Search

Crime script analysis as a methodology to analyse criminal processes is underdeveloped. This is apparent from the various approaches in which scholars apply crime scripting and present their cybercrime scripts. The plethora of scripting methods raise significant concerns about the reliability and validity of these scripting studies. In this methodological paper, we demonstrate how object-oriented modelling (OOM) could address some of the currently identified methodological issues, thereby refining crime script analysis. More specifically, we suggest to visualise crime scripts using static and dynamic modelling with the Unified Modelling Language (UML) to harmonise cybercrime scripts without compromising their depth. Static models visualise objects in a system or process, their attributes and their relationships. Dynamic models visualise actions and interactions during a process. Creating these models in addition to the typical textual narrative could aid analysts to more systematically consider, organise and relate key aspects of crime scripts. In turn, this approach might, amongst others, facilitate alternative ways of identifying intervention measures, theorising about offender decision-making, and an improved shared understanding of the crime phenomenon analysed. We illustrate the application of these models with a phishing script. [ABSTRACT FROM AUTHOR]

Accessible tourism has become relevant, generating significant economic and social impacts. Even though the accessible tourism market is rising and presents an excellent business opportunity, this market is largely ignored, as it is challenging to stimulate the flow of accessibility information. Accessible technologies, such as tourism information systems, can be a potential solution, increasing accessibility through communication. However, these solutions are few and tend to fail the integration of users upon development processes. This research aims to present a technological platform to improve accessibility in the tourism industry. The name of this accessible and adaptable technological solution is access@tour by action, and it was created following a user-centered design methodology. This development involved a requirement engineering process based on three crucial stakeholders in accessible tourism: educational institutions, supply agents, and demand agents. The design phase was achieved with the help of a conceptual model based on a unified modeling language. The initial prototype of the solution, created in Adobe XD, implements a wide range of informational and accessibility requirements. Some access@tour by action interfaces outline the design, content, and primary functionalities. By linking technological development, tourism, and social inclusion components, this study highlights the relevance and interdisciplinarity of processes in developing accessible information systems. [ABSTRACT FROM AUTHOR]

Cyberbullying, a widespread issue in digital communication, involves using online platforms to harass or demean individuals. Addressing it effectively requires understanding its manifestations across different linguistic contexts. This study presents a novel approach to cyberbullying detection, exploring its manifestations in seven languages through two distinct research paradigms: monolingual and multilingual scenarios. The monolingual approach focuses on developing and testing detection models within a single language framework. In contrast, the multilingual approach, which has shown superior performance, integrates data from multiple languages to train a unified model. This innovative strategy aims to harness broader linguistic diversity and enhance the model’s generalizability. We utilized three computational models: SONAR+DNN, MUSE+CNN-BiLSTM, and XLM-RoBERTa, with the SONAR+DNN architecture demonstrating the most effective performance. This model combines SONAR’s sentence-level embeddings with the nuanced understanding of DNN, making it particularly adept at handling the complex variations of cyberbullying across languages. Our results indicate that multilingual models perform better, particularly in languages with significant representation, such as Arabic and English. Our evaluation shows that our models consistently outperform the best-recorded results on seven diverse datasets, achieving superior performance in six. This significant achievement underscores the robustness of our approach and marks an essential advancement in cyberbullying detection. [ABSTRACT FROM AUTHOR]

This systematic literature review examines the effectiveness of automated test case generation, optimization, and prioritization methods based on Unified Modeling Language (UML) diagrams. The review summarizes the methods, main contributions, and limitations, and suggests areas for future research. This paper examines various optimization algorithms, model-based testing methods, and UML diagram validation methods to determine how well they perform. The review highlights some issues with the current situation, such as the fact that it only examines a few types of UML diagrams and does not go into great detail about how they work or compare to other diagrams. However, it also suggests ways in which these issues could be addressed in future research. Some of the suggested directions include researching different modeling languages and devising solutions to handle the complexity of system models. Model-based testing should also be combined with optimization and prioritization methods to increase the flexibility and usefulness of research in this field. This article makes no direct comparisons to UML diagrams, but it does provide a thorough discussion of the current state of the art and a list of strategic priorities to advance the field of automated test case generation, optimization, and prioritization. These reviews are useful for both researchers and practitioners because they demonstrate how things are currently done and how they should be done in the future. [ABSTRACT FROM AUTHOR]

This study aims to propose a method for constructing basic digital twin data in South Korea by adhering to international standards and by utilizing publicly available data. Specifically, the study focuses on designing and proposing a digital twin data model for buildings, as building-related digital twin data are the most applicable among the basic digital twin data. To achieve this, the first section provides essential background information, introduces concepts and requirements related to basic digital twin data, and offers a brief overview of City Geography Markup Language (CityGML). The second section explains the methodology and the data used in this study. The third section presents the main findings: the selection of public data (building data) for constructing basic digital twin data, the mapping process using CityGML, and the creation of Unified Modeling Language (UML) diagrams. The fourth section discusses these findings. Finally, the conclusion and recommendations for future research are provided. This approach enhances the accuracy of building-related digital twin data and supports the use of digital twin services in both public and private sectors by enabling various spatial analyses. [ABSTRACT FROM AUTHOR]

Market trends in the space sector suggest a notable increase in satellite operations and market value for the coming decade. In parallel, there has been a shift in the industrial and academic sectors from traditional Document-Based System Engineering to Model-based systems engineering (MBSE) combined with Concurrent engineering (CE) practices. Due to growing demands, the drivers behind this change have been the need for quicker and more cost-effective design processes. A key challenge in this transition remains to determine how to effectively formalize and exchange data during all design stages and across all discipline-specific tools; as representing systems through models can be a complex endeavor. For instance, during the Preliminary design (PD) phase, the integration of system models with external mathematical models for simulations, analyses, and system budgeting is crucial. The introduction of CubeSats and their standard has partly addressed the question of standardization and has aided in reducing overall development time and costs in the space sector. Nevertheless, questions about how to successfully exchange data endure. This paper focuses on formalizing a CubeSat model for use across various stages of the PD phase. The entire process is conducted with the exclusive use of open-source tools, to facilitate the transparency of data integration across the PD phases, and the overall life cycle of a CubeSat. The paper has two primary outcomes: (i) developing a generic CubeSat model using Systems modeling language (SysML) that includes data storage and visualization through the application of Unified modeling language (UML) stereotypes, streamlining in parallel information exchange for integration with various simulation and analysis tools; (ii) creating an end-to-end use case scenario within the Nanostar software suite (NSS), an open-source framework designed to streamline data exchange across different software during CE sessions. A case study from a theoretical academic space mission concept is presented as the illustration of how to utilize the proposed formalization, and it serves as well as a preliminary validation of the proposed formalization. The proposed formalization positions the CubeSat SysML model as the central data source throughout the design process. It also supports automated trade-off analyses by combining the benefits of SysML with effective data instantiating across all PD study phases. [ABSTRACT FROM AUTHOR]

Blockchain technologies can support traceability, transparency and trust among participants. This has primarily been explored in established supply chains and not in the growing use of business networks or ecosystems, which is a notable limitation since supply chains typically are organised with a dominant actor that ensures common information systems and standards that negate blockchain benefits. Hence, this study explores the design of a blockchain-based collaborative framework for resource sharing using smart contracts. These are particularly well-suited for supporting operations in broader networks or ecosystems beyond supply chains with established collaborations and hierarchies. Based on a systematic literature review, a demonstrator framework was developed for stakeholder interactions through a procurement and distribution unit backed with blockchain technology. The framework consists of (a) network architecture to demonstrate partner interactions; (b) rules for network working principles based on supply collaboration requirements; (c) UML diagram to define smart contract interaction sequence; and (d) algorithm for smart contract network verification and validation. Applicability of these smart contracts was verified by deployment on an Ethereum blockchain. The demonstrator framework ensures quality and data authenticity in supply networks, so it is useful for effective resource utilisation in networks where outsourcing and production surpluses are major issues. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) have demonstrated promising in-context learning capabilities, especially with instructive prompts. However, recent studies have shown that existing large models still face challenges in specific information extraction (IE) tasks. Moreover, it could have more effectively utilized various prompts such as instruction tuning, diverse demonstrations of in-context learning, and long-range token sequences for assisting language modeling in understanding context. In this study, we propose DILUIE, a unified information extraction framework based on in-context learning with diverse demonstration examples. DILUIE is encoded with an EVA attention mechanism and incremental encoding technology. Based on the constructed diverse demonstrations, we expand the size of instances efficiently in both instruction tuning and in-context learning to gain insights into the potential benefits of utilizing diverse information extraction datasets. To deepen the understanding of context, we further design three auxiliary tasks to assist in aligning contextual semantics. Experimental results demonstrate that DILUIE achieves 2.23 and 2.53% improvements in terms of Micor-/Macor-F1 on average relative to the current state-of-the-art baseline, which also significantly outperforms the GPT-3.5-turbo in zero-shot settings, and the average token length of achieving the best performance over tasks is around 15k. Furthermore, we observe that in-context learning shows enhanced performance when provided with more demonstrations during multiple-shot instruction tuning (8 k). Additionally, increasing the length of instructions (10 k) can result in a more substantial improvement in the upper limits of scaling for in-context learning. Code is available on https://github.com/Phevos75/DILUIE. [ABSTRACT FROM AUTHOR]

Due to the criticality of software and IT in today's business environment, organisations often align business goals and IT strategies. One alignment method is GQM+Strategies® (GQM+Strategies® is a registered trademark (No. 302008021763 at the German Patent and Trade Mark Office and international registration number IR992843). Although GQM+Strategies employs a vertical refinement tree grid based on rationales to align business goals and IT strategies in each department and throughout the organisation, it allows multiple perspectives. This can lead to strategic problems and risks because the GQM+Strategies grid may be unclear. To address this deficiency, this study defines modelling rules with a metamodel specified using a Unified Modelling Language (UML) class diagram and employs design principles described by Object Constraint Language (OCL) to automatically configure GQM+Strategies grids. These design principles are used in an experiment as the evaluation criteria to assess potential strategic problems and risks. The results confirm that our method has the potential to support the construction of GQM+Strategies grids with a consistent perspective, aiding in the alignment of business goals and IT strategies throughout an organisation. [ABSTRACT FROM AUTHOR]

The exclusion of monolingual natives from cyberspace is a global socioeconomic and cultural problem. Efforts at addressing this problem have been socioeconomic, culminating in training, empowerment, and digital access with the indelible hurt of language inequities. This paper is aimed at the cyber‐inclusion of monolingual natives. Since cyber participation is basically through human interaction with cyber‐applications in a human language, encapsulating these applications for interaction in any human language will help evade the hurt of language inequities. Information retrieval system (IRS) remains a fundamental cyber‐application. Consequently, adopting the design science research methodology, we introduced a lingual agnostic IRS architecture designed on the principle of transparency on user language detection, information translations, and caching. The detailed design of the architecture was done using the unified modeling language. The designed IRS architecture has been implemented using the agile and component‐based software engineering approaches. The resultant lingual agnostic IRS (LAIRS) was evaluated using heuristics and system evaluation methods for parity of language of interaction against the default language and was excellently stable across queries and languages, guaranteeing 86% parity with the default language in the use of other languages for information access and retrieval. Furthermore, it has been shown that LAIRS is the most appropriate IRS to address the problem of language barriers to cyber‐inclusion compared with existing IRSs. [ABSTRACT FROM AUTHOR]

Motivation The current paradigm of deep learning models for the joint representation of molecules and text primarily relies on 1D or 2D molecular formats, neglecting significant 3D structural information that offers valuable physical insight. This narrow focus inhibits the models' versatility and adaptability across a wide range of modalities. Conversely, the limited research focusing on explicit 3D representation tends to overlook textual data within the biomedical domain. Results We present a unified pre-trained language model, MolLM, that concurrently captures 2D and 3D molecular information alongside biomedical text. MolLM consists of a text Transformer encoder and a molecular Transformer encoder, designed to encode both 2D and 3D molecular structures. To support MolLM's self-supervised pre-training, we constructed 160K molecule-text pairings. Employing contrastive learning as a supervisory signal for learning, MolLM demonstrates robust molecular representation capabilities across four downstream tasks, including cross-modal molecule and text matching, property prediction, captioning, and text-prompted molecular editing. Through ablation, we demonstrate that the inclusion of explicit 3D representations improves performance in these downstream tasks. Availability and implementation Our code, data, pre-trained model weights, and examples of using our model are all available at https://github.com/gersteinlab/MolLM. In particular, we provide Jupyter Notebooks offering step-by-step guidance on how to use MolLM to extract embeddings for both molecules and text. [ABSTRACT FROM AUTHOR]

Testing is one of the most time‐consuming and unpredictable processes within the software development life cycle. As a result, many test case optimization (TCO) techniques have been proposed to make this process more scalable. Object Constraint Language (OCL) was initially introduced as a constraint language to provide additional details to Unified Modeling Language models. However, as OCL continues to evolve, an increasing number of systems are being expressed by this language. Despite this growth, a noticeable research gap exists for the testing of systems whose specifications are expressed in OCL. In our previous work, we verified the effectiveness and efficiency of performing the test case prioritization (TCP) process for these systems. In this study, we extend our previous work by integrating the test case minimization (TCM) process to determine whether TCM can also benefit the testing process under the context of OCL. The evaluation of TCO approaches often relies on well‐established metrics such as the average percentage of fault detection (APFD). However, the suitability of APFD for model‐based testing (MBT) is not ideal. This paper addresses this limitation by proposing a modification to the APFD metric to enhance its viability for MBT scenarios. We conducted four case studies to evaluate the feasibility of integrating the TCM and TCP processes into our proposed approach. In these studies, we applied the multi‐objective optimization algorithm NSGA‐II and the genetic algorithm independently to the TCM and TCP processes. The objective was to assess the effectiveness and efficiency of combining TCM and TCP in enhancing the testing phase. Through experimental analysis, the results highlight the benefits of integrating TCM and TCP in the context of OCL‐based testing, providing valuable insights for practitioners and researchers aiming to optimize their testing efforts. Specifically, the main contributions of this work include the following: (1) we introduce the integration of the TCM process into the TCO process for systems expressed by OCL. This integration benefits the testing process further by reducing redundant test cases while ensuring sufficient coverage. (2) We comprehensively analyze the limitations associated with the commonly used metric, APFD, and then, a modified version of the APFD metric has been proposed to overcome these weaknesses. (3). We systematically evaluate the effectiveness and efficiency of OCL‐based TCO processes on four real‐world case studies with different complexities. [ABSTRACT FROM AUTHOR]

Electromyographic (EMG) signals are biomedical signals that represent neuromuscular activities. The EMG signal is neither stationary nor periodic and exhibits complex interference patterns of several single motor unit action potentials (SMUAPs). This study aims to characterize EMG signals concerning firing patterns and other characteristics and to identify whether these MUAP firing patterns present short-range dependencies (SRD) or long-range dependencies (LRD). To do so, we characterized 208 EMG signals in terms of the number of phases, turns and combinations of phases. Then, we performed a statistical comparison of the (more efficient) Variance-time plot against the (less bias) Log-scale diagram for the estimation of the Hurst parameter and detection of LRD. Using these estimators, we managed to detect LRD in a sample taken with needle electrodes. In contrast, the tools used for the dependence identification on signals achieved with surface electrodes did not yield conclusive results on such dependence. [ABSTRACT FROM AUTHOR]

The automatic code generation from software design which is represented by UML diagrams is an essential research issue that could be acquired with high-level productivity and convenience in object-oriented software development. This paper presents the issue of the automatic generation of code model for State Machine with internal transitions represented by UML state diagrams. First, promoting states from state diagram to state objects based on the State Design Pattern. Secondly, Meta Information - Meta Class Information for meta classes (static information for state classes) and Meta Behavior Information for class behavior (dynamic information for state objects) - is construced for code generation. Finally, using the above Meta Information, code model generation rules for state diagram with internal transition are presented and those rules are applied on the context class, abstract state class, and concrete state classes for generating class code models. Executable codes for code models are mapped on Java language. [ABSTRACT FROM AUTHOR]

The missions of complex systems, organizations, or groups can be identified through careful requirements and domain analysis. Mission architecture modeling is a crucial step for enterprise modeling and design. However, mission modeling is lacking from the Unified Architecture Framework (UAF), which system engineers must specify and model from sketch. This paper proposes a Mission Architecture Modeling Language (MissionML). This two‐layer architecture language generalizes the general common and special knowledge from four typical missions as a core layer and mission layer. The elements of the core layer are obtained through slight extensions of the operational layer elements in UAFML, and the elements of the mission layer are derived from the elements in the core layer. Moreover, MissionML is implemented as a UAF profile, incorporating numerous domain concepts in its syntax and semantics for mission modeling. Finally, we use five public case studies to demonstrate learnability and extensibility from the viewpoint of system engineers. [ABSTRACT FROM AUTHOR]

This paper aims to develop a conceptual system architecture utilising the land survey data model (LSDM) to manage spatial information associated with field design for oil and gas projects. A widely accepted design science research approach was used, which includes five phases as the foundation phase, development phase, implementation phase, demonstration phase, and validation phase. The developed system architecture consists of five major components: data classes and categories, a data management system, map servers, a visualisation system, and users. This study utilised Unified Modelling Language (UML) diagrams, such as use case, and sequence diagrams to illustrate the relationship between the developed architecture and the field design process and demonstrate workflow and its interaction with stakeholders. A prototype was developed to demonstrate the viability of developed conceptual system architecture. Furthermore, a study area situated near a mining town Chinchilla at the Western Down Regional Council, Queensland, Australia, was selected to validate the prototype in the real world. This study provides a theoretical contribution towards Industrial Revolution 4.0, aiding enhanced decision-making processes within the oil and gas industry and the more effective management of energy resources. [ABSTRACT FROM AUTHOR]

The grid integration of large-scale photovoltaic and other distributed energy sources is an effective solution for addressing power supply shortages and environmental pollution. However, the widespread adoption of photovoltaics and grid integration presents various technological and management challenges. To fulfill the demands of grid management and ensure safe operations, the exchange of information between different terminals is continuously escalating. Use of diverse communication standards creates the problem of "information islands" among terminals. Hence, a standardized information model is crucial for describing the photovoltaic grid integration business and enhancing the efficiency of related software platform research and development. This study extends the IEC 61970/61968 standards and presents a common information model for the integration of photovoltaic systems into the grid. Initially, the operational procedures for integrating photovoltaic systems into the grid are analyzed, and UML modeling tools are employed for business modeling purposes. Subsequently, leveraging the outcomes of the business modeling and the content of the IEC 61970/61968 standards, the development of the common information model is executed. Lastly, causal analysis is conducted along with the modeling of communication standard extensions specifically targeted for the integration of photovoltaic systems into the grid, culminating in the finalization of the construction of the common information model for photovoltaic grid connection. [ABSTRACT FROM AUTHOR]

Infrastructure facilities that serve the city as a whole and should be considered as a whole should be built in an orderly and planned manner, just as cities are. Infrastructure facilities become obsolete over time. Aging infrastructure facilities may become unserviceable over time. When the need for maintenance and repair arises, it is mandatory to renew or replace infrastructure facilities. In this case, necessary maintenance/repair and renovation works should be completed as soon as possible. These infrastructure facilities may not be transferred to maps in the digital environment and may often be managed with person-oriented information, not institutional. There is a problem for decision makers, namely, that the construction, maintenance, repair and governance of infrastructure facilities cannot be carried out systematically, on time and effectively. The only way to provide such a service is through the combined use of today's informatics, Geographical Information System (GIS) and Global Navigation Satellite System (GNSS) technologies, unlike the classical methods of the past. The aim of the study is to effectively manage the scarce resource of drinking water and its facilities, which are an important component of infrastructure facilities, with a method that uses current mapping technologies and informatics facilities. Especially after Infrastructure for Spatial Information (INSPIRE) and the transformation of Land Administration Domain Model (LADM) to the International Organization for Standardization (ISO) standard, Turkish National Geographic Information System (TNGIS) studies and many academic studies carried out in Türkiye have been modelled with Unified Modelling Language (UML) diagrams in accordance with LADM. Similarly, within the scope of this study, UML diagrams were prepared, and then a GIS database was established. Thanks to field workers, chiefs, engineers and others working on water pipelines, all necessary data, classic, as-built and digital, were gathered. These were collected in different ways in order to conduct spatial and non-spatial analysis in the study area of Trabzon. The most important result from the study is that the entire drinking water infrastructure of Trabzon has been transferred to the system in a structure that allows spatial queries, ensuring that damage detection on water components, maintenance and repair processes are carried out in the shortest time and at the lowest cost. The investigation and application of a sensor-integrated GIS-aided system, making it possible to control and monitor the use of lost and illegal water to be controlled as well as inform consumers who will be affected by possible maintenance and repair, is recommended. [ABSTRACT FROM AUTHOR]

Test Case Generation (TCG) generates various types of tests, including functional tests, performance tests, security tests, and reliability tests to ensure software quality, while Test Case Prioritization (TCP) prioritizes the generated tests. However, the previous studies had challenges, including resource constraints, detecting crucial requirements, and automating the Test Case (TC) process efficiently. Additionally, the process is costlier and takes a maximum time duration that affects the effective performance. Therefore, an effective framework is proposed to overcome such issues by optimizing TCG and TCP processes effectively. The proposed work starts with the generation of a Unified Modeling Language (UML) diagram from historical project source code, which is then converted into a Comma-Separated Value (CSV) format. Then, the feature extraction is performed on this CSV file, followed by optimal TCG using the Entropy-based Locust Swarm Optimization Algorithm (Ent-LSOA). Additionally, factors are extracted and reduced from the historical project source code using Pearson Correlation Coefficient-Generalized Discriminant Analysis (PCC-GDA). Finally, the optimal TCs and selected factors are prioritized with the highest accuracy and recall of 96.89% and 96.92%, respectively using an Interpolated Multiple Time scale Recurrent Neural Network (IMTRNN). Thus, the proposed work outperformed the existing techniques by providing an efficient solution for TCG and TCP in software testing. [ABSTRACT FROM AUTHOR]

Spatial planning plays a crucial role in shaping the future of urban development and land administration. While land registration information is necessary for spatial planning processes, it is also probable that changes in land registration data occur in line with spatial plan decisions. Development of the Land Administration Domain Model (LADM) Edition II It also aimed to extend its existing conceptual model with spatial plan data, considering the close connection between the two systems. The study aims to design a conceptual model for Turkey's spatial planning system within the LADM Turkey country profile context. This article researches the capability of the proposed conceptual model for representing spatial planning data with instance‐level diagrams and the implementation opportunities of a technical model. To demonstrate the functionality of the proposed model, the zoning status certificate, which contains spatial plan and land registration data and is provided to inform about the legal conditions before development, is chosen as the mission. The results show that the LADM Turkey country profile extended with spatial planning system data can represent spatial plan data and be implemented in a technical model to support land administration applications. [ABSTRACT FROM AUTHOR]

Growing global concern over greenhouse gas emissions has led to a demand for understanding and addressing carbon emissions, with China being one of the main contributors to global carbon emissions, committed to reach the carbon peak by 2030. As a result, much previous research has delved into the drivers of carbon emissions in China; however, few studies have included new energy factors in the extended STIRPAT model when analysing the data, employed more advanced visualisation techniques such as force-directed diagrams, and explored factors outside of the industrial and energy sectors in determining China's ability to reach their environmental goals. In this study, we use the extended STIRPAT model to analyse a more diverse range of drivers for carbon emissions in China and discuss methods to reach peak carbon emissions through the implementation of environmental policies. Using data from China's 14th Five-Year Plan and Vision 2035 to set up two simulation scenarios, we predict China's carbon emissions, introducing ridge regression to ensure validity, and employing big data and visualisation techniques to aid in interpreting results. Our findings suggest that China needs to implement more stringent environmental policies to meet its commitment to reach peak carbon emissions by 2030, revealing that factors such as per capita arable land area, per capita GDP, the proportion of people living in extreme poverty, the level of tourism development, the use of fossil fuels, and new energy technologies have a significant impact on China's carbon emissions. As such, we can recommend more stringent policies relating to the agricultural, energy, and tourism sectors to help China achieve their goal of carbon peak by 2030. [ABSTRACT FROM AUTHOR]

Efficient and complete medical charting is essential for patient care and research purposes. In this study, we sought to determine if Chat Generative Pre-Trained Transformer could generate cogent, suitable charts from recorded, real-world poison center calls and abstract and tabulate data. De-identified transcripts of real-world hospital-initiated poison center consults were summarized by Chat Generative Pre-Trained Transformer 4.0. Additionally, Chat Generative Pre-Trained Transformer organized tables for data points, including vital signs, test results, therapies, and recommendations. Seven trained reviewers, including certified specialists in poison information and board-certified medical toxicologists, graded summaries using a 1 to 5 scale to determine appropriateness for entry into the medical record. Intra-rater reliability was calculated. Tabulated data was quantitatively evaluated for accuracy. Finally, reviewers selected preferred documentation: original or Chat Generative Pre-Trained Transformer organized. Eighty percent of summaries had a median score high enough to be deemed appropriate for entry into the medical record. In three duplicate cases, reviewers did change scores, leading to moderate intra-rater reliability (kappa = 0.6). Among all cases, 91 percent of data points were correctly abstracted into table format. By utilizing a large language model with a unified prompt, charts can be generated directly from conversations in seconds without the need for additional training. Charts generated by Chat Generative Pre-Trained Transformer were preferred over extant charts, even when they were deemed unacceptable for entry into the medical record prior to the correction of errors. However, there were several limitations to our study, including poor intra-rater-reliability and a limited number of cases examined. In this study, we demonstrate that large language models can generate coherent summaries of real-world poison center calls that are often acceptable for entry to the medical record as is. When errors were present, these were often fixed with the addition or deletion of a word or phrase, presenting an enormous opportunity for efficiency gains. Our future work will focus on implementing this process in a prospective fashion. [ABSTRACT FROM AUTHOR]

