Pembangunan modul pembelajaran autocad dan kajian penerimaan pelajar. Satu kajian kes di Politeknik Kota Bharu

Modul Pengajaran dan Pembelajaran AutoCAD (MPP) merupakan satu media pengajaran yang mengandungi asas-asas mengenai komputer, perisian AutoCAD 2000 dan langkah-langkah berperingkat membuat lukisan teknikal menggunakan AutoCAD 2000. Kajian ini adalah bertujuan untuk menilai sejauh mana MPP ini boleh digunakan dalam proses pengajaran dan pembelajaran dalam aspek kesesuaian isi kandungan, sifat mesra pengguna dan kebolehlaksanaannya. Respondan untuk kajian ini ialah seramai 42 orang pelajar Diploma Kejuruteraan Elektrik Politeknik Kota Bharu. Untuk kajian ini instrumen yang digunakan ialah borang soal selidik di mana penilaian dilakukan berdasarkan persepsi responden terhadap MPP. Data-data yang dikumpulkan dianalisis menggunakan SPSS VI1.0 yang melibatkan skor min. Hasil kajian melaporkan dapatan yang diperolehi berkenaan penerimaan terhadap MPP. Hasil dapatan kajian menunjukkan penerimaan yang positif terhadap MPP oleh pelajar dan ianya mempimyai kebolehlaksanaan yang tinggi (skor min = 3.96) untuk diaplikasikan dalam proses pengajaran dan pembelajaran. Walaubagaimanapun pengkaji percaya MPP ini mempunyai ruang untuk penambahbaikan seperti saranan oleh penilai yang mengesahkan MPP ini agar ia lebih menarik dan sesuai digunakan pada masa depan

Impacts of trends and uncertainties in river flooding due to climate change

Projected climate changes will have an effect on frequencies and duration of\ud river flooding and therefore on design criteria for dikes or on risk assessment. In\ud addition to existing sources of uncertainty, extremes and variability of climatological\ud input will change. To deal with this problem the purpose of this project can be split into\ud two main parts. First, to identify possible effects of climate changes on extreme\ud discharges of rivers and particularly the uncertainty involved. Second, to determine the\ud appropriate level of modelling needed to predict such effects taking into account the\ud uncertainties. The major subsystems are climate, catchment and river. Important aspects\ud are the additional uncertainty introduced by each subsystem and the appropriate level of\ud modelling a subsystem. In this paper some preliminary excersises to address these\ud questions with respect to catchment and river are shown, based on very schematic\ud models not representing any particular catchment

Time tracking of different cropping patterns using Landsat images under different agricultural systems during 1990-2050 in Cold China

Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and associated environmental effects. The Cold China contains different agricultural systems (state and private farming), and such systems could lead to different cropping patterns. So far, such changes have not been revealed yet. Based on the Landsat images, this study tracked cropping information in five-year increments (1990-1995, 1995-2000, 2000-2005, 2005-2010, and 2010-2015) and predicted future patterns for the period of 2020-2050 under different agricultural systems using developed method for determining cropland patterns. The following results were obtained: The available time series of Landsat images in Cold China met the requirements for long-term cropping pattern studies, and the developed method exhibited high accuracy (over 91%) and obtained precise spatial information. A new satellite evidence was observed that cropping patterns significantly differed between the two farm types, with paddy field in state farming expanding at a faster rate (from 2.66 to 68.56%) than those in private farming (from 10.12 to 34.98%). More than 70% of paddy expansion was attributed to the transformation of upland crop in each period at the pixel level, which led to a greater loss of upland crop in state farming than private farming (9505.66 km(2) vs. 2840.29 km(2)) during 1990-2015. Rapid cropland reclamation is projected to stagnate in 2020, while paddy expansion will continue until 2040 primarily in private farming in Cold China. This study provides new evidence for different land use change pattern mechanisms between different agricultural systems, and the results have significant implications for understanding and guiding agricultural system development

A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

Drought is a complex stochastic natural hazard caused by prolonged shortage of rainfall. Several environmental factors are involved in determining drought classes at the specific monitoring station. Therefore, efficient sequence processing techniques are required to explore and predict the periodic information about the various episodes of drought classes. In this study, we proposed a new weighting scheme to predict the probability of various drought classes under Weighted Markov Chain (WMC) model. We provide a standardized scheme of weights for ordinal sequences of drought classifications by normalizing squared weighted Cohen Kappa. Illustrations of the proposed scheme are given by including temporal ordinal data on drought classes determined by the standardized precipitation temperature index (SPTI). Experimental results show that the proposed weighting scheme for WMC model is sufficiently flexible to address actual changes in drought classifications by restructuring the transient behavior of a Markov chain. In summary, this paper proposes a new weighting scheme to improve the accuracy of the WMC, specifically in the field of hydrology

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover