Добірка наукової літератури з теми "Traffic surveys Computer programs"

Road safety awareness is one of the many awareness programs that are often highlighted and discussed around the world. The road accident statistics are increased due to the lack of exposure and awareness among communities about traffic environments and rules. Children are one of the most vulnerable populations involved in traffic accidents. The children are unable to familiarize themselves with the surroundings, especially when crossing the road. This research attempts to improve road-safety awareness among children by using computer games as a learning tool. Specifically, it determines the progress of knowledge on the road rules and conditions after the children using the tool. The computer online game is suitable methods to use for teaching them on road safety due to interactive application always intimate the children. Besides the survey questions that related to road traffic rules, we also measures the attitude towards road safety in the participant (i.e., children and adult). Descriptive analysis in frequency, mean, and percentage are used to describe the respondent’s information. Statistical Package for Social Science (SPSS) is used to analyze the findings. The overall findings show that all respondents have positive feedback on online games as a road safety tool. Interestingly, the significant output shows on the different knowledge about road safety when the children are analyzed for before and after they played the games. The future research is suggested to study the other group of participant as the respondent in this work is limited to the primary school children. It can be improved by involving the large sample size and wider location.

Survey items developed in behavioral Information Security (InfoSec) research should be practically useful in identifying individuals who are likely to create risk by failing to comply with InfoSec guidance. The literature shows that attitudes, beliefs, and perceptions drive compliance behavior and has influenced the creation of a multitude of training programs focused on improving ones’ InfoSec behaviors. While automated controls and directly observable technical indicators are generally preferred by InfoSec practitioners, difficult-to-monitor user actions can still compromise the effectiveness of automatic controls. For example, despite prohibition, doubtful or skeptical employees often increase organizational risk by using the same password to authenticate corporate and external services. Analysis of network traffic or device configurations is unlikely to provide evidence of these vulnerabilities but responses to well-designed surveys might. Guided by the relatively new IPAM model, this study administered 96 survey items from the Behavioral InfoSec literature, across three separate points in time, to 217 respondents. Using systematic feature selection techniques, manageable subsets of 29, 20, and 15 items were identified and tested as predictors of non-compliance with security policy. The feature selection process validates IPAM's innovation in using nuanced self-efficacy and planning items across multiple time frames. Prediction models were trained using several ML algorithms. Practically useful levels of prediction accuracy were achieved with, for example, ensemble tree models identifying 69% of the riskiest individuals within the top 25% of the sample. The findings indicate the usefulness of psychometric items from the behavioral InfoSec in guiding training programs and other cybersecurity control activities and demonstrate that they are promising as additional inputs to AI models that monitor networks for security events.

Problem. To solve the problems of rational organization of work of urban passenger transport on the routes and determine the modes of vehicles work and labor of drivers of motor transport enterprises when carrying out transportation of the city population. It is necessary to know all the input conditions for creating traffic schedules on the route. One of the main parameters is the existing traffic volumes on a certain public transport route. In order to improve the management of transportation on the routes of urban passenger transport, various approaches to their survey were considered, the problem of studying traffic volumes for further drawing up traffic schedules was identified. In this article, the task was to analyze the work of a separate route and passenger traffic on it. Goal. The goal is studying passenger traffic on a separate public transport route, studying the regularities of traffic volumes and their dependence on operating time. Methodology. When fulfilling the task, the procedure by which the input data is processed is given. Having examined the known methods and principles of applying certain groups of methods to solve various types of problems, to solve the problem of organizing work on the route, namely, to distribute changes in the operation of vehicles for the transportation of passengers, we opted for a readable tabular method of examining passenger traffic. Thus, an incoming sequence of values was obtained, which we presented as time series levels. An analysis of incoming time series was carried out, their modeling using an adaptive algorithmic method. Results. A method of using computer mathematics systems for modeling and predicting input time series was developed, during which the solution process was programmed and the results of adaptive algorithmic modeling of passenger traffic dependencies on time were obtained, which can be used to build schedules for the movement of vehicles during passenger transportation by public transport. Originality. Passenger traffic on a separate route was investigated, the methodology of this study was presented, all components of the time series were taken into account and modeled. The graphic representation was provided. This article has developed programs for performing modeling and forecasting using adaptive algorithmic models. Practical value. This provides an opportunity to investigate the passenger traffic of any passenger transport route, carrying out transportation, sequences of volume whose values have similar components of the time series. The result of these studies is building a model and obtaining forecast values, which plays a large role in management of road passenger transport.

