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Isu atau masalah rasuah menjadi topik utama sama ada di peringkat antarabangsa mahupun di peringkat dalam negara. Pertubuhan Bangsa- bangsa Bersatu menegaskan komitmen komuniti antarabangsa bertegas untuk mencegah dan mengawal rasuah melalui buku bertajuk United Nations Convention against Corruption. Hal yang sama berlaku di Malaysia. Melalui pernyataan visi oleh mantan Perdana Menteri Malaysia, Tun Dr. Mahathir bin Mohamed memberikan indikasi bahawa kerajaan Malaysia komited untuk mencapai aspirasi agar Malaysia dikenali kerana integriti dan bukannya rasuah. Justeru, tujuan penulisan bab ini adalah untuk membincangkan rasuah dari beberapa sudut termasuk perbincangan dari sudut agama Islam, faktor-faktor berlakunya gejala rasuah, dan usaha-usaha yang dijalankan di Malaysia untuk membanteras gejala rasuah. Perkara ini penting bagi mengenalpasti penjawat awam menanamkan keyakinan dalam melaksanakan tanggungjawab dengan menghindari diri daripada rasuah agar mereka sentiasa peka mengutamakan kepentingan awam

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

Structural Changes in Data Communication in Wireless Sensor Networks

Wireless sensor networks are an important technology for making distributed autonomous measures in hostile or inaccessible environments. Among the challenges they pose, the way data travel among them is a relevant issue since their structure is quite dynamic. The operational topology of such devices can often be described by complex networks. In this work, we assess the variation of measures commonly employed in the complex networks literature applied to wireless sensor networks. Four data communication strategies were considered: geometric, random, small-world, and scale-free models, along with the shortest path length measure. The sensitivity of this measure was analyzed with respect to the following perturbations: insertion and removal of nodes in the geometric strategy; and insertion, removal and rewiring of links in the other models. The assessment was performed using the normalized Kullback-Leibler divergence and Hellinger distance quantifiers, both deriving from the Information Theory framework. The results reveal that the shortest path length is sensitive to perturbations.Comment: 12 pages, 4 figures, Central European Journal of Physic

Constrained K-means and Genetic Algorithm-based Approaches for Optimal Placement of Wireless Structural Health Monitoring Sensors

Optimal placement of wireless structural health monitoring (SHM) sensors has to consider modal identification accuracy and power efficiency. In this study, two-tier wireless sensor network (WSN)-based SHM systems with clusters of sensors are investigated to overcome this difficulty. Each cluster contains a number of sensor nodes and a cluster head (CH). The lower tier is composed of sensors communicating with their associated CHs, and the upper tier is composed of the network of CHs. The first step is the optimal placement of sensors in the lower tier via the effective independence method by considering the modal identification accuracy. The second step is the optimal placement of CHs in the upper tier by considering power efficiency. The sensors in the lower tier are partitioned into clusters before determining the optimal locations of CHs in the upper tier. Two approaches, a constrained K-means clustering approach and a genetic algorithm (GA)-based clustering approach, are proposed in this study to cluster sensors in the lower tier by considering two constraints: (1) the maximum data transmission distance of each sensor; (2) the maximum number of sensors in each cluster. Given that each CH can only manage a limited number of sensors, these constraints should be considered in practice to avoid overload of CHs. The CHs in the upper tier are located at the centers of the clusters determined after clustering sensors in the lower tier. The two proposed approaches aim to construct a balanced size of clusters by minimizing the number of clusters (or CHs) and the total sum of the squared distance between each sensor and its associated CH under the two constraints. Accordingly, the energy consumption in each cluster is decreased and balanced, and the network lifetime is extended. A numerical example is studied to demonstrate the feasibility of using the two proposed clustering approaches for sensor clustering in WSN-based SHM systems. In this example, the performances of the two proposed clustering approaches and the K-means clustering method are also compared. The two proposed clustering approaches outperform the K-means clustering method in terms of constructing balanced size of clusters for a small number of clusters. Doi: 10.28991/CEJ-2022-08-12-01 Full Text: PD

