In view of the inherent defects in current airport surface surveillance system, this paper
proposes an asynchronous target-perceiving-event driven surface target surveillance scheme
based on the geomagnetic sensor technology. Furthermore, a surface target tracking and
prediction algorithm based on I-IMM is given, which is improved on the basis of IMM
algorithm in the following aspects: Weighted sum is performed on the mean of residual errors
and model probabilistic likelihood function is reconstructed, thus increasing the identification
of a true motion model; Fixed model transition probability is updated with model posterior
information, thus accelerating model switching as well as increasing the identification of a
model. In the period when a target is non-perceptible, prediction of target trajectories can be
implemented through the target motion model identified with I-IMM algorithm. Simulation
results indicate that I-IMM algorithm is more effective and advantageous in comparison with
the standard IMM algorithm.
Waypoint Flight Parameter Comparison of an Autonomous Uavijaia
The present paper compares the effect of different waypoint parameters on the flight performance of a
special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical
sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for
reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters
on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the
acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus
influence the performance of the presented autonomous quadrocopter under real indoor navigation
circumstances. Furthermore the paper demonstrates a drawback of the standard potential field method for
navigation of such autonomous quadrocopters and points to an improvement
Automatic Landing of a UAV Using Model Predictive Control for the Surveillanc...AM Publications
The objective of this paper is to provide safe landing of an UAV on any demanding conditions and can be very useful during the period of floods, rescuing the affected people. It can be also be useful in military operations. This system provides stable method for landing of an aircraft. Image processing technique is used to capture the image and find the angle of inclinations. MATLAB produces four types of image through Image processing technique. They are Gray image, Edge Detection image, Histogram image, object detection image. MATLAB sends the histogram signal to microcontroller using UART. It is used to convert the received parallel data into serial data for transmitting the data to longer distance. Relay drives the DC motor. Angle of inclinations is measured according to the detected image of the surface. MATLAB produces the total inclination value of the surface. DC motor automatically adjusts the landing gear according to the obtained input inclination value of the surface. An UAV is programmed to adjust the landing gear according to angle of inclination. When the landing surface is detected for landing the aircraft, it automatically adjusts the landing gear and lands the aircraft according to the inclined surface of the landing area.
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 Computational Engineering Research (IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Waypoint Flight Parameter Comparison of an Autonomous Uavijaia
The present paper compares the effect of different waypoint parameters on the flight performance of a
special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical
sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for
reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters
on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the
acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus
influence the performance of the presented autonomous quadrocopter under real indoor navigation
circumstances. Furthermore the paper demonstrates a drawback of the standard potential field method for
navigation of such autonomous quadrocopters and points to an improvement
Automatic Landing of a UAV Using Model Predictive Control for the Surveillanc...AM Publications
The objective of this paper is to provide safe landing of an UAV on any demanding conditions and can be very useful during the period of floods, rescuing the affected people. It can be also be useful in military operations. This system provides stable method for landing of an aircraft. Image processing technique is used to capture the image and find the angle of inclinations. MATLAB produces four types of image through Image processing technique. They are Gray image, Edge Detection image, Histogram image, object detection image. MATLAB sends the histogram signal to microcontroller using UART. It is used to convert the received parallel data into serial data for transmitting the data to longer distance. Relay drives the DC motor. Angle of inclinations is measured according to the detected image of the surface. MATLAB produces the total inclination value of the surface. DC motor automatically adjusts the landing gear according to the obtained input inclination value of the surface. An UAV is programmed to adjust the landing gear according to angle of inclination. When the landing surface is detected for landing the aircraft, it automatically adjusts the landing gear and lands the aircraft according to the inclined surface of the landing area.
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 Computational Engineering Research (IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Photogrammetry Surveying, its Benefits & DrawbacksNI BT
Learn the Photogrammetry Surveying and benefits-drawbacks of photogrammetry. Photogrammetry is the process of generating a 3D model from a set of 2D photographs. In Surveying, this is done by taking two or more images of the same point from different angles
Inertial Navigation for Quadrotor Using Kalman Filter with Drift Compensation IJECEIAES
The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and drift error in the inertial sensor. This research aims to develop the accelerometer and gyroscope sensor for quadrotor navigation system, bias compensation, and Zero Velocity Compensation (ZVC). Kalman Filter is designed to reduce the noise on the sensor while bias compensation and ZVC are designed to eliminate the bias and drift error in the sensor data. Test results showed the Kalman Filter design is acceptable to reduce the noise in the sensor data. Moreover, the bias compensation and ZVC can reduce the drift error due to integration process as well as improve the position estimation accuracy of the quadrotor. At the time of testing, the system provided the accuracy above 90 % when it tested indoor.
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Effectiveness of Fast Speed Yaw and Roll Control Switching Instead of Normal ...AM Publications
In this paper, the effectiveness of new position control strategy - fast speed yaw and roll control switching method instead of the roll control only in Parrot AR Drone 4 rotor helicopter in horizontal plane for automatic fixed position flight was confirmed. General 4 rotor basic flight controller considers only simple floating control and does not concern the position control in the space, the AR Drone was also developed as realizing the floating control only and it is necessary to control the position by the user. Instead of a simple roll control, fast speed switching yaw and roll controls (plus pitch control) could realize stable automatic fixed position control comparing with the simple roll plus pitch controls in the horizontal plane. Proposed method reduced the AR Drone automatic fixed control within S.D. of x and y axis to 31.6% and 54.8% comparing with the normal roll plus pitch controls S.D. of x and y in 3.5 x 5 x 2.4 m room, and it will useful for hobby-class 4 rotor system's the aircraft position control in such a small room condition.
