bluuebunny/crossref_metadata_2025 huggingface dataset:
Mind the Gap! Populism, Participation and Representation in Europe
Authors: Huber Robert A. , Ruth Saskia P.
Published: November 2017

This article assesses the influence of populist parties on two central aspects of democracy – participation and representation. In line with traditional theories on populism and democracy, we argue that populist parties have a positive effect on electoral turnout and the equality of participation. This effect, however, is moderated by the party's role in government or opposition as well as their host‐ideology, i.e. left, centre or right. We argue that populist parties also have a positive effect on substantive representation, but that this effect is strongly dependent on their host‐ideology. We test these arguments with lagged dependent variable models using data from 31 European countries from 1990 until 2014. We find mixed support for our theoretical expectations.
Producing Lexical Stress in Second Language German
Authors: Maczuga Paulina , O'Brien Mary Grantham , Knaus Johannes
Published: November 2017

Lexical stress assignment plays a central role in being understood in a second language. In fact, research has shown that it may be more important for the comprehensibility of second language learners’ speech than, for example, grammatical correctness (Trofimovich & Isaacs, ). Nonetheless, its production poses challenges for second language learners. This study investigated the effect of perceptual training on the production of three types of predictable German lexical stress patterns by native speakers of English. Beginner and intermediate learners produced German words from three categories: words ending in schwa; words with unstressed suffixes; and German‐English cognates. The results demonstrate that both beginner and intermediate learners improved in their production of lexical stress after the training. Though participants in both groups had more difficulties in assigning lexical stress to cognate words than to non‐cognate words, production accuracy could best be predicted by the presence of certain suffixes. The results have implications for teaching second language vocabulary.
Web Application Security Tools Analysis
Authors: Alzahrani Abdulrahman , Alqazzaz Ali , Almashfi Nabil , Fu Huirong , Zhu Ye
Published: November 2017

Strong security in web applications is critical to the success of your online presence. Security importance has grown massively, especially among web applications. Dealing with web application or website security issues requires deep insight and planning, not only because of the many tools that are available but also because of the industry immaturity. Thus, finding the proper tools requires deep understanding and several steps, including analyzing the development environment, business needs, and the web applications’ complexity. In this paper, we demonstrate the architecture of web applications then list and evaluate the widespread security vulnerabilities. Those vulnerabilities are: Fingerprinting, Insufficient Transport Layer Protection, Information Leakage, Cross-Site Scripting, SQL Injection, and HTTP Splitting. In addition, this paper analyzes the tools that are used to scan for these widespread vulnerabilities in web applications. Finally, it evaluates tools due to security vulnerabilities and gives recommendations to the web applications’ users and administrators aiming to educate them.
Prediction of Process Forces in Fiber Metal Laminate Stamping
Authors: Hahn Marlon , Khalifa Nooman Ben , Shabaninejad Arash
Published: November 2017

The stamping of fiber metal laminates (FMLs) at thermoforming temperature of the thermoplastic matrix is investigated. The studied FML types consist of a unidirectional carbon fiber-reinforced core that is attached to metal cover layers either made of a steel or magnesium alloy. An analytical model is established in order to predict the process forces during forming, which are the blankholder force required to make the metal covers yield plastically, the punch force, and the corresponding load distribution on the individual layers (outer layer, core layer, and inner layer). The global forces are primarily verified through experimental force measurements, while numerical simulations are mainly performed to assess the resulting load distribution with the help of strain distributions in the cover layers. The results show that the introduced model can be applied successfully if the stamp-forming process is dominated by friction-induced tensional loading rather than by bending.
A Power-Law Mixing Rule for Predicting Apparent Diffusion Coefficients of Binary Gas Mixtures in Heavy Oil
Authors: Jang Hyun Woong , Yang Daoyong , Li Huazhou
Published: November 2017

