2,756 research outputs found
Gear optimization
The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future
Lost in Translation: When GPT-4V(ision) Can't See Eye to Eye with Text. A Vision-Language-Consistency Analysis of VLLMs and Beyond
Recent advancements in multimodal techniques open exciting possibilities for
models excelling in diverse tasks involving text, audio, and image processing.
Models like GPT-4V, blending computer vision and language modeling, excel in
complex text and image tasks. Numerous prior research endeavors have diligently
examined the performance of these Vision Large Language Models (VLLMs) across
tasks like object detection, image captioning and others. However, these
analyses often focus on evaluating the performance of each modality in
isolation, lacking insights into their cross-modal interactions. Specifically,
questions concerning whether these vision-language models execute vision and
language tasks consistently or independently have remained unanswered. In this
study, we draw inspiration from recent investigations into multilingualism and
conduct a comprehensive analysis of model's cross-modal interactions. We
introduce a systematic framework that quantifies the capability disparities
between different modalities in the multi-modal setting and provide a set of
datasets designed for these evaluations. Our findings reveal that models like
GPT-4V tend to perform consistently modalities when the tasks are relatively
simple. However, the trustworthiness of results derived from the vision
modality diminishes as the tasks become more challenging. Expanding on our
findings, we introduce "Vision Description Prompting," a method that
effectively improves performance in challenging vision-related tasks
Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMs
Large Language Models (LLMs) have demonstrated exceptional natural language
understanding abilities and have excelled in a variety of natural language
processing (NLP)tasks in recent years. Despite the fact that most LLMs are
trained predominantly in English, multiple studies have demonstrated their
comparative performance in many other languages. However, fundamental questions
persist regarding how LLMs acquire their multi-lingual abilities and how
performance varies across different languages. These inquiries are crucial for
the study of LLMs since users and researchers often come from diverse language
backgrounds, potentially influencing their utilization and interpretation of
LLMs' results. In this work, we propose a systematic way of qualifying the
performance disparities of LLMs under multilingual settings. We investigate the
phenomenon of across-language generalizations in LLMs, wherein insufficient
multi-lingual training data leads to advanced multi-lingual capabilities. To
accomplish this, we employ a novel back-translation-based prompting method. The
results show that GPT exhibits highly translating-like behaviour in
multilingual settings.Comment: Paper accepted to EMNLP 202
4,6-Bis[5-methyl-3-(trifluoromethyl)pyrazol-1-yl]pyrimidine
The complete molecule of the the title compound, C14H10F6N6, is generated by crystallographic twofold symmetry, with two C atoms lying on the roatation axis. The dihedral angle between the central and peripheral rings is 25.97 (8)°
Research on a Model of Extracting Persons\u27 Information Based on Statistic Method and Conceptual Knowledge
PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200
Fumigant Activity of Eight Plant Essential Oils Against Workers of Red Imported Fire Ant, Solenopsis invicta
Plant essential oils from eight plant species were tested for their insecticidal activities against the red imported fire ant, Solenopsis invcita, by using a fumigation bioassay. This study reveals that the mortalities after treatment of the workers of red imported fire ants varied according to the classification of workers, oil type, dosage, and exposure time. Among the essential oils tested, strong insecticidal activity was observed with the essential oils of camphor (Cinnamomum camphora), artemisia annua (Artemisia annua), eucalyptus (Eucalyptus globulus), mugwort (Artemisia argyi), and wintergreen (Ilex chinensis). Ant mortalities from chrysanthemum oil (Dendranthema indicum), turpentine oil (Pinus massoniana), and forsythia oil (Forsythia suspense) treatments were significantly lower than those from the previously mentioned five essential oil treatments. This study showed that camphor, artemisia annua, eucalyptus, mugwort, and wintergreen oils may have potential to be used as substitutes for chemical insecticides
6′,7′-Dimethoxy-1′,2′-dihydrospiro[cyclohexane-1,2′-quinazolin]-4′(3′H)-one
In the title compound, C15H20N2O3, prepared from the reaction of 2-amino-4,5-dimethoxybenzonitrile and cyclohexanone, the six-membered diaza ring assumes an envelope conformation. In the crystal, inversion dimers are formed by pairs of N—H⋯O hydrogen bonds. Futher N—H⋯O hydrogen bonds link the dimers into a two-dimensional structure parallel to (001)
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