perspective as Fishburn’s SD. One of his many results was the development of fractional-order SD for continuous distributions. However, discrete fractional-order SD cannot be directly generalized, because some properties of fractional calculus may not possess a discrete counterpart. In this paper, we develop a discrete analogue of fractional-order SD for discrete utilities from the view of distributions. We generalize the order of SD by Lizama’s fractional delta operator, show the preservation of SD hierarchy, and formulate the utility classes that are congruent with our SD relations. This work brings a message that some results of discrete SD cannot be directly generalized from continuous SD. We characterize the difference between discrete and continuous fractional-order SD, as well as the way to handle it for further applications in mathematics and computer science.

FDM data driven U-Net as a 2D Laplace PINN solver

Efficient solution of partial differential equations (PDEs) of physical laws is of interest for manifold applications in computer science and image analysis. However, conventional domain discretization techniques for numerical solving PDEs such as Finite Difference (FDM), Finite Element (FEM) methods are unsuitable for real-time applications and are also quite laborious in adaptation to new applications, especially for non-experts in numerical mathematics and computational modeling. More recently, alternative approaches to solving PDEs using the so-called Physically Informed Neural Networks (PINNs) received increasing attention because of their straightforward application to new data and potentially more efficient performance. In this work, we present a novel data-driven approach to solve 2D Laplace PDE with arbitrary boundary conditions using deep learning models trained on a large set of reference FDM solutions. Our experimental results show that both forward and inverse 2D Laplace problems can efficiently be solved using the proposed PINN approach with nearly real-time performance and average accuracy of 94% for different types of boundary value problems compared to FDM. In summary, our deep learning based PINN PDE solver provides an efficient tool with various applications in image analysis and computational simulation of image-based physical boundary value problems.

Analysis of Electronic Banking and Information Technology using the TOPSIS Method

Electronic banking, sometimes referred to as electronic transfer of funds (EFT), is the process of moving money electronically from one account to another. A 2015 Treasury Department poll found that 22% of mobile telephone owners conduct banking transactions online or over the phone as opposed to in person. They accomplish this via computer technology, telecommunications, and mobile payments. Automatic bill and paycheck deductions, computerized money transfers for online spending, and payment machines (ATMs) are some of its features. In the banking sector, information technology refers to the application of cutting-edge computer science and information and communication technologies. It retains a strategic advantage over all the other banks by offering its customers safe, dependable, and inexpensive services. A variety of banking services and other facilities that use electronic technology are referred to as electronic banking. Services for debit cards and ATMs. Banking over the phone. Online banking is one of the main services offered by banks, and it is also a relatively safe platform. Banks often use encryption technology to safeguard all client data and stop security lapses. Last, it provides protection from online scams and account hacking. Electronic banking, sometimes known as e-banking, is a broad term for using technology to access banking services, Internet banking, on the other hand, is a type of electronic banking. It employs electronic ways to move money straight from one accounts to another and is also referred to as an "Electronic Funds Transfer" (EFT). Automatic Teller Machines (ATMs) are online banking facilities that let customers do transactions without going to a bank location. Some ATMs only let you withdraw cash, while others let you do a wide range of things like check deposits, current accounts, and bill payments. Mobile banking is only possible through mobile devices, but digital banking gives you access to a variety of banking options from your desktop, tablet, laptop, etc. Also, you can do mobile banking through SMS or banking applications without the need for the Internet. By replacing document and labor-intensive techniques with automated processes, internet banking has become an effective resource for increased productivity and profitability, operational control, and cost savings. Examining how online banking affects consumer happiness is the goal of this empirical study. The goal of electronic banking is to increase customer happiness and lessen crowding in bank lobby areas. Banks have not adequately utilized these facilities despite their introduction. Customers' unhappiness and being crowded in the financial institutions are results of this. To convey different financial services and goods, telecommunication systems and electronic networks are used. A customer can use his or her computer or mobile device to access his or her account and manage several transactions with e-banking. E-banking has become a more important aspect thanks to advancements in financial innovation and inventiveness of the banking sector. In the present day, e-banking has changed everyone's lives. The wave of the information revolution is taken into consideration after the farms and factories revolutions. Prior to the introduction of online banking, customers had to physically visit the credit union to conduct their savings account operations. Many computer-savvy people enjoy using e-banking. Since the number of individuals using the internet has expanded over time and more people are becoming aware of the numerous advantages that online banking offers, its popularity has surged rapidly. TOPSIS method of ranking evaluated based on enhanced ambiguity comparison with weighted average. One of the typical approaches Multiple responses in the process used in TOPSIS to improve problems, reduce uncertainty determining the weight of each response and manageable at the same time A global approach continuously. Magnetic ink character recognition (MICR) technology, Real time gross settlement (RTGS), National electronic fund transfers (NEFT), Cheque truncation system (CTS), Automated teller machines (ATMs), Smartcard banking, Core banking solutions (CBS), Mobile banking and Internet banking. Global financial environment, financial innovations and technologies and Information technology. Electronic Banking and Information Technology. Automated teller machines (ATMs) is got the first rank whereas is the National electronic fund transfer (NEFT) is having the Lowest rank. Electronic Banking and Information Technology. Automated teller machines (ATMs) is got the first rank whereas is the National electronic fund transfer (NEFT) is having the Lowest rank.