System requirements can occasionally be ill-defined and difficult to define. In this case, graphic representation of the system created using semi-formal modelling is advantageous. A smart power grid, for example, includes numerous important needs and function points. We can portray the system functionalities graphically to better grasp the requirements before moving forward with the formal definition. Though, graphic models like Unified Modeling Language (UML) have ambiguity issues as they work on predefined rules. On the other hand, the formal technique uses the correct-by-construction method to guarantee the system's dependability. The formal technique is based on well-practiced mathematical notation. In this article, a smart grid (SG) system based on blockchain (BC) is formally modelled and verified. The system requirements are validated using the formal modelling technique Event-B. To illustrate the system, we first suggest various graphical notations. After that, the notations are translated into a JSON (JavaScript Object Notation) format. Java executable codes are generated in order to validate the JSON schemas. The graphical model is then translated into Event-B specifications and validated using RODIN, a standard tool support. [ABSTRACT FROM AUTHOR]

Requirements Engineering (RE) has undergone several transitions over the years, from traditional methods to agile approaches emphasising increased automation. In many software development projects, requirements are expressed in natural language and embedded within large volumes of text documents. At the same time, RE activities aim to define software systems' functionalities and constraints. However, manually executing these tasks is time-consuming and prone to errors. Numerous research efforts have proposed tools and technologies for automating RE activities to address this challenge, which are documented in published works. This review aims to examine empirical evidence on automated RE and analyse its impact on the RE sub-domain and software development. To achieve our goal, we conducted a Systematic Literature Review (SLR) following established guidelines for conducting SLRs. We aimed to identify, aggregate, and analyse papers on automated RE published between 1996 and 2022. We outlined the output of the support tool, the RE phase covered, levels of automation, development approach, and evaluation approaches. We identified 85 papers that discussed automated RE from various perspectives and methodologies. The results of this review demonstrate the significance of automated RE for the software development community, which has the potential to shorten development cycles and reduce associated costs. The support tools primarily assist in generating UML models (44.7%) and other activities such as omission of steps, consistency checking, and requirement validation. The analysis phase of RE is the most widely automated phase, with 49.53% of automated tools developed for this purpose. Natural language processing technologies, particularly POS tagging and Parser, are widely employed in developing these support tools. Controlled experimental methods are the most frequently used (48.2%) for evaluating automated RE tools, while user studies are the least employed evaluation method (8.2%). This paper contributes to the existing body of knowledge by providing an updated overview of the research literature, enabling a better understanding of trends and state-of-the-art practices in automated RE for researchers and practitioners. It also paves the way for future research directions in automated requirements engineering. [ABSTRACT FROM AUTHOR]

State machines are widely used in industry and academia to capture behavioural models of control. They are included in popular notations, such as UML and its variants, and used (sometimes informally) to describe computational artefacts. In this paper, we present laws for state machines that we prove sound with respect to a process algebraic semantics for refinement, and complete, in that they are sufficient to reduce an arbitrary model to a normal form that isolates basic (action and control) elements. We consider two variants of UML-like state machines, both enriched with facilities to deal with time budgets, timeouts and deadlines over triggers and actions. In the first variant, machines are self-contained components, declaring all the variables, events and operations that they require or define. In contrast, in the second variant, machines are open, like in UML for instance. Laws for open state machines do not depend on a specific context of variables, events and operations, and normalization uses a novel operator for open-machine (de)composition. Our laws can be used in behaviour-preservation transformation techniques. Their applications are automated by a model-transformation engine. [ABSTRACT FROM AUTHOR]

Despite recent efforts by the Artificial Intelligence (AI) community to move towards standardised procedures for documenting models, methods, systems or datasets, there is currently no methodology focused on use cases aligned with the risk-based approach of the European AI Act (AI Act). In this paper, we propose a new framework for the documentation of use cases that we call use case cards, based on the use case modelling included in the Unified Markup Language (UML) standard. Unlike other documentation methodologies, we focus on the intended purpose and operational use of an AI system. It consists of two main parts: firstly, a UML-based template, tailored to allow implicitly assessing the risk level of the AI system and defining relevant requirements, and secondly, a supporting UML diagram designed to provide information about the system-user interactions and relationships. The proposed framework is the result of a co-design process involving a relevant team of EU policy experts and scientists. We have validated our proposal with 11 experts with different backgrounds and a reasonable knowledge of the AI Act as a prerequisite. We provide the 5 use case cards used in the co-design and validation process. Use case cards allows framing and contextualising use cases in an effective way, and we hope this methodology can be a useful tool for policy makers and providers for documenting use cases, assessing the risk level, adapting the different requirements and building a catalogue of existing usages of AI. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

