|Commenced in January 1999 || Frequency: Monthly || Edition: International|| Paper Count: 18 |
Computer, Electrical, Automation, Control and Information Engineering
Importance of Hardware Systems and Circuits in Secure Software Development Life Cycle
Although it is fully impossible to ensure that a software system is quite secure, developing an acceptable secure software system in a convenient platform is not unreachable. In this paper, we attempt to analyze software development life cycle (SDLC) models from the hardware systems and circuits point of view. To date, the SDLC models pay merely attention to the software security from the software perspectives. In this paper, we present new features for SDLC stages to emphasize the role of systems and circuits in developing secure software system through the software development stages, the point that has not been considered previously in the SDLC models.
Architecture Design of the Robots Operability Assessment Simulation Testbed
This paper presents the architecture design of the robot operability assessment simulation testbed (called "ROAST") for the resolution of robot operability problems occurred during interactions between human operators and robots. The basic idea of the ROAST architecture design is to enable the easy composition of legacy or new simulation models according to its purpose. ROAST architecture is based on IEEE1516 High Level Architecture (HLA) of defense modeling and simulation. The ROAST architecture is expected to provide the foundation framework for the easy construction of a simulation testbed to order to assess the robot operability during the robotic system design. Some of ROAST implementations and its usefulness are demonstrated through a simple illustrative example.
Implementation and Demonstration of Software-Defined Traffic Grooming
Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.
Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images
Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.
Secure Cryptographic Operations on SIM Card for Mobile Financial Services
Mobile technology is very popular nowadays and it provides a digital world where users can experience many value-added services. Service Providers are also eager to offer diverse value-added services to users such as digital identity, mobile financial services and so on. In this context, the security of data storage in smartphones and the security of communication between the smartphone and service provider are critical for the success of these services. In order to provide the required security functions, the SIM card is one acceptable alternative. Since SIM cards include a Secure Element, they are able to store sensitive data, create cryptographically secure keys, encrypt and decrypt data. In this paper, we design and implement a SIM and a smartphone framework that uses a SIM card for secure key generation, key storage, data encryption, data decryption and digital signing for mobile financial services. Our frameworks show that the SIM card can be used as a controlled Secure Element to provide required security functions for popular e-services such as mobile financial services.
Investigation of Flame and Soot Propagation in Non-Air Conditioned Railway Locomotives
Propagation of fire through a non-air conditioned
railway compartment is studied by virtue of numerical simulations.
Simultaneous computational fire dynamics equations, such as
Navier-Stokes, lumped species continuity, overall mass and energy
conservation, and heat transfer are solved using finite volume based
(for radiation) and finite difference based (for all other equations)
solver, Fire Dynamics Simulator (FDS). A single coupe with an eight
berth occupancy is used to establish the numerical model, followed
by the selection of a three coupe system as the fundamental unit
of the locomotive compartment. Heat Release Rate Per Unit Area
(HRRPUA) of the initial fire is varied to consider a wide range of
compartmental fires. Parameters, such as air inlet velocity relative
to the locomotive at the windows, the level of interaction with the
ambiance and closure of middle berth are studied through a wide
range of numerical simulations. Almost all the loss of lives and
properties due to fire breakout can be attributed to the direct or
indirect exposure to flames or to the inhalation of toxic gases and
resultant suffocation due to smoke and soot. Therefore, the temporal
stature of fire and smoke are reported for each of the considered
cases which can be used in the present or extended form to develop
guidelines to be followed in case of a fire breakout.
Predicting Groundwater Areas Using Data Mining Techniques: Groundwater in Jordan as Case Study
Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.
Evaluation of AR-4BL-MAST with Multiple Markers Interaction Technique for Augmented Reality Based Engineering Application
Augmented reality (AR) technology has the capability to provide many benefits in the field of education as a modern technology which aided learning and improved the learning experience. This paper evaluates AR based application with multiple markers interaction technique (touch-to-print) which is designed for analyzing the kinematics of 4BL mechanism in mechanical engineering. The application is termed as AR-4BL-MAST and it allows the users to touch the symbols on a paper in natural way of interaction. The evaluation of this application was performed with mechanical engineering students and human–computer interaction (HCI) experts to test its effectiveness as a tangible user interface application where the statistical results show its ability as an interaction technique, and it gives the users more freedom in interaction with the virtual mechanical objects.
Algorithm for Information Retrieval Optimization
When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (
An Indoor Guidance System Combining Near Field Communication and Bluetooth Low Energy Beacon Technologies
Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study presents a methodology based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoor and outdoor on smartphones, with aim to provide users a smart life through this system. The presented system is implemented on a smartphone and evaluated on a student campus environment. The experimental results confirm the ability of the presented app to switch automatically from an outdoor mode to an indoor mode and to guide the user to the requested target destination via the shortest possible route.
