No abstract

Soil moisture is one of the contributing factors that accelerates soil erosion and landslide events due to the increase in pore pressure which eventually reduces the soil strength. For landslide prediction and monitoring purposes, large-scale measurement involves estimating the soil moisture. However, estimation of soil moisture usually involves point-based measurements at a particular site and time, which is difficult to capture the spatial and temporal soil moisture dynamics. This paper presents the estimation of the SMI using Landsat 8 images for prediction and monitoring of landslide events in Ulu Kelang, Selangor. The selected SMI map for dry, moist, and wet seasons are obtained from climatology rainfall analysis over 20-year periods (1998-2017). SMI is assessed based on remote sensing data which are land surface temperature (LST) and normalized difference vegetation index (NDVI) using GIS software. Overall results indicated that rainfall distribution is high during inter-monsoon (IM), followed by northeast monsoon (NEM) and southwest monsoon (SWM) season. High rainfall distribution is a direct contributor towards SMI condition. Results from simulation show that April 2017 is known to have the highest SMI estimation season and selected to be the best SMI mapping parameter to be applied for prediction and monitoring of landslide events.

In this paper, we propose an uplink (UL) scheduling algorithm for Mobile WiMAX (IEEE 802.16e) system that satisfies the throughput and delay for the real and non real time application taking the adaptive modulation and coding scheme (MCS) into consideration. The proposed algorithm works by adjusting the threshold which is imposed on the nrtPS queue. The threshold value here represents the number of bandwidth request messages in the nrtPS queue. The algorithm then allocate the resources in two stages: The inter-class scheduling allocates the resources to different classes of service in accordance to the threshold based priority while the intra-class scheduling allocates the resources within the same class with the exhaustive service strategy. Finally, the simulation results validate the propose algorithm, and show that higher system throughput as well as lower delay and delay jitter can be achieved compared to other existing approaches.

Landslide can be triggered by intense or prolonged rainfall. Precipitation data obtained from ground-based observation is very accurate and commonly used to do analysis and landslide prediction. However, this approach is costly with its own limitation due to lack of density of ground station, especially in mountain area. As an alternative, satellite derived rainfall techniques have become more favorable to overcome these limitations. Moreover, the satellite derived rainfall estimation needs to be validated on its accuracy and its capability to predict landslide which presumably triggered by rainfall. This paper presents the investigation of using the TRMM-3B42V7 data in comparison to the available rain-gauge data in Ulu Kelang, Selangor. The monthly average rainfall, cumulative rainfall and rainfall threshold analysis from 1998 to 2011 is compared using quantitative statistical criteria (Pearson correlation, bias, root mean square error, mean different and mean). The results from analysis showed that there is a significant and strong positive correlation between the TRMM 3B42V7 and rain gauge data. The threshold derivative from the satellite products is lower than the rain gauge measurement. The findings indicated that the proposed method can be applied using TRMM satellite estimates products to derive rainfall threshold for the possible landslide occurrence.

With the rapid development of today’s communication technology, the need for a system capable to improve spectral efficiency, high data rates and at the same time can reduce inter-symbol interference (ISI) is necessary. Orthogonal Frequency Division Multiplexing (OFDM) meet all the requirements needed. However, the high peak to average power ratio (PAPR) has become its major obstacle. This paper is focusing on the development of Median Codeword Shift (MCS), which a new PAPR reduction technique with the capability to reduce the computational complexity of the system. This can be achieved through codeword structure alterization and bit position manipulation by utilizing the circulant shift process. The simulation results revealed that the proposed technique overwhelm conventional OFDM and SCS with 24% improvement and 0.5 dB gap from SCS. In fact, the proposed technique possess a lower computational complexity by reducing 16.67% of the use of IFFT block in the system in contrast with SCS technique.