Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549519
Alyssa A. Chisholm, Camrynn L. Genda, Siddhartha Pailla, Jeremy L. Martin, Andrew M. Thrash, Kevin J. Sheehy, G. Louis
Non-governmental organizations (NGOs) around the world are engaged in community development activities to improve access to basic human services, such as water supply and sanitation (WASAN). In spite of their efforts to address critical human needs, a lack of communication between NGOs, the communities they serve, and the agencies that fund them has inhibited widespread efforts or sustained progress. Because the most severely affected communities lack reliable access to the Internet, they cannot use available web-based systems to connect to agents and resources that can help them. Additionally, an effective accountability system that evaluates the performance of NGOs delivering services to communities-in-need does not exist. This capstone project develops a system called DevClear that allows communities-in-need, NGOs, funding agents (FAs), and external service providers (ESPs) to share information about the need for and acquisition of access to WASAN services. DevClear is an SMS-enabled web-based tool that facilitates information sharing between these four major stakeholders. DevClear also includes a simple rating system of NGOs and their respective projects that may serve as an informal accountability system for NGOs. The project's success is measured by; the extent of reach of information, the speed in disseminating the information, the accessibility to the information sharing service by stakeholders, the flexibility in changing and updating the information, and the cost. This paper outlines the approach used to design and develop the system, and describes the frontend design, backend design, SMS functionality, and integration of subsystems into a prototype.
{"title":"DevClear: An information-sharing platform for rural development","authors":"Alyssa A. Chisholm, Camrynn L. Genda, Siddhartha Pailla, Jeremy L. Martin, Andrew M. Thrash, Kevin J. Sheehy, G. Louis","doi":"10.1109/SIEDS.2013.6549519","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549519","url":null,"abstract":"Non-governmental organizations (NGOs) around the world are engaged in community development activities to improve access to basic human services, such as water supply and sanitation (WASAN). In spite of their efforts to address critical human needs, a lack of communication between NGOs, the communities they serve, and the agencies that fund them has inhibited widespread efforts or sustained progress. Because the most severely affected communities lack reliable access to the Internet, they cannot use available web-based systems to connect to agents and resources that can help them. Additionally, an effective accountability system that evaluates the performance of NGOs delivering services to communities-in-need does not exist. This capstone project develops a system called DevClear that allows communities-in-need, NGOs, funding agents (FAs), and external service providers (ESPs) to share information about the need for and acquisition of access to WASAN services. DevClear is an SMS-enabled web-based tool that facilitates information sharing between these four major stakeholders. DevClear also includes a simple rating system of NGOs and their respective projects that may serve as an informal accountability system for NGOs. The project's success is measured by; the extent of reach of information, the speed in disseminating the information, the accessibility to the information sharing service by stakeholders, the flexibility in changing and updating the information, and the cost. This paper outlines the approach used to design and develop the system, and describes the frontend design, backend design, SMS functionality, and integration of subsystems into a prototype.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123160057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549486
J. Pearson, Z. Moore, J. S. Ogdoc, F. J. Choi
Since 2008, the demand for Unmanned Aircraft Systems (UAS) within the National Airspace System (NAS) has more than doubled. The Congressional Mandate of 2012 tasked the Secretary of Transportation to develop a comprehensive plan to safely accelerate the integration of UAS into the NAS by 2014. A major concern with integration is Sense-and-Avoid (SAA) capabilities of UAS. This paper describes the design for the standard for onboard UAS sensors which meet the Target Level of Safety (TLS) of 10-7, or 1 incident in 10,000,000 flight hours, set forth by the Federal Aviation Administration's (FAA) System Safety Handbook (SSH). To successfully perform SAA the RQ-7B Shadow needs a total of 5.73 seconds to detect and maneuver safely to avoid an incident with another aircraft. The hardware to satisfy these design requirements is the POP300D sensor.