Photogrammetry for Architecture and ConstructionDat Lien
Part of the North America Revit technology Conference in Arizona in 2016, this presentation focuses on using drones and other vehicles combined with different payloads to acquire visual data that can be converted to 3d point clouds and ortho mosaics that can then be used as part of a Building Information Modeling (BIM) workflow in such applications as Autodesk Revit, Navisworks and 3ds Max for design and construction.
Photogrammetry Surveying, its Benefits & DrawbacksNI BT
Learn the Photogrammetry Surveying and benefits-drawbacks of photogrammetry. Photogrammetry is the process of generating a 3D model from a set of 2D photographs. In Surveying, this is done by taking two or more images of the same point from different angles
Inertial Navigation for Quadrotor Using Kalman Filter with Drift Compensation IJECEIAES
The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and drift error in the inertial sensor. This research aims to develop the accelerometer and gyroscope sensor for quadrotor navigation system, bias compensation, and Zero Velocity Compensation (ZVC). Kalman Filter is designed to reduce the noise on the sensor while bias compensation and ZVC are designed to eliminate the bias and drift error in the sensor data. Test results showed the Kalman Filter design is acceptable to reduce the noise in the sensor data. Moreover, the bias compensation and ZVC can reduce the drift error due to integration process as well as improve the position estimation accuracy of the quadrotor. At the time of testing, the system provided the accuracy above 90 % when it tested indoor.
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Effectiveness of Fast Speed Yaw and Roll Control Switching Instead of Normal ...AM Publications
In this paper, the effectiveness of new position control strategy - fast speed yaw and roll control switching method instead of the roll control only in Parrot AR Drone 4 rotor helicopter in horizontal plane for automatic fixed position flight was confirmed. General 4 rotor basic flight controller considers only simple floating control and does not concern the position control in the space, the AR Drone was also developed as realizing the floating control only and it is necessary to control the position by the user. Instead of a simple roll control, fast speed switching yaw and roll controls (plus pitch control) could realize stable automatic fixed position control comparing with the simple roll plus pitch controls in the horizontal plane. Proposed method reduced the AR Drone automatic fixed control within S.D. of x and y axis to 31.6% and 54.8% comparing with the normal roll plus pitch controls S.D. of x and y in 3.5 x 5 x 2.4 m room, and it will useful for hobby-class 4 rotor system's the aircraft position control in such a small room condition.
Photogrammetry for Architecture and ConstructionDat Lien
Part of the North America Revit technology Conference in Arizona in 2016, this presentation focuses on using drones and other vehicles combined with different payloads to acquire visual data that can be converted to 3d point clouds and ortho mosaics that can then be used as part of a Building Information Modeling (BIM) workflow in such applications as Autodesk Revit, Navisworks and 3ds Max for design and construction.
Aircraft position estimation using angle of arrival of received radar signalsjournalBEEI
With increasing demand of air traffic, there is a need to optimize the use of available airspace. Effective utilization of airspace relies on quality of aircraft surveillance. Active research is carried out for enhancements in surveillance techniques and various methods are evaluated for future use. This paper evaluates the use of multiple signal classification (MUSIC) based angle of arrival (AOA) estimation along with multiangulation for locating aircrafts from their electromagnetic wave emission. The performance evaluation of the system is presented by evaluating the AOA estimation errors and position estimation (PE) errors. The errors are evaluated by comparing the estimated value to the actual value. An analysis on the system parameters, AOA error and PE error are presented in the end. AOA errors are affected by the AOA value (emitter bearing), number of array elements, SNR and resolution of AOA estimation algorithm. Errors in AOA estimation lead to PE errors. The simulation results show small errors for short ranges. The system performance can be improved at the expense of computational time by using higher MUSIC resolution and larger antenna arrays.
Computer Aided Visual Inspection of Aircraft SurfacesCSCJournals
Non Destructive Inspections (NDI) plays a vital role in aircraft industry as it determines the structural integrity of aircraft surface and material characterization. The existing NDI methods are time consuming, we propose a new NDI approach using Digital Image Processing that has the potential to substantially decrease the inspection time. Automatic Marking of cracks have been achieved through application of Thresholding, Gabor Filter and Non Subsampled Contourlet transform. For a novel method of NDI, the aircraft imagery is analyzed by three methods i.e Neural Networks, Contourlet Transform (CT) and Discrete Cosine Transform (DCT). With the help of Contourlet Transform the two dimensional (2-D) spectrum is divided into fine slices, using iterated directional filterbanks. Next, directional energy components for each block of the decomposed subband outputs are computed. These energy values are used to distinguish between the crack and scratch images using the Dot Product classifier. In next approach, the aircraft imagery is decomposed into high and low frequency components using DCT and the first order moment is determined to form feature vectors.A correlation based approach is then used for distinction between crack and scratch surfaces. A comparative examination between the two techniques on a database of crack and scratch images revealed that texture analysis using the combined transform based approach gave the best results by giving an accuracy of 96.6% for the identification of crack surfaces and 98.3% for scratch surfaces.
