bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reducing Waste Outflow to Motivate Water Conservation
Authors: Halabieh S. , Shu L. H. 
Published: November 2021

Abstract
Resource-consumption systems can be defined by a resource inlet, a control volume where the resource is used, and a waste outlet. Specific to water, many existing conservation strategies focus on reducing the in-flow of water into a control volume. Instead, this work explores reducing waste out-flow, which causes accumulation in the control volume. This strategy aims to motivate users to reduce resource in-flow in response to accumulation in the control volume, and thus modify behavior.
To test this strategy, Amazon Mechanical Turk workers completed three randomly ordered handwashing simulations with different sink-outflow rates online. Study participants (N = 74) significantly reduced consumption of water when it accumulated quickly in the sink (p &lt; 0.0001). Participants reduced water consumption, on average by 14% at lower outflow rates, as they decreased inflow rates to prevent sink overflow.
Many pro-environmental behavior interventions are limited in their reliance on user motivation and intention to reduce resource consumption. In contrast, the reduced-outflow intervention significantly reduced water usage (p &lt; 0.001) of individuals, regardless of self-reported daily pro-environmental behavior. This result suggests that the developed intervention relies less on user intention. Overall results support that reducing outflow can increase sustainable user behavior when properly executed. In-person testing is discussed as future work.
Exploring a Temperature-Decreasing Shower Concept to Conserve Water and Energy
Authors: Saniei N. , Shibata E. , Lui S. , Magcalas J. , McPhee B. , Tariq S. , Shu L. H. 
Published: November 2021

Abstract
Climate change is threatening the availability, quality and quantity of water for basic human needs. In much of North America, showering is an activity that consumes significant water, as well as energy to heat the water. This study investigates the feasibility of an intervention that gradually decreases shower-water temperature to encourage shorter shower times, towards reduced water and energy usage.
The two parts of this work were performed over two academic years. The first part explored user acceptance in 23 study participants who underwent a shower while manually decreasing their own water temperature, as prescribed by a protocol. Immediately following the temperature-decreasing shower, participants were asked questions to assess their attitudes and willingness to use or install such a shower concept. Participants also completed questionnaires determining their regulatory focus and environmental attitudes, the effects of which on their attitudes about the shower concept are discussed.
Over 56% of participants were able to abide by the temperature-decreasing showering protocol. Out of 23 participants, only 3 found the temperature-decreasing shower experience to be negative, 12 were neutral, and the remaining 8 found the experience to be a positive one.
Given this result, the second part of the work implemented a microcontroller-based system that automatically controls shower temperature, pressure, and duration. This system is described and simulations are used to project the resource-saving potential of the concept.
Kinematic Modeling and Inverse Kinematics of Serial 6R Fragment of Molecule
Authors: Arikawa Keisuke 
Published: November 2021

Abstract
Depending on their mobilities around bond axes, molecules (e.g., proteins, DNA, and RNA) can be modeled as robotic manipulators. We focus on the serial 6R fragments, or the fragments containing six revolute joints connected in series, extracted from these molecules. We solved the inverse kinematics problems of the fragments. We obtained multiple conformations that maintained the relative position and orientation between both ends. Raghavan and Roth’s solution effectively conveys all real solutions. However, the solution is not directly applicable when some link lengths are zeros. To cope with the problem, in addition to the known method based on the modified elimination, we introduced the small-length link strategy. Here, by setting sufficiently small values for the zero-length links, we solved the inverse kinematics problems based on Raghavan and Roth’s solution combined with the symbolic formulation. Moreover, we formulated a method to systematically build manipulator models from structural data of molecules. We systematically identified the Danavit-Hartenberg parameters (link length, offset, and twist angle) and joint angles at the conformation in the structural data from the seven pairs of positions of atoms. Finally, using the structural data of a protein stored in the protein data bank, we demonstrated an application example of kinematic modeling and inverse kinematics calculation.
Normal Form of Bifurcation for Caputo-Hadamard Fractional Differential System With a Parameter
Authors: Yin Chuntao 
Published: November 2021

Abstract
This paper focuses on the normal form computation of the pitchfork bifurcation for the Caputo-Hadamard fractional differential system with a parameter. By using Taylor’s expansion and Implicit Function Theorem, we derive the normal form of the pitchfork bifurcation for the Caputo-Hadamard fractional differential system with a parameter.
Orientation Control of Self-Righting Tensegrity Landers
Authors: Zhang Alan , Hutchings Douglas , Gupta Mayank , Agogino Alice 
Published: November 2021

