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Freeway service patrol (FSPs) programs have been considered as an effective tool for traffic incident management in minimizing the adverse effects of traffic incidents. In this study, random parameters hazard-based duration modeling method was used to evaluate the impact of the newly implemented Alabama Service and Assistance Patrol (ASAP) program, using incident clearance time as a performance measure. It was determined that there is a statistically significant difference in the factors that influence incidents clearance times between incidents that occurred inside and outside the ASAP regions. A total of five variables (on-road, nighttime, peak hours, rain, and fire response present) were observed to have random effects along with ten fixed effects variables on incidents occurring inside the ASAP regions. On the other hand, incidents that occurred outside the ASAP regions were found to have three random effects variables (on-road, nighttime, and fire response present) and seven fixed effects variables. The estimation results indicate a significant association of incident clearance times to incident related variables such as involvement of CMVs, fatality, vehicle towing, seat belt indicated as involved, and on-road incidents that occurred both inside and outside the ASAP regions. The results also reveal that incident clearance times are influenced strongly by temporal variables (e.g., nighttime), traffic factors (e.g., AADT), and operational variables (e.g., fire response present) for incidents both inside and outside the ASAP area models. Overall, it was observed that the incident clearance times recorded in the regions where the ASAP program is in effect are significantly different. The findings of this study are expected to be useful for the state traffic incident management (TIM) agencies in developing and executing strategies to minimize incident clearance times. Ultimately, the study provides a data-driven evidence-based assessment of the ASAP program in the state.

Poor communication within healthcare teams occurs commonly, contributing to inefficiency, medical errors, conflict, and other adverse outcomes. Interprofessional bedside rounds (IBR) are a promising model that brings two or more health professions together with patients and families as part of a consistent, team-based routine to share information and collaboratively arrive at a daily plan of care. The purpose of this systematic scoping review was to investigate the breadth and quality of IBR literature to identify and describe gaps and opportunities for future research. We followed an adapted Arksey and O'Malley Framework and PRISMA scoping review guidelines. PubMed, CINAHL, PsycINFO, and Embase were systematically searched for key IBR words and concepts through June 2020. Seventy-nine articles met inclusion criteria and underwent data abstraction. Study quality was assessed using the Mixed Methods Assessment Tool. Publications in this field have increased since 2014, and the majority of studies reported positive impacts of IBR implementation across an array of team, patient, and care quality/delivery outcomes. Despite the preponderance of positive findings, great heterogeneity, and a reliance on quantitative non-randomized study designs remain in the extant research. A growing number of interventions to improve safety, quality, and care experiences in hospital settings focus on redesigning daily inpatient rounds. Limited information on IBR characteristics and implementation strategies coupled with widespread variation in terminology, study quality, and design create challenges in assessing the effectiveness of models of rounds and optimal implementation strategies. This scoping review highlights the need for additional studies of rounding models, implementation strategies, and outcomes that facilitate comparative research.

Objective To determine the efficacy of a program to limit the use of the intravenous (IV) push route for opioids on the experience of pain by inpatients and on associated safety events. Design Retrospective cohort study. Setting Two inpatient general medicine floor units at an urban tertiary care academic medical center. Subjects 4,752 inpatient opioid recipients. Methods Patients in one unit were exposed to a multidisciplinary intervention to limit the prescription of opioids via the IV push route, with the other unit used as a control unit. The primary study outcome was the mean numeric pain score per patient during the hospital stay. Secondary measures included the hospital length of stay and postdischarge patient satisfaction. Fidelity measures included the percentage of the patient population exposed to each opioid administration route and the amount of opioid administered per route. Safety measures included patient disposition, transfer to intensive care, and incidence of naloxone administration. Results The intervention was successful in decreasing both the percentage of patients exposed to IV push opioids and the amount of opioid administered via the IV push route, but no associated changes in other study outcomes were identified. Conclusions For the treatment of acute pain in medical inpatients, no evidence of benefit or harm was identified in relation to an increase or decrease in the use of the IV push opioid route.

The digitization of archival collections has become ubiquitous in the modern age. Contrary to the prevalence and popularity of these virtual collections, they are not without their limitations. Archivists have not sufficiently addressed the relationship between digital surrogates and their original objects. This article reviews a project undertaken by the authors who examined forty-two digitized archival collections from seven midwestern states. The study sought to determine whether digital surrogates include sufficient metadata to enable the viewer to understand that the virtual object is a representation of a physical object, that the physical object may be accessed, and that the physical object is part of a larger collection. The article concludes that the metadata fields used to describe digital surrogates vary across repositories, as well as within the institutions; and that very little metadata provides strong connections between the virtual images and the physical materials they represent. The authors conclude by providing recommendations for how archivists might improve the linkages between digital surrogates and their physical counterparts.

