Digital image is considered as a powerful tool to carry and transmit information between people. Thus, it attracts the attention of large number of researchers, among them those interested in preserving the image features from any factors that may reduce the image quality. One of these factors is the noise which affects the visual aspect of the image and makes others image processing more difficult. Thus far, solving this noise problem remains a challenge for the researchers in this field. A lot of image denoising techniques have been introduced in order to remove the noise by taking care of the image features; in other words, getting the best similarity to the original image from the noisy one. However, the findings are still inconclusive. Beside the enormous amount of researches and studies which adopt several mathematical concepts (statistics, probabilities, modeling, PDEs, wavelet, fuzzy logic, etc.), there is also the scarcity of review papers which carry an important role in the development and progress of research. Thus, this review paper intorduce an overview of the different fundamental approaches that yield the several image-denoising techniques, presented with a new classification. Furthermore, the paper presents the different evaluation tools needed on the comparison between these techniques in order to facilitate the processing of this noise problem, among a great diversity of techniques and concepts.

Environmental awareness has received much attention in recent years due to human population growth, even though science is improving every day. Still, that improvement comes with risks that can be avoided with a little bit of knowledge. Understanding the public’s environmental awareness is essential to inform government approaches to addressing this issue. This study presents a cross-sectional survey of young generations, Universiti Malaysia Perlis (UniMAP) students between the ages of 20 and 25, to examine the perception, awareness and opinions of Malaysian students about the environment. The survey consisted of three sections, which included information on socio-demographic information, information on public perception of the environment, information on public awareness of the environment and its related impacts, and information on environmental attitudes and recommendations to address some of the related environmental issues. The results show that the value of environmental awareness and knowledge is good, which indicates that there is a high level of knowledge and awareness among university students. Of the 107 respondents, more than 70 per cent were positive and had an adequate level of environmental awareness, and 60 per cent showed positive environmental practices and behaviours.

Rapid urbanisation has caused an increased in peak discharge that conventional drainage systems cannot adequately handle. Low Impact Development (LID) practices are becoming a new approach in helping to better mimic the pre-development discharges. This study aims to evaluate the effectiveness of LID and Best Management Practices (BMP) under different rainfall conditions. Vegetative swale and detention pond were selected to represent LID and BMP. Simulations of four main scenarios namely, base case, LID, BMP, and combined LID-BMP were performed using Stormwater Management Model (SWMM). Results show that among the scenarios simulated, the combined LID-BMP is most effective with average peak flow reduction of 54%. This is followed by BMP that achieved 37% in average peak flow reduction as compared to 27% peak flow reduction by LID. The findings indicate the need for integrated strategy when dealing with stormwater management measures.

Removing noise from the image by retaining the details and features of this treated image remains a standing challenge for the researchers in this field. Therefore, this study is carried out to propose and implement a new denoising technique for removing impulse noise from the digital image, using a new way. This technique permits the narrowing of the gap between the original and the restored images, visually and quantitatively by adopting the mathematical concept ''arithmetic progression''. Through this paper, this concept is integrated into the image denoising, due to its ability in modelling the variation of pixels' intensity in the image. The principle of the proposed denoising technique relies on the precision, where it keeps the uncorrupted pixels by using effective noise detection and converts the corrupted pixels by replacing them with other closest pixels from the original image at lower cost and with more simplicity.

Water quality is always affected by a wide range of human and natural factors which is commonly a result of mismanagement of land, dumping of rubbish and unintentional introduction of chemical material into the river. The rivers in Kuala Selangor and Sabak Bernam districts which lie in active agriculture and aquaculture activities are also not spared from pollution. This study focused on water quality investigation and source of pollution identification in seven rivers in Kuala Selangor and Sabak Bernam. The water quality parameters investigated were Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), pH and Ammoniacal Nitrogen (AN). Water Quality Index (WQI) was then calculated based on Department of Environmental guidelines. Based on the WQI results, Sungai Selangor and Sungai Tengi were classified as Class III showing slightly polluted, while Sungai Buloh, Sungai Nibong, Sungai Haji Dorani, Sungai Besar (Bagan Cina), Sungai Besar (Parit Timur) and Sungai Bernam were classified as Class IV or polluted. The industrial, residential, agricultural activities in the surrounding area of the rivers that were suspected of being sources of river pollution were also identified.