This document summarizes a research article that proposes a hierarchical fuzzy inference system to analyze transportation experts' subjective opinions on factors influencing median safety. It describes constructing fuzzy membership functions based on literature reviews and experts' judgments to represent how six factors (ADT, median width, etc.) influence safety. A hierarchical structure reduces computational complexity. The system was validated by comparing its fuzzy median safety index values to observed crash data. Results showed indexes increasing exponentially with crash frequency, indicating the system reasonably explains median safety on the roadways studied.
Analyzing Specialized Views of Transportation Under Mean Safety By Using Fuzz...IJERA Editor
Transportation is an essential part in social, industrial and economical process that encounters to the increasing of level of vechile which leads to increasing demand and deterioration of transportation infrastructure as well as others. The transportation expert may be asked to support a decision, determine a preference, rank influencing factors, or assess alternatives through various methods including surveys, interviews, panel meetings, and expert analyses. In many of these cases, before the experts render their opinion they formulate it through the use of linguistic information and their own subjective decision criteria. An efficient method to analyze subjective and linguistic information employed by people, whether expert or layman is to apply a fuzzy set concept. The primary strength of a fuzzy approach is that it is applicable for the analysis of human knowledge and subjective human perception, which are represented by linguistic terms rather than numerical terms, and the deductive process. The fuzzy inference system, which mimics the human perception and decision making processes, is a deductive process of mapping given inputs to certain outputs based on fuzzy membership functions and fuzzy rules. It has been widely applied in various analysis of subjective and ambiguous information.
EVALUATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM IN PREDICTION OF THE CAR ...ijcsa
Road traffic accidents are the most common accidents that annually Endangers lives of many people in the world. Our country Iran is one of the countries with highest incidence and mortality due to accidents that has been introduced. So it’s requires identification of underlay in dimensions in this field. Due to the increasing amount of car accidents in order to increase volume of information related to car accidents and needs to explore and reveal hidden dependencies and very long time among this information. So using traditional methods to discover these complex relations don't response between involved factors and we need to use new techniques. Considering that main aim of this paper is to find best relationship between volumes of information in shortest time. So, in this paper, we classify accidents in West Azerbaijan province in Iran by accident type (damage, injury, death) and we describe it by using Particle Swarm Optimization (PSO) algorithm
BEARINGS PROGNOSTIC USING MIXTURE OF GAUSSIANS HIDDEN MARKOV MODEL AND SUPPOR...IJNSA Journal
Prognostic of future health state relies on the estimation of the Remaining Useful Life (RUL) of physical
systems or components based on their current health state. RUL can be estimated by using three main
approaches: model-based, experience-based and data-driven approaches. This paper deals with a datadriven
prognostics method which is based on the transformation of the data provided by the sensors into
models that are able to characterize the behavior of the degradation of bearings.
For this purpose, we used Support Vector Machine (SVM) as modeling tool. The experiments on the
recently published data base taken from the platform PRONOSTIA clearly show the superiority of the
proposed approach compared to well established method in literature like Mixture of Gaussian Hidden
Markov Models (MoG-HMMs).
An improvement in history based weighted voting algorithm for safety critical...prjpublications
The document discusses a novel history-based weighted voting algorithm for safety-critical systems. It first reviews existing majority and weighted average voting algorithms and their limitations. It then proposes a new algorithm that assigns weights dynamically based on fuzzy logic assessments of module agreement and each module's historical reliability. The algorithm is evaluated experimentally against triple modular redundancy and shown to provide near 100% safety with two error-free modules or better results than existing algorithms with one or multiple errors. It concludes the new approach offers a better compromise between safety and availability for safety-critical applications.
The document discusses approaches for providing accurate and robust traffic forecasts using empirical data. It describes two main types of empirical approaches: basic forecast approaches that use individual prediction models, and combined forecast approaches that combine different forecasts into a single prediction. Basic approaches can be parametric (e.g. linear regression) or non-parametric (e.g. neural networks), while combined approaches aim to improve accuracy by incorporating each model's unique strengths. The document provides an overview of various techniques within each category.
IRJET- Smart Automated Modelling using ECLAT Algorithm for Traffic Accident P...IRJET Journal
This document discusses using the Eclat algorithm and association rule mining to analyze traffic accident data and predict accident patterns. It aims to identify hidden rules between factors influencing accidents. The Eclat algorithm is used to find frequent itemsets in the accident data and determine commonly occurring accident patterns. This allows precautionary measures to be taken to reduce accidents by avoiding frequently occurring patterns. The system was developed and found to effectively identify accident patterns from the data, which can help traffic departments focus on road safety.
Choosing Optimization Process In The Event Of Fligh Plan Interruption With Th...IJESM JOURNAL
In the world today, superior industry is one that makes balance between its capabilities and demands of customer. This requires organization’s knowledge of customer, and their demands. In this research, a process-oriented process was proposed for choosing optimized process by managers of aviation industry in the event of interruption of flight plan. In first stage, interrupting factors of flight plan were described together with solutions to reduce them. Then, effect of each of these factors on interruption as well as on chosen options were collected from experts using paired comparison questionnaires, by geometrical average of combination and the outcomes were analyzed using network analysis process. The results included effect of each factor on interruption of flight plan together with weight of each option for decision making. In the end, based on the obtained results, proper decisions to be adopted in the event of interruption were proposed. This research shows that technical defect and delayed arrival are among the most important interrupting factors of flight plan, and notice of delay, cancellation, and replacement of route were among the most important decision instances faced by managers in aviation industry in the event of interruption of flight.
