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Articles 80761 - 80790 of 717394
Full-Text Articles in Entire DC Network
Dynamic Tire Response And The Effect On Roughness-Induced Vehicle Energy Dissipation, Gabriela Ann Lukanus
Dynamic Tire Response And The Effect On Roughness-Induced Vehicle Energy Dissipation, Gabriela Ann Lukanus
Master's Theses (2009 -)
Vehicle dynamics models rely on accurate inputs to quantify dynamic loading and energy dissipation to design pavement structures and assess the environmental impacts. The tire’s response to loading is one of the inputs used in these models, and it is typically represented by a linear spring and dashpot connected in parallel. However, tires are made of rubber, a viscoelastic material, so their load response depends on the excitation frequency. Yet, existing models do not incorporate this parameter. This thesis will first examine the load response and its variation with excitation frequency of two truck tires – a dual tire assembly …
Current Vehicle Fleet Inventory And Future Implementation Of A Centralized Electric Fleet At Portland State University, Dane Kovaleski
Current Vehicle Fleet Inventory And Future Implementation Of A Centralized Electric Fleet At Portland State University, Dane Kovaleski
Environmental Science and Management Professional Master's Project Reports
As the effects of climate change continue to impact the world, many institutions have developed climate action goals to reduce their effects on the environment. Portland State University (PSU) has committed to an 80% reduction of greenhouse gas emissions by 2030 and carbon neutrality by 2040. A part of this commitment must include looking at the contributions of transportation on campus to reduce carbon emissions. According to a greenhouse gas emissions report done by the Campus Planning and Sustainability Office in 2016, transportation contributed to 12% of total greenhouse gas emissions on campus.
This project aims to evaluate the management …
The Effectiveness Of Nedam's Constructive Model In Teaching Technology To Develop Productive Thinking Skills And Technological Awareness Among Middle School Students In Palestine, Mohamed S. Sharaf
Journal of Educational and Psychological Studies
The study aimed to reveal the effectiveness of using Needham's Constructivist Model in teaching technology to develop productive thinking skills and technological awareness among middle school students in Palestine. The study followed the semi-experimental approach. In order to achieve these goals, two study tools were prepared, which are a test of productive thinking skills, and a measure of technological awareness. The sample consisted of (90) female students, (45) students for the experimental group, and the other (45) students for the control group, from the ninth grade students at Ramez Fakhira Basic School for Girls. A teachers’ guideline was developed to …
A Dynamical Systems Approach To Characterizing Brain–Body Interactions During Movement: Challenges, Interpretations, And Recommendations, Derek C. Monroe, Nathaniel T. Berry, Peter C. Fino, Christopher K. Rhea
A Dynamical Systems Approach To Characterizing Brain–Body Interactions During Movement: Challenges, Interpretations, And Recommendations, Derek C. Monroe, Nathaniel T. Berry, Peter C. Fino, Christopher K. Rhea
Rehabilitation Sciences Faculty Publications
Brain–body interactions (BBIs) have been the focus of intense scrutiny since the inception of the scientific method, playing a foundational role in the earliest debates over the philosophy of science. Contemporary investigations of BBIs to elucidate the neural principles of motor control have benefited from advances in neuroimaging, device engineering, and signal processing. However, these studies generally suffer from two major limitations. First, they rely on interpretations of ‘brain’ activity that are behavioral in nature, rather than neuroanatomical or biophysical. Second, they employ methodological approaches that are inconsistent with a dynamical systems approach to neuromotor control. These limitations represent a …
A Robotic System For In-Situ Measurement Of Soil Total Carbon And Nitrogen, Husein Harun