Background Teamwork and collaboration are essential to providing high-quality care. Prior research has found discrepancies between nurses’ and physicians’ perceptions in operating rooms, ICUs, and labor and delivery units. Less is known about health care professionals’ perceptions of teamwork and collaboration on general medical services. Methods This cross-sectional study included nurses, nurse assistants, and physicians working on general medical services in four mid-sized hospitals. Researchers assessed teamwork climate using the Safety Attitudes Questionnaire and asked respondents to rate the quality of collaboration experienced with their own and other professional categories. Results Data for 380 participants (80 hospitalists, 13 resident physicians, 193 nurses, and 94 nurse assistants) were analyzed. Hospitalists had the highest median teamwork climate score (83.3, interquartile range [IQR] = 72.3–91.1), and nurses had the lowest (78.6, IQR = 69.6–87.5), but the difference was not statistically significant (p = 0.42). Median teamwork climate scores were significantly different across the four sites (highest = 83.3, IQR = 75.0–91.1; lowest = 76.8, IQR = 66.7–88.4; p = 0.003). Ratings of the quality of collaboration differed significantly based on professional category. Specifically, 63.3% (50/79) of hospitalists rated the quality of collaboration with nurses as high or very high, while 48.7% (94/193) of nurses rated the quality of collaboration with hospitalists as high or very high. Conclusion This study found significant differences in perceptions of teamwork climate across sites and in collaboration across professional categories on general medical services. Given the importance in providing high-quality care, leaders should consider conducting similar assessments to characterize teamwork and collaboration on general medical services within their own hospitals.

BackgroundThe second Multicenter Medication Reconciliation Quality Improvement Study demonstrated a marked reduction in medication discrepancies per patient. The aim of the current analysis was to determine the association of patient exposure to each system-level intervention and receipt of each patient-level intervention on these results.MethodsThis study was conducted at 17 North American Hospitals, the study period was 18 months per site, and sites typically adopted interventions after 2–5 months of preintervention data collection. We conducted an on-treatment analysis (ie, an evaluation of outcomes based on patient exposure) of system-level interventions, both at the category level and at the individual component level, based on monthly surveys of implementation site leads at each site (response rate 65%). We then conducted a similar analysis of patient-level interventions, as determined by study pharmacist review of documented activities in the medical record. We analysed the association of each intervention on the adjusted number of medication discrepancies per patient in admission and discharge orders, based on a random sample of up to 22 patients per month per site, using mixed-effects Poisson regression with hospital site as a random effect. We then used a generalised linear mixed-effects model (GLMM) decision tree to determine which patient-level interventions explained the most variance in discrepancy rates.ResultsAmong 4947 patients, patient exposure to seven of the eight system-level component categories was associated with modest but significant reductions in discrepancy rates (adjusted rate ratios (ARR) 0.75–0.97), as were 15 of the 17 individual system-level intervention components, including hiring, reallocating and training personnel to take a best possible medication history (BPMH) and training personnel to perform discharge medication reconciliation and patient counselling. Receipt of five of seven patient-level interventions was independently associated with large reductions in discrepancy rates, including receipt of a BPMH in the emergency department (ED) by a trained clinician (ARR 0.40, 95% CI 0.37 to 0.43), admission medication reconciliation by a trained clinician (ARR 0.57, 95% CI 0.50 to 0.64) and discharge medication reconciliation by a trained clinician (ARR 0.64, 95% CI 0.57 to 0.73). In GLMM decision tree analyses, patients who received both a BPMH in the ED and discharge medication reconciliation by a trained clinician experienced the lowest discrepancy rates (0.08 per medication per patient).Conclusion and relevancePatient-level interventions most associated with reductions in discrepancies were receipt of a BPMH of admitted patients in the ED and admission and discharge medication reconciliation by a trained clinician. System-level interventions were associated with modest reduction in discrepancies for the average patient but are likely important to support patient-level interventions and may reach more patients. These findings can be used to help hospitals and health systems prioritise interventions to improve medication safety during care transitions.

The traditional approach to injury-severity analyses does not allow in-depth understanding of no-injury crashes, as crash factors found to contribute to the various injury severities may have similar effects on the severity of vehicle damage even if no injury is recorded. Viewing no-injury crashes using the vehicle damage severities as sub-categories and bases for potential injuries can improve understanding of future injury crashes. To better understand the mechanism of no-injury crashes and the crash factors that contribute to the extent of vehicle damage beyond the single categorization of these crashes in injury severity analysis, this study presents a vehicle damage severity analysis for no-injury crashes. To compare the effects of crash contributing factors on crash outcomes, two injury severity models were also estimated. Random parameters multinomial logit models with heterogeneity in means and variances were developed to account for unobserved heterogeneity. Model estimation results revealed that several common factors (e.g., unsafe speed, distracted driving, driving under influence, vehicle age, and run-off-road) are correlated with both injury severity in injury crashes and vehicle damage severity in no-injury crashes. Therefore, the sub-categorization of no-injury crashes by vehicle damage severity can potentially improve estimates of injury severity considered in resource allocation decisions for traffic safety.

