Cluster identification and separation in the growing self-organizing map: application in protein sequence classification

Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. Unlike the traditional SOM, GSOM has a dynamic structure which allows nodes to grow reflecting the knowledge discovered from the input data as learning progresses. The spread factor parameter (SF) in GSOM can be utilized to control the spread of the map, thus giving an analyst a flexibility to examine the clusters at different granularities. Although GSOM has been applied in various areas and has been proven effective in knowledge discovery tasks, no comprehensive study has been done on the effect of the spread factor parameter value to the cluster formation and separation. Therefore, the aim of this paper is to investigate the effect of the spread factor value towards cluster separation in the GSOM. We used simple k-means algorithm as a method to identify clusters in the GSOM. By using Davies–Bouldin index, clusters formed by different values of spread factor are obtained and the resulting clusters are analyzed. In this work, we show that clusters can be more separated when the spread factor value is increased. Hierarchical clusters can then be constructed by mapping the GSOM clusters at different spread factor values.

Urban surface temperature behaviour and heat island effect in a tropical planned city

 Putrajaya is a model city planned with concepts of a "city in the garden" and an "intelligent city" in the tropics. This study presents the behaviour of the surface temperature and the heat island effect of Putrajaya. Findings show that heat island intensity is 2 °C on average at nighttime and negligible at daytime. But high surface temperature values were recorded at the main boulevard due to direct solar radiation incident, street orientation in the direction of northeast and southwest and low building height-to-street width ratio. Buildings facing each other had cooling effect on surfaces during the morning and evening hours; conversely, they had a warming effect at noon. Clustered trees along the street are effective in reducing the surface temperature compared to scattered and isolated trees. Surface temperature of built up areas was highest at noon, while walls and sidewalks facing northwest were hottest later in the day. Walls and sidewalks that face northwest were warmer than those that face southeast. The surface temperatures of the horizontal street surfaces and of vertical façades are at acceptable levels relative to the surface temperature of similar surfaces in mature cities in subtropical, temperate and Mediterranean climates. © 2014 Springer-Verlag Wien.

Packet faking attack: a novel attack and detection mechanism in OppNets

 Security is a major challenge in Opportunistic Networks (OppNets) due to its characteristics of being an open medium with dynamic topology, there is neither a centralized management nor clear lines of defence. A packet dropping attack is one of the major security threats in OppNets as neither source nodes nor destination nodes have any knowledge of when or where a packet will be dropped. In this paper, we present a novel attack and detection mechanism against a special type of packet dropping where the malicious node drops one packet or more and injects a new fake packet instead. Our novel detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea; the creation time of each packet. Significant results show this robust mechanism achieves a very high accuracy and detection rate.

Defense against packet dropping attacks in opportunistic networks

Opportunistic networks (OppNets) are an interesting topic that are seen to have a promising future. Many protocols have been developed to accommodate the features of OppNets such as frequent partitions, long delays, and no end-to-end path between the source and destination nodes. Embedding security into these protocols is challenging and has taken a lot of attention in research. One of the attacks that OppNets are exposed to is the packet dropping attack, where the malicious node attempts to drop some packets and forwards an incomplete number of packets which results in the distortion of the message. To increase the security levels in OppNets, this paper presents an algorithm developed to detect packet dropping attacks, and finds the malicious node that attempted the attack. The algorithm detects the attack by using an indicative field in the header section of each packet; the indicative field has 3 sub fields - the identification field, the flag field, and the offset field. These 3 fields are used to find if a node receives the complete original number of packets from the previous node. The algorithm will have the advantage of detecting packets dropped by each intermediate node, this helps solve the difficulties of finding malicious nodes by the destination node only.

A multilevel trust management framework for service oriented environment

In service-oriented computing applications, trust management systems are emerging as a promising technology to improve the e-commerce consumers and provider's relationship. Both consumers and providers need to evaluate the trust levels of potential partners before engaging in interactions. The accuracy of trust evaluation greatly affects the success rate of the interaction. This paper addresses the threats and challenges that can compromise the reliability of the current trust management system. This paper studies and examines the importance of the trust factors of the trust management framework, specifically in dealing with malicious feedback ratings from e-commerce users. To improve the reliability of the trust management systems, an approach that addresses feedback-related vulnerabilities is paramount. A multilevel trust management system computes trust by combining different types of information. Using this combination, we introduce a multilevel framework for a new interactive trust management to improve the correctness in estimate of trust information.

Digital library service quality assessment model

With the introduction of digital library services, the quality of service (QoS) has become paramount importance for evaluating the performance of the digital library service provisioning. Various models and frameworks have been proposed to evaluate digital library QoS. However, the prevalent research concentration in QoS for digital library is on the dimensions of the perspective of users’ perception. In this paper, we address the same research problem from a different dimension which is from the perspective of the digital service providers. To this end, we propose a new model suitable for evaluating the performance of digital library services. We argue that the level of QoS provided by the digital service providers have direct impact on the perception and satisfaction of the digital service end-users.

Service level agreements for the digital library

Digital libraries offer a massive set of digital services to geographically distributed library patrons. The digital services are commonly sourced from third-party service providers for charge. As externally sourced digital services are becoming prevalence, issues regarding their quality assessment are gaining critical importance. Unfortunately, sourcing digital services from external providers has brought with it stringent quality of service (QoS) demand from the library service users. Currently, there is no way for ensuring QoS between the digital service providers and the library management. In this paper, we propose service level agreements (SLAs) to capture the QoS requirements of the digital service users and the commitments, as well as adherence of the digital service providers.

Extending scheduling algorithms to minimise the impact of bounded uncertainty using interval programming

 This research proposed a new methodology to extend algorithms to accept interval-based uncertain parameters. The methodology is applied on scheduling algorithms, including heuristic and meta-heuristic algorithms and produced optimal results with higher accuracy. The research outcomes are effective for decision making process using uncertain or predicted data.

Impact of Assurance of Learning (AOL) in programming course for novices

One of the aims of any higher education institution is to align its curriculum with program learning goals. Programs which ensure proper learning have positive effects on students, instructors, departments and also on the higher education institution itself. This paper discusses the implementation and effects of Assurance Of Learning (AOL) processes on introductory programming (IP) courses. It elaborates five stages of AOL to align program learning goals with IP curriculum. Then, it discusses how the AOL process identifies shortcomings in the assessment methods of IP courses. Furthermore, it enlightens how the assessment findings, as a result of the AOL process, provide mechanisms to address the drawbacks during the delivery of such courses. Feedback on