{"title":"Design of sense-and-avoid standards for RQ-7B shadow under loss-link","authors":"J. Pearson, Z. Moore, J. S. Ogdoc, F. J. Choi","doi":"10.1109/SIEDS.2013.6549486","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549486","url":null,"abstract":"Since 2008, the demand for Unmanned Aircraft Systems (UAS) within the National Airspace System (NAS) has more than doubled. The Congressional Mandate of 2012 tasked the Secretary of Transportation to develop a comprehensive plan to safely accelerate the integration of UAS into the NAS by 2014. A major concern with integration is Sense-and-Avoid (SAA) capabilities of UAS. This paper describes the design for the standard for onboard UAS sensors which meet the Target Level of Safety (TLS) of 10-7, or 1 incident in 10,000,000 flight hours, set forth by the Federal Aviation Administration's (FAA) System Safety Handbook (SSH). To successfully perform SAA the RQ-7B Shadow needs a total of 5.73 seconds to detect and maneuver safely to avoid an incident with another aircraft. The hardware to satisfy these design requirements is the POP300D sensor.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114134710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549487
Sarah Almujahed, N. Ongor, J. Tigmo, N. Sagoo
From 2006-2012, George Mason University's (GMU) division I men's and women's volleyball teams were outplayed by their top competitors within their associated conference. Analysis of historic data showed that the GMU's men's and women's volleyball teams have a lower probability of scoring points on average of 0.21 and 0.05 respectively. The win/loss outcome is a function of the combinations of sequences of events caused by team's actions and coach's tactics. The data is so complex that no human can comprehensively conduct the analysis. A Computer-Aided Analysis Tool (CAAT) is needed to analyze the underlying trends contributing to the wins and losses as well as provide a meaningful recommendation to improve the overall team performance in a volleyball game. The CAAT determines the probability of each transition that can occur in a volleyball game, uses an Absorbing Markov Chain to evaluate how events influence the point scoring probability, and runs a Monte Carlo Simulation to analyze how random variations in transition probabilities, caused by extreme conditional scenarios can affect the team performance and end result of a game. Four design alternatives were identified through analysis of historic data and evaluated for improving team performance through specific skill improvement training: 1) Increasing aces; 2) Increasing kills; 3) Increasing blocks; 4) Decreasing errors. A utility analysis was conducted to determine the most effective design alternative to achieve the target level of performance. Based on the utility analysis, the GMU's women's and men's teams must focus on increasing their blocks. Out of 10 blocks, at least 9 should lead to a point for the men and 3 should lead to a point for the women in order to achieve the target level of performance.
{"title":"Sports analytics: Designing a volleyball game analysis decision-support tool using big data","authors":"Sarah Almujahed, N. Ongor, J. Tigmo, N. Sagoo","doi":"10.1109/SIEDS.2013.6549487","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549487","url":null,"abstract":"From 2006-2012, George Mason University's (GMU) division I men's and women's volleyball teams were outplayed by their top competitors within their associated conference. Analysis of historic data showed that the GMU's men's and women's volleyball teams have a lower probability of scoring points on average of 0.21 and 0.05 respectively. The win/loss outcome is a function of the combinations of sequences of events caused by team's actions and coach's tactics. The data is so complex that no human can comprehensively conduct the analysis. A Computer-Aided Analysis Tool (CAAT) is needed to analyze the underlying trends contributing to the wins and losses as well as provide a meaningful recommendation to improve the overall team performance in a volleyball game. The CAAT determines the probability of each transition that can occur in a volleyball game, uses an Absorbing Markov Chain to evaluate how events influence the point scoring probability, and runs a Monte Carlo Simulation to analyze how random variations in transition probabilities, caused by extreme conditional scenarios can affect the team performance and end result of a game. Four design alternatives were identified through analysis of historic data and evaluated for improving team performance through specific skill improvement training: 1) Increasing aces; 2) Increasing kills; 3) Increasing blocks; 4) Decreasing errors. A utility analysis was conducted to determine the most effective design alternative to achieve the target level of performance. Based on the utility analysis, the GMU's women's and men's teams must focus on increasing their blocks. Out of 10 blocks, at least 9 should lead to a point for the men and 3 should lead to a point for the women in order to achieve the target level of performance.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116863304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549489
A. Elessawy, G. Singh, J. Singh, K. Zabara
