Mengenal pasti masalah pemahaman dan hubungannya dengan latar belakang matematik, gaya pembelajaran, motivasi dan minat pelajar terhadap bab pengawalan kos makanan di Sekolah Menengah Teknik (ert) Rembau: satu kajian kes.

Kajian ini dijalankan untuk mengkaji hubungan korelasi antara latar belakang Matematik, gaya pembelajaran, motivasi dan minat dengan pemahaman pelajar terhadap bab tersebut. Responden adalah seramai 30 orang iaitu terdiri daripada pelajar tingkatan lima kursus Katering, Sekolah Menengah Teknik (ERT) Rembau, Negeri Sembilan. Instrumen kajian adalah soal selidik dan semua data dianalisis menggunakan program SPSS versi 10.0 untuk mendapatkan nilai min dan nilai korelasi bagi memenuhi objektif yang telah ditetapkan. Hasil kajian ini menunjukkan bahawa hubungan korelasi antara gaya pembelajaran pelajar terhadap pemahaman pelajar adalah kuat. Manakala hubungan korelasi antara latar belakang Matematik, motivasi dan minat terhadap pemahaman pelajar adalah sederhana. Nilai tahap min bagi masalah pemahaman pelajar, latar belakang Matematik, gaya pembelajaran, motivasi dan minat terhadap bab Pengawalan Kos Makanan adalah sederhana. Kajian ini mencadangkan penghasilan satu Modul Pembelajaran Kendiri bagi bab Pengawalan Kos Makanan untuk membantu pelajar kursus Katering dalam proses pembelajaran mereka

Clustering algorithms for sensor networks and mobile ad hoc networks to improve energy efficiency

Includes bibliographical references (leaves 161-172).Many clustering algorithms have been proposed to improve energy efficiency of ad hoc networks as this is one primary challenge in ad hoc networks. The design of these clustering algorithms in sensor networks is different from that in mobile ad hoc networks in accordance with their specific characteristics and application purposes. A typical sensor network, which consists of stationary sensor nodes, usually has a data sink because of the limitation on processing capability of sensor nodes. The data traffic of the entire network is directional towards the sink. This directional traffic burdens the nodes/clusters differently according to their distance to the sink. Most clustering algorithms assign a similar number of nodes to each cluster to balance the burden of the clusters without considering the directional data traffic. They thus fail to maximize network lifetime. This dissertation proposes two clustering algorithms. These consider the directional data traffic in order to improve energy efficiency of homogeneous sensor networks with identical sensor nodes and uniform node distribution. One algorithm is for sensor networks with low to medium node density. The other is for sensor networks with high node density. Both algorithms organize the clusters in such a way that the cluster load is proportional to the cluster energy stored, thereby equalizing cluster lifetimes and preventing premature node/cluster death. Furthermore, in a homogeneous sensor network with low to medium node density, the clusterhead is maintained in the central area of the cluster through re-clustering without ripple effect to save more energy. The simulation results show that the proposed algorithms improve both the lifetime of the networks and performance of data being delivered to the sink. A typical mobile ad hoc network, which usually consists of moveable nodes, does not have a data sink. Existing energy-efficient clustering algorithms maintain clusters by periodically broadcasting control messages. In a typical mobile ad hoc network, a greater speed of node usually needs more frequent broadcasting. To efficiently maintain the clusters, the frequency of this periodic broadcasting needs to meet the requirement of the potentially maximum speed of node. When the node speed is low, the unnecessary broadcasting may waste significant energy. Furthermore, some clustering algorithms limit the maximum cluster size to moderate the difference in cluster sizes. Unfortunately, the cluster sizes in these algorithms still experience significant difference. The larger clusters will have higher burdens. Some clustering algorithms restrict the cluster sizes between the maximum and minimum limits. The energy required to maintain these clusters within the maximum and minimum sizes is quite extensive, especially when the nodes are moving quickly. Thus, energy efficiency is not optimized

Resource Allocation in Relay Enhanced Broadband Wireless Access Networks

The use of relay nodes to improve the performance of broadband wireless access (BWA) networks has been the subject of intense research activities in recent years. Relay enhanced BWA networks are anticipated to support multimedia traffic (i.e., voice, video, and data traffic). In order to guarantee service to network users, efficient resource distribution is imperative. Wireless multihop networks are characterized by two inherent dynamic characteristics: 1) the existence of wireless interference and 2) mobility of user nodes. Both mobility and interference greatly influence the ability of users to obtain the necessary resources for service. In this dissertation we conduct a comprehensive research study on the topic of resource allocation in the presence of interference and mobility. Specifically, this dissertation investigates the impact interference and mobility have on various aspects of resource allocation, ranging from fairness to spectrum utilization. We study four important resource allocation algorithms for relay enhanced BWA networks. The problems and our research achievements are briefly outlined as follows. First, we propose an interference aware rate adaptive subcarrier and power allocation algorithm using maximum multicommodity flow optimization. We consider the impact of the wireless interference constraints using Signal to Interference Noise Ratio (SINR). We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating the impact of interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution. Second, we investigate the benefits of decoupled optimization of interference aware routing and scheduling using SINR and spatial reuse to improve the overall achievable throughput. We model the routing optimization problem as a linear program using maximum concurrent flows. We develop an optimization formulation to schedule the link traffic such that interference is mitigated and time slots are reused appropriately based on spatial TDMA (STDMA). The scheduling problem is shown to be NP-hard and is solved using the column generation technique. We compare our formulations to conventional counterparts in the literature and show that our approach guarantees higher throughput by mitigating the effect of interference effectively. Third, we investigate the problem of multipath flow routing and fair bandwidth allocation under interference constraints for multihop wireless networks. We first develop a novel isotonic routing metric, RI3M, considering the influence of interflow and intraflow interference. Second, in order to ensure QoS, an interference-aware max-min fair bandwidth allocation algorithm, LMX:M3F, is proposed where the lexicographically largest bandwidth allocation vector is found among all optimal allocation vectors while considering constraints of interference on the flows. We compare with various interference based routing metrics and interference aware bandwidth allocation algorithms established in the literature to show that RI3M and LMX:M3F succeed in improving network performance in terms of delay, packet loss ratio and bandwidth usage. Lastly, we develop a user mobility prediction model using the Hidden Markov Model(HMM) in which prediction control is transferred to the various fixed relay nodes in the network. Given the HMM prediction model, we develop a routing protocol which uses the location information of the mobile user to determine the interference level on links in its surrounding neighborhood. We use SINR as the routing metric to calculate the interference on a specific link (link cost). We minimize the total cost of routing as a cost function of SINR while guaranteeing that the load on each link does not exceed its capacity. The routing protocol is formulated and solved as a minimum cost flow optimization problem. We compare our SINR based routing algorithm with conventional counterparts in the literature and show that our algorithm reinforces routing paths with high link quality and low latency, therefore improving overall system throughput. The research solutions obtained in this dissertation improve the service reliability and QoS assurance of emerging BWA networks

A Cluster Based Mobility Prediction Scheme for Ad hoc networks

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