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This paper explores the patterns of knowledge production of science and engineering from catching-up via overtaking to the achievement of leadership in global industries. In particular, it examines the depth and direction of knowledge production with proxy variables of patents and bibliometric data of a latecomer firm. Moreover, it explores the changing patterns of knowledge sourcing in the firm during the transition from catch-up to forging ahead and with specific references to the experience of Samsung Electronics Company. This study shows that the patterns of scientific and engineering activities increased as the firm proceeds to the forging ahead period, the patterns of knowledge sourcing evolved in the direction of increasing importance of the domestic knowledge base, and the collaborative partners for generating knowledge changed as the firm's capabilities were enhanced to approach cutting-edge technologies. This paper illuminates the importance of intraorganizational capabilities and domestic knowledge bases to advance a latecomer firm's knowledge generating capabilities into a stage of forging ahead. [ABSTRACT FROM AUTHOR]

Transformers are one of the most strategic components in balancing the voltage levels and hence a high priority is given to their performance [1]. It is established that, insulation technology plays a critical role in judging the performance and service life in oil filled apparatus [2]. Performance of the insulation system depends mainly on the deterioration behavior of insulation oil and paper. The mechanisms that are responsible for premature aging of oil/paper insulation are almost the same in all the oil filled apparatus. Yet, there will be a significant difference in the intensity of the aging mechanisms in different apparatus. This intensity is attributable to rating, design, and duration of operation for different machines. The detailed discussions on these mechanisms are presented in the subsequent sections of this paper. However, aging of service insulants is unavoidable and is to be maintained at a lower rate or arrested to the greatest possible extent, such that, catastrophic failures and unscheduled outages may be mitigated [3]. Normally, utilities follow scheduled condition monitoring activities to avoid the consequences of premature aging. Hence, knowledge on these in-service condition monitoring activities will be helpful in understanding the exact deterioration rate of the insulation system. Real time in-service experience of several transformer fleets that belong to United Kingdom utilities are reported in [4]. An early degradation of insulation is noticed through increase in acidity and furan concentration in oil for several transformers in the fleet. Authors investigated this early degradation in different perspectives including loading conditions, manufacturers, and oil chemistry changes. It is inferred that changes in oil chemistry is an important attribute for early degradation and hence utilities are advised to adopt different asset management strategies for affected and unaffected transformers in a fleet. Recently, failure rate data of service aged transformer fleets of an Australian utility were analyzed to establish the relationship between aging and different failure types [5]. It is noticed that degradation of the insulation system will be rapid after 20 years of service aging thus entailing the frequent condition monitoring activities after 20 years to identify premature aging failures. [ABSTRACT FROM AUTHOR]

The emergence of Internet of Things (IoT) and new manufacturing paradigms have brought greater complexity of massive datasets. Radio frequency identification (RFID), as one of the key IoT technologies, has been used to collect real-time production data to support the manufacturing decision-making in smart factories. The adoption of these technologies results in a large amount of data collection. To extract useful information from this data, this paper utilizes a big data approach to figure out useful insights from RFID-enabled data regarding possible bottlenecks or inefficiencies on the shop floor so as to improve the quality management. Time and quality are the main metrics measured in this paper, where the longest process times, part accuracy percentage, and failure rate are determined for each of the workers (UserIDs) and process types (ProcCodes). Key findings and observations are significant to make advanced decisions in the smart factory by making full use of the RFID captured data. Note to Practitioners— This paper was motivated by a real-life company which has used RFID technology for over ten years. Great myriad of data has been captured from frontline production shop floors where machines, workers, materials, and manufacturing jobs were logically associated. Processing time and quality data are studied in this paper so as to investigate the production performance in the RFID-enabled smart factory. [ABSTRACT FROM AUTHOR]

Decision support is a vital function in electronic commerce (e-commerce). The purpose of this paper is to construct a review-based decision support model for items comparison in e-commerce. The proposed model uses probability multivalued neutrosophic linguistic numbers (PMVNLNs) to characterize online reviews. It overcomes the limitation of existing models by considering neutral information and hesitancy in text reviews. The fuzzy characterization of reviews (i.e., PMVNLN) can reflect similarities and differences in positive (negative) information. In addition, the model considers consumers’ bounded rational behaviors by combining the regret theory with an outranking method. We empirically compare the proposed model with models in http://PConline.com and four existing models with data from http://PConline.com. The performance of these models in terms of accuracy is measured by the total relative difference metric. Results indicate the good performance of the proposed model. Our model is a promising option for e-commerce to provide consumers with good decision support service. [ABSTRACT FROM AUTHOR]

The article provides guidelines in the preparation of tutorial papers and teaching cases for use in classrooms or for publication in the "IEEE Transactions on Professional Communication."