Over the last five years, the Center for Migration Studies of New York (CMS) has conducted four surveys of Catholic immigrant-serving institutions, programs, and ministries in the United States. These surveys identify the multi-faceted needs of immigrants and refugees, and examine the successes and challenges of Catholic institutions in responding to them. CMS administered its most recent survey, the Catholic Refugee and Immigrant Service Integration Survey (the “CRISIS Survey”) from December 14, 2020 through February 5, 2021. This survey explored the work of Catholic institutions during the Trump administration and the COVID-19 pandemic. The CRISIS Survey documents the reach, diversity, and productivity of Catholic institutions that worked with immigrants and refugees during a pandemic that particularly devastated their communities and an administration whose policies and rhetoric made their work far more difficult. At a time of rampant “Catholic decline” narratives, the survey also documents the reach, vitality, and relevance of Catholic immigrant-serving institutions. It identifies the obstacles encountered by immigrants in accessing Catholic programs and ministries — both organizational (funding, staffing, and siting) and exogenous (federal policies, the pandemic, and community opposition). It underscores the threat posed by US immigration policies to immigrants and to the work of Catholic institutions. Survey respondents reported that they offered new services during this period, such as: Financial assistance for families, particularly those at risk of losing housing or utilities. COVID-19 testing, education, contact tracing, and quarantine services. Mental health services. Grief support and assistance with funeral expenses. Delivery of food and sanitation supplies for infected and other homebound persons. Voter registration and Census promotion activities. Virtually all respondents provided services remotely during the pandemic. Many reported on difficulties faced by immigrants in accessing their services, due to poor internet connections, limited computer access, and lack of communications technology and training. Respondents identified several factors that negatively affected immigrants’ access to their services pre-pandemic. As in previous CMS surveys, these factors included lack of immigration status, negative community attitudes toward immigrants, fear of apprehension (particularly after traffic stops) and deportation, public transportation deficiencies, stigma over receipt of mental health services, and identification requirements to access public benefits. Respondents also reported on obstacles in working with immigrants during the pandemic. These included the pandemic itself, limited funding, demand that outpaced resources, government restrictions on relief and benefit eligibility, and (particularly for students) living arrangements, work, and family caretaking responsibilities. Respondents overwhelmingly believed that immigration enforcement, tied to fear of deportation, very negatively or somewhat negatively affected participation in their services and programs. In Catholic terms, they reported that nativist immigration policies, rhetoric, and media sources interfered with their practice of discipleship. One respondent stated, “Fear of ICE and round-ups, locally in our state and nationally, along with negative immigration rhetoric from the out-going president have made our clients very fearful to access services they rightly qualify for.” A healthcare provider reported that immigrants were “avoiding or delaying seeking treatment for COVID-19 for fear of apprehension and/or deportation.” Many said that enforcement partnerships between Immigration and Customs Enforcement and states and localities made immigrants fearful of reporting crimes or accessing government facilities. One said that potential sponsors feared coming forward to reunify with children. Respondents also cited as problems delays in family reunification, barriers to asylum-seekers entering the United States, decreased refugee admissions, and the Trump administration's rule on the public charge ground of inadmissibility. The report recommends that Catholic institutions take stock of the creative new programs, skills and capacities that they have developed during the pandemic and build on them. It also recommends that scholars and researchers prioritize independent, person-centered research that critically analyzes the work of Catholic immigrant-serving institutions. Such research would ask whether these institutions, in the words of Pope Francis, are putting “the person at the center, in his or her many aspects” and honoring the “fundamental equality” of every person. It would draw on the perspectives of immigrants served by Catholic institutions to examine the degree to which these institutions advance the rights, participation, and wellbeing of immigrants and their families in US society. Finally, it would analyze how Catholic institutions work with each other — within Arch/dioceses, regionally, nationally, and across these realms — in response to the cross-cutting needs of immigrants. The report recommends that Catholic institutions develop programmatic plans to ensure that immigrants can return to or can continue to access their programs and ministries as the pandemic subsides. These plans will need to combine communication strategies, financial support, and services such as transportation and childcare. In addition, Catholic institutions should make it a high priority to ensure that immigrants can access the infrastructure, platforms, and training that will allow them to access virtual services. They should also develop strategies to engage Catholics who do not understand, who ignore, or who work at cross-purposes to Catholic teaching and policy positions in this area. Finally, they should redouble their work with the administration and Congress to reform US immigration laws, and with states and localities to promote welcoming and inclusive communities.

Taxi drivers face many problems every day including safety issues. The tendency to quickly transport passengers to their destinations for more income has resulted in dangerous driving behaviors leading to traffic violations. So, taxi drivers need appropriate support and training programs to improve safety and reduce the risk of crashes. Implementing different support and safety training programs requires an effective management system. There is a dearth of research on the safety issues of taxis from the perspective of taxi organization managers. This study aims to evaluate the safety issues of taxi transport management through a case study of the Tehran Taxi Organization. A questionnaire survey was conducted with 22 regional managers and 20 transportation specialists of the Tehran Taxi Organization. Issues related to taxi drivers, roads and road users, vehicles, and management systems were evaluated in the questionnaire. Participants determined the relevance level and priority ranking of each question. The level of agreement was then tested using the Kendall concordance test. According to the results, the use of GPS was selected as the best in-vehicle monitoring system that can be used to evaluate drivers in the fleet. Participants believed that passengers’ loading and unloading had the most risk for taxi users. The start-inhibit technology to detect open doors was unanimously evaluated as an efficient technology for taxi safety. With respect to educating taxi users, starting education in schools had the most relevance and priority. Recommendations for increasing the safety of taxis include the use of GPS in taxis to monitor and evaluate drivers, receiving crash reports from police and submitting monthly safety assessment reports, flexibility in drivers’ working hours’ schedule, providing training on drivers fatigue management, and evaluating drivers’ health.