A Robotic System For In-Situ Measurement Of Soil Total Carbon And Nitrogen, Husein Harun
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Surges in the cost of fertilizer in recent times coupled with the environmental effects of their over-application have driven the need for farmers to optimize the amount of fertilizer they apply on the farm. One of the key steps in determining the right amount of fertilizer to apply in a given field is measuring the amount of nutrients present in the soil. To ascertain nutrient deficiencies, most farmers perform wet chemistry analysis of soil samples which requires a lot of time and is expensive. In this research project, a robotic system was designed and developed that could autonomously move to …
Dynamic Fallowing In The Middle Rio Grande: A Look At The Environmental Water Leasing Program, Jared Wood
Dynamic Fallowing In The Middle Rio Grande: A Look At The Environmental Water Leasing Program, Jared Wood
Water Resources Professional Project Reports
The Environmental Water Leasing Program (EWLP) is a federally-funded collaborative effort of the Middle Rio Grande Conservancy District and the U.S. Bureau of Reclamation that has paid irrigators in the Middle Rio Grande to temporarily lease water rights and forgo their water use so that it may be used to provide environmental flows for the endangered Rio Grande Silvery Minnow. The program operates in a sometimes socially contentious context, in a region with an overallocated, legally constrained water system, to offer much needed water management flexibility. While dynamic fallowing payments for ecosystem services programs like the EWLP are common policy …
Divine Forgetting And Perfect Being Theology, Christopher Willard-Kyle
Divine Forgetting And Perfect Being Theology, Christopher Willard-Kyle
Faith and Philosophy: Journal of the Society of Christian Philosophers
No abstract provided.
Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein
Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein
All Works
The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone’s life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance …
Applications Of Environmental Dna (Edna) To Detect Subterranean And Aquatic Invasive Species: A Critical Review On The Challenges And Limitations Of Edna Metabarcoding, Sakib Tahmid Rishan, Richard Kline, Md Saydur Rahman
Applications Of Environmental Dna (Edna) To Detect Subterranean And Aquatic Invasive Species: A Critical Review On The Challenges And Limitations Of Edna Metabarcoding, Sakib Tahmid Rishan, Richard Kline, Md Saydur Rahman
School of Earth, Environmental, & Marine Sciences Faculty Publications
The world is struggling to solve a devastating biodiversity loss that not only affects the extinction of treasured species and irreplaceable genetic variation, but also jeopardizes the food production, health, and safety of people. All initiatives aimed to conserve biodiversity rely heavily on the monitoring of both species and populations to get accurate spatial patterns and overall population assessments. Conventional monitoring techniques, such as visual surveys and counting individuals, are problematic due to challenges in identifying cryptic species or immature life stages. Environmental DNA (eDNA) is a relatively new technology that has the potential to be a faster, non-invasive, and …
Operationalizing The Duty Of Care Through Rubrics, Emily Faulconer
Operationalizing The Duty Of Care Through Rubrics, Emily Faulconer
Publications
Laboratory experiments are a key aspect of science education. However, they do have risks, and accidents do happen. Science educators have a duty of care, which includes duty of instruction. One tool that can be leveraged for duty of instruction is course rubrics. Including clear safety criteria in the rubric operationalizes the duty of care and allows students to clearly understand safety expectations and competencies. Specifically, the use of organizing schemes such as RAMP (recognize hazards, assess risks, minimize risks, prepare for emergencies) in rubrics can provide clear communication to students.
