Distance Estimation using Deep Learning Approaches for Rear-end Collision Avoidance Alerts

Autonomous Emergency Braking (AEB) and Autonomous Emergency Steering (AES) are part of the advanced driver assistance system (ADAS) equipped in intelligent vehicles. AEB is a system that warns drivers of potential collisions and assists them in utilizing the vehicle\u27s maximum capabilities. AES is an active safety system that aids in evasive steering. If it detects a potential collision, unlike AEB, the AES system will autonomously adjust the steering to prevent it. The challenges for AEB and AES include determining how much space is required to avoid an accident while turning or braking and how much distance is required to avoid an impact when braking and turning simultaneously. Considering such inquiries, it is necessary to devise a system to estimate the distance between the vehicles. Therefore, this study proposes a Monocular Vision Distance Estimation (MVDE) method employing deep learning techniques for accurately calculating the distance between vehicles, particularly for use in AEB and AES systems. The MVDE technique uses monocular vision, emphasizing object detection and distance estimation. In contrast to complex depth estimation techniques, the proposed method employs a Single Shot Detector (SSD) with MobileNet architecture for object recognition and Deep Artificial Neural Networks (Deep ANN) for accurate distance estimation. Using a real-world dataset collected in Cyberjaya, Malaysia, this study rigorously assesses the performance of this method. Results indicate that the MVDE method with four hidden layers in Deep ANN outperforms earlier techniques, with a maximum measured error of 4m to actual distances. In addition, it is competitive with RADAR-based systems and offers a cost-effective alternative for widespread adoption. These findings support the potential of MVDE for augmenting vehicle safety, shaping future automotive standards, and facilitating the widespread implementation of AEB and AES systems

Passivation Layer Reduction of Chalcopyrite for Sustainable Extraction of Copper Using Additives Assisted Bioleaching: A Mini Review

Nowadays, rich copper ore grades have been exploited and thus mining companies have been increasing their interest to liberate or extract copper from low grade copper ores, mainly from chalcopyrite. However, chalcopyrite ore is the future source of copper, its extraction is hindered due to the formation of passivation film, which consequently inhibiting the leaching efficiency of copper. This review paper sheds light on and critically assesses the recent advancements in passivation film reduction strategies to enhance the recovery rate of copper from chalcopyrite using a synergetic effect of bioleaching and external additives. The microorganisms used in bioleaching enhance the surface property of chalcopyrite due to their unique capabilities of biofilm formation, which enhances adhesion properties. Addition of external additives during the bioleaching improve the microbial activities the ore by providing an active surface for microbial attachment, which boosts dissolution of the chalcopyrite and consequently reduces the formation of passivation film. According to their optimum temperature, microorganisms used in bioleaching classify as mesophilic, moderate thermophilic and extremely thermophilic microorganisms. Mesophilic microorganisms are dominated in bioleaching. This review paper aims as a compiled reference material for future studies towards high recovery of copper from chalcopyrite by modifying the surface property of the ore. Recognizing the rapid advancement and importance of bioleaching in the extractive metallurgy industry (mainly in the extraction of copper from low grade copper sulphide ores), this review paper serves for practitioners as a crucial and technically advanced source for future researches in chalcopyrite bioleaching, techniques for passivation layer reduction of chalcopyrite and current advancements in bioleaching

Understanding Consumer Preferences in the Funeral Service Industry: Insights from the Johor Bahru Market

Funeral service organisations preserve the memory of the departed as they assist families in mourning. Research examining consumer choices in this market sector is currently relatively sparse. A research investigation explores how ethnic Chinese people in Johor Bahru, Malaysia, prefer their funeral services. A total of 50 respondents participated in this study using Microsoft Forms and quantitative research methods. The convenience sampling method produced data analysed through descriptive techniques in Excel software. All participants belonged to a group that experienced death, yet 70% of this group was directly responsible for organising funerals. A significant 48% of the participants estimated their funeral expenses would fall from RM30,000 to RM34,999. Funeral services were the most popular choice among respondents who wanted services in public funeral facilities (84%) and followed the Buddhist/Taoist religious customs (70%). Research results demonstrate that people need accessible funeral services which also offer transparent pricing and maintain respect for local customs. The providers of funeral services should create inexpensive package solutions which permit flexible payment options. Providing more religious services and better professional support would offer improved solutions for this multicultural community. The support system provided by Johor Bahru funeral providers needs to tackle financial, logistical and cultural considerations to benefit bereaved families effectively

