Hasil untuk "Machine design and drawing"

Hardik Gajera, Srinivas S. Pulugurtha

The deployment of autonomous vehicles (AVs) is gaining popularity due to their predicted safety and operational benefits and is driven by advancements in the automobile industry. However, due to the unavailability of fully AVs in the automobile market, users’ perception of their adoption is driven by available knowledge and personal attitudes towards AVs. The effects of users’ perception of policy requirements, the potential effects of AVs, and their familiarity with AV technology on their willingness to ride AVs are investigated in this research. The effect of personal characteristics, such as gender and education level, on users’ perceptions of various aspects related to AVs is also modeled. Stated preference survey data of 2323 respondents from the United States was used for modeling, and three models were developed using confirmatory factor analysis and structural equation modeling (SEM) techniques. The results show that users’ perception of the required policies restricting AVs, the influence of widespread AVs, and their familiarity with AV technology are unrelated. Persons with higher education levels and females were found to give more weight to policies restricting AVs than the potential effects of AVs. Users’ familiarity with AV technology and their perception of the anticipated effects of AVs were found to positively influence their willingness to ride AVs. Even though users favored policies restricting the use of AVs in certain areas, they were still willing to ride them. The findings provide valuable insights for policymakers to restrict the use of AVs in certain areas during their early deployment stages. They can also assist automobile manufacturers in prioritizing and focusing on technical advancements that will increase their acceptance and penetration into the market.

Marius Staat, Martin Gießler, Frank Gauterin et al.

This research paper describes a new method to measure the groove wander effect on real concrete road surfaces using an Internal Drum Test Bench. Groove wander describes lateral forces resulting from interactions between a tire and the road surface texture. To create these lateral forces, the test bench induces a continuous lateral displacement of the tire on a textured road surface. It was found that the groove wander effect could be reproduced on a test bench. The presented method was shown to provide reproducible results that meet the expectations from previous studies. The overall findings of the measurements were that smaller tires and tires with longitudinally aligned profile show higher susceptibility to the groove wander effect.

Satsuya Noda, Yoshimura Shuto, Kunii Haruki

Abstract To realize rough-terrain vehicles with omi-directional motion, the authors have developed the “Mecanum crank,” which consists of Mecanum wheels and “crank wheels.”. To improve the rough-terrain locomotion of the Mecanum crank, this paper describes a design method for the crank legs that enhances the climbable step height. To improve the climbable step height, we focus on four dominant physical phenomena(jamming, hooking of the crank legs, slippage of wheels, and tumbling). Because the climbable step height increases as the vehicle and wheel size increases, this paper discusses the relationship between the maximum climbable step height and the size limitation. Thus, the proposed method maximizes the climbable step height relative to the wheel diameter within the size limitation. The experimental results for step climbing reveal that the proposed method increases the climbable step height from 95% to 160% of the Mecanum wheel diameter. Moreover, we verify that the proposed method does not decrease the feasibility of stair climbing and horizontal-gap traversing.

G. Blelloch

Gajdzik Bożena, Wolniak Radosław, Grebski Wiesław

The paper discusses the changes occurring in the steel industry and related markets as they move towards Industry 4.0. With significant investments in new technologies, steel mills are creating a smart environment for cooperation between producers, distributors, and consumers of steel products. The influence of Industry 4.0 within mills is being transferred to other participants in the steel product chains, and vice versa. The research aimed to determine the impact of Industry 4.0 technologies on the steel product chains in the Polish steel market. The research was conducted in Poland. The obtained database comprised 208 respondents (company executives), including steel mills and steel product manufacturers. Technologies (the pillars of Industry 4.0) are grouped into five technological fields: automation and robotics; warehouse automation; Computer systems, systems integration, mobile technologies, Big Data and IIoT, Blockchain and cybersecurity. Analysis was realized in the three respondent segments representing the steel chain in Poland [RSs]: Producer [P], Distributor [D], and Consumer [C]. The results of the research can help companies improve their steel product chains. The study takes a value chain approach, considering steel production, distribution of steel products, and services for orders and consumers of steel and steel products.

Renkai Ma, Yubo Kou

To manage user-generated harmful video content, YouTube relies on AI algorithms (e.g., machine learning) in content moderation and follows a retributive justice logic to punish convicted YouTubers through demonetization, a penalty that limits or deprives them of advertisements (ads), reducing their future ad income. Moderation research is burgeoning in CSCW, but relatively little attention has been paid to the socioeconomic implications of YouTube's algorithmic moderation. Drawing from the lens of algorithmic labor, we describe how algorithmic moderation shapes YouTubers' labor conditions through algorithmic opacity and precarity. YouTubers coped with such challenges from algorithmic moderation by sharing and applying practical knowledge they learned about moderation algorithms. By analyzing video content creation as algorithmic labor, we unpack the socioeconomic implications of algorithmic moderation and point to necessary post-punishment support as a form of restorative justice. Lastly, we put forward design considerations for algorithmic moderation systems.