Scalable two-terminal selector devices are key technology enablers for cross-bar array (CBA) architectures. Based on an analysis of CBA and sneak path, this paper discusses the essential characteristics of selector devices for the reduction of sneak leakage: nonlinearity and asymmetry. Both characteristics help to increase the resistance of sneak paths and reduce their impact on CBA operations. The reduction of sneak leakage and the improvement of CBA performance by selectors are quantified based on a comprehensive CBA model. The writing and reading operations of a 4-kb CBA are simulated as a case study, to analyze the effect of selector characteristics on CBA operations. [ABSTRACT FROM AUTHOR]

This paper proposes a collaborative approach to enhancing the student learning experience based on Web 2.0 principles. Specifically, wiki Web sites are used by students for collaboration and for publication of course assignments, which are then shared with the class. Web 2.0 principles include: the Web as platform, harnessing collective intelligence, data are the next Intel Inside, and rich user experiences. Based on a case study in a junior-level undergraduate class, this paper studies a set of six factors with comprehensive grading and evaluation criteria that are critical to make this approach successful. The six factors are knowledge base, motivation, research, social aspects, presentation, and feedback and support. The data collected show that most of the students who participated feel that this approach is exciting and rewarding, and that even some undergraduate students are able to produce original and innovative concepts. The data also show other interesting phenomena with respect to motivation, undergraduate research, and social aspects. Finally, the paper proposes a methodology of conducting a wiki project in a university class using a cyclic constant improvement process. [ABSTRACT FROM AUTHOR]

To remain competitive, it is critical for firms to integrate external sources of knowledge. However, finding the right degree of openness is challenging, especially in complex open innovation ecosystems. The interdependencies and dynamics related to the choice of openness are not well-understood. This paper investigates the role of openness as a competitive mechanism. Specifically, we research how openness affects firms’ interactions with user communities and how it changes the preference structure of customers. We build a longitudinal case study in the open source gaming handheld industry and trace the evolution and the dynamics of firms, user communities, and their interactions. We find that a suboptimal level of openness can pose a threat to a firm's very existence. Further, we identify repeated patterns characterizing the dynamics in the ecosystem. Based on these patterns, we propose a framework of the dynamics of openness. Our paper contributes to the literature on open innovation. We illuminate the relevance and the dynamics of openness as a dimension for competition. This paper also contributes to the literature on user innovation by showing a shift from manufacturer-based to user-based innovation over the course of the product lifecycle. [ABSTRACT FROM AUTHOR]

Severe Geomagnetic Disturbances (GMD) pose a threat to the reliability of the United States bulk electrical power system. The NERC reliability standard TPL-007 requires transmission planners to assess potential problems in their service territories due to Geomagnetically Induced Currents (GIC) including transformer thermal assessment. If the assessment indicates a vulnerability, the standard requires the development of a corrective action plan to resolve potential issues. GIC calculation accuracy is critical to the assessment. In this paper, the impact of various geoelectric field calculation methods on the accuracy of calculated GIC is evaluated by comparing with observations for a geomagnetic storm that occurred on 07–08 September, 2017. The GIC calculation is carried out for a fairly large-scale power system model and the comparison with observation indicates that better results are achieved using magnetotelluric transfer functions that incorporate the effects of 3-D earth conductivity. The results also indicate an improvement in the comparisons when the transfer-function derived E-fields are interpolated between the original survey site locations. [ABSTRACT FROM AUTHOR]

Real-world applications typically have multiple sparse reconstruction tasks to be optimized. In order to exploit the similar sparsity pattern between different tasks, this paper establishes an evolutionary multitasking framework to simultaneously optimize multiple sparse reconstruction tasks using a single population. In the proposed method, the evolutionary algorithm aims to search the locations of nonzero components or rows instead of searching sparse vector or matrix directly. Then the within-task and between-task genetic transfer operators are employed to reinforce the exchange of genetic material belonging to the same or different tasks. The proposed method can solve multiple measurement vector problems efficiently because the length of decision vector is independent of the number of measurement vectors. Finally, a case study on hyperspectral image unmixing is investigated in an evolutionary multitasking setting. It is natural to consider a sparse unmixing problem in a homogeneous region as a task. Experiments on signal reconstruction and hyperspectral image unmixing demonstrate the effectiveness of the proposed multitasking framework for sparse reconstruction. [ABSTRACT FROM AUTHOR]