A power-law mixing rule has been developed to determine apparent diffusion coefficient of a binary gas mixture on the basis of molecular diffusion coefficients for pure gases in heavy oil. Diffusion coefficient of a pure gas under different pressures and different temperatures is predicted on the basis of the Hayduk and Cheng's equation incorporating the principle of corresponding states for one-dimensional gas diffusion in heavy oil such as the diffusion in a pressure–volume–temperature (PVT) cell. Meanwhile, a specific surface area term is added to the generated equation for three-dimensional gas diffusion in heavy oil such as the diffusion in a pendant drop. In this study, the newly developed correlations are used to reproduce the measured diffusion coefficients for pure gases diffusing in three different heavy oils, i.e., two Lloydminster heavy oils and a Cactus Lake heavy oil. Then, such predicted pure gas diffusion coefficients are adjusted based on reduced pressure, reduced temperature, and equilibrium ratio to determine apparent diffusion coefficient for a gas mixture in heavy oil, where the equilibrium ratios for hydrocarbon gases and CO2 are determined by using the equilibrium ratio charts and Standing's equations, respectively. It has been found for various gas mixtures in two different Lloydminster heavy oils that the newly developed empirical mixing rule is able to reproduce the apparent diffusion coefficient for binary gas mixtures in heavy oil with a good accuracy. For the pure gas diffusion in heavy oil, the absolute average relative deviations (AARDs) for diffusion systems with two different Lloydminster heavy oils and a Cactus Lake heavy oil are calculated to be 2.54%, 14.79%, and 6.36%, respectively. Meanwhile, for the binary gas mixture diffusion in heavy oil, the AARDs for diffusion systems with two different Lloydminster heavy oils are found to be 3.56% and 6.86%, respectively.
A Study on Methodology to Make Team: Methodology — Phase II
Authors: Sugimoto Yoichi , Arakawa Masao , Ishimaru Masahiko
Published: November 2017

Improvement in labor productivity is a common problem in each country. In particular, in Japan where the productive age population is decreasing, it is necessary to steadily advance efforts for the improvement at various sites throughout the entire society. In doing so, in order to make it prevail over broad areas, it is necessary to consider that on-site holding resources can be utilized, that it can be easily introduced, and that it will surely be effective. Therefore, we have focused on improving the way of collaboration from an angle of “person’s personality”. Specifically, we have aimed to build a methodology, for a “team” that is a collaborative form widely introduced and utilized at companies and educational sites, which enhances the effectiveness of team activities. As for the overall structure of the methodology, we have designed it with a three-layer structure in order to clarify separation from other intellectual properties and consideration to ethical aspects. That is, the designed methodology comprises the following three phases. Phase I: a team formation methodology; Phase II: a team management methodology; and Phase III: a team development support methodology.

Study results of Phase I were presented at the 26th Design Engineering and System Division Lecture by the Japan Society of Mechanical Engineers (JSME). In this study, we have used the methodology of Phase I to devise, as a method included in Phase II, three Rules for creating a team environment that makes it easy for “introverted” persons in Jungian psychology to express their opinions. Then, we have conducted parallel group randomized trials comparing an intervention group with a control group, analyzed the results by an analysis method such as Data Envelopment Analysis (DEA), and verified the effectiveness of the devised method. As a result, the findings have revealed that teams in which the team management was carried out according to the devised method tends to be more effective and prone to excellent effectiveness.
Optimality Conditions for Constrained Least-Squares Fitting of Circles, Cylinders, and Spheres to Establish Datums
Authors: Shakarji Craig M. , Srinivasan Vijay
Published: November 2017

This paper addresses the combinatorial characterizations of the optimality conditions for constrained least-squares fitting of circles, cylinders, and spheres to a set of input points. It is shown that the necessary condition for optimization requires contacting at least two input points. It is also shown that there exist cases where the optimal condition is achieved while contacting only two input points. These problems arise in digital manufacturing, where one is confronted with the task of processing a (potentially large) number of points with three-dimensional coordinates to establish datums on manufactured parts. The optimality conditions reported in this paper provide the necessary conditions to verify if a candidate solution is feasible, and to design new algorithms to compute globally optimal solutions.
A Method of Utilizing Digital Manikins to Assist Passenger Vehicle Design
Authors: Wan Jian , Wang Nanxin , Kozak Ksenia , Gomez-levi Gianna , Mikulionis Linas
Published: November 2017

Most occupant accommodation assessments of a new vehicle design currently still utilize human appraisal. That is, human subjects experience the new design physically and provide feedback including a numerical rating or verbatim description. There are two drawbacks with this type of assessment: 1) the outcome is subjective. They are likely affected by other factors such as the vehicle’s appearance or brand and the individual’s own bias; 2) the outcome may not be able to reveal where the issues are nor how to resolve them.

The digital manikin technology has been widely used in different areas: starting from movie and video gaming industries, and getting more and more involved in the product life circle of manufacture industries. Human motions are captured, and the digital manikin is utilized to present these motions virtually. This paper introduces a method that uses digital manikins to assist the process of vehicle design. Subjects’ motions interacting with a vehicle, which are related to a new design change, are captured. These motions are used to drive digital manikins that represent their respective subjects in size and body shape. A software system that animates the digital manikin according to the motions and creates swept volumes of selected body segments was created. The collection of the swept volumes of all subjects represents the space that is occupied by the human body during the motion. This space can be used to assess the design changes by indicating the minimum clearance between the swept volume and vehicle components or the interference between the human body with the components. In addition, the space described by the swept volumes provides a guideline or space limit for any future design changes.