Understanding The Role Of External Pull Requests In The Npm Ecosystem, Vittunyuta Maeprasart, Supatsara Wattanakriengkrai, Raula Gaikovina Kula, Christoph Treude, Kenichi Matsumoto
Understanding The Role Of External Pull Requests In The Npm Ecosystem, Vittunyuta Maeprasart, Supatsara Wattanakriengkrai, Raula Gaikovina Kula, Christoph Treude, Kenichi Matsumoto
Research Collection School Of Computing and Information Systems
The risk to using third-party libraries in a software application is that much needed maintenance is solely carried out by library maintainers. These libraries may rely on a core team of maintainers (who might be a single maintainer that is unpaid and overworked) to serve a massive client user-base. On the other hand, being open source has the benefit of receiving contributions (in the form of External PRs) to help fix bugs and add new features. In this paper, we investigate the role by which External PRs (contributions from outside the core team of maintainers) contribute to a library. Through …
The Impact Of A Continuous Integration Service On The Delivery Time Of Merged Pull Requests, João Helis Bernardo, Daniel Alencar Da Costa, Uirá Kulesza, Christoph Treude
The Impact Of A Continuous Integration Service On The Delivery Time Of Merged Pull Requests, João Helis Bernardo, Daniel Alencar Da Costa, Uirá Kulesza, Christoph Treude
Research Collection School Of Computing and Information Systems
Continuous Integration (CI) is a software development practice that builds and tests software frequently (e.g., at every push). One main motivator to adopt CI is the potential to deliver software functionalities more quickly than not using CI. However, there is little empirical evidence to support that CI helps projects deliver software functionalities more quickly. Through the analysis of 162,653 pull requests (PRs) of 87 GitHub projects, we empirically study whether adopting a CI service (TRAVISCI) can quicken the time to deliver merged PRs. We complement our quantitative study by analyzing 450 survey responses from participants of 73 software projects. Our …
Socialz: Multi-Feature Social Fuzz Testing, Francisco Zanartu, Christoph Treude, Markus Wagner
Socialz: Multi-Feature Social Fuzz Testing, Francisco Zanartu, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Online social networks have become an integral aspect of our daily lives and play a crucial role in shaping our relationships with others. However, bugs and glitches, even minor ones, can cause anything from frustrating problems to serious data leaks that can have farreaching impacts on millions of users. To mitigate these risks, fuzz testing, a method of testing with randomised inputs, can provide increased confidence in the correct functioning of a social network. However, implementing traditional fuzz testing methods can be prohibitively difficult or impractical for programmers outside of the network’s development team. To tackle this challenge, we present …
Learning To Ask Clarification Questions With Spatial Reasoning, Yang Deng, Shuaiyi Li, Wai Lam
Learning To Ask Clarification Questions With Spatial Reasoning, Yang Deng, Shuaiyi Li, Wai Lam
Research Collection School Of Computing and Information Systems
Asking clarifying questions has become a key element of various conversational systems, allowing for an effective resolution of ambiguity and uncertainty through natural language questions. Despite the extensive applications of spatial information grounded dialogues, it remains an understudied area on learning to ask clarification questions with the capability of spatial reasoning. In this work, we propose a novel method, named SpatialCQ, for this problem. Specifically, we first align the representation space between textual and spatial information by encoding spatial states with textual descriptions. Then a multi-relational graph is constructed to capture the spatial relations and enable spatial reasoning with relational …
Towards Robust Personalized Dialogue Generation Via Order-Insensitive Representation Regularization, Liang Chen, Hongru Wang, Yang Deng, Wai-Chung Kwan, Zezhong Wang, Kam-Fai Wong
Towards Robust Personalized Dialogue Generation Via Order-Insensitive Representation Regularization, Liang Chen, Hongru Wang, Yang Deng, Wai-Chung Kwan, Zezhong Wang, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Generating persona consistent dialogue response is important for developing an intelligent conversational agent. Recent works typically fine-tune large-scale pre-trained models on this task by concatenating persona texts and dialogue history as a single input sequence to generate the target response. While simple and effective, our analysis shows that this popular practice is seriously affected by order sensitivity where different input orders of persona sentences significantly impact the quality and consistency of generated response, resulting in severe performance fluctuations (i.e., 29.4% on GPT2 and 83.2% on BART). To mitigate the order sensitivity problem, we propose a model-agnostic framework, ORder Insensitive Generation …