A Method for Predicting Vehicles Motion Based on Road Scene Reconstruction an...ITIIIndustries
The suggested method helps predicting vehicles movement in order to give the driver more time to react and avoid collisions on roads. The algorithm is dynamically modelling the road scene around the vehicle based on the data from the onboard camera. All moving objects are monitored and represented by the dynamic model on a 2D map. After analyzing every object’s movement, the algorithm predicts its possible behavior.
Speed Determination of Moving Vehicles using Lucas- Kanade AlgorithmEditor IJCATR
This paper presents a novel velocity estimation method for ground vehicles. The task here is to automatically estimate
vehicle speed from video sequences acquired with a fixed mounted camera. The vehicle motion is detected and tracked along the
frames using Lucas-Kanade algorithm. The distance traveled by the vehicle is calculated using the movement of the centroid over the
frames and the speed of the vehicle is estimated. The average speed of cars is determined from various frames. The application is
developed using MATLAB and SIMULINK.
Image Fusion of Video Images and Geo-localization for UAV ApplicationsIDES Editor
We present in this paper a very fine method for
determining the location of a ground based target when viewed
from an Unmanned Aerial Vehicle (UAV). By determining the
pixel coordinates on the video frame and by using a range
finder the target’s geo-location is determined in the North-
East-Down (NED) frame. The contribution of this method is
that the target can be localized to within 9m when view from
an altitude of 2500m and down to 1m from an altitude of 100m.
This method offers a highly versatile tracking and geolocalisation
technique that has very good number of
advantages over the previously suggested methods. Some of
the key factors that differentiate our method from its
predecessors are:
1) Day and night time operation
2) All weather operation
3) Highly accurate positioning of target in terms of
latitude-longitude (GPS) and altitude.
4) Automatic gimbaled operation of the camera once
target is locked
5) Tracking is possible even when the target stops
moving
6) Independent of target (moving or stationary)
7) No terrain database is required
8) Instantaneous target geolocalisation is possible
Vehicle positioning in urban environments using particle filtering-based glob...IJECEIAES
This article presents a new method for land vehicle navigation using global positioning system (GPS), dead reckoning sensor (DR), and digital road map information, particularly in urban environments where GPS failures can occur. The odometer sensors and map measure can be used to provide continuous navigation and correct the vehicle location in the presence of GPS masking. To solve this estimation problem for vehicle navigation, we propose to use particle filtering for GPS/odometer/map integration. The particle filter is a method based on the Bayesian estimation technique and the Monte Carlo method, which deals with non-linear models and is not limited to Gaussian statistics. When the GPS sensor cannot provide a location due to the number of satellites in view, the filter fuses the limited GPS pseudo-range data to enhance the vehicle positioning. The developed filter is then tested in a transportation network scenario in the presence of GPS failures, which shows the advantages of the proposed approach for vehicle location compared to the extended Kalman filter.
Intelligent road surface quality evaluation using rough mereologyMohamed Mostafa
The road surface condition information is very useful for the safety of road users and to inform road administrators
for conducting appropriate maintenance. Roughness features of road surface; such as speed bumps and potholes, have bad effects on road users and their vehicles. Usually speed bumps are used to slow motor-vehicle traffic in specific areas in order to increase
safety conditions. On the other hand driving over speed bumps at high speeds could cause accidents or be the reason for spinal injury. Therefore informing road users of the position of speed bumps through their journey on the road especially at night or when lighting is poor would be a valuable feature. This paper exploits a mobile sensor computing framework to monitor and assess road surface conditions. The framework measures the changes in the gravity orientation through a gyroscope and the shifts in the accelerator's indications, both as an assessment
for the existence of speed bumps. The proposed classification approach used the theory of rough mereology to rank the modified data in order to make a useful recommendation to road users.
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
Using social media in education provides learners with an informal way for communication. Informal communication tends to remove barriers and hence promotes student engagement. This paper presents our experience in using three different social media technologies in teaching software project management course. We conducted different surveys at the end of every semester to evaluate students’ satisfaction and engagement. Results show that using social media enhances students’ engagement and satisfaction. However, familiarity with the tool is an important factor for student satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The amount of piracy in the streaming digital content in general and the music industry in specific is posing a real challenge to digital content owners. This paper presents a DRM solution to monetizing, tracking and controlling online streaming content cross platforms for IP enabled devices. The paper benefits from the current advances in Blockchain and cryptocurrencies. Specifically, the paper presents a Global Music Asset Assurance (GoMAA) digital currency and presents the iMediaStreams Blockchain to enable the secure dissemination and tracking of the streamed content. The proposed solution provides the data owner the ability to control the flow of information even after it has been released by creating a secure, selfinstalled, cross platform reader located on the digital content file header. The proposed system provides the content owners’ options to manage their digital information (audio, video, speech, etc.), including the tracking of the most consumed segments, once it is release. The system benefits from token distribution between the content owner (Music Bands), the content distributer (Online Radio Stations) and the content consumer(Fans) on the system blockchain.