This method is objective. It not only pin-points the locations that cause discomfort or inconvenience by the new design, but also provides quantitative suggestions on how much improvement is needed for a better design.
Implicit Knowledge Discovery in Design Semantic Network by Applying Pythagorean Means on Shortest Path Searching
Authors: Shi Feng , Chen Liuqing , Han Ji , Childs Peter
Published: November 2017

With the advent of the big-data era, massive textual information stored in electronic and digital documents have become valuable resources for knowledge discovery in the fields of design and engineering. Ontology technologies and semantic networks have been widely applied with text mining techniques including Natural Language Processing (NLP) to extract structured knowledge associations from the large-scale unstructured textual data. However, most existing works mainly focus on how to construct the semantic networks by developing various text mining methods such as statistical approaches and semantic approaches, while few studies are found to focus on how to subsequently analyze and fully utilize the already well-established semantic networks. In this paper, a specific network analysis method is proposed to discover the implicit knowledge associations from the existing semantic network for improving knowledge discovery and design innovation. Pythagorean means are applied with Dijkstra’s shortest path algorithm to discover the implicit knowledge associations either around a single knowledge concept or between two concepts. Six criteria are established to evaluate and rank the correlation degree of the implicit associations. Two engineering case studies were conducted to illustrate the proposed knowledge discovery process, and the results showed the effectiveness of the retrieved implicit knowledge associations on helping providing relevant knowledge from various aspects, and provoking creative ideas for engineering innovation.
Correlating Integrative Complexity With System Modularity
Authors: Sinha Kaushik , Suh Eun Suk , de Weck Olivier
Published: November 2017

Modularity is the degree to which a system is made up of relatively independent but interacting elements. Modularization is not necessarily a means of reducing intrinsic complexity of the system, but it is a means of effectively redistributing the total complexity across the system. High degree of modularization enable reductionist strategies of system development and is an effective mechanism for complexity redistribution that can be better managed by system developers by enabling design encapsulation. In this paper, we introduce a complexity attribution framework to enable consistent complexity accounting and management procedure and show that integrative complexity has a strong inverse relationship with system modularity and its implication on complexity management for engineered system design and development.
A Virtual CMM Inspection Tool for Capturing Planning Strategies
Authors: Anagnostakis Dimitrios , Ritchie James , Lim Theodore , Sung Raymond , Dewar Richard
Published: November 2017

One of the most challenging tasks throughout the development and manufacturing of a product is the capturing and formalization of engineering knowledge and expertise. In the past, many researchers have successfully proposed different techniques for capturing knowledge during the design, process and assembly planning of a product. However, few efforts have focused on applying knowledge capture to the task of product verification for Coordinate Measuring Machine (CMM) inspection; most of these are manual, obtrusive for the user and time consuming since the main sources of knowledge come from documentation such as handbooks, guides or interview transcripts. This paper describes a tool for the automated logging of a planner’s actions while carrying out an inspection planning task in a virtual CMM measurement environment. The tool involves a combination of 3D motion tracking and a post-processor to decipher the context strategy in the form of an inspection plan. Various representations of a captured strategy will benefit CMM operators by providing them a tool for: understanding planning strategies, better training methods for inexperienced users and producing more efficient part programs in a shorter time.
Automatic Derivation of Geometric Properties of Components From 3D Polygon Models
Authors: Brandt Sascha , Fischer Matthias , Gerges Maria , Jähn Claudius , Berssenbrügge Jan
Published: November 2017

To detect errors or find potential for improvement during the CAD-supported development of a complex technical system like modern industrial machines, the system’s virtual prototype can be examined in virtual reality (VR) in the context of virtual design reviews. Besides exploring the static shape of the examined system, observing the machines’ mechanics (e.g., motor-driven mechanisms) and transport routes for the material transport (e.g., via conveyor belts or chains, or rail-based transport systems) can play an equally important role in such a review. In practice it is often the case, that the relevant information about transport routes, or kinematic properties is either not consequently modeled in the CAD data or is lost during conversion processes. To significantly reduce the manual effort and costs for creating animations of the machines complex behavior with such limited input data for a design review, we present a set of algorithms to automatically determine geometrical properties of machine parts based only on their triangulated surfaces. The algorithms allow to detect the course of transport systems, the orientation of objects in 3d space, rotation axes of cylindrical objects and holes, the number of tooth of gears, as well as the tooth spacing of toothed racks. We implemented the algorithms in the VR system PADrend and applied them to animate virtual prototypes of real machines.
PDSIDES: A Knowledge-Based Platform for Decision Support in the Design of Engineering Systems
Authors: Ming Zhenjun , Nellippallil Anand Balu , Yan Yan , Wang Guoxin , Goh Chung Hyun , Allen Janet K. , Mistree Farrokh
Published: November 2017

