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Focuses on the reliability and power quality at Champion International Corp. paper mill in Deferiet, New York. Numerous process interruptions experienced by Champion; Voltage sags emanating from the Niagara Mohawk Power Corp. transmission system; Causes and location of faults; Mitigation techniques.

The IEEE International Conference on Plasma Science (ICOPS) is held annually, sponsored by the Plasma Science and Applications Committee (PSAC) of the IEEE Nuclear and Plasma Science Society (NPSS). The 45th IEEE NPSS ICOPS was held on June 24–28, 2018, in Denver, CO, USA. The conference's technical program included a wide range of topics, which ranged from basic and fundamental research to traditional and emerging technology applications. Over 530 accepted abstracts, representing scientists from over 30 countries. The program also included a minicourse on “New Directions in Plasma Diagnostics for High Energy Density and Burning Plasmas.” This year, the ICOPS sessions were enhanced by several exceptional plenary talks and two IEEE Birdsall award talks. John Cary from the University of Colorado (the 2016 Birdsall Award Winner) gave a talk entitled “The Evolution of Computational Physics,” and Alex Friedman from the Lawrence Livermore National Laboratory (the 2017 Birdsall Award Winner) spoke on “Computer Simulations of Plasmas and Beams: A View From Multiple Angles.” Other plenary talks covered areas that included: particle accelerator technology; challenges of high-energy density physics and inertial fusion; the physics, chemistry, and interactions of plasma with liquids; radiation belt remediation; and electron beams, plasmas, and EM fields and waves. [ABSTRACT FROM AUTHOR]

This paper presents a unified physics-based insulated-gate bipolar transistor (IGBT) compact model for circuit simulation that predicts the performance of both Si and SiC, n- and p-channel devices. The model can predict the detailed switching waveforms of these technologies based on its charge-based formulation. Further, this compact IGBT model is presented alongside a unique datasheet-driven parameter extraction process. The parameter extraction process enables users to quickly extract model parameters from data typically published without the need of taking physical measurements. The model has been validated with both Si and SiC devices for static and dynamic characteristics. The SiC IGBTs used for validation are a 12.5-kV n-channel device and a 13-kV p-channel device, while the Si IGBT chosen was IXDH30N120 from IXYS Corp. (Milpitas, CA, USA). This is the only IGBT model that predicts the performance of both n- and p-channel, Si and SiC devices, providing more freedom for the development of complex power electronics circuit designs. The convergence of the model has been verified by implementing a complex circuit consisting of both a dc–dc converter and a dc–ac inverter. The results presented here show that the unified model can be used to describe the behavior of a wide range of Si and SiC IGBT circuits. This paper is accompanied by a Verilog-A source code and a power point file demonstrating the model parameter extraction sequence. [ABSTRACT FROM AUTHOR]

In this paper, we consider the development of algorithms for the automatic detection of buried threats using ground penetrating radar (GPR) measurements. GPR is one of the most studied and successful modalities for automatic buried threat detection (BTD), and a large variety of BTD algorithms have been proposed for it. Despite this, large-scale comparisons of GPR-based BTD algorithms are rare in the literature. In this paper, we report the results of a multi-institutional effort to develop advanced BTD algorithms for a real-world GPR BTD system. The effort involved five institutions with substantial experience with the development of GPR-based BTD algorithms. In this paper, we report the technical details of the advanced algorithms submitted by each institution, representing their latest technical advances, and many state-of-the-art GPR-based BTD algorithms. We also report the results of evaluating the algorithms from each institution on the large experimental data set used for development. The experimental data set comprised 120 000 m2 of GPR data using surface area, from 13 different lanes across two U.S. test sites. The data were collected using a vehicle-mounted GPR system, the variants of which have supplied data for numerous publications. Using these results, we identify the most successful and common processing strategies among the submitted algorithms, and make recommendations for GPR-based BTD algorithm design. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) is the third most common cause of cancer death in the United States. Predicting tumors like PDACs (including both classification and segmentation) from medical images by deep learning is becoming a growing trend, but usually a large number of annotated data are required for training, which is very labor-intensive and time-consuming. In this paper, we consider a partially supervised setting, where cheap image-level annotations are provided for all the training data, and the costly per-voxel annotations are only available for a subset of them. We propose an Inductive Attention Guidance Network (IAG-Net) to jointly learn a global image-level classifier for normal/PDAC classification and a local voxel-level classifier for semi-supervised PDAC segmentation. We instantiate both the global and the local classifiers by multiple instance learning (MIL), where the attention guidance, indicating roughly where the PDAC regions are, is the key to bridging them: For global MIL based normal/PDAC classification, attention serves as a weight for each instance (voxel) during MIL pooling, which eliminates the distraction from the background; For local MIL based semi-supervised PDAC segmentation, the attention guidance is inductive, which not only provides bag-level pseudo-labels to training data without per-voxel annotations for MIL training, but also acts as a proxy of an instance-level classifier. Experimental results show that our IAG-Net boosts PDAC segmentation accuracy by more than 5% compared with the state-of-the-arts. [ABSTRACT FROM AUTHOR]

