Search results

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose of this paper is to identifity the flow regime in a pneumatic conveyor system by electrodynamic sensor placed around the pipe using fuzzy logic tools.

Electrical charge tomography is used to detect the existence of inherent charge on the moving particles through the pipe. Linear back projection algorithm and filtered back projection algorithm are employed to produce tomography image. Baffles of different shapes are inserted to create various flow regimes, such as full flow, three quarter flow, half flow and quarter flow. Fuzzy logic tools are used to identify different flow regimes and produce filtered back concentration profiles for each flow regime.

The results show significant improvement in the pipe flow image resolution and measurement.

This paper presents a flow identifier method using electrical charge tomography and fuzzy logic to monitor solid particles flow in pipeline.

This chapter provided systematic and comprehensive analysis on trawl fisheries management and conservation measures in the Straits of Malacca. Detailed analysis is conducted on Malaysian fishery management framework particularly domestic country's trawl fishery status, legal structure, input-control strategies, ecosystem protection plan, pollution, law enforcement, and complementary measures that designed to reduce and prevent overfishing in the exclusive economic zone (EEZ) of Malacca Straits. Gaps and challenges found in existing trawl fisheries literature are presented followed by recommendations for improvement in the management and conservation of trawl fisheries.

The purpose of this paper is to provide some empirical findings on the predicaments of lawyers’ anti-money laundering (AML) compliance in Malaysia and the rationales for such predicaments.

This paper adopts a qualitative research in which the primary data are obtained from seven case studies involving legal firms within the Klang Valley, Selangor, Malaysia, which is triangulated with the data from the Central Bank and the Malaysian Bar Council.

The authors contend that despite the vulnerability of their profession to money laundering, the level of awareness of the AML obligations amongst Malaysian legal practitioners is rather minimal. Also, the imposition of obligations upon them in policing their clients and regulating money laundering is not only onerous but also contrary to the ethics of their profession.

This paper fills the gap in providing the empirical evidence on lawyers’ compliance to their statutory AML obligations in Malaysia. Also, this paper could be a useful source of information for practitioners, academicians and students. It could also be a beneficial guide for policymakers for any possible future amendments to the law.

The purpose of this paper is to investigate multiple criteria decision-making (MCDM) processes within a flow-line production-improvement activity. Investigation can lead to understanding of how a process improvement framework influences the decision and fulfillment of the potential to successfully change the operation process.

The improvement process selection (IPS) framework is built systematically by incorporating all related decision criteria with suitable tools required to select improvement alternatives. The process consists of three phases: identification, prediction, and selection. The IPS framework is validated through a case study of a company that was carrying out a flow-line production-improvement project.

The developed framework is used to prioritize the problem scope and select the solutions from various options. The case study illustrates the process through which the developed framework provided a systematic approach in identifying the solutions and achieving the desired performance improvement. Prediction result analysis shows the framework achieved sustainable process improvement changes and prevents management levels from higher risks in failure improvement. The feedback of the case study has verified the robustness of the framework.

Quantitative improvement tools, such as MCDM employed in the IPS framework are vital for better understanding of the improvement impact of changes. Thus, the improvement solution alternatives can be analyzed in more comprehensive ways by considering numerous performance metrics in order to select the best improvement alternatives.

The IPS framework can assist the company in determining optimal decisions in relation to selection of improvement alternatives. As a result, production performance can be affected positively.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.

An identification model for materials flow through a pipeline is presented in this paper. The development of the model involves fuzzy C-means clustering, in which different flow regimes can be identified by every adaptive network-based fuzzy inference system (ANFIS). The paper aims to discuss these issues.

For experimentation, 16 electrodynamic sensors were used to monitor and measure the charge carried by dense particles flow through a pipeline in a vertical gravity flow rig system. Four ANFIS models were also used simultaneously to provide the expected output on thresh-holding and were evaluated for ten different flow regimes, which produced satisfactory results at high flow rate.

The observations made on the four ANFIS models in the flow identification experimentation (in ten different flow regimes) have shown convincing and satisfactory results at high-flow rate of the particles.

Electrodynamic sensors have shown strong sensing capability in identification of dense-particle flows within a conveyor; and also proven capability to operate effectively in harsh industrial environments due to their firm and simple structures. Moreover, it has been verified that these sensors can conveniently be applied in flow regime identification of solid particles.

A perusal of extant literature suggests asymmetric devotions in empirical research that overlooks unique social and industrial dynamics of married working women in highly competitive male-dominated industries. Drawing on the social role theory, the study addressed this asymmetry by proposing a multivariate regression model that examined performance drivers of married female real estate brokers, as mediated by organizational, cognitive and social influences.

The study employed a descriptive design. A structured electronic questionnaire was used to collect data from a sample of 256 married female brokers who are active on online messaging platforms. Snowball sampling was used to reach the research participants. Collected data were subjected to multivariate regression analysis.

The results infer that social influences were the most significant drivers of married female brokers in the real estate industry (r = 0.932, p < 0.05, F = 556.581). Significant interventions of diversity management, work-life balance, family support and access to economic opportunities were found.

In acknowledging the societal stereotype and culturally imposed burdens married women face in emerging economies, the study advanced theoretical, practical and policy initiatives for a more inclusive, supportive and learning-oriented work environment.

The novelty of the paper lies in its exposition of the unregulated real estate brokerage market in an emerging economy and the dynamic organizational, cognitive and societal influences of married female brokers.

This chapter introduces the book by revolving around its core concept: digital citizenship. This introductory chapter on digital citizenship regimes in the postpandemics could be established by including several brief discussion points that gradually introduce and lead us comprehensively to the chapters of the book previously introduced. These discussion points are informative and attempt to introduce progressively to the key chapters of the book as follows: (1) Urban-Digital Citizenship Nexus; (2) Advancing Recent Literature on Citizenship; (3) Rescaling Nation-States: Pandemic Citizenship and Algorithmic Nations; (4) Beyond the Smart Cities; (5) Exploring Digital Citizenship Towards Technopolitical Dynamics; (6) Borderless and Pandemic Citizenship; and (7) In Summary: Towards Future Research and Policy Avenues in the Postpandemics.

Intelligent pneumatic actuator (IPA) is a new generation of actuator developed for Research and Development (R&D) purposes in the academic and industrial fields. The purpose of this paper is to show the application of optical encoder and pressure sensor in IPA, to develop a real-time model similar to the existing devices, and to assess the position control performance using a proportional-integrative (PI) controller and a bang-bang controller in real-time.

A micro optical encoder chip is used to detect cylinder rod position by reading constructed laser stripes on a guide rod, whereas a pressure sensor is used to detect the chamber pressure reading. To control the cylinder movements by manipulating pulse-width modulation (PWM) cycles, two unit valves of two ports and two positions were used. A PI controller and a bang-bang controller are used with suitable gain value to drive the valve using PWM to achieve the target actuator position.

The results show the experimental results of the closed-loop position tracking performance of the system using a data acquisition (DAQ) card over MATLAB software.

This paper presents a real-time model used to replace the microcontroller-based system from previous IPA design. The paper proposes two control strategies, PI and bang-bang, to control position using encoder and pressure reading.