Computer Applications Research Articles

Celebrating Computer Applications in Engineering Education

Celebrating Computer Applications in Engineering Education

Unsupervised co-generation of foreground–background segmentation from Text-to-Image synthesis

Text-to-Image (T2I) synthesis is a challenging task requiring modelling both textual and image domains and their relationship. The substantial improvement in image quality achieved by recent works has paved the way for numerous applications such as language-aided image editing, computer-aided design, text-based image retrieval, and training data augmentation. In this work, we ask a simple question: Along with realistic images, can we obtain any useful by-product (e.g. foreground/background or multi-class segmentation masks, detection labels) in an unsupervised way that will also benefit other computer vision tasks and applications?. In an attempt to answer this question, we explore generating realistic images and their corresponding foreground/background segmentation masks from the given text. To achieve this, we experiment the concept of co-segmentation along with GAN. Specifically, a novel GAN architecture called Co-Segmentation Inspired GAN (COS-GAN) is proposed that generates two or more images simultaneously from different noise vectors and utilises a spatial co-attention mechanism between the image features to produce realistic segmentation masks for each of the generated images. The advantages of such an architecture are two-fold: (1) The generated segmentation masks can be used to focus on foreground and background exclusively to improve the quality of generated images, and (2) the segmentation masks can be used as a training target for other tasks, such as object localisation and segmentation. Extensive experiments conducted on CUB, Oxford-102, and COCO datasets show that COS-GAN is able to improve visual quality and generate reliable foreground/background masks for the generated images.

Thermodynamic linear algebra

AbstractLinear algebra is central to many algorithms in engineering, science, and machine learning; hence, accelerating it would have tremendous economic impact. Quantum computing has been proposed for this purpose, although the resource requirements are far beyond current technological capabilities. We consider an alternative physics-based computing paradigm based on classical thermodynamics, to provide a near-term approach to accelerating linear algebra. At first sight, thermodynamics and linear algebra seem to be unrelated fields. Here, we connect solving linear algebra problems to sampling from the thermodynamic equilibrium distribution of a system of coupled harmonic oscillators. We present simple thermodynamic algorithms for solving linear systems of equations, computing matrix inverses, and computing matrix determinants. Under reasonable assumptions, we rigorously establish asymptotic speedups for our algorithms, relative to digital methods, that scale linearly in matrix dimension. Our algorithms exploit thermodynamic principles like ergodicity, entropy, and equilibration, highlighting the deep connection between these two seemingly distinct fields, and opening up algebraic applications for thermodynamic computers.

Role of Information Technology in Agriculture : A Review

Information Technology (IT) is the application of computers and telecommunications equipment to store, retrieve, transmit and manipulate data, often in the context of a business, education or other enterprise. This paper reviewed the India’s IT Industry and in addition studied the Impact of IT on the Indian Agriculture. To improve the quality of agricultural products and production using information technology that requires efficiency and information in all sectors of agriculture. Information technology support new methods and ideas for precision and healthy agriculture used computers in farm, climate or weather forecasting, use of method and materials and kind of crops. In this paper I tried to find how information technology is useful for making choices to setting goals, improve planning and produce better agriculture products and study the key elements and basic issues of information technology in agriculture.

Qubit: The Leap into Quantum Computation

Abstract. This article delves into the fundamental aspects of qubits in quantum computation, emphasizing their coordination, mathematical representation through the Bloch Sphere, and the unique advantages and challenges of superconducting, trapped ion, and photonic qubits. It highlights the transformative potential of quantum algorithms in solving complex problems in cryptography and information security, while addressing key sources of quantum errors such as decoherence and quantum noise. The study discusses advanced error correction methods and underscores the necessity of improving qubit coherence, stability, scalability, and integration for the practical application and commercialization of quantum computers. Ongoing research and collaboration are deemed essential for overcoming technical challenges and unlocking the full potential of quantum computation across various industries.

IEEE Computer Graphics and Applications

IEEE Computer Graphics and Applications

Option pricing under stochastic volatility on a quantum computer

We develop quantum algorithms for pricing Asian and barrier options under the Heston model, a popular stochastic volatility model, and estimate their costs, in terms of T-count, T-depth and number of logical qubits, on instances under typical market conditions. These algorithms are based on combining well-established numerical methods for stochastic differential equations and quantum amplitude estimation technique. In particular, we empirically show that, despite its simplicity, weak Euler method achieves the same level of accuracy as the better-known strong Euler method in this task. Furthermore, by eliminating the expensive procedure of preparing Gaussian states, the quantum algorithm based on weak Euler scheme achieves drastically better efficiency than the one based on strong Euler scheme. Our resource analysis suggests that option pricing under stochastic volatility is a promising application of quantum computers, and that our algorithms render the hardware requirement for reaching practical quantum advantage in financial applications less stringent than prior art.

Design and implementation of the dual-center programming platform for ternary optical computer and electronic computer

In order to utilize the advantages of optical computing and promote the application and popularization of Ternary Optical Computer (TOC), this paper proposes a dual-center programming model consisting of electronic processor and optical processor, presents the theory and technologies of the dual-center model in detail, and for the first time explains the SAN ZHI GUANG (SZG) file chain technology, gives the implementation method of the dual-center model. The model tries to effectively manage the resources of optical processor and solve the problem of the distance and network connection mode of using the TOC. Experimental results show that the dual-center model is correct and the implementation method is feasible. It can improve the usability of the TOC and further simplify the TOC programming process, and makes common users apply the TOC and electronic computer to work cooperatively for the same task.

Thought-Controlled Computer Applications: A Brain–Computer Interface System for Severe Disability Support

This study introduces an integrated computational environment that leverages Brain–Computer Interface (BCI) technology to enhance information access for individuals with severe disabilities. Traditional assistive technologies often rely on physical interactions, which can be challenging for this demographic. Our innovation focuses on creating new assistive technologies that use novel Human–Computer interfaces to provide a more intuitive and accessible experience. The proposed system offers four key applications to users controlled by four thoughts: an email client, a web browser, an e-learning tool, and both command-line and graphical user interfaces for managing computer resources. The BCI framework translates ElectroEncephaloGraphy (EEG) signals into commands or events using advanced signal processing and machine learning techniques. These identified commands are then processed by an integrative strategy that triggers the appropriate actions and provides real-time feedback on the screen. Our study shows that our framework achieved an 82% average classification accuracy using four distinct thoughts of 62 subjects and a 95% recognition rate for P300 signals from two users, highlighting its effectiveness in translating brain signals into actionable commands. Unlike most existing prototypes that rely on visual stimulation, our system is controlled by thought, inducing brain activity to manage the system’s Application Programming Interfaces (APIs). It switches to P300 mode for a virtual keyboard and text input. The proposed BCI system significantly improves the ability of individuals with severe disabilities to interact with various applications and manage computer resources. Our approach demonstrates superior performance in terms of classification accuracy and signal recognition compared to existing methods.

Doubly Optimal Parallel Wire Cutting without Ancilla Qubits

A restriction in the quality and quantity of available qubits presents a substantial obstacle to the application of near-term and early fault-tolerant quantum computers in practical tasks. To confront this challenge, some techniques for effectively augmenting the system size through classical processing have been proposed; one promising approach is quantum circuit cutting. The main idea of quantum circuit cutting is to decompose an original circuit into smaller subcircuits and combine outputs from these subcircuits to recover the original output. Although this approach enables us to simulate larger quantum circuits beyond physically available circuits, it needs classical overheads quantified by two metrics: the sampling overhead in the number of measurements to reconstruct the original output, and the number of channels in the decomposition. Thus, it is crucial to devise a decomposition method that minimizes both of these metrics, thereby reducing the overall execution time. This paper studies the problem of decomposing the n-qubit identity channel, i.e., n-parallel wire cutting, into a set of local operations and classical communication; then we give an optimal wire-cutting method composed of channels based on mutually unbiased bases that achieves minimal overheads in both the sampling overhead and the number of channels, without ancilla qubits. This is in stark contrast to the existing method that achieves the optimal sampling overhead yet with ancilla qubits. Moreover, we derive a tight lower bound on the number of channels in parallel wire cutting without ancilla systems and show that only our method achieves this lower bound among the existing methods. Notably, our method shows an exponential improvement in the number of channels, compared to the aforementioned ancilla-assisted method that achieves optimal sampling overhead. Our work significantly alleviates the additional overheads for the wire-cutting method and may provide essential components for the early success of quantum computing. Published by the American Physical Society 2024

