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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]

Focuses on the technical program presented at the 2001 Institute of Electrical and Electronics Engineers Microwave Theory and Techniques Society International Microwave Symposium in Phoenix, Arizona. Coverage of the technical program; Record on the number of paper submission; Citations on the topics in the symposium.

The article discusses about the special section on cross-layer design for mobile ad hoc networks and wireless sensor networks published within the May 01, 2006 issue in the U.S. The first section, which consist of seven papers, focuses on the capacity analysis/enhancement and quality-of-service support. The following papers, from eight to twelve, address the routing issues. In addition, four paper after the 12th explores the idea of cross-layer design.

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]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [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]

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]

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]

Editorial. Reports on developments in the Wireless Information Technology and Networks initiative announced by the National Science Foundation (NSF) for research in wireless communication systems in the U.S. in 1999. Number of proposals received by the NSF; Information on the Wireless Grantees Workshop at the National Academy of Science in Washington D.C.; Organization of papers in the May 2002 issue of the periodical 'IEEE Transactions on Antennas and Propagation.'

The article offers updates concerning the publication "IEEE Transactions on Systems, Man, and CyberneticsߞPart B: Cynbernetics" in the U.S. It is stated that the publication processed 1,093 papers and project over 1,300 research in 2008. The development resulted in a larger pool of high-quality research under consideration of the publication policy. The Technical Correspondences, special class of papers in the publication, are not simply short papers but still represent significant contributions on par with regular papers. The authors are encouraged to use the National Library of Medicine vocabulary in order to help better disseminate their work in the publication.

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]

Focuses on the computer vision research for undergraduates in the United States. Ability of students to prepare and present papers in conferences; Accomplishments of students in journal publications; Continuance of students on graduate studies at various institutions.

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]

The article reports on the International Conference on Software Engineering (ICSE) 2003 held in Portland, Oregon. The article discusses three papers that were selected for representing the best of ICSE 2003. The first paper "Scaling Step Wise Refinement," by D. Batory, J.N. Sarvela and A. Rauschmayer, is about development of computer software. The second paper is "Fragment Class Analysis for Testing of Polymorphism in Java Software" by A. Rountev, A. Milanova and B.C. Ryder, and the third paper is "Modular Verification of Software Components in C," by S. Chaki, F. Clarke, A. Groce, S. Jha and H. Veith. These two papers concern validation of software. The article also names some persons who devoted their time and energy in organizing ICSE 2003. The author suggests that managing the complexity of modern software systems is a grand challenge. Throughout the conference, there were exhibits, posters and informal research demonstrations as well as an onsite newsletter describing memorable moments, humor and fascinating facts.

Editorial. Comments on the Institute of Electrical and Electronics Engineers Topical Meeting on Electrical Performance of Electronic Packaging in Scottsdale, Arizona. Benefits of the meeting; Discussion of various topics on packaging; List of review authors.

Focuses on the agenda for the 1999 International Conference of Software Engineering in Los Angeles, California. Enhancement of the industrial presentation programs; List of participating research papers; Topics and writers for the research papers.

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]

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]

This Transactions’ Mini-Special Issue includes a selection of papers presented last year at the 2018 IEEE Radio Frequency Integrated Circuits (RFIC) Symposium held in the Pennsylvania Convention Center and Loews Philadelphia Hotel, Philadelphia, PA, USA, during June 10–12, 2018. The 2018 RFIC Symposium focused on the major themes of millimeter-wave 5G and autonomous vehicles in the plenary sessions. The first plenary talk was delivered by Zachary J. Lemnios, the Vice President of IBM Research, and discussed silicon-based mm-wave systems for 5G and beyond. The second plenary talk was presented by Lars Reger, CTO of NXP Semiconductors’ Automotive Business Unit, and focused on RF systems in the automotive industry, including the technical aspects related to future self-driving cars. [ABSTRACT FROM AUTHOR]

This special collection of papers had its genesis at the IEEE Computer Society Workshop on Software Testing and Test Documentation held in Fort Lauderdale, Florida during December 18-20, 1978. This collection is devoted to selected papers on program testing that were presented at the Workshop. The thrust is towards approaches that can support the heuristic components of testing. There is increasing recognition that it is unlikely there will be a grand theory of testing which will lead to fully automated testing systems. Instead the tester will be called upon to use his intuition and problem-dependent knowledge in a discipline manner to test for a variety of specified error types. But it is crucial that this less ambitious, heuristic activity be nevertheless firmly embedded in an underlying framework which is logical, rigorous and well-understood.