After confirming that formaldehyde (FA) is carcinogenic, many studies were conducted in different countries to investigate this finding. Therefore, according to the dispersion of related studies, a bibliometric review of the current literature was performed with the aim of better understanding the exposure to FA and the resulting health risk, for the first time, using the Scopus database and the two open-source software packages, Bibliometrix R package. After screening the documents in Excel, the data was analyzed based on three aspects including performance analysis, conceptual structure, and intellectual structure, and the results were presented in tables and diagrams. A total of 468 documents were analyzed over period 1977–2023, in which 1956 authors from 56 countries participated. The number of scientific publications has grown significantly from 1977 (n = 1) to 2022 (n = 19). Zhang Y., from the Yale School of Public Health (USA), was identified as the most impactful author in this field. The Science of the Total Environment journal was identified as the main source of articles related to exposure to formaldehyde by publishing 25 studies. The United States and China were the most active countries with the most international collaboration. The main topics investigated during these 46 years included "formaldehyde" and "health risk assessment", which have taken new directions in recent years with the emergence of the keyword "asthma". The present study provides a comprehensive view of the growth and evolution of studies related to formaldehyde and the resulting health risks, which can provide a better understanding of existing research gaps and new and emerging issues. [ABSTRACT FROM AUTHOR]

The object of this study is the business processes of making an investment decision based on determining the state of the investment attractiveness of the enterprise. To support the adoption of investment decisions under the conditions of a fast-moving and dynamic environment, information-analytical support to the algorithm using intelligent information systems has been developed. The relevance of the study is justified by the continuous development of digitization processes, in particular in the financial realm. The traditional approach to the reproduction of management decision-making technology is complemented by the tools and methods of intelligent information systems. In particular, the modeling of the target subject area using UML made it possible to determine the main requirements for the projected information-analytical support (user roles, available options, types of connections and the logic of interaction between them). SQL queries to the information database speed up the process of processing and obtaining the necessary data samples. Business intelligence (BI) tools are used to create interactive reports that provide access to operational financial data. At the stage of making investment decisions, these tools make it possible to study a wide range of analytical data based on the results of the assessment of the investment attractiveness of the enterprise obtained at the previous stage of the developed algorithm. Monitoring of the main indicators of the enterprise’s investment attractiveness is carried out on the basis of a dashboard, an information panel (display) with graphs, tables, and figures that clearly reflect the dynamics and rates of change of the investigated indicators. The results of the use of algorithmic information-analytical support make it possible to quickly prepare and make investment decisions. A visual description of the projected information-analytical support, visual content of the results of investment analysis, the validity of decisions due to the use of reliable retrospective information from an aggregated database [ABSTRACT FROM AUTHOR]

Summary: Voronoi diagram is a versatile geometric structure used in solving many computational geometry problems in the field of image analysis, computer vision, engineering, medicine, molecular biology and various other disciplines. As a result it is a popular research domain. The literature boasts of many elegant and efficient methods for the construction of the Voronoi diagram in the real space. But these algorithms often fail to perform well when applied to the discrete domain. We present in this paper a novel algorithm for the construction of discrete Voronoi diagram using digital geometric concepts that takes care of the geometric perspective of the Voronoi diagram in the discrete domain. Although our technique is more suited for the CPU but by careful use of some cut‐off heuristics we are able to design a parallel programming approach for the construction of the Voronoi diagram making use of the GPU computational power. The speedup of our algorithm is compatible with the popular GPU technique for Voronoi diagram construction, namely, Jump flood algorithm. But since our algorithm uses the geometric perspective for the construction of Voronoi diagram it gives more accurate output and hence requires no correction step as is the case for the Jump flood algorithm. Furthermore, our approach focuses on extensibility, allowing for easy amenability for construction of higher dimensional Voronoi diagram. This ensures that the Voronoi diagram generation process can be adapted and expanded upon to meet specific requirements or incorporate future enhancements. We present an implementation of the proposed algorithm on a GPU using TAICHI language and describe its performance benefits on multiple input sites. [ABSTRACT FROM AUTHOR]

Glycyrrhetinic acid (GA) is a pentacyclic triterpene component in Glycyrrhize glabra L, it has demonstrated an inhibitive effect on high-altitude pulmonary hypertension (HAPH), but the molecular action is still not known. We aimed to explore the mechanism of GA for the treatment of HAPH based on network pharmacology and molecular docking method. Cell experiment validation was also conducted. The targets for GA were screened using the Swiss Target Prediction and Batman databases. The HAPH-related targets were obtained using the GeneCards and OMIM databases. The common targets for diseases and drugs were obtained using a Venn diagram. The core targets were screened using the String database. Then, a component-target-disease diagram and protein–protein interaction (PPI) network mutual assistance diagram were developed using Cytoscape3.9.1 software. GO functional and KEGG pathway enrichment analyses were conducted using the Metascape database. Finally, molecular docking of the target and its corresponding active components were performed using Autodock software. A total of 68 common targets for glycyrrhetinic acid high-altitude pulmonary hypertension were screened out. The core targets include PTGS1, MMP1, SERPINA6, and nitric oxide synthase (NOS2), involving PPAR signal pathway, human cytomegalovirus infection, IL-17 signal pathway, proteoglycans in cancer, and other pathways. The molecular docking affinity was −8.4 kcal·mol−1 in average, indicating that GA has a good binding stability with key target proteins. In the PDGF-BB-induced PASMC proliferation model, PASMC proliferation and the p-p38, p38, p-ERK1/2, and ERK1/2 protein expression were inhibited. The pharmacological mechanism of GA for the treatment of HAPH was characterized by multi-target and multi pathway. GA may serve as a promising therapeutic candidate for HAPH but still needs further in vivo/in vitro experiment. [ABSTRACT FROM AUTHOR]