Semantic-Based Neural Network Repair, Richard Schumi, Jun Sun
Semantic-Based Neural Network Repair, Richard Schumi, Jun Sun
Research Collection School Of Computing and Information Systems
Recently, neural networks have spread into numerous fields including many safety-critical systems. Neural networks are built (and trained) by programming in frameworks such as TensorFlow and PyTorch. Developers apply a rich set of pre-defined layers to manually program neural networks or to automatically generate them (e.g., through AutoML). Composing neural networks with different layers is error-prone due to the non-trivial constraints that must be satisfied in order to use those layers. In this work, we propose an approach to automatically repair erroneous neural networks. The challenge is in identifying a minimal modification to the network so that it becomes valid. …
Proactive Conversational Agents In The Post-Chatgpt World, Lizi Liao, Grace Hui Yang, Chirag Shah
Proactive Conversational Agents In The Post-Chatgpt World, Lizi Liao, Grace Hui Yang, Chirag Shah
Research Collection School Of Computing and Information Systems
ChatGPT and similar large language model (LLM) based conversational agents have brought shock waves to the research world. Although astonished by their human-like performance, we find they share a significant weakness with many other existing conversational agents in that they all take a passive approach in responding to user queries. This limits their capacity to understand the users and the task better and to offer recommendations based on a broader context than a given conversation. Proactiveness is still missing in these agents, including their ability to initiate a conversation, shift topics, or offer recommendations that take into account a more …
Information Screening Whilst Exploiting! Multimodal Relation Extraction With Feature Denoising And Multimodal Topic Modeling, Shengqiong Wu, Hao Fei, Yixin Cao, Lidong Bing, Tat-Seng Chua
Information Screening Whilst Exploiting! Multimodal Relation Extraction With Feature Denoising And Multimodal Topic Modeling, Shengqiong Wu, Hao Fei, Yixin Cao, Lidong Bing, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Existing research on multimodal relation extraction (MRE) faces two co-existing challenges, internal-information over-utilization and external-information under-exploitation. To combat that, we propose a novel framework that simultaneously implements the idea of internal-information screening and external-information exploiting. First, we represent the fine-grained semantic structures of the input image and text with the visual and textual scene graphs, which are further fused into a unified cross-modal graph (CMG). Based on CMG, we perform structure refinement with the guidance of the graph information bottleneck principle, actively denoising the less-informative features. Next, we perform topic modeling over the input image and text, incorporating latent multimodal …
Few-Shot Event Detection: An Empirical Study And A Unified View, Yubo Ma, Zehao Wang, Yixin Cao, Aixin Sun
Few-Shot Event Detection: An Empirical Study And A Unified View, Yubo Ma, Zehao Wang, Yixin Cao, Aixin Sun
Research Collection School Of Computing and Information Systems
Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e.g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress. This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline. For fair evaluation, we compare 12 representative methods on three datasets, which are roughly grouped into prompt-based and prototype-based models for detailed analysis. Experiments consistently demonstrate that prompt-based methods, including ChatGPT, still significantly trail prototype-based methods in terms of overall performance. To investigate their superior performance, we break down their design elements along …
Context-Aware Neural Fault Localization, Zhuo Zhang, Xiaoguang Mao, Meng Yan, Xin Xia, David Lo, David Lo
Context-Aware Neural Fault Localization, Zhuo Zhang, Xiaoguang Mao, Meng Yan, Xin Xia, David Lo, David Lo
Research Collection School Of Computing and Information Systems
Numerous fault localization techniques identify suspicious statements potentially responsible for program failures by discovering the statistical correlation between test results (i.e., failing or passing) and the executions of the different statements of a program (i.e., covered or not covered). They rarely incorporate a failure context into their suspiciousness evaluation despite the fact that a failure context showing how a failure is produced is useful for analyzing and locating faults. Since a failure context usually contains the transitive relationships among the statements of causing a failure, its relationship complexity becomes one major obstacle for the context incorporation in suspiciousness evaluation of …