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]

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]

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]

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]

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]

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]

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]

Short-term load forecasting is always a popular topic in the electric power industry because of its essentiality in energy system planning and operation. In the deregulated power system, an improvement of a few percentages in the prediction accuracy would bring benefits worth of millions of dollars, which makes load forecasting become more important than ever before. This paper focuses on the short-term load forecasting for a power system in the U.S., where several alternative meteorological forecasts are available from different commercial weather services. To effectively take advantage of the alternative meteorological predictions in the load forecasting system, a new comprehensive forecasting methodology has been proposed in this paper. Specifically, combining forecasting using adaptive coefficients is applied to share the strength of the different temperature forecasts in the first stage, and then, ensemble neural networks have been used to improve the model's generalization performance based on bagging. The proposed load forecasting system has been verified by using the real data from the utility. A range of comparisons with different forecasting models have been conducted. The forecasting results demonstrate the superiority of the proposed methodology. [ABSTRACT FROM AUTHOR]

In a power system covering a large geographical area, a single model for load forecasting of the entire area sometimes cannot guarantee satisfactory forecasting accuracy. One of the major reasons is because of the load diversity, usually caused by weather diversity, throughout the area. Multiregion load forecasting will be a feasible and effective solution to generate more accurate forecasting results, as well as provide regional forecasts for the utilities. However, a major challenge is how to optimally partition/merge the areas according to the regional load and weather conditions. This paper investigates the electricity demand and weather data from an electric utility in Midwest, U.S. Based on the data analysis, we demonstrate the existence of weather and load diversity within its control area and then develop a short-term multiregion load forecasting system based on support vector regression for day-ahead operation and market. The proposed multiregion forecasting system can find the optimal region partition under diverse weather and load conditions and finally achieve more accurate forecasts for aggregated system load. The proposed forecasting system has been tested by using the real data from the system. The numerical results obtained for different region partition schemes validate the effectiveness of the proposed multiregion forecasting system. The detailed discussions on the forecasting results have also been given in this paper. [ABSTRACT FROM AUTHOR]

A very popular method utilized in quantifying the benefit of power delivery service reliability is to estimate the customer monetary losses associated with power supply interruptions by collecting data with customer surveys. MidAmerican Energy Company, a Midwest utility, recently performed surveys of its customers in the residential, commercial, industrial, and company/organization sectors. This paper presents the industrial and commercial customer results of these surveys with primary focus on the cost results. The results of this paper are compared with the results of other studies performed in high-cost areas of the United States' east and west coasts. This is the first ever paper of this nature performed for the electrical customers in the United States' Midwest region. Methodological differences in study design compared with coastal surveys are discussed. The major contribution of this paper is that particulars of Midwest customers compared with customers of coastal utilities are noted, the impact on customers with backup supply is identified, a suggested approach to enhance customer satisfaction due to advance warning on outages is recommended, and relatively high survey response return rates are elaborated. The customer damage functions derived from the survey results are being routinely used in power delivery project justifications in annual delivery system budgeting processes. [ABSTRACT FROM AUTHOR]

This paper updates an earlier report by the authors that studied electrical injuries from 1992 to 1998. The previous information is expanded and supplemented with fatal and nonfatal injury rates and trends through 2002. Injury numbers and rates were used to compare and trend electrical injury experience for various groups and categories. This information allowed identification of at-risk groups that could most benefit from effective electrical safety interventions. The data presented in this paper are derived from the U.S. Labor Department's Bureau of Labor Statistics' Census of Fatal Occupational Injuries, Survey of Occupational Illnesses and Injuries, and Current Population Survey. Between 1992 and 2002, 3378 workers died from on-the-job electrical injuries. Electricity remained the sixth leading cause of injury-related occupational death. From 1999 to 2002, 4.7% of all occupational deaths were caused by electricity, down from 5.2% in the 1992-1998 time period. The cause of death was listed as electrocution in 99.1% of fatal cases. Contact with overhead power lines was involved in 42% of all on-the-job electrical deaths. The construction industry accounted for 47% of all electrical deaths between 1992 and 2002 but showed overall improvement from 1995 to 2002 by reducing its electrical fatality rate from 2.2 to 1.5 per 100 000 workers. In addition, 46 598 workers were nonfatally injured by electricity. Contact with electric current of machine, tool, appliance, or light fixture and contact with wiring, transformers, or other electrical components accounted for 36% and 34% of nonfatal electrical injuries, respectively. Contact with underground buried power lines was involved with 1% of fatal injuries and 2% of nonfatal injuries. The research of the National Institute for Occupational Safety and Health aimed at evaluating commercially available overhead power line proximity warning alarms is described. This paper is expected to be the initial step for eventual development of a performance standard for such systems. [ABSTRACT FROM AUTHOR]