The standard for electrical safety in the workplace, National Fire Protection Association 70E, and relevant Occupational Safety and Health Act electrical safety standards evolved in the U.S. over the past 40 years to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. This leaves a substantial gap in the management of other types of electrical hazards including battery banks, dc power systems, capacitor banks, and solar power systems. Although many of these systems are fed by 50/60-Hz energy, we find substantial use of electrical energy, and the use of capacitors, inductors, batteries, solar, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz ac power. At the IEEE Electrical Safety Workshop in 2009, we presented a comprehensive approach to classifying the electrical shock hazards of all types of electricity, including various waveforms and various types of sources of electrical energy. That paper introduced a new comprehensive electrical shock hazard classification system that used a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards with a focus on the shock hazard. That paper was based on research conducted over the past 100 years and on decades of experience. This paper continues the effort in understanding and managing all forms of injury from all forms of electricity with the introduction of a comprehensive approach to classifying all forms of injury from the electrical arc, including thermal, blast pressure, hearing, radiation, and shrapnel injury. The general term “arc” is divided into the arc, arc flash, and arc blast as a first subdivision of type of source of injury. Then, the parameters of voltage, short-circuit current, energy, waveform, gap distance, gap geometry, enclosure geometry, and time are used to choose various approaches to analysis. Recent efforts to understand, model, and estimate injury for these types of systems are reviewed. Most of the focus to understand and predict injury for dc, capacitor, solar, and RF arc hazards has been only in the past 10 years. A comprehensive approach to analyzing all forms of injury from all forms of electrical arcs is presented. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is a serious neurodegenerative condition that affects millions of individuals across the world. As the average age of individuals in the United States and the world increases, the prevalence of AD will continue to grow. To address this public health problem, the research community has developed computational approaches to sift through various aspects of clinical data and uncover their insights, among which one of the most challenging problem is to determine the biological mechanisms that cause AD to develop. To study this problem, in this paper we present a novel Joint Multi-Modal Longitudinal Regression and Classification method and show how it can be used to identify the cognitive status of the participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort and the underlying biological mechanisms. By intelligently combining clinical data of various modalities (i.e., genetic information and brain scans) using a variety of regularizations that can identify AD-relevant biomarkers, we perform the regression and classification tasks simultaneously. Because the proposed objective is a non-smooth optimization problem that is difficult to solve in general, we derive an efficient iterative algorithm and rigorously prove its convergence. To validate our new method in predicting the cognitive scores of patients and their clinical diagnosis, we conduct comprehensive experiments on the ADNI cohort. Our promising results demonstrate the benefits and flexibility of the proposed method. We anticipate that our new method is of interest to clinical communities beyond AD research and have open-sourced the code of our method online. 1 The code package for the proposed Joint Multi-Modal Longitudinal Regression and Classification model have been made publicly available online at https://github.com/minds-mines/jmmlrc. [ABSTRACT FROM AUTHOR]

Natural disasters affect structural health of buildings, thus directly impacting public safety. Continuous structural monitoring can be achieved by deploying an Internet of things network of distributed sensors in buildings to capture floor movement. These sensors can be used to compute the displacements of each floor, which can then be employed to assess building damage after a seismic event. The peak relative floor displacement is computed, which is directly related to damage level according to the United States federal agencies standards. With this information, the building inventory can be classified into immediate occupancy, life safety, or collapse prevention categories. In this paper, we propose a zero velocity update technique to minimize displacement estimation error. Theoretical derivation and experimental validation are presented. In addition, we investigate modeling sensor error and interstory drift ratio distribution. Moreover, we discuss the impact of sensor error on the achieved building classification accuracy. [ABSTRACT FROM AUTHOR]

Organizational leaders routinely note the critical importance of human capital in enabling successful innovation outcomes. However, strategic human resource management (SHRM) practices, especially in large firms, often are not aligned with practices that facilitate breakthrough innovation (BI), where uncertainty, ambiguity, and risk of failure are high. In this paper, drawing from the motivation–opportunity–ability (MOA) framework, we identify and delineate SHRM practices that are likely to affect BI outcomes in firms. These include career risk mitigation, extrinsic rewards (motivation), idea generation facilitation (opportunity), innovation talent development, and managerial ambidexterity development (ability). We theorize that while these SHRM practices may directly affect BI outcomes, these effects are likely to be modulated by the broader organizational context, specifically, the degree of organizational conservatism. We test our hypotheses using survey data collected from 79 U.S.-based multinational firms and find that first, the impacts of career risk, extrinsic rewards, and innovation talent development on BI outcomes vary with the firm's degree of conservatism. Second, developing ambidextrous talent among middle managers positively influences BI outcomes, irrespective of the firm's level of conservatism. Overall, our study provides a basic framework to understand how SHRM practices can be leveraged to influence innovation under varying degrees of conservatism in organizations. [ABSTRACT FROM AUTHOR]

In this paper, we propose bag of adversarial features (BAFs) for identifying mild traumatic brain injury (MTBI) patients from their diffusion magnetic resonance images (MRIs) (obtained within one month of injury) by incorporating unsupervised feature learning techniques. MTBI is a growing public health problem with an estimated incidence of over 1.7 million people annually in USA. Diagnosis is based on clinical history and symptoms, and accurate, concrete measures of injury are lacking. Unlike most of the previous works, which use hand-crafted features extracted from different parts of brain for MTBI classification, we employ feature learning algorithms to learn more discriminative representation for this task. A major challenge in this field thus far is the relatively small number of subjects available for training. This makes it difficult to use an end-to-end convolutional neural network to directly classify a subject from MRIs. To overcome this challenge, we first apply an adversarial auto-encoder (with convolutional structure) to learn patch-level features, from overlapping image patches extracted from different brain regions. We then aggregate these features through a bag-of-words approach. We perform an extensive experimental study on a dataset of 227 subjects (including 109 MTBI patients, and 118 age and sex-matched healthy controls) and compare the bag-of-deep-features with several previous approaches. Our experimental results show that the BAF significantly outperforms earlier works relying on the mean values of MR metrics in selected brain regions. [ABSTRACT FROM AUTHOR]

This paper explores the history of, and addresses certain perceived procedural misunderstandings in, Hush-A-Phone v. United States (D.C. Cir. 1956) and its progeny In re Carterfone (F.C.C. 1968) to illuminate what the Hush-A-Phone Corporation actually did in its dispute with AT&T prior to the breakup of AT&T's century-long telephone monopoly. [ABSTRACT FROM AUTHOR]