We hypothesize that by providing decision support for designers in industry we can speed up the design process and facilitate the creation of quality cost-effective designs. One of the challenges in providing design decision support is that the decision workflows embody various degrees of complexity due to the inherent complexity embodied in engineering systems. To tackle this, we propose a Knowledge-Based Platform for Decision Support in the Design of Engineering Systems (PDSIDES). PDSIDES is built on our earlier work that is anchored in modeling decision-related knowledge with templates using ontology to facilitate execution and reuse. In this paper, we extend the ontological decision templates to a computational platform that provides knowledge-based decision support for three types of users, namely, Template Creators, Template Editors, and Template Implementers, in original design, adaptive design, and variant design respectively. The efficacy of PDSIDES is demonstrated using a Hot Rod Rolling System (HRRS) design example.
Hyperelastic Material Model Selection of Structural Silicone Sealants for Use in Finite Element Modeling
Authors: Carbary Larry D. , Kimberlain Jon H. , Oliva John C.
Published: November 2017

Hyperelastic material model parameters have been developed to capture the behavior of silicone based construction sealants. Modern commercially available finite element analysis software makes it quite accessible to develop hyperelastic material models, automating the process of curve-fitting experimental lab data to specific hyperelastic formulations. However, the process of selecting a particular hyperelastic model from those supported is not straightforward. Here, a series of lab experiments are employed to guide the selection of the hyperelastic model that best describes various structural silicone glazings. A total of 10 different sealants are characterized with discussion of variations among the models. Comparisons of the best performing hyperelastic models for the different sealants are presented. Finally, an application is described in which these hyperelastic models have begun to be implemented in practice.
Recent Developments of the Multiphysics Discrete Element Method for Additive Manufacturing Modeling and Simulation
Authors: Steuben John C. , Iliopoulos Athanasios P. , Michopoulos John G.
Published: November 2017

Recent years have seen a sharp increase in the development and usage of Additive Manufacturing (AM) technologies for a broad range of scientific and industrial purposes. The drastic microstructural differences between materials produced via AM and conventional methods has motivated the development of computational tools that model and simulate AM processes in order to facilitate their control for the purpose of optimizing the desired outcomes. This paper discusses recent advances in the continuing development of the Multiphysics Discrete Element Method (MDEM) for the simulation of AM processes. This particle-based method elegantly encapsulates the relevant physics of powder-based AM processes. In particular, the enrichment of the underlying constitutive behaviors to include thermoplasticity is discussed, as are methodologies for modeling the melting and re-solidification of the feedstock materials. Algorithmic improvements that increase computational performance are also discussed. The MDEM is demonstrated to enable the simulation of the additive manufacture of macro-scale components. Concluding remarks are given on the tasks required for the future development of the MDEM, and the topic of experimental validation is also discussed.
Functional Performance Tailoring of Additively Manufactured Components via Topology Optimization
Authors: Steuben John C. , Michopoulos John G. , Iliopoulos Athanasios P. , Birnbaum Andrew J.
Published: November 2017

The freedom of design that is afforded by Additive Manufacturing (AM) processes opens exciting possibilities for the production of lightweight, high performance components and structures. Consequently, in recent years the development of software tools to enable engineering design methods that exploit the unique features of AM has become a subject of increased research interest. In this paper we explore the use of Topology Optimization (TO) algorithms to tailor component shape in order to achieve the intended functionality of additively manufactured components at the macro length scale. We present two case studies: the first concerns the hierarchical nesting of functions in a hand tool, while the second covers the development of a metamaterial component substructure for an Uninhabited Underwater Vehicle (UUV) hull. We offer conclusions regarding the usefulness of TO techniques for the design of AM components, and a summary of future work, which we feel is necessary to improve such methodologies.
An Exploration Study for Augmented and Virtual Reality Enhancing Situation Awareness for Plant Teleanalysis
Authors: Aschenbrenner Doris , Maltry Nicolas , Schilling Klaus , Verlinden Jouke
Published: November 2017

This work wants to investigate which visualization method is able to support remote teleanalysis of industrial plants best regarding comprehension, usability and situation awareness. The application goal is the remote optimization of an industrial plant and the examined scenario was generated out of a large data set of a real production entity. The plant consists of an industrial manipulator, a molding machine and a montage system. Prior studies on the same plant with video based visualization explored by remote experts showed a large potential for optimization, but indicated a higher demand for situation awareness.