Analyzing Specialized Views of Transportation Under Mean Safety By Using Fuzz...IJERA Editor
Transportation is an essential part in social, industrial and economical process that encounters to the increasing of level of vechile which leads to increasing demand and deterioration of transportation infrastructure as well as others. The transportation expert may be asked to support a decision, determine a preference, rank influencing factors, or assess alternatives through various methods including surveys, interviews, panel meetings, and expert analyses. In many of these cases, before the experts render their opinion they formulate it through the use of linguistic information and their own subjective decision criteria. An efficient method to analyze subjective and linguistic information employed by people, whether expert or layman is to apply a fuzzy set concept. The primary strength of a fuzzy approach is that it is applicable for the analysis of human knowledge and subjective human perception, which are represented by linguistic terms rather than numerical terms, and the deductive process. The fuzzy inference system, which mimics the human perception and decision making processes, is a deductive process of mapping given inputs to certain outputs based on fuzzy membership functions and fuzzy rules. It has been widely applied in various analysis of subjective and ambiguous information.
EVALUATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM IN PREDICTION OF THE CAR ...ijcsa
Road traffic accidents are the most common accidents that annually Endangers lives of many people in the world. Our country Iran is one of the countries with highest incidence and mortality due to accidents that has been introduced. So it’s requires identification of underlay in dimensions in this field. Due to the increasing amount of car accidents in order to increase volume of information related to car accidents and needs to explore and reveal hidden dependencies and very long time among this information. So using traditional methods to discover these complex relations don't response between involved factors and we need to use new techniques. Considering that main aim of this paper is to find best relationship between volumes of information in shortest time. So, in this paper, we classify accidents in West Azerbaijan province in Iran by accident type (damage, injury, death) and we describe it by using Particle Swarm Optimization (PSO) algorithm
BEARINGS PROGNOSTIC USING MIXTURE OF GAUSSIANS HIDDEN MARKOV MODEL AND SUPPOR...IJNSA Journal
Prognostic of future health state relies on the estimation of the Remaining Useful Life (RUL) of physical
systems or components based on their current health state. RUL can be estimated by using three main
approaches: model-based, experience-based and data-driven approaches. This paper deals with a datadriven
prognostics method which is based on the transformation of the data provided by the sensors into
models that are able to characterize the behavior of the degradation of bearings.
For this purpose, we used Support Vector Machine (SVM) as modeling tool. The experiments on the
recently published data base taken from the platform PRONOSTIA clearly show the superiority of the
proposed approach compared to well established method in literature like Mixture of Gaussian Hidden
Markov Models (MoG-HMMs).
An improvement in history based weighted voting algorithm for safety critical...prjpublications
The document discusses a novel history-based weighted voting algorithm for safety-critical systems. It first reviews existing majority and weighted average voting algorithms and their limitations. It then proposes a new algorithm that assigns weights dynamically based on fuzzy logic assessments of module agreement and each module's historical reliability. The algorithm is evaluated experimentally against triple modular redundancy and shown to provide near 100% safety with two error-free modules or better results than existing algorithms with one or multiple errors. It concludes the new approach offers a better compromise between safety and availability for safety-critical applications.
The document discusses approaches for providing accurate and robust traffic forecasts using empirical data. It describes two main types of empirical approaches: basic forecast approaches that use individual prediction models, and combined forecast approaches that combine different forecasts into a single prediction. Basic approaches can be parametric (e.g. linear regression) or non-parametric (e.g. neural networks), while combined approaches aim to improve accuracy by incorporating each model's unique strengths. The document provides an overview of various techniques within each category.
IRJET- Smart Automated Modelling using ECLAT Algorithm for Traffic Accident P...IRJET Journal
This document discusses using the Eclat algorithm and association rule mining to analyze traffic accident data and predict accident patterns. It aims to identify hidden rules between factors influencing accidents. The Eclat algorithm is used to find frequent itemsets in the accident data and determine commonly occurring accident patterns. This allows precautionary measures to be taken to reduce accidents by avoiding frequently occurring patterns. The system was developed and found to effectively identify accident patterns from the data, which can help traffic departments focus on road safety.