Abstract
Squishy Robotics, Inc. has developed a spherical sensor robot that can be rapidly deployed by air drops of up to 1,000 ft for emergency response situations to improve situational awareness for first responders. Although the tensegrity structure has successfully been shown to survive the drop, some payloads require orientation when they land. For example, a payload that contains sensors and communication equipment to relay the data may need the robot to be oriented such that the antennas are pointing upward, or some sensors are positioned in a specific plane for operation. This requirement presents a challenge for a tensegrity-based delivery system because the structure absorbs energy using passive compliance and bounces several times upon landing. Although active systems using motors and actuators could be used to control orientation after landing, they increase the overall weight and complexity of the system. This paper describes the research on a passive control solution that achieves the correct orientation by placing weights on selected rods forming an asymmetrically weighted tensegrity structure that preferentially rolls and orients itself during the impact process. The design approach is applied to three robot sizes and the self-righting behavior is validated through experimental results.
A Simple Approach for the Computation of Lyapunov-Floquet Transformations for the Mathieu Equation
Authors: Sharma Ashu 
Published: November 2021

Abstract
Lyapunov-Floquet (L-F) transformations reduce linear ordinary differential equations with time-periodic coefficients (so-called linear time-periodic systems) to equations with constant coefficients. The present work proposes a simple approach to construct L-F transformations. The solution of a linear time-periodic system can be expressed as a product of an exponential term and a periodic term. Using this Floquet form of a solution, the ordinary differential equation corresponding to a linear time-periodic system reduces to an eigenvalue problem. Next, eigenanalysis is performed to obtain the general solution and subsequently, the state transition matrix of the time-periodic system is constructed. Then, the Lyapunov-Floquet theorem is used to compute L-F transformation. The inverse of L-F transformation is determined by defining the adjoint system to the time-periodic system. Mathieu equation is investigated in this work and L-F transformations and their inverse are generated for stable and unstable cases. These transformations are very useful in the design of controllers using time-invariant methods and in the bifurcation studies of nonlinear time-periodic systems.
Racing Driver Modeling Based on Driving Behavior
Authors: Wang Jinzhen , Cheng Yiming , Yu Liangyao 
Published: November 2021

Abstract
The driver model is an important link in the research of shared autonomy control. In order to simulate the driver’s handling characteristics in the complex human-vehicle-road closed-loop system, the driver model is required to accomplish the driving operation under specific working conditions. In this paper, a lateral-longitudinal combined racing driver model is designed. The lateral control model adopts the preview model with far and near viewpoints and the dynamic velocity controller is added into the longitudinal control model to obtain the expected speed of the target trajectory. Finally, the racing driver model proposed in this paper is validated through simulation on track conditions of FSAE. In the given conditions, the result shows the racing driver model outperforms the typical driver model in lateral path tracking and the speed of racing driver model is higher than typical model on straight and corners. Meanwhile, the representation of driving skills is a key step to enhance the adaptive control of vehicles in the future. The control parameters can be adjusted according to the driver’s skill information to make the vehicle control system adapt to the driver’s skill level. This paper introduces the method of driving skill recognition based on wavelet transform and Lipschitz singularity detection theory and the preliminary test results prove the feasibility of using this method to characterize the driver’s operating skill level.
A Graphical Stability Analysis Method for Cascade Conjugate Order Systems
Authors: Cetintas Gulten , Hamamci Serdar Ethem 
Published: November 2021

Abstract
The theory and applications of complex fractional analysis have recently become a hot topic in the fields of mathematics and engineering. Therefore, studies on the complex order systems and their subset called the complex conjugate order systems began to appear in the control community. On the other hand, the concept of stability has always been an important issue, especially in the analysis and control of dynamical systems. In this paper, a graphical method for stability analysis of the complex conjugate order systems is presented. Since the proposed method is based on the Mikhailov stability criterion known from the stability theory of integer order systems, it is named the generalized modified Mikhailov stability criterion. This method gives stability information about the higher order complex conjugate order systems, i.e. cascade conjugate order systems, according to whether it encloses the origin in the complex plane or not. Three simulation examples for the cascade conjugate order systems are given to show the effectiveness and reliability of the method presented. The results are verified by the poles on the first sheet of Riemann surface and also time responses of the systems, which are calculated analytically in a very complex way.
A User-Centered Medical Device Design Decision Making Approach Using Hybrid Rough Cooperative Game Model
Authors: Jing Liting , Ma Junfeng 
Published: November 2021