In order to test the influence of the visualization method, a user study has been carried out with 60 student participants with six different visualization methods, including various VR and AR implementations. Overall, our used AR environment performed significantly better than the used VR and video implementations, but the VR implementation surpasses AR regarding situation awareness.
Anterior Cruciate Ligament (ACL) Injury: A Literature Review
Authors: Aguilar Jazmin , Yang James
Published: November 2017

Anterior Cruciate Ligament (ACL) injuries occur often in competitive sports such as soccer, basketball, football, and more. Athletes of all ages are at risk of experiencing this injury due to living highly active lifestyles. ACL injuries account for over $500 million in total medial cost in the United States, with about 150,000 annual occurrences of injury. Much research over this knee injury has been conducted as early as 1850, but confirmation of definite mechanisms of ACL injury have proved to be a difficult endeavor due to conflicting results found from experiments. Solving this problem could lead to implementation of preventative measures to help reduce to number of victims that undergo ACL injuries. The intention of this paper is to review the state-of-the-art of ACL injury research, including possible mechanisms of injury and the experimental methods used to analyze ACL performance.
A Domain-Driven Approach to Metamodeling in Additive Manufacturing
Authors: Yang Zhuo , Hagedorn Thomas , Eddy Douglas , Krishnamurty Sundar , Grosse Ian , Denno Peter , Lu Yan , Witherell Paul
Published: November 2017

Recent studies have shown advantages to utilizing metamodeling techniques to mimic, analyze, and optimize system input-output relationships in Additive Manufacturing (AM). This paper addresses a key challenge in applying such metamodeling methods, namely the selection of the most appropriate metamodel. This challenge is addressed with domain-specific AM information, derived from physics, heuristics and prior knowledge of the process. Domain-specific input/output models and their interrelationships are studied as a basis for a domain-driven metamodeling approach in AM. A metamodel selection process is introduced that evaluates global and local modeling performances, with different AM datasets, for three types of surrogate metamodels (polynomial regression (PR), Kriging, and artificial neural network (ANN)). A salient feature of this approach is its ability to seamlessly integrate domain-specific information in the model selection process. The approach is demonstrated with the aid of a metal powder bed fusion (PBF) case study and the results are discussed.
Ontology-Based Representation of Meta-Design in Designing Decision Workflows
Authors: Wang Ru , Wang Guoxin , Yan Yan , Sabeghi Maryam , Ming Zhenjun , Allen Janet K. , Mistree Farrokh
Published: November 2017

Utilizing the enterprise capital related the knowledge of design processes has become a crucial to improve enterprise agility and respond to shifts or changes in markets. The complexity and uncertainty of design processes raise the challenge of capturing tacit knowledge and the ability to provide assistance in designing design processes. In this paper, an ontology is proposed for capturing, representing and documenting the knowledge related to hierarchical decision workflows in the meta-design of complex engineered systems. The ontology is developed in the context of Decision Support Problem Technique (DSPT), taking into account the requirements being able to guide assistance in designing design workflows, and integrating problem, product and process information in a design decision-making process. Then, the method of building procedure and design of process templates are presented to facilitate the reuse of the populated template instances in future design. Finally, the meta-design of the heat exchanger in a small thermal system is presented as an example to illustrate the effectiveness of this approach.
Design Review Using Virtual Reality Enabled CAD
Authors: de Casenave Luis , Lugo José E.
Published: November 2017

Computer Aided Design (CAD) has been crucial to the engineering design process since the 1960s due to the ability to create 2D and 3D design representations and easily incorporate design changes without the cost of physical prototypes. However, CAD is hindered by its hardware displaying 3D objects as 2D representations, causing a loss of realism compared to a physical prototype. This paper seeks to observe if increasing the realism of interaction between subjects and virtual prototypes using virtual reality hardware will affect users ability to analyze the assembly model for errors. For this end, an experiment asked participants to perform a design review of assembly models and determine if they successfully form a cube without deformations or voids in four different environments. The environments ranged from low to high levels of immersion controlled through the use of two factors: movement of user’s point of view and assembly rotation. It is expected the highly immersive VR environment will allow for improved assembly reviews due to the increased realism of the virtual prototype.
Evaluating Sampling Methods for Reusing Knowledge From Large and Ill-Structured Qualitative Data Sets
Authors: Nelson Jacob , Marrs G. Austin , Schmidt Greg , Donndelinger Joseph A. , Nagel Robert L.
Published: November 2017