The rise in aviation-related emissions accompanying the increase in demand for air travel is raising concerns about aviation's impact on the climate. There is a growing public interest in climate change issues as a body of activists drives corporations to heed environmental concerns. The Federal Aviation Administration (FAA), the Air Navigation Service Provider (ANSP) for the U.S., controls the transit time for flights in its airspace, which is a major factor that determines the fuel burn and emissions produced. However, the FAA has no current system to estimate emissions from en-route operations, measure performance and set targets for improvement. The purpose of this paper is to provide the U.S. ANSP, the FAA, with a decision support tool to estimate the amount of CO2 emissions produced from en-route flights and analyze alternative routes to increase the ANSP's performance in regard to CO2 taking into consideration the workload of the air traffic controllers. The focus of the analysis is to reduce the flight transit time. The alternatives are Near Wind Optimal Routes (NWORs) for flights in one or more of the four distance categories of the baseline (Flights flying: less than 500, from 500 to 999, from 1000 to 1500 and greater than 1500 nautical miles). The tool, Aircraft Emissions Decision Support Tool (AEDST), is a deterministic model developed to calculate the fuel burn and emissions for any aircraft given the 4-D trajectory data (longitude, latitude, altitude, velocity, time) and the fuel burn rate per unit time at different phases of the flight. The Future Air Traffic Management Concepts Evaluation Tool (FACET) was used to calculate the number of conflicts between flights, which represent the air traffic controllers' workload. The results show the improvement in the ANSP's performance by implementing NWORs for flight distances less than 1500 nautical miles by 19%, which provide the airlines with approximately $16M in fuel savings. Implementing those routes also reduces the workload of air traffic controllers by 2.5%.
{"title":"Corporate responsibility for the U.S. Air Navigation Service Provider: A decision support tool to reduce CO2 emissions from en-route flights","authors":"A. Elessawy, G. Singh, J. Singh, K. Zabara","doi":"10.1109/SIEDS.2013.6549489","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549489","url":null,"abstract":"The rise in aviation-related emissions accompanying the increase in demand for air travel is raising concerns about aviation's impact on the climate. There is a growing public interest in climate change issues as a body of activists drives corporations to heed environmental concerns. The Federal Aviation Administration (FAA), the Air Navigation Service Provider (ANSP) for the U.S., controls the transit time for flights in its airspace, which is a major factor that determines the fuel burn and emissions produced. However, the FAA has no current system to estimate emissions from en-route operations, measure performance and set targets for improvement. The purpose of this paper is to provide the U.S. ANSP, the FAA, with a decision support tool to estimate the amount of CO2 emissions produced from en-route flights and analyze alternative routes to increase the ANSP's performance in regard to CO2 taking into consideration the workload of the air traffic controllers. The focus of the analysis is to reduce the flight transit time. The alternatives are Near Wind Optimal Routes (NWORs) for flights in one or more of the four distance categories of the baseline (Flights flying: less than 500, from 500 to 999, from 1000 to 1500 and greater than 1500 nautical miles). The tool, Aircraft Emissions Decision Support Tool (AEDST), is a deterministic model developed to calculate the fuel burn and emissions for any aircraft given the 4-D trajectory data (longitude, latitude, altitude, velocity, time) and the fuel burn rate per unit time at different phases of the flight. The Future Air Traffic Management Concepts Evaluation Tool (FACET) was used to calculate the number of conflicts between flights, which represent the air traffic controllers' workload. The results show the improvement in the ANSP's performance by implementing NWORs for flight distances less than 1500 nautical miles by 19%, which provide the airlines with approximately $16M in fuel savings. Implementing those routes also reduces the workload of air traffic controllers by 2.5%.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124611304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549512
T. W. Bernica, V. Guarino, A. Han, L. F. Hennet, M. Mitchell, M. Gerber, D. Brown
Given that many of the U.S. Military's current conflicts involve insurgent groups, it is critical that the military understands the nature, motivations, and workings of these non-traditional forces. Many models have attempted to predict successful insurgent conflicts; however, most fail to incorporate the different types of factors collectively, namely: political, geographic, social, economic and cultural. With the creation of a model that incorporates all of these factors, predicting the success of an insurgent group before they gain influence will become a more attainable pursuit. We focused on researching past insurgencies to identify factors that lead to their successes or failures in gaining influence. Once the historical conflict data was compiled, we used the information to train and test statistical models to predict the success or failure of future insurgent conflicts. Our results indicate that certain factors have a strong correlation with the success and failure of an insurgent conflict. For historical conflicts in the testing set, the model accurately predicted the outcome of the conflict 27 out of 36 times. We discuss our data collection and modeling work in detail and offer insights into future work in this area.