Background Hospital-based studies have reported variable associations between outcome after spontaneous intracerebral hemorrhage and peri-hematomal edema volume. Aims In a community-based study, we aimed to investigate the existence, strength, direction, and independence of associations between intracerebral hemorrhage and peri-hematomal edema volumes on diagnostic brain CT and one-year functional outcome and long-term survival. Methods We identified all adults, resident in Lothian, diagnosed with first-ever, symptomatic spontaneous intracerebral hemorrhage between June 2010 and May 2013 in a community-based, prospective inception cohort study. We defined regions of interest manually and used a semi-automated approach to measure intracerebral hemorrhage volume, peri-hematomal edema volume, and the sum of these measurements (total lesion volume) on first diagnostic brain CT performed at ≤3 days after symptom onset. The primary outcome was death or dependence (scores 3–6 on the modified Rankin Scale) at one-year after intracerebral hemorrhage. Results Two hundred ninety-two (85%) of 342 patients (median age 77.5 y, IQR 68–83, 186 (54%) female, median time from onset to CT 6.5 h (IQR 2.9–21.7)) were dead or dependent one year after intracerebral hemorrhage. Peri-hematomal edema and intracerebral hemorrhage volumes were colinear ( R2 = 0.77). In models using both intracerebral hemorrhage and peri-hematomal edema, 10 mL increments in intracerebral hemorrhage (adjusted odds ratio (aOR) 1.72 (95% CI 1.08–2.87); p = 0.029) but not peri-hematomal edema volume (aOR 0.92 (0.63–1.45); p = 0.69) were independently associated with one-year death or dependence. 10 mL increments in total lesion volume were independently associated with one-year death or dependence (aOR 1.24 (1.11–1.42); p = 0.0004). Conclusion Total volume of intracerebral hemorrhage and peri-hematomal edema, and intracerebral hemorrhage volume alone on diagnostic brain CT, undertaken at three days or sooner, are independently associated with death or dependence one-year after intracerebral hemorrhage, but peri-hematomal edema volume is not. Data access statement Anonymized summary data may be requested from the corresponding author.

BACKGROUND Hospital medical groups use various staffing models that may systematically affect care continuity during the admission process. OBJECTIVE To compare the effect of 2 hospitalist admission service models (“general” and “admitter-rounder”) on patient disposition and length of stay. DESIGN Retrospective observational cohort study with difference-in-difference analysis. SETTING Large tertiary academic medical center in the United States. PARTICIPANTS Patients (n = 19,270) admitted from the emergency department to hospital medicine and medicine teaching services from July 2010 to June 2013. INTERVENTIONS Admissions to hospital medicine staffed by 2 different service models, compared to teaching service admissions. MEASUREMENTS Incidence of transfer to critical care within the first 24 hours of hospitalization, hospital and emergency department length of stay, and hospital readmission rates ≤30 days postdischarge. RESULTS The change of hospitalist services to an admitter-rounder model was associated with no significant change in transfer to critical care or hospital length of stay compared to the teaching service (difference-in-difference P = 0.32 and P = 0.87, respectively). The admitter-rounder model was associated with decreased readmissions compared to the teaching service on difference-in-difference analysis (odds ratio difference: −0.21, P = 0.01). Adoption of the hospitalist admitter-rounder model was associated with an increased emergency department length of stay compared to the teaching service (difference of +0.49 hours, P < 0.001). CONCLUSIONS Rates of transfer to intensive care and overall hospital length of stay between the hospitalist admission models did not differ significantly. The hospitalist admitter-rounder admission service structure was associated with extended emergency department length of stay and a decrease in readmissions. Journal of Hospital Medicine 2016. © 2016 Society of Hospital Medicine

Background and Purpose— The characteristics of intracerebral hemorrhage (ICH) may vary by ICH location because of differences in the distribution of underlying cerebral small vessel diseases. Therefore, we investigated the incidence, characteristics, and outcome of lobar and nonlobar ICH. Methods— In a population-based, prospective inception cohort study of ICH, we used multiple overlapping sources of case ascertainment and follow-up to identify and validate ICH diagnoses in 2010 to 2011 in an adult population of 695 335. Results— There were 128 participants with first-ever primary ICH. The overall incidence of lobar ICH was similar to nonlobar ICH (9.8 [95% confidence interval, 7.7–12.4] versus 8.6 [95% confidence interval, 6.7–11.1] per 100 000 adults/y). At baseline, adults with lobar ICH were more likely to have preceding dementia (21% versus 5%; P =0.01), lower Glasgow Coma Scale scores (median, 13 versus 14; P =0.03), larger ICHs (median, 38 versus 11 mL; P P P =0.02) than those with nonlobar ICH. One-year case fatality was lower after lobar ICH than after nonlobar ICH (adjusted odds ratio for death at 1 year: lobar versus nonlobar ICH 0.21; 95% confidence interval, 0.07–0.63; P =0.006, after adjustment for known predictors of outcome). There were 4 recurrent ICHs, which occurred exclusively in survivors of lobar ICH (annual risk of recurrent ICH after lobar ICH, 11.8%; 95% confidence interval, 4.6%–28.5% versus 0% after nonlobar ICH; log-rank P =0.04). Conclusions— The baseline characteristics and outcome of lobar ICH differ from other locations.