The desire to use ever growing qualitative data sets of user generated content in the engineering design process in a computationally effective manner makes it increasingly necessary to draw representative samples. This work investigated the ability of alternative sampling algorithms to draw samples with conformance to characteristics of the original data set. Sampling methods investigated included: random sampling, interval sampling, fixed-increment (or systematic) sampling method, and stratified sampling. Data collected through the Vehicle Owner’s Questionnaire, a survey administered by the U.S. National Highway Traffic Safety Administration, is used as a case study throughout this paper. The paper demonstrates that existing statistical methods may be used to evaluate goodness of fit for samples drawn from large bodies of qualitative data. Evaluation of goodness of fit not only provides confidence that a sample is representative of the data set from which it is drawn, but also yields valuable real-time feedback during the sampling process. This investigation revealed two interesting and counterintuitive trends in sampling algorithm performance. The first is that larger sample sizes do not necessarily lead to improved goodness of fit. The second is that depending on the details of implementation, data cleansing may degrade performance of data sampling algorithms rather than improving it. This work illustrates the importance of aligning sampling procedures to data structures and validating the conformance of samples to characteristics of the larger data set to avoid drawing erroneous conclusions based on unexpectedly biased samples of data.
Design for Repair: A Game Between Manufacturer and Independent Repair Service Provider
Authors: Sabbaghi Mostafa , Behdad Sara
Published: November 2017

Design for ease-of-repair is an efficient solution to effectively use resources by extending the lifespan of products. However, designing a repairable product may not be necessarily an economically viable solution for manufacturers. Repairable products enable independent repair businesses to compete with original manufacturers on offering repair services. On the other hand, although designing a less repairable product may dissuade competition, it increases the cost of repair for manufacturers at the same time, in addition to decreasing consumers’ satisfaction. In this paper, a game-theoretic model is developed to represent the competition between a manufacturer acting as a leader, and a coalition of independent repair service providers acting as a follower. The subgame perfect Nash equilibrium is derived, representing the optimal prices for repair services offered by the two service-providers based on the level of repairability. In addition, based on the information extracted from a repair-related survey, we provide insights about consumers’ attitudes towards repairability of products to help manufacturers make better design decisions.
Basic Study on Development of Delight Design Method: Proposal and Application of Beer Cup Design Based on Value Model and Evaluation Model of KANSEI
Authors: Tanaka Yukako , Misaka Mai , Aoyama Hideki
Published: November 2017

Customers with diversified tastes have come to expect more than high product quality and performance. A high level of added value is required, and the provision for products that meet the individual requirements customers has become important. In recent years, delight design has attracted attention as a method for enhancing customer satisfaction. Delight design describes a design that offers attractive qualities beyond the required performance and quality requirements. However, attractiveness depends on the quality of the designer; furthermore, there are difficulties associated with the definition and expression based on similarities between the actual design and the original idea.

Therefore, in this study, we have proposed two methods for constructing neural network models: one for a value model using customer KANSEI data and one for an evaluation model for customers (designed as an inverse model). The customer value model creates the required product design from KANSEI. The evaluation model analyzes KANSEI for the individual customer and creates a design (delight design) according to KANSEI engineering and the preferences of the individual customer. The method proposed in this study was applied to the crack pattern seen on ceramic surfaces.
Developing a Method for Classifying Design Enablers
Authors: Gendreau Elizabeth , O’Shields Steven , Summers Joshua D.
Published: November 2017

The following paper aims to create a classification method for design enablers which will later be used to measure the impact of design enablers on industry. First, a classification method for design enablers is developed based on a review of relevant literature. Second, this method is applied to a series of design enablers developed by the CEDAR lab strictly based on information published within literature. Finally, non-published documentation available for one of the reviewed design enablers will be considered further to better illustrate the classification method. In later work, additional unpublished documentation will be considered alongside interviews of design enabler developers to fully classify the remaining enablers. This research will later be used to map design enabler development to its impact in order to make recommendations for decision making for future design enabler development.
Gaming the System: An Agent-Based Model of Estimation Strategies and Their Effects on System Performance
Authors: Meluso John , Austin-Breneman Jesse
Published: November 2017

Parameter estimates in large-scale complex engineered systems affect system evolution yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Interviews with several expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model simulation which recreates these characteristics is presented. Model results suggest that the systems engineers’ “gaming” strategy of counteracting subsystem bias may decrease system-level estimate accuracy and increase uncertainty.
Immersive Virtual Reality System for Treatment of Phantom Limb Pain (PLP)
Authors: Covarrubias Rodriguez Mario , Aruanno Beatrice , Bordegoni Monica , Rossini Mauro , Molteni Franco
Published: November 2017

This paper presents an immersive virtual reality system (IVRS) that has been designed for unilateral amputees in order to reduce the phantom limb pain (PLP). The patient’s healthy limb is tracked by using a motion sensor. Data of the limb in motion are used as input parameters to move the phantom limb in the immersive virtual reality system. In this way, the patient has the illusion of moving the phantom limb while moving the real and contra-lateral limb. The system has been implemented by using low cost and open technologies, and combines the Oculus Rift SDK2 device, the LeapMotion device, a motion sensor, and an engine for interactive 3D content and gaming generation (Unity 3D). The Oculus Rift head mounted display is used to provide the immersive experience.
The Potential Effects on Design of Increased Prevalence of Obesity in US Children
Authors: Thind Harsimran , Parkinson Matthew B.
Published: November 2017

