Comparisons of various imputation methods for incomplete water quality data: a case study of the Langat River, Malaysia

In this study, the ability of numerous statistical and machine learning models to impute water quality data was investigated at three monitoring stations along the Langat River in Malaysia. Inconsistencies in the percentage of missing data between monitoring stations (varying from 20 percent (moderate) to over 50 percent (high)) represent the greatest obstacle of the study. The main objective was to select the best method for imputation and compare whether there are differences between the methods used by the different stations. The paper focuses on different imputation methods such as Multiple Predictive Mean Matching (PMM), Multiple Random Forest Imputation (RF), Multiple Bayesian Linear Regression Imputation (BLR), Multiple Linear Regression (non-Bayesian) Imputation (LRNB), Multiple Classification and Regression Tree (CART), k-nearest neighbours (kNN) and Bootstrap-based Expectation Maximisation (EMB). Remarkably, among all seven imputation techniques, the kNN produces identically reliable results. The imputed data is all rated as ‘very good’ (NSE > 0.75). This was confirmed by the calculation of |PBIAS|<5.30 (all imputed data are‘very good’) and KGE≥0.87 (all imputations are rated as’ good’). Imputation performance improves for all three monitoring stations with an index of agreement, WI ≥ 0.94, despite varying percentages of missing data. According to the findings, the kNN imputation approach outperforms the others and should be prioritised in actual use. Future research with the existing methods could benefit from the addition of geographical data

Short-, Medium-, and Long-Term Prediction of Carbon Dioxide Emissions using Wavelet-Enhanced Extreme Learning Machine

Carbon dioxide (CO2) is the main greenhouse gas responsible for global warming. Early prediction of CO2 is critical for developing strategies to mitigate the effects of climate change. A sophisticated version of the extreme learning machine (ELM), the wavelet enhanced extreme learning machine (W-EELM), is used to predict CO2 on different time scales (weekly, monthly, and yearly). Data were collected from the Mauna Loa Observatory station in Hawaii, which is ideal for global air sampling. Instead of the traditional method (singular value decomposition), a complete orthogonal decomposition (COD) was used to accurately calculate the weights of the ELM output layers. Another contribution of this study is the removal of noise from the input signal using the wavelet transform technique. The results of the W-EELM model are compared with the results of the classical ELM. Various statistical metrics are used to evaluate the models, and the comparative figures confirm the superiority of the applied models over the ELM model. The proposed W-EELM model proves to be a robust and applicable computer-based technology for modeling CO2concentrations, which contributes to the fundamental knowledge of the environmental engineering perspective. Doi: 10.28991/CEJ-2023-09-04-04 Full Text: PD

Baltische Flora, enthaltend die in Est-, Liv-, und Kurland wilddwachsenden Samenpflanzen und höheren Sporenpflanzen : eine zur Erlangung der Magister-Würde verfasste und mit Bewilligung der Hochverordneten physico-mathematischen Facultät der Kaiserl. Universität zu Dorpat zur öffentlichen Vertheidigung bestimmte Abhandlung

http://tartu.ester.ee/record=b1868533~S1*es

Does the Household Save Water? Evidence from Behavioral Analysis

Management of water supply in urban areas is a challenge that must be faced by water supply companies to ensure the continuity of domestic water supply to the residents in the area. Hence, this study aims to identify local people’s behavior and daily activities that led to domestic water wastage. Furthermore, the relationship between the demographic factors of the population trends in reducing water use through water savings in their daily activities or installing a home-saving water system is also undertaken. The data were analyzed and interpreted using IBM SPSS software such as descriptive analysis, covering frequencies, mean and standard deviation, correlation with bivariate correlation, cross-tabulation, and multivariate analysis (MANOVA). Availability and demand in water management will only be managed if water resources and water supply engineers address all the balance sides. It will ensure a more comprehensive and interconnected water sector, ensuring the security and sustainability of water

Programme Outcomes Assessment for Civil & Structural Engineering Courses at Universiti Kebangsaan Malaysia

AbstractProgramme Outcomes (PO) is the expected achievement of the level of knowledge, skills and abilities essential to each student after their graduation. The Department of Civil & Structural Engineering, Faculty of Engineering and Built Environment, UKM has established 10 POs, PO1 to PO10 for all undergraduate courses from Year 1 to Year 4. Measurements of the POs are made through several assessments such as tutorials, quizzes, laboratory works, projects, mid-semester examinations and final examinations. This study presents the results from calculations based on the POs of the final examinations for two semesters (semester 1 and semester 2) of session 2010/2011 Civil & Structural and Civil & Environmental Engineering undergraduate programmes. It was made using the average marks for the sample of five excellent students, five moderate students and five weak students for all courses which have final examinations. The results showed an average overall marks for the PO4 is the highest around 78% followed by PO3 and PO10 which are about 68% and 63% respectively, while PO1 and PO2 have the lowest values which are around 56%-59%

