bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting the Value of Excess in Personal Gaming Desktops
Authors: Long Daniel , Morkos Beshoy , Ferguson Scott 
Published: November 2020

Abstract
A widely held belief in engineering design is that the optimal design is the one that satisfies all requirements at the lowest cost. Recent research has begun challenging this notion by arguing that a system’s total lifetime value may be improved by designing for uncertain future requirements, even after considering additional incurred costs. Excess, the purposeful inclusion of margin beyond what is required for known uncertainties, is the method used in this work for addressing uncertain future requirements. This paper provides evidence that excess can make a system more robust (insensitive to changing requirements) and thereby increase its value. This evidence is drawn from the study from the video game industry data including: console and desktop hardware performance specifications with release dates, video game requirements, and contemporaneous expert suggested gaming desktops over a span of 20 years — from 2001 to mid-2019. Additionally, this paper advances the notion of strategic excess (excess added to a single component) by examining its potential impact on historical systems. The study of strategic excess provides guidance for how one might baseline the appropriate degree of excess inclusion based on technology and requirements trends. The analysis conducted in this paper shows that higher degrees of excess in desktops can increase overall system value, that strategic excess in RAM would have improved system performance by 14% (on average) for 7% of total system cost, and that trends in technology improvement can be used for baselining excess inclusion by suggesting specific performance tiers for CPUs and GPUs.
Characterisation, Design and Experimentation of a Fabric Based Wearable Joint Sensing Device
Authors: Lau Jun Liang , Soh Gim Song 
Published: November 2020

Abstract
The use of conductive fabrics (CF) in the design of wearables for joint sensing has recently received much interest in a wide range of applications such as robotics, rehabilitation, personal wellness, sports, and entertainment. In this paper, we evaluate a new wearable device concept that comprises of a CF strain-voltage sensor embedded as part of an inverted slider-crank mechanism for joint extension sensing. This has the benefit of not requiring anthropometric information from the user to related the joint parameters to the fabric strain readings, as opposed to an existing design. Firstly, we characterize the electromechanical property of a commercially available CF. Secondly, we formulate the geometric synthesis procedure of the joint sensing device as a constrained revolute joint system, where the CF is designed and introduced as an RPR chain to obtain an inverted slider-crank linkage. Lastly, we develop and validate our wearable joint sensing device against an experimental setup that represents an elbow joint. Our concept shows that our proposed joint sensing device can track the elbow extension motion of 140° with a maximum error of 7.66%.
Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction
Authors: Williams Glen , Puentes Lucas , Nelson Jacob , Menold Jessica , Tucker Conrad , McComb Christopher 
Published: November 2020

Abstract
Online data repositories provide designers and engineers with a convenient source of data. Over time, the wealth and type of readily-available data within online repositories has greatly expanded. This data increase permits new uses for machine learning approaches which rely on large, high-dimensional datasets. However, a comparison of the efficacies of attribute-based data, which lends itself well to traditional machine learning algorithms, and form-based data, which lends itself to deep machine learning algorithms, has not fully been established. This paper presents one such comparison for an exemplar dataset. As the efficacy of different machine learning approaches may be dependent on the specific application, this method is intended to lay the groundwork for future studies that produce more extensive comparisons. Specifically, this work makes use of a manufactured gear dataset for sale price prediction. Two traditional machine learning algorithms, M5Rules and SMOreg, are selected due to their applicability to the gear attribute-based data. These algorithms are compared to a neural network model that is trained on a voxelized version of the gears’ 3D models, defined in this work as form-based data. Results show that both data types provide comparable predictive accuracy.
Smooth/Non-Smooth Multibody Co-Simulation of a Particle Damper
Authors: Zhang Runsen , Zhang Huimin , Zanoni Andrea , Tasora Alessandro , Masarati Pierangelo 
Published: November 2020