Balancing Privacy And Flexibility Of Cloud-Based Personal Health Records Sharing System, Yudi Zhang, Fuchun Guo, Willy Susilo, Guomin Yang
Balancing Privacy And Flexibility Of Cloud-Based Personal Health Records Sharing System, Yudi Zhang, Fuchun Guo, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
The Internet of Things and cloud services have been widely adopted in many applications, and personal health records (PHR) can provide tailored medical care. The PHR data is usually stored on cloud servers for sharing. Weighted attribute-based encryption (ABE) is a practical and flexible technique to protect PHR data. Under a weighted ABE policy, the data user's attributes will be “scored”, if and only if the score reaches the threshold value, he/she can access the data. However, while this approach offers a flexible access policy, the data owners have difficulty controlling their privacy, especially sharing PHR data in collaborative e-health …
Binalign: Alignment Padding Based Compiler Provenance Recovery, Maliha Ismail, Yan Lin, Donggyun Han, Debin Gao
Binalign: Alignment Padding Based Compiler Provenance Recovery, Maliha Ismail, Yan Lin, Donggyun Han, Debin Gao
Research Collection School Of Computing and Information Systems
Compiler provenance is significant in investigating the source-level indicators of binary code, like development-environment, source compiler, and optimization settings. Not only does compiler provenance analysis have important security applications in malware and vulnerability analysis, but it is also very challenging to extract useful artifacts from binary when high-level language constructs are missing. Previous works applied machine-learning techniques to predict the source compiler of binaries. However, most of the work is done on the binaries compiled on Linux operating system. We highlight the importance and need to explore Windows compilers and the complicated binaries compiled on the latest versions of these …
Reducing Spatial Labeling Redundancy For Active Semi-Supervised Crowd Counting, Yongtuo Liu, Sucheng Ren, Liangyu Chai, Hanjie Wu, Dan Xu, Jing Qin, Shengfeng He
Reducing Spatial Labeling Redundancy For Active Semi-Supervised Crowd Counting, Yongtuo Liu, Sucheng Ren, Liangyu Chai, Hanjie Wu, Dan Xu, Jing Qin, Shengfeng He
Research Collection School Of Computing and Information Systems
Labeling is onerous for crowd counting as it should annotate each individual in crowd images. Recently, several methods have been proposed for semi-supervised crowd counting to reduce the labeling efforts. Given a limited labeling budget, they typically select a few crowd images and densely label all individuals in each of them. Despite the promising results, we argue the None-or-All labeling strategy is suboptimal as the densely labeled individuals in each crowd image usually appear similar while the massive unlabeled crowd images may contain entirely diverse individuals. To this end, we propose to break the labeling chain of previous methods and …
Prompt To Be Consistent Is Better Than Self-Consistent? Few-Shot And Zero-Shot Fact Verification With Pre-Trained Language Models, Fengzhu Zeng, Wei Gao
Prompt To Be Consistent Is Better Than Self-Consistent? Few-Shot And Zero-Shot Fact Verification With Pre-Trained Language Models, Fengzhu Zeng, Wei Gao
Research Collection School Of Computing and Information Systems
Few-shot or zero-shot fact verification only relies on a few or no labeled training examples. In this paper, we propose a novel method called ProToCo, to Prompt pre-trained language models (PLMs) To be Consistent, for improving the factuality assessment capability of PLMs in the few-shot and zero-shot settings. Given a claim-evidence pair, ProToCo generates multiple variants of the claim with different relations and frames a simple consistency mechanism as constraints for making compatible predictions across these variants. We update PLMs by using parameter-efficient fine-tuning (PEFT), leading to more accurate predictions in few-shot and zero-shot fact verification tasks. Our experiments on …
Safe Mdp Planning By Learning Temporal Patterns Of Undesirable Trajectories And Averting Negative Side Effects, Siow Meng Low, Akshat Kumar, Scott Sanner
Safe Mdp Planning By Learning Temporal Patterns Of Undesirable Trajectories And Averting Negative Side Effects, Siow Meng Low, Akshat Kumar, Scott Sanner
Research Collection School Of Computing and Information Systems