I. Maksymov

Ambiguous optical illusions have been a paradigmatic object of fascination, research and inspiration in arts, psychology and video games. However, accurate computational models of perception of ambiguous figures have been elusive. In this paper, we design and train a deep neural network model to simulate human perception of the Necker cube, an ambiguous drawing with several alternating possible interpretations. Defining the weights of the neural network connection using a quantum generator of truly random numbers, in agreement with the emerging concepts of quantum artificial intelligence and quantum cognition, we reveal that the actual perceptual state of the Necker cube is a qubit-like superposition of the two fundamental perceptual states predicted by classical theories. Our results finds applications in video games and virtual reality systems employed for training of astronauts and operators of unmanned aerial vehicles. They are also useful for researchers working in the fields of machine learning and vision, psychology of perception and quantum–mechanical models of human mind and decision making.

Hing Lie, Kachina Studer, Zhen Zhao et al.

Virtual Reality (VR) can support effective and scalable training of psychomotor skills in manufacturing. However, many industry training modules offer experiences that are close-ended and do not allow for human error. We aim to address this gap in VR training tools for psychomotor skills training by exploring an open-ended approach to the system design. We designed a VR training simulation prototype to perform open-ended practice of drilling using a 3-axis milling machine. The simulation employs near “endto-end” instruction through a safety module, a setup and drilling tutorial, open-ended practice complete with warnings of mistakes and failures, and a function to assess the geometries and locations of drilled holes against an engineering drawing. We developed and conducted a user study within an undergraduate-level introductory fabrication course to investigate the impact of open-ended VR practice on learning outcomes. Study results reveal positive trends, with the VR group successfully completing the machining task of drilling at a higher rate (75% vs 64%), with fewer mistakes (1.75 vs 2.14 score), and in less time (17.67 mins vs 21.57 mins) compared to the control group. We discuss our findings and limitations and implications for the design of open-ended VR training systems for learning psychomotor skills.

Luke Stark

Abstract Drawing on prior work in the history and philosophy of statistics, I argue that in many cases analyses powered by artificial-intelligence (AI) techniques such as machine learning (ML) are fundamentally ‘conjectural’: reliant on ex post facto abductive logics often misinterpreted in contemporary machine-learning systems as reliably reproducible truth. Here I relate what Carlo Ginzburg calls ‘the conjectural sciences’ as a historical category to their contemporary instantiation in machine learning and the practice of ‘automated conjecture’. I observe how the automation of physiognomic and phrenological concepts are exemplary of the ways in which discredited conjectural pseudosciences are being revived by today's AI research. Finally, I argue that the conceptual distinction between ‘conjectural’ and ‘empirical’ science can help support contemporary efforts to regulate the design and use of AI systems by providing conceptual and historical justification for the non-development of certain classes of systems intended to automate inference.

Alexa A. Woodward, R. Urbanowicz, Adam C. Naj et al.

Genetic heterogeneity describes the occurrence of the same or similar phenotypes through different genetic mechanisms in different individuals. Robustly characterizing and accounting for genetic heterogeneity is crucial to pursuing the goals of precision medicine, for discovering novel disease biomarkers, and for identifying targets for treatments. Failure to account for genetic heterogeneity may lead to missed associations and incorrect inferences. Thus, it is critical to review the impact of genetic heterogeneity on the design and analysis of population level genetic studies, aspects that are often overlooked in the literature. In this review, we first contextualize our approach to genetic heterogeneity by proposing a high‐level categorization of heterogeneity into “feature,” “outcome,” and “associative” heterogeneity, drawing on perspectives from epidemiology and machine learning to illustrate distinctions between them. We highlight the unique nature of genetic heterogeneity as a heterogeneous pattern of association that warrants specific methodological considerations. We then focus on the challenges that preclude effective detection and characterization of genetic heterogeneity across a variety of epidemiological contexts. Finally, we discuss systems heterogeneity as an integrated approach to using genetic and other high‐dimensional multi‐omic data in complex disease research.

Huixu Dong, Haitao Yang, Shuo Ding et al.

Khmil Roman, Blikharskyy Zinoviy, Vegera Pavlo et al.