During the 1980s, many software developers and enthusiasts reacted to software's unclear status within the U.S. copyright law by pursuing technical, rather than legislative fixes. This paper applies forensic methods to recover records of conflict between commercial software developers and the enthusiasts who sought to "crack" commercial programs' copy protection. [ABSTRACT FROM AUTHOR]

Hybrid energy storage system (HESS) based on Li-ion and supercapacitor (SC) can play a potential role to stabilize the grid by providing the fast frequency ancillary services. The SC helps to reduce the battery charge/discharge stress and, hence, assists to extend the battery lifespan. The power sharing method (PSM) is the heart in control part to improve the HESS performance and reduce the battery stress. This paper proposes a hybrid PSM and investigates its impact on battery life extension along with its relation to the system design and regulation signal. The performance of hybrid PSM is compared with three other PSMs (low-pass filter, first and second rule based) in a 10 MW/10 MWh full-active parallel HESS for frequency regulation service in two networks: U.K. (national grid) and USA (PJM). Considering maximum possible battery lifetime upto 25 years, result shows that the hybrid PSM approach allows a degree of the better performance for both grid while the sharing of SC is kept maximum 2.0% and 2.5% (for U.S. and U.K. grid, respectively) of the HESS capacity. This study also analyses the impact of PSM on shared capacity and design of HESS for different grid regulation signals. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most common neurological disorders affecting a significant portion of the world’s population and approximately 2.5 million people in the United States. Important biomedical research effort is focused on the development of energy efficient devices for the real-time detection of seizures. In this paper, we propose an Internet of Medical Things (IoMT)-based automated seizure detection system which will detect a seizure from electroencephalography (EEG) signals using a voltage level detector (VLD) and a signal rejection algorithm (SRA). The proposed system analyzes neural signals continuously and extracts the hyper-synchronous pulses for the detection of seizure onset. Within a time frame, if the number of pulses exceeds a predefined threshold value, a seizure is declared. The SRA reduces false detections, which in turn enhances the accuracy of the seizure detector. The design was validated using system-level simulations and consumer electronics proof of concept. The proposed seizure detector reports a sensitivity of 96.9% and specificity of 97.5%. The use of minimal circuitry can lead to reduction of power consumption compared to many contemporary approaches. The proposed approach can be generalized to other sensor modalities and the use of wearable or implantable solutions, or a combination of the two. [ABSTRACT FROM AUTHOR]

Epilepsy, which is characterized by recurrent spontaneous seizures, has a considerably negative impact on both the quality and the expectancy of life of the patient. Approximately 3.4 million individuals in the USA and up to 1% of the world population is afflicted by epilepsy. This necessitates the real-time detection of seizures which can be done by the use of an Internet of Things (IoT) framework for smart healthcare. In this paper, we propose an electroencephalogram (EEG)-based seizure detection system in the IoT framework which uses the discrete wavelet transform (DWT), Hjorth parameters (HPs), statistical features, and a machine learning classifier. Seizure detection is done in two stages. In the first stage, EEG signals are decomposed by the DWT into sub-bands and features (activity, signal complexity, and standard deviation) were extracted from each of these sub-bands. In the second stage, a deep neural network (DNN) classifier is used to classify the EEG data. A prototype of the proposed neuro-detect was implemented using the hardware-in-the-loop approach. The results demonstrate a significant difference in HP values between interictal and ictal EEG with ictal EEG being less complex than interictal EEG. In this approach, we report an accuracy of 100% for a classification of normal versus ictal EEG and 98.6% for normal and interictal versus ictal EEG. [ABSTRACT FROM AUTHOR]

Presents abstracts of papers presented to the Association for Computing Machinery Conference at Rutgers University on March 28-29, 1950, in New Brunswick, New Jersey. 'Maddida'--General Theory,' by Floyd G. Steele; 'Maddida--Design Features,' by Donald E. Eckdahl.

This issue of the IEEE Transactions on Nuclear Science (TNS) is devoted to the 21st IEEE-NPSS Real Time Conference (RT2018) on Computing Applications in Nuclear and Plasma Sciences held in Williamsburg, VA, USA, in June 2018. A total of 98 papers presented at the conference have been submitted for possible publication in TNS. The conference accepted 54 papers as oral and 149 as poster presentations in 13 tracks. [ABSTRACT FROM AUTHOR]

This paper deals with the challenges of railgun electromagnetic compatibility. After some general remarks on integration issues, the current regulations, norms, and standards of a high-power railgun are discussed. Different standards for ordnance or staff are considered. Also, preliminary results from the French-German Research Institute of Saint-Louis are presented. Since these laboratory data are not yet representative for future weapon systems, scaling calculations were carried out concerning energy levels, electrical sources, and cabling architecture. The obtained signal profiles are compared to the values defined by U.S., EU, or NATO standards. [ABSTRACT FROM AUTHOR]

The accurate estimation of the terrestrial latent heat flux (LE) from satellite observations at high spatial and temporal scales plays an important role in the assessment of the water and heat exchange between the earth’s surface and the atmosphere. Although a variety of data fusion methods have been proposed to merge different LE products for more reliable estimates, most of them have ignored the spatiotemporal consistency of LE products across different resolutions. In this paper, we apply the multiresolution tree (MRT) method to improve the accuracy and reduce the inconsistency between the Moderate Resolution Imaging Spectroradiometer (MODIS) LE (MOD16) product and the Landsat-based LE product at different resolutions. Eddy covariance (EC) ground measurements at five sites, MODIS and Landsat images from January 2005 to December 2005 in the north central USA, are used to evaluate the performance of the MRT method. The results show that the MRT method can improve the accuracy of the original LE products (MOD16 and Landsat), and it has the potential to significantly reduce the uncertainty and inconsistency of these products. The bias decreased by 38.3% on average, and the root-mean-square error (RMSE) decreased by approximately 49.2% after the MRT was applied at each scale. Further studies are still required to make the MRT method more universal on a variety of land cover types for long-time periods. [ABSTRACT FROM AUTHOR]