Combining data sets from multiple satellite sensors is a powerful method for studying Earth-atmosphere problems. By fusing data, we can utilize the strengths of the individual sensors that may not be otherwise possible. In this paper, we provide the framework for combining level 2 data products, using data from three sensors aboard the National Aeronautics and Space Administration (NASA)'s Terra satellite. These data include top-of-the-atmosphere (TOA) radiative energy fluxes obtained from the Clouds and the Earth's Radiant Energy System (CERES), aerosol optical thickness from the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS), and aerosol properties from the Multi-angle Imaging SpectroRadiometer (MISR). The CERES Single Scanner Footprint (SSF) contains the pixel level CERES TOA fluxes and the level 2 MODIS aerosol data. We specifically focus upon fusing the CERES SSF with the MISR aerosol products. Although this project was undertaken specifically to address aerosol research, the methods employed for fusing data products can be used for other problems requiring synergistic data sets. We present selected case studies over different aerosol regimes and indicate that multisensor information provides value-added information for aerosol research that is not available from a single sensor. [ABSTRACT FROM AUTHOR]

This paper describes several small printed circuit board planar antennas that can be integrated with amplifiers for short-range vehicle wireless communication. The antennas are designed for the 315-MHz frequency band, which is commonly used for control and security devices in the USA and Canada. Each antenna has dimensions of 50 × 70 mm (much less than the free-space wavelength λ = 0.95 m) and is implemented on FR-4 dielectric substrate. These investigated antennas were compared with respect to input impedance, radiation resistance, radiation efficiency, directivity, directionality, bandwidth, matching system complexity, and gain. This paper also includes experimental verification of the final antenna design in the vehicle. It is shown that the antenna diversity method can increase communication range for remote keyless entry systems. [ABSTRACT FROM AUTHOR]

An advanced high side voltage control (HSVC) that can improve power system stability by adding supplemental con- trol to conventional generator excitation systems has been developed. Since the introduction of this advanced HSVC at the IEEE PES 2000 Summer Meeting, additional development has further improved the advanced HSVC as reported in a companion paper. This paper describes field verification results for the HSVC that were carried out on a hydro power plant of the U.S. Army Corps of Engineers on the Columbia River at The Dalles. The advanced HSVC was temporarily added to the existing digital automatic voltage regulators (AVRs) of two generators in a 22-machine hydro power plant. Various tests, such as confirmation of droop, performance of the cross-current suppression function, switching on and off of a nearby capacitor bank, and others, were successfully carried out. It was confirmed through these field verification tests that the advanced HSVC displayed beneficial impacts on voltage control and system stability as compared to a conventional AVR. [ABSTRACT FROM AUTHOR]

There has been recent extensive research on integrating cellular networks and ad hoc networks to overcome the limitations of cellular networks. Although several schemes have been proposed to use such hybrid networks to improve the performance of individual multicast groups, they do not address quality of service (QoS) issues when multiple groups are present. This paper, on the other hand, considers an interesting scenario of hybrid networks when an ad hoc network cannot accommodate all the groups and a base station has to select a subset of groups to optimize its bandwidth savings and maximize the utilization of the ad hoc network while providing QoS support for multicast users. In this paper, a network model for multicast admission control that takes wireless interference into account is developed, the group selection problem is formulated as a multidimensional knapsack problem, and an integer linear programming (ILP) formulation and a polynomial-time dynamic algorithm are proposed. A distributed implementation of the dynamic algorithm in real systems is also examined. Simulation studies demonstrate that the dynamic algorithm is able to achieve very competitive performance under various conditions, in comparison with the optimal solution computed by the ILP approach. [ABSTRACT FROM AUTHOR]

Online advertising continues to be a significant source of income for many Internet-based organizations. Recent indications of improved economic growth are having an impact on advertisement revenue, with the estimated online advertising revenue in the United States for the fourth quarter of 2003 totaling a record of $2.2 billion. A substantial portion of this income comes from banner advertisements, and efficient scheduling of these advertisements could result in a considerable increase in profits. The problem of scheduling banner advertisements has been observed to be intractable via traditional optimization techniques and has received only limited attention in the literature. In addition, all past attempts to address this problem have been based on an ‘all-or-nothing’ framework, where a customer specifies the exact number of copies of the ad to be displayed over the planning horizon, if it is selected for display by the provider of the advertisement space. This paper extends it to a more realistic setting, where the customer is allowed to specify a set of acceptable display frequencies. The Lagrangian decomposition-based solution approaches presented in this paper are observed to provide good schedules in a reasonable period of time. [ABSTRACT FROM AUTHOR]

Focuses on the publishing of reviews for books in newspapers in the United States. Details on the awards given by the Institute of Electrical and Electronics Engineers Signal Processing Society to authors; Updates on the publications of the organization.