Choosing Optimization Process In The Event Of Fligh Plan Interruption With Th...IJESM JOURNAL
In the world today, superior industry is one that makes balance between its capabilities and demands of customer. This requires organization’s knowledge of customer, and their demands. In this research, a process-oriented process was proposed for choosing optimized process by managers of aviation industry in the event of interruption of flight plan. In first stage, interrupting factors of flight plan were described together with solutions to reduce them. Then, effect of each of these factors on interruption as well as on chosen options were collected from experts using paired comparison questionnaires, by geometrical average of combination and the outcomes were analyzed using network analysis process. The results included effect of each factor on interruption of flight plan together with weight of each option for decision making. In the end, based on the obtained results, proper decisions to be adopted in the event of interruption were proposed. This research shows that technical defect and delayed arrival are among the most important interrupting factors of flight plan, and notice of delay, cancellation, and replacement of route were among the most important decision instances faced by managers in aviation industry in the event of interruption of flight.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses using fuzzy set theory to analyze driver perceptions of service quality from variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on the survey data to appropriately represent the fuzzy perceptions.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses using fuzzy set theory to analyze driver perceptions of variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on survey data distributions and design rules to quantitatively model vague perceptions.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
This document proposes a mobile safety system for automobiles that uses Android operating system. The system has two main components: a safety device and an automobile base unit. The safety device allows users to monitor the vehicle's location on a map, check its status, and control functions remotely. It communicates with the base unit in the vehicle using GPRS. The base unit collects data from sensors, determines the vehicle's GPS location, and can execute control commands like activating the brakes or switching off the engine. The document provides details on the design and algorithms of both components and includes examples of Java code implementation. The goal is to create an intelligent, secure and easy-to-use mobile safety system for vehicles using embedded systems and Android
This document summarizes research on transaction reordering techniques. It discusses transaction reordering approaches based on reducing resource conflicts and increasing resource sharing. Specifically, it covers:
1) A "steal-on-abort" technique that reorders an aborted transaction behind the transaction that caused the abort to avoid repeated conflicts.
2) A replication protocol that attempts to reorder transactions during certification to avoid aborts rather than restarting immediately.
3) Transaction reordering and grouping during continuous data loading to prevent deadlocks when loading data for materialized join views.
Performance measurement of different requirements engineeringiaemedu
This document summarizes a research paper that compares the performance of different requirements engineering (RE) process models. It describes three RE process models - two existing linear models and the authors' iterative model. It also reviews literature on common RE activities and issues with descriptive models not reflecting real-world practices. The authors conducted interviews at two Indian companies to model their RE processes and compare them to the three models. They found the existing linear models did not fully capture the iterative nature of observed RE processes.
Website based patent information searching mechanismiaemedu
This document summarizes a research paper on developing a website-based patent information searching mechanism. It discusses how patent information can be used for technology development, rights acquisition and utilization, and management information. It describes different types of patent searches including novelty, validity, infringement, and state-of-the-art searches. It also evaluates and compares two major patent websites, Delphion and USPTO, in terms of their search capabilities and features.
Revisiting the experiment on detecting of replay and message modificationiaemedu
This document summarizes a research paper that proposes methods for detecting message modification and replay attacks in ad-hoc wireless networks. It begins with background on security issues in wireless networks and types of attacks. It then reviews existing intrusion detection systems and security techniques. Related work that detects attacks using features from the media access control layer or radio frequency fingerprinting is also discussed. The paper aims to present a simple, economical, and platform-independent system for detecting message modification, replay attacks, and unauthorized users in ad-hoc networks.
IRJET- Algorithms for the Prediction of Traffic AccidentsIRJET Journal
This document discusses algorithms for predicting traffic accidents using association rules. It first provides background on studying factors that influence traffic accidents and using data mining approaches like association rules. It then reviews related literature applying decision trees and other algorithms to injury severity prediction. The document proposes a method to calculate minimum support and automatically extract strong association rules from accident data to predict patterns and promote applications in intelligent transportation systems.
Governance of fuzzy systems to predict driver perception of service qualityIAEME Publication
This document discusses using fuzzy set theory to analyze driver perceptions of variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on survey data distributions and design rules to quantitatively model vague perceptions.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses evaluating driver perception of service quality from variable message signs using fuzzy systems. It presents a method using fuzzy set theory and membership functions to quantify subjective human perceptions from survey data. Drivers completed a survey rating their satisfaction with six criteria of VMS quality on linguistic scales. Fuzzy membership functions were constructed to transform the survey responses into fuzzy numbers. Individual perceptions were aggregated using fuzzy arithmetic operations. The final fuzzy set represented the overall group perception, which was defuzzified into a single value indicating satisfaction level considering perception variability and criteria importance. This allowed numerical evaluation of service quality incorporating the complexity of human perception.
IRJET- Road Traffic Prediction using Machine LearningIRJET Journal
This document summarizes a research paper on predicting road traffic using machine learning. The paper aims to develop accurate prediction models using accident data to identify factors that contribute to accidents. This will help develop safety measures to prevent accidents. The paper reviews previous literature on identifying accident-prone locations and factors. It then describes the methodology used, which involves collecting accident data and dividing it into categories based on accident severity. Statistical analysis is performed on the data and results show predictions of accidents in urban, rural and other areas over time. The conclusions are that a broader analysis of more accident factors can improve predictions and help reduce accidents.
Sensor Based Detection & Classification of Actionable & Non-Actionable Condit...IRJET Journal
This document describes a proposed system to detect and classify the conditions of roadways using sensors in smartphones. The system aims to differentiate between actionable obstacles that require maintenance from non-actionable bumps or obstacles. It collects data from smartphone sensors like accelerometers and GPS under precise conditions while the phone is in a moving vehicle. This data is then analyzed using classification algorithms and thresholds to identify anomalous bumps or potholes that require repair. The locations and details of potential issues are stored on a server and displayed to users through a mobile app to help maintain road quality and provide route guidance. The system is intended to leverage daily smartphone use to engage people in contributing to improvements in their local transportation infrastructure.