Financial Literacy and Resilience Among Students in Southern Malaysian Public Universities

This study investigates the relationship between financial literacy and financial resilience among students in Malaysian public universities (IPTA). In the context of rising living costs and limited financial resources, financial literacy emerges as a crucial skill for young adults navigating economic challenges. Utilizing data from 107 respondents, the research examines how socio-demographic factors, financial literacy, and economic resources influence financial resilience. The findings indicate that students with higher financial literacy demonstrate better financial resilience, thereby enhancing student well-being. By advocating for the inclusion of financial management education in university curricula, this study supports Sustainable Development Goal 4 (SDG 4), which emphasizes quality education and lifelong learning opportunities. The integration of financial literacy into educational programs not only prepares students for financial challenges but also contributes to their long-term financial stability and overall well-being

Architecture of Coastal Rural Houses in Thai Binh Province, Vietnam for Adaptation to Climate Change and Sea-Level Rise

In Thai Binh province, Vietnam, according to the RC4.5 climate change scenario by the end of the 21st century, sea levels are projected to rise by a maximum of 100 cm. This will result in the flooding of 22,313 hectares (66.13%) of Tien Hai District, 21,750 hectares (64.39%) of Kien Xuong District, and 26,756 hectares (47.94%) of Thai Thuy District. Such a rise in sea levels will significantly impact residential areas, housing, and agricultural production in the coastal villages of Thai Binh Province. The article\u27s aim is to propose architectural models for rural housing in these coastal hazard areas, allowing communities to adapt to climate change and sea-level rise. The goal is to help coastal residents continue living with inundation while ensuring a good quality of life and sustainable working conditions. The study uses field survey methods, document collection, data analysis, evaluation and computer simulation based on actual sea level rise to propose housing solutions. The article contributes proposes housing and shelter models for communities affected by rising sea levels, including houses with horizontally integrated shelter spaces in estuary areas, as well as houses with raised platforms and those integrating vertical shelter spaces in alluvial land areas

Impact of Conflict Management Competence on Effective Management of Technical Education Programme in Tertiary Institutions in Southeast, Nigeria

The study explored the impact of conflict management competence on effective management of technical education programme in tertiary institutions in Anambra state. Specifically, the study determined the impact of arbitration, collective bargaining, dialogue and smoothing competencies on effective management of technical education programme in tertiary institutions in Anambra state. In this study, a mixed methods design was adopted because it involved collecting data to answer questions about the current state of the study subject through both the quantitative and qualitative means. The participants in in this study were 168 stakeholders in the management of technical education programme in tertiary institutions in South-Eastern Nigeria which offer technical education. Structured questionnaire and Interview were the instruments used for collecting data in this study. Cronbach\u27s Alpha was used to determine the reliability of the questionnaire. Reliability coefficients of 0.90, 0.92, 0.92 and 0.95 for arbitration, collective bargaining, dialogue and smoothing competencies respectively. Linear Regression and thematic analysis via illustrative quotes were used to analyze the data. Findings revealed that arbitration, collective bargaining, dialogue and smoothing competencies have a positive and significant impact on effective management of technical education programme in tertiary institutions in Anambra state.

Risky Driving Behaviours and Their Impact on Road Traffic Accidents: Insights from Commercial Bus Drivers in Nigeria

Public transport safety mainly depends on bus drivers due to their crucial roles. Therefore, understanding commercial bus drivers\u27 driving behaviours can aid in determining areas that need urgent attention. The study examines the influence of their risky driving behaviour on road traffic accidents (RTAs) and the moderating effect of the bus drivers\u27 driving experience and education level. The validity results showed that Driver Behaviour Questionnaire (DBQ) is reliable and valid for commercial bus drivers. Also, through the structural model assessment of risky driving behaviour, the findings reveal that violations (β = 0.121, p < 0.05) and erors (β = 0.094, p < 0.05) are significant predictors of road traffic accidents among commercial bus drivers, explaining 4% of the variance in accident involvement. In other words, the study revealed a significant influence of driving violations and errors on RTA, while inattention errors were insignificant. The Importance-performance map indicates that serious measures and attention are needed to reduce driving violations. Additionally, driving experience and educational level did not moderate the relationship between risky driving behaviour and RTA. The study offers unique insights by identifying critical driving behaviour that demands strategic intervention from policymakers, driver trainers, and transport employers