As the number of combined-cycle units increases, efficient modeling approaches for these units play important roles for independent system operators (ISOs). Based on various combinations of combustion turbines (CTs) and steam turbines (STs), the combined-cycle unit could work at different configurations (modes) with different efficiencies. In this paper, we propose an edge-based formulation for the combined-cycle units in the unit commitment problem to improve the accuracy and effectiveness of current modeling approaches. Our formulation can 1) clearly describe the transition processes among different configurations so as to satisfy the ISO financial offer submission requirements and (2) capture physical constraints of each turbine, including the exact min-up/down time and time dependent startup cost, in the combined-cycle units so as to increase the operational flexibility while ensuring system feasibility. This model fits well with the current U.S. deregulated electricity market. The final numerical studies show that our approaches perform better than the current configuration-based modeling approach. [ABSTRACT FROM AUTHOR]

Secondary or low-voltage (LV) networks are applied in many large cities throughout the U.S., and in some other countries. Various grounding schemes have been employed for the primary systems supplying these secondary networks. In this paper, characteristics of the different grounding schemes for the substation and primary feeders that supply the LV networks are reviewed. The impacts of primary system grounding on the ground fault currents, the unfaulted line-to-ground voltages, as well as the voltage sags in the LV network have been considered for the single line-to-ground fault on the primary. The differences between systems with network transformers having the delta- or grounded-wye-connected primary windings are discussed. The relationships between grounding characteristics and protection settings, including actual examples, have been documented. [ABSTRACT FROM AUTHOR]

The article provides various announcement related to the Institute of Electrical and Electronics Engineers (IEEE) Inc. Management Society, provides an overview on various issues published within the issue. Starting January 2008, the society will change its name into IEEE Technology Management Council. Names of the recipient for the 2006, volume 53 best paper award are presented. The issue of the journal presents various reports including one by D. Libaers on the role and contribution of foreign-born scientist in the U.S.

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]

In this paper, we analyze how carbon emissions affect the selection of transportation modes and social welfare by using a two-stage Stackelberg gaming model. Based on this model, the government’s optimal carbon-emission tax scheme and the company’s optimal transportation mode and production decisions are explored. We find that: 1) whether or not the transport carbon-emission tax can increase social welfare depends on the relationships among the social cost of carbon (SCC), the transportation mode shifting threshold (TMST), and the biggest carbon-emission tax that a company can afford (BCRA); 2) a greater SCC implies a higher probability of improving social welfare via imposing transportation carbon-emission tax; and 3) a smaller TMST or BCRA yields a higher probability of improving social welfare when a carbon-emission tax is imposed. Further study shows that imposing a carbon-emission tax on the product with a higher production cost, a bigger product volume, or a bigger product density can increase the probability of improving social welfare. [ABSTRACT FROM PUBLISHER]

Interconnection wide electric transmission system has been envisioned to facilitate the growth of renewable energy, enhance reliability, improve system operating efficiency, and reduce emissions. In this paper, we propose an explicit planning approach for transmission design at the national level. It has been applied to the U.S. system to design transmission overlays for multiple future generation scenarios. Associated simulation results suggest that a national transmission overlay provides economic, environmental, and system performance benefits. [ABSTRACT FROM PUBLISHER]

FERC Order 755 requires each RTO/ISO to use market-based mechanisms to select and compensate frequency regulation resources based on a two-part payment methodology, i.e., a capacity payment to keep the capacity in reserve and a performance payment to reflect the amount of work each resource performs in real-time in response to the system operator's dispatch signal. This paper discusses how MISO enhanced its market rules to implement a market-based regulation performance payment. The market enhancement includes four key areas: quantifying the movement of regulation, modifications to the market clearing processes, performance accuracy measurement, and performance-based two-part regulation compensation. [ABSTRACT FROM PUBLISHER]

The papers appearing in this special issue of the "IEEE Transactions on Software Engineering" periodical are based on papers that originally appeared in the proceedings of the First International Conference on Data Engineering which was held in Los Angeles, California, on April 25-27, 1984. The paper by Braegger, Dudler, Rebsamen and Zehnder was selected as the best paper at the conference by the awards committee, and concerns a database tool called Gambit. This design tool is based on an extended relational/entity relationship model and assists the designer with a wide variety of subtools. The paper by Farmer, King, and Myers is also about a design tool which is called the Semantic Database Constructor (Sedaco). It is based on a semantic data model which buffers the designer from most low level data structuring issues.

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]