This document provides a summary of a systematic literature review on behavioral intention to use autonomous vehicles. It reviewed 27 empirical studies on the topic. The review developed a meta-framework called the AV Acceptance Meta-framework (AVAM) that categorizes the antecedents and consequences of behavioral intention to use AVs found in prior research. The review found personality traits like self-efficacy, emotional states, perceptions of AVs, social environment factors, and descriptive variables influence behavioral intention. Few studies examined moderator variables. The review aims to identify gaps in the literature and provide a basis for further empirical research on influential new variables.
IRJET - Predicting Accident Severity using Machine LearningIRJET Journal
This document discusses predicting accident severity using machine learning. It begins with background on the large human and economic toll of road accidents worldwide. It then discusses using machine learning techniques like association rule mining to discover patterns between accident types and injury types in a dataset. Specifically, it uses an unsupervised learning approach with the Eclat algorithm to build a model and identify these patterns from accident records of a particular area. This can help traffic authorities and medical professionals better analyze accidents and injuries.
This document discusses developing a standardized set of indicators and metrics to assess the sustainability of aircraft designs. It proposes indicators within three pillars: environmental, economic, and societal. Potential indicators are identified through literature review. A survey of industry experts is used to validate the indicator set. The survey employs a Delphi method, sending multiple rounds of questionnaires to determine the relative importance of indicators and gather feedback to refine the set. The goal is to allow aircraft designers to quantitatively evaluate sustainability impacts during conceptual design.
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Accident Analysis Models And Methods Guidance For Safety ProfessionalsLeslie Schulte
This document provides an overview of accident analysis models and methods. It discusses three categories of analysis techniques: sequential, epidemiological, and systemic. Sequential techniques view accidents as resulting from time-ordered causal events, but cannot adequately account for organizational and human factors. Epidemiological techniques were developed to consider organizational influences, and view accidents as stemming from latent failures within a system. More recently, systemic techniques have emerged that treat socio-technical systems holistically and focus on the interactions between system components. The document aims to inform readers on different analysis approaches and factors that influence model selection.
The euroFOT project aims to test eight in-vehicle safety systems through field operational tests involving over 1500 drivers. To rigorously and practically evaluate the systems' impacts on safety, efficiency, and the environment, the project developed a methodology balancing experimental methods and real-world testing. This involved defining performance indicators, events, and situational variables for consistent analysis, as well as an experimental design addressing participant selection, study environments, and system exposure conditions. The methodology framework ensures comparable evaluations while allowing flexibility tailored to each field test.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses using fuzzy set theory to analyze driver perceptions of service quality from variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on the survey data to appropriately represent the fuzzy perceptions.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses using fuzzy set theory to analyze driver perceptions of variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on survey data distributions and design rules to quantitatively model vague perceptions.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
This document proposes a mobile safety system for automobiles that uses Android operating system. The system has two main components: a safety device and an automobile base unit. The safety device allows users to monitor the vehicle's location on a map, check its status, and control functions remotely. It communicates with the base unit in the vehicle using GPRS. The base unit collects data from sensors, determines the vehicle's GPS location, and can execute control commands like activating the brakes or switching off the engine. The document provides details on the design and algorithms of both components and includes examples of Java code implementation. The goal is to create an intelligent, secure and easy-to-use mobile safety system for vehicles using embedded systems and Android
This document summarizes research on transaction reordering techniques. It discusses transaction reordering approaches based on reducing resource conflicts and increasing resource sharing. Specifically, it covers:
1) A "steal-on-abort" technique that reorders an aborted transaction behind the transaction that caused the abort to avoid repeated conflicts.
2) A replication protocol that attempts to reorder transactions during certification to avoid aborts rather than restarting immediately.
3) Transaction reordering and grouping during continuous data loading to prevent deadlocks when loading data for materialized join views.
Performance measurement of different requirements engineeringiaemedu
This document summarizes a research paper that compares the performance of different requirements engineering (RE) process models. It describes three RE process models - two existing linear models and the authors' iterative model. It also reviews literature on common RE activities and issues with descriptive models not reflecting real-world practices. The authors conducted interviews at two Indian companies to model their RE processes and compare them to the three models. They found the existing linear models did not fully capture the iterative nature of observed RE processes.
Website based patent information searching mechanismiaemedu
This document summarizes a research paper on developing a website-based patent information searching mechanism. It discusses how patent information can be used for technology development, rights acquisition and utilization, and management information. It describes different types of patent searches including novelty, validity, infringement, and state-of-the-art searches. It also evaluates and compares two major patent websites, Delphion and USPTO, in terms of their search capabilities and features.
Revisiting the experiment on detecting of replay and message modificationiaemedu
This document summarizes a research paper that proposes methods for detecting message modification and replay attacks in ad-hoc wireless networks. It begins with background on security issues in wireless networks and types of attacks. It then reviews existing intrusion detection systems and security techniques. Related work that detects attacks using features from the media access control layer or radio frequency fingerprinting is also discussed. The paper aims to present a simple, economical, and platform-independent system for detecting message modification, replay attacks, and unauthorized users in ad-hoc networks.
IRJET- Algorithms for the Prediction of Traffic AccidentsIRJET Journal
This document discusses algorithms for predicting traffic accidents using association rules. It first provides background on studying factors that influence traffic accidents and using data mining approaches like association rules. It then reviews related literature applying decision trees and other algorithms to injury severity prediction. The document proposes a method to calculate minimum support and automatically extract strong association rules from accident data to predict patterns and promote applications in intelligent transportation systems.