Digitalization of the social infrastructure of cities is becoming increasingly important in the strategy of city development and improving the efficiency of municipal management. The purpose of this study is to assess the level of digitalization of social infrastructure as part of the implementation of the smart city development strategy on the example of Yekaterinburg. It is determined that digital technologies have become an integral attribute of the lifestyle of the population. The population actively uses the Internet and mobile communication capabilities. The Internet is especially actively used to search for information, as well as communication, personal and business contacts. The Internet is actively replacing television and radio as sources of information. The reasons that reduce the digitalization of the urban environment are highlighted. A considerable number of respondents indicated the low level of communication between the local population and municipal authorities during the mass survey. The reasons for the weak formation of a digital society are also noted: low level of digital competencies, insufficient provision of computer equipment, lack of automated research systems, lack of affordable high-speed Internet. The directions of improving the social practice of smart city development are determined. In the field of improving the Internet, it is necessary to increase the speed of data transmission, ensure stability of operation, and improve information sites. In the field of education, it is proposed to provide educational institutions with the necessary equipment and appropriate programs, to replace outdated computers in educational institutions. In the field of healthcare, the achievements have been highly appreciated, but a wish has been expressed to simplify online registration in hospitals. Internet services, online payments, e-mail, delivery, and other services were highly appreciated. In general, transport services were also positively evaluated, but wishes were expressed to improve the organization of public transport, observe the traffic schedule, and use digital technologies at bus stations. Residents propose to upgrade bus shelters throughout the city, install more “smart stops”, introduce taxi drones.

It is reported by the British Aerospace (BAE Systems) that their researchers have developed a revolutionary airborne computer system that, they claim, can land aircraft safely without the need of human air traffic controllers. The new system will allow a pilot to determine an aircraft's landing by pressing a button in the cockpit to initiate the computer system.

Large countries with extensive road networks, such as Brazil, require large volumes of financial resources to perform traffic surveys. In Brazil, the biggest road traffic survey was performed in 2011 with 120 counting survey stations. This survey was divided into three stages and 83 support units provided survey teams. A support unit is a place, such as a military organization, close to the survey stations. A stage indicates that only some survey stations must be considered at a time. In large scale traffic surveys with multi-stages, we must define which support unit will serve each survey station so that travel costs for the survey teams and the costs to use the support units are minimized. We present the Support Unit Location Problem to Assist Road Traffic Survey with Multi-Stages where, given a set of available support units, each one with a coverage area, and a set of multi-stage traffic survey stations, we must select units to serve stations so that the cost is minimized. Scenarios are evaluated for a real traffic survey with 300 counting stations and four stages in Brazil. Computational experiments show that large cost reductions can be found when a mathematical model is used.

Introduction. On the basis of the priority project “Safe and High-quality Roads”, the researches develop and implement the programs of the transport infrastructure integrated development – highways and municipal roads, bringing the urban agglomeration network into a standard transport and operational state, eliminating the congestion of the urban agglomerations’ network, optimizing traffic flows, increasing efficiency traffic management systems. The paper assesses the options’ effectiveness of the transport infrastructure development in the Omsk region until 2041.Materials and methods. The authors used analysis methods of existing regulatory, legal, program documents; of carrying out and analyzing the results of traffic intensity surveys at key nodes by means of transport; of conducting and analyzing the results of pedestrian traffic surveys at key points; analyzing the existing traffic conditions obtained from the results of the development of the transport macro model of the Omsk agglomeration in the PTV Vision VISUM software; of analyzing causes and conditions of accidents; of analyzing statistical data on freight turnover and passenger traffic in the Omsk agglomeration.Results. The paper presented the research results on the Omsk agglomeration’s example. The results formed the programs’ basis for the integrated development of the transport infrastructure of Omsk and eight districts of the Omsk agglomeration. Moreover, the authors presented the literature review and took into account the achievements of foreign science.Discussion and conclusions. The authors emphasize that it is necessary to improve the methods of obtaining data used in the formation of the transport model and to improve the performance of the transport i modern cities’ infrastructure.The authors have read and approved the final manuscript. Financial transparency: the authors have no financial interest in the presented materials or methods. There is no conflict of interest.

Road traffic surveys determine the number and type of vehicles passing by a specific point over a certain period of time. The manual estimation of the number and type of vehicles from images captured by a camera is the most commonly used method. However, this method has the disadvantage of requiring high amounts of manpower and cost. Recently, methods of automating traffic volume surveys using sensors or deep learning have been widely attempted, but there is the disadvantage that a person must finally manually verify the data in order to ensure that they are reliable. In order to address these shortcomings, we propose a method for efficiently conducting road traffic volume surveys and obtaining highly reliable data. The proposed method detects vehicles on the road from CCTV (Closed-circuit television) images and classifies vehicle types using deep learning or a similar method. After that, it automatically informs the user of candidates with a high probability of error and provides a method for efficient verification. The performance of the proposed method was tested using a data set collected by an actual road traffic survey company. As a result, we proved that our method shows better accuracy than the previous method. The proposed method can reduce the labor and cost in road traffic volume surveys, and increase the reliability of the data due to more accurate results.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): John C. McEachen. "December 2006." Includes bibliographical references (p.65-66). Also available in print.

Thesis (M.S. in Modeling, Virtual Environments, and Simulation)--Naval Postgraduate School, June 2006.
Thesis Advisor(s): Arnold Buss. "June 2006." Includes bibliographical references (p. 83-85). Also available in print.

