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Software Agent Simulation Design on the Efficiency of Food Delivery
Full text linkFood delivery services have gained popularity since the emergence of online food delivery. Since the recent pandemic, the demand for service has increased tremendously. Due to several factors that affect how much time additional riders spend on the road; food delivery companies have no control over the location or timing of the delivery riders. There is a need to study and understand the
food delivery riders' efficiency to estimate the service system's capacity. The study can ensure that the capacity is sufficient based on the number of orders, which usually depends on the number of potential customers within a territory and the time each rider takes to deliver the orders successfully. This study is an opportunity to focus on the efficiency of the riders since there is not much work at the
operational level of the food delivery structure. This study takes up the opportunity to design a software agent simulation on the efficiency of riders' operations in food service due to the lack of simulation to predict this perspective, which could be extended to efficiency prediction. The results presented in this paper are based on the system design phase using the Tropos methodology. At
movement in the simulation, the graph of the efficiency is calculated. Upon crossing the threshold, it is considered that the rider agents have achieved the efficiency rate required for decision-making. The simulation's primary operations depend on frontline remotely mobile workers like food delivery riders. It can benefit relevant organizations in decision-making during strategic capacity planning
Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
No full textStreaming applications are being extensively run on portable embedded systems, which are battery-operated and with limited memory. Thus, minimizing the total energy consumption of such a system is important. We investigate the problem of offline scheduling for streaming applications composed of non-preemptible periodic dependent tasks on homogeneous Network-on-Chip (NoC)-based Multiprocessor System-on-Chip (MPSoCs) such that their total energy consumption is minimized under memory constraints. We propose a novel unified approach that integrates task-level software pipelining with Dynamic Voltage and Frequency Scaling (DVFS) to solve the problem. Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete
frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. Using a set of real and synthetic benchmarks, we have implemented and compared our unified approach with two state-of-the-art approaches, RDAG+GeneS (Wang et al., 2011) , and JCCTS (Wang et al., 2013a). Experimental results show that our approach’s maximum, average, and minimum improvements over RDAG+GeneS (Wang et al., 2011) are 31.72%, 14.05%, and 7.00%, respectively. Our approach’s maximum, average, and minimum improvement over JCCTS (Wang et al., 2013a)
are 35.58%, 17.04%, and 8.21%, respectively
The effectiveness of Building Information Modelling (BIM) in solving railway project management issues in Malaysia
No full textRailway projects involve complex planning and management as compared to regular construction projects, but BIM can simplify and improve the management of these projects. MRT
2 faced problems like design discrepancies and coordination issues, while Gemas - JB ETS encountered issues with construction changes, cost overruns, and project delays. Hence, this research intends to investigate the project management issues and examine the effectiveness of
BIM implementation in solving project management issues in railway construction projects in Malaysia. A qualitative study was executed by conducting semi- structured interview on BIM professionals from the MRT 2 and Gemas-JB ETS railway construction projects. Six purposively selected respondents from the railway construction industry were interviewed, achieving data saturation. The main issues discovered were lack of communication, lack of coordination, clashes in construction, redesign and unrealistic schedules. The said issues mainly occurred during pre – construction stage. The level of BIM effectiveness in MRT 2 is high when full BIM
was implemented as compared to Gemas – JB ETS that have low effectiveness when partial BIM was implemented. The findings of this study is able to show that full BIM implementation in a project management can greatly enhance coordination and efficiency while reducing costs in the railway industry
Development of Adaptive Neuro-Fuzzy Inference System to Predict Concrete Compressive Strength
No full textPredicting the compressive strength of concrete is one of the complex problems in civil engineering because different parameters and factors must be considered. There is several research that have predicted the compressive strength of normal concrete using neuro-fuzzy systems. However, little research has been done to predict the strength of high strength concrete. Recently, machine learning techniques such as artificial neural networks (ANNs), fuzzy logic, and adaptive neuro-fuzzy inference system (ANFIS) are becoming extensively established in predicting complex problems. ANFIS has the advantages of both ANNs and fuzzy systems and is most suitable in engineering complicated applications. This study focuses on the development of ANFIS in predicting the compressive strength of high strength concrete. A total of 550 experimental datasets of concrete were used in this research. Each dataset was consisting of six input variables that were water, cement, fine and coarse aggregates, silica fume, and superplasticizer. The compressive strength of high strength concrete was considered as the output of the ANFIS model. In this study, 440 datasets were assigned as training datasets and 110 datasets were considered as testing sets to verify the ANFIS model. The mean square error (MSE) for the training set was 0.00573, and 0.00647 for the testing datasets. The ANFIS model was able to quickly predict the concrete compressive strength with high accuracy. Also, in this research, a sensitivity analysis was applied to study the contribution of input parameters to predict the compressive strength of concrete
Adoption of Technology–Organization–Environment Framework in the Digitization Decision of the Inventory Management