The article presents the results of the bearing capacity of reinforced concrete beams with and without damages of internal reinforcement. One of the main elements of the production of the reinforced concrete industry is beams. The analysis of the experimental tests showed that the bearing capacity of reinforced concrete beams with damaged tensile main reinforcement decreases according to control undamaged samples due to the reduction of the reinforcement cross-section. However, the bearing capacity of reinforced concrete beams with tensile main reinforcement Ø20А500C, damaged to the cross-section area equal the rebar Ø16mm is more on 3.7… 24.0% than the bearing capacity of reinforced concrete beams with undamaged Ø16mm rebar. This is due to the non-uniform material properties of used thermally strengthened reinforcement A500C. When during testing the tensile main reinforcement is damaged by drilling a hole, the most damages occur in the core with lower physical and mechanical characteristics. In contrast, the outer thermally strengthened layer with bigger physical and mechanical characteristics is damaged to a lesser extent. The analysis of the obtained results shows that during design of reinforced concrete beams with damaged, it is necessary to consider using thermally strengthened non-uniform steel A500C as tensile main reinforcement.

Sojiro Sugiura, Jayant Unde, Yaonan Zhu et al.

Abstract Wearable body weight support systems can assist individuals with mobility impairments in performing daily living activities with greater ease and independence. However, existing systems have limitations in terms of balancing their strength, compact size, interaction with the ground, and driving. In this paper, we present the High-Strength and Flexible Mechanism (HSFM) designed for body weight support. The HSFM utilizes a coiling truss mechanism to perform flexible transformation between a straight and spiral shape. Its complex linkages create the mechanical constraints of the structure and enhance its stiffness. Additionally, the HSFM achieved a high extension rate, effective wire-driven mechanism, and smooth shift of the grounding point. We provide a detailed description of the HSFM, including the simplest 4-linkage mechanism, its mechanical constraints, and the wire-driven mechanism. Moreover, we conducted parametric analysis and geometric calculation on the link structure. The results justified the mechanical constraints of the HSFM and ensured the high extension rate. Further, its functionality for body weight support was evaluated with the hardware and showed sufficient results in terms of strength, smooth grounding, and wire-driven. This novel mechanism has the potential to develop a wearable body weight support robot enhancing daily living activities such as sit-to-stand transfer and walking.

Di Wu, Shuang Z. Tu, Robert W. Whalin et al.

Detecting drivers’ cognitive states poses a substantial challenge. In this context, cognitive driving anomalies have generally been regarded as stochastic disturbances. To the best of the author’s knowledge, existing safety studies in the realm of human Driving Anomaly Detection (DAD) utilizing vehicle trajectories have predominantly been conducted at an aggregate level, relying on data aggregated from multiple drivers or vehicles. However, to gain a more nuanced understanding of driving behavior at the individual level, a more detailed and granular approach is essential. To bridge this gap, we developed a Data Anomaly Detection (DAD) model designed to assess a driver’s cognitive abnormal driving status at the individual level, relying solely on Basic Safety Message (BSM) data. Our DAD model comprises both online and offline components, each of which analyzes historical and real-time Basic Safety Messages (BSMs) sourced from connected vehicles (CVs). The training data for the DAD model consist of historical BSMs collected from a specific CV over the course of a month, while the testing data comprise real-time BSMs collected at the scene. By shifting our focus from aggregate-level analysis to individual-level analysis, we believe that the DAD model can significantly contribute to a more comprehensive comprehension of driving behavior. Furthermore, when combined with a Conflict Identification (CIM) model, the DAD model has the potential to enhance the effectiveness of Advanced Driver Assistance Systems (ADAS), particularly in terms of crash avoidance capabilities. It is important to note that this paper is part of our broader research initiative titled “Automatic Safety Diagnosis in the Connected Vehicle Environment”, which has received funding from the Southeastern Transportation Research, Innovation, Development, and Education Center.

Devi Andriani, Wahyono Suprapto, Yudy Surya Irawan et al.

Motorcycle users in 2019 reached 133,617,012 units in Indonesia. The impact of a large number of motorcycle certainly attracts the interest of the industry to produce two-wheeled automotive vehicles. The piston is part of the engine that functions as a compression barrier in the combustion chamber, the piston material is aluminum alloy. Therefore, research was carried out on making pistons with investment casting methods, physical and mechanical patterns from 3D printers on pistons. This research starts from drawing the piston using CAD (computer-aided design), making a printed pattern from a 3D Printer machine with PLA (polylactide acid) material. The mold pattern is coated with a mixture of gypsum cement and silica powder. The casting process with a pouring temperature of 750ᵒC and a mold temperature of 200 ᵒC, 250 ᵒC, 300 ᵒC, 350 ᵒC, and 400 ᵒC. The results showed the largest grain size at a mold temperature of 400ᵒC. The highest hardness at 200 ᵒC mold temperature is 47.00 HRB and the lowest hardness at 400 ᵒC mold temperature is 40.56 HRB. The higher the temperature of the mold used, the level of porosity of a material will decrease. This is due to the temperature difference when pouring the molten metal and the lower mold temperature. This makes the metal solidification time longer. The higher the mold temperature, the slower the solidification time, the larger the grain structure, and the decreased hardness.