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This paper discusses the importance of verb suffix mapping in Discourse translation system. In
discourse translation, the crucial step is Anaphora resolution and generation. In Anaphora
resolution, cohesion links like pronouns are identified between portions of text. These binders
make the text cohesive by referring to nouns appearing in the previous sentences or nouns
appearing in sentences after them. In Machine Translation systems, to convert the source
language sentences into meaningful target language sentences the verb suffixes should be
changed as per the cohesion links identified. This step of translation process is emphasized in
the present paper. Specifically, the discussion is on how the verbs change according to the
subjects and anaphors. To explain the concept, English is used as the source language (SL) and
an Indian language Telugu is used as Target language (TL)
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The using of information technology resources is rapidly increasing in organizations,
businesses, and even governments, that led to arise various attacks, and vulnerabilities in the
field. All resources make it a must to do frequently a penetration test (PT) for the environment
and see what can the attacker gain and what is the current environment's vulnerabilities. This
paper reviews some of the automated penetration testing techniques and presents its
enhancement over the traditional manual approaches. To the best of our knowledge, it is the
first research that takes into consideration the concept of penetration testing and the standards
in the area.This research tackles the comparison between the manual and automated
penetration testing, the main tools used in penetration testing. Additionally, compares between
some methodologies used to build an automated penetration testing platform.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
In order to treat and analyze real datasets, fuzzy association rules have been proposed. Several
algorithms have been introduced to extract these rules. However, these algorithms suffer from
the problems of utility, redundancy and large number of extracted fuzzy association rules. The
expert will then be confronted with this huge amount of fuzzy association rules. The task of
validation becomes fastidious. In order to solve these problems, we propose a new validation
method. Our method is based on three steps. (i) We extract a generic base of non redundant
fuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.
(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rules
using structural equation model.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
2. 22 Computer Science & Information Technology (CS & IT)
devices. These three systems, however, have the following inherent defects: (1) SMR is
susceptible to factors like building block, ground clutters and weather; (2) MALT and ADS can
only monitor a target equipped with a transponder, but not a non-cooperative target on the
surface; (3) These three surveillance approaches feature in low trajectory update rate,
communication delay and high cost. The study of surface moving surveillance system based on
event-driven non-cooperative can fundamentally solve the above-mentioned defects. Honeywell
developed a dual infrared/magnetic sensor, and thousands of such sensors are equipped at airports
for detection of the aircraft
[3]
. Chartier et al. proposed that the position of the aircraft could be
determined though the information of coil sensor installed on the boundary of the airfield
pavement segmentation[4]
. K. Dimitropoulos et al. proposed to detect a magnetic target using a
magnetic sensor network[5]
. Schonefeld J et al. conducted comprehensive analysis on the
performance of runway intrusion prevention system, XL-RIAS, based on distributed sensors, and
testified that the response rate thereof is faster than that of ASDE-X [6]
.
Trajectory tracking and prediction of a target on the airport surface is a main function of the
surface surveillance system. Two main trajectory tracking and prediction algorithms are studied.
One is algorithm based on parameter identification in aircraft dynamics and kinemics models,
wherein Gong studied taxing velocity and acceleration characteristics of the aircraft, and obtained
kinematics trajectory model using regression analysis [7]
; Capoozi et al. analyzed historical data
of surface surveillance and excavated parameters of kinematics equation model [8]
; Rabah W et
al. employed high-gain observer and variable structure control method to perform output
feedback tracking on nonlinear system, with effects of tracking uncertain system being
undesirable
[9]
. Another is algorithm based on optimal estimation theory, wherein conventional
Kalman filters like -α β and - -α β γ are single model tracking algorithms, which are not suitable
for the variety and uncertainty of target motion on the surface[10]
; Farina et al. applied the
restricted information to IMM model set self-adaption in consideration of peculiarity of a target
motion on the airport surface, thus improving the tracking precision
[11]
; Gong Shuli et al. applied
VS-IMM algorithm to the surface target tracking in combination with the airport map
[12]
.
In order to solve the inherent defects in SMR, ADS and MLAT, an asynchronous target-
perceiving-event driven surface moving target surveillance scheme based on the geomagnetic
sensor technology is proposed in this paper. In this scheme, geomagnetic detection nodes are
deployed in the center of the runway/taxiway, thereby the target position can be accurately
perceived as well as the real-time velocity being obtained as a target passes through the nodes.
However, the node deployment density is low, causing the continuous motion state of a moving
target in the adjacent nodes not to be perceived. Regarding such problems, this paper presents a
new algorithm I-IMM, in which the likelihood function of IMM algorithm is improved to
increase the identification of a true motion model. Furthermore, motion model switching is
accelerated and model identification is improved through modification of state transition
probability for self-adaption using posterior information. In the period when the motion state of a
target is not perceptible, memory tracking and prediction on target trajectories can be
implemented through the target motion model identified with I-IMM algorithm, combined with
the final self-adapting state transition probability in the perceptible period.
3. Computer Science & Information Technology (CS & IT) 23
2. SURFACE TARGET SURVEILLANCE SCHEME BASED ON GEO-
MAGNETIC SENSOR TECHNOLOGY
2.1. Surface target surveillance scheme
In general, moving targets on the airport surface comprise aircraft and special vehicles, which are
relatively large ferromagnetic objects, generating disturbance to the surrounding magnetic field
during their moving, thereby targets can be detected by the geomagnetic sensor with an
anisotropic magnetoresistance effect according to the disturbance
[13]
. Combination of
geomagnetic sensor and event-driven wireless sensor network can achieve high precision, small
volume, low cost, no need for wiring and deployment flexibility, without affecting the surface
surveillance performance. The surface moving target surveillance scheme based on the magnetic
sensor technology is as shown in Figure 1.
Figure1. Surveillance scheme for targets on the surface
2.2. Node deployment and runway section information
Due to the large surveillance area, the geomagnetic technology-based surveillance scheme needs
to consider the way of deployment and quantity of geomagnetic detection nodes to reduce the
cost of tracking and communication redundancy. From surface restrictions given by reference [14]
,
it can be known that considering the restrictions on a moving target in different airport areas, the
target motion characteristics can be transcendentally predicted. In this paper, nodes are deployed
4. 24 Computer Science & Information Technology (CS & IT)
in combination with surface restrictions as is shown in Figure 2 (taking a taxiway section as an
example).