The objective of this study is to identify potential consequences for design of the increased prevalence of obesity in children in the US. Data on stature and mass of children in the US have been collected since the 1960s. These data confirm an increased prevalence of obesity, particularly since the early 2000s. Many design tools and standards that inform the design process for this market are based on data collected in the 1970s. The design implications of these changes are examined in the context of a case study on vehicle safety (i.e., “booster”) seats. This study concludes that trends of increased prevalence of obesity in children can lead to higher than expected rates of disaccommodation on measures of breadth in some situations.
A Distributed Intelligence Approach to Using Collaborating Unmanned Aerial Vehicles for Oil Spill Mapping
Authors: Odonkor Philip , Ball Zachary , Chowdhury Souma
Published: November 2017

From swarming locusts to schools of fish, the complex emergent behaviors exhibited by multi-agent swarm systems in nature present a compelling basis for their application towards real-world challenges. This paper capitalizes on this potential by proposing a swarm-intelligence inspired approach towards mapping complex offshore oil spills — one that uses a collaborating team of small (inexpensive) unmanned aerial vehicles. By leveraging the idea of occupancy grids, a new probability map concept is developed to enable agent-level situational awareness, while significantly reducing computing overheads (image data to intelligence generation in <1 sec) and communication overheads (< 1.7 KB of average data sharing across the swarm agents). The probability map is further exploited for waypoint planning using the principles of swarm dynamics and a rule-based reasoning approach to allow for dynamic preference shifts towards map exploitation and exploration. Detection of oil is performed by using a generalizable concept of anomaly detection that is derived from a color-based segmentation approach. Two simulated case studies, derived from actual oil spill images, are presented with results highlighting the strengths of the proposed approach.
Design of an Agent-Based Technique for Controlling Interconnected Distributed Energy Resource Transactions
Authors: Janko Samantha , Johnson Nathan G.
Published: November 2017

Electricity has traditionally been a commodity that is bought and sold through a rigid marketplace between an electric utility and a ratepayer. Today, however, the electricity market is rapidly evolving to be comprised of distributed energy resources and microgrids that change the structure of the technical and financial relationship between utilities and ratepayers. Regulation, a reduction in cost of renewable energy technologies, interoperability and improved communications, and public interest in green power are facilitating this transition. Microgrids require an additional layer of control, often use preprogrammed rule sets, and lack bi-directional self-awareness, self-management, and self-diagnostics necessary to dynamically adapt to changes on-site and in the grid. Research is needed in optimization and controls. This study explores the viability of self-organizing control algorithms to manage multiple distributed energy resources within a distribution network and reduce electricity cost to one or more ratepayers having such resources installed on-site. Such research provides insight into the transition from a traditional power distribution architecture into a flexible smart network that is better prepared for future technological advances, renewables integration, and customer-side control. Agent-based techniques are employed for least-cost optimization and implements these to manage transactions between three decentralized distributed energy resource systems within an electrical network.
Topology Optimization for Additive Manufacturing Considering Layer-Based Minimum Feature Sizes
Authors: Osanov Mikhail , Guest James K.
Published: November 2017

The rapid advance of additive manufacturing technologies has provided new opportunities for creating complex structural shapes. In order to fully exploit these opportunities, however, engineers must re-think the design process and leverage these new capabilities while respecting manufacturing constraints inherent in various processes. Topology optimization, as a free-from design tool, is a potentially powerful approach to addressing this design challenge provided the manufacturing process is properly accounted for. This work examines geometric constraints related to feature size and the layer-by-layer nature of the manufacturing process. A simple modification to the Heaviside Projection Method, an approach for naturally achieving geometric constraints in topology optimization, is proposed and demonstrated to have clear, understandable impact on three-dimensional optimized beam designs.
A Novel Transition Region Representation for Additive Manufacturing for Graded Materials, Structures and Tolerances
Authors: Ameta Gaurav , Witherell Paul
Published: November 2017

Additive manufacturing (AM) has enabled control over heterogeneous materials in ways that were not previously possible. This paper presents a novel method for representing and communicating heterogeneous materials based structures that include tolerancing of geometry and material together. AM has expanded design possibilities to include specified material heterogeneities, including functionally graded materials. The aim of the paper is to propose a means to specify nominal materials and allowable material variations in parts, including (a) explicit material transitions and (b) functional transitions to support single and multiple material behaviors. The transition region combines bounded regions (volumes and surfaces) and material distribution equations. Tolerancing is defined at two levels, that of the geometry including bounded regions and that of the materials. Material tolerances are defined as allowable material variations from nominal material fractions within a unit volume at a given location computed using material distribution equations. The method is described thorough several case studies of abrupt transitions, lattice based transitions, and multi-material transitions.
Calibration and Validation of a Time-Dependent Temperature Field Model for Steel Slabs in a Reheating Furnace
Authors: Dong Xiaoxu , Xi Zhimin , Shao Jian , He Anrui
Published: November 2017