In safe MDP planning, a cost function based on the current state and action is often used to specify safety aspects. In real world, often the state representation used may lack sufficient fidelity to specify such safety constraints. Operating based on an incomplete model can often produce unintended negative side effects (NSEs). To address these challenges, first, we associate safety signals with state-action trajectories (rather than just immediate state-action). This makes our safety model highly general. We also assume categorical safety labels are given for different trajectories, rather than a numerical cost function, which is harder to specify by the …
Duplicate Bug Report Detection: How Far Are We?, Ting Zhang, Donggyun Han, Venkatesh Vinayakarao, Ivana Clairine Irsan, Bowen Xu, Thung Ferdian, David Lo, Lingxiao Jiang
Duplicate Bug Report Detection: How Far Are We?, Ting Zhang, Donggyun Han, Venkatesh Vinayakarao, Ivana Clairine Irsan, Bowen Xu, Thung Ferdian, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many Duplicate Bug Report Detection (DBRD) techniques have been proposed in the research literature. The industry uses some other techniques. Unfortunately, there is insufficient comparison among them, and it is unclear how far we have been. This work fills this gap by comparing the aforementioned techniques. To compare them, we first need a benchmark that can estimate how a tool would perform if applied in a realistic setting today. Thus, we first investigated potential biases that affect the fair comparison of the accuracy of DBRD techniques. Our experiments suggest that data age and issue tracking system choice cause a significant …
A Data-Driven Approach For Scheduling Bus Services Subject To Demand Constraints, Brahmanage Janaka Chathuranga Thilakarathna, Thivya Kandappu, Baihua Zheng
A Data-Driven Approach For Scheduling Bus Services Subject To Demand Constraints, Brahmanage Janaka Chathuranga Thilakarathna, Thivya Kandappu, Baihua Zheng
Research Collection School Of Computing and Information Systems
Passenger satisfaction is extremely important for the success of a public transportation system. Many studies have shown that passenger satisfaction strongly depends on the time they have to wait at the bus stop (waiting time) to get on a bus. To be specific, user satisfaction drops faster as the waiting time increases. Therefore, service providers want to provide a bus to the waiting passengers within a threshold to keep them satisfied. It is a two-pronged problem: (a) to satisfy more passengers the transport planner may increase the frequency of the buses, and (b) in turn, the increased frequency may impact …
Singapore's Hospital To Home Program: Raising Patient Engagement Through Ai, John Abisheganaden, Kheng Hock Lee, Lian Leng Low, Eugene Shum, Han Leong Goh, Christine Gian Lee Ang, Andy Wee An Ta, Steven M. Miller
Singapore's Hospital To Home Program: Raising Patient Engagement Through Ai, John Abisheganaden, Kheng Hock Lee, Lian Leng Low, Eugene Shum, Han Leong Goh, Christine Gian Lee Ang, Andy Wee An Ta, Steven M. Miller
Research Collection School Of Computing and Information Systems
Because of their complex care needs, many elderly patients are discharged from hospitals only to be readmitted for multiple stays within the following twelve months. John Abisheganaden and his fellow authors describe Singapore’s Hospital to Home program, a community care initiative fueled by artificial intelligence.
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Research Collection School Of Computing and Information Systems
This work concerns the estimation of recursive route choice models in the situation that the trip observations are incomplete, i.e., there are unconnected links (or nodes) in the observations. A direct approach to handle this issue could be intractable because enumerating all paths between unconnected links (or nodes) in a real network is typically not possible. We exploit an expectation–maximization (EM) method that allows dealing with the missing-data issue by alternatively performing two steps of sampling the missing segments in the observations and solving maximum likelihood estimation problems. Moreover, observing that the EM method could be expensive, we propose a …
A Lightweight Privacy-Preserving Path Selection Scheme In Vanets, Guojun Wang, Huijie Yang
A Lightweight Privacy-Preserving Path Selection Scheme In Vanets, Guojun Wang, Huijie Yang
Research Collection School Of Computing and Information Systems
With the rapid development of edge computing, artificial intelligence and other technologies, intelligent transportation services in the vehicular ad hoc networks (VANETs) such as in-vehicle navigation and distress alert are increasingly being widely used in life. Currently, road navigation is an essential service in the vehicle network. However, when a user employs the road navigation service, his private data maybe exposed to roadside nodes. Meanwhile, when the trusted authorization sends the navigation route data to the user, the user can obtain all the road data. Especially, other unrequested data might be related to the military. Therefore, how to achieve secure …