Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based approach for extracting data from the deep web. Deep iCrawl splits the process into two phases. The first phase includes Query analysis and Query translation and the second covers vision-based extraction of data from the dynamically created deep web pages. There are several established approaches for the extraction of deep web pages but the proposed method aims at overcoming the inherent limitations of the former. This paper also aims at comparing the data items and presenting them in the required order.

Conceptualization of the Attractive Work Environment and Organizational Activity for Humans in Future Deep Mines

The purpose of this paper is to conceptualize a futureoriented human work environment and organizational activity in deep mines that entails a vision of good and safe workplace. Futureoriented technological challenges and mental images required for modern work organization design were appraised. It is argued that an intelligent-deep-mine covering the entire value chain, including environmental issues and with work organization that supports good working and social conditions towards increased human productivity could be designed. With such intelligent system and work organization in place, the mining industry could be seen as a place where cooperation, skills development and gender equality are key components. By this perspective, both the youth and women might view mining activity as an attractive job and the work environment as a safe, and this could go a long way in breaking the unequal gender balance that exists in most mines today.

An Agent-Based Scheduling Framework for Flexible Manufacturing Systems

The concept of flexible manufacturing is highly appealing in gaining a competitive edge in the market by quickly adapting to the changing customer needs. Scheduling jobs on flexible manufacturing systems (FMSs) is a challenging task of managing the available flexibility on the shop floor to react to the dynamics of the environment in real-time. In this paper, an agent-oriented scheduling framework that can be integrated with a real or a simulated FMS is proposed. This framework works in stochastic environments with a dynamic model of job arrival. It supports a hierarchical cooperative scheduling that builds on the available flexibility of the shop floor. Testing the framework on a model of a real FMS showed the capability of the proposed approach to overcome the drawbacks of the conventional approaches and maintain a near optimal solution despite the dynamics of the operational environment.

Teachers Learning about Sustainability while Co-Constructing Digital Games

Teaching and learning about sustainability is a pedagogical endeavour with various innate difficulties and increased demands. Higher education has a dual role to play in addressing this challenge: to identify and explore innovative approaches and tools for addressing the complex and value-laden nature of sustainability in more meaningful ways, and to help teachers to integrate these approaches into their practice through appropriate professional development programs. The study reported here was designed and carried out within the context of a Masters course in Environmental Education. Eight teachers were collaboratively engaged in reconstructing a digital game microworld which was deliberately designed by the researchers to be questioned and evoke critical discussion on the idea of ‘sustainable city’. The study was based on the design-based research method. The findings indicate that the teachers’ involvement in processes of co-constructing the microworld initiated discussion and reflection upon the concepts of sustainability and sustainable lifestyles.

Towards Sustainable Urban Transportation Case Studies

Climate change is one of the greatest environmental, economic, and social challenges of our time. Urban transportation has had a major negative impact on our environment—most of our air pollution comes from transport. This paper explores ways to move toward a more sustainable transport system by focusing on creating a more efficient and livable city and improving the environmental efficiency of transport activity. The analytical study covers some international examples of applying sustainable transportation and uses them to suggest a frame work to develop the transportation system in Egypt to be sustainable and more intelligent.

Metal Streak Analysis with different Acquisition Settings in Postoperative Spine Imaging: A Phantom Study

CT assessment of postoperative spine is challenging in the presence of metal streak artifacts that could deteriorate the quality of CT images. In this paper, we studied the influence of different acquisition parameters on the magnitude of metal streaking. A water-bath phantom was constructed with metal insertion similar with postoperative spine assessment. The phantom was scanned with different acquisition settings and acquired data were reconstructed using various reconstruction settings. Standardized ROIs were defined within streaking region for image analysis. The result shows increased kVp and mAs enhanced SNR values by reducing image noise. Sharper kernel enhanced image quality compared to smooth kernel, but produced more noise in the images with higher CT fluctuation. The noise between both kernels were significantly different (P

The Analysis of Radial/Axial Error Motion on a Precision Rotation Stage

Rotating stages in semiconductor, display industry and many other fields require challenging accuracy to perform their functions properly. Especially, Axis of rotation error on rotary system is significant; such as the spindle error motion of the aligner, wire bonder and inspector machine which result in the poor state of manufactured goods. To evaluate and improve the performance of such precision rotary stage, unessential movements on the other 5 degrees of freedom of the rotary stage must be measured and analyzed. In this paper, we have measured the three translations and two tilt motions of a rotating stage with high precision capacitive sensors. To obtain the radial error motion from T.I.R (Total Indicated Reading) of radial direction, we have used Donaldson's reversal technique. And the axial components of the spindle tilt error motion can be obtained accurately from the axial direction outputs of sensors by Estler face motion reversal technique. Further more we have defined and measured the sensitivity of positioning error to the five error motions.