Quantum-Chemical Approach to Nuclear Magnetic Resonance of Paramagnetic Systems

Nuclear magnetic resonance (NMR) is a central method for investigating the microscopic structure and dynamics of molecules and materials, with numerous applications in science, technology, and medicine. Computational modelling is indispensable in NMR research due to the indirect nature of NMR information and the rich physical phenomenology behind its observables. While NMR is conventionally used to study diamagnetic systems, paramagnetic NMR (pNMR) of electronically open-shell systems is rapidly gaining importance. This inaugural article concerns the methodology and application of computational molecular science to the observables pNMR, including current challenges and outlook for the future.

Fast floating-point filters for robust predicates

Geometric predicates are at the core of many algorithms, such as the construction of Delaunay triangulations, mesh processing and spatial relation tests. These algorithms have applications in scientific computing, geographic information systems and computer-aided design. With floating-point arithmetic, these geometric predicates can incur round-off errors that may lead to incorrect results and inconsistencies, causing computations to fail. This issue has been addressed using a combination of exact arithmetic for robustness and floating-point filters to mitigate the computational cost of exact computations. The implementation of exact computations and floating-point filters can be a difficult task, and code generation tools have been proposed to address this. We present a new C++ meta-programming framework for the generation of fast, robust predicates for arbitrary geometric predicates based on polynomial expressions. We combine and extend different approaches to filtering, branch reduction, and overflow avoidance that have previously been proposed. We show examples of how this approach produces correct results for data sets that could lead to incorrect predicate results with naive implementations. Our benchmark results demonstrate that our implementation surpasses state-of-the-art implementations.

Applications of Computer Science in Agricultural Engineering

Agricultural engineering is the branch of engineering that deals with the design and exploitation of farm machinery and devices; the location and planning of farm structures; farm drainage, soil management, and erosion control; water supply and irrigation; rural electrification; farm product processing; and deriving renewable energy from agricultural products [...]

Does technology really outpace policy, and does it matter? A primer for technical experts and others

AbstractThis paper reconsiders the outpacing argument, the belief that changes in law and other means of regulation cannot keep pace with recent changes in technology. We focus on information and communication technologies (ICTs) in and of themselves as well as applied in computer science, telecommunications, health, finance, and other applications, but our argument applies also in rapidly developing technological fields such as environmental science, materials science, and genetic engineering. First, we discuss why the outpacing argument is so closely associated with information and computing technologies. We then outline 12 arguments that support the outpacing argument, by pointing to some particular weaknesses of policy making, using the United States as the primary example. Then arguing in the opposite direction, we present 4 brief and 3 more extended criticisms of the outpacing thesis. The paper's final section responds to calls within the technical community for greater engagement of policy and ethical concerns and reviews the paper's major arguments. While the paper focuses on ICTs and policy making in the United States, our critique of the outpacing argument and our exploration of its complex character are of utility to actors in other political contexts and in other technical fields.