{"title":"Analysis and prediction of insurgent influence for U.S. military strategy","authors":"T. W. Bernica, V. Guarino, A. Han, L. F. Hennet, M. Mitchell, M. Gerber, D. Brown","doi":"10.1109/SIEDS.2013.6549512","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549512","url":null,"abstract":"Given that many of the U.S. Military's current conflicts involve insurgent groups, it is critical that the military understands the nature, motivations, and workings of these non-traditional forces. Many models have attempted to predict successful insurgent conflicts; however, most fail to incorporate the different types of factors collectively, namely: political, geographic, social, economic and cultural. With the creation of a model that incorporates all of these factors, predicting the success of an insurgent group before they gain influence will become a more attainable pursuit. We focused on researching past insurgencies to identify factors that lead to their successes or failures in gaining influence. Once the historical conflict data was compiled, we used the information to train and test statistical models to predict the success or failure of future insurgent conflicts. Our results indicate that certain factors have a strong correlation with the success and failure of an insurgent conflict. For historical conflicts in the testing set, the model accurately predicted the outcome of the conflict 27 out of 36 times. We discuss our data collection and modeling work in detail and offer insights into future work in this area.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116352991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549496
H. Pangborn, S. Brennan, K. Reichard
To investigate the standardization of ground robot endurance as defined by the National Institute of Standard and Technology (NIST), this paper presents the development and applications of a novel robot tracking system that uses three overhead cameras to record the number of laps and the distance traveled by a robot over the duration of a test. The computer algorithms employed perform four primary functions: 1) image acquisition and correction for camera barrel distortion, 2) localization of the robot through fiducial identification, 3) lap counting between user-defined “end-zones,” and 4) conversion of the path traversed from pixels to real-world distances via user-conducted calibrations. Analyses of the precision and accuracy of this system and expected sources of error are provided. Two applications relevant to robot endurance are discussed using data from three separate testing events. The first evaluation is the consistency of laps completed (the current NIST method of estimating the distance traversed), comparing distance and time across different robots and operators. The second evaluation considers trends in operator performance over time for the duration of a test.