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Bachelors
Engineering
Computer Engineering

A new approach for the development of problem-solvers for combinatorial problems is proposed in this thesis. The approach combines incremental knowledge acquisition and probabilistic search algorithms, such as evolutionary algorithms, to allow a human to rapidly develop problem-solvers in new domains in a framework called HeurEAKA. The approach addresses a known problem, that is, adapting evolutionary algorithms to the search domain by the introduction of domain knowledge. The development of specialised problem-solvers has historically been labour intensive. Implementing a problem-solver from scratch is very time consuming. Another approach is to adapt a general purpose search strategy to the problem domain. This is motivated by the observation that in order to scale an algorithm to solve complex problems, domain knowledge is needed. At present there is no systematic approach allowing one to efficiently engineer a specialpurpose search strategy for a given search problem. This means that, for example, adapting evolutionary algorithms (which are general purpose algorithms) is often very difficult and has lead some people to refer to their use as a ???black art???. In the HeurEAKA approach, domain knowledge is introduced by incrementally building a knowledge base that controls parts of the evolutionary algorithm. For example, the fitness function and the mutation operators in a genetic algorithm. An evolutionary search algorithm ismonitored by a human whomakes recommendations on search strategy based on individual solution candidates. It is assumed that the human has a reasonable intuition of the search problem. The human adds rules to a knowledge base describing how candidate solutions can be improved, or why they are desirable or undesirable in the search for a good solution. The incremental knowledge acquisition approach is inspired by the idea of (Nested) Ripple Down Rules. This approach sees a human provide exception rules to rules already existing in the knowledge base using concrete examples of inappropriate performance of the existing knowledge base. The Nested Ripple Down Rules (NRDR) approach allows humans to compose rules using concepts that are natural and intuitive to them. In HeurEAKA, NRDR are significantly adapted to form part of a probabilistic search algorithm. The probabilistic search algorithms used in the presented system are a genetic algorithm and a hierarchical bayesian optimization algorithm. The success of the HeurEAKA approach is demonstrated in experiments undertaken on industrially relevant domains. Problem-solvers were developed for detailed channel and switchbox routing in VLSI design and traffic light optimisation for urban road networks. The problem-solvers were developed in a short amount of time, in domains where a large amount of effort has gone into developing existing algorithms. Experiments show that chosen benchmark problems are solved as well or better than existing approaches. Particularly in the traffic light optimisation domain excellent results are achieved.

One of the significant advances in software design afforded by the internet has been the open source movement, an effort to collaboratively create software and make it widely and freely available to the online community. Although the open source movement started with Unix-like computer operating systems, it has expanded to include a wide variety of software programs, including tools to publish and analyze online surveys. This article introduces the open source movement and then profiles three leading open source survey programs: php Easy Survey Package (phpESP), PHP Surveyor, and the Moodle course management system.

We discuss a software infrastructure that provides a virtual proving ground for designing, training, and auditing the computer programs used to pilot connected autonomous vehicles (CAVs). This effort does not concentrate on developing the piloting computer programs (PCPs) responsible for path planning in autonomous vehicles (AVs). Instead, we have established a first version of an emulation platform that changes the PCP design/test/improve process, which is often times carried out covertly [46], or in actual traffic conditions with potentially fatal consequences [45, 47].

One of the significant advances in software design afforded by the Internet has been the open source movement, an effort to collaboratively create software and make it widely and freely available to the online community. Although the open source movement started with Unix-like computer operating systems, it has expanded to include a wide variety of software programs, including tools to publish and analyze online surveys. This chapter introduces the open source movement, and then profiles three leading open source survey programs: php Easy Survey Package (phpESP), PHP Surveyor, and the Moodle course management system.

In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.

Every software application has its own minimum set of requirements like CPU, storage, memory, networking, and power. These have to be integrated into a specific configuration to allow the smooth functioning of the software application. When data traffic becomes higher than expected, higher resources are required. There may not be enough time to provision new resources manually; in such cases, an auto-scaling system is required for managing these situations. Cloud computing means using data, programs, and other resources pooled in the data center and accessed through the internet instead of the user's computer. In the chapter, the authors discussed some aspects related to cloud computing like cloud workload, load balancing, load balancing algorithms, scaling techniques, and auto-scaling to fulfill cloud workload balancing requirements.

This chapter first points out the need for a reader on information technology by reviewing the importance given computing education by MPA programs and practitioners. Next, the chapter surveys current textbooks’ and general public administration journals’ treatments of the topic. Three highly respected public administration journals and six textbooks are reviewed. The journals are found to barely treat the topic of computing, whether as a main focus or as merely a mention in articles. The textbooks also barely mention computing. In addition, there is no consistent rubric or chapter topic under which computing is discussed. The need for a reader on information technology and computer applications in public administration is apparent. The chapter then turns to the consideration of what hands-on skills in computer applications should be a mark of a graduate degree in public administration. It is suggested that there are six generic skills with a seventh one on the horizon. Finally, the chapter concludes by briefly discussing a range of issues that public administrators should be conversant with if they are to successfully utilize computer applications in the delivery of public sector services.

One of the most powerful weapons for attackers is the Internet worm. Specifically, a worm attacks vulnerable computer systems and employs self-propagating methods to flood the Internet rapidly. Since a “Worm” is self-propagated through the connected network, it doesn’t need human interaction or file transmission to replicate itself. It spreads in minutes; Slammer worms infect about 75,000 nodes through the internet in about 10 minutes. Since most of antivirus programs detect viruses based on their signature, then this approach can’t detect new viruses or worms till being updated with their signature, which can’t be known unless some systems had already been infected. This highlights worms are still on the top of malware threats attacking computer systems, although the evolution of worms detection techniques. Early detection of unknown worms is still a problem. This chapter produce a method for detecting unknown worms based on local victim information. The proposed system uses Artificial Neural Network (ANN) for classifying worm/ nonworm traffic and predicting the percentage of infection in the infected network. This prediction can be used to support decision making processes for network administrators to respond quickly to worm propagation in an accurate procedure.

Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.

Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.

The Scalable Coherent Interface (SCI) is an IEEE/ANSI standard that defines a hardware platform for scalable shared-memory multiprocessors. This paper contains a quantitative performance evaluation of SCI-connected multiprocessors that assesses both the communication and cache coherence subsystems. 1D, 2D and 3D tori with 16 and 64 nodes are investigated. For the architecture (100MHz Sparc, 2 levels of caches) and workload simulated, it was found that raw network bandwidth seen by a processing element is under 100Mbytes/s. The 3-D toros is 10-15% faster than the 2-D toros for programs that generate high leveis of network traffic. Otherwise, the differences in performance between 2-D and 3-D tori are negligible.

Computer simulations have implications across disciplines and with learners at all levels. By requiring learners to develop and apply knowledge and skills in interactive changing environments, they encourage deeper levels of learning. Additionally, simulations have been shown to be particularly effective at teaching complicated concepts that depend on the ability to understand interrelationships, strategize, make predictions, analyze and evaluate, and engage in multi-faceted decision making. In order to help students gain a deeper understanding of key business concepts, encourage critical thinking and decision making, foster collaboration and critical discourse, and encourage the application of concepts into real world business practices, the University of Maryland Eastern Shore, a minority serving institution, decided in 2004 to introduce a series of competitive web-based simulations at key junctures throughout the curriculum but focused primarily in the course Strategic Management. The simulation selected covers topics such as Strategy & Tactics, Policy, Production, Accounting, Marketing, Finance, Quality control, Human resources, Leadership, and Teamwork and involves students competing in teams against other teams. In order to assess the effectiveness of the simulation, a research protocol was introduced that included the administration of student surveys as well as the collection of performance data. The findings indicate that students overwhelmingly felt that the simulation helped them understand the application of key concepts and learn the decision making process that occurs in professional business practice. The examination of student performance data gathered in this study, with consideration given to the strong levels of student satisfaction, encouraged the authors to postulate based on the high success rates of this student population, which traditionally underperforms in more traditional mode of assessments, that simulations may serve as an equalizer that offers all students, from low to high achievers, an opportunity to succeed and that competitive web-based simulations enhance the overall educational and personal development experiences of minority students enrolled in higher education business programs.

While traditionally archaeological research has mainly been focused on individual cultural heritage monuments or distinct archaeological sites, the Austrian based Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology goes beyond the limitations of discrete sites in order to understand their archaeological context. This is achieved by investigating the space in-between the sites, studying entire archaeological landscapes from the level of individual postholes to the mapping of numerous square kilometres. This large-scale, high-resolution, multi-method prospection approach leads to enormous digital datasets counting many terabytes of data that until recently were technically not manageable. Novel programs and methods of data management had to be developed for data acquisition, processing and archaeological interpretation, in order to permit the extraction of the desired information from the very big amount of data. The analysis of the generated datasets is conducted with the help of semi-automatic algorithms within complex three-, or even four-dimensional geographical information systems. The outcome of landscape archaeological prospection surveys is visually communicated to the scientific community as well as to the general public and stakeholders. In many cases, a visualization of the scientific result and archaeological interpretations can be a powerful and suitable tool to illustrate and communicate even complex contexts to a wide audience. This paper briefly presents the great potential offered by a combination of large-scale non-invasive archaeological prospection methods and standardized workflows for the integration of big data, its interpretation and visualization. The proposed approach provides a context for buried archaeology across entire archaeological landscapes, changing our understanding of known monuments. We address the overcome and remaining challenges with the help of examples taken from outstanding landscape archaeological prospection case studies.

Since its launch Ford SYNC™ with MyFord Touch™ in-vehicle infotainment (IVI) system has migrated to many vehicle programs and had multiple software updates, which presented Ford dealers with the ever-increasing challenge of training new owners effectively and efficiently. This paper presents the design, architecture and implementation of “MyFord Touch Guide”, a novel, cross-platform mobile app that delivers a unique MyFord Touch learning and familiarization experience for dealers and consumers alike. This app incorporates the production MyFord Touch graphical user interface for an interactive learning experience. Additionally, it integrates a host of video tutorials featuring a computer-animated character, which offers an insightful, personalized and self-guided tour experience of the essential features and functions of the system. MyFord Touch Guide is a cross-platform app and based on a “hybrid” app architecture that uses both native mobile and web technologies. Feedback gathered from multiple nation-wide surveys indicates that the proposed approach provides a highly effective and scalable solution towards developing a diverse range of cross-platform, interactive, mobile learning apps.