Video Based Ambient Smoke Detection By Detecting Directional Contrast Decrease
Fire-related incidents account for extensive loss of life and
material damage. Quick and reliable detection of occurring fires has high
real world implications. Whereas a major research focus lies on the detection
of outdoor fires, indoor camera-based fire detection is still an open issue.
Cameras in combination with computer vision helps to detect flames and
smoke more quickly than conventional fire detectors. In this work, we present
a computer vision-based smoke detection algorithm based on contrast changes
and a multi-step classification. This work accelerates computer vision-based
fire detection considerably in comparison with classical indoor-fire detection.
A Static Android Malware Detection Based on Actual Used Permissions Combination and API Calls
Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.
Real Time Video Based Smoke Detection Using Double Optical Flow Estimation
In this paper, we present a video based smoke detection
algorithm based on TVL1 optical flow estimation. The main part
of the algorithm is an accumulating system for motion angles and
upward motion speed of the flow field. We optimized the usage of
TVL1 flow estimation for the detection of smoke with very low smoke
density. Therefore, we use adapted flow parameters and estimate the
flow field on difference images. We show in theory and in evaluation
that this improves the performance of smoke detection significantly.
We evaluate the smoke algorithm using videos with different smoke
densities and different backgrounds. We show that smoke detection
is very reliable in varying scenarios. Further we verify that our
algorithm is very robust towards crowded scenes disturbance videos.
Numerical Simulations of Fire in Typical Air Conditioned Railway Coach
Railways in India remain primary mode of transport
having one of the largest networks in the world and catering to
billions of transits yearly. Catastrophic economic damage and loss
to life is encountered over the past few decades due to fire to
locomotives. Study of fire dynamics and fire propagation plays an
important role in evacuation planning and reducing losses. Simulation
based study of propagation of fire and soot inside an air conditioned
coach of Indian locomotive is done in this paper. Finite difference
based solver, Fire Dynamic Simulator (FDS) version 6 has been
used for analysis. A single air conditioned 3 tier coupe closed to
ambient surroundings by glass windows having occupancy for 8
people is the basic unit of the domain. A system of three such
coupes combined is taken to be fundamental unit for the entire
study to resemble effect to an entire coach. Analysis of flame and
soot contours and concentrations is done corresponding to variations
in heat release rate per unit volume (HRRPUA) of fire source,
variations in conditioned air velocity being circulated inside coupes
by vents and an alternate fire initiation and propagation mechanism
via ducts. Quantitative results of fractional area in top and front
view of the three coupes under fire and smoke are obtained using
MATLAB (IMT). Present simulations and its findings will be useful
for organizations like Commission of Railway Safety and others in
designing and implementing safety and evacuation measures.
Surveillance Video Summarization Based on Histogram Differencing and Sum Conditional Variance
For more efficient and fast video summarization, this paper presents a surveillance video summarization method. The presented method works to improve video summarization technique. This method depends on temporal differencing to extract most important data from large video stream. This method uses histogram differencing and Sum Conditional Variance which is robust against to illumination variations in order to extract motion objects. The experimental results showed that the presented method gives better output compared with temporal differencing based summarization techniques.
Optimal Bayesian Control of the Proportion of Defectives in a Manufacturing Process
In this paper, we present a model and an algorithm for
the calculation of the optimal control limit, average cost, sample size,
and the sampling interval for an optimal Bayesian chart to control
the proportion of defective items produced using a semi-Markov
decision process approach. Traditional p-chart has been widely
used for controlling the proportion of defectives in various kinds
of production processes for many years. It is well known that
traditional non-Bayesian charts are not optimal, but very few optimal
Bayesian control charts have been developed in the literature, mostly
considering finite horizon. The objective of this paper is to develop
a fast computational algorithm to obtain the optimal parameters of a
Bayesian p-chart. The decision problem is formulated in the partially
observable framework and the developed algorithm is illustrated by
a numerical example.
Simulation of Utility Accrual Scheduling and Recovery Algorithm in Multiprocessor Environment
This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.
Evaluation of Context Information for Intermittent Networks
The context aware adaptive routing protocol is presented for unicast communication in intermittently connected mobile ad hoc networks (MANETs). The selection of the node is done by the Kalman filter prediction theory and it also makes use of utility functions. The context aware adaptive routing is defined by spray and wait technique, but the time consumption in delivering the message is too high and also the resource wastage is more. In this paper, we describe the spray and focus routing scheme for avoiding the existing problems.