Abstract
With the advancement of new technologies and diverse customer-centered design requirements, the medical device design decision making becomes challenge. Incorporating multiple stakeholders’ requirements into the medical device design will significantly affect the market competitiveness and performance. The classic design decision making approaches mainly focused on design criteria priority determination and conceptual schemes evaluation, which lack the capacity of reflecting the interdependence of interest among stakeholders and capturing the ambiguous influence on the overall design expectations, leading to the unreliable decision making results. In order to relax these constraints in the medical device design, this paper incorporates rough set theory with cooperative game theory model to develop a novel user-centered design decision making framework. The proposed approach is composed of three components: 1) end/professional user needs identification and classification, 2) evaluation criteria correlation diagram and scheme value matrix establishment using rough set theory; and 3) fuzzy coalition utility model development to obtain optimal desirability considering users’ conflict interests. We used a blood pressure meter case study to demonstrate and validate the proposed approach. Compared with the traditional Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, the proposed approach is more robust.
A Strategy for Fine Mesh Resolution in Contact Mechanics
Authors: Chauda Gaurav , Segalman Daniel J. 
Published: November 2021

Abstract
To obtain detail in elastic, frictional contact problems involving contact many — at least tens, and more suitably hundreds [1] — of nodes are necessary over the contact patch. Generally, this fine discretization results in intractable numbers of system equations that must be solved, but this problem is greatly mitigated when the elasticity of the contacting bodies is represented by elastic compliance matrices rather than stiffness matrices.
An examination of the classical analytic expressions for the contact of disks — an example of smooth contact — shows that for most standard engineering metals, such as brass, steel, or titanium, the pressures that would cause more than one degree of arc of contact would push the materials past the elastic limit.
The discretization necessary to capture the interface tractions would be on the order of at least tens of nodes. With the resulting boundary integral formulation would involve several hundreds of nodes over the disk, and the corresponding finite element mesh would have tens of thousands. The resulting linear system of equations must be solved at each load step and the numerical problem becomes extremely difficult or intractable.
A compliance method of facilitating extremely fine contact patch resolution can be achieved by exploiting Fourier analysis and the Michell solution. The advantages of this compliance method are that only degrees of freedom on the surface are introduced and those not in the region of contact are eliminated from the system of equations to be solved.
Automatic Composition of Encoding Scheme and Search Operators in System Architecture Optimization
Authors: Apaza Gabriel , Selva Daniel 
Published: November 2021

Abstract
The purpose of this paper is to propose a new method for the automatic composition of both encoding schemes and search operators for system architecture optimization. The method leverages prior work that identified a set of six patterns that appear often in system architecture decision problems (down-selecting, combining, assigning, partitioning, permuting, and connecting). First, the user models the architecture space as a directed graph, where nodes are decisions belonging to one of the aforementioned patterns, and edges are dependencies between decisions that affect architecture enumeration (e.g., the outcome of decision 1 affects the number of alternatives available for decision 2). Then, based on a library of encoding scheme and operator fragments that are appropriate for each pattern, an algorithm automatically composes an encoding scheme and corresponding search operators by traversing the graph. The method is demonstrated in two case studies: a study integrating three architectural decisions for constructing a portfolio of earth observing satellite missions, and a study integrating eight architectural decisions for designing a guidance navigation and control system. Results suggest that this method has comparable search performance to hand-crafted formulations from experts. Furthermore, the proposed method drastically reducing the need for practitioners to write new code.
Reliability-Based Co-Design of Lithium-Ion Batteries for Enhanced Fast Charging and Cycle Life Performances
Authors: Cui Tonghui , Wang Pingfeng 
Published: November 2021

Abstract
As enablers of electric vehicles, lithium-ion batteries are drawing much attention for their high energy density and low self-discharging rate. However, “range anxiety” has remained a significant hindrance to its further development. Of the many design objectives, minimizing the charging time and maximizing the cycle life are conflicting design objectives. In the past, enormous efforts have been carried out to resolve the dispute between high charging rates and large capacity losses by either improving the battery design or optimizing the charging/discharging protocols. However, the battery design and the control are usually coupled that integration of the two discipline, or control co-design, may offer improved performances as compared with traditional sequential optimization approaches. In an previous study, we have shown that efficient control co-design is achievable for Lithium-ion batteries through surrogate modeling. In this work, a reliability-based design optimization framework is integrated to guarantee the performances under parametric uncertainties. The challenges, such as simultaneous model update for the dynamic system and excessive computation burden due to optimal control and reliability assessment, are resolved through coupling the first principle model and the empirical models by an adaptive surrogate modeling process. Such a combination captures the multi-scale nature of the battery and allows efficient numerical analysis for the reliability-based co-design (RBCD) problem. A nested co-design approach and a double-loop reliability assessment method were implemented. The results show that the algorithm can shorten the charging time while satisfying the probability constraint on the cycle-life performances under parametric uncertainties.
Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment
Authors: Hu Shuaizhou , Zhang Xinyao , Liao Hao-yu , Liang Xiao , Zheng Minghui , Behdad Sara 
Published: November 2021