Abstract
To tackle coupled problems between smooth multibody systems and particle dampers, co-simulation between two general-purpose multibody codes is carried out, where the coupled system is decomposed by the force/displacement technique, and integrated by a loose coupling scheme or a tight one with iterative process. The stability properties of the coupling schemes are discussed using a two-mass oscillator, and it follows that the tight coupling scheme is more stable than the loose one, as expected. Besides, results also denote that the stability is influenced by the parameters of the integrator in each solver. Finally, the co-simulation schemes are applied to a simple system coupled with a particle damper, and the comparison among results obtained by co-simulation, monolithic simulation and experiments verifies the effectiveness of the proposed co-simulation scheme.
Brand Affiliation Through Curved and Angular Surfaces Using the Example of the Vehicle Front
Authors: Fischer Matthias Sebastian , Holder Daniel , Maier Thomas 
Published: November 2020

Abstract
With visual similarity products can be assigned to a brand. The brand assignment based on shapes has only examined the contours (orientation, proportion and position) of selected elements so far. This paper investigates whether brand affiliation is also related to different surface types (curved and angular). For the investigation the vehicle front was selected. Distinguishable contours and surfaces were selected according to their semantic effect (friendliness, aggressiveness and perceived gender). The contours of the headlights and the lower air intake were determined based on anthropometric investigations (smiling and frowning faces) and were selected to be neutral to existing brands. Comparable semantic effects were found for curved and angular surfaces. Self-made vehicle fronts were designed with these parameters. An online survey was conducted with 150 users. First of all, the effects of the stimulus patterns generated for the factors contour (face) and surface were confirmed in the survey. Then the stimulus patterns were evaluated in pairs regarding their brand affiliation. The results show that brand affiliation can be implemented with contours and surfaces. Furthermore, it was determined that there are two user groups which differ in the evaluation of the brand affiliation.
A Model Predictive Control Strategy for Lateral and Longitudinal Dynamics in Autonomous Driving
Authors: Khan Irfan , Feraco Stefano , Bonfitto Angelo , Amati Nicola 
Published: November 2020

Abstract
This paper presents a controller dedicated to the lateral and longitudinal vehicle dynamics control for autonomous driving. The proposed strategy exploits a Model Predictive Control strategy to perform lateral guidance and speed regulation. To this end, the algorithm controls the steering angle and the throttle and brake pedals for minimizing the vehicle’s lateral deviation and relative yaw angle with respect to the reference trajectory, while the vehicle speed is controlled to drive at the maximum acceptable longitudinal speed considering the adherence and legal speed limits. The technique exploits data computed by a simulated camera mounted on the top of the vehicle while moving in different driving scenarios. The longitudinal control strategy is based on a reference speed generator, which computes the maximum speed considering the road geometry and lateral motion of the vehicle at the same time. The proposed controller is tested in highway, interurban and urban driving scenarios to check the performance of the proposed method in different driving environments.
Advanced Vehicle Dynamics Through Active Aerodynamics and Active Body Control
Authors: de Carvalho Pinheiro Henrique , Russo Francesco , Sisca Lorenzo , Messana Alessandro , De Cupis Davide , Ferraris Alessandro , Airale Andrea Giancarlo , Carello Massimiliana 
Published: November 2020

Abstract
In this paper, the development procedure of an innovative control algorithm is shown, with the aim of improving handling performance of a high-end sport vehicle by actively controlling aerodynamic forces acting on the vehicle itself. The proposed control algorithm operates indirectly by modifying ride-heights of the vehicle through an active suspensions system.
The vehicle dynamics analysis is conducted in parallel to the aerodynamics analysis performed in a concurrent engineering operation.
The software used for control algorithms development is VI-CarRealTime, in co-simulation with Matlab-Simulink, with an extended use of the MaxPerformance package. Specific tracks have been implemented ad hoc to highlight the effects of the control systems operation in development phase.
To better explore the potential of the technique, a fuzzy logic system was developed.
Consistent and Inertia-Shape-Integral-Free Invariants of the Floating Frame of Reference Formulation
Authors: Zwölfer Andreas , Gerstmayr Johannes 
Published: November 2020