Modern network intrusion detection systems (NIDS) employ regular expressions as attack signatures. Internally, NIDS represent and operate these regular expressions as finite automata. However, finite automata present a well-known time/space tradeoff. Deterministic automata (DFAs) provide fast matching, but DFAs for large signature sets often consume gigabytes of memory because DFA combination results in a multiplicative increase in the number of states. Non-deterministic automata (NFAs) address this problem and are space-efficient, but are several orders of magnitude slower than DFAs. This time/space tradeoff has motivated much recent research, primarily with a focus on improving the space-efficiency of DFAs, often at the cost of reducing their performance. We consider an alternative approach that focuses instead on improving the time-efficiency of NFA-based signature matching. NFAs are inefficient because they maintain a frontier of multiple states at any instant during their operation, each of which must be processed for every input symbol. We introduce NFA-OBDDs, which use ordered binary decision diagrams (OBDDs) to efficiently process sets of NFA frontier states. Experiments using HTTP and FTP signature sets from Snort show that NFA-OBDDs can outperform traditional NFAs by up to three orders of magnitude, thereby making them competitive with a variant of DFAs, while still retaining the space-efficiency of NFAs.

Intrusion prevention systems (IPSs) determine whether incoming traffic matches a database of signatures, where each signature is a regular expression and represents an attack or a vulnerability. IPSs need to keep up with ever-increasing line speeds, which has lead to the use of custom hardware. A major bottleneck that IPSs face is that they scan incoming packets one byte at a time, which limits their throughput and latency. In this paper, we present a method to search for arbitrary regular expressions by scanning multiple bytes in parallel using speculation. We break the packet in several chunks, opportunistically scan them in parallel, and if the speculation is wrong, correct it later. We present algorithms that apply speculation in single-threaded software running on commodity processors as well as algorithms for parallel hardware. Experimental results show that speculation leads to improvements in latency and throughput in both cases.

This study tests the neoclassical concept of interregional migration in post-World War II Japan. The lead-lag relationship between net migration to a core area and regional income inequalities is examined by modeling an ARIMA transfer function. Until 1961 there was a rapid growth in net migration from the periphery to the core area that was accompanied by rapid divergence in regional income inequalities. Since then migration to the core apparently has declined due to a convergence of regional income inequalities. The time series analysis indicates there has been short-run as well as long-run volatility in migration related to cyclical variations in economic performance in the core. (EXCERPT)

Deep packet inspection is playing an increasingly important role in the design of novel network services. Regular expressions are the language of choice for writing signatures, but standard DFA or NFA representations are unsuitable for high-speed environments, requiring too much memory, too much time, or too much per-flow state. DFAs are fast and can be readily combined, but doing so often leads to state-space explosion. NFAs, while small, require large per-flow state and are slow. We propose a solution that simultaneously addresses all these problems. We start with a first-principles characterization of state-space explosion and give conditions that eliminate it when satisfied. We show how auxiliary variables can be used to transform automata so that they satisfy these conditions, which we codify in a formal model that augments DFAs with auxiliary variables and simple instructions for manipulating them. Building on this model, we present techniques, inspired by principles used in compiler optimization, that systematically reduce runtime and per-flow state. In our experiments, signature sets from Snort and Cisco Systems achieve state-space reductions of over four orders of magnitude, per-flow state reductions of up to a factor of six, and runtimes that approach DFAs.

Hospital medical groups use various staffing models that may systematically affect care continuity during the admission process.To compare the effect of 2 hospitalist admission service models ("general" and "admitter-rounder") on patient disposition and length of stay.Retrospective observational cohort study with difference-in-difference analysis.Large tertiary academic medical center in the United States.Patients (n = 19,270) admitted from the emergency department to hospital medicine and medicine teaching services from July 2010 to June 2013.Admissions to hospital medicine staffed by 2 different service models, compared to teaching service admissions.Incidence of transfer to critical care within the first 24 hours of hospitalization, hospital and emergency department length of stay, and hospital readmission rates ≤30 days postdischarge.The change of hospitalist services to an admitter-rounder model was associated with no significant change in transfer to critical care or hospital length of stay compared to the teaching service (difference-in-difference P = 0.32 and P = 0.87, respectively). The admitter-rounder model was associated with decreased readmissions compared to the teaching service on difference-in-difference analysis (odds ratio difference: -0.21, P = 0.01). Adoption of the hospitalist admitter-rounder model was associated with an increased emergency department length of stay compared to the teaching service (difference of +0.49 hours, P0.001).Rates of transfer to intensive care and overall hospital length of stay between the hospitalist admission models did not differ significantly. The hospitalist admitter-rounder admission service structure was associated with extended emergency department length of stay and a decrease in readmissions. Journal of Hospital Medicine 2016;11:669-674. © 2016 Society of Hospital Medicine.