NS-SVM: Bolstering Chicken Egg Harvesting Prediction with Normalization and Standardization

Breeding chickens and chicken eggs are poignant, and recent studies have applied computer science to optimize this field, including chicken egg harvesting prediction. However, existing research does not emphasize the importance of data transformation to obtain optimum chicken egg harvesting prediction. This paper proposes the normalization and standardization-bolstered support vector machine (NS-SVM) method, namely normalization, and standardization, to improve the prediction of chicken egg harvest using SVM. First, we obtain the chicken egg dataset from Africa using Kaggle. The problem and solution become urgent, whereas chicken egg production can ease businesspeople to invest in chicken eggs. We adopt the normalization and standardization method from previous research. However, the notation is to differentiate the method from legacy SVM. The dataset has up to 13 features. Then we apply standard pre- processing such as label encoding and random oversampling. We also review the dataset feature using the Pearson correlation coefficient (PCC). We use two SVM kernels: radial basis function (RBF) and the 2nd-degree polynomial. Then we again apply the same model but by applying normalization and standardization. We use cross- validation with 𝑲 = 𝟏𝟎 to measure the Accuracy of the compared models. The results show that normalization and standardization positively affect the prediction model of the two SVM kernels. The model with the highest performance is NS-SVM with a 2nd-degree kernel, namely 𝑨𝒄𝒄𝒖𝒓𝒂𝒄𝒚 = 𝟎. 𝟗𝟗𝟔. At the same time, the model with the lowest performance is SVM with RBF, namely𝑨𝒄𝒄𝒖𝒓𝒂𝒄𝒚 = 𝟎. 𝟗𝟖𝟔. In addition, the results of ROC AUC analysis show that the performance of our model on the imbalanced dataset with a moderate degree is 𝑨𝑼𝑪 = 𝟎.𝟗𝟐𝟕 to 𝟎.𝟗𝟗𝟑.

Performance Portable Batched Sparse Linear Solvers

Solving large number of small linear systems is increasingly becoming a bottleneck in computational science applications. While dense linear solvers for such systems have been studied before, batched sparse linear solvers are just starting to emerge. In this paper, we discuss algorithms for solving batched sparse linear systems and their implementation in the Kokkos Kernels library. The new algorithms are performance portable and map well to the hierarchical parallelism available in modern accelerator architectures. The sparse matrix vector product (SPMV) kernel is the main performance bottleneck of the Krylov solvers we implement in this work. The implementation of the batched SPMV and its performance are therefore discussed thoroughly in this paper. The implemented kernels are tested on different Central Processing Unit (CPU) and Graphic Processing Unit (GPU) architectures. We also develop batched Conjugate Gradient (CG) and batched Generalized Minimum Residual (GMRES) solvers using the batched SPMV. Our proposed solver was able to solve 20,000 sparse linear systems on V100 GPUs with a mean speedup of 76x and 924x compared to using a parallel sparse solver with a block diagonal system with all the small linear systems, and compared to solving the small systems one at a time, respectively. We see mean speedup of 0.51 compared to dense batched solver of cuSOLVER on V100, while using lot less memory. Thorough performance evaluation on three different architectures and analysis of the performance are presented.

Crossing the AI Chasm in Neurocritical Care

Despite the growing interest in possible applications of computer science and artificial intelligence (AI) in the field of neurocritical care (neuro-ICU), widespread clinical applications are still missing. In neuro-ICU, the collection and analysis in real time of large datasets can play a crucial role in advancing this medical field and improving personalized patient care. For example, AI algorithms can detect subtle changes in brain activity or vital signs, alerting clinicians to potentially life-threatening conditions and facilitating rapid intervention. Consequently, data-driven AI and predictive analytics can greatly enhance medical decision making, diagnosis, and treatment, ultimately leading to better outcomes for patients. Nevertheless, there is a significant disparity between the current capabilities of AI systems and the potential benefits and applications that could be achieved with more advanced AI technologies. This gap is usually indicated as the AI chasm. In this paper, the underlying causes of the AI chasm in neuro-ICU are analyzed, along with proposed recommendations for utilizing AI to attain a competitive edge, foster innovation, and enhance patient outcomes. To bridge the AI divide in neurocritical care, it is crucial to foster collaboration among researchers, clinicians, and policymakers, with a focus on specific use cases. Additionally, strategic investments in AI technology, education and training, and infrastructure are needed to unlock the potential of AI technology. Before implementing a technology in patient care, it is essential to conduct thorough studies and establish clinical validation in real-world environments to ensure its effectiveness and safety. Finally, the development of ethical and regulatory frameworks is mandatory to ensure the secure and efficient deployment of AI technology throughout the process.

