New Approaches to Analyze Gasoline Rationing

In this paper, the relation among factors in the road transportation sector from March, 2005 to March, 2011 is analyzed. Most of the previous studies have economical point of view on gasoline consumption. Here, a new approach is proposed in which different data mining techniques are used to extract meaningful relations between the aforementioned factors. The main and dependent factor is gasoline consumption. First, the data gathered from different organizations is analyzed by feature selection algorithm to investigate how many of these independent factors have influential effect on the dependent factor. A few of these factors were determined as unimportant and were deleted from the analysis. Two association rule mining algorithms, Apriori and Carma are used to analyze these data. These data which are continuous cannot be handled by these two algorithms. Therefore, the two-step clustering algorithm is used to discretize the data. Association rule mining analysis shows that fewer vehicles, gasoline rationing, and high taxi trips are the main factors that caused low gasoline consumption. Carma results show that the number of taxi trips increase after gasoline rationing. Results also showed that Carma can reach all rules that are achieved by Apriori algorithm. Finaly it showed that association rule mining algorithm results are more informative than statistical correlation analysis

Development of the ChatGPT, Generative Artificial Intelligence and Natural Large Language Models for Accountable Reporting and Use (CANGARU) Guidelines

The swift progress and ubiquitous adoption of Generative AI (GAI), Generative Pre-trained Transformers (GPTs), and large language models (LLMs) like ChatGPT, have spurred queries about their ethical application, use, and disclosure in scholarly research and scientific productions. A few publishers and journals have recently created their own sets of rules; however, the absence of a unified approach may lead to a 'Babel Tower Effect,' potentially resulting in confusion rather than desired standardization. In response to this, we present the ChatGPT, Generative Artificial Intelligence, and Natural Large Language Models for Accountable Reporting and Use Guidelines (CANGARU) initiative, with the aim of fostering a cross-disciplinary global inclusive consensus on the ethical use, disclosure, and proper reporting of GAI/GPT/LLM technologies in academia. The present protocol consists of four distinct parts: a) an ongoing systematic review of GAI/GPT/LLM applications to understand the linked ideas, findings, and reporting standards in scholarly research, and to formulate guidelines for its use and disclosure, b) a bibliometric analysis of existing author guidelines in journals that mention GAI/GPT/LLM, with the goal of evaluating existing guidelines, analyzing the disparity in their recommendations, and identifying common rules that can be brought into the Delphi consensus process, c) a Delphi survey to establish agreement on the items for the guidelines, ensuring principled GAI/GPT/LLM use, disclosure, and reporting in academia, and d) the subsequent development and dissemination of the finalized guidelines and their supplementary explanation and elaboration documents.Comment: 20 pages, 1 figure, protoco

Bibliometric Analysis of Publisher and Journal Instructions to Authors on Generative-AI in Academic and Scientific Publishing

We aim to determine the extent and content of guidance for authors regarding the use of generative-AI (GAI), Generative Pretrained models (GPTs) and Large Language Models (LLMs) powered tools among the top 100 academic publishers and journals in science. The websites of these publishers and journals were screened from between 19th and 20th May 2023. Among the largest 100 publishers, 17% provided guidance on the use of GAI, of which 12 (70.6%) were among the top 25 publishers. Among the top 100 journals, 70% have provided guidance on GAI. Of those with guidance, 94.1% of publishers and 95.7% of journals prohibited the inclusion of GAI as an author. Four journals (5.7%) explicitly prohibit the use of GAI in the generation of a manuscript, while 3 (17.6%) publishers and 15 (21.4%) journals indicated their guidance exclusively applies to the writing process. When disclosing the use of GAI, 42.8% of publishers and 44.3% of journals included specific disclosure criteria. There was variability in guidance of where to disclose the use of GAI, including in the methods, acknowledgments, cover letter, or a new section. There was also variability in how to access GAI guidance and the linking of journal and publisher instructions to authors. There is a lack of guidance by some top publishers and journals on the use of GAI by authors. Among those publishers and journals that provide guidance, there is substantial heterogeneity in the allowable uses of GAI and in how it should be disclosed, with this heterogeneity persisting among affiliated publishers and journals in some instances. The lack of standardization burdens authors and threatens to limit the effectiveness of these regulations. There is a need for standardized guidelines in order to protect the integrity of scientific output as GAI continues to grow in popularity.Comment: Pages 16, 1 figure, 2 table