Energetic electrons can be trapped in Earth’s magnetic field, forming the radiation belts (also known as the Van Allen Belts). These electrons, which can originate from the solar wind or a high-altitude nuclear explosion (HANE), have the potential to damage satellites in low-Earth orbit (LEO). For example, in 1962, the U.S. detonated a nuclear device at an altitude of about 400 km in the Starfish experiment. The resulting enhancement of the radiation belts disabled several satellites within a few months and energetic electrons remained in the radiation belts for up to several years. In order to address this potential vulnerability, schemes have been proposed to drain electrons from the radiation belts, with the most promising approaches based on using high-power very-low-frequency (VLF) waves to scatter the electrons into more field-aligned trajectories, forcing them to precipitate into Earth’s atmosphere. This paper will provide an overview of enhanced electron distributions in the radiation belts as well as approaches to VLF wave belt remediation including the use of either antennas or relativistic electrons beams in space to generate the VLF waves. [ABSTRACT FROM AUTHOR]

Heat conduction load test is a main and tough issue in the complex and huge general atom (GA) feeder system cold test. The GA feeder system is a superconducting system connects from the room temperature power supply system to the 4.5-K busbar of the magnet, supply 52 kA current and cryogenic provisions to the central solenoid magnet (CSM) coil, used for International Thermonuclear Experimental Reactor CSM magnet test at General Atomics Company, San Diego, CA, USA. This system have been developed and constructed at the Institute of Plasma Physics, Chinese Academy of Sciences, and completed the full cold test before transferred to the USA. In all the cold test items, the requirement of overall heat load 68 W is a big challenge, for its many leakage heat sources and cooling circuits: high temperature superconducting current lead, vacuum barrier, busbars, pipes, supports, etc. In order to get the steady results, many efforts were took to achieve the required value, such as reduce the inlet pressure of the 5-K loop as much as possible, minimize the flow rate of different 5-K cooling circuits, and at the same time, a dedicated program was developed to online calculate the density and the heat load while monitoring and analyzing the heat load. This paper will give a detail description of the 5-K overall heat load measurement. [ABSTRACT FROM AUTHOR]

Higher fuel economy standards and more stringent limitations on greenhouse gas emissions for ground vehicles have been made due to public concerns about energy crisis and environmental issues. By organizing a group of automated vehicles into a platoon at a short intervehicular distance, the overall fuel consumption and greenhouse gas emissions of vehicle platoon can be decreased due to reduced aerodynamic drag, which is called the platooning technology. In addition, the eco-driving technology can help further increase the fuel efficiency of vehicle platoon by optimizing speed trajectories of vehicles. However, little research has been done into the combination of the eco-driving and platooning technologies. Based on distributed model predictive control (DMPC), this paper proposes an ecological cooperative look-ahead control strategy for a platoon of automated vehicles travelling on a freeway with varying slopes, where both the eco-driving and platooning technologies are used. To maximize the fuel efficiency of vehicle platoon, an ecological cooperative look-ahead control problem (Eco-CLC) is first formulated based on DMPC, where rotational inertia coefficient related to reduction ratio of gear box, aerodynamic drag related to spacing and model constraints are considered. Since the Eco-CLC problem is a nonconvex and nonlinear optimization problem with hard state constraints, it is very difficult to quickly obtain its optimal solution. To enhance real-time control performance, after the hard state constraints of the Eco-CLC problem are transformed into parts of the multi-objective function using the band-stop function, the improved ecological cooperative look-ahead control (iEco-CLC) based on DMPC is given. A particle swarm optimization algorithm with multiple dynamic populations is further presented to quickly solve the iEco-CLC problem online. Simulation results demonstrate, compared with benchmarks, the proposed strategy can save more than 21% of fuel for vehicle platoon. [ABSTRACT FROM AUTHOR]

Nineteenth and early twentieth century American governments—local, state, and national—profoundly shaped diffusion of novel mathematical instruments. The federal government ran an office that judged what inventions were patentable and a legal system for those who defended or challenged patent rights. Governments at all levels employed inventors. Sometimes new laws required extensive calculations promoting invention and sale of computing instruments. Governments were customers for mathematical instruments ranging from teaching apparatus to adding and calculating machines to harmonic analyzers to tabulating machines. They not only bought goods, but set standards for what they would purchase. Government buyers also offered testimonials to businesses. From the 1890s, ant.itrust legislation led to some federal government oversight of corporations. Historians usually rely on documents to tell this story. This paper begins from objects—a few known only from patent descriptions, but most surviving in museum collections. This perspective complements rich existing accounts. [ABSTRACT FROM AUTHOR]

The American automobile industry is facing substantial environmental and energy challenges driving the pursuit of alternative powertrain technologies—“The intervening mechanism by which power is transmitted from an engine to a propeller or axle that it drives,” which nominally includes engine, transmission, drive shafts, differentials, and the final drive. Emerging alternative fuel vehicles are showing their potential to address these challenges. However, diffusion of new technologies has many complications. This paper uses system dynamics modeling to investigate the impacts of individual and organizational parameters. This model embeds two traditional modeling methods for technology adoption, the Bass diffusion model and multinomial logit regression method. Five types of powertrain systems and three major stakeholders are considered. Mathematical relationships among different variables are elaborated. The qualitative impacts of government feebate, manufacturer willingness, and consumer purchasing preferences on economic and environmental issues are addressed using scenario analysis. [ABSTRACT FROM AUTHOR]