Governance of fuzzy systems to predict driver perception of service qualityIAEME Publication
This document discusses using fuzzy set theory to analyze driver perceptions of variable message signs (VMS). It involves using survey data to develop fuzzy membership functions representing linguistic scales and criteria importance weights. Individual driver perceptions are evaluated using these membership functions. The results are aggregated using fuzzy arithmetic mean and defuzzified to provide an overall service quality measure. Trapezoidal membership functions are constructed based on survey data distributions and design rules to quantitatively model vague perceptions.
Governance of fuzzy systems to predict driver perception of service qualityiaemedu
This document discusses evaluating driver perception of service quality from variable message signs using fuzzy systems. It presents a method using fuzzy set theory and membership functions to quantify subjective human perceptions from survey data. Drivers completed a survey rating their satisfaction with six criteria of VMS quality on linguistic scales. Fuzzy membership functions were constructed to transform the survey responses into fuzzy numbers. Individual perceptions were aggregated using fuzzy arithmetic operations. The final fuzzy set represented the overall group perception, which was defuzzified into a single value indicating satisfaction level considering perception variability and criteria importance. This allowed numerical evaluation of service quality incorporating the complexity of human perception.
IRJET- Road Traffic Prediction using Machine LearningIRJET Journal
This document summarizes a research paper on predicting road traffic using machine learning. The paper aims to develop accurate prediction models using accident data to identify factors that contribute to accidents. This will help develop safety measures to prevent accidents. The paper reviews previous literature on identifying accident-prone locations and factors. It then describes the methodology used, which involves collecting accident data and dividing it into categories based on accident severity. Statistical analysis is performed on the data and results show predictions of accidents in urban, rural and other areas over time. The conclusions are that a broader analysis of more accident factors can improve predictions and help reduce accidents.
Sensor Based Detection & Classification of Actionable & Non-Actionable Condit...IRJET Journal
This document describes a proposed system to detect and classify the conditions of roadways using sensors in smartphones. The system aims to differentiate between actionable obstacles that require maintenance from non-actionable bumps or obstacles. It collects data from smartphone sensors like accelerometers and GPS under precise conditions while the phone is in a moving vehicle. This data is then analyzed using classification algorithms and thresholds to identify anomalous bumps or potholes that require repair. The locations and details of potential issues are stored on a server and displayed to users through a mobile app to help maintain road quality and provide route guidance. The system is intended to leverage daily smartphone use to engage people in contributing to improvements in their local transportation infrastructure.
This document provides a summary of a systematic literature review on behavioral intention to use autonomous vehicles. It reviewed 27 empirical studies on the topic. The review developed a meta-framework called the AV Acceptance Meta-framework (AVAM) that categorizes the antecedents and consequences of behavioral intention to use AVs found in prior research. The review found personality traits like self-efficacy, emotional states, perceptions of AVs, social environment factors, and descriptive variables influence behavioral intention. Few studies examined moderator variables. The review aims to identify gaps in the literature and provide a basis for further empirical research on influential new variables.
IRJET - Predicting Accident Severity using Machine LearningIRJET Journal
This document discusses predicting accident severity using machine learning. It begins with background on the large human and economic toll of road accidents worldwide. It then discusses using machine learning techniques like association rule mining to discover patterns between accident types and injury types in a dataset. Specifically, it uses an unsupervised learning approach with the Eclat algorithm to build a model and identify these patterns from accident records of a particular area. This can help traffic authorities and medical professionals better analyze accidents and injuries.
This document discusses developing a standardized set of indicators and metrics to assess the sustainability of aircraft designs. It proposes indicators within three pillars: environmental, economic, and societal. Potential indicators are identified through literature review. A survey of industry experts is used to validate the indicator set. The survey employs a Delphi method, sending multiple rounds of questionnaires to determine the relative importance of indicators and gather feedback to refine the set. The goal is to allow aircraft designers to quantitatively evaluate sustainability impacts during conceptual design.
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Accident Analysis Models And Methods Guidance For Safety ProfessionalsLeslie Schulte
This document provides an overview of accident analysis models and methods. It discusses three categories of analysis techniques: sequential, epidemiological, and systemic. Sequential techniques view accidents as resulting from time-ordered causal events, but cannot adequately account for organizational and human factors. Epidemiological techniques were developed to consider organizational influences, and view accidents as stemming from latent failures within a system. More recently, systemic techniques have emerged that treat socio-technical systems holistically and focus on the interactions between system components. The document aims to inform readers on different analysis approaches and factors that influence model selection.
The euroFOT project aims to test eight in-vehicle safety systems through field operational tests involving over 1500 drivers. To rigorously and practically evaluate the systems' impacts on safety, efficiency, and the environment, the project developed a methodology balancing experimental methods and real-world testing. This involved defining performance indicators, events, and situational variables for consistent analysis, as well as an experimental design addressing participant selection, study environments, and system exposure conditions. The methodology framework ensures comparable evaluations while allowing flexibility tailored to each field test.