Preface: 6th International Conference on Information Science and Electronic Technology (ISET 2024)

We are pleased to announce that the 2024 6th International Conference on Information Science and Electronic Technology (ISET 2024) was successfully held in Venice, Italy during September 07-08, 2024. The objective of this conference is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in information science, computer applications, mechatronics, electrical engineering, and electronic technology. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations, and to find global partners for future collaboration. There were over 50 participants attended ISET 2024. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and Q&A discussion. Their insightful speeches had triggered heated discussion in the conference. Every participant praised this conference for disseminating useful and insightful knowledge. We would like to acknowledge all of those who have supported ISET 2024. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the organizing committee for their valuable advices in the organization and helpful peer review of the papers. The Conference Scientific Committee Venice, Italy

Computer Models Assist Innovative Design of Graphic Arts

In order to study the theory and application of computer aided design (CAD) related to the composition of art, the theory of symbolic matrix was introduced to realize the purpose of the study of the interaction between perceptual and rational problems. In this paper, the original image was extracted from the design object, and the transformation between the original image and the symbol matrix was realized by the correspondence with the elements in the matrix. Based on the research route, four kinds of mathematical models were established, namely random distribution, symmetric distribution, central diffusion, and reorganization. By applying the mathematical model constructed in this paper, the picture was transformed, the combination of various styles of graphics was added, and how to put the simple image picture into a meaningful integrated image picture was discussed. The computer-aided design method of the existing verification examples was summarized in this paper, and the design method was accurate and effective. Compared with traditional graphic art design methods, the computer-aided design method mentioned in the paper has the following advantages. Computer-aided design can quickly process and analyze images, convert and combine them through mathematical models and algorithms, greatly saving designers time and energy. By introducing symbol matrix theory and establishing various mathematical models, computer-aided design can provide diverse graphic combinations and style transformations, helping designers explore more innovative design solutions.

Enabling large-scale and high-precision fluid simulations on near-term quantum computers

Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method “Iterative-QLS” that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation. The Poiseuille flow simulation achieved a relative error of less than 0.2%, and the unsteady acoustic wave simulation solved a 5043-dimensional matrix. We emphasize the utilization of the quantum–classical hybrid approach in applications of near-term quantum computers. By adapting to quantum hardware constraints and offering scalable solutions for large-scale CFD problems, our method paves the way for practical applications of near-term quantum computers in computational science.

IEEE Computer Graphics and Applications

IEEE Computer Graphics and Applications

Point Cloud Completion: A Survey.

Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of articles on point cloud completion untill August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. Finally, we discuss challenges faced by the research community and future research directions.

Effectiveness of Computer Application in Improving Reading Skills in Chinese Language and Towards Post-Attitudes as Home-based Learning

Background: As technology continues to advance, language acquisition methodologies have increasingly been integrated into computer-assisted language learning (CALL) systems. In the context of Chinese language acquisition, characters are structured in three phases: the overall character, its components, and its strokes. Proficiency in identifying and distinguishing individual characters hinges upon understanding their structural composition. Objective: This study aims to explore the impact of a computer application on Chinese language reading skills and students' perceptions regarding the utilization of computer applications for home-based learning. Method: A total of 60 students engaged in home-based learning using a designated computer application were involved in the study. Employing a quantitative approach with a quasi-experimental design, the study assessed the effects of the intervention. Results and Conclusion: Following one month of home-based learning through computer applications, participants exhibited higher gain scores in reading skill tests, albeit the differences were not statistically significant. Students expressed a preference for and perceived greater ease in acquiring reading skills through computer applications compared to traditional methods. Furthermore, the integration of computer applications in teaching and learning processes demonstrated the potential to enhance students' motivation, interest, and confidence in language acquisition, albeit without a notable impact on attention levels. The study underscores the pedagogical promise of Computer-Assisted Language Learning (CALL) and advocates for further research endeavors in this domain.