Grouping-Based Job Scheduling Model In Grid Computing

Grid computing is a high performance computing environment to solve larger scale computational applications. Grid computing contains resource management, job scheduling, security problems, information management and so on. Job scheduling is a fundamental and important issue in achieving high performance in grid computing systems. However, it is a big challenge to design an efficient scheduler and its implementation. In Grid Computing, there is a need of further improvement in Job Scheduling algorithm to schedule the light-weight or small jobs into a coarse-grained or group of jobs, which will reduce the communication time, processing time and enhance resource utilization. This Grouping strategy considers the processing power, memory-size and bandwidth requirements of each job to realize the real grid system. The experimental results demonstrate that the proposed scheduling algorithm efficiently reduces the processing time of jobs in comparison to others.

A Hybridized Competency-Based Teacher Candidate Selection System

Teachers form the backbone of any educational system, hence selecting qualified candidates is very crucial. In Malaysia, the decision making in the selection process involves a few stages: Initial filtering through academic achievement, taking entry examination and going through an interview session. The last stage is the most challenging since it highly depends on human judgment. Therefore, this study sought to identify the selection criteria for teacher candidates that form the basis for an efficient multi-criteria teacher-candidate selection model for that last stage. The relevant criteria were determined from the literature and also based on expert input that is those who were involved in interviewing teacher candidates from a public university offering the formal training program. There are three main competency criteria that were identified which are content of knowledge, communication skills and personality. Further, each main criterion was divided into a few subcriteria. The Analytical Hierarchy Process (AHP) technique was employed to allocate weights for the criteria and later, integrated a Simple Weighted Average (SWA) scoring approach to develop the selection model. Subsequently, a web-based Decision Support System was developed to assist in the process of selecting the qualified teacher candidates. The Teacher-Candidate Selection (TeCaS) system is able to assist the panel of interviewers during the selection process which involves a large amount of complex qualitative judgments.

Strategies and Compromises: Towards an Integrated Energy and Climate Policy for Egypt

Until recently, energy security and climate change were considered separate issues to be dealt with by policymakers. The two issues are now converging, challenging the security and climate communities to develop a better understanding of how to deal with both issues simultaneously. Although Egypt is not a major contributor to the world's total GHG emissions, it is particularly vulnerable to the potential effects of global climate change such as rising sea levels and changed patterns of rainfall in the Nile Basin. Climate change is a major threat to sustainable growth and development in Egypt, and the achievement of the Millennium Development Goals. Egypt-s capacity to respond to the challenges of climate instability will be expanded by improving overall resilience, integrating climate change goals into sustainable development strategies, increasing the use of modern energy systems with reduced carbon intensity, and strengthening international initiatives. This study seeks to establish a framework for considering the complex and evolving links between energy security and climate change, applicable to Egypt.

Curbing Cybercrime by Application of Internet Users’ Identification System (IUIS) in Nigeria

Cybercrime is now becoming a big challenge in Nigeria apart from the traditional crime. Inability to identify perpetrators is one of the reasons for the growing menace. This paper proposes a design for monitoring internet users’ activities in order to curbing cybercrime. It requires redefining the operations of Internet Service Providers (ISPs) which will now mandate users to be authenticated before accessing the internet. In implementing this work which can be adapted to a larger scale, a virtual router application is developed and configured to mimic a real router device. A sign-up portal is developed to allow users to register with the ISP. The portal asks for identification information which will include bio-data and government issued identification data like National Identity Card number, et cetera. A unique username and password are chosen by the user to enable access to the internet which will be used to reference him to an Internet Protocol Address (IP Address) of any system he uses on the internet and thereby associating him to any criminal act related to that IP address at that particular time. Questions such as “What happen when another user knows the password and uses it to commit crime?” and other pertinent issues are addressed.

Key Issues and Challenges of Intrusion Detection and Prevention System: Developing Proactive Protection in Wireless Network Environment

Nowadays wireless technology plays an important role in public and personal communication. However, the growth of wireless networking has confused the traditional boundaries between trusted and untrusted networks. Wireless networks are subject to a variety of threats and attacks at present. An attacker has the ability to listen to all network traffic which becoming a potential intrusion. Intrusion of any kind may lead to a chaotic condition. In addition, improperly configured access points also contribute the risk to wireless network. To overcome this issue, a security solution that includes an intrusion detection and prevention system need to be implemented. In this paper, first the security drawbacks of wireless network will be analyzed then investigate the characteristics and also the limitations on current wireless intrusion detection and prevention system. Finally, the requirement of next wireless intrusion prevention system will be identified including some key issues which should be focused on in the future to overcomes those limitations.

Roadmapping as a Collaborative Strategic Decision-Making Process: Shaping Social Dialogue Options for the European Banking Sector

The new status generated by technological advancements and changes in the global economy raises important issues on how communities and organisations need to innovate upon their traditional processes in order to adapt to the challenges of the Knowledge Society. The DialogoS+ European project aims to study the role of and promote social dialogue in the banking sector, strengthen the link between old and new members and make social dialogue at the European level a force for innovation and change, also given the context of the international crisis emerging in 2008- 2009. Under the scope of DialogoS+, this paper describes how the community of Europe-s banking sector trade unions attempted to adapt to the challenges of the Knowledge Society by exploiting the benefits of new channels of communication, learning, knowledge generation and diffusion focusing on the concept of roadmapping. Important dimensions of social dialogue such as collective bargaining and working conditions are addressed.