Routing Design Issues in Heterogeneous Wireless Sensor Network

WSN has important applications such as habitat monitoring, structural health monitoring, target tracking in military and many more. This has evolved due to availability of sensors that are cheaper and intelligent but these are having battery support. So, one of the major issues in WSN is maximization of network life. Heterogeneous WSNs have the potential to improve network lifetime and also provide higher quality networking and system services than the homogeneous WSN. Routing is the main concern of energy consumption in WSN. Previous research shows that performance of the network can be improve significantly using protocol of hierarchical HWSN. However, the appropriateness of a particular routing protocol mainly depends on the capabilities of the nodes and on the application requirements. This study presents different aspects of Heterogeneous Wireless Sensor network and design issues for routing in heterogeneous environment. Different perspectives from different authors regarding energy efficiency based on resource heterogeneity for heterogeneous wireless sensor networks have been presented

Design Methods for the Cluster Head Selection in WSNs based on Node Residual Status to Enhance the Lifetime and Performance of the Network

This study introduces a novel approach to enhance Wireless Sensor Networks (WSNs) by proposing an energy-balancing algorithm and a unique Cluster Head (CH) selection strategy based on nodes' residual energy states. Unlike conventional methods, our algorithm dynamically distributes energy across nodes, mitigating localized energy depletion and extending the overall network lifetime. The Knapsack method optimizes resource allocation considering energy constraints. Performance evaluations, conducted using NS2.34/2.35, compare our approach with a widely used energy-balancing technique in WSNs. Our results showcase significant improvements. Notably, our algorithm achieves a remarkable 20% increase in network lifetime and a 25% enhancement in data throughput, demonstrating its effectiveness in optimizing resource usage. Furthermore, a 30% reduction in latency ensures faster and more responsive data transmission. The CH selection method positively impacts network coverage, resulting in a substantial 20% expansion of monitored areas. Compared to the existing technique, our proposed strategy consistently outperforms in key metrics, indicating its superior efficacy. This research contributes to advancing WSN sustainability and efficiency, particularly in scenarios prioritizing energy efficiency. The proposed algorithm emerges as a promising solution, demonstrating its potential to optimize WSN performance and longevity. Furthermore, the network simulator (NS) is used to examine the performance of the network with the NS2.34/2.35 version. The results exhibit the dominance of the projected method compared to existing techniques. Additionally, the method shows adaptability to dynamic network conditions, ensuring effective CH reselection in the presence of node failures or energy fluctuations

Effect of steel fibre volume fraction on thermal performance of lightweight foamed mortar (LFM) at ambient temperature

Lightweight foamed mortar (LFM) has grow into utmost commercial building material in the construction industry for non-structural and semi-structural applications owing to its reduced self-weight, flowability, stability and excellent thermal insulation properties. Hence, this study was conducted with the aims to develop an alternative for conventional concrete bricks and blocks for non-structural and semi-structural applications of masonry. Lightweight foamed mortar (LFM) is either a cement paste or mortar, relegated as lightweight concrete, in which suitable foaming agent entraps the air-voids in mortar. It therefore has a wide range of applications such as material for wall blocks or panels, floor & roof screeds, trench reinstatement, road foundations and voids filling. This research focuses on experimental investigation of thermal properties of LFM with inclusion of relatively low volume fraction (0.2% and 0.4%) of steel fibre at ambient temperature. There are three parameters will be scrutinized such as thermal conductivity, thermal diffusivity as well as the specific heat capacity. There are two densities of 600kg/m3 and 1200kg/m3 had been cast and tested. The mix design proportion of LFM used for cement, aggregate and water ratio was 1: 1.5:0.45. The experimental results had indicated that the thermal conductivity, thermal diffusivity and specific heat value slightly higher than control mix due to the addition of steel fibres. For instance, thermal conductivity, diffusivity and specific heat of 600 kg/m3 density control mix were 0.212W/mK, 0.477mm2/s and 545 J/kg◦C respectively. When 0.2% volume fraction of steel fiber was added in the mix of 600 kg/m3 density, the value of thermal conductivity, diffusivity and specific heat were increased to 0.235W/mK, 0.583mm2/s and 578 J/kg◦C correspondingly. This is due to the characteristic of the steel fibre application in which steel fibre is good as heat conductor and excellent in absorbing heat. Therefore there is a potential of utilizing steel fiber in cement based material like LFM for components that needs excellent heat absorption capacity