Influence of Higher Modes on Strength and Ductility Demands of Soil-Structure Systems

Due to the inherent complexity, the common approach in analysing nonlinear response of structures with soil-structure interaction (SSI) in current seismic provisions is based on equivalent SDOF systems (E-SDOF). This paper aims to study the influence of higher modes on the seismic response of SSI systems by performing intensive parametric analyses on more than 6400 linear and non-linear MDOF and E-SDOF systems subjected to 21 earthquake records. An established soil-shallow foundation-structure model with equivalent linear soil behaviour and nonlinear superstructure has been utilized using the concept of cone models. The lateral strength and ductility demands of MDOF soil-structure systems with different number of stories, structure-to-soil stiffness ratio, aspect ratio and level of inelasticity are compared to those of ESDOF systems. The results indicate that using the common E-SDOF soil-structure systems for estimating the strength and ductility demands of medium and slender MDOF structures can lead to very un-conservative results when SSI effect is significant. This implies the significance of higher mode effects for soil-structure systems in comparison with fixed-based structures, which is more pronounced for the cases of elastic and low level of inelasticity

Lyapunov-Based Control Strategy for a Single-Input Dual-Output Three-Level DC/DC Converter

This paper proposes a robust control strategy using direct Lyapunov strategy (DLS) for a single-input dual-output three-level dc-dc converter (SIDO-TLC) while the output loads and voltage references are disturbed. The first proceeding is to concurrently focus on the current and voltage dynamics of the converter buck and boost segments for exerting the related variable errors to the DLS-based function. Accordingly, through a comprehensive analysis based on the outcome of this proceeding, the PI controller coefficients allotted to the current reference design process are enabled to reach their maximum robustness capabilities against any output voltage variation. Moreover, the converter reference current tracking-based assessment leads to several smooth hyperbolic curves with their unique geometric properties. Consequently, the alteration trend of these curves facilitates the Lyapunov coefficients to be adjusted commensurate with the dynamic operation of the converter while converging to zero steady-state errors. Using a TMS320F28335 digital signal processor (DSP), disparate experimental results are conducted on the SIDO-TLC to verify the accurate and robust performance of the proposed control strategy.</p

Mathematical Model of Common-Mode Sources in Long-Cable-Fed Adjustable Speed Drives

Motor drive systems with long feeder cables are widely used in mining and energy sectors, such as offshore oil and gas drilling. In recent decades, to prevent issues with electromagnetic interference, power quality standards have been defined for the 2-150 kHz frequency range. In order to comply with these standards, manufacturers need to design filters to avoid exceeding the thresholds set by the standards. An important aspect that needs to be considered is the accurate modeling of currents circulating through common-mode loops. This article addresses this modeling by using a mathematical approach. The power cable's common-mode model is extracted from the measurement data using the finite-element method via finding the effective permittivity of the PVC materials. The common-mode noise sources, including the grid side voltage through the front-end diode rectifier and the output voltage through the rear-end inverter, are both modeled by extracting the Fourier series calculations. Consequently, noise emissions circulating through different common-mode loops are analytically modeled. Through the proposed modeling strategy, the harmonic spectrum of resonances can be precisely analyzed. The results are validated through simulation and experimental data. </p

The Transonics Spoken Dialogue Translator: An aid for English-Persian Doctor-Patient interviews, in Working Notes of the AAAI Fall symposium on Dialogue Systems for Health Communication

In this paper we describe our spoken english-persian medical dialogue translation system. We describe the data collection effort and give an overview of the component technologies, including speech recognition, translation, dialogue management, and user interface design. The individual modules and system are designed for flexibility, and to be able to leverage different amounts of available resources to maximize the ability for communication between medical care-giver and patient