A survey of memory based methods for collaborative filtering based techniquesIAEME Publication
This document summarizes a study that evaluates three collaborative filtering techniques - Euclidean distance, Pearson correlation, and cosine similarity. The study uses a movie rating dataset to calculate similarities between users and generate predictions for unseen movie ratings. The techniques are evaluated by comparing actual ratings to predicted ratings on a test set of 120 movie ratings. The mean absolute error and number of predictions within certain deviation thresholds are used to assess accuracy. The process is repeated three times to arrive at a conclusion on the relative performance of the three similarity measures for collaborative filtering.
This document describes the development and initial validation of the Wheelchair Interface Questionnaire (WIQ), which aims to provide a brief professional assessment of the fit between a wheelchair user and their wheelchair. The WIQ was developed based on a need identified during field studies in Kenya for an outcome measure focused specifically on the user-wheelchair interface. It involves two rounds of online surveys and a focus group with 24 experienced wheelchair professionals to evaluate the face and content validity. Their feedback supported the WIQ as a useful tool that is brief, widely applicable, and provides specific feedback to inform wheelchair modifications. The preliminary studies indicate the WIQ demonstrates initial validity as a method for professionals to assess the user-wheelchair interface.
IRJET- Fuzzy Logic based Route Choice Behaviour ModellingIRJET Journal
This document describes a study that uses fuzzy logic to model route choice behavior in Thrissur City, India. Household surveys were conducted to collect data on travelers' socioeconomic characteristics and their reasons for choosing routes between origin-destination pairs in the city. Fuzzy logic concepts were then used to analyze the data and predict the most chosen routes. The results identified the mostly chosen routes between specific origin zones like Punkunnam and destination zones like Thekkinkadu. Key factors affecting route choice that were identified include travel cost, distance, travel time, and type of employment.
PREDICTING ACCIDENT SEVERITY: AN ANALYSIS OF FACTORS AFFECTING ACCIDENT SEVER...IJCI JOURNAL
Road accidents have significant economic and societal costs, with a small number of severe accidents
accounting for a large portion of these costs. Predicting accident severity can help in the proactive
approach to road safety by identifying potential unsafe road conditions and taking well-informed
actions to reduce the number of severe accidents. This study investigates the effectiveness of the
Random Forest machine learning algorithm for predicting the severity of an accident. The model is
trained on a dataset of accident records from a large metropolitan area and evaluated using various
metrics. Hyperparameters and feature selection are optimized to improve the model's performance.
The results show that the Random Forest model is an effective tool for predicting accident severity with
an accuracy of over 80%. The study also identifies the top six most important variables in the model,
which include wind speed, pressure, humidity, visibility, clear conditions, and cloud cover. The fitted
model has an Area Under the Curve of 80%, a recall of 79.2%, a precision of 97.1%, and an F1 score
of 87.3%. These results suggest that the proposed model has higher performance in explaining the
target variable, which is the accident severity class. Overall, the study provides evidence that the
Random Forest model is a viable and reliable tool for predicting accident severity and can be used to
help reduce the number of fatalities and injuries due to road accidents in the United States.
2023-02-01-A novel Road User Safety Field Theory for traffic safety assessmen...akhileshakm
This document presents a novel Road User Safety Field theory for traffic safety assessment applying video analytics. The theory was developed based on a systematic review of traffic conflict literature and analysis of video data from four intersections. It aims to integrate crash severity estimation and account for heterogeneity in traffic environments and road users. The theory models the risk inherent in interactions between road users, vehicles, and the environment through a risk force that increases with proximity and accounts for change in momentum in a crash. A case study applying the theory to rear-end crash prediction found it significantly better than competing conflict-based models. The theory provides a comprehensive and adaptable method for modeling crash risk across contexts.
Feasibility study of metro transport case study maduraiIAEME Publication
This document discusses a feasibility study for a proposed metro rail system in Madurai, India. It begins with an introduction to feasibility studies and their importance in project development. It then outlines a proposed methodology for conducting feasibility studies for rail projects, covering factors like location assessment, demand analysis, costs, cost-benefit analysis, and social/environmental impacts. The document applies this methodology to the specific case of Madurai, describing the city's traffic issues, proposed metro alignments, and population growth trends. Traffic surveys were conducted at key intersections to analyze existing demand. The study aims to determine if a metro rail system in Madurai would be a feasible and beneficial public transportation solution.
Schwarz et al._2016_The Detection of Visual Distraction using Vehicle and Dri...Julie J. Kang, Ph.D.
This document summarizes a research paper that developed algorithms to detect visual driver distraction using vehicle-based sensors and driver-based head tracking data. Researchers collected driving simulator data from participants performing secondary tasks of varying difficulty levels. They developed machine learning algorithms including Random Forest and Hidden Markov Models to detect distraction. The algorithms were trained on distraction ground truth from an eye tracking system and evaluated on their ability to detect distraction using only vehicle-based and head tracking data. The research aims to help detect distraction in a way that could be implemented in vehicles to warn drivers and enhance safety.
Similar to Prediction of transportation specialized views of median safety (20)
Tech transfer making it as a risk free approach in pharmaceutical and biotech iniaemedu
Tech transfer is a common methodology for transferring new products or an existing
commercial product to R&D or to another manufacturing site. Transferring product knowledge to the
manufacturing floor is crucial and it is an ongoing approach in the pharmaceutical and biotech
industry. Without adopting this process, no company can manufacture its niche products, let alone
market them. Technology transfer is a complicated, process because it is highly cross functional. Due
to its cross functional dependence, these projects face numerous risks and failure. If anidea cannot be
successfully brought out in the form of a product, there is no customer benefit, or satisfaction.