{"title":"Development and applications of a robot tracking system for NIST test methods","authors":"H. Pangborn, S. Brennan, K. Reichard","doi":"10.1109/SIEDS.2013.6549496","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549496","url":null,"abstract":"To investigate the standardization of ground robot endurance as defined by the National Institute of Standard and Technology (NIST), this paper presents the development and applications of a novel robot tracking system that uses three overhead cameras to record the number of laps and the distance traveled by a robot over the duration of a test. The computer algorithms employed perform four primary functions: 1) image acquisition and correction for camera barrel distortion, 2) localization of the robot through fiducial identification, 3) lap counting between user-defined “end-zones,” and 4) conversion of the path traversed from pixels to real-world distances via user-conducted calibrations. Analyses of the precision and accuracy of this system and expected sources of error are provided. Two applications relevant to robot endurance are discussed using data from three separate testing events. The first evaluation is the consistency of laps completed (the current NIST method of estimating the distance traversed), comparing distance and time across different robots and operators. The second evaluation considers trends in operator performance over time for the duration of a test.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122716468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549511
J. Talbot, W. Weber, M. Myers, E. Wangerin, J. Lunsford, W. Scherer
Videology is an online advertising company with a targeted advertising platform that more efficiently connects brands with target consumers. By obtaining and utilizing user data, advertisers have targeted specific groups through a process known as behavioral targeting. This process increases the odds that a user will click on an advertisement and reduces the odds that a customer will encounter irrelevant advertisements. While Videology has grown their market share in this space, inefficient forecasts have cost several hundred thousand dollars in lost opportunity costs. This paper addresses this problem by leveraging a systems engineering approach to suggest procedures for optimizing the validity and performance of two forecast variables for Videology. The paper first analyzes a volume forecast variable: the expected number of visitors, and second, a frequency forecast variable: the number of times a visitor comes back to the same website. Research used existing data to construct a pseudo-process to replicate Videology's algorithm in order to test the validity of and make enhancements to forecasts. Videology will then utilize findings from this process to continue forecast improvements.
{"title":"Optimizing volume and frequency forecasts for an online video advertiser","authors":"J. Talbot, W. Weber, M. Myers, E. Wangerin, J. Lunsford, W. Scherer","doi":"10.1109/SIEDS.2013.6549511","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549511","url":null,"abstract":"Videology is an online advertising company with a targeted advertising platform that more efficiently connects brands with target consumers. By obtaining and utilizing user data, advertisers have targeted specific groups through a process known as behavioral targeting. This process increases the odds that a user will click on an advertisement and reduces the odds that a customer will encounter irrelevant advertisements. While Videology has grown their market share in this space, inefficient forecasts have cost several hundred thousand dollars in lost opportunity costs. This paper addresses this problem by leveraging a systems engineering approach to suggest procedures for optimizing the validity and performance of two forecast variables for Videology. The paper first analyzes a volume forecast variable: the expected number of visitors, and second, a frequency forecast variable: the number of times a visitor comes back to the same website. Research used existing data to construct a pseudo-process to replicate Videology's algorithm in order to test the validity of and make enhancements to forecasts. Videology will then utilize findings from this process to continue forecast improvements.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116656907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549492
K. Yu, R. Tan, J. Santos
Natural disasters cause unexpected disruptions to the flow of goods and services in an economy. These disruptions may affect production in a single sector but sector interdependence guarantees that this will trickle down to other sectors, leading to increased damages. This study seeks to provide an estimate of the impact of a disruption in the transportation sector in the largest island in the Philippines and its ripple effects. Through the inoperability input-output model (IIM), the degree of failure in a system can be quantified on a scale from 0 (normal state) to 1 (complete failure). Inoperability is initially measured for the transportation sector based on estimates from the World Bank coupled with region-specific input-output data to forecast the ripple effects to other sectors in the economy. Aside from inoperability, economic loss is also assessed. Sensitivity analysis is implemented to capture the uncertainties relating to varying magnitudes of transportation disruptions and associated recovery horizons. Results show that the sectors that were strongly affected, both in terms of inoperability and economic loss are mainly manufacturing, agriculture and private services. Nevertheless, slight divergence in other sectors may be observed. While this study focuses on a static estimation, dynamic extensions introducing time-varying perturbations on the transportation, and multi-sector disruptions may be explored.