Increases in export pipeline development can result in a corresponding increase in marine transportation activities and the potential to escalate adverse interactions with marine wildlife. Ship traffic introduces risks of vessel strikes as well as the amount of underwater noise produced in the marine environment. Growing public and scientific concern over the potential effects of increasing ship traffic on marine wildlife mean that even terrestrially-based pipeline projects need to start considering the effects of shipping in developing environmental mitigation programs for their export operations. Northern Gateway is proposing to construct and operate twin pipelines between Alberta and British Columbia, and an associated tank and marine terminal for export operations. While Northern Gateway will not own or operate any of the tankers, they have committed to implementing a comprehensive marine mitigation, monitoring and research program, including measures to reduce ship strikes and effects of underwater noise on marine mammals. Vessel strikes can cause severe or fatal injuries. Higher relative risk exists where shipping traffic overlaps with increased densities of marine mammals. Vessel speed has been positively correlated with the degree of risk and injury; consequently, Northern Gateway has set maximum year-round speed restrictions of 10–12 knots for all Project-related tankers calling at the marine terminal, with further restrictions of 8–10 knots in key areas. Other large vessels in this region currently travel at speeds of 16–21 knots. Mandatory speed restrictions will also reduce the Project’s contribution to underwater noise. Effects of underwater noise on marine mammals include temporary habitat avoidance, reduced feeding efficiency, behavioural change, increased stress, and communication masking. Acoustic modeling conducted for the project predicted that reducing vessel speeds from 15 to 9.6 knots would decrease underwater noise input by nearly 12 dB, making the zone of ensonification 2–3 times smaller than in the absence of mitigations. Purpose-built escort tugs will use best commercially-available noise-quieting technology and speed restriction areas will be refined through six-years of surveys and a quantitative vessel strike analysis. Vessel traffic is not unique to Northern Gateway; however, through minimizing their incremental contribution, they hope to serve as an industry example. This approach to minimizing effects of routine marine export operations is unique in the shipping industry in Canada and the United States. If other proponents were to adopt similar types of measures, Northern Gateway believes that the marine environment would see some net benefits in terms of a reduction in adverse effects on marine mammals.

Road traffic noise, as a form of environmental pollution, is an important element causing discomfort among inhabitants and leading to the emergence of noise nuisance influencing the shaping of urban space. The basic tool in combating noise is a Strategic Noise Map (SNM), which, understood as a system, constitutes an element of a city’s information layer. The system, illustrating the noise situation within a city, is prepared by means of a calculationmeasurement method using specialized computer programs. The assessment of road traffic noise begins by defining the amount of noise emissions coming from acoustically-homogenous sections (emission map), and ends with determining the extent of noise propagation in urban space (immission map). The above process is based on the analysis of actual input data describing, in a detailed manner, the analyzed road infrastructure in terms of the characteristics of the road section, information on the volume and type of traffic, and data on the organization of traffic. Under such extensive analysis of the condition of the environment, it is appropriate to apply GIS data as a methodological basis for creating SNMs. GIS data make it possible to unify the rules for collecting and archiving values characterizing the condition of the environment, as well as parameters influencing the level of noise. The aim of work is create a theoretical road traffic noise model with the help of GIS. The scope of information in attribute tables of acoustically-homogenous road sections comprising a GIS thematic layer was described in detail. The above information are the basis for generating digital road traffic noise emission maps as well as being the starting point for assessing road traffic noise in the area of a city in the form of immission maps. The article additionally analyzes the results of data derived from the first phase of noise mapping in Europe, as well as familiarizing the reader with the procedure of modelling road traffic noise emission in accordance with the CNOSSOS-EU which will become binding as of 31 December 2018 throughout the European Union, and which was introduced by the provisions of the new noise directive – Directive 2015/996 of 19 May 2015.

Data compression virtually increases the effective network bandwidth on an interconnection network of parallel computers. Although a floating-point dataset is frequently exchanged between compute nodes in parallel applications, its compression ratio often becomes low when using simple lossless compression algorithms. In this study, we aggressively introduce a lossy compression algorithm for floating-point values on interconnection networks. We take an application-level compression for providing high portability: a source process compresses communication datasets at an MPI parallel program, and a destination process decompresses them. Since recent interconnection networks are latency-sensitive, sophisticated lossy compression techniques that introduce large compression overhead are not suitable for compressing communication data. In this context, we apply a linear predictor with the userdefined error bound to the compression of communication datasets. We design, implement, and evaluate the compression technique for the floating-point communication datasets generated in MPI parallel programs, i.e., Ping Pong, Himeno, K-means Clustering, and Fast Fourier Transform (FFT). The proposed compression technique achieves 2.4x, 6.6x, 4.3x and 2.7x compression ratio for Ping Pong, Himeno, K-means and FFT at the cost of the moderate decrease of quality of results (error bound is 10-4 ), thus achieving 2.1x, 1.7x, 2.0x and 2.4x speedup of the execution time, respectively. More generally, our cycle-accurate network simulation shows that a high compression ratio provides comparably low communication latency, and significantly improves effective network throughput on typical synthetic traffic patterns when compared to no data compression on a conventional interconnection network.

Layer-elastic, finite-element computer programs are available for performance-based structural design and analysis of railway trackbeds. This paper utilizes the KENTRACK design program. It is possible to consider the fatigue lives of the various layers relative to the imposed wheel loads, tonnages, environmental conditions and other factors. The service lives of the individual components of the trackbed are predicted by damage analysis for various combinations of traffic loadings, accumulated tonnages, subgrade support, and component layer properties and thicknesses. The results are presented graphically. The latest version, KENTRACK 3.0, is utilized. It is coded in C#.NET a popular computer language for achieving accuracy and efficiency. The graphical user interface in the KENTRACK 3.0 provides a technique to analyze trackbeds as structures. It is possible with KENTRACK 3.0 to select individual trackbed layers and associated thicknesses to satisfy roadbed and trackbed performance requirements. In addition, it is possible to performance-rank different track sectional designs based on the relative importance of the particular track section and track type. The types of roadbed and trackbed configurations are selected to meet each of the various performance ranks.