We present a new distributed model for graph computations motivated by limited information sharing. Two or more independent entities have collected large social graphs. They wish to compute the result of running graph algorithms on the entire set of relationships. Because the information is sensitive or economically valuable, they do not wish to simply combine the information in a single location. We consider two models for computing the solution to graph algorithms in this setting: 1) limited-sharing: the two entities can share only a poly logarithmic size subgraph, 2) low-trust: the entities must not reveal any information beyond the query answer, assuming they are all honest but curious. We believe this model captures realistic constraints on cooperating autonomous data centres' have results for both models for s-t connectivity, one of the simplest graph problems that requires global information in the worst case. In the limited-sharing model, our results exploit social network structure. Standard communication complexity gives polynomial lower bounds on s-t connectivity for general graphs. However, if the graph for each data centre has a giant component and these giant components intersect, then we can overcome this lower bound, computing-t connectivity while exchanging O(log ^2 n) bits for a constant number of data centers. We can also test the assumption that the giant components overlap using O(log ^2 n) bits provided the (unknown) overlap is sufficiently large. The second result is in the low trust model. We give a secure multi-party computation (MPC) algorithm that 1) does not make cryptographic assumptions when there are 3 or more entities, and 2) is efficient, especially when compared to the usual garbled circuit approach. The entities learn only the yes/no answer. No party learns anything about the others' graph, not even node names. This algorithm does not require any special graph structure. This secure MPC result for s-t connectivity is one of the first that involves a few parties computing on large inputs, instead of many parties computing on a few local values.

The unexpected expansion of a 14-bed medical intensive care unit exposed the need for a structured preceptor/orientation program. Staff feedback and a review of quality indicators further substantiated this finding and revealed a decrease in standards of practice and problems in staff development. A restructured preceptor/orientation program yielded improvements in communication and staff satisfaction. Preceptors and orientees now have a better understanding of their roles and expectations, and quality of care is improving in an environment that promotes personal and professional growth.

Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document's content. For these kinds of data-rich, multiple-record documents (e.g., advertisements, movie reviews, weather reports, travel information, sports summaries, financial statements, obituaries, and many others) we can apply a conceptual-modeling approach to extract and structure data automatically. The approach is based on an ontology – a conceptual model instance – that describes the data of interest, including relationships, lexical appearance, and context keywords. By parsing the ontology, we can automatically produce a database scheme and recognizers for constants and keywords, and then invoke routines to recognize and extract data from unstructured documents and structure it according to the generated database scheme. Experiments show that it is possible to achieve good recall and precision ratios for documents that are rich in recognizable constants and narrow in ontological breadth. Our approach is less labor-intensive than other approaches that manually or semiautomatically generate wrappers, and it is generally insensitive to changes in Web-page format.

Nidificacion En Acantilados De Strix Occidentalis caurina En Oregon El buho Strix occidentalis lucida nidifica ocasionalmente en acantilados o en cuevas, mientras que la subespecie caurina nidifica casi exclusivamente en arboles. Describimos las caracteristicas fisicas y geologicas de cinco nidos en cuevas de S. occidentalis caurina. Los cinco nidos estuvieron en el oeste de Oregon y todos se encontraron en afloramientos de rocas de arenisca o en acantilados. Las caracteristicas fisiograficas de los sitios de los nidos en acantilados fueron similares a aquellas de los sitios de los nidos en arboles. La altura y dimensiones de los nidos de la subespecie caurina fueron similares a la de los nidos de las subespecies lucida y occidentalis. [Traduccion del equipo editorial]

The American system of federalism creates frequent opportunities for clashes between state and federal environmental regulators.State and federal environmental laws overlap but are not easily reconciled. Most federal environmental law provides no clear answer as to how to reconcile differing mandates of state and federal environmental regulators. In this article, they will examine these state-federal conflicts as they played out in 1994 in the cleanup of contaminated sites in the state of Washington. This article describes the way a regional office of the Environmental Protection Agency and the state`s Department of Ecology developed a novel approach to managing the essential tension between overlapping state and federal cleanup laws.

Public Service Company of Colorado (PSCo), in cooperation with the US Department of Energy (DOE) and the Electric Power Research Institute (EPRI), is testing the Integrated Dry NO{sub x}/SO{sub 2} Emissions Control system. This system combines low-NO{sub x} burners, overfire air, selective non-catalytic reduction (SNCR), and dry sorbent injection with humidification to reduce by up to 70% both NO{sub x} and SO{sub 2} emissions from a 100 MW coal-fired utility boiler. The project is being conducted at PSCo`s Arapahoe Unit 4 located in Denver, Colorado as part of the DOE`s Clean Coal Technology Round 3 program. The urea-based SNCR system, supplied by Noell, Inc., was installed in late 1991 and was tested with the unmodified boiler in 1992. At full load, it reduced NO{sub x} emissions by about 35% with an associated ammonia slip limit of 10 ppm. Babcock & Wilcox XLS{reg_sign} burners and a dual-zone overfire air system were retrofit to the top-fired boiler in mid-1992 and demonstrated a NO{sub x} reduction of nearly 70% across the load range. Integrated testing of the combustion modifications and the SNCR system were conducted in 1993 and showed that the SNCR system could reduce NO{sub x} emissions by an additional 45% whilemore » maintaining 10 ppm of ammonia slip limit at full load. Lower than expect4ed flue-gas temperatures caused low-load operation to be less effective than at high loads. NO{sub x} reduction decreased to as low as 11% at 60 MWe at an ammonia slip limit of 10 ppm. An ammonia conversion system was installed to improve performance at low loads. Other improvements to increase NO{sub x} removal at low-loads are planned. The combined system of combustion modifications and SNCR reduced NO{sub x} emissions by over 80% from the original full-load baseline. 11 figs.« less