{"title":"Impact estimation of flooding in Manila: An inoperability input-output approach","authors":"K. Yu, R. Tan, J. Santos","doi":"10.1109/SIEDS.2013.6549492","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549492","url":null,"abstract":"Natural disasters cause unexpected disruptions to the flow of goods and services in an economy. These disruptions may affect production in a single sector but sector interdependence guarantees that this will trickle down to other sectors, leading to increased damages. This study seeks to provide an estimate of the impact of a disruption in the transportation sector in the largest island in the Philippines and its ripple effects. Through the inoperability input-output model (IIM), the degree of failure in a system can be quantified on a scale from 0 (normal state) to 1 (complete failure). Inoperability is initially measured for the transportation sector based on estimates from the World Bank coupled with region-specific input-output data to forecast the ripple effects to other sectors in the economy. Aside from inoperability, economic loss is also assessed. Sensitivity analysis is implemented to capture the uncertainties relating to varying magnitudes of transportation disruptions and associated recovery horizons. Results show that the sectors that were strongly affected, both in terms of inoperability and economic loss are mainly manufacturing, agriculture and private services. Nevertheless, slight divergence in other sectors may be observed. While this study focuses on a static estimation, dynamic extensions introducing time-varying perturbations on the transportation, and multi-sector disruptions may be explored.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126130675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549488
A. E. Cheytanov, N. R. Bales, P. Khanna, C. Swift
U.S. energy prices have risen by 51% over the last two decades. Buildings account for 39% of the total energy consumption in the United States. The Federal Government is a significant user of commercial buildings and can save money, improve the environment, and stimulate the green technology sector by migrating to sustainable facilities. The 2009 Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance, set a goal for all federal agencies to make 15% of their buildings High Performance Sustainable Buildings (HPSB) by 2015. The Federal Aviation Administration (FAA), which operates over 700 buildings, must convert 15 of its 126 directly leased buildings into HPSB within its existing budget resources. The FAA is currently leasing its building on rent cost per square foot and not Life Cycle Costs (LCCs). This is comparable to buying a car solely based on the sticker price to cargo capacity ratio. There are many more costs to consider over the length of ownership of a car, such as fuel economy, passenger capacity, and maintenance costs. One way for the FAA to meet the target in the existing budget is to incorporate LCC practices in the lease acquisition process. This way buildings are evaluated based on operational costs incurred over the entire lease term to yield net savings. To evaluate potential savings, an LCC Lease Analysis (LCCLA) decision support tool has been developed to assess leasing options factoring energy and water cost fluctuations for specific buildings in the FAA database. The tool includes three leasing strategies: (1) renewing the existing lease-this option will not help the FAA achieve the E.O.13514; (2) renovating the buildings to meet HPSB standards-the FAA may incur a higher rent, but will be able to satisfy E.0.13514; and (3) relocating the employees to a building that already satisfies E.O.13514. To generate accurate LCCLA results, surrogate data was used to analyze relationships between number of employees per building, cost per square foot, climate zones, and energy costs with respect to lease term, inflation, and energy costs projections. The analysis has identified fifteen buildings showing either a positive savings, net zero financial impact, or lowest costs. All but one of these buildings is less than 25000 square feet. This is a result of the lower cost of renovating smaller buildings. The analysis also reveals that full service leases do not allow the FAA to reap the benefits of the green technology. Since the responsibility of paying utilities falls to the lessor, the lessor is in a position to charge a premium rent to cover the stochastic energy costs. If those costs are actually less than what was negotiated, the lessor can pocket the difference. Partial service leases give finer control over money for utility bills. This method of leasing also has the capability of giving immediate feedback as to the performance of the efficiency of the building.