Persepsi pelajar mengenai aplikasi quizizz dan padlet bagi kursus kejuruteraan geoteknik

Kejuruteraan Geoteknik adalah salah satu sub bidang didalam kejuruteraan awam. Kursus ini melibatkan penggunaan prinsip asas geologi dan mekanik tanah dalam penentuan rekabentuk dan pembinaan struktur tanah yang selamat. Dalam konteks pengajaran di kuliah, kaedah tradisional seperti slaid and buku teks dilihat membosankan kerana pengajaran hanya berbentuk satu hala dan pelajar tidak mempunyai medium untuk berinteraksi. Oleh itu, pendekatan di dalam kuliah yang berkesan dapat memastikan pemahaman yang lebih baik serta penguasaan terhadap konsep asas dalam kejuruteraan geoteknik. Objektif kajian ini adalah untuk mendapatkan persepsi para pelajar mengenai pendekatan pengajaran yang sesuai dijalankan di kuliah menggunakan aplikasi Quizizz dan Padlet bagi kursus Kejuruteraan Geoteknik. Seterusnya, ia juga bertujuan untuk mengenal pasti kaedah terbaik yang wajar digunapakai bagi kursus Kejuruteraan Geoteknik. Sekain itu, kajian ini turut menilai kesan pendekatan mengunakan kedua-dua aplikasi tersebut terhadap tahap pemahaman pelajar serta keterlibatan pelajar secara aktif semasa sesi kuliah berlangsung. Kajian ini melibatkan soal selidik ke atas pelajar prasiswazah Tahun 3 sesi akademik 2022/2023, Ijazah Sarjana Muda Kejuruteraan Awam, Universiti Kebangsaan Malaysia yang mengikuti kursus ini. Soal selidik bagi kajian ini dilakukan secara atas talian, dimana pelajar perlu mengisi tinjauan tersebut pada hari terakhir sesi kuliah dijalankan. Daripada kajian yang dijalankan, didapati sebanyak 82.10% pelajar bersetuju dengan perlaksanaan aplikasi Quizizz dan 57.10% pelajar bersetuju dengan perlaksanaan Padlet semasa kuliah diajalankan. Namun, terdapat 35.70% pelajar menjawab tidak pasti, 5.40% tidak setuju, dan 1.80% sangat tidak setuju dengan penggunakan aplikasi Padlet kerana mereka seringkali mempunyai kesukaran ketika ingin memuat naik fail. Aplikasi Quizizz turut dilihat mempunyai potensi untuk dijadikan sebagai e-penilaian. Hal ini kerana aplikasi tersebut dapat mengira markah pelajar secara automatik dan sekali gus dapat meringankan beban tugasan pelajar serta beban ahli akademik untuk menanda markah tugasan

Research Trends of Hydrological Drought: A Systematic Review

The frequency and severity of global drought-induced impacts have led to raising awareness of the need for improved river management. Although academic publications on drought have proliferated, a systematic review of literature has not yet been conducted to identify trends, themes, key topics, and authorships. This study aims to evaluate the scientific evidence for the hydrological drought characteristics and the methodologies by performing as a framework. This systematic review performed three-stage screening of literature review for current applicable hydrological drought studies that have been conducted since the year of 2000 concerning methodologies, literature research gaps, and trends, and contribute to future studies. The analysis shows the increasing trends of research and publications in the hydrological drought assessment. The primary research themes are hydrological drought is drought severity, drought vulnerability, and drought forecast. Despite the current research findings, spatial and temporal variability, low flow analysis and regional modelling are the most important to encourage a holistic approach and international collaborations. The finding identified the shortcomings of most research, which are the use of non-standardized methodological and distinct sample sizes, resulting in data summary challenges and unrealistic comparisons

Modified Hydrological Drought Risk Assessment Based on Spatial and Temporal Approaches

This study was conducted using a modified drought risk assessment in which hydrological data were processed to assess the hazards and risk of hydrological drought in Peninsular Malaysia. Although drought vulnerability and risk assessment are critical components of the drought phenomenon, the lack of a comprehensive integrated drought risk assessment in Malaysia has led to increased socio-economic impacts. The Hydrological Drought Risk Index (HDRI) illustrates the relative importance of hazard and vulnerability assessments in drought risk management for Peninsular Malaysia using the Streamflow Drought Index (SDI). This study presents an integrated drought characteristics-based risk assessment framework to improve hydrological drought risk assessment. The hydrological drought risk assessment was conducted by combining physical hazard and socioeconomic variables across the region. The periods of 1998–1999 and 2017–2018 mark the most critical hydrological droughts. The results also show that the trend of hydrological drought in river basins is towards dry conditions with no change in the foreseeable future. This study proposes a theoretical framework for effective drought risk management that can be used by the government and its stakeholders for sustainable water resource management