Receding horizon temporal logic planning for dynamical systems

Many temporal and modal logic languages can be regarded as subsets of first order logic, i.e. the semantics of a temporal logic formula is given as a first order condition on points of the underlying models (Kripke structures). Often the set of possible models is restricted to models which are trees. A temporal logic language is (first order) expressively complete, if for every first order condition for a node of a tree there exists an equivalent temporal formula which expresses the same condition. In this paper expressive completeness of the temporal logic language with the set of operators U (until), S (since), and X k (k-next) is proved, and the result is extended to various other tree-like structures.

Scientists today rely on advances in computer science, mathematics, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to meet these needs and to advance research in such areas as global climate change, combustion, fusion energy, nanotechnology, biology, and astrophysics.

Welcome to the proceedings of the 2023 International Conference on Advances in Computer Science and Engineering Technology (ACSE 2023), held from July 29 to 30 in Guangzhou, China. These proceedings are a compilation of the valuable research contributions and innovative ideas presented during the conference, showcasing the latest advancements in the fields of computer science and engineering technology.As we navigate the complexities of the modern world, computer science and engineering technology have emerged as indispensable tools in addressing challenges and creating new possibilities. Our collective efforts, expertise, and willingness to embrace change are vital in harnessing the potential of these transformative fields. ACSE 2023 provided a unique platform for researchers, academicians, professionals, and industry experts to come together and exchange their insights, experiences, and discoveries. The conference aimed to foster interdisciplinary discussions, explore emerging trends, and promote collaboration among individuals from various domains within the realm of computer science and engineering technology.This volume features a diverse collection of papers covering a wide range of topics, including but not limited to Artificial Intelligence, Machine Learning, Engineering and Simulation, Optimization, Control, and Algorithms and more. The contributions presented here reflect the dedication and enthusiasm of the research community in addressing the complex challenges and opportunities that our rapidly evolving technological landscape presents.The peer-reviewed papers presented in these proceedings undergo a rigorous evaluation process, ensuring the quality, originality, and significance of the research work. Each paper represents the author’s commitment to advancing their respective fields and contributing to the global body of knowledge.We extend our sincere gratitude to the conference organizers, the program committee, the reviewers, and all the authors who have contributed to these proceedings. Their hard work and dedication have been instrumental in making ACSE 2023 a success and enriching the academic discourse in the fields of computer science and engineering technology. Special thanks to the members of the Journal of Physics: Conference Series for making this Proceedings published, which ensures that the valuable insights shared during the conference will reach a broader audience and have a lasting impact on the advancement of science and technology.Once again, we welcome you to the proceedings of the 2023 International Conference on Advances in Computer Science and Engineering Technology and hope that this collection of research papers will both inform and inspire you in your own academic and professional pursuits. ACSE 2023 Organizing Committee List of Committee Members are available in this pdf.

As a defacto industry standard, UML has been more and more widely used in software development. However, with the increase of software scale and complexity, deficiencies of UML are increasingly obvious. As the latest version of UML, UML2.0 has been improved and refined base on UML1.x. Whereas UML still lacks precise semantics which is difficult to analyze and validate the described model. In a unified temporal logic framework, temporal logic language XYZ/E can represent both static semantics and dynamic semantics. In addition, it supports stepwise refinement, model checking, as well as executable code automatically converted. Based on these, a practical scheme is proposed for modeling software with combining UML2.0 and XYZ/E, which also provides a formal basis for analysis and validation of the model.

Graph structured data, called networks, can represent many economic activities and phenomena. Such representations are not only powerful for developing economic theory but are also helpful in examining their applications in empirical analyses. This has been particularly the case recently as data associated with networks are often readily available. While researchers may have access to real-world network structured data, in many cases, their volume and complexities make analysis using traditional econometric methodology prohibitive. One plausible solution is to embed recent advancements in computer science, especially machine learning algorithms, into the existing econometric methodology that incorporates large networks. This chapter aims to cover a range of examples where existing algorithms in the computer science literature, machine learning tools, and econometric practices can complement each other. The first part of the chapter provides an overview of the challenges associated with high-dimensional, complex network data. It discusses ways to overcome them by using algorithms developed in computer science and econometrics. The second part of this chapter shows the usefulness of some machine learning algorithms in complementing traditional econometric techniques by providing empirical applications in spatial econometrics.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

In recent years, the rapid advancements in computer science have spurred the development of various cutting-edge intelligent algorithms. Among these, the transformer, which is built upon a multi-head attention mechanism, is one of the most prominent AI models. The advent of such algorithms has significantly advanced retrosynthesis prediction, though challenges remain in chemical interpretability and real-world deployment. Unlike traditional models, AI-based retrosynthesis prediction systems can automatically extract chemical knowledge from vast datasets to forecast retrosynthesis pathways. This review provides a comprehensive overview of modern intelligent algorithms applied to retrosynthesis prediction, with a particular focus on artificial intelligence techniques. We begin by discussing key deep learning models, then explore available chemical reaction datasets and molecular representations. The discussion extends to the latest state-of-the art in AI-assisted retrosynthesis models, including template-based, template-free, and semi-template-based approaches. Finally, we compare these models across various classifications, highlighting several challenges and limitations of current methods, and suggesting promising directions for future research.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Grand Challenge Problems have been used to catalyze advances in computer science, engineering, environmental science, and world health.

Abstract. With the onset of new satellite radar constellations (e.g. Sentinel-1) and advances in computational science (e.g. grid computing) enabling the supply and processing of multi-mission satellite data at a temporal frequency that is compatible with real-time flood forecasting requirements, this study presents a new concept for the sequential assimilation of Synthetic Aperture Radar (SAR)-derived water stages into coupled hydrologic-hydraulic models. The proposed methodology consists of adjusting storages and fluxes simulated by a coupled hydrologic-hydraulic model using a Particle Filter-based data assimilation scheme. Synthetic observations of water levels, representing satellite measurements, are assimilated into the coupled model in order to investigate the performance of the proposed assimilation scheme as a function of both accuracy and frequency of water level observations. The use of the Particle Filter provides flexibility regarding the form of the probability densities of both model simulations and remote sensing observations. We illustrate the potential of the proposed methodology using a twin experiment over a widely studied river reach located in the Grand-Duchy of Luxembourg. The study demonstrates that the Particle Filter algorithm leads to significant uncertainty reduction of water level and discharge at the time step of assimilation. However, updating the storages of the model only improves the model forecast over a very short time horizon. A more effective way of updating thus consists in adjusting both states and inputs. The proposed methodology, which consists in updating the biased forcing of the hydraulic model using information on model errors that is inferred from satellite observations, enables persistent model improvement. The present schedule of satellite radar missions is such that it is likely that there will be continuity for SAR-based operational water management services. This research contributes to evolve reactive flood management into systematic or quasi-systematic SAR-based flood monitoring services.

The advances in computer science & technology have gone to new levels. The process of computational technology and ubiquitous computing is expanding exponentially daily. The computer system & its related inventions have become an integral part of our lives. People & services are migrating towards clouds and decentralized platforms. Nowadays, commerce & finance on the Internet rely on trusted third parties like banks to process electronic online payments. Though it fits well with most transactions, it still suffers from the inherent weakness of trust-based models. Blockchain Technology- the technology behind the cryptocurrency Bitcoin is buzzing a lot nowadays to invent and witness the future of data storage & processing in an efficient, decentralized, tamper-proof, and peer-to-peer (P2P) network. Nowadays, the use of blockchain is not confined to crypto-currencies only. This revolutionary technology is drawing its impact & use in many fields and applications. Primarily, a blockchain network can be used for storing, sharing & transparently transferring data without the intervention of third parties and other intermediaries. In a blockchain network, blocks are added using a consensus algorithm & connected cryptographically. Hence it is merely impossible to delete and modify the content of blocks stored in a blockchain network. Other advantages of this technology include consistency, security, transparency, distributed ledger, decentralized network, etc. This paper systematically reviews the work accomplished by many researchers for the past 11 years. Specifically, the application & impact of blockchain technology in various fields like crypto currencies, the health sector, e-governance, banking, finance, and food supply management systems have been discussed, and a projection of a novel application of the same technology has been proposed.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.