Photonic counterdiabatic quantum optimization algorithm

One of the key applications of near-term quantum computers has been the development of quantum optimization algorithms. However, these algorithms have largely been focused on qubit-based technologies. Here, we propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm reduces the required quantum operations for optimization compared to adiabatic protocols. This reduction enables us to tackle non-convex continuous optimization within the near-term era of quantum computing. Through illustrative benchmarking, we show that our approach can outperform existing state-of-the-art hybrid adiabatic quantum algorithms in terms of convergence and implementability. Our algorithm offers a practical and accessible experimental realization, bypassing the need for high-order operations and overcoming experimental constraints. We conduct a proof-of-principle demonstration on Xanadu’s eight-mode nanophotonic quantum chip, successfully showcasing the feasibility and potential impact of the algorithm.

Сегнетоэлектрические материалы в современных вычислениях

Background: Ferroelectric materials, known for their spontaneous electric polarization, are reshaping the landscape of modern computing. These materials have unique qualities, such as non-volatility, high-speed operation, and energy efficiency, which are critical for advancing modern computer technology. Objective: This study intends to investigate integrating ferroelectric materials into current computer systems, emphasizing to improve memory devices and processors and solve the accompanying technological obstacles and possibilities. Methods: A thorough analysis of existing literature and experimental data was carried out to determine the capabilities and limitations of ferroelectric materials in computing applications. Key performance indicators examined include polarization retention, energy consumption, scalability, and integration with existing semiconductor technology. Results: The results show that ferroelectric materials considerably increase memory device performance and efficiency by allowing quicker write/read operations and lowering power use. However, concerns such as material deterioration, data retention, and integration complexity with silicon-based technology remain. Conclusion: Ferroelectric materials provide exciting prospects for the next generation of computer technology. While they provide significant gains in memory and processing power, addressing the technological obstacles is critical to their effective adoption into mainstream computer applications. Further research and development are needed to solve these issues and fully realize the promise of ferroelectric materials in improving computer performance.

Effectiveness of Using Accounting Computer Applications in Accounting Learning

Effectiveness of Using Accounting Computer Applications in Accounting Learning

Undrained Shear Strength Mapping of Al-Khalis Districts: A Geotechnical GIS Approach

A geographic information system is an integrated collection of computer applications and materials that it is employed to assess geographic relationships, model spatial processes, and analyze and arrange geographic data. The gathering, organizing, and analysis of geographic data are made easier with the use of a geographic information system (GIS). Information systems pertaining to geography Thus, it is employed in the gathering, examination, assessment, updating, and presentation of geographic data. This study dealt with Al-Khalis District, one of the five districts of Diyala Governorate. Al-Khalis District is in the western part of Diyala Governorate and the northern part of the capital, Baghdad, about 55 km north of the capital, Baghdad. 227 boreholes were collected for the entire governorate. The soil was classified, its properties were taken, and they were collected in an Excel sheet. After that, this data was entered into geographic information systems to produce clay shear strength maps. A very helpful soil map that can be used in all aspects through structural and engineering simulation is produced when GIS is used in conjunction with physical and strong geotechnical qualities. Building engineering facilities, roadways, and industrial structures may be made easier with the use of a GIS map. Additionally, it offers a strong tool for extrapolating developed regions. GIS soil maps are anticipated to positively influence the next geotechnical work. The results revealed a significant variance in shear resistance across the depths of the Khalis area, with the soil's strength ranging from weak to medium in the first layer and increasing downward with depth. So, we recommend not going for more than three multi-story buildings unless doing site investigation on the site and making sure it is suitable for that or using a pile foundation. This study aims to give geotechnical engineers and designers a first impression of the type of soil and help them quickly make decisions in terms of the type of foundations and the number of floors for multi-story buildings