2l
3l
1sn
2sn
3sn
4sn
1l
Figure 2. Node deployment
The taxiing route of a moving target on the surface is divided into different sections,
{ }1 2 3, ,L l l l= . A target mostly maintains single motion characteristics in different sections. For
instance, the aircraft maintains accelerated motion during section 1l , constant motion during
section 2l , and decelerated motion during section 3l . Geomagnetic detection nodes
{ }1 2 3 4, , ,SN sn sn sn sn= , are deployed at the cut-off rule of the adjacent sections. Each section
comprises four parameters. For instance, sectioni can be defined as( )1, , ,i i i il sn sn long+ , where
il denotes number, isn denotes start node, 1isn + denotes terminal node, and ilong denotes length.
The section information is preserved in geomagnetic detection nodes for distributed computation
after nodes perceive a target. In above-mentioned deployment, nodes can accurately perceive the
target position as a target passes through them and modify the previous position information, and
the velocity information can also be modified instantaneously via the target velocity obtained
from nodes.
3. I-IMM-BASED SURFACE TARGET TRACKING AND PREDICTION
ALGORITHM
In the surface surveillance scheme based on geomagnetic sensor technology, a target is in a
perceptible state as it passes through nodes, which provide the velocity information. The data
volume, however, is not large and can only be seen as small data samples. When a target
completely detaches from nodes, it would be in an imperceptible state when moving in the
section between nodes. Accordingly, the target tracking and prediction algorithm put forward in
this paper needs to satisfy requirements as follows: When a target is perceptible, the real-time
tracking is performed using the observed velocity information and the target motion model is
accurately identified; When a target is not perceptible, extrapolated prediction is performed on
trajectories thereof using the identified motion model.
3.1. I-IMM algorithm
I-IMM algorithm is improved based on IMM algorithm in the following two aspects: Weighted
sum is performed on the mean of residual errors and model probabilistic likelihood function is
reconstructed, thus increasing the identification of a true motion model; Model transition
5. Computer Science & Information Technology (CS & IT) 25
probability is updated for self-adaption using model posterior probability, thus accelerating
model switching as well as increasing the identification of a model. The schematic diagram of I-
IMM algorithm is as shown in Figure 3. This algorithm comprises the following 5 steps:Input
interaction; Kalman filter; Model probability update; Model transition probability self-adaption;
Output fusion.
1
ˆ ( 1/ 1)X k k− − 2
ˆ ( 1/ 1)X k k− − ˆ ( 1/ 1)rX k k− −
01
ˆ ( / 1)X k k − 02
ˆ ( / 1)X k k − 0
ˆ ( / 1)rX k k −
1
ˆ ( / )X k k 2
ˆ ( / )X k k ˆ ( / )nX k k
1( )kΛ
2 ( )kΛ
( )r kΛ
( )iu k
ˆ ( / )X k k
Figure 3. Schematic diagram of I-IMM algorithm
3.1.1. Input interaction
Assuming that a model set consists of r motion models, the state estimation value and covariance
matrix of each model at time 1k − are respectively as follows: ˆ ( 1| 1)jX k k− − and ˆ ( 1| 1)jP k k− −
, 1,2, ,j r= L .
After interaction, the input in model j at time k is expressed as follows:
0
1
ˆ ˆ( 1| 1) ( 1| 1) ( 1| 1)
r
j i ij
i
X k k X k k u k k
=
− − = − − − −∑ (1)
0
1
0
ˆ ˆ( 1| 1) ( 1| 1){ ( 1| 1)
ˆ ˆ[ ( 1| 1) ( 1| 1)] }
r
j ij i
i
T
i j
P k k u k k P k k
X k k X k k
=
− − = − − − −
+ − − − − −
∑ (2)
Where, the mixture probability after input interaction is defined as:
( 1| 1) ( 1) /ij ij i ju k k p u k c− − = − (3)
6. 26 Computer Science & Information Technology (CS & IT)
Where,
1
( 1)
r
j ij i
i
c p u k
=
= −∑ , ijp denotes model transition probability, and ( 1)iu k − denotes
probability in model i at time 1k − .
3.1.2. Kalman filter
Kalman filter consists of prediction process and update process. The prediction process is
expressed by Eq. (4) and Eq. (5):
0
ˆ ˆ( | 1) ( 1| 1)j j jX k k F X k k− = − − (4)
T
0
ˆ ˆ( | 1) ( 1| 1)j j j jP k k F P k k F Q− = − − + (5)
In the above equations, jF is the model state transition matrix; Q is the noise covariance in
each model during the estimation.
Residual sequence and covariance matrix are:
ˆ( ) ( ) ( | 1)j j jr k Z k HX k k= − − (6)
Tˆ( ) ( | 1)j jS k HP k k H R= − + (7)
In the above equations, ( )jZ k is the observed value for the time k ; H is the observation
matrix; R is the noise covariance of observation.