Considering the difficulty and high cost of collecting sufficient data in the real world, driving simulators are used in many studies as an alternative data source, which can provide a much easier and safer way to collect driving data. However, because of the inherent differences between the virtual and real world, the recognition model for driving behavior trained using simulation-based data cannot fit the real driving scenes well. To fill the gap between simulation and real data, a knowledge transfer framework is proposed in this paper. Two transfer learning (TL) methods namely semi-supervised manifold alignment (SMA) and kernel manifold alignment (KEMA) are used in the proposed framework to map the data collected from the virtual and real world to one latent common space. A typical lane-changing scenario is selected for a case study. Three classifiers are trained in the latent space and used to do the lane-changing behavior recognition in the real world. In this way, sufficient simulation data are transferred to supplement the training set with few labeled real data, and thus improve the performance of behavior recognition in the real world. Compared with the traditional methods without knowledge transfer, classifiers combined with TL can reduce the error rate of recognition from around 30% (when only the real data are used) or higher than 50% (when only the simulation data are used) to as low as 11%. [ABSTRACT FROM AUTHOR]

This paper presents three case studies involving smartphone-based health sensing projects undertaken by our team. We highlight key challenges that we have encountered while advancing these projects beyond their pilot stages and propose potential directions for engineers, manufacturers, and researchers to address such challenges in the future. [ABSTRACT FROM AUTHOR]

Track-before-detect (TkBD) algorithms have been shown to greatly abate measurement-to-track association (MTA) challenges. These simplifications are aptly relevant for reducing operator workload in deployed sonar systems that require a human “in the loop.” This paper presents a case study of a passive bearings-only target motion analysis TkBD algorithm using two complex data sets: one simulated and one obtained at sea, which are representative of scenario characteristics typically encountered with advanced operational sonar systems. The simulated data set exhibits crossing contacts of differing signal-to-noise ratios and short data gaps. The at-sea data, obtained from an open ocean exercise, are used to assess performance under realistic conditions that exhibit high levels of clutter, varying background noise levels, fading contacts, a high bearing-rate contact, and large data gaps. The TkBD algorithm is designed for the general complexities encountered in the examined data sets and employs a particle filter that defines its likelihood function as the accumulation of raster bin values from the output of the sonar beamformer conditioned on the particle's state trajectory. For the scenarios examined the localization performance of the algorithm is encouraging. The paper briefly reviews the chief motivation for using a TkBD approach, which is to circumvent MTA. [ABSTRACT FROM AUTHOR]

In Part II of this paper, we demonstrate on a modified 24-bus IEEE Reliability Test System (RTS) that it is indeed possible to manage large-scale intermittent resources in coordination with price-responsive demand. The algorithms introduced in Part I of this paper are simulated assuming 20% and 50% wind capacity. We show that the look-ahead dispatch of the proposed method is physically implementable and, when used with elastic demand, can accommodate the integration of close to 50% wind capacity. This is contrasted with the observation that, without elastic demand, 50% wind integration is not physically implementable. From the perspective of total market surplus, the predictive dispatch of the proposed method is 3.8% suboptimal when compared to the centralized most efficient predictive economic dispatch. Further simulations are needed to test the feasibility of coordinating wind power and price-responsive demand on realistic large-scale power systems. [ABSTRACT FROM PUBLISHER]

In this paper, two optimization models for improvement of the boiler-turbine system performance are formulated. The models are constructed using a data-mining approach. Historical process data is clustered and the discovered patterns are selected for performance improvement of the boiler-turbine system. The first model optimizes a widely used performance index, the unit heat rate. The second model minimizes the total fuel consumption while meeting the electricity demand. The strengths and weaknesses of the two models are discussed. An industrial case study illustrates the concepts presented in the paper. [ABSTRACT FROM AUTHOR]

Scan chains are exploited to develop attacks on cryptographic hardware and steal intellectual properties from the chip. This paper proposes a secured strategy to test designs by inserting a certain number of inverters between randomly selected scan cells. The security of the scheme has been analyzed. Two detailed case studies of RC4 stream cipher and AES block cipher have been presented to show that the proposed strategy prevents existing scan-based attacks in the literature. The elegance of the scheme lies in its less hardware overhead. [ABSTRACT FROM AUTHOR]

Few existing visualization systems can handle large data sets with hundreds of dimensions, since high-dimensional data sets cause clutter on the display and large response time in interactive exploration. In this paper, we present a significantly improved multidimensional visualization approach named Value and Relation (VaR) display that allows users to effectively and efficiently explore large data sets with several hundred dimensions. In the VaR display, data values and dimension relationships are explicitly visualized in the same display by using dimension glyphs to explicitly represent values in dimensions and glyph layout to explicitly convey dimension relationships. In particular, pixel-oriented techniques and density-based scatterplots are used to create dimension glyphs to convey values. Multidimensional scaling, Jigsaw map hierarchy visualization techniques, and an animation metaphor named Rainfall are used to convey relationships among dimensions. A rich set of interaction tools has been provided to allow users to interactively detect patterns of interest in the VaR display. A prototype of the VaR display has been fully implemented. The case studies presented in this paper show how the prototype supports interactive exploration of data sets of several hundred dimensions. A user study evaluating the prototype is also reported in this paper. [ABSTRACT FROM AUTHOR]