This paper describes a research effort to use executable slicing as a pre-processing aid to improve the prediction performance of rogue software detection. The prediction technique used here is an information retrieval classifier known as cosine similarity that can be used to detect previously unknown, known or variances of known rogue software by applying the feature extraction technique of randomized projection. This paper provides direction in answering the question of is it possible to only use portions or subsets, known as slices, of an application to make a prediction on whether or not the software contents are rogue. This research extracts sections or slices from potentially rogue applications and uses these slices instead of the entire application to make a prediction. Results show promise when applying randomized projections to cosine similarity for the predictions, with as much as a 4% increase in prediction performance and a five-fold decrease in processing time when compared to using the entire application.

Network intrusion detection systems (NIDS) make extensive use of regular expressions as attack signatures. Internally, NIDS represent and operate these signatures using finite automata. Existing representations of finite automata present a well-known time-space tradeoff: Deterministic automata (DFAs) provide fast matching but are memory intensive, while non-deterministic automata (NFAs) are space-efficient but are several orders of magnitude slower than DFAs. This time/space tradeoff has motivated much recent research, primarily with a focus on improving the space-efficiency of DFAs, often at the cost of reducing their performance. This paper presents NFA-OBDDs, a symbolic representation of NFAs that retains their space-efficiency while improving their time-efficiency. Experiments using Snort HTTP and FTP signature sets show that an NFA-OBDD-based representation of regular expressions can outperform traditional NFAs by up to three orders of magnitude and is competitive with a variant of DFAs, while still remaining as compact as NFAs.

Quantitative trait locus (QTL) analysis is a statistical method to link phenotypes with regions of the genome that affect the phenotypes in a mapping population. R/qtl is a powerful statistical program commonly used for analyzing rodent QTL crosses, but R/qtl is a command line program that can be difficult for novice users to run. J/qtl was developed as an R/qtl graphical user interface that enables even novice users to utilize R/qtl for QTL analyses. In this chapter, we describe the process for analyzing rodent cross data with J/qtl, including data formatting, data quality control, main scan QTL analysis, pair scan QTL analysis, and multiple regression modeling; this information should enable new users to identify QTL affecting phenotypes of interest within their rodent cross datasets.

The concept of Free Space Optical (FSO) communications has been around since the late 1960's.This paper will describe some recent experimental results that demonstrate and validate hybrid FSO/RF communication links as viable components in a tactical high data rate network. In particular, we will describe air-mountain link closure up to ranges of 200 km under heavy atmospheric turbulence. These links were operated at low packet and bit error rates, with occasional link outages. Like the internet, we used retransmission to minimize the effect of these outages on link throughput. For example, when the FSO system is running, ORCA uses the RF system for retransmission to improve link efficiency. In addition, we will discuss potential losses created by the aircraft aero-optics effects. Finally, we will show comparison between model predictions and experimental data that suggest we can predict link performance if the atmospheric turbulence conditions are known.

Modern network devices employ deep packet inspection to enable sophisticated services such as intrusion detection, traffic shaping, and load balancing. At the heart of such services is a signature matching engine that must match packet payloads to multiple signatures at line rates. However, the recent transition to complex regular-expression based signatures coupled with ever-increasing network speeds has rapidly increased the performance requirements of signature matching. Solutions to meet these requirements range from hardwarecentric ASIC/FPGA implementations to software implementations using high-performance microprocessors. In this paper, we propose a programmable signature matching system prototyped on an Nvidia G80 GPU. We first present a detailed architectural and microarchitectural analysis, showing that signature matching is well suited for SIMD processing because of regular control flow and parallelism available at the packet level. Next, we examine two approaches for matching signatures: standard deterministic finite automata (DFAs) and extended finite automata (XFAs), which use far less memory than DFAs but require specialized auxiliary memory and small amounts of computation in most states. We implement a fully functional prototype on the SIMD-based G80 GPU. This system out-performs a Pentium4 by up to 9X and a Niagara-based 32-threaded system by up to 2.3X and shows that GPUs are a promising candidate for signature matching.

Protocol parsing is an essential step in several networkingrelated tasks. For instance, parsing network traffic is an essential step for Intrusion Prevention Systems (IPSs). The task of developing parsers for protocols is challenging because network protocols often have features that cannot be expressed in a context-free grammar. We address the problem of parsing protocols by using attribute grammars (AGs), which allow us to factor features that are not context-free and treat them as attributes. We investigate this approach in the context of protocol normalization, which is an essential task in IPSs. Normalizers generated using systematic techniques, such as ours, are more robust and resilient to attacks. Our experience is that such normalizers incur an acceptable level of overhead (approximately 15% in the worst case) and are straightforward to implement.

