Abdulaziz S. Almazyad

A Proposed Scalable Design and Simulation of Wireless Sensor Network-Based Long-Distance Water Pipeline Leakage Monitoring System

Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID) and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

Fused features mining for depth-based hand gesture recognition to classify blind human communication

Abstract Gesture recognition and hand pose tracking are applicable techniques in human–computer interaction fields. Depth data obtained by depth cameras present a very informative explanation of the body or in particular hand pose that it can be used for more accurate gesture recognition systems. The hand detection and feature extraction process are very challenging task in the RGB images that they can be effectively dissolved with simple ways with depth data. However, depth data could be combined with the color information for more reliable recognition. A common hand gesture recognition system requires identifying the hand and its position or direction, extracting some useful features and applying a suitable machine-learning method to detect the performed gesture. This paper presents the novel fusion of the enhanced features for the classification of static signs of the sign language. It begins by explaining how the hand can be separated from the scene by depth data. Then, a combination feature extraction method is introduced for extracting some appropriate features of the images. Finally, an artificial neural network classifier is trained with these fused features and applied to critically analyze various descriptors performance.

Online versus offline Arabic script classification

Abstract Arabic script classification is a complex area of research in the field of computer vision. The issue of offline Arabic script classification has been a concern of many researchers interest currently as it is assumed that online Arabic script recognition is comparatively simple and significant achievements have been attained. Numerous researchers deal with these issues evolved in pre-processing and post-processing techniques of Arabic script and presented various approaches to improve its accuracy rate. However, offline Arabic script classification and its related issues are still fresh. In this paper, we focus on pre-processing to post-processing techniques and highlight several issues in each phase in order to highlight need of high classification performance for Arabic script classification (offline and online). Additionally, top experimental results are reported, discussed and compared, and current challenges are also discussed. Finally, online versus offline Arabic script recognition achievements are also compared.

Multifocus watermarking approach based on discrete cosine transform

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both “pertinent” and “immaterial” information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Qabf, standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. Microsc. Res. Tech. 79:431–437, 2016.

Concise analysis of current text automation and watermarking approaches

With ceaseless utilization of web and other online advances, it has turned out to be amazingly simple to imitate, discuss, and convey digital material. Subsequently, confirmation and copyright assurance issues have been emerged. Text is the most widely used media of communication on the web as compared with images and videos. The significant part of books, daily papers, websites, commercial, research papers, reports, and numerous different archives are just the plain text. Therefore, copyrights protection of plain text is a critical issue that could not be accepted at all. This paper presents a concise analysis on information hiding techniques and their consequences. Various watermarking systems properties are highlighted along with different types of attacks and their possible defenses. Additionally, the current applications for text document watermarking and the reasons for the problems of text document watermarking are described. Finally, attacks characteristics are discussed including types of attacks, volumes, and nature on text. Current watermarking approaches are reviewed in depth, and consequently, their advantages and weaknesses are highlighted. Copyright

Language independent rule based classification of printed & handwritten text

Handwriting in data entry forms/documents usually indicates users filled information that should be treated differently from the printed text. In Arab world, these filled information are normally in English or Arabic. Secondly, classification approaches are quite different for machine printed and script. Therefore, prior to segmentation & classification, text distinction into Printed & script entries is mandatory. In this research, the dilemma of the language independent text distinction in multilingual data entry forms is addressed. Our main focus is to distinguish the machine printed text and script in multilingual data entry forms that are language independent. The proposed approach explore new statistical and structural features of text lines to classify them into separate categories. Accordingly a set of classification rules is derived to explicitly differentiate machine printed and handwritten entries, written in any language. Additional, novelty of the proposed approach is that no training/training data is required rather text is discriminated on basis of simple rules. Promising experimental results with 90 % accuracy exhibit that proposed approach is simple and robust. Finally, the scheme is independent of language, style, size, and fonts that commonly co-exist in multilingual data entry forms.

An Incremental View Maintenance Approach Using Version Store in Warehousing Environment

Data warehouse is a repository of information collected from multiple, possibly heterogeneous, autonomous and distributed databases. The information stored in the warehouse is in the form of Materialized views. In data warehouses materialized views are used to pre-compute and store aggregated data such as sums and averages. Materialized views are the derived relation, which are stored as the relation in the database, when some update occurs in the parent relation all its child relations also gets updated by viewing to maintain the consistency and convergence [3]of the database. In this paper we present a new method of incremental view maintenance with the inclusion of some existing approaches [2][3]. We utilized the concept of version store [2] for older versions of tables that have been updated at the source.

Accuracy enhancement in environment sound recognition using ZC features and MPEG-7 with modified K-NN classifier feature

In this paper, we modify the K-NN classifier feature for environment recognition from audio particularly for forensic application. We compute the distance between the first frame from the testing file with all frames from the training file, instead of only the corresponding frames, then we take the average. We investigated the effect of temporal zero crossing feature and some selected MPEG-7 audio low level descriptors on environment sound recognition. Experimental results show that higher recognition accuracy is achieved by using the modified K-NN classifier and confirm that the accuracy is increased when the size of the training file is decreased.

Formalizing certain tasks for processor architecture verification

Present day verification is a time consuming task. With processor architecture complexity increasing by the day, managing the complete verification process has become a major challenge. Besides, a small bug in the final product may ruin all the efforts. This problem has resulted in the popularity of verification and other related technologies. For example formal verification is now considered as an important part of any verification process. Similarly other technologies and methodologies are gaining acceptance. However, despite all these tools and technologies, verification still remains the main bottleneck and challenge in the overall process for the development of a modern processor. This problem can be looked from a different angle. We believe that a proper strategy is equally important for the verification efforts to succeed. The strategy will be easier once we formalize certain aspects of the process. This paper is an attempt to formalize some of the important aspects, ideas and methodologies towards the verification of processor architecture.

Reputation-based mechanisms to avoid misbehaving nodes in ad hoc and wireless sensor networks

Securing mobile ad hoc networks (MANET) has been the interest of researchers recently because of its use in important security sectors such as police, rescue teams, and the military. One method to ensure a secure ad hoc network is to identify malicious nodes (hostile) from good nodes by their reputation based on the past experience of packet delivery. In this paper, we explore by applying reputation in various ways the effect to the throughput of a MANET ad hoc network. We simulate four different scenarios where the node reputation is evaluated to choose the most reliable route and eliminate the effect of malicious nodes performing gray-hole attack. One of the applied scenarios is a hybrid method where a sender node takes in consideration the reputation of all the nodes forming a route to choose the most reliable route. We find that by applying the hybrid method the performance of the network is the best and data packets are more likely to be delivered successfully to the intended destination in a very hostile environment.