Optimising The Implementation of Building Information Modelling in 4D (Scheduling) and 5D (Cost) for Highway and Bridge Construction

Building Information Modelling (BIM) is a shared knowledge repository for information about a facility that serves as a trustworthy foundation for decision-making throughout the facility\u27s life cycle, which is described as "existing from inception to demise." BIM is still lacking in usage and awareness of BIM benefits in implementation in the highway and bridges construction industry. Furthermore, the disconnect between project scheduling, cost estimation, and BIM models exacerbates the complexity of construction processes, hindering the seamless integration of BIM in highway and bridge projects. Therefore, the objective of this study is to identify the current level of awareness of Building Information Modelling implementation in the highway and bridge construction industry, to produce a BIM 4D (Scheduling) and 5D (Cost Estimating) model based on the highway and bridge construction project and to recognize the benefits and challenges of implementing Building Information Modelling approaches in the highway and bridge construction industry. This research conducted an industrial survey, literature review, and 4D/5D BIM modelling focusing on the Malaysian highway and bridge construction industry. The results suggest that the industry has a moderate understanding of 4D/5D BIM but has superior scheduling and cost estimating skills. The three highest listed benefits are improved on-site cooperation, model-based cost estimation, and project visualization in preconstruction with 3.633, 3.767 and 3.900 mean rank respectively. The three highest-ranked challenges are technical problems, legal challenges, and reluctance to change with 3.500, 3.467 and 3.400 mean rank respectively. In order to replicate the 4D/5D model, modelling is constructed using Infraworks, MS Project, and Navisworks

Factors Affecting the Rate of CaCO3 Precipitation in Biocementation of Heavy Metal Contaminated Soil

Ground improvement methods using physical and chemical treatments are considered effective but costly, involving large engineering work and may pose serious environmental problems. Therefore, biocementation using enzyme-induced calcite precipitation (EICP) technique is introduced. The efficiency of EICP is influenced by the production of calcite carbonate, CaCO3 and governed by multiple factors. While some preliminary studies have been done on variety of soil types, none the them were performed on heavy-metal contaminated soil. This paper presents the research conducted on factors affecting the CaCO3 precipitation in biocementation of mining waste collected from a copper mine in Sabah, Malaysia treated using EICP solution, cured in a leaching cell and tested using inductively coupled plasma optical emission spectroscopy and acid washing test. Results concluded that factors affecting the production of calcite carbonate content are the cementation concentration (1.0M > 0.5M), degree of compaction (70% MDD> 80% MDD) and curing temperature (25 ⁰C > 15 ⁰C > 5 ⁰C). Meanwhile, immediate production is observed (1-day curing) indicating that curing time is not a significant factor. Hence, the results proposed that the optimum production of CaCO3 for treatment of heavy metal in contaminated soils is at cementation solution of 1.0M, compacted at 70% MDD and cured at 25 °C temperature

Monte Carlo Simulation of a Beam Resting on an Elastic Foundation Considering the Two-Dimensional Stochastic Properties of the Elastic Modulus

The analysis of the random behavior of beams on an elastic foundation, considering a two-dimensional random elastic modulus, contributes to bringing the analytical model closer to the physical model of the problem and enhancing the reliability of structural calculations. This paper aims to develop a Monte Carlo simulation (MCs) to represent the two-dimensional random field of elastic modulus combined with the finite element method to analyze the random response of beams resting on an elastic foundation according to the Winkler model. The spectral representation method generates the two-dimensional elastic modulus\u27s Gaussian. This sample function is used to construct the formulation of finite elements. The influence of the random field\u27s standard deviation, the correlation distance along the in-plane axes, and the stiffness of the elastic foundation on the coefficient of variation of displacement are also investigated and analyzed in detail in this article. The two-dimensional randomness of the elastic modulus and the stiffness coefficient of the foundation significantly affect the random response of the beam. The coefficient of variation (COV) of displacement tends to increase when the standard deviation of the stochastic field or the correlation distance along the axes increases. Still, conversely, when the stiffness of the elastic foundation rises, the coefficient of variation decreases. The COV of displacement approaches the standard deviation value of the stochastic field of material properties when the correlation distance along the axes approaches infinity