For the past decade, the discussion of occupational electrical safety in the U.S. has largely focused on compliance with NFPA70E, Standard for Electrical Safety in the Workplace. Without taking away from the importance of the requirements in the standard, this paper describes a more comprehensive solution, based on proven concepts derived from systems safety engineering. This paper provides an overview of systems safety engineering and includes a 20 $+$ year case history of a global Fortune 500 company's effort to change the electrical safety culture in its operations to demonstrate results of applying systems safety techniques to electrical safety. [ABSTRACT FROM PUBLISHER]

Microinverter-based photovoltaic (PV) systems now represent about 8% of the U.S. residential market, and offer many advantages including safety, performance, and simplified installation. The next-generation of PV microinverter will include more ancillary functions to support grid stability and reliability in more distributed generation smart-grid systems. A commercial ready PV microinverter not only focuses on efficiency and cost, but also on reliability, manufacturability, compliance of various grid-code, and electromagnetic interference regulations. This paper presents a detailed design and development process of a microinverter system from concept all the way to final commercial-ready prototype. Various design tradeoffs such as topology, control, filter solutions and power supplies, and mechanical packaging are provided. The required prototype testing and final system field tests are also presented. The presented design and test process intends to accelerate the future microinverter system design and development toward a commercial ready product. [ABSTRACT FROM PUBLISHER]

Today's power utilities, around the world, own multiple substations that are connected together to form a complex energy network. The functions within and between these substations are being automated according to globally accepted power utility automation standard IEC 61850. This automation results in efficient operation and enhanced protection of power network with the aid of the communication system. Implementing the protection schemes modeled using communication configurations of standardized information exchange will lead to digital power grid. Designing an IEC-61850-based protection scheme to take care of the faults outside the substations is a challenge, as the typical local-area-network-based generic-object-oriented substation events and sampled-value messages need to be transmitted over a wide-area network. This paper presents communication configuration for line current differential protection schemes applied between two automated substations. It presents the simulation results of communication configuration network between two substations. Its performance is evaluated using a network simulator tool. This study intends to guide the development of a robust protection scheme with IEC-61850-based communication configuration. [ABSTRACT FROM PUBLISHER]

In many radio-frequency identification (RFID) applications, one of the essential systematic functionalities is to quickly detect missing-tag event in case of misplacement or other incorrect operations. In this paper, we focus on probabilistically detecting the missing tags for the anonymous multicategory RFID systems without revealing the tag privacy. The main objective is to minimize the detection time while satisfying the required detection reliability of each category. First, we propose to use a multihash technique to sequentially detect the missing tags category-by-category, called segmented sequential detection approach, in which the frame segmentation is adopted to reduce the detection time. Then, we propose an enhanced segmented sequential detection approach to further improve the detection efficiency by deactivating the identified existing tags. We conduct extensive simulations to illustrate the effectiveness of our proposed two missing tag detection approaches. [ABSTRACT FROM AUTHOR]

In the context of the hierarchy of risk controls, warnings, administrative controls, and personal protective equipment are sometimes referred to as lower order controls. In practice, the effectiveness of these controls can be overestimated due to a misunderstanding of the human factors that affect error likelihood in their implementation. This paper explores one human factor: the limitation of attention on residual risk inherent in lower order controls. The limitation of attention has implications for identifying hazards, assessing risk, taking appropriate actions based on warnings, executing safe work practices, and proper selection and use of personal protective equipment. Raising awareness and improved understanding of these topics can enable more effective risk assessment, quantification of residual risk, and more effective selection and combination of risk controls to achieve risk as low as reasonably practicable. [ABSTRACT FROM PUBLISHER]

Energy efficiency policies require the implementation of strategies to reduce energy use during the operation of integrated urban water systems. In Italy, the overall amount of electrical energy consumption for water systems is close to 2.3% of the total national consumption, thus efforts to minimize costs are crucial. This paper analyzes a case study of urban water systems in a specific area in the Piedmont Region, Italy; the case study includes the data collection methodology and the analysis of the energy consumption of seven large water providers. The discussion includes the quantification of the energy consumption reduction, achievable with the replacement of existing transformers with high-efficiency transformers, power factor correction, and the use of variable-frequency drives for the centrifugal pumps. [ABSTRACT FROM PUBLISHER]

Load participation is vital for the smart grid development. As an effective tool to improve reliability, stability, and financial efficiency of the power grids, demand response (DR) has brought significant financial and technical benefits to power systems. As one of the price-based DR programs with less control costs, the time-of-use (TOU) program has been applied as the default rate structure by many utility companies. To avoid financial risks and make the most profit from the market, utility companies treat TOU as an effective strategy to change customers’ electricity consumption patterns. As reported in many literature, existing TOU programs are not as effective as expected in many developed countries due to the complexity of human behaviors and disparities of residential customers. To examine whether to obtain different outcomes of TOU on the residential customers in developing countries, actual utility usage data from residential consumers in Shanghai, China, are analyzed in this paper. The result shows current TOU in Shanghai, China, has similar trends as TOU in developed countries. With high penetration level of renewable energy, an effective TOU program is urgently needed in the utility industry. In recent years, a creative TOU pricing structure has been introduced at the Electrical Reliability Council of Texas deregulated market, and it shows that the introduced “zero pricing” strategy has a significant impact on customers’ consumption patterns. The purpose of this research is to examine the key reasons that underlie ineffectiveness/effectiveness of TOU programs at residential level. [ABSTRACT FROM PUBLISHER]

