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A Model-Driven Requirements engineering Method for human-Centered digitalisation of Agriculture

A Model-Driven Requirements Engineering Method for Human-Cen...

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IEEE International conference on Requirements engineering

作者： Chiara Mannari University of Pisa and National Research Council Pisa Italy

ISBN: (数字)9798350395112

ISBN: (纸本)9798350395129

[Context and motivation] digitalisation in agriculture is a socio-technical process that involves multiple stakeholders with diverse backgrounds and skills, e.g., in farming or technology. Capturing process transformation requires focusing on different dimensions, i.e., system structure, process flow, and actors' goals. Model-driven requirements engineering (MoDRE) techniques can offer the means to elicit and represent this multi-dimensional information. [Question/problem] This research investigates how MoDRE techniques can support the information exchange within interdisciplinary teams involved in the representation of process transformation in digital agriculture. [Principal ideas/results] We propose a method for process modelling in agricultural domains consisting of (1) a set of different diagrams, namely UML, i* and BPMN, (2) a procedure based on guidelines and (3) a tool to support the co-creation of the diagrams within the context of living labs (LLs, i.e., networks of stakeholders involved in a common socio-technical system). We plan to apply the method through action research in the context of 20 European living labs in the agricultural domain and evaluate the method through standard user questionnaires. [Contribution] There is little empirical evidence on using MoDRE techniques in real-world environments. This study fills this gap by developing a method for socio-technical process modelling in co-design contexts.

关键词： Smart agriculture Sociotechnical systems Unified modeling language Focusing Requirements engineering Stakeholders Standards

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Toward Developing Arrays of Active Artificial Hair Cells 39th

Toward Developing Arrays of Active Artificial Hair Cells

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39th IMAC, A conference and exposition on Structural Dynamics, 2021

作者： Davaria, Sheyda Tarazaga, Pablo A. Vibrations Adaptive Structures and Testing Lab Department of Mechanical Engineering Virginia Tech BlacksburgVA United States

ISBN: (纸本)9783030759131

The human cochlea perceives frequencies over a range of 20 Hz to 20 kHz, while a section of the organ of Corti in the cochlea transduces a particular frequency. The cochlear amplifier then amplifies or compresses the signal based on the stimulus level. An individual artificial hair cell (AHC) made of a piezoelectric beam with a feedback controller replicates the cochlear amplifier at a particular frequency. However, to capture a wider frequency range and mimic the tonotopic basilar membrane, an array of AHCs is required. Thus, numerical modeling of an array of active beams with different geometries is the focus of this chapter. With the dynamics of a single active artificial hair cell established, an array of AHCs with self-sensing characteristics is developed. A sample array is modeled using a few sensors to transduce a small set of frequencies in the human speech frequency range. The AHC array is simulated in Simulink and its response is controlled using a nonlinear cubic damping feedback control law that was presented in the authors’ previous work (Davaria, S., Malladi, V.V.S., Motaharibidgoli, S., Tarazaga, P.A.: Cochlear amplifier inspired two-channel active artificial hair cells. Mechanical Systems and Signal Processing, 129, 568–589 (2019)). The response of the active system to complex stimuli with multiple frequencies is analyzed. The design, modeling, and feedback control techniques developed in the current work will be applicable to future sensor arrays and cochlear implants with more beam elements. Because each sensor will utilize the active AHC technology, the total array will offer advantages over a passive series of cantilevers or traditional sensors. © 2022, The Society for Experimental Mechanics, Inc.

关键词： Feedback control

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Leveraging Deep Learning Models for Machine-Generated Text Detection Using Transformer-Based Models

Leveraging Deep Learning Models for Machine-Generated Text D...

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International conference on

作者： P. Suthanthiradevi G Revathy K. Rejini Muthu Lakshmi.V Department of Data Science and Business Systems School of Computing SRM institute of Science and Technology Kattankulathur Chennai Department of Computer science and engineering Vels Institute of science Technology and Advanced studies Chennai Department of Computer Science Engineering Amrita college of Engineering and Technology Nagercoil Department of Computer Science and Engineering St. Joseph's College of Engineering OMR Chennai

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

GPT is a large language model (LLM) derived from natural language processing that can generate a human-like text using machine learning. However, these models raise questions about authenticity and reliability of material, particularly in fields such as journalism, social media, and academia, despite their usefulness for automating text-based tasks. Detecting machine-generated text is thus an important difficulty in ensuring content integrity. This study investigates the use of huge language models as a technique for recognizing machine-generated material. The author proposes a comprehensive detection model by evaluating the language patterns, syntactic structures, and stylistic traits that separate AI-generated literature from human writing. In addition, this research investigate the possibilities of fine-tuning models designed expressly for text identification tasks and evaluate their performance using LLM - Detect AI Generated Text datasets. In digital ecosystems, LLMs are effective at detecting AI-generated text, providing a novel approach for content moderation, academic integrity checks, and synthetic media detection. An increasingly AI-powered future will require a model that can discriminate between human and machine-generated writing in real-time. According to experimental findings, the CNN architecture's design combined with the use of DistilBERT embeddings allows for the effective and efficient classification of AI generated text data, achieving an exceptional 98% accuracy rate.

关键词： Deep learning Deepfakes Accuracy Social networking (online) Biological system modeling Large language models Text detection Writing Transformers Natural language processing

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Research on the Ming Dynasty Dao Robe modeling Method Based on 3D Simulation Technology 7

Research on the Ming Dynasty Dao Robe Modeling Method Based ...

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2021 7th International Forum on Manufacturing Technology and engineering Materials, IFEMMT 2021

作者： Song, Ma Yue, Li Xiaogang, Wang Wuhan Textile University School of Fashion Hubei Wuhan China Wuhan Textile University School of Computer Science and Artificial Intelligence Hubei Wuhan China Research Center of Wuhan Textile and Garment Digital Engeering and Technology

With the rapid development of 3D virtual fitting technology, the study of virtual simulation models of traditional Chinese clothing is of great significance to the establishment of a visual database. In this article, the Ming Dynasty Dao gown is taken as the research object. First, the method of combining historical documents and archeological objects is used to analyze the Dao gown's clothing culture, plane structure, and modeling characteristics in depth. Use virtual simulation technology to establish a three-dimensional model, and simulate and reproduce the color pattern, fabric material, human body proportion, and replica modeling of the robe. In the research of this thesis, the clothing CAD technology is used to restore the historical pattern and the three-dimensional simulation technology to show the effect of the ready-made clothing, and more concretely reproduce the clothing shape and style characteristics of the Ming Dynasty Taoist robe. The modeling method of 3D simulation technology provides new ideas for the reproduction and reproduction of visualized Chinese historical costumes and the promotion of the digital inheritance of Chinese historical costumes. © Published under licence by IOP Publishing Ltd.

关键词： Computer aided design

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Meta-Learning Based Forecasting for Non-Stationary Time Series

Meta-Learning Based Forecasting for Non-Stationary Time Seri...

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Intelligent Computing and human-Computer Interaction (ICHCI), International conference on

作者： Xinying Li Anqi Hong Qiang Gao Ru Zhang School of Electronic and Information Engineering Beihang University Beijing China Wuhan Digital Engineering Institute Wuhan China Planning and Infrastructure Department Shenzhen Air Traffic Management Station of Civil Aviation of China Shenzhen China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

The prediction of non-stationary time series is of great importance in various fields such as finance, meteorology, and network traffic. Analyzing and predicting non-stationary time series can provide decision-making guidance, help forecasters determine future trends, and reduce operational risks across different domains. In this paper, we address long non-stationary time series by dividing them into relatively stationary short-term segments and propose a forecasting model based on meta-learning for non-stationary time series. This meta-learning forecasting model consists of a predictor module and a meta-learner module. Based on this model, We design both a meta-learning based linear AR forecasting model and a meta-learning based nonlinear CNN forecasting model. Experiments on the Dow Jones index data and wind speed data demonstrate that the forecasting model based on meta-learning for non-stationary time series outperforms traditional AR forecasting model and CNN forecasting model in terms of prediction accuracy. Moreover, the meta-learning based nonlinear CNN forecasting model, which extracts the nonlinear features of the time series, performs better than the meta-learning-based linear AR forecasting model.

关键词： Metalearning Adaptation models Computational modeling Wind speed Time series analysis Predictive models Feature extraction Data models Indexes Forecasting

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COMPUTATIONAL PROTOTYPING METHODS TO design human CENTERED PRODUCTS OF HIGH AND LOW LEVEL human INTERACTIONS

COMPUTATIONAL PROTOTYPING METHODS TO DESIGN HUMAN CENTERED P...

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ASME International design engineering Technical conferences / Computers and Information in engineering conference (IDETC-CIE)

作者： Ahmed, Salman Irshad, Lukman Demirel, H. Onan Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA

ISBN: (纸本)9780791859278

Incorporating human factors engineering guidelines early in design has the potential to reduce the cost and product lead-time to market. Also, products that go through strict ergonomics assessments are associated with better comfort and safety ratings. However, designers are often caught in the dilemma of what prototyping method to use when assessing product ergonomics early in design. This is especially problematic during the conceptual design phase before the physical prototypes are available or built. In this research, we explore the computational prototyping dilemma for early design ergonomics assessments from both fidelity and human-product interaction perspectives. In this paper, three computational prototypes with different fidelity levels (low, medium-, and high-fidelity) are compared in their adequacy for evaluating designs that comprise low- to high-levels of human product interactions. We used three computational prototyping strategies: (1) Method 1 is a low-fidelity methodology based a digital sketchpad tool;(2) Method 2 is a medium fidelity methodology consisted of computer-aided design and digital human modeling;and, (3) Method 3 is a high-fidelity methodology composed of computer-aided design, digital human modeling, and surrogate modeling. In order to perform computational ergonomics analyses using above approach, we selected a generic wall mounted cabinet design and a simplified Boeing 767 cockpit model as case studies to illustrate designs that require low- and high-levels of human product interactions. Our preliminary results show that low-, medium- and high-level prototyping strategies produce similar ergonomics outcomes when evaluating low-level human-computer interaction (e.g., cabinet model). On the other hand, both low- and medium fidelity (Method 1 and Method 2) prototyping strategies are limited in terms of providing detailed information about human performance when compared to high-fidelity prototyping (Method 3) in evaluating designs with

关键词： Ergonomics prototyping fidelity level human-product interaction digital human modeling concept design

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Social Equality-Aware Resource Allocation for Post-Disaster Communication Restoration

Social Equality-Aware Resource Allocation for Post-Disaster ...

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International conference on Computer Communications and Networks (ICCCN)

作者： Jianqing Liu Shangjia Dong Thomas Morris Yuguang Fang Department of Computer Science NC State University Raleigh USA Department of Civil & Environmental Engineering University of Delaware Newark USA Department of Electrical and Computer Engineering University of Alabama in Huntsville Huntsville USA Department of Computer Science City University of Hong Kong PRC

Disasters are constant threats to humankind, and beyond losses in lives, they may cause many implicit yet profound societal issues such as wealth disparity and digital divide. Among those recovery measures in the aftermath of disasters, restoring communication services is of vital importance. Although existing works have proposed many architectural and protocol designs, none of them have taken human factors and social equality into consideration. Recent sociological studies have shown that people from marginalized groups (e.g., low income) are more vulnerable to communication outages. In this paper, we make efforts in integrating human factors – extracted from our collected dataset after Hurricane Harvey in 2017 in Texas, US – into an empirical optimization model to determine strategies for post-disaster communication restoration. We cast the design into a mix-integer non-linear programming problem, which captures the essential features of the design but is proven too complex to be solved. To find approximate solutions, we leverage a suite of convex relaxations and then develop heuristic algorithms to efficiently solve the transformed optimization problem. Based on our collected dataset, we further evaluate and demonstrate how our design could prioritize communication services for vulnerable people and promote social equality compared with an existing modeling benchmark.