Selecting Materialized Views Using Two-Phase Optimization with Multiple View Processing Plan

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance cost. Therefore, in this paper, we introduce a new approach aimed at solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that our method provides a further improvement in term of query processing cost and view maintenance cost.

GPT Onto: A New Beginning for Malaysia Gross Pollutant Trap Ontology

Ontology is widely being used as a tool for organizing information, creating the relation between the subjects within the defined knowledge domain area. Various fields such as Civil, Biology, and Management have successful integrated ontology in decision support systems for managing domain knowledge and to assist their decision makers. Gross pollutant traps (GPT) are devices used in trapping and preventing large items or hazardous particles in polluting and entering our waterways. However choosing and determining GPT is a challenge in Malaysia as there are inadequate GPT data repositories being captured and shared. Hence ontology is needed to capture, organize and represent this knowledge into meaningful information which can be contributed to the efficiency of GPT selection in Malaysia urbanization. A GPT Ontology framework is therefore built as the first step to capture GPT knowledge which will then be integrated into the decision support system. This paper will provide several examples of the GPT ontology, and explain how it is constructed by using the Protégé tool.

Machine Vision for the Inspection of Surgical Tasks: Applications to Robotic Surgery Systems

The use of machine vision to inspect the outcome of surgical tasks is investigated, with the aim of incorporating this approach in robotic surgery systems. Machine vision is a non-contact form of inspection i.e. no part of the vision system is in direct contact with the patient, and is therefore well suited for surgery where sterility is an important consideration,. As a proof-of-concept, three primary surgical tasks for a common neurosurgical procedure were inspected using machine vision. Experiments were performed on cadaveric pig heads to simulate the two possible outcomes i.e. satisfactory or unsatisfactory, for tasks involved in making a burr hole, namely incision, retraction, and drilling. We identify low level image features to distinguish the two outcomes, as well as report on results that validate our proposed approach. The potential of using machine vision in a surgical environment, and the challenges that must be addressed, are identified and discussed.

The Future Regulatory Challenges of Liquidity Risk Management

Liquidity risk management ranks to key concepts applied in finance. Liquidity is defined as a capacity to obtain funding when needed, while liquidity risk means as a threat to this capacity to generate cash at fair costs. In the paper we present challenges of liquidity risk management resulting from the 2007- 2009 global financial upheaval. We see five main regulatory liquidity risk management issues requiring revision in coming years: liquidity measurement, intra-day and intra-group liquidity management, contingency planning and liquidity buffers, liquidity systems, controls and governance, and finally models testing the viability of business liquidity models.

Web Page Watermarking: XML files using Synonyms and Acronyms

Advent enhancements in the field of computing have increased massive use of web based electronic documents. Current Copyright protection laws are inadequate to prove the ownership for electronic documents and do not provide strong features against copying and manipulating information from the web. This has opened many channels for securing information and significant evolutions have been made in the area of information security. Digital Watermarking has developed into a very dynamic area of research and has addressed challenging issues for digital content. Watermarking can be visible (logos or signatures) and invisible (encoding and decoding). Many visible watermarking techniques have been studied for text documents but there are very few for web based text. XML files are used to trade information on the internet and contain important information. In this paper, two invisible watermarking techniques using Synonyms and Acronyms are proposed for XML files to prove the intellectual ownership and to achieve the security. Analysis is made for different attacks and amount of capacity to be embedded in the XML file is also noticed. A comparative analysis for capacity is also made for both methods. The system has been implemented using C# language and all tests are made practically to get the results.

An Efficient Obstacle Detection Algorithm Using Colour and Texture

This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.

Optimizing Materials Cost and Mechanical Properties of PVC Electrical Cable-s Insulation by Using Mixture Experimental Design Approach

With the development of the Polyvinyl chloride (PVC) products in many applications, the challenge of investigating the raw material composition and reducing the cost have both become more and more important. Considerable research has been done investigating the effect of additives on the PVC products. Most of the PVC composites research investigates only the effect of single/few factors, at a time. This isolated consideration of the input factors does not take in consideration the interaction effect of the different factors. This paper implements a mixture experimental design approach to find out a cost-effective PVC composition for the production of electrical-insulation cables considering the ASTM Designation (D) 6096. The results analysis showed that a minimum cost can be achieved through using 20% virgin PVC, 18.75% recycled PVC, 43.75% CaCO3 with participle size 10 microns, 14% DOP plasticizer, and 3.5% CPW plasticizer. For maximum UTS the compound should consist of: 17.5% DOP, 62.5% virgin PVC, and 20.0% CaCO3 of particle size 5 microns. Finally, for the highest ductility the compound should be made of 35% virgin PVC, 20% CaCO3 of particle size 5 microns, and 45.0% DOP plasticizer.