In spite of the names of “building attachments” and “secondary elements” usually given to nonstructural components and equipment, they are far from being secondary in importance. In the worst case of critical facilities, the failure of equipment strongly impacts on the postearthquake functionality, causing the loss of essential services or businesses. Such considerations highlight the need for a seismic qualification of equipment as the essential means to demonstrate its adequacy to perform the required function during the expected earthquake event. In this paper, the authors deal with a new approach to the problem of seismic qualification, in which the seismic demand posed to the component is defined in terms of equipment seismic levels (ESLs), whereas its inherent seismic capacity is classified in terms of equipment qualification categories. The determination of the ESL, which is the subject of this paper, has to satisfy the requirements prescribed by the codes for the seismic design of equipment. A comparative study of the current seismic codes in the USA and in Europe is hence carried out in order to critically assess their provisions and to develop a methodology that can be implemented straightforwardly also by designers not having expertise in the field of earthquake engineering. [ABSTRACT FROM PUBLISHER]

This paper proposes the use of two indicators of the predictability of the load series along with an accuracy value such as mean average percentage error as standard measures of load forecasting performance. Over the last 10 years, there has been a significant increase in load forecasting models proposed in engineering journals. Most of these models provide a description of the inner design of the model, the results from applying this model to a specific data base and the conclusions drawn from this application. However, a single accuracy value may not be sufficient to describe the performance of the model when applied to other data bases. The aim of this paper is to provide researchers with a tool that is able to assess the predictability of a load series and, therefore, contextualize the forecasting accuracy reported. Nine different data bases from the U.S. have been used; all of them include hourly load and temperature data. [ABSTRACT FROM PUBLISHER]

A significant amount of green power is being installed at the distribution level through the installation of green power generation facilities in the U.S. and Canada. This paper discusses green-power-generating sources (of 10 MW or less), which are connected to the utility system at the distribution level, and their impact on the distribution system. This paper also discusses the impact of smart grid and whether this new technology can solve some of the issues raised in this paper. Distribution circuits are designed to supply radial loads. Therefore, the introduction of green generation could mean redistribution of fault and load currents on the feeder circuit, overvoltage, and ferroresonance, plus a possible loss of protection system coordination—all of which can result in customer outages. This paper discusses these issues which are generally not well understood by many distribution protection engineers and can adversely affect distribution system reliability. [ABSTRACT FROM PUBLISHER]

Precipitation classification is a critical module in the retrieval algorithm set, for the dual-frequency precipitation radar (DPR) that will be onboard the global precipitation measurement (GPM) core satellite. Precipitation type classification namely stratiform, convective, and other rain type classification is an important part of the classification module. Characteristics of measured dual-frequency ratio ( DFRm), defined as the difference between measured reflectivity at two frequency channels (Ku- and Ka- band), were studied for different rain types. This paper shows that DFRm can be used to separate stratiform and convective rain. In this paper, a precipitation type classification model is developed for DPR profile classification using characteristics of DFRm. Data collected by the airborne PR (ARP-2) in NASA African Monsoon Multidisciplinary Analysis, Genesis and Rapid Intensification Processes, and Wakasa Bay campaigns are employed in model validation. The performance of the precipitation classification method for the GPM-DPR resolution is evaluated and is shown to be applicable to the GPM resolution. [ABSTRACT FROM PUBLISHER]

In this paper, a multiinput dc–dc converter is proposed and studied for hybrid electric vehicles. Compared to conventional works, the output gain is enhanced. Fuel cell (FC), photovoltaic panel, and energy storage system are the input sources for the proposed converter. The FC is considered as the main power supply, and roof-top PV is employed to charge the battery, increase the efficiency, and reduce fuel economy. The converter has the capability of providing the demanded power by load in absence of one or two resources. Moreover, the power management strategy is described and applied in a control method. A prototype of the converter is also implemented and tested to verify the analysis. [ABSTRACT FROM AUTHOR]

This paper examines the cultural climate faced by women in the American computer industry from the 1960s to the early 1980s, a period in which the percentage of the industry workforce that was female almost tripled. Drawing on a comprehensive study of articles and advertisements in the trade journal Datamation, sources from IBM, Control Data, and the Burroughs Corporation, and the records of the user group SHARE, Inc, the study argues that the cultural climate of the industry shifted radically in the early 1970s, from hostility in the 1960s to a more open one in the late 1970s and early 1980s. [ABSTRACT FROM PUBLISHER]

This paper discusses historical and technical events in the U.S. and Europe over the last few years that are aimed at modernizing the electric power grid. The U.S. federal government has ratified the “smart grid initiative” as the official policy for modernizing the electricity grid including unprecedented provisions for timely information and control options to consumers and deployment of “smart” technologies. European countries are unified in researching and developing related technologies through various structures supported by the European Union. This paper presents the development of smart grids and an analysis of the methodologies, milestones, and expected evolutions of grid technologies that will transform society in the near future. [ABSTRACT FROM AUTHOR]

Probabilistic flood mapping offers flood managers, decision makers, insurance agencies, and humanitarian relief organizations a useful characterization of uncertainty in flood mapping delineation. Probabilistic flood maps are also of high interest for data assimilation into numerical models. The direct assimilation of probabilistic flood maps into hydrodynamic models would be beneficial because it would eliminate the intermediate step of having to extract water levels first. This paper introduces a probabilistic flood mapping procedure based on synthetic aperture radar (SAR) data. Given a SAR image of backscatter values, we construct a total histogram of backscatter values and decompose this histogram into probability distribution functions of backscatter values associated with flooded (open water) and non-flooded pixels, respectively. These distributions are then used to estimate, for each pixel, its probability of being flooded. The new approach improves on binary SAR-based flood mapping procedures, which do not inform on the uncertainty in the pixel state. The proposed approach is tested using four SAR images from two floodplains, i.e., the Severn River (U.K.) and the Red River (U.S.). In all four test cases, reliability diagrams, with error values ranging from 0.04 to 0.23, indicate a good agreement between the SAR-derived probabilistic flood map and an independently available validation map, which is obtained from aerial photography. [ABSTRACT FROM PUBLISHER]