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Sensor-Based Optimization of Energy Efficiency in Internet of Things: A Review 1

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International conference on Sustainable Development through engineering Innovations, SDEI 2020

作者： Sharma, Meera Singla, Manish Kumar Nijhawan, Parag Dhingra, Arvind Electrical and Instrumentation Engineering Department Thapar Institute of Engineering and Technology Patiala147004 India Electrical Engineering Department Guru Nanak Dev Engineering College Ludhiana141006 India

ISBN: (数字)9789811595547

ISBN: (纸本)9789811595530

Optimization of energy footprint using clean and eco-friendly renewable energy resources is an ideal design for human–computer interface. The Internet of things is also very helpful in developing sustainable products. digital and IoT twins in product design can help manufacturers determine the energy impact and resource utilization of the equipment they manufacture, as well as determine legality. With smart design, manufacturers can create devices that produce less energy and less waste. They can use digital modeling tools to help manufacturers, correct design errors, and save on maintenance and repair costs to identify potential problems. Organizations can identify ways to improve the Internet of things. The supply chain is intended on the basis of each product line and segment, allowing for the unique product information found in the chain to be fully customized and used in the market. This paper reviews various strategies of optimization of energy requirements in smart houses/buildings by improving device efficiency, and by emphasizing on the necessity of balancing the resources required for the IoT infrastructure and reducing the environmental costs. Optimization through simple design has been adopted as the finest strategy for regulating and planning energy consumption. This sudden increase in usage of IoT technology has impacted vividly on the renewable energy requirements and its consumption efficiencies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Energy efficiency

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Information Express of Soft Bionic Finger Based on Visual Recognition

Information Express of Soft Bionic Finger Based on Visual Re...

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IEEE International conference on Cyborg and Bionic Systems (CBS)

作者： Sai Li Jiarun Wang Xinpeng Li Zixin Huang School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan China Ministry of Education Key Laboratory of Textile Fiber and Products (Wuhan Textile University) Wuhan China State Key Laboratory of New Textile Materials and Advanced Processing Technologies (Wuhan Textile University) Wuhan China

Soft robots have developed rapidly because of their own structure, adaptability and safety, which can be applied in different fields. However, the human robot interaction of soft robots faces enormous challenges. In this paper, we take the soft bionic finger (SBF) as the research object, design a multi chamber SBF, and propose a visual recognition to drive SBF. The bending information of the finger is converted into the information of driving air pressure, and drive the SBF. The SBF can simulate the bending of human finger and replace human finger to express some information. Finally, in the visual bending experiment, it is verified that the error between the bending angle of the human finger and the bending angle of the SBF is within a certain allowable range. It shows the feasibility of driving SBF to express information based on visual recognition, and also reflects strong human robot interaction.

关键词： Deformable models Visualization Computational modeling Fingers human-robot interaction Bending Soft robotics

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Comparison of 3D Scene Construction Technologies in Virtual Tourism

Comparison of 3D Scene Construction Technologies in Virtual ...

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2021 International conference on Culture-Oriented Science and Technology, ICCST 2021

作者： Wang, Yishuxun Wang, Hanxi Wuhan University of Technology Key Laboratory of Digital Stage Design and Service Culture and Tourism Ministry PRC School of Mechanical and Engineering Wuhan China

ISBN: (纸本)9781665442541

This paper studies the 3D scene construction technologies in virtual tourism and analyzes the models and display technology of typical tourism systems at home and abroad. Based on the analysis, it evaluates the systems as a whole and summarizes the problems in the three aspects of the current virtual tourism services: display effect, human-machine interface, and operation model. Moreover, through the comparative analysis of approaches to obtaining material, production difficulty, real-time performance, interactivity level, and other indicators in the implementation of the modeling technology involved in 3D scene construction, this paper proposes a scheme for selecting modeling methods for scene construction based on different needs. In the end, through the comparative analysis of mainstream modeling software in terms of real-time rendering, model fineness, interactivity, and data volume, the paper identifies the software suitable for building complex and simple scenes, providing new solutions and ideas for the development and application of virtual tourism services. © 2021 IEEE.

关键词： Three dimensional computer graphics

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