Iftikhar Azim Niaz

Identification and prioritization of critical issues for the promotion of e-learning in Pakistan

Identification of state-of-the-art issues for the promotion of e-learning in Pakistan.Analysis of the impact of issues on the promotion of e-learning in HEIs of Pakistan.Classifying the identified issues in to respective dimensions.Development of taxonomy for the identified issues of e-learning.Prioritization of the issues according to their importance for the promotion of e-learning. Integration of information and communication technology in education is emerging as the new paradigm of learning and training. Higher education institutions are struggling to shift to this new paradigm to facilitate more and more learners with the flexibility of any time-anywhere learning. E-learning is not gaining as much popularity in the developing countries as it was expected in the last decade. Little work has been done in this area of research in the developing countries. This study contributes to identify and analyze the impact of critical issues which are creating barriers in the promotion of e-learning in the developing countries like Pakistan. Furthermore, this study contributes in devising taxonomy and proposing new category software for the identified critical issues. A mix mode research model has been applied to collect data from the e-learning experts of different public sector universities of Pakistan to get a deeper understanding of the issues and their impact on the promotion of e-learning in Pakistan. The findings of this study reveal sixteen (16) critical issues which are classified in five (5) dimensions, to be addressed on priority basis to promote e-learning in Pakistan. The identified dimensions and issues have been prioritized according to their importance using the Analytical Hierarchy Process method.

Logo detection and recognition in video stream

Logos sometimes also known as trademark have high importance in todays marketing world. Products, companies and different gaming leagues are often recognized by their respective logos. In this paper, an implementation system for logo detection and recognition in video stream is presented. Feature set using SIFT (Scale Invariant Feature Transform) key-points is created for each query logo and the video frame being processed. The system uses a concept of bidirectional or two-way matching of features. Model fitting is carried out by using Random Sample Consensus (RANSAC) algorithm to suppress any outliers from two-way matching process. Also novel threshold scheme is used to finally make decision regarding presence of logo. Finally boundary is detected around the matched logo. The system provides various kinds of statistics like frequency of recognized logos, their visibility time and their locations in the video. Experiments were performed on various sports videos. The results of the experiments show that the developed system has achieved the precision rate of 89% and a recall of 99%.

M3L: Architecture for Multimedia Information Retrieval

Multimedia information retrieval systems operate on multimedia information. Multimedia information exists in text, audio, image and video forms. Existing multimedia information retrieval systems do not satisfy multimedia information needs. Information needs are only satisfied when information is searched within all information modalities of a multimedia based document and within a user specified subsets of multimedia object types. We propose a layered based architecture for multimedia information retrieval that is able to search multimedia information within multiple modalities and all subsets of multimedia object types. Architecture follows layered based architectural approach. Architecture contains three layers which are mode, model and modality. Architecture organizes system objects within three layers and also provides communication among them. We develop a prototypical multimedia information retrieval system based on proposed architecture.

Towards Optimal Fault Tolerant Scheduling in Computational Grid

Grid environment has significant challenges due to diverse failures encountered during job execution. Computational grids provide the main execution platform for long running jobs. Such jobs require long commitment of grid resources. Therefore fault tolerance in such an environment cannot be ignored. Most of the grid middleware have either ignored failure issues or have developed adhoc solutions. Most of the existing fault tolerance techniques are application dependant and causes cognitive problem. This paper examines existing fault detection and tolerance techniques in various middleware. We have proposed fault tolerant layered grid architecture with cross-layered design. In our approach Hybrid Particle Swarm Optimization (HPSO) algorithm and Anycast technique are used in conjunction with the Globus middleware. We have adopted a proactive and reactive fault management strategy for centralized and distributed environments. The proposed strategy is helpful in identifying root cause of failures and resolving cognitive problem. Our strategy minimizes computation and communication thus achieving higher reliability. Anycast limits the effect of Denial of Service/Distributed Denial of Service D(DoS) attacks nearest to the source of the attack thus achieving better security. Significant performance improvement is achieved through using Anycast before HPSO. The selection of more reliable nodes results in less overhead of checkpointing.

A Balanced Energy-Consuming and Hole-Alleviating Algorithm for Wireless Sensor Networks

In wireless sensor networks (WSNs) energy balancing and energy efficiency are the key requirements to prolong the network lifetime. In this paper, we investigate the problem of energy hole, where sensor nodes located near the sink or in some other parts of the network die very early due to unbalanced load distribution. Moreover, there is a dire need to utilize the energy resource efficiently. For this purpose, a balanced energy consuming and hole alleviating (BECHA), and energy-aware balanced energy consuming and hole alleviating (EA-BECHA) algorithms are proposed, not only to balance the load distribution of entire network, but also to utilize the energy resource efficiently. This work mainly adopts data forwarding and routing selection strategy for the entire network. An optimal distance and energy-based transmission strategy which is free of location error is adopted to forward the different size of data to the neighbors by selecting the optimal forwarder. Finally, the simulation results validate the proposed schemes by showing improvement in network lifetime, energy balancing and enhanced throughput.