Intrusion prevention systems determine whether incoming traffic matches a database of signatures, where each signature in the database represents an attack or a vulnerability. IPSs need to keep up with ever-increasing line speeds, which leads to the use of custom hardware. A major bottleneck that IPSs face is that they scan incoming packets one byte at a time, which limits their throughput and latency. In this paper, we present a method for scanning multiple bytes in parallel using speculation. We break the packet in several chunks, opportunistically scan them in parallel and if the speculation is wrong, correct it later. We present algorithms that apply speculation in single-threaded software running on commodity processors as well as algorithms for parallel hardware. Experimental results show that speculation leads to improvements in latency and throughput in both cases.

Signature matching is a performance critical operation in intrusion prevention systems. Modern systems express signatures as regular expressions and use Deterministic Finite Automata (DFAs) to efficiently match them against the input. In principle, DFAs can be combined so that all signatures can be examined in a single pass over the input. In practice, however, combining DFAs corresponding to intrusion prevention signatures results in memory requirements that far exceed feasible sizes. We observe for such signatures that distinct input symbols often have identical behavior in the DFA. In these cases, an Alphabet Compression Table (ACT) can be used to map such groups of symbols to a single symbol to reduce the memory requirements.In this paper, we explore the use of multiple alphabet compression tables as a lightweight method for reducing the memory requirements of DFAs. We evaluate this method on signature sets used in Cisco IPS and Snort. Compared to uncompressed DFAs, multiple ACTs achieve memory savings between a factor of 4 and a factor of 70 at the cost of an increase in run time that is typically between 35% and 85%. Compared to another recent compression technique, D2FAs, ACTs are between 2 and 3.5 times faster in software, and in some cases use less than one tenth of the memory used by D2FAs. Overall, for all signature sets and compression methods evaluated, multiple ACTs offer the best memory versus run-time trade-offs.

Automata-based representations and related algorithms have been applied to address several problems in information security, and often the automata had to be augmented with additional information. For example, extended finite-state automata (EFSA) augment finite- state automata (FSA) with variables to track dependencies between arguments of system calls. In this paper, we introduce extended finite automata (XFAs) which augment FSAs with finite scratch memory and instructions to manipulate this memory. Our primary motivation for introducing XFAs is signature matching in Network Intrusion Detection Systems (NIDS). Representing NIDS signatures as deterministic finite-state automata (DFAs) results in very fast signature matching but for several classes of signatures DFAs can blowup in space. Using nondeterministic finite-state automata (NFA) to represent NIDS signatures results in a succinct representation but at the expense of higher time complexity for signature matching. In other words, DFAs are time-efficient but space-inefficient, and NFAs are space- efficient but time-inefficient. In our experiments we have noticed that for a large class of NIDS signatures XFAs have time complexity similar to DFAs and space complexity similar to NFAs. For our test set, XFAs use 10 times less memory than a DFA-based solution, yet achieve 20 times higher matching speeds.

Automata-based representations and related algorithms have been applied to address several problems in information security, and often the automata had to be augmented with additional information. For example, extended finite-state automata (EFSA) augment finite-state automata (FSA) with variables to track dependencies between arguments of system calls. In this paper, we introduce extended finite automata (XFAs) which augment FSAs with finite scratch memory and instructions to manipulate this memory. Our primary motivation for introducing XFAs is signature matching in Network Intrusion Detection Systems (NIDS). Representing NIDS signatures as deterministic finite-state automata (DFAs) results in very fast signature matching but for several types of signatures DFAs can blowup in space. Nondeterministic finite-state automata (NFA) representation of NIDS signatures results in a succinct representation but at the expense of higher time complexity for signature matching. In other words, DFAs are time-efficient but space-inefficient, and NFAs are space-efficient but time-inefficient. Our goal is to find a representation of signatures that is both time and space efficient. In our experiments we have noticed that for a large class of NIDS signatures XFAs have time complexity similar to DFAs and space complexity similar to NFAs. For our test set, XFAs use 10 times less memory than a DFA-based solution, yet achieve 20 times higher matching speeds.

Packet classification is central to modern network functionality, yet satisfactory memory usage and performance remains elusive at the highest speeds. The recent emergence of low-cost, highly parallel architectures provides a promising platform on which to realize increased classification performance. We analyze two classic algorithms (ABV and HiCuts) in multiple parallel contexts. Our results show that performance depends strongly on many factors, including algorithm choice, hardware platform, and parallelization scheme. We find that there is no clear "best solution," but in the best cases hardware constraints are mitigated by the parallelization scheme and vice versa, yielding near-linear speedups as the degree of parallelization increases.

Network Intrusion Detection Systems (NIDS) have become crucial to securing modern networks. To be effective, a NIDS must be able to counter evasion attempts and operate at or near wire-speed. Failure to do so allows malicious packets to slip through a NIDS undetected. In this paper, we explore NIDS evasion through algorithmic complexity attacks. We present a highly effective attack against the Snort NIDS, and we provide a practical algorithmic solution that successfully thwarts the attack. This attack exploits the behavior of rule matching, yielding inspection times that are up to 1.5 million times slower than that of benign packets. Our analysis shows that this attack is applicable to many rules in Snort?s ruleset, rendering vulnerable the thousands of networks protected by it. Our countermeasure confines the inspection time to within one order of magnitude of benign packets. Experimental results using a live system show that an attacker needs only 4.0 kbps of bandwidth to perpetually disable an unmodified NIDS, whereas all intrusions are detected when our countermeasure is used.

