35 research outputs found
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
The association between animal flesh foods consumption and semen parameters among infertile Iranian men:a cross-sectional study
Clinical perspective: monitoring sodium oxybate-treated narcolepsy patients for the development of sleep-disordered breathing
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
Effects of soilâstructure interaction and lateral design load pattern on performanceâbased plastic design of steel moment resisting frames
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