Product innovation strategies of emerging market companies are increasingly challenging conventional wisdom. Drawing on a qualitative case study of Mahindra Reva, the only electric vehicle producer in India, this paper explores how a bricolage strategy enabled a resource-constrained emerging market firm to deliver affordable, innovative, and high-tech products with minimal capital investments. The findings of this study illustrate how multiple forms of bricolage can be implemented and managed at organizational and interorganizational levels. They show how different bricolage activities relate to different stages of the new product development process, and further, highlight the complementarities between bricolage and engineering activities. This paper argues that bricolage, which is typically regarded as a behavioral trait or skill that allows entrepreneurs and innovators to operate in challenging environments, can also be a carefully planned and executed strategy conducive to innovation. Thus, it suggests that a cost-effective bricolage strategy can underpin emerging market companies' development of discontinuity-creating and market disrupting technology products. [ABSTRACT FROM AUTHOR]

The condition of power transformers has a significant impact on the reliable operation of the electric power grid. A number of techniques have been in use for condition assessment of transformers. However, interpreting measurement data obtained from these techniques is still a non-trivial task; correlating measurement data to transformer condition is even more difficult. This paper investigates statistical learning techniques, which is able to learn statistical properties of a system from known samples and to predict the system output for unknown samples. Within the statistical learning framework, this paper develops a support vector machine (SVM) algorithm, which can be utilised for automatically analyzing measurement data and assessing condition of transformers. Case studies are presented to demonstrate the applicability of the developed algorithm for condition assessment of power transformer. [ABSTRACT FROM AUTHOR]

Rede Electrica Nacional (REN) is the operator of the Portuguese National Electricity Transmission Grid (RNT), which currently has about 170 large power transformers and autotransformers on the 400-, 220-, and 150-kV networks. Rede El?ctrica Nacional's network expansion and reinforcement program over the last few years has resulted in a significant increase in the number of installed units, number of substations, and the total mega volt amperes, as shown in Figure 1. Presently, about 24% of the units installed are more than 30 years old and 39% are up to 10 years old. The group of more recent units represents 47% of the total power installed, and most have a rated power above or equal to 120 MVA (84%), which is presently the minimum power rating specified for new transformers. Older units are still in service with power ratings of 60 to 90 MVA. [ABSTRACT FROM PUBLISHER]

The work reported in this paper aims at developing a practical and efficient tool for utility transmission planners to protect critical transmission assets from potential physical attacks. A trilevel min–max–min optimization model is proposed to represent actions of a planner, an attacker, and an operator. These three agents share a common objective function, which is the system load shedding. The strong duality theorem is used to merge the middle- and lower-level problems into a single-level one. The resulting mixed-integer bilevel model is solved by a Benders decomposition technique using primal cuts. Two case studies are presented as applications of this novel technique. Additionally, the proposed technique is compared with an implicit enumeration algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a generic model for analyzing the microwave power sensor calibration by direct comparison transfer. The model is derived using a signal flow graph together with nontouching loop rule analyses. The proposed model is investigated through several case studies which are commonly encountered and provides a theoretical basis for practical applications. Finally, realizations of the derived calibration equations for some practical cases are also discussed. [ABSTRACT FROM PUBLISHER]

The redundancy allocation problem has been extensively studied with the aim of determining optimal redundancy levels of components at various stages to achieve the required system reliability or availability. In most existing studies, failed elements are assumed to be as good as new after repair, from a failure perspective. Due to deterioration, the repaired element cannot always be restored to a virtually new condition unless replaced with a new element. In this paper, we present an approach of joint redundancy and imperfect maintenance strategy optimization for multi-state systems. Along with determining the optimal redundancy levels, the element replacement strategy under imperfect repair is also optimized simultaneously, so as to reach the desired availability with minimal average expenditure. A generalized imperfect repair model is proposed to characterize the stochastic behavior of multi-state elements (MSEs) after repair, and a replacement policy under which a MSE is replaced once it reaches the pre-determined number of failures is introduced. The cost-repair efficiency relation, which regards the imperfect repair efficiency as a function of assigned repair cost, is put forth to provide a flexibility of assigning repair efforts strategically among MSEs. The benefits of the proposed method compared to the existing ones are demonstrated and verified via an illustrative case study of a three-stage coal transportation system. [ABSTRACT FROM AUTHOR]