Abstract
Remanufacturing sites often receive products with different brands, models, conditions, and quality levels. Proper sorting and classification of the waste stream is a primary step in efficiently recovering and handling used products. The correct classification is particularly crucial in future electronic waste (e-waste) management sites equipped with Artificial Intelligence (AI) and robotic technologies. Robots should be enabled with proper algorithms to recognize and classify products with different features and prepare them for assembly and disassembly tasks. In this study, two categories of Machine Learning (ML) and Deep Learning (DL) techniques are used to classify consumer electronics. ML models include Naïve Bayes with Bernoulli, Gaussian, Multinomial distributions, and Support Vector Machine (SVM) algorithms with four kernels of Linear, Radial Basis Function (RBF), Polynomial, and Sigmoid. While DL models include VGG-16, GoogLeNet, Inception-v3, Inception-v4, and ResNet-50. The above-mentioned models are used to classify three laptop brands, including Apple, HP, and ThinkPad. First the Edge Histogram Descriptor (EHD) and Scale Invariant Feature Transform (SIFT) are used to extract features as inputs to ML models for classification. DL models use laptop images without pre-processing on feature extraction. The trained models are slightly overfitting due to the limited dataset and complexity of model parameters. Despite slight overfitting, the models can identify each brand. The findings prove that DL models outperform them of ML. Among DL models, GoogLeNet has the highest performance in identifying the laptop brands.
Physics-Informed Machine Learning for Degradation Diagnostics of Lithium-Ion Batteries
Authors: Thelen Adam , Lui Yu Hui , Shen Sheng , Laflamme Simon , Hu Shan , Hu Chao 
Published: November 2021

Abstract
State of health (SOH) estimation of lithium-ion batteries has typically been focused on estimating present cell capacity relative to initial cell capacity. While many successes have been achieved in this area, it is generally more advantageous to not only estimate cell capacity, but also the underlying degradation modes which cause capacity fade because these modes give further insight into maximizing cell usage. There have been some successes in estimating cell degradation modes, however, these methods either require long-term degradation data, are demonstrated solely on artificially constructed cells, or exhibit high error in estimating late-life degradation. To address these shortfalls and alleviate the need for long-term cycling data, we propose a method for estimating the capacity of a battery cell and diagnosing its primary degradation mechanisms using limited early-life degradation data. The proposed method uses simulation data from a physics-based half-cell model and early-life degradation data from 16 cells cycled under two temperatures and C rates to train a machine learning model. Results obtained from a four-fold cross validation study indicate that the proposed physics-informed machine learning method trained with only 60 early life data (five data from each of the 12 training cells) and 30 high-degradation simulated data can decrease estimation error by up to a total of 9.77 root mean square error % when compared to models which were trained only on the early-life experimental data.
Design 3D Printed Coils for WPT
Authors: Xu Jun , Doubrovski E. (Zjenja) L. , Geraedts Jo M. P. , Song Yu (Wolf) 
Published: November 2021

Abstract
The geometric shapes of coils influence the performance of a 3D IPT system. In this paper, we proposed a 3D coil design method based on (3D) printing electronics. Given a 3D transmitter coil, the center position of the receiver coil is estimated as a random seed position in the corresponding 3D surface first. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the coil. For each extension of the coil, i.e. a new turn, the shape of the coil is optimized by calculating the convex hull of the new turn in the 2D projection plane. Using this method, we are able to generate a receiver coil to transmit “just enough” power at a given seed position. Then, by fixing the receiver coil, the 3D shape of the transmitter coil can be optimized as well. This zig-zag optimization process iterates until there are few changes of the position and 3D shapes in the iteration. Experiment results with Ansys Maxwell verified the effectiveness of the proposed 3D coil design method, and highlighted possible future research directions as well.