BACKGROUND: Extracorporeal shock wave therapy, as its potential benefits for various musculoskeletal diseases, has received widespread attention. Increasingly studies have demonstrated that it has excellent effects such as pain relief and functional recovery. However, bibliometric analysis in the domain of extracorporeal shock wave therapy for pain is relatively lacking. OBJECTIVE: To visually analyze the studies related to extracorporeal shock wave therapy for pain and to sort out the knowledge structure and explore its research status as well as hot trends in this field at home and abroad. METHODS: The publications related to extracorporeal shock wave therapy for pain from 2002 to 2022 in Web of Science Core Collection database and CNKI database were searched. Visual analysis using Citespace software was performed to produce the diagrams and interpret their meanings. RESULTS AND CONCLUSION: A total of 2 101 studies were included. The number of documents issued showed a fluctuating upward trend and the United States and China had certain advantages in the number of documents issued. The issuing institutions are mainly universities and hospitals and the issuing authors mostly belonged to independent teams. The exchange between issuing institutions and authors needed to be strengthened and the degree of crossinstitutional and cross-regional cooperation was low. Keyword visual analysis indicated that extracorporeal shock wave therapy has been widely used in musculoskeletal diseases and further studies should focus on multidisciplinary in-depth study and observation of the clinical efficacy of combined therapy. The studies on the topic of extracorporeal shock wave therapy treating pain mainly focus on musculoskeletal diseases, including plantar fasciitis, scapulohumeral periarthritis, and tennis elbow. In recent years, combined treatment with ultrasound-guided injection therapy, traditional Chinese treatment techniques and expansion of new fields become research trends and hotspots of concern. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to examine students' perceptions and comprehension of modeling techniques in the context of structured methodology (SM) and united modeling language (UML). This investigation will make use of a fundamental system that describes a university's registration system. Students frequently encounter projects that require the use of structured techniques and the creation of artifacts like data flow diagrams and entity relationship diagrams for documentation. In contrast, the use case and object data hierarchy are incorporated into the specification of UML artifacts. The students are provided with specification diagrams and instructed to evaluate the two system specifications using a set of 20 questions for each form of modeling artifact and six questions regarding the incorporation of both modeling methodologies. Under the guidance and supervision of a faculty member, students complete the questionnaire in a classroom setting. The study's findings indicated that statistically significant variation was not observed in the vast majority of questions. This discovery provides additional evidence to support the notion that both methodologies may be utilized successfully in undergraduate courses, albeit within the context of distinct courses. This examination places a primary emphasis on the educational instruction environment. However, project managers should exercise caution before adopting Unified Modeling Language (UML) without scrutinizing the unique characteristics and requirements of the given application domain. Future research may examine the adoption of active documentation by student collectives, with an emphasis on comparing agile methodologies to Unified Modeling Language (UML) and Structured Methods (SM). [ABSTRACT FROM AUTHOR]

Within the scope of the current study, the researchers developed activities for middle school students to raise their awareness on the harm of plastics and microplastics, which are detrimental to nature and living things. In addition, through the activities developed, the study aimed to provide students with knowledge of and experience with bioplastics, which have emerged as an alternative to plastic materials and are environmentally friendly. Twelve eighth grade students participated in the current study. The activities developed by the researchers within the framework of the REACT strategy covered a four-week period. The researchers made sure that the activities designed included each step of the REACT strategy (Relating, Experiencing, Applying, Cooperating, Transferring) and the researchers used different tools (mind map, concept map, Vee diagram). The study suggests that activities designed for classroom use should be integrated with tools such as Vee diagram, concept map and mind map in order to increase students' knowledge and awareness about global environmental problems as well as support students' ability to produce solutions to such problems. [ABSTRACT FROM AUTHOR]

Movement behaviour data are compositional in nature, therefore the logratio methodology has been demonstrated appropriate for their statistical analysis. Compositional data can be mapped into the ordinary real space through new sets of variables (orthonormal logratio coordinates) representing balances between the original compositional parts. Geometric rotation between orthonormal logratio coordinates systems can be used to extract relevant information from any of them. We exploit this idea to introduce the concept of pivoting balances, which facilitates the construction and use of interpretable balances according to the purpose of the data analysis. Moreover, graphical representation through ternary diagrams has been ordinarily used to explore time-use compositions consisting of, or being amalgamated into, three parts. Data dimension reduction techniques can however serve well for visualisation and facilitate understanding in the case of larger compositions. We here develop suitable pivoting balance coordinates that in combination with an adapted formulation of compositional partial least squares regression biplots enable meaningful visualisation of more complex time-use patterns and their relationships with an outcome variable. The use and features of the proposed method are illustrated in a study examining the association between movement behaviours and adiposity from a sample of Czech school-aged girls. The results suggest that an adequate strategy for obesity prevention in this group would be to focus on achieving a positive balance of vigorous physical activity in combination with sleep against the other daily behaviours. [ABSTRACT FROM AUTHOR]

This article discusses the use of ternary energy diagrams in computational physics to model systems with energy distributed among three or more forms. The diagrams can show a system's changing energy distribution at fine intervals of time or position. The article provides examples of using ternary energy diagrams in simulations of a mass on a vertical spring, a batted baseball subject to air resistance, and an RLC circuit. The authors also provide resources and tools for introducing ternary energy diagrams to students. [Extracted from the article]

Copyright of Journal of Mathematics, Mechanics & Computer Science is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)