Though very important in software engineering, linking artifacts of the same type (clone detection) or different types (traceability recovery) is extremely tedious, error-prone, and effort-intensive. Past research focused on supporting analysts with techniques based on Natural Language Processing (NLP) to identify candidate links. Because many NLP techniques exist and their performance varies according to context, it is crucial to define and use reliable evaluation procedures. The aim of this paper is to propose a set of seven principles for evaluating the performance of NLP techniques in identifying equivalent requirements. In this paper, we conjecture, and verify, that NLP techniques perform on a given dataset according to both ability and the odds of identifying equivalent requirements correctly. For instance, when the odds of identifying equivalent requirements are very high, then it is reasonable to expect that NLP techniques will result in good performance. Our key idea is to measure this random factor of the specific dataset(s) in use and then adjust the observed performance accordingly. To support the application of the principles we report their practical application to a case study that evaluates the performance of a large number of NLP techniques for identifying equivalent requirements in the context of an Italian company in the defense and aerospace domain. The current application context is the evaluation of NLP techniques to identify equivalent requirements. However, most of the proposed principles seem applicable to evaluating any estimation technique aimed at supporting a binary decision (e.g., equivalent/nonequivalent), with the estimate in the range [0,1] (e.g., the similarity provided by the NLP), when the dataset(s) is used as a benchmark (i.e., testbed), independently of the type of estimator (i.e., requirements text) and of the estimation method (e.g., NLP). [ABSTRACT FROM AUTHOR]

The electrostatic discharge (ESD) sensitivity of ICs with respect to the charged-device model (CDM) is strongly dependent on the IC package, the substrate resistivity, and the effectiveness of the ESD protection network. This paper presents a case study of predictive CDM circuit simulation method based on the tester, package, and full IC modeling approach. [ABSTRACT FROM PUBLISHER]

This is the second part of a two-paper series. The first paper presented the transient modeling methodology for various components of wind power plants (WPPs). This paper presents a general methodology for transient analysis of WPPs and discusses case studies which investigate some of the most important high-frequency interactions between different components of the WPP. The focus has been on switching transients, and lighting transients have been excluded. Transient case studies conducted on a typical WPP are presented which discuss the impact of fast system surges on the performance of the circuit breaker and impact of fast surges caused by the circuit breaker on the adjacent power components. These case studies investigate the opening and closing of the collector grid vacuum circuit breaker for loaded and unloaded conditions. Simulation results provide a close match with the field measurements conducted on a laboratory prototype of a typical WPP. Differences caused by modeling assumptions or insufficient accuracy of measurement devices are highlighted. To understand the most onerous overvoltages that can be experienced in the test system, a couple of additional simulation case studies are reported. These case studies discuss the interruption of inrush current with an unloaded transformer and interruption of a small inductive current following the transformer energization. [ABSTRACT FROM PUBLISHER]

Tracking low-resolution (LR) targets is a practical yet quite challenging problem in real video analysis applications. Lack of discriminative details in the visual appearance of the LR target leads to the matching ambiguity, which confronts most existing tracking methods. Although artificially enhancing the video resolution by superresolution (SR) techniques before analyzing might be an option, the high demand of computational cost can hardly meet the requirements of the tracking scenario. This paper presents a novel solution to track LR targets without explicitly performing SR. This new approach is based on discriminative metric preservation that preserves the data affinity structure in the high-resolution (HR) feature space for effective and efficient matching of LR images. In addition, we substantialize this new approach in a solid case study of differential tracking under metric preservation and derive a closed-form solution to motion estimation for LR video. In addition, this paper extends the basic linear metric preservation method to a more powerful nonlinear kernel metric preservation method. Such a solution to LR target tracking is discriminative, robust, and efficient. Extensive experiments validate the entrustments and effectiveness of the proposed approach and demonstrate the improved performance of the proposed method in tracking LR targets. [ABSTRACT FROM AUTHOR]

This paper proposes a reliability model for a superconducting fault current limiter (SFCL), which is a new alternative in limiting the fault current recently increasing in a network. An evaluation technique for distribution reliability that uses the improved failure rate of all protective devices in a network, depending on the location of the SFCL, is also proposed. As a result, it is expected that the SFCL makes the reliability of adjacent equipment on an existing network improve, and these changes are analyzed. In addition, in order to apply the effect of the intermittent output of renewable-energy sources, distribution reliability indices were redefined in this paper. Case studies verify that the SFCL is effective in reducing fault currents and improving distribution reliability. These effects are analyzed with respect to the location of the SFCL in a case study system. [ABSTRACT FROM AUTHOR]

This paper discusses the results of a study of the requirements for developing a remote radio frequency (RF) laboratory for electrical engineering students. It investigates students' preferred usage of the technical content of a state-of-the-art RF laboratory. The results of this study are compared to previous findings, which dealt with other user groups (technicians in technical colleges and engineers in the RF domain). Based on the results of these analyses, seven essential principles for designing and developing such a laboratory were identified. As a case study, these principles were then implemented into a remote laboratory system. In this paper, the implementation examples are also provided and discussed. The primary aim of this study is to guide remote laboratory platform developers toward the most effective instructional design. This study also determined, from the remote laboratory system case study, what the requirements are of such a laboratory from the students' perspective. [ABSTRACT FROM AUTHOR]