Kalman filter gain matrix is:
1ˆ( ) ( | 1) ( )T
j j jK k P k k H S k−
= − (8)
State estimate and covariance matrix update are expressed as follows:
ˆ ˆ( | ) ( | 1) ( ) ( )j j j jX k k X k k K k r k= − + (9)
Tˆ ˆ( | ) ( | 1) ( ) ( | 1) ( )j j j j jP k k P k k K k S k k K k= − − − (10)
3.1.3. Model probability update
In IMM algorithm, maximum likelihood function in model j is as given in Eq. (11):
11 1
( ) exp{ ( ) ( ) ( )}
22 ( )
T
j j j j
j
k r k S k r k
S kπ
−
Λ = − (11)
As can be seen from the Eq. (11), it is assumed that the motion model set can contain all motion
models of a target during the operation in IMM algorithm. However, due to the factors like
uncertainty of the motion of a surface target, surface restrictions and spot dispatch, the target
motion model may exceed the model set in the algorithm. Therefore, innovation information is no
longer considered to obey Gaussian distribution, in which mean value is zero and variance is
( )jS k , and thus model probabilistic likelihood function is reconstructed.
7. Computer Science & Information Technology (CS & IT) 27
Let assume the true motion model of a surface moving target to be as follows:
( ) ( 1) ( 1) ( 1)T T T TX k F k X k w k= − − + − (12)
( ) ( ) ( )T TZ k HX k v k= + (13)
Define the model state transition matrix error as follows:
j T jF F F∆ = − (14)
Define the state estimation error as follows:
ˆ( 1) ( 1| 1) ( 1| 1)j T je k X k k X k k− = − − − − − (15)
Expression for the state estimation error after input interaction is obtained:
0 0
1
ˆ( 1) ( 1| 1) ( 1| 1) ( 1| 1) ( 1)
r
j T j ij i
i
e k X k k X k k u k k e k
=
− = − − − − − = − − −∑ (16)
Given by Eq. (6) and Eq. (12), the residual error is obtained:
0
ˆ( ) ( ) ( ) ( 1| 1)j T T j jr k HX k v k HF X k k= + − − − (17)
Given by Eq. (12) and Eq. (15), the residual error is obtained:
0 0
ˆ( ) ( -1) ( -1| -1) ( ) ( )j T j j j T Tr k HF e k H F X k k Hw k v k= + ∆ + + (18)
Mean value obtained from Eq. (18) can be expressed as follows:
0 0
ˆ( ) ( 1) ( -1| -1)j T j j jr k HF e k H F X k k= − + ∆ (19)
Where, 0
1
( 1) ( 1| 1) ( 1)
r
j ij i
i
e k u k k e k
=
− = − − −∑ (20)
Because of the uncertainty of the true motion model of a surface target, the quantization of TF
and jF∆ in Eq. (19) cannot be performed, causing the mean of residual errors not to be obtained.
To solve this problem, the true motion model of a target is assumed to be j , and weighted sum is
performed on another model in the model set to obtain ( )jr k .
( )0 0
1
ˆ( ) ( 1) ( -1| -1) 1| 1
r
j j i i j i i
i
r k HF e k H F X k k u k k
=
= − + ∆ − − ∑ (21)
Where, i j iF F F∆ = − ,and 0
1
( 1) ( 1| 1) ( 1)
r
i in n
n
e k u k k e k
=
− = − − −∑ .
Then, maximum likelihood function in model j at time k can be given as:
11 1
( ) exp ( ) ( ) ( ) ( ) ( )
22 ( )
T
j j j j j j
j
k r k r k S k r k r k
S kπ
−
Λ = − − −
(22)
8. 28 Computer Science & Information Technology (CS & IT)
( ) ( ) ( ) ( )
1
1
1 /
r
j j ij i j j
i
u k k p u k k c c
c =
= Λ − = Λ∑ (23)
Where, ( )
1
r
j j
j
c k c
=
= Λ∑ (24)
3.1.4. Model transition probability self-adaption
In IMM algorithm, because of the uncertainty of the target maneuver and the distortion of the
prior information, the fixed model transition probability ijp fails to reflect the true motion model
of a target, and switching velocity between models is also delayed during the target maneuver.
Given that the observed velocity is small sample information, applying the fixed model transition
probability ijp may likely cause the target motion model hard to be identified or even not to be
identified. Therefore, the model transition probability ijp is updated using posterior information in
I-IMM algorithm to solve this problem.
Assuming that the probability in model j at time 1k − is ( )1ju k − and at time k is ( )ju k , the
probability differential value of the same model at adjoining times reflects the change in the
matching degree between model j and the true motion model. The rate of change of the posterior
probability in model j can be defined as:
( ) ( ) ( )1j j ju k u k u k∆ = − − (25)
Let the model transition probability from model i to model j at time 1k − be ( )1ijp k − , and
update ( )1ijp k − using ( )ju k∆ , then the expression is obtained:
( ) ( )( ) ( )exp 1ij j ijp k u k p k′ = ∆ − (26)
Model transition probability needs to satisfy basic properties as follows:
1
0 1, , 1,2, ,
1
ij
r
ij
j
p i j r
p
=
< < =
=
∑
L
(27)
Then, normalization needs to be performed on ( )ijp k′ , and the transition probability ( )ijp k can
be obtained:
( )
( )
( )
( )( ) ( )
( )( ) ( )
1 1
exp 1
exp 1
j ijij
ij r r
ij j ij
j j
u k p kp k
p k
p k u k p k
= =
∆ −′
= =
′ ∆ −∑ ∑
(28)
9. Computer Science & Information Technology (CS & IT) 29
As can be seen from Eq. (28), updated ( ), 1,2, ,ijp k i r= L increases as the transition of model
from modeli to model j , when the posterior information ( )ju k∆ increases, thus model j plays a
critical role in input interaction at next time period.