Abstract
The conventional continuum-mechanics-based floating frame of reference formulation involves unhandy so-called inertia-shape-integrals in the equations of motion, which is why, commercial multibody software codes resort to a lumped mass approximation to avoid the evaluation of these integrals in their computer implementations. This paper recaps the conventional continuum mechanics floating frame of reference formulation and addresses its drawbacks by summarizing recent developments of the so-called nodal-based floating frame of reference formulation, which avoids inertia shape integrals ab initio, does not rely on a lumped mass approximation, and exhibits a way to calculate the so-called invariants, which are constant “ingredients” required to set up the equations of motion, in a consistent way.
Linking Performance Data and Geospatial Information of Manufacturing Assets Through Standard Representations
Authors: Hanke Aaron , Vernica Teodor , Bernstein William Z. 
Published: November 2020

Abstract
Interoperability across emerging visualization modalities, including augmented reality (AR) and virtual reality (VR), remains a challenge with respect to industrial applications. One critical issue relates to the lack of standard approaches for coordinating geospatial representations that are required to facilitate AR/VR scenes with domain-specific information in the form of time-series data, solid models, among other data types. In this paper, we focus on the linking of manufacturing asset data via the MTConnect standard with geospatial data via the IndoorGML standard. To this end, we demonstrate the utility of this integration through two visualization-based prototype implementations, including one focused on (i) monitoring production facilities to improve situational awareness and (ii) evaluating and delivering suggested navigation paths in production facilities. We then comment on implications of such standards-driven approaches for related domains, including AR prototype development and automatic guided vehicles.
Identification of Non-Transversal Bifurcations of Linkages
Authors: Müller Andreas , López Custodio P. C. , Dai J. S. 
Published: November 2020

Abstract
The local analysis is an established approach to the study of singularities and mobility of linkages. Key result of such analyses is a local picture of the finite motion through a configuration. This reveals the finite mobility at that point and the tangents to smooth motion curves. It does, however, not immediately allow to distinguish between motion branches that do not intersect transversally (which is a rather uncommon situation that has only recently been discussed in the literature). The mathematical framework for such a local analysis is the kinematic tangent cone. It is shown in this paper that the constructive definition of the kinematic tangent cone already involves all information necessary to separate different motion branches. A computational method is derived by amending the algorithmic framework reported in previous publications.
A Low Cost Motion Analysis System Based on RGB Cameras to Support Ergonomic Risk Assessment in Real Workplaces
Authors: Altieri Alex , Ceccacci Silvia , Talipu Abudukaiyoumu , Mengoni Maura 
Published: November 2020

Abstract
This paper introduces a motion analysis system based on a network of common RGB cameras, which provides the measurement of various angles considered for postural assessment, in order to facilitate the evaluation of the ergonomic indices commonly used for the determination of risk of musculoskeletal disorders of operators in manufacturing workplaces. To enable the tracking of operator postures during the performed tasks, the system exploits the multi person keypoints detection library “OpenPose”. The proposed system has been validated with a real industrial case study regarding a washing machine assembly line. Results suggest how the proposed system supports ergonomists in risk assessment of musculoskeletal disorders through the OCRA index.
Additively Manufactured Tags for Cast Part Traceability Using Two-Dimensional Digital Code Direct-Part-Marking
Authors: Uyan Tekin , Jalava Kalle , Orkas Juhani , Otto Kevin 
Published: November 2020