Many of the sensors deployed at materials and test reactors cannot withstand the high flux/high temperature test conditions often requested by users at U.S. test reactors, such as the Advanced Test Reactor (ATR) at the Idaho National Laboratory. To address this issue, an instrumentation development effort was initiated as part of the ATR National Scientific User Facility in 2007 to support the development and deployment of enhanced in-pile sensors. This paper provides an update on this effort. Specifically, this paper identifies the types of sensors currently available to support in-pile irradiations and those sensors currently available to ATR users. Accomplishments from new sensor technology deployment efforts are highlighted by describing new temperature and thermal conductivity sensors now available to ATR users. Efforts to deploy enhanced in-pile sensors for detecting elongation and real-time flux detectors are also reported, and recently-initiated research to evaluate the viability of advanced technologies to provide enhanced accuracy for measuring key parameters during irradiation testing are noted. [ABSTRACT FROM AUTHOR]

The globalization of complex engineering services has resulted in physically dispersed teams that can no longer rely on the traditional and familiar oral transmission of engineering expertise nor can they assume knowledge of their team members’ culture. Yet, such teams need to be able coordinate effectively the dispersed knowledge of team members. We know little about how cultural differences among engineering team members impact the coordination of dispersed knowledge, so called transactive memory systems (TMSs)—or “who knows what” and “who knows who knows what.” In this paper, we present a longitudinal case study of a dispersed, cross-cultural team involving U.S. and Romanian engineers. The cultural differences in values, practices, and institutions had a major impact on TMS indicators of specialization, coordination, and credibility. The paper demonstrates how the cultural differences impeded TMS development. The results provide insight into TMS as an implicit coordination mechanism in a global team. We provide advice in terms of interventions that can promote the development of TMS in a culturally diverse team. [ABSTRACT FROM PUBLISHER]

This paper provides novel analysis methods and detailed simulations for determining the impact of out-of-band emissions (OOBE) of adjacent band wireless services on mobile receive-only wireless services. Using the interference from the adjacent cellular bands on an operational digital wireless receive-only system as an example, we demonstrate the impact of the interference from adjacent cellular band transmitters and determine the performance impact such as outage on satellite receivers in realistic roadway conditions. This paper presents new methods for determining appropriate OOBE spectral masks for use by new cellular subscriber transmitters. This paper considers realistic propagation and traffic conditions in five cities throughout the United States and offers approaches that the engineering community may use to determine interference conditions between new cellular and fixed broadband mobile services in adjacent spectrum bands to existing receive-only mobile receiver systems, such as satellite radio. [ABSTRACT FROM PUBLISHER]

This paper proposes using phasor measurement unit (PMU) data to trigger one-shot control in response to loss of synchronism detection. Decision trees (DTs) are trained to associate voltage magnitude and angle measurements with loss of synchronism. Different approaches to the DT construction process are illustrated in an early section of the paper by restricting the input vector to only two elements. Response-based control is obtained by triggering one-shot control the first time the DT classifies measurements as “Unstable”. The same combination of one-shot controls is applied to any event the first time the DT outputs “Unstable”. The method is demonstrated on a 176-bus reduced-order model of the western U.S. interconnection. An effective one-shot control consists of a combination of fast power changes on four buses. This control is similar to 500-MW fast power increases on two HVDC interties and it reduces angle differences in the AC network. [ABSTRACT FROM PUBLISHER]

This paper proposes a new framework in calculating the ex post prices for the spot electricity market. The proposed method finds a set of prices that are as consistent as possible with the actual outputs of resources correctly following their dispatch instructions. Two alternative consistency metrics are proposed in the paper. One measures the difference between the actual performance of an individual resource and its bid-based profit-maximizing response to the ex post prices in a perfectly competitive market. Another measures the difference between the ex post price and the price that supports the actual response of an individual resource. Compared to the existing approaches adopted in the real-time electricity markets in the U.S., the proposed method solves the ex post energy and ancillary service prices directly and simultaneously. It does not require heuristics that are hard to justify, and has a much clear definition for the pricing problem than the existing approaches do. Moreover, the proposed approach is flexible in the price control required by the market operators. Numerical examples are presented to further demonstrate the validity of this approach. [ABSTRACT FROM AUTHOR]

This paper presents a fully wireless cardiac pressure sensing system. Food and Drug Administration (FDA) approved medical stents are explored as radiating structures to support simultaneous transcutaneous wireless telemetry and powering. An application-specific integrated circuit (ASIC), designed and fabricated using the Texas Instruments 130-nm CMOS process, enables wireless telemetry, remote powering, voltage regulation, and processing of pressure measurements from a microelectromechanical systems (MEMS) capacitive sensor. This paper demonstrates fully wireless-pressure-sensing functionality with an external 35-dB⋅m RF powering source across a distance of 10 cm. Measurements in a regulated pressure chamber demonstrate the ability of the cardiac system to achieve pressure resolutions of 0.5 mmHg over a range of 0-50 mmHg using a channel data-rate of 42.2 kb/s. [ABSTRACT FROM AUTHOR]