This paper describes a method for automatically inspecting the top edge region of a wafer for defects and how this method was used to evaluate process improvements. The need for such an inspection was driven by a within wafer defect problem first seen on product. The root cause of the defect was found to be the redistribution of certain defect types from the wafer edge exclusion region into the product area. Process partition and manual inspection using a scanning electron microscope (SEM) revealed the mechanism to be the formation and rupture of blisters during part of the process sequence. These blisters were found to be as small as 2μm, and appeared along the top edge of wafers. During processing, a high percentage of these blisters would rupture and redeposit debris on the topside of the wafer resulting in nearly 100 percent kill rate. While the root cause was understood, the use of SEM inspection to quantifiably evaluate process improvements intended to reduce the edge defects was impractical. This was deemed impractical because of the large of the number of wafers required to generate meaningful statistics and the number of process options. Additionally, manual inspections used to count the number of defects were inconsistent as well as slow. An automated macro defect inspection system (August Technology AXi Series 930) was used in a novel way to enable fast, accurate, and repeatable defect counts from the wafer top edge to help determine the most appropriate process improvement.

Partial or total duplication of document content is common to large digital libraries. We present a copy detection system to automate the detection of application in digital documents. The system we present is sentence-based and makes three contributions: it proposes an intuitive definition of similarity between documents; it produces the distribution of overlap that exists between overlapping documents; it is resistant to inaccuracy due to large variations in document size. We report the results of several experiments that illustrate the behavior and functionality of the system.

BACKGROUND: Patients who are refractory to platelet transfusion as a result of HLA alloimmunization are generally given HLA-matched or crossmatched platelets. However, HLA-matched platelets that are matched at HLA-A and -B loci (A-matched) or those without any mismatched or cross-reactive antigens (BU-matched) are frequently unavailable. A disadvantage of crossmatching is that crossmatched platelets have a shelf life of only 5 days, so that crossmatch tests must be performed frequently for patients requiring long-term platelet transfusions. An alternative method is the selection of platelets according to the patient's HLA antibody specificity, called the antibody specificity prediction (ASP) method. STUDY DESIGN AND METHODS: An anti-human globulin-enhanced microlymphocytotoxicity test modified by a double addition of serum and a computer program were used to determine the specificity of patients' HLA antibodies. Platelet crossmatching was performed with a solid-phase adherence assay. The percentage of platelet recovery (PPR) was determined in 1621 platelet transfusions in an observational study in 114 patients, and the PPR of platelets selected by the ASP method was compared with the PPR of those that were HLA-matched, crossmatched, or randomly selected. The numbers of potential donors in files of HLA-typed donors as identified by HLA matching vs. the ASP method were determined. RESULTS: After adjustments for covariates, the mean ± SEM PPR was similar for HLA-matched (21 ± 4%), cross-matched (23 ± 4%), and ASP-selected (24 ± 3%) platelets and was significantly lower for randomly selected (15 ± 1.4%) platelets. For 29 alloimmunized HLA-typed patients, the mean number of potential donors found in a file of 7247 HLA-typed donors was 6 who were an HLA-A match (median = 1), 33 who were an HLA-BU match (median = 20), and 1426 who were identified by the ASP method (median = 1365). CONCLUSION: The ASP method of donor selection for refractory alloimmunized patients appears as effective as HLA matching or crossmatching. Far more donors are identified in a file of HLA-typed donors by the ASP method than by HLA matching, and this indicates that the ASP method provides important advantages regarding the availability of compatible platelet components.

We present a new approach to extracting information from unstructured documents based on an application ontology that describes a domain of interest. Starting with such an ontology, we formulate rules to extract constants and context keywords from unstructured documents. For each unstructured document of interest, we extract its constants and keywords and apply a recognizer to organize extracted constants as attribute values of tuples in a generated database schema. To make our approach general, we fix all the processes and change only the ontological description for a different application domain. In experiments we conducted on two different types of unstructured documents taken from the Web, our approach attained recall ratios in the 80% and 90% range and precision ratios near 98%.

Oil and gas production from the Texaco-operated Petronius Compliant Tower will begin in early 1999. The field is located at Viosea Knoll Bloek 786 in 1750 feet of water. The Petronius Subsurface Development Team has employed fluid-flow simulation as the primary tooI for optimizing plans for development drilling and reservoir management.

Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document’s content. For these kinds of data-rich documents (e.g., advertisements, movie reviews, weather reports, travel information, sports summaries, financial statements, obituaries, and many others) we can apply a conceptual-modeling approach to extract and structure data. The approach is based on an ontology – a conceptual model instance – that describes the data of interest, including relationships, lexical appearance, and context keywords. By parsing the ontology, we can automatically produce a database scheme and recognizers for constants and keywords, and then invoke routines to recognize and extract data from unstructured documents and structure it according to the generated database scheme. Experiments show that it is possible to achieve good recall and precision ratios for documents that are rich in recognizable constants and narrow in ontological breadth.