Moreover, high emphasis is in sustaining manufacturing with highest quality each and every time. It
is vital that tech transfer projects need to be executed flawlessly. To accomplish this goal, risk
management is crucial and project team needs to use the risk management approach seamlessly.
Integration of feature sets with machine learning techniquesiaemedu
This document summarizes a research paper that proposes a novel approach for spam filtering using selective feature sets combined with machine learning techniques. The paper presents an algorithm and system architecture that extracts feature sets from emails and uses machine learning to classify emails and generate rules to identify spam. Several metrics are identified to evaluate the efficiency of the feature sets, including false positive rate. An experiment is described that uses keyword lists as feature sets to train filters and compares the proposed approach to other spam filtering methods.
Effective broadcasting in mobile ad hoc networks using gridiaemedu
This document summarizes a research paper that proposes a new grid-based broadcasting mechanism for mobile ad hoc networks. The paper argues that flooding approaches to broadcasting are inefficient and cause network congestion. The proposed approach divides the network into a hierarchical grid structure. When a node needs to broadcast a message, it sends the message to the first node in the appropriate grid, which is then responsible for updating and forwarding the message within that grid. Simulation results showed the grid-based approach outperformed other broadcasting protocols and was more reliable, efficient and scalable.
Effect of scenario environment on the performance of mane ts routingiaemedu
The document analyzes the effect of scenario environment on the performance of the AODV routing protocol in mobile ad hoc networks (MANETs). It studies AODV performance under different scenarios varying network size, maximum node speed, and pause time. The performance is evaluated based on packet delivery ratio, throughput, and end-to-end delay. The results show that AODV performs best in some scenarios and worse in others, indicating that scenario parameters significantly impact routing protocol performance in MANETs.
Adaptive job scheduling with load balancing for workflow applicationiaemedu
This document discusses adaptive job scheduling with load balancing for workflow applications in a grid platform. It begins with an abstract that describes grid computing and how scheduling plays a key role in performance for grid workflow applications. Both static and dynamic scheduling strategies are discussed, but they require high scheduling costs and may not produce good schedules. The paper then proposes a novel semi-dynamic algorithm that allows the schedule to adapt to changes in the dynamic grid environment through both static and dynamic scheduling. Load balancing is incorporated to handle situations where jobs are delayed due to resource fluctuations or overloading of processors. The rest of the paper outlines the related works, proposed scheduling algorithm, system model, and evaluation of the approach.
The document discusses semantic web services and their challenges. It provides an overview of semantic web technologies like WSDL, SOAP, UDDI, and OIL which are used to build semantic web services. The semantic web architecture adds semantics to web services through ontologies written in OWL and DAML+OIL. Key approaches to semantic web services include annotation, composition, and addressing privacy and security. However, semantic web services still face challenges in achieving their full potential due to issues in representation, reasoning, and a lack of real-world applications and data.
1) The document discusses the Cyclic Model Analysis (CMA) technique for sequential pattern mining which aims to predict customer purchasing behavior.
2) CMA calculates the Trend Distribution Function from sequential patterns to model purchasing trends over time. It then uses Generalized Periodicity Detection and Trend Modeling to identify periodic patterns and construct an approximating model.
3) The Cyclic Model Analysis algorithm is applied to further analyze the patterns, dividing the domain into segments where the distribution function is increasing or decreasing and applying the other techniques recursively to fully model the cyclic behavior.
Performance analysis of manet routing protocol in presenceiaemedu
This document analyzes the performance of different routing protocols in a mobile ad hoc network (MANET) under hybrid traffic conditions. It simulates a MANET with 50 nodes moving at speeds up to 20 m/s using the AODV, DSDV, and DSR routing protocols. Traffic included both constant bit rate and variable bit rate sources. Results found that AODV had lower average end-to-end delay and higher packet delivery ratios than DSDV and DSR as the percentage of variable bit rate traffic increased. AODV also performed comparably under both low and high node mobility scenarios with hybrid traffic.
Efficient text compression using special character replacementiaemedu
The document describes a proposed algorithm for efficient text compression using special character replacement and space removal. The algorithm replaces words with non-printable ASCII characters or combinations of characters to compress text files. It uses a dynamic dictionary to map words to their symbols. Spaces are removed from the compressed file in some cases to further reduce file size. Experimental results show the algorithm achieves better compression ratios than LZW, WinZip 10.0 and WinRAR 3.93 for various text file types while allowing lossless decompression.
The document discusses agile programming and proposes a new methodology. It provides an overview of existing agile methodologies like Scrum and Extreme Programming. Scrum uses short sprints to define tasks and deadlines. Extreme Programming focuses on practices like test-first development, pair programming, and continuous integration. The document notes drawbacks like an inability to support large or multi-site projects. It proposes designing a new methodology that combines the advantages of existing methods while overcoming their deficiencies.
Adaptive load balancing techniques in global scale grid environmentiaemedu
The document discusses various adaptive load balancing techniques for distributed applications in grid environments. It first describes adaptive mesh refinement algorithms that partition computational domains using space-filling curves or by distributing grids independently or at different levels. It also discusses dynamic load balancing using tiling and multi-criteria geometric partitioning. The document then covers repartitioning algorithms based on multilevel diffusion and the adaptive characteristics of structured adaptive mesh refinement applications. Finally, it discusses adaptive workload balancing on heterogeneous resources by benchmarking resource characteristics and estimating application parameters to find optimal load distribution.