Unified Multimodal Search Framework for Multimedia Information Retrieval

There is a trend towards construction of multimedia digital information resources which may hold diverse data types in the form of image, graphics, audio, video, and text based retrieval artifacts or objects. WWW is a huge multimedia information resource. Existing search mechanisms available on WWW are mostly mono-modal. Multimedia information needs are partially satisfied by using mono-modal search mechanisms. Multiple modalities of information are associated with multimedia retrieval object so multimodal search mechanisms are required for searching multimedia information resources. Existing search mechanisms available on WWW whether they are general purpose, domain specific or media specific partially fulfil multimedia information needs because they are mostly mono-modal and able to perform search with in one media type at a time. We explore with the help of multimedia object analysis that search with in all the subsets of multimedia object types is possible by using only four index types, two models of interactions and fifteen possible modes at most. A framework based on an architectural approach is proposed for multimedia information retrieval. Proposed retrieval framework is implemented. Present implementation gives query formulation and information presentation for all modes and search functionality with in few modes of multimedia search framework.

Monitoring square and circular fields with sensors using energy-efficient cluster-based routing for underwater wireless sensor networks:

In this article, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks. First one is sparsity-aware energy-efficient clustering, second one is circular sparsity-aware energy-efficient clustering, and the third one is circular depth–based sparsity-aware energy-efficient clustering routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions, whereas sparsity search algorithm is proposed to find sparse regions and density search algorithm is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet, while sink mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold ( d th ) value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counter-part schemes (depth-based routing and energy-efficient depth-based routing) in terms of energy efficiency.

Designing interactions using OAI model: A new interface modeling paradigm

Human Computer Interaction (HCI) based interface modeling techniques can be employed in designing interactions. They provide complete mechanism for the design of an interactive interface in analysis and design phases of interface development. Interface design using these techniques incorporates usability and utility aspects. Object Action Interface (OAI) model is an interaction modeling technique. Our investigation revealed that existing model lacks interface responses, change of the interface states, relationship among interface constructs and mapping of sequence of actions on sequence of objects. OAI model may not be efficiently employed in designing interactions due to the investigated shortcomings. In this study we propose an enhancement in the existing OAI model. Response is introduced in the existing OAI model that will provide an improved mechanism for the design of interactions. The proposed mechanism can be employed as a new interface modeling paradigm. This modeling paradigm will lead to better interface response, improved relationships among interface constructs and better mapping of sequence of actions on sequence of objects.

Component Based Proactive Fault Tolerant Scheduling in Computational Grid

Computational Grids have the capability to provide the main execution platform for high performance distributed applications. Grid resources having heterogeneous architectures, being geographically distributed and interconnected via unreliable network media are extremely complex and prone to different kinds of errors, failures and faults. Grid is a layered architecture and most of the fault tolerant techniques developed on grids use its strict layering approach. In this paper, we have proposed a cross-layer design for handling faults proactively. In a cross-layer design, the top- down and bottom-up approach is not strictly followed, and a middle layer can communicate with the layer below or above it [1]. At each grid layer there would be a monitoring component that would decide on predefined factors that the reliability of that particular layer is high, medium or low. Based on Hardware Reliability Rating (HRR) and Software Reliability Rating (SRR), the Middleware Monitoring Component / Cross- Layered Component (MMC/CLC) would generate a Combined Rating (CR) using CR calculation matrix rules. Each grid participating node will have a CR value generated through cross layered communication using HMC, MMC/CLC and SMC. All grid nodes will have their CR information in the form of a CR table and high rated machines would be selected for job execution on the basis of minimum CPU load along with different intensities of check pointing. Handling faults proactively at each layer of grid using cross communication model would result in overall improved dependability and increased performance with less overheads of check pointing.

A Localization Based Cooperative Routing Protocol for Underwater Wireless Sensor Networks

Localization is one of the major aspects in underwater wireless sensor networks (UWSNs). Therefore, it is important to know the accurate position of the sensor node in large scale applications like disaster prevention, tactical surveillance, and monitoring. Due to the inefficiency of the global positioning system (GPS) in UWSN, it is very difficult to localize a node in underwater environment compared to terrestrial networks. To minimize the localization error and enhance the localization coverage of the network, two routing protocols are proposed; the first one is mobile autonomous underwater vehicle (MobiL-AUV) and the second one is cooperative MobiL (CO-MobiL). In MobiL-AUV, AUVs are deployed and equipped with GPS and act as reference nodes. These reference nodes are used to localize all the nonlocalized ordinary sensor nodes in order to reduce the localization error and maximize the network coverage. CO-MobiL is presented in order to improve the network throughput by using the maximal ratio combining (MRC) as diversity technique which combines both signals, received from the source and received from the relay at the destination. It uses amplify-and-forward (AF) mechanism to improve the signal between the source and the destination. To support our claims, extensive simulations are performed.