{"title":"A decision support tool for building leasing strategies to achieve the executive order mandate for federal government green buildings","authors":"A. E. Cheytanov, N. R. Bales, P. Khanna, C. Swift","doi":"10.1109/SIEDS.2013.6549488","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549488","url":null,"abstract":"U.S. energy prices have risen by 51% over the last two decades. Buildings account for 39% of the total energy consumption in the United States. The Federal Government is a significant user of commercial buildings and can save money, improve the environment, and stimulate the green technology sector by migrating to sustainable facilities. The 2009 Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance, set a goal for all federal agencies to make 15% of their buildings High Performance Sustainable Buildings (HPSB) by 2015. The Federal Aviation Administration (FAA), which operates over 700 buildings, must convert 15 of its 126 directly leased buildings into HPSB within its existing budget resources. The FAA is currently leasing its building on rent cost per square foot and not Life Cycle Costs (LCCs). This is comparable to buying a car solely based on the sticker price to cargo capacity ratio. There are many more costs to consider over the length of ownership of a car, such as fuel economy, passenger capacity, and maintenance costs. One way for the FAA to meet the target in the existing budget is to incorporate LCC practices in the lease acquisition process. This way buildings are evaluated based on operational costs incurred over the entire lease term to yield net savings. To evaluate potential savings, an LCC Lease Analysis (LCCLA) decision support tool has been developed to assess leasing options factoring energy and water cost fluctuations for specific buildings in the FAA database. The tool includes three leasing strategies: (1) renewing the existing lease-this option will not help the FAA achieve the E.O.13514; (2) renovating the buildings to meet HPSB standards-the FAA may incur a higher rent, but will be able to satisfy E.0.13514; and (3) relocating the employees to a building that already satisfies E.O.13514. To generate accurate LCCLA results, surrogate data was used to analyze relationships between number of employees per building, cost per square foot, climate zones, and energy costs with respect to lease term, inflation, and energy costs projections. The analysis has identified fifteen buildings showing either a positive savings, net zero financial impact, or lowest costs. All but one of these buildings is less than 25000 square feet. This is a result of the lower cost of renovating smaller buildings. The analysis also reveals that full service leases do not allow the FAA to reap the benefits of the green technology. Since the responsibility of paying utilities falls to the lessor, the lessor is in a position to charge a premium rent to cover the stochastic energy costs. If those costs are actually less than what was negotiated, the lessor can pocket the difference. Partial service leases give finer control over money for utility bills. This method of leasing also has the capability of giving immediate feedback as to the performance of the efficiency of the building.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116586869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-04-26DOI: 10.1109/SIEDS.2013.6549493
M. Mackrell, K. Twilley, W. Kirk, L. Q. Lu, J. L. Underhill, L. Barnes
The world's interconnected data assets provide rapid options for individuals looking to communicate and retrieve information, which is especially critical in times of emergency. The ability for populations to get in touch with emergency responders, loved-ones, and retrieve or disseminate critical information about events as they unfold translates into better survivability in the face of crisis. Although telecommunication infrastructures are incapacitated and millions of people experienced hindered Internet access, mobile phone usage soars as people access wireless networks to communicate and seek information regarding an event such as a natural disaster. The demands for communication and information during crisis events distinctly differ from the typical data loads seen during normal operation in both traffic and content. Detecting the anomalies in network traffic data that occur during disruptive events such as earthquakes, hurricanes, and political uprisings can provide potential aid to first responders and be a potentially useful public surveillance tool. Utilizing historic data on network activity and content, a system for assessing the range, intensity, and category of a disruptive event is designed. Systems such as the one described in this manuscript, will detect changes in network traffic caused by disruptive events in real-time.
{"title":"Discovering anomalous patterns in network traffic data during Crisis Events","authors":"M. Mackrell, K. Twilley, W. Kirk, L. Q. Lu, J. L. Underhill, L. Barnes","doi":"10.1109/SIEDS.2013.6549493","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549493","url":null,"abstract":"The world's interconnected data assets provide rapid options for individuals looking to communicate and retrieve information, which is especially critical in times of emergency. The ability for populations to get in touch with emergency responders, loved-ones, and retrieve or disseminate critical information about events as they unfold translates into better survivability in the face of crisis. Although telecommunication infrastructures are incapacitated and millions of people experienced hindered Internet access, mobile phone usage soars as people access wireless networks to communicate and seek information regarding an event such as a natural disaster. The demands for communication and information during crisis events distinctly differ from the typical data loads seen during normal operation in both traffic and content. Detecting the anomalies in network traffic data that occur during disruptive events such as earthquakes, hurricanes, and political uprisings can provide potential aid to first responders and be a potentially useful public surveillance tool. Utilizing historic data on network activity and content, a system for assessing the range, intensity, and category of a disruptive event is designed. Systems such as the one described in this manuscript, will detect changes in network traffic caused by disruptive events in real-time.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126940971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：