Aim/Purpose: Science is becoming a computational endeavor therefore Computational Thinking (CT) is gradually being accepted as a required skill for the 21st century science student. Students deserve relevant conceptual learning accessible through practical, constructionist approaches in cross-curricular applications therefore it is required for educators to define, practice and assess practical ways of introducing CT to science education starting from elementary school. Background: Computational Thinking is a set of problem-solving skills evolving from the computer science field. This work-in-progress research assesses the CT skills, along with science concepts, of students participating in a science program in school. The program pertains learning science by modeling and simulating real world phenomenon using an agent-based modeling practice. Methodology: This is an intervention research of a science program. It takes place as part of structured learning activities of 4th and 5th grade classes which are teacher-guided and are conducted in school. Both qualitative and quantitative evaluations are parts of the mixed methods research methodology using a variety of evaluation technique, including pretests and posttests, surveys, artifact-based interviews, in class observations and project evaluations. Contribution: CT is an emerging skill in learning science. It is requiring school systems to give increased attention for promoting students with the opportunity to engage in CT activities alongside with ways to promote a deeper understanding of science. Currently there is a lack of practical ways to do so and lack of methods to assess the results therefore it is an educational challenge. This paper presents a response to this challenge by proposing a practical program for school science courses and an assessment method. Findings: This is a research in progress which finding are based on a pilot study. The researches believe that findings may indicate improved degree of students' science understanding and problem-solving skills. Recommendations for Practitioners: Formulating computer simulations by students can have great potential on learning science with embedded CT skills. This approach could enable learners to see and interact with visualized representations of natural phenomena they create. Although most teachers do not learn about CT in their initial education, it is of paramount importance that such programs, as the one described in this research, will assist teachers with the opportunity to introduce CT into science studies. Recommendation for Researchers: Scientific simulation design in primary school is at its dawn. Future research investment and investigation should focus on assessment of aspects of the full Computational Thinking for Science taxonomy. In addition, to help teachers assess CT skills, new tools and criteria are required. Impact on Society: STEM related professions are lacking the man power required therefore the full potential of the economy of developed countries is not fulfilled. Having students acquire computational thinking skills through formal education may prepare the next generation of world class scientists and attract larger populations to these fields. Future Research: The inclusion of computational thinking as a core scientific practice in the Next Generation Science Standards is an important milestone, but there is still much work to do toward addressing the challenge of CT-Science education to grow a generation of technologically and scientifically savvy individuals. New comprehensive approaches are needed to cope with the complexity of cognitive processes related to CT.