Abstract
Statistical quality control is applied in factories and foundries to identify special cause defects and to identify root causes through statistical correlation of process input variations to defects. A difficulty arises in associating process data collected with individual cast parts as they are worked through the foundry and out into the supply chain. Typically, alphanumeric labels for marking castings and manual identification of the castings with route-paper based tracing approaches have been used. Such manual based systems make root cause analysis of quality defect issues tedious. We here develop a semi-automated approach using 3D printed sand mold inserts shaped as 2D matrix codes which thereby permit directly cast identification code into the parts. This enables automated part tracking at the very beginning of the casting process including mold making. Automated scan-based tracking of parts through a foundry and subsequent supply chain allows for statistical process data collected to also be associated with each part processed with unique identification.
Experimental Modal Analysis of Business Jet Fuselage Tail Section Sub-Assemblies
Authors: Donaldson Ian A. , Mechefske Chris K. 
Published: November 2020

Abstract
Experimental modal testing is a technique through which the dynamic response of a system can be found. Parameters such as the natural frequencies and mode shapes of a system can be extracted through experimentation, and these results can be used to confirm computational models and guide structural improvements. This paper provides an overview of experimental modal analysis performed on two aircraft fuselage half scale subassemblies, with the use of shaker excitation. The experimental methodology including the construction of each structure, data acquisition parameters, and validity checks, is presented in detail. Linearity and repeatability checks were used to validate the testing methodology and increase the level of confidence in the experimental results. The experimental natural frequencies were correlated with the computational results, and recommendations were made. The experimental results presented in this work provide a basis for computational model updating work to be considered in future work.
Design of a Miniaturized Actuation System for Robotic Lumbar Discectomy Tools
Authors: Craker Ryan , Johnson Benjamin V. , Sakthivel Haripriya , Cappelleri David J. 
Published: November 2020

Abstract
In this paper, we present the design of a miniaturized actuation system for robotic lumbar discectomy tools. Lumbar dis-cectomy is one of the most common types of back surgery in the United States. Our previous work proposed a new robotic lumbar discectomy (RLD) system consisting of teleoperated articulated instruments inside a robotic cannula for performing this operation. The robotic cannula is used for the independent translation and rotation of the instruments residing in it. Due to the large servo-motor based actuation systems of the initially developed instruments, it was not possible to achieve a fully integrated RLD system. Here, we present the design of a shape memory alloy actuation system for teleoperating RLD tools that allows full integration with the robotic cannula. More than a 10X size reduction in footprint has been achieved. Experimental results show that SMA-driven actuation system meets the instrument range-of-motion, manipulation, and grasping force requirements. Integrated system tests demonstrate the successful operation of the miniaturized RDL tools with the robotic cannula.
Investigating Cyber-Physical Threats of Numerically Controlled Manufacturing Processes
Authors: Piacenza Joseph , Faller Kenneth J. , Regez Bradley , Gomez Luisfernando 
Published: November 2020

Abstract
Motivated by cyber-physical vulnerabilities in precision manufacturing processes, there is a need to externally examine the operational performance of Computer Numerically Controlled (CNC) manufacturing systems. The overarching objective of this work is to design and fabricate a proof-of-concept CNC machine evaluation device, ultimately re-configurable to the mill and lathe machine classes. This device will assist in identifying potential cyber-physical security threats in manufacturing systems by identifying perturbations, outside the expected variations of machining processes, and comparing the desired command inputted into the numerical controller and the actual machine performance (e.g., tool displacement, frequency). In this directed research, a device design is presented based on specific performance requirements provided by the project sponsor. The first design iteration is tested on a Kuka KR 6 R700 series robotic arm, and machine movement comparisons are performed ex-situ using Keyence laser measurement sensors. Data acquisition is performed with a Raspberry Pi 4 microcomputer, controlled by custom, cross-platform Python code, and includes a touch screen human-computer interface. A device design adapted for a CNC mill is also presented, and the Haas TM-2 is used as a case study, which can be operated by technicians to check CNC machine accuracy, as needed, before a critical manufacturing process.
Parametric Stiffness in Large-Scale Wind-Turbine Blades and the Effects on Resonance and Speed Locking
Authors: Sapmaz Ayse , Feeny Brian F. 
Published: November 2020