A Reference Network Model (RNM) is a large-scale distribution planning tool that can help regulators to estimate efficient costs in the context of incentive regulation applied to distribution companies. This paper presents the main features of an RNM developed for planning distribution networks from scratch, greenfield planning, or incrementally from an existing grid. Two properties of the model are highlighted: the simultaneous planning of high-, medium-, and low-voltage networks by using simultaneity factors; and the layout of cables in urban areas, taking into consideration the street map, which is automatically generated by the model. A case study evaluates the impact of these features on the results. [ABSTRACT FROM AUTHOR]

Adverse weather such as hurricanes can have significant impact on power system reliability. One of the challenges of incorporating weather effects in power system reliability evaluation is to assess how adverse weather affects the reliability parameters of system components. In this paper, a fuzzy inference system (FIS) built by using fuzzy clustering method is combined with the regional weather model to solve the preceding problem. The composite power system is assumed to be partitioned into different regions and the FIS maps the nonlinear functional relationship between hurricane parameters and the increment multipliers of the failure rates (IMFR) of the transmission lines in different regions. The possible case that transmission lines traverse bordering regions is investigated by using the weighted average method. Since hurricanes last only a limited time period, the short-term reliability indices over the duration of hurricane instead of the steady-state ones are calculated by using the minimal cut-set method (MCSM). The proposed method is applied to the modified IEEE Reliability Test System (RTS). The implementation demonstrates that the proposed method is effective and efficient and is flexible in applications. [ABSTRACT FROM AUTHOR]

3-D integration technology is emerging as an attractive alternative to increase the transistor count for future chips. The majority of the existing 3-D integrated circuit (IC) research is focused on the performance, power, density, and heterogeneous integration benefits offered by 3-D integration. All such advantages, however, ultimately have to translate into cost evaluation when a design strategy has to be decided. Consequently, system-level cost analysis at early design stages is imperative to decide on whether 3-D integration should be adopted. This paper presents a cost estimation method for 3-D ICs at early design stages and proposes a set of cost models that include wafer cost, 3-D bonding cost, package cost, and cooling cost. The proposed 3-D IC cost estimation method can help designers analyze the cost implication for 3-D ICs during the design space exploration at the early stage, and it enables a cost-driven 3-D IC design flow that can guide the design choice toward a cost-effective direction. Based on the proposed cost estimation method, this paper demonstrates two case studies that explore the cost benefits of 3-D integration for application-specific integrated circuit designs and many-core microprocessor designs style, respectively. Finally, this paper suggests the optimum partitioning strategy for future 3-D IC designs. [ABSTRACT FROM AUTHOR]

Stability analysis of priority-based kinematic control algorithms for redundant robotic systems is approached in this paper. Starting from the classical applications in position control of manipulators, the kinematic-based approaches have lately been applied to, e.g., visual servoing and quadruped or multirobot coordination control. A common approach consists in the definition of several tasks properly combined in priority. In this paper, by resorting to a Lyapunov-based stability discussion for several prioritized inverse kinematics algorithms, sufficient conditions for the control gains and the tasks' design are given for the regulation problem. Two case studies show the practical implementation of the results. [ABSTRACT FROM AUTHOR]

One of the most common problems in recommender systems is a "cold-start" problem, which is related to users who do not indicate any behavior on social media. This paper proposes a solution for tackling this problem by using data mining techniques and improving the recommender systems by using the Cuckoo algorithm. [ABSTRACT FROM AUTHOR]

Mega-engineering projects in the construction industry are generally carried out by public–private partnership models with the participation of different stakeholders. This paper aims to identify the effect of stakeholder-associated risks on the success of mega-engineering projects. Therefore, the risks were determined and then validated by focus discussions. Afterwards, an illustrative case study was presented to better understand the effects. Finally, a fuzzy analytical hierarchy process method was used to prioritize the identified risks. The prominent risks were found to include “improper partner selection,” “inadequate relationships with employer,” and “incompetent contractor selection.” Engineering managers need to work in close coordination with all members of the project. To better manage projects, engineering managers are expected to be familiar with the concepts of project risk management, because effective project risk management has a direct and positive effect on project management performance. Professionals in the field of engineering management can benefit greatly from the findings of this study by using it as a baseline for coordinating the relationships in multistakeholder organizational structures and analyzing stakeholder-associated risks throughout their projects. [ABSTRACT FROM AUTHOR]