In Part I of this paper, an operational fully automated Landsat-like image spectral rule-based decision-tree classifier (LSRC), suitable for mapping radiometrically calibrated sevenband Landsat-4/-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM+ (ETM+) spaceborne images [eventually synthesized from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and theModerate Resolution Imaging Spectroradiometer (MODIS) imaging sensor] into a discrete and finite set of spectral categories, has been downscaled to properly deal with spaceborne multispectral imaging sensors whose spectral resolution overlaps with, but is inferior to Landsat's, namely: 1) Satellite Pour l'Observation de la Terre (SPOT)-4/-5, Indian Remote Sensing Satellite (IRS)-1C/-1D/-P6 Linear Imaging Self-Scanner (LISS)-III, and IRS-P6 Advanced Wide Field Sensor (AWiFS); 2) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and Meteosat Second Generation (MSG); 3) Environmental Satellite (ENVISAT) Advanced Along-Track Scanning Radiometer (AATSR); 4) GeoEye-1, IKONOS-2, QuickBird-2, OrbView-3, TopSat, KOrean MultiPurpose SATellite (KOMPSAT)-2, FORMOsa SATellite (FORMOSAT)-2, Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), RapidEye, WorldView-2, PLEIADES-1/-2, and SPOT-6/-7; and 5) Disaster Monitoring Constellation (DMC), IRS-P6 LISS-IV, and SPOT-1/-2. LSRC, together with its five downscaled versions, identified, respectively, as the four-band SPOT-like SRC (SSRC), the four-band AVHRR-like SRC (AVSRC), the five-band AATSR-like SRC (AASRC), the four-band IKONOS-like SRC (ISRC), and the three-band DMClike SRC (DSRC), form the so-called integrated SRC system of systems. In this paper, first, the classification accuracy and robustness to changes in the input data set of SSRC, AVSRC, AASRC, ISRC, and DSRC are assessed, both qualitatively and quantitatively, in comparison with LSRC's. Next, ongoing and future SRC applications are presented and discussed. They encompass: 1) the implementation of operational two-stage stratified hierarchical Remote Sensing (RS) image understanding systems discussed in Part I of this paper; 2) the integration of near real-time satellite mapping services with Internet map servers; and 3) the development of a new approach to semantic querying of large-scale multisensor image databases. These experimental results and application examples prove that the integrated SRC system of systems is operational, namely, it is effective, near real-time, automatic, and robust to changes in the input data set. Therefore, SRC appears eligible for use in operational satellite-based measurement systems such as those envisaged by the ongoing international Global Earth Observation System of Systems (GEOSS) Programme and the Global Monitoring for Environment and Security (GMES) system project. [ABSTRACT FROM AUTHOR]

This paper describes a case study of the development and testing of a prototype system to support condition-based maintenance of the door systems of airport transportation vehicles. Every door open/close cycle produces a "signature" that can indicate the current degradation level of the door system. A combined statistical and neural network approach was used. Time, electrical current and voltage signals from the open/close cycles are processed in real-time to estimate, using the neural network, the condition of the door set relative to maintenance needs. Data collection hardware for the vehicle was designed, developed and tested to monitor door characteristics to quickly predict degraded performance, and to anticipate failures. The prototype system was installed on vehicle door sets at the Pittsburgh International Airport and tested for several months under actual operating conditions. Note to Practitioners-This paper describes the development of an automated system that consists of hardware and software to monitor the condition of a mechanical door set on board airport ground transportation vehicles. The aim is to use the current and past conditions to estimate (using neural network predictions) when the door set is in need of scheduled maintenance. This will allow airports to achieve very high availability rates (near 100%) for these vehicles, while also achieving cost effective maintenance policies. Currently, vehicles tend to be over-maintained because of the availability levels mandated by airport authorities. This system, although in prototype form, shows the viability of an automated condition-based maintenance approach. The drawback proved to be the variability among door sets from vehicle to vehicle, which means the predictive software of the system would need to be customized for each vehicle. Several patents, both U.S. and foreign; have been granted to this automated system. [ABSTRACT FROM AUTHOR]

This paper evaluates ERCOT's existing annual Black Start service selection analysis and subsequently presents novel selection procedures. ERCOT procures Black Start resources annually through a competitive process. It selects and awards contracts to qualifying resources after completing a Black Start unit selection analysis, which selects a group of Black Start resources that meet a set of system selection criteria consisting of system reliability and minimum cost parameters. A current analysis methodology exists, but due to its inherent limitations, it is very labor intensive. Further analysis methodology development is performed to streamline the selection process, enable additional functions, reduce the manual intervention of personnel, and overall to improve the selection analysis. This paper analyzes the current Black Start automatic program analysis, and proposes new methodologies, programming improvements, and enhanced user ability. [ABSTRACT FROM AUTHOR]

The increase of mobile applications requires antennas ever smaller in form factor. In this paper, an effective method is presented for antenna size miniaturization of ultrawideband (UWB) monopole antennas with symmetric structure and perfect magnetic conductor (PMC) plane. Two small antennas are designed for pulsed UWB applications in the 3.1-10.6-GHz band with and without notch behavior in the band. The presented technique is applied to both antennas for an even further 50% area reduction. The performance of the miniaturized antennas is then compared with the main-size structures. Using both simulations and measurements the paper analyzes and demonstrates in detail the effectiveness of the presented technique in the time and frequency domain. [ABSTRACT FROM AUTHOR]

This paper presents a sensitivity analysis of similar days (SD) parameters to increase the accuracy of artificial neural network (ANN) and SD-based short-term price forecasting. Work presented in this paper is an extended version of previous works done by the authors to integrate ANN and SD method for predicting electricity price. The focus here is on sensitivity analysis of SD parameters while keeping the parameters same for ANN to forecast hourly electricity prices in the Pennsylvania--New Jersey--Maryland (PJM) (regional transmission organization in northeast America) electricity market. Several cases are simulated by choosing (a) two, (b) three, (c) four, and (d) five SD parameters to calculate the norm. In addition, sensitivity analysis has been carried out by changing the time framework of SD (d = 15,30, 45, 60) and the number of selected similar price days (N = 5, 10). From sensitivity analysis, it is identified that the optimized mean absolute percentage error (MAPE) is obtained using case-c with d = 30 and N = 10. MAPE of reasonably small value, along with forecast mean square error and mean absolute error of around 2$/MWh and 1$/MWh, is obtained for the PJM data, which has correlation coefficient of determination (R²) of 0.7758 between load and electricity price. Numerical results show that forecasts generated by the developed ANN model based on the optimized case are accurate and efficient. [ABSTRACT FROM AUTHOR]