3.1.5. Output fusion
Interactive output results at time k are expressed as follows:
( ) ( ) ( )
1
ˆ ˆ| |
r
j j
j
X k k X k k u k
=
= ∑ (29)
( ) ( ) ( ) ( ) ( ) ( ) ( ){ }T
1
ˆ ˆ ˆ ˆ ˆ| | | | | |
r
j j j j
j
P k k u k P k k X k k X k k X k k X k k
=
= + − − ∑ (30)
3.2. Trajectory prediction of targets not perceptible
A target would be not perceptible as moving in the section between two adjacent nodes, requiring
memory tracking of target trajectories using extrapolated prediction.
At last moment of the period when a target is perceptible, I-IMM provides identification of each
model in the model set, namely, model posterior probability ( ), 1,2, ,ju k j r= L . Then given by
the self-adapting model transition probability ( )ijp k , the expression for prediction probability of
each model in the model set when a target not perceptible at time 1k + can be obtained:
( ) ( )
1
1| ( ) , 1,2, ,
r
j i ij
i
u k k u k p k j r
=
′ + = =∑ g L (31)
At the same time, posterior probability of each model needs to satisfy the following properties:
1
0 1, 1,2, ,
1
j
r
j
j
u j r
u
=
< < =
=
∑
L
(32)
Then, normalization needs to be performed on posterior probability of each model predicted from
Eq. (31), and model posterior probability at moment 1k + is obtained:
( )
( )
( )
1
1|
1| =
1|
j
j r
j
j
u k k
u k k
u k k
=
′ +
+
′ +∑
(33)
After substituting state predicted value, ( )ˆ 1|jX k k+ and prediction model probability,
( )1|ju k k+ of each model into Eq. (29), state predicted value of the period when a target is not
perceptible can be defined as :
10. 30 Computer Science & Information Technology (CS & IT)
( ) ( ) ( )
1
ˆ ˆ1| 1| 1|
r
j j
j
X k k X k k u k k
=
+ = + +∑ (34)
By performing extrapolated prediction on surface target trajectories using state predicted value
obtained from Eq. (34), memory tracking and prediction can be implemented on a target not
perceptible.
4. SIMULATION AND ANALYSIS
4.1. Preparation for simulation
This paper presents, taking aircraft passing through a certain geomagnetic detection node on the
taxiway for an example, IMM algorithm and I-IMM algorithm are compared through Monte
Carlo simulation, regarding the performance of trajectory tracking of the aircraft perceptible and
trajectory prediction of the aircraft not perceptible.
According to the motion characteristics of the aircraft on the surface, the aircraft motion can be
expressed by a model set comprising constant velocity (CV) model, constant acceleration (CA)
model and constant jerk (CJ) model. State transition matrixes of three models are respectively
expressions as follows:
1 0 0
0 1 0 0
0 0 0 0
0 0 0 0
CV
T
F
=
,
2
1 0
2
0 1 0
0 0 1 0
0 0 0 0
CA
T
T
TF
=
,
2 3
2
1
2 6
0 1
2
0 0 1
0 0 0 1
CJ
T T
T
T
F T
T
=
Where, T is the interval of sampling. Motion state vector of the aircraft is , and
observation matrix is [ ]0 1 0 0H = .
In the period when aircraft is perceptible, the process of the aircraft operation is as follows:(1)
Performing CJ at 0.3 3
/m s from 0 to 4.5 seconds; (2) Performing CA at 0.45 2
/m s from 4.58 to
12 seconds; (3) Performing CV at the velocity obtained from step (2) from 12 to15 seconds.
In the period when aircraft is not perceptible, it maintains CV for about 30 seconds at the velocity
obtained from step (3) and then operates to the next detection node.
The actual position of the aircraft according to the operation process is as shown in Figure 4.
11. Computer Science & Information Technology (CS & IT) 31
Figure 4. Actual position of the aircraft
The simulation parameters selection is as follows: Noise covariance in each model during the
estimation is
0.01 0 0 0
0 0.01 0 0
0 0 0.01 0
0 0 0 0.01
Q
=
; Noise covariance of velocity observation is
0.15R = ; the interval of sampling is 0.3T s= ; Initial model probabilities of CV model,CA
model and CJ model are respectively 0.4,0.3 and 0.3; Initial model transition matrix can be
given as:
0.9 0.05 0.05
0.05 0.9 0.05
0.05 0.05 0.9
markovP
=
.
4.2. Simulation results and analysis in perceptible period
Simulation results in the period when the aircraft is perceptible are as displayed in Figure 5 to 8.
Figure 5. Position tracking
13. Computer Science & Information Technology (CS & IT) 33
Figure 5 to 8 illustrate the excellence of I-IMM algorithm when used to track the motion state of
the aircraft. Fig. 5 and 6 demonstrate that compared with IMM algorithm, the position and
velocity tracked with I-IMM algorithm are more approximate to the actual position and velocity
of the aircraft. To show the advantage of I-IMM more manifestly, the position error curve and
velocity root-mean-square error(RMSE) curve of I-IMM and IMM algorithm are respectively
plotted, as shown in Figure 9 and 10.