A survey on the performance of job scheduling in workflow applicationiaemedu
This document summarizes a survey on job scheduling performance in workflow applications on grid platforms. It discusses an adaptive dual objective scheduling (ADOS) algorithm that takes both completion time and resource usage into account for measuring schedule performance. The study shows ADOS delivers good performance in completion time, resource usage, and robustness to changes in resource performance. It also describes the system architecture used, which includes a planner and executor component. The planner focuses on scheduling to minimize completion time while considering resource usage, and can reschedule if needed. The executor enacts the schedule on the grid resources.
A survey of mitigating routing misbehavior in mobile ad hoc networksiaemedu
This document summarizes existing methods to detect misbehavior in mobile ad hoc networks (MANETs). It discusses how routing protocols assume nodes will cooperate fully, but misbehavior like packet dropping can occur. It describes several techniques to detect misbehavior, including watchdog, ACK/SACK, TWOACK, S-TWOACK, and credit-based/reputation-based schemes. Credit-based schemes use virtual currencies to provide incentives for nodes to forward packets, while reputation-based schemes track nodes' past behaviors. The document aims to survey approaches for mitigating the impact of misbehaving nodes in MANET routing.
A novel approach for satellite imagery storage by classifyiaemedu
This document presents a novel approach for classifying and storing satellite imagery by detecting and storing only non-duplicate regions. It uses kernel principal component analysis to reduce the dimensionality and extract features of satellite images. Fuzzy N-means clustering is then used to segment the images into blocks. A duplication detection algorithm compares blocks to identify duplicate and non-duplicate regions. Only the non-duplicate regions are stored in the database, improving storage efficiency and updating speed compared to completely replacing existing images. Support vector machines are used to categorize the non-duplicate blocks into the appropriate classes in the existing images.
A self recovery approach using halftone images for medical imageryiaemedu
This document summarizes a proposed approach for securely transferring medical images over the internet using visual cryptography and halftone images. The approach uses error diffusion techniques to generate a halftone host image from the grayscale medical image. Shadow images are then created from the halftone host image using visual cryptography algorithms. When stacked together, the shadow images reveal the secret medical image. The halftone host image also contains an embedded logo that can be extracted to verify the integrity of the reconstructed image without a trusted third party.
A comprehensive study of non blocking joining techniqueiaemedu
The document discusses and compares various non-blocking joining techniques for databases. It describes 7 different non-blocking joining algorithms: 1) Symmetric hash join, 2) XJoin, 3) Progressive merge join, 4) Hash merge join, 5) Rate based progressive join, 6) Multi-way join, and 7) Early hash join. For each algorithm, it explains the basic approach, memory overflow handling technique, and provides diagrams to illustrate the process. The goal of the paper is to explain and evaluate these non-blocking joining techniques based on factors like execution time, memory usage, I/O complexity, and ability to handle continuous data streams.
A comparative study on multicast routing using dijkstra’siaemedu
This document presents a comparative study of Dijkstra's algorithm, Prim's algorithm, and Ant Colony Systems (ACS) for multicast routing. It describes an example network with 5 nodes and 10 paths and applies each algorithm to find the optimal routing paths. Dijkstra's algorithm is applied to the directed graph and finds the shortest paths from each node. Prim's algorithm is applied to the undirected graph to find the minimum spanning tree. ACS is also applied to the undirected graph using state transition rules and pheromone updating rules to determine paths. The results are analyzed and the computational complexity of each approach is compared.
The detection of routing misbehavior in mobile ad hoc networksiaemedu
This document discusses detecting routing misbehavior in mobile ad hoc networks using the 2ACK scheme with the OLSR protocol. It begins by describing how packet loss can occur in MANETs due to selfish or misbehaving nodes that agree to forward packets but then drop them. It then summarizes existing methods for detecting misbehavior, including credit-based schemes using virtual currencies, reputation-based schemes using watchdog and path rater modules, and end-to-end acknowledgment schemes using ACKs and SACKs. The rest of the document focuses on simulating the 2ACK scheme with OLSR to reduce overhead and packet loss by having receivers acknowledge only a fraction of received packets. The results show this approach reduces packet loss
Visual cryptography scheme for color imagesiaemedu
This document summarizes a research paper on a new visual cryptography scheme for color images. The proposed scheme decomposes a color image into cyan, magenta, and yellow color spaces. Each color channel is then converted to binary using halftoning and shared using a (2,3) visual threshold scheme to generate three image shares. When two or more shares are stacked together, the original color image is revealed without loss of quality, as measured by structural similarity indices near 1. The scheme achieves encryption without increasing image size or bandwidth requirements compared to the original image.
Software process methodologies and a comparative study of various modelsiaemedu
This document provides a summary of different software process methodologies including the waterfall model, iterative model, extreme programming (XP), ISO standards, CMMI, Six Sigma, formal methods, and agile model. It compares these methods and discusses where each is best applied based on factors like project type, risk, and industry. The waterfall model is described as the traditional sequential approach while agile methods embrace adaptive planning and iterative development.