Networks of Migrants’ Narratives: A Post-authentic Approach to Heritage Visualisation

Digital tools, technologies, and infrastructures have increasingly shaped how knowledge is understood, created, managed, maintained, and shared. In sectors such as cultural heritage, for example, curators and scholars now widely apply computer science approaches to their collections for tasks such as enriching content and providing users with visual access. Although there has been an increasing interest in critical digital visual design and cultural heritage, what still seems to be largely missing is a problematised and critical approach to the application of these techniques. Drawing on critical posthumanities, in this article I propose a new critical framework, the post-authentic framework to digital objects and cultural heritage. The framework advocates transparency and openness as well as the active and reflexive participation of the scholar/curator in the process of knowledge production. To exemplify how the post-authentic framework may be applied to digital research, I explore two use cases: critical visualisation design and critical digital heritage research. For the first use case, I examine the design choices for developing the tool DeXTER, an interactive visualisation app that allows users to explore enriched cultural heritage material interactively. I specifically emphasise the challenges facing product design, with a focus on visualising the ambiguities and uncertainties of Network Analysis and Sentiment Analysis. For the second use case, I explore the potential of DeXTER for testing hypotheses on large textual collections, for example by accessing the layers of meaning attached to referential entities. The use case is the Italian American labour movement from 1898 to 1936. The article concludes with key concepts and methods for applying the post-authentic framework to digital heritage practices and knowledge creation more widely.

Deriving of the Standard Machine Name Programmatically A Study from the Perspective of Computational Languages

This paper is a joint research between linguistic sciences and applied computer sciences, in order to introduce the linguistic phenomenon to digital computer science within what is known as (computational languages). The paper dealt with making a computer program to derive the Arabic machine's name in standard derivation with all its morphological fluctuations, whether It is the correct or the faulty one. The applied technique has been able to program the morphological law in a computerized algorithmic technique. So that it performs the exchange process and its requirements of explaining or substituting or others, as it simulates the user of the Arabic language in the production of an infinite number of standard machine names according to what the program user enters. This step is a confident beginning, Allah Almighty willing, for new programs in the service of Arabic language : studying, teaching and using.

Ontogeny of collective behaviour.

During their lifetime, superorganisms, like unitary organisms, undergo transformations that change the machinery of their collective behaviour. Here, we suggest that these transformations are largely understudied and propose that more systematic research into the ontogeny of collective behaviours is needed if we hope to better understand the link between proximate behavioural mechanisms and the development of collective adaptive functions. In particular, certain social insects engage in self-assemblage, forming dynamic and physically connected architectures with striking similarities to developing multicellular organisms, making them good model systems for ontogenetic studies of collective behaviour. However, exhaustive time series and three-dimensional data are required to thoroughly characterize the different life stages of the collective structures and the transitions between these stages. The well-established fields of embryology and developmental biology offer practical tools and theoretical frameworks that could speed up the acquisition of new knowledge about the formation, development, maturity and dissolution of social insect self-assemblages and, by extension, other superorganismal behaviours. We hope that this review will encourage an expansion of the ontogenetic perspective in the field of collective behaviour and, in particular, in self-assemblage research, which has far-reaching applications in robotics, computer science and regenerative medicine. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Industry-research fronts – Private sector collaboration with research institutions in Latin America and the Caribbean

In which research fields is industry involved with research institutions in Latin America and the Caribbean (LAC)? To shed light on this question, we applied bibliographic coupling to 13,000+ research articles and 500,000+ references indexed in Scopus for 1996–2021 as a means of determining the research fronts in which LAC-based research institutions collaborated with knowledge-intensive companies. Fields with higher betweenness centrality were those multidisciplinary, followed by physical (e.g. computer science applications), life (e.g. genetics), health (e.g. public health, environmental and occupational health) and social sciences and humanities (e.g. strategy and management). Furthermore, the period-by-period analysis unveiled a focused venturing into the physical sciences from 1996 to 2002. However, from the 2003–2021 periods, the new fields explored were mainly in the social sciences and humanities. Finally, we identified several unexplored research fronts, particularly in health (e.g. care planning) and the social sciences and humanities (e.g. demography).