With recent improvements in healthcare, individuals with Duchenne muscular dystrophy (DMD) have prolonged life expectancy, and it is therefore vital to preserve their independence. Hand function plays a central role in maintaining independence in daily living. This requires sufficient grip force and the ability to modulate it with no substantially added effort. Individuals with DMD have low residual grip force and its modulation is challenging and fatiguing. To assist their hand function, we developed a novel dynamic hand orthosis called SymbiHand, where the user’s hand motor intention is decoded by means of surface electromyography, enabling the control of an electrohydraulic pump for actuation. Mechanical work is transported using hydraulic transmission and flexible structures to redirect interaction forces, enhancing comfort by minimizing shear forces. This paper outlines SymbiHand’s design and control, and a case study with an individual with DMD. Results show that SymbiHand increased the participant’s maximum grasping force from 2.4 to 8 N. During a grasping force-tracking task, muscular activation was decreased by more than 40% without compromising task performance. These results suggest that SymbiHand has the potential to decrease muscular activation and increase grasping force for individuals with DMD, adding to the hand a total mass of no more than 241 g. Changes in mass distributions and an active thumb support are necessary for improved usability, in addition to larger-scale studies for generalizing its assistive potential. [ABSTRACT FROM AUTHOR]

For application specialists to accept virtual reality (VR) as a valid new measuring environment, we conducted several case studies. This paper describes a case study in dentistry in which VR is used to measure the length of the root canal of a tooth from processed tomography data. This paper shows the advantages of measuring in visualization space rather than in reality. We present a software framework aimed at the application specialist rather than the VR expert. Furthermore, the VR measuring technique is analyzed and compared to traditional measuring techniques for this particular application. We show that VR allows for intuitive measuring paradigms that are accurate and versatile alternatives to situations where traditional techniques are deficient. [ABSTRACT FROM AUTHOR]

The article discusses some issues that are relevant to other software technologies with similar types of evidence on model-based testing (MBT). MBT approaches not only help generate test cases using models extracted from software artifacts, it also promises to affect how users build software as well as the level of confidence developers can have that their software meets its requirements. An assessment of available MBT case studies highlighted its use in hardware or embedded systems such as processor architectures, communication protocols, and smart-card applications.

This paper studies the impact of government's incentives on a fresh-product supply chain (FSC) system with a stochastic multifactor-dependent demand. The investigated supplier–buyer chain is modeled using two different approaches including: 1) the traditional selling cycle (TSC) in the open market without considering the government's incentives; and 2) the modern selling cycle (MSC) in the organized market considering the government's incentives. In the TSC approach, a Stackelberg game model is proposed for deteriorating products by considering the shortage inventory, the leftover inventory, and value-added tax (VAT) plan. The stochastic demand is dependent on the retail price, freshness degree of the fresh-product item, and marketing efforts. To develop a model for the MSC approach, we have extended the model of a TSC approach considering the government's incentives including short-term tax breaks and a single-window system. Finally, the proposed models are approved with a dataset from a real-life case study. The results show that the government's incentives increase the profit of all the FSC members under the MSC approach. Moreover, the results of conducted sensitivity analyses help governments to accurately adjust the VAT rate and commission percentages in TSC and MSC approach, respectively. [ABSTRACT FROM AUTHOR]

In large organizations, local use of innovations is not enough; extracting the full use of the innovation requires deployment across the organization. The purpose of this paper is to explore strategies for the deployment of service innovations and factors influencing success. We adopt an inductive theory-building approach with a longitudinal embedded case study of ten successful service innovations. We find two deployment strategies: required adoption, in which subsidiaries are required to adopt innovations, and voluntary adoption, in which adoption is not compulsory—innovations are showcased, but the adoption decision is left to the subsidiaries. We have investigated the factors influencing deployment, including the decentralized nature of service innovation, fit with the internal and external context, extrinsic and intrinsic motivations, and handovers. Based on analyses of case evidence, we put forward research propositions accordingly. This study provides managerial guidance for multidivisional organizations to extract full value from service innovations. Although some results may be particular to the Chinese context, research in other contexts can broaden the generalizability of the findings. [ABSTRACT FROM AUTHOR]

During the last 10–15 years, there has been an increasingly growing number of reports on the so-called stray gassing of mineral insulating oils. Some contributions suggested that the problem may be connected with introducing new types of insulating oils [1] and mainly associated with evolution of hydrogen, as also confirmed by transformer oil producers [2]. Oil passivation has also been reported to contribute to stray gassing, being used as a remedy for sulfur corrosion problems [3]. We exclude from further consideration gassing due to material incompatibilities, e.g., outgassing of paints, cross-linked polyethylene (XLPE) or other materials, as it remains the transformer manufacturer's duty to develop test methods for avoiding this problem. [ABSTRACT FROM AUTHOR]