The temperature field model of steel slabs in a reheating furnace is pivotal in quality control of the steel rolling process. Computationally efficient models have been developed for online temperature control. However, accuracy of these models is often not satisfactory and thus causes quality control issues in the steel rolling process. This paper presents a model validation approach to improve accuracy of a temperature field model while maintaining its computational efficiency. Deterministic validation is firstly conducted by ignoring material property uncertainties through building a bias regression model with respect to different geometrical locations of a steel slab. With foreseeable accuracy improvement, statistical model validation is then further conducted by considering material property uncertainties so that reliable temperature control can be achieved for different batches of steel slabs in production.
Giant positive magnetoresistance in half-metallic double-perovskite Sr
2
CrWO
6
thin films
Authors: Zhang Ji , Ji Wei-Jing , Xu Jie , Geng Xiao-Yu , Zhou Jian , Gu Zheng-Bin , Yao Shu-Hua , Zhang Shan-Tao
Published: November 2017

Ferrimagnetic half-metallic Sr
2
CrWO
6
thin films show giant positive magnetoresistance up to 17,200%.
Invasive Disease Caused Simultaneously by Dual Serotypes of Streptococcus pneumoniae
Authors: Ndlangisa Kedibone , du Plessis Mignon , Allam Mushal , Wolter Nicole , de Gouveia Linda , Klugman Keith P. , Cohen Cheryl , Gladstone Rebecca A. , von Gottberg Anne
Published: November 2017

There are at least 98 known pneumococcal serotypes. Invasive pneumococcal disease (IPD) is usually caused by a single serotype, and dual-serotype IPD is rare. To assess factors associated with dual-serotype IPD, patient information obtained through laboratory-based surveillance for IPD from 2005 through 2014 in South Africa was reviewed. Genomes of isolate pairs from coinfected individuals were sequenced to determine their molecular characteristics. For 30 (91%) of 33 patients with dual serotypes, one or both isolates were a pneumococcal conjugate vaccine (PCV13) serotype. Dual-serotype IPD was associated with children <5 years of age (adjusted odds ratio [aOR], 4.7; 95% confidence interval [95% CI], 1.8 to 11.7), underlying illness (other than HIV) (aOR, 2.8; 95% CI, 1.1 to 6.6) and death (aOR, 2.5; 95% CI, 1.08 to 6.09). For each coinfecting pair, isolates were genotypically unrelated, and their genotypes were common among isolates of the same serotype in South Africa. Of 701 accessory genes identified among dual-serotype IPD isolates, four were common between isolate pairs. Coinfecting isolate pairs had different genotypic backgrounds. The association of dual serotypes with death warrants increased awareness of IPD coinfection caused by two or more serotypes.
Assessment of Chronic Wasting Disease Prion Shedding in Deer Saliva with Occupancy Modeling
Authors: Davenport Kristen A. , Mosher Brittany A. , Brost Brian M. , Henderson Davin M. , Denkers Nathaniel D. , Nalls Amy V. , McNulty Erin , Mathiason Candace K. , Hoover Edward A.
Published: November 2017

The detection of prions is difficult due to the peculiarity of the pathogen, which is a misfolded form of a normal protein. The specificity and sensitivity of detection methods are imperfect in complex samples, including in excreta. Here, we combined optimized prion amplification procedures with a statistical method that accounts for false-positive and false-negative errors to test deer saliva for chronic wasting disease (CWD) prions. This approach enabled us to discriminate the shedding of prions in saliva and the detection of prions in saliva—a distinction crucial to understanding the role of prion shedding in disease transmission and for diagnosis. We found that assay sensitivity and specificity were indeed imperfect, and we were able to draw several conclusions pertinent to CWD biology from our analyses: (i) the shedding of prions in saliva increases with time postinoculation, but is common throughout the preclinical phase of disease; (ii) the shedding propensity is influenced neither by sex nor by prion protein genotype at codon 96; and (iii) the source of prion-containing inoculum used to infect deer affects the likelihood of prion shedding in saliva; oral inoculation of deer with CWD-positive saliva resulted in 2.77 times the likelihood of prion shedding in saliva compared to that from inoculation with CWD-positive brain. These results are pertinent to horizontal CWD transmission in wild cervids. Moreover, the approach described is applicable to other diagnostic assays with imperfect detection.