Han-yin Huang, Cynthia C. S. Liem

Artificial intelligence literature suggests that minority and fragile communities in society can be negatively impacted by machine learning algorithms due to inherent biases in the design process, which lead to socially exclusive decisions and policies. Faced with similar challenges in dealing with an increasingly diversified audience, the museum sector has seen changes in theory and practice, particularly in the areas of representation and meaning-making. While rarity and grandeur used to be at the centre stage of the early museum practices, folk life and museums’ relationships with the diverse communities they serve become a widely integrated part of the contemporary practices. These changes address issues of diversity and accessibility in order to offer more socially inclusive services. Drawing on these changes and reflecting back on the AI world, we argue that the museum experience provides useful lessons for building AI with socially inclusive approaches, especially in situations in which both a collection and access to it will need to be curated or filtered, as frequently happens in search engines, recommender systems and digital libraries. We highlight three principles: (1) Instead of upholding the value of neutrality, practitioners are aware of the influences of their own backgrounds and those of others on their work. By not claiming to be neutral but practising cultural humility, the chances of addressing potential biases can be increased. (2) There should be room for situational interpretation beyond the stages of data collection and machine learning. Before applying models and predictions, the contexts in which relevant parties exist should be taken into account. (3) Community participation serves the needs of communities and has the added benefit of bringing practitioners and communities together.

Philip T. Roundy

Purpose Entrepreneurs are increasingly relying on artificial intelligence (AI) to assist in creating and scaling new ventures. Research on entrepreneurs’ use of AI algorithms (machine learning, natural language processing, artificial neural networks) has focused on the intra-organizational implications of AI. The purpose of this paper is to explore how entrepreneurs’ adoption of AI influences their inter- and meta-organizational relationships. Design/methodology/approach To address the limited understanding of the consequences of AI for communities of entrepreneurs, this paper develops a theory to explain how AI algorithms influence the micro (entrepreneur) and macro (system) dynamics of entrepreneurial ecosystems. Findings The theory’s main insight is that substituting AI for entrepreneurial ecosystem interactions influences not only entrepreneurs’ pursuit of opportunities but also the coordination of their local entrepreneurial ecosystems. Originality/value The theory contributes by drawing attention to the inter-organizational implications of AI, explaining how the decision to substitute AI for human interactions is a micro-foundation of ecosystems, and motivating a research agenda at the intersection of AI and entrepreneurial ecosystems.

Vaško Alan

Graphitic cast irons are the most important and most widely used materials for the production of castings. Increasing requirements for the quality of these castings lead to increased demands on the control of foundry production from raw materials through technological operations to the finished product. An integral part of this control process is structural analysis, because the properties of graphitic cast irons depend mainly on their structure (on the shape, size and number of graphitic particles and on the character of a metal matrix in which graphite occurs).

K. Tzioumis

We introduce a list that offers information on the relation between first names and race or ethnicity. Drawing information from mortgage applications, the list includes 4,250 first names and information on their respective count and proportions across six mutually exclusive racial and Hispanic origin groups. These six categories are consistent with the categories used in the Census Bureau's list on surnames' demographic information. Also, just like the Census Bureau's list of surnames, the list of first names is highly aggregated, so as to not identify any specific individuals. Design Type(s) data integration objective Measurement Type(s) First Name Technology Type(s) digital curation Factor Type(s) ethnic group Sample Characteristic(s) United States of America Design Type(s) data integration objective Measurement Type(s) First Name Technology Type(s) digital curation Factor Type(s) ethnic group Sample Characteristic(s) United States of America Machine-accessible metadata file describing the reported data (ISA-Tab format)

Toshiaki Nishio, Yuichiro Yoshikawa, Takamasa Iio et al.

Abstract The number of isolated elderly people with few opportunities to talk to other people is currently increasing. Research is ongoing to develop talking robots for addressing the situation. The aim of the present study was to develop a talking robot that could converse with elderly people over an extended period. To enable long-duration conversation, we added a previously proposed active listening function for twining the robot dialogue system to prompt the user to say something. To verify the effectiveness of this function, a comparative experiment was performed using the proposed robot system and a control system with identical functions except the active listening function. The results showed that the conversation of the elderly subjects with the proposed robot system was significantly more than that with the control system. The capability of the developed robot system was further demonstrated in a nursing home for the elderly, where its conversation durations with different residents were measured. The results revealed that the robot could converse for more than 30 min with more than half of the elderly subjects. These results indicate that the additional function of the proposed talking robot system would enable elderly people to talk over longer periods of time.