Aim/Purpose: This paper provides the results of the preliminary analysis of the findings of an ongoing study that seeks to examine the social media use, cultural and political awareness, civic engagement, issue prioritization, and social activism of Gen Z students enrolled at four different institutional types located in the Mid-Atlantic region of the United States. The aim of this study is to look at the group as a whole as well as compare findings across populations. The institutional types under consideration include a mid-sized majority serving or otherwise referred to as a traditionally white institution (TWI) located in a small coastal city on the Atlantic Ocean, a small Historically Black University (HBCU) located in a rural area, a large community college located in a county that is a mixture of rural and suburban and which sits on the border of Maryland and Pennsylvania, and graduating high school students enrolled in career and technical education (CTE) programs in a large urban area. This exploration is purposed to examine the behaviors and expectations of Gen Z students within a representative American region during a time of tremendous turmoil and civil unrest in the United States. Background: Over 74 million strong, Gen Z makes up almost one-quarter of the U.S. population. They already outnumber any current living generation and are the first true digital natives. Born after 1996 and through 2012, they are known for their short attention spans and heightened ability to multi-task. Raised in the age of the smart phone, they have been tethered to digital devices from a young age with most having the preponderance of their childhood milestones commemorated online. Often called Zoomers, they are more racially and ethnically diverse than any previous generation and are on track to be the most well-educated generation in history. Gen Zers in the United States have been found in the research to be progressive and pro-government and viewing increasing racial and ethnic diversity as positive change. Finally, they are less likely to hold xenophobic beliefs such as the notion of American exceptionalism and superiority that have been popular with by prior generations. The United States has been in a period of social and civil unrest in recent years with concerns over systematic racism, rampant inequalities, political polarization, xenophobia, police violence, sexual assault and harassment, and the growing epidemic of gun violence. Anxieties stirred by the COVID-19 pandemic further compounded these issues resulting in a powder keg explosion occurring throughout the summer of 2020 and leading well into 2021. As a result, the United States has deteriorated significantly in the Civil Unrest Index falling from 91st to 34th. The vitriol, polarization, protests, murders, and shootings have all occurred during Gen Z’s formative years, and the limited research available indicates that it has shaped their values and political views. Methodology: The Mid-Atlantic region is a portion of the United States that exists as the overlap between the northeastern and southeastern portions of the country. It includes the nation’s capital, as well as large urban centers, small cities, suburbs, and rural enclaves. It is one of the most socially, economically, racially, and culturally diverse parts of the United States and is often referred to as the “typically American region.” An electronic survey was administered to students from 2019 through 2021 attending a high school dual enrollment program, a minority serving institution, a majority serving institution, and a community college all located within the larger mid-Atlantic region. The survey included a combination of multiple response, Likert scaled, dichotomous, open ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by several content and methodological experts in order to examine bias, vagueness, or potential semantic problems. Finally, the survey was pilot tested prior to implementation in order to explore the efficacy of the research methodology. It was then modified accordingly prior to widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors all of whom are educators. Participation was voluntary, optional, and anonymous. Over 800 individuals completed the survey with just over 700 usable results, after partial completes and the responses of individuals outside of the 18-24 age range were removed. Findings: Participants in this study overwhelmingly were users of social media. In descending order, YouTube, Instagram, Snapchat, Twitter, Facebook, Pinterest, WhatsApp, LinkedIn and Tik Tok were the most popular social media services reported as being used. When volume of use was considered, Instagram, Snapchat, YouTube and Twitter were the most cited with most participants reporting using Instagram and Snapchat multiple times a day. When asked to select which social media service they would use if forced to choose just one, the number one choice was YouTube followed by Instagram and Snapchat. Additionally, more than half of participants responded that they have uploaded a video to a video sharing site such as YouTube or Tik Tok. When asked about their familiarity with different technologies, participants overwhelmingly responded that they are “very familiar” with smart phones, searching the Web, social media, and email. About half the respondents said that they were “very familiar” with common computer applications such as the Microsoft Office Suite or Google Suite with another third saying that they were “somewhat familiar.” When asked about Learning Management Systems (LMS) like Blackboard, Course Compass, Canvas, Edmodo, Moodle, Course Sites, Google Classroom, Mindtap, Schoology, Absorb, D2L, itslearning, Otus, PowerSchool, or WizIQ, only 43% said they were “very familiar” with 31% responding that they were “somewhat familiar.” Finally, about half the students were either “very” or “somewhat” familiar with operating systems such as Windows. A few preferences with respect to technology in the teaching and learning process were explored in the survey. Most students (85%) responded that they want course announcements and reminders sent to their phones, 76% expect their courses to incorporate the use of technology, 71% want their courses to have course websites, and 71% said that they would rather watch a video than read a book chapter. When asked to consider the future, over 81% or respondents reported that technology will play a major role in their future career. Most participants considered themselves “informed” or “well informed” about current events although few considered themselves “very informed” or “well informed” about politics. When asked how they get their news, the most common forum reported for getting news and information about current events and politics was social media with 81% of respondents reporting. Gen Z is known to be an engaged generation and the participants in this study were not an exception. As such, it came as no surprise to discover that, in the past year more than 78% of respondents had educated friends or family about an important social or political issue, about half (48%) had donated to a cause of importance to them, more than a quarter (26%) had participated in a march or rally, and a quarter (26%) had actively boycotted a product or company. Further, about 37% consider themselves to be a social activist with another 41% responding that aren’t sure if they would consider themselves an activist and only 22% saying that they would not consider themselves an activist. When asked what issues were important to them, the most frequently cited were Black Lives Matter (75%), human trafficking (68%), sexual assault/harassment/Me Too (66.49%), gun violence (65.82%), women’s rights (65.15%), climate change (55.4%), immigration reform/deferred action for childhood arrivals (DACA) (48.8%), and LGBTQ+ rights (47.39%). When the schools were compared, there were only minor differences in social media use with the high school students indicating slightly more use of Tik Tok than the other participants. All groups were virtually equal when it came to how informed they perceived themselves about current events and politics. Consensus among groups existed with respect to how they get their news, and the community college and high school students were slightly more likely to have participated in a march, protest, or rally in the last 12 months than the university students. The community college and high school students were also slightly more likely to consider themselves social activists than the participants from either of the universities. When the importance of the issues was considered, significant differences based on institutional type were noted. Black Lives Matter (BLM) was identified as important by the largest portion of students attending the HBCU followed by the community college students and high school students. Less than half of the students attending the TWI considered BLM an important issue. Human trafficking was cited as important by a higher percentage of students attending the HBCU and urban high school than at the suburban and rural community college or the TWI. Sexual assault was considered important by the majority of students at all the schools with the percentage a bit smaller from the majority serving institution. About two thirds of the students at the high school, community college, and HBCU considered gun violence important versus about half the students at the majority serving institution. Women’s rights were reported as being important by more of the high school and HBCU participants than the community college or TWI. Climate change was considered important by about half the students at all schools with a slightly smaller portion reporting out the HBCU. Immigration reform/DACA was reported as important by half the high school, community college, and HBCU participants with only a third of the students from the majority serving institution citing it as an important issue. With respect to LGBTQ rights approximately half of the high school and community college participants cited it as important, 44.53% of the HBCU students, and only about a quarter of the students attending the majority serving institution. Contribution and Conclusion: This paper provides a timely investigation into the mindset of generation Z students living in the United States during a period of heightened civic unrest. This insight is useful to educators who should be informed about the generation of students that is currently populating higher education. The findings of this study are consistent with public opinion polls by Pew Research Center. According to the findings, the Gen Z students participating in this study are heavy users of multiple social media, expect technology to be integrated into teaching and learning, anticipate a future career where technology will play an important role, informed about current and political events, use social media as their main source for getting news and information, and fairly engaged in social activism. When institutional type was compared the students from the university with the more affluent and less diverse population were less likely to find social justice issues important than the other groups. Recommendations for Practitioners: During disruptive and contentious times, it is negligent to think that the abounding issues plaguing society are not important to our students. Gauging the issues of importance and levels of civic engagement provides us crucial information towards understanding the attitudes of students. Further, knowing how our students gain information, their social media usage, as well as how informed they are about current events and political issues can be used to more effectively communicate and educate. Recommendations for Researchers: As social media continues to proliferate daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. Additionally, in other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Impact on Society: During a highly contentious period replete with a large volume of civil unrest and compounded by a global pandemic, understanding the behaviors and attitudes of students can help us as higher education faculty be more attuned when it comes to the design and delivery of curriculum. Future Research This presentation presents preliminary findings. Data is still being collected and much more extensive statistical analyses will be performed.