Figure 9. Position error curve
Figure 10. Velocity RMSE curve
Figure 9 shows maximum position error using IMM algorithm is 1.600m, while using I-IMM
algorithm is only 0.600m. Figure 10 shows maximum RMSE error using IMM algorithm is
0.059m/s, while using I-IMM algorithm is 0.023m/s. As can be seen from the result, the tracking
precision is well improved when using I-IMM algorithm.
Figure 11 presents the selection probability curves of CV, CA and CJ models when IMM and I-
IMM algorithm are respectively employed. Figure 11 demonstrates that IMM algorithm cannot
identify each motion model very clearly, and three selection probability curves intersect
intensely. For instance, in constant accelerating phase, IMM algorithm’s maximum identification
0 1.5 3 4.5 6 7.5 9 10.5 12 13.5 15
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Time/s
positionerror/m
IMM position error
I-IMM position error
14. 34 Computer Science & Information Technology (CS & IT)
degree of CA model is 0.710; Comparatively, I-IMM algorithm can largely improve the
identification degree. In constant jerking phase, the maximum identification degree of CJ model
is 0.987, while in constant accelerating phase, the maximum identification degree of CA model
can reach to 0.987, and in constant velocity phase, the maximum identification degree of CV
model is 0.987. As for model switching, the switching velocity in I-IMM algorithm is much
faster than that in IMM algorithm. In IMM algorithm, it takes 2.4 seconds to switch from CJ
model to CA model, and 1.8 seconds from CA model to CV model. In comparison, when
employing I-IMM algorithm, it only takes 0.9 seconds to switch from CJ model to CA model,
and only 0.9 seconds from CA model to CV model.
Figure 11. Selection probability in IMM and I-IMM
4.3. Simulation results and analysis in imperceptible period
Simulation results of trajectory prediction in the period when the aircraft is not perceptible are as
displayed in Figure 12 and 13.
Figure 12. Position prediction
15. Computer Science & Information Technology (CS & IT) 35
Figure 13. Position prediction error
Figure 12 illustrates that the deviation between the aircraft position predicted with either IMM or
I-IMM algorithm and the real position increases with the increase of the running time. Figure 13
illustrates that at the last moment of position prediction, the position prediction error is
accumulated to 9.790m when IMM algorithm is used, while only to 2.160m when I-IMM
algorithm is used. It is apparent that I-IMM algorithm outperforms IMM algorithm in terms of
trajectory extrapolated prediction, particularly in the period when the aircraft is not perceptible.
5. CONCLUSIONS
In view of the inherent defects in current surface surveillance system, this paper proposes a
asynchronous target-perceiving-event driven surface moving target surveillance scheme based on
the geomagnetic sensor technology. Furthermore, a surface moving target tracking and prediction
algorithm is given based on I-IMM, which is improved on the basis of IMM algorithm in the
following aspects: Weighted sum is performed on the mean of residual errors and model
probabilistic likelihood function is reconstructed, thus increasing the identification of a true
motion model; Model transition probability is updated for self-adaption with model posterior
probability, thus accelerating model switching as well as increasing the identification of a model.
At last, this paper presents simulation results of target tracking and prediction in both periods
when a target is perceptible and not perceptible using two algorithms, demonstrating that the I-
IMM algorithm is more effective than IMM algorithm, particularly when a target is not
perceptible.
ACKNOWLEDGEMENTS
This work is supported by the National Science Foundation of China (grant no. U1433125), Civil
Aviation Science and Technology Guidance Foundation (grant no. 14014J0340035), Science
Foundation of Jiangsu Provence (grant no. BK20141413), Fundamental Research Funds for the
Central Universities (grant no. NS2014065), and Startup Project for Introduced Talents of
Sichuan University.
16. 36 Computer Science & Information Technology (CS & IT)
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17. Computer Science & Information Technology (CS & IT) 37
AUTHORS
Dr. Xinmin Tang was born in 1979. He obtained his Ph.D. in Mechanical Engineering at
the Harbin Institute of Technology in 2007. He is currently an Associate Professor in the
College of Civil Aviation at Nanjing University of Aeronautics and Astronautics. His
research interests include (1) Petri Net and Discrete Event Dynamic System theory; (2)
Hybrid System Theory.
Shangfeng Gao was born in 1990. He holds a Master Degree in Engineering from the
College of Civil Aviation at Nanjing University of Aeronautics and Astronautics. His
major course is Transportation planning and management. His research interests include
Advanced Surface Movement Guidance and Control System (A-SMGCS).
Dr. Songchen Han was born in 1964. He obtained his Ph.D. in Engineering at Harbin
Institute of Technology. He is currently a professor in Sichuan University in China. His
research interests include (1) next generation air traffic management system (2) air traffic
planning and simulation.
Dr. Zhiyuan Shen is an assistant professor at college of civil aviation, Nanjing
University of Aeronautics and Astronautics (NUAA). He received Ph.D in control
science and engineering from the Harbin Institute of Technology, China. Between 2010
and 2012, he was a visiting scholar in Electrical and Computer Engineering at Georgia
Institute of Technology, Atlanta. His current research interest includes ADS-B technique
and 4D trajectory prediction.
Liping Di was born in 1964. She obtained his Bachelor Degree in Aircraft Control at the
Harbin Institute of Technology in China. She is currently a teacher in Sichuan University.
Her research interest is aircraft control.
Binbin Liang was born in 1990. He got a Master Degree in Engineering from the College
of Civil Aviation at Nanjing University of Aeronautics and Astronautics. His research
interests include civil aviation emergency management and computer vision.