Several wireless charging methods are under development or available as an aftermarket option in the light-duty automotive market. However, there are not a sufficient number of studies detailing the vehicle integration methods, particularly a complete vehicle integration with higher power levels. This paper presents the design, development, implementation, and vehicle integration of wireless power transfer (WPT) based electric vehicle charging systems for various test vehicles. Before having the standards effective, it is expected that WPT technology first will be integrated as an aftermarket retrofitting approach. Inclusion of this technology on production vehicles is contingent upon the release of the international standards. The power stages of the system are introduced with the design specifications and control systems, including the active front-end rectifier with power factor correction, high frequency power inverter, high frequency isolation transformer, coupling coils, vehicle side full-bridge rectifier and filter, and the vehicle battery. The operating principles of the control and communication systems are presented. Aftermarket conversion approaches, including the WPT on-board charger integration, WPT CHAdeMO integration, and WPT direct battery connection scenarios, are described. The experiments are carried out using the integrated vehicles and the results obtained to demonstrate the system performance including the stage-by-stage efficiencies. [ABSTRACT FROM AUTHOR]

The rapidly emerging technology of Web services paves a new cost-effective way of engineering software to quickly develop and deploy Web applications by dynamically integrating other independently developed Web-service components to conduct new business transactions. This paper reports our efforts on designing and developing a Web service of pass-through authentication (PTA) for 12 online electronic-payment Web applications. In accordance with how a PTA service is developed and integrated with a corresponding back-end e-payment system, our strategies can be categorized in three stages: end-to-end integration stage, Web-services-enabled stage, and Web-services-oriented stage. Derived from real-world industrial experience, this three-stage pathway can be applied to a broad range of Web-application development projects to guide smooth transformation from a specific application-oriented design and development model toward a reusable Web-services-oriented model. Furthermore, this paper contributes to an engineering process that leads to practical Web-services-oriented software development. New research issues revealed by this project are also reported. [ABSTRACT FROM AUTHOR]

Many robot systems employ logic-based or reactive controllers, making them hybrid systems (i.e., mixed discrete continuous). However, designing such control laws in a systematic manner remains a challenging task. In this paper, we apply the formal modeling paradigm to a team of mobile robots. The linear hybrid automata modeling framework is used to describe the high-level design, and the verification software HYTECH is used for symbolic analysis of the description. The goal is to symbolically quantify system-level performance as a function of the design parameters, for the purpose of optimizing and synthesizing design parameters, verifying safe operation, and quantitatively exploring tradeoff issues. In order to make the analysis tractable, a series of restrictive assumptions and simplifications must be made-some dictated by the linear hybrid automata model and others necessitated by computational cost. We comment on the restrictiveness of these assumptions and the overall utility of this automated analysis approach in designing complex robotic systems. [ABSTRACT FROM AUTHOR]

The feature selective validation (FSV) method has been proposed as a technique to allow the objective, quantified, comparison of data for inter alia validation of computational electromagnetics. In the companion paper "Feature selective validation for validation of computational electromagnetics. Part I–The FSV method," the method was outlined in some detail. This paper addresses two specific issues related to the implementation of the FSV method, namely "how well does it produce results that agree with visual assessment?" and "what benefit can it provide in a practical validation environment?" The first of these questions is addressed by comparing the FSV output to the results of an extensive survey of EMC engineers from several countries. The second is approached via a case study analysis. [ABSTRACT FROM AUTHOR]

It is challenging to get reliable performance benchmarking results. Benchmarking matters because one of the defining characteristics of big data systems is the ability to process large datasets faster. “How large” and “how fast” drive technology choices, purchasing decisions, and cluster operations. Even with the best intentions, performance benchmarking is fraught with pitfalls—easy to get numbers, hard to tell if they are sound. This paper discusses five common pitfalls drawn from engineering and customer experiences at Cloudera, a leading big data vendor. These pitfalls are: “Comparing Apples to Oranges”—when too many parameters are modified and comparison is impossible, “Not Testing at Scale”—trying to test a big data system by extrapolating from an under-sized test system, “Believing in Miracles”—failing to question suspicious results, “Using Unrealistic Benchmarks”—using workloads far removed from what will realistically be used by customers, and “Communicating Results Poorly”—neglecting to communicate sufficient information for customers to understand and reproduce the results. These pitfalls offers a behind-the-scenes look at internal engineering and review processes that produces rigorous benchmark results. Readers working on big data in both the industry and in academia can draw lessons from our experience. [ABSTRACT FROM PUBLISHER]

Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist. Instead, computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this paper, we provide a taxonomy of different data driven evolutionary optimization problems, discuss main challenges in data-driven evolutionary optimization with respect to the nature and amount of data, and the availability of new data during optimization. Real-world application examples are given to illustrate different model management strategies for different categories of data-driven optimization problems. [ABSTRACT FROM AUTHOR]