Abstract
This paper is on parametric effect in large scale horizontal-axis wind-turbine blades and speed locking phenomenon for a simplified model of the in-plane blade-hub dynamics. The relative strength of the parametric stiffness is evaluated for actual and scaled-length blades. Fixed-position natural frequencies are found at different rotation angles to show the significance of the gravity’s parametric effect. The ratio of the parametric and elastic modal stiffness is then estimated for the scaled versions of the NREL’s blades for four models to present the relation between the blade size and the parametric effects. The parametric effect on blade tip placements are investigated for superharmonic resonances at orders two and three for blades of various lengths. An analysis of speed-locking is presented, and interpreted for the various blades.
A Novel Design of a Robotic Glove System for Patients With Brachial Plexus Injuries
Authors: Xu Wenda , Pradhan Sarthak , Guo Yunfei , Bravo Cesar , Ben-Tzvi Pinhas 
Published: November 2020

Abstract
This paper presents the design of an exoskeleton glove system for people who suffer from the brachial plexus injuries in an effort to restore their lost grasping functionality. The robotic system consists of an embedded controller and a portable glove system. The glove system consists of Linear Series Elastic Actuators (SEA), Rotary SEA and optimized finger linkages to provide motion to each finger and a coupled motion of the hand and the wrist. The design is based on various functionality requirements such as being lightweight and portable for activities of daily living, especially for grasping. The contact force at each fingertip and bending angle of each finger are measured for future implementation of intelligent control algorithms for autonomous grasping. To provide better flexibility and comfort for the users, abduction and adduction of each finger as well as flexion of the thumb were taken into consideration in the design. The glove system is adjustable for different hand sizes. The micro-controllers and batteries are integrated on the forearm in order to provide a completely portable design solution.
Simulation Assisted Design of LCO Cathode Materials With High Performance Stability
Authors: Zheng Zhuoyuan , Bansal Parth , Wang Pingfeng , Li Yumeng 
Published: November 2020

Abstract
Lithium cobalt oxide (LCO) cathode is one of the most commonly used positive active materials for lithium ion batteries (LIBs). However, one reliability issue that limits its applications is the presence of moisture adsorbing on the LCO cathode surface, which may react with the electrolyte and lead to detrimental effects. In this study, a novel LCO thin film cathode is proposed, by adding a layer of high diffusion resistant (003) phase of LCO as the protective coating onto the diffusion favorable (110) phase, in order to simultaneously achieve good electrochemical performance and chemical stability of the LIB. A multi-physics-based finite element model is built to investigate the performance of the cathode and the influences of the design and operation variables, including the layout the two crystal phases, the fraction of each phase and the lithiation C rate. In addition, a Gaussian Process based surrogate model is developed, using the simulated results from the FE model as training data, to efficiently explore the design space of the cathode. It is found that, the 110//003 layout cathode could provide high capacity and good rate performance; meanwhile, the 003//110 design may lead to a largely reduced capacity, especially at high lithiation C rates.
Integrated and Configurable Voice Activation and Speaker Verification System for a Robotic Exoskeleton Glove
Authors: Guo Yunfei , Xu Wenda , Pradhan Sarthak , Bravo Cesar , Ben-Tzvi Pinhas 
Published: November 2020

Abstract
Efficient human-machine interface (HMI) for exoskeletons remains an active research topic, where sample methods have been proposed including using computer vision, EEG (electroencephalogram), and voice recognition. However, some of these methods lack sufficient accuracy, security, and portability. This paper proposes a HMI referred as integrated trigger-word configurable voice activation and speaker verification system (CVASV). The CVASV system is designed for embedded systems with limited computing power that can be applied to any exoskeleton platform. The CVASV system consists of two main sections, including an API based voice activation section and a deep learning based text-independent voice verification section. These two sections are combined into a system that allows the user to configure the activation trigger-word and verify the user’s command in real-time.