4,039 research outputs found

    Mobile forensic triage for damaged phones using M_Triage

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    Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool

    Mobile forensic triage for damaged phones using M_Triage

    Get PDF
    Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool

    Sensor-based navigating mobile robots for people with disabilities

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    People with severe physical disabilities need help with everyday tasks, such as getting dressed, eating, brushing their teeth, scratching themselves, drinking, etc. They also need support to be able to work. They are usually helped by one or more persona

    AMTV headway sensor and safety design

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    A headway sensing system for an automated mixed traffic vehicle (AMTV) employing an array of optical proximity sensor elements is described, and its performance is presented in terms of object detection profiles. The problem of sensing in turns is explored experimentally and requirements for future turn sensors are discussed. A recommended headway sensor configuration, employing multiple source elements in the focal plane of one lens operating together with a similar detector unit, is described. Alternative concepts including laser radar, ultrasonic sensing, imaging techniques, and radar are compared to the present proximity sensor approach. Design concepts for an AMTV body which will minimize the probability of injury to pedestrians or passengers in the event of a collision are presented

    DEVELOPMENT OF A NOVEL VEHICLE GUIDANCE SYSTEM: VEHICLE RISK MITIGATION AND CONTROL

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    Over a half of fatal vehicular crashes occur due to vehicles leaving their designated travel lane and entering other lanes or leaving the roadway. Lane departure accidents also result in billions of dollars in cost to society. Recent vehicle technology research into driver assistance and vehicle autonomy has developed to assume various driving tasks. However, these systems are do not work for all roads and travel conditions. The purpose of this research study was to begin the development a novel vehicle guidance approach, specifically studying how the vehicle interacts with the system to detect departures and control the vehicle A literature review was conducted, covering topics such as vehicle sensors, control methods, environment recognition, driver assistance methods, vehicle autonomy methods, communication, positioning, and regulations. Researchers identified environment independence, recognition accuracy, computational load, and industry collaboration as areas of need in intelligent transportation. A novel method of vehicle guidance was conceptualized known as the MwRSF Smart Barrier. The vision of this method is to send verified road path data, based AASHTO design and vehicle dynamic aspects, to guide the vehicle. To further development research was done to determine various aspects of vehicle dynamics and trajectory trends can be used to predict departures and control the vehicle. Tire-to-road friction capacity and roll stability were identified as traits that can be prevented with future road path knowledge. Road departure characteristics were mathematically developed. It was shown that lateral departure, orientation error, and curvature error are parametrically linked, and discussion was given for these metrics as the basis for of departure prediction. A three parallel PID controller for modulating vehicle steering inputs to a virtual vehicle to remain on the path was developed. The controller was informed by a matrix of XY road coordinates, road curvature and future road curvature and was able to keep the simulated vehicle to within 1 in of the centerline target path. Recommendations were made for the creation of warning modules, threshold levels, improvements to be applied to vehicle controller, and ultimately full-scale testing. Advisor: Cody S. Stoll

    Development of rear-end collision avoidance in automobiles

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    The goal of this work is to develop a Rear-End Collision Avoidance System for automobiles. In order to develop the Rear-end Collision Avoidance System, it is stated that the most important difference from the old practice is the fact that new design approach attempts to completely avoid collision instead of minimizing the damage by over-designing cars. Rear-end collisions are the third highest cause of multiple vehicle fatalities in the U.S. Their cause seems to be a result of poor driver awareness and communication. For example, car brake lights illuminate exactly the same whether the car is slowing, stopping or the driver is simply resting his foot on the pedal. In the development of Rear-End Collision Avoidance System (RECAS), a thorough review of hardware, software, driver/human factors, and current rear-end collision avoidance systems are included. Key sensor technologies are identified and reviewed in an attempt to ease the design effort. The characteristics and capabilities of alternative and emerging sensor technologies are also described and their performance compared. In designing a RECAS the first component is to monitor the distance and speed of the car ahead. If an unsafe condition is detected a warning is issued and the vehicle is decelerated (if necessary). The second component in the design effort utilizes the illumination of independent segments of brake lights corresponding to the stopping condition of the car. This communicates the stopping intensity to the following driver. The RECAS is designed the using the LabVIEW software. The simulation is designed to meet several criteria: System warnings should result in a minimum load on driver attention, and the system should also perform well in a variety of driving conditions. In order to illustrate and test the proposed RECAS methods, a Java program has been developed. This simulation animates a multi-car, multi-lane highway environment where car speeds are assigned randomly, and the proposed RECAS approaches demonstrate rear-end collision avoidance successfully. The Java simulation is an applet, which is easily accessible through the World Wide Web and also can be tested for different angles of the sensor

    Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 159

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    This bibliography lists 257 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1976

    Technology utilization program report, 1974

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    The adaptation of various technological innovations from the NASA space program to industrial and domestic applications is summarized
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