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Corporate and Shariah Governance Mechanisms and Earnings Quality in Islamic Banks: A Review and Evaluation of Patterns
No full text
Comparative Study of Physico-Chemical Analyses of Different Water Resources in Setiu Wetland, Terengganu.
No full textPhysico-chemical properties of water are usually reflecting the functioning
of an aquatic ecosystem like Setiu Wetland, Terengganu. Therefore, this study was
conducted to determine the physico-chemical properties and chemical nature of
their water resources (trench, rivers, drainage and tap water) and their impact on
sustainable water resource in Setiu Wetland, Terengganu. A total of 12 water
samples were collected aseptically from in this area and the field work was conducted from August to September 2015. In-situ measurements of physico-chemical
properties of the water samples were recorded using YSI Professional Plus Parameter
(XYLEM, USA) with multi-sensor probe. The analyses of physico-chemical of
water include of water temperature, barometric pressure, dissolved oxygen, specific
conductance, conductance, redox potential, total suspended solids, salinity and pH.
In comparison to previous study conducted in 2008, most of the parameters showed
that water quality at Setiu Wetland, Terengganu remained Class 1 based on National
Water Quality Standards for Malaysia. In conclusion, the various water resources in
Setiu Wetland was in very good condition indicating that the habitats in Setiu
Wetlands have conditions suitable to support a biotic community. Further study
should be carried out in monitoring water qualities of the water resources at Malaysia
to increase safety of water consumption
Anthropometry correlation towards archery performance
No full textThis chapter assesses the association of a selection of anthropometry parameters in identifying HPA and LPA. It was
shown that the selected parameters, i.e. abdominal circumference, arm span, calf circumference, height, hip
circumference, thigh circumference and weight, are essential in the identification of potential of the archers.
Furthermore, it was demonstrated that the linear SVM variation model provided the best prediction capability
amongst the other evaluated SVM models. © 2019, The Author(s), under exclusive license to Springer Nature
Singapore Pte Ltd
An Enhanced Adaptive Duty Cycle Scheme for Optimum Data Transmission in Wireless Sensor Network
No full textIn wireless sensor network (WSN), energy efficiency is the most fundamental issue that requires special attention during the design of communication
protocols. Energy waste is largely contributed by collision, idle listening, overhearing
and over-emitting that occur at medium access control layer. One of the most widely
used mechanism energy saving in WSN, specifically at MAC layer is Duty Cycle.
Duty Cycling coordinates the sleep/wake-up time sensor nodes to maximize the network lifetime while achieving specific application goals such as high throughput or
low latency. Most existing works focused more on static duty cycling which cannot
guarantee the desire end-to-end delay at varying network condition. In applications
with specific delay requirement, the duty cycling of every node should be adjusted
separately ay runtime depending on the network conditions to achieve desired delay
guarantees and energy efficiency. Recently, a few adaptive duty cycle schemes were
introduced. Although energy consumption has been reduced by some degree, it leaves
an open ended to the degradation of quality of service. In this research, we find
the optimum data transmission in WSN. We purpose a variant of an adaptive duty
cycle scheme for MAC protocol. By adaptive, these factors determine the duration
of node’s listen period for various packet transmission scenarios and requirements.
This result in less waiting time for each packet to be transferred as well as reduce
the re-transmission of undelivered packets. We anticipate this proposed method will
improve the energy consumption and QoS of each node and thus the WSN. The
success of this project will be contributed to the performance improvement and
cost-effective sensing device
Sustainable development of Tasik Kenyir eco-tourism using system dynamic
No full textThe sustainable development of Tasik Kenyir eco-tourism depends on the availibility of spatially explicit information on
the state and trends of ecosystems and their services. Thus, we develop an interactive dynamic model of Tasik Kenyir
Eco-Tourism that links ecological and economic systems, and generated the effects of the short and long terms
besides to determine the direction of development and conservation in Tasik Kenyir development policies. In this
study, Tasik Kenyir eco-tourism coins Macro Management Framework for Tasik Kenyir Tourism Dynamics consist of
four different subsystem; Toursim Activity, Development of Tasik Kenyir (infrastucture and tourism activities), Waste
Generated and Environment Sustainability (flora and fauna). The Model developed reveals that sustainable
development of Tasik Kenyir eco-tourism requires continuous prolonged effort and insight towards creating a balance
between social, economic and environmental developments. © Springer Nature Switzerland AG 2019
Identity and Ketuanan Melayu in Malaysia: Effects of Globalization and Challenges to the Ketuanan Melayu
No full textDistributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
No full textNetwork monitoring system consists of large data streams, distributed architecture, and multiple computers that are
geographically located all over the world caused a difficulty to detect abnormalities in the system. In addition, when
handling network traffic, the data in network is fast incoming and requires an online learning where immediately
response and predict the pattern of network traffic for classification once there is an event or request occur. Therefore,
this paper aims to develop an effective and efficient network anomaly detection system by using distributed online
averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome
these issues. The finding of DOAODE algorithm for multi-class classification is high in accuracy with average 83% and
fast to train the network traffic recorded less than ten seconds and takes shorter time when the number of nodes
increase