No full textThis study investigates the possible adoption of the technology–organizations–environment (TOE) paradigm to influence the food manufacturer to shift their warehouse operation to a digitalization process to boost their food production efficiency. It examines the elements that impact digitalization in inventory management, using the TOE framework as a lens for the adoption. This study employed a quantitative approach involving 63 respondents, and SmartPLS software was selected and used to analyze the information collected from the respondents. The findings indicated that accessibility, compatibility, performance expectations, top management support, company size, competitive pressure, and regulatory support directly the influence inventory management digitalization adoption. This study helps investors, government, logistics, and supply chain sectors, and students to understand what factors drive digital inventory management adoption. The developed framework provides input for related stakeholders in enhancing the inventory management process in Malaysia
Molecularly imprinted polymer based on deep eutectic solvent as functional monomer for paracetamol adsorption
No full textParacetamol, a popular analgesic, has been linked to harmful health effects, such as kidney and liver damage. The detection of paracetamol in the environment and its overdose use in humans and animals has raised global
concerns, highlighting the need for its efficient removal or detection in real samples. In this study, a deep eutectic solvent-molecularly imprinted polymer (DES-MIP) was synthesized and applied as an adsorbent to recognize the
removal of paracetamol selectively. DES-MIP was synthesized using a deep eutectic solvent (DES) as a functional monomer, ethylene glycol dimethacrylate as a crosslinker, and paracetamol as a template. DES was initially prepared by combining choline chloride (ChCl) with methacrylic acid at a molar ratio of 1:2. A deep eutectic solvent-non-imprinted polymer (DES-NIP) was synthesized as a control. The characterization analysis, including Fourier transform infrared spectroscopy (FTIR), Scanning emission microscopy (SEM), and Brunauer-EmmettTeller (BET) was conducted for both polymers to confirm the synthesis occurred. The selectivity study inferred that DES-MIP (15.95 mg/g) was more selective towards paracetamol than DES-NIP (7.00 mg/g). Response
surface methodology (RSM) coupled with central composite design (CCD) was employed to examine the effect of pH, contact time, and dosage on paracetamol adsorption. The analysis of variance (ANOVA) demonstrated the
relative significance of process parameters in the adsorption process. The contact time and dosage were found to be more significant than the pH. The result indicated that the optimal conditions for paracetamol adsorption
were pH 7, 35 min, and 5.5 mg. The behavior of paracetamol adsorption on DES-MIP was well-fitted using the second-order kinetic and Langmuir isothermal models, respectively. Then, the DES-MIP with optimized parameter studies was applied to herbs, medicine, and dietary supplements, achieving good recoveries of 94.46 %, 86.79 %, and 85.13 % and relative standard deviations (RSD) of 1.15 %, 2.39 %, and 2.52 %, respectively
Enhanced fresh and hardened properties of foamed concrete modified with nano-silica
No full textNowadays, the application of nanotechnology has gained increased attention in the concrete technology field. Several applications of concrete require light weight; one such concrete used is foamed concrete (FC), which has more voids in the microstructure. In this study, nano-silica (NS) was utilized, which exhibits a pozzolanic nature, and it reacts with other pozzolanic compositions (like lime, alumina, etc.) to form hydrated compounds in concrete. Apart from these hydrated compounds, NS acts as a filler material and enhances properties of concrete such as the fresh and hardened properties. This research examines the fresh, hardened, and microstructural properties of FC blended with NS. The ratio of binder and filler used in this research is 1:1.5, with a water-tobinder ratio of 0.45 and a density of 880 kg/m3 . A total of six different weight fractions of NS
were added to FC mixes, namely 0%, 1%, 2%, 3%, 4%, and 5%. Properties assessed for FC blended with NS were the slump, bulk density, strength parameters (flexural, splitting tensile, and compressive strengths), morphological analysis, water absorption, and porosity. It was concluded from this study that the optimum NS utilized to improve the properties was 3%. Apart from this, the relationship between the mechanical properties and NS dosages was developed. The correlations between the compressive strength and other properties were analyzed, and relationships were developed based on the best statistical approach. This study helps academicians, researchers, and industrialists enhance the properties of FC blended with NS and their relationships to predict concrete properties from other properties
Ergonomic Risk Assessment of Warehouse Workers in the Courier Service Industry: A Case Study from Kuantan, Malaysia
No full texte global surge in demand for courier services has introduced both benefits and challenges. Courier workers face immense pressure to handle large volumes of orders, leading to increasing cases of health and occupational injuries. e lack of ergonomic interventions in their work highlights the urgent need for ergonomic assessments in the courier industry. In Malaysia, current ergonomic risk assessments for warehouse courier workers are insufficient, making it essential to identify prevalent musculoskeletal disorders (MSDs)
and determine the associated risk factors and levels posed by their daily tasks. is study aimed to address this gap by conducting ergonomic risk assessments among 35 warehouse workers using the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ), the Initial Ergonomic Risk Assessment (ERA) Checklist, and Rapid Entire Body Assessment (REBA). ree different work tasks were
observed: scanning and sorting, tiered storage and stacking, and load unloading. e findings revealed that lower back pain was the most common ailment (14.5%), followed by hip pain (8.39%) and neck pain (7.89%). e tiered stacking storage activity posed the highest ergonomic risk, with identified risk factors including awkward postures, static and sustained activity, and repetitive tasks. e REBA analysis indicated a very high-level risk for tiered stacking storage, necessitating immediate ergonomic interventions. ese findings contribute to the field of ergonomics and provide valuable insights for safety practitioners, ergonomists, researchers, and academicians in occupational safety and health and the courier service industries
Multidisciplinary Optimization of Axial Turbine Blade Based on CFD Modelling and FEA Analysis
No full textThe turbine blade is designed to achieve expansion at high efficiency levels. For
improving the turbine efficiency, different aerodynamic design optimisations are
performed. On the other hand, the aerodynamic design must be enhanced to match the mechanical design. This research proposes a novel design optimisation method for both aerodynamic and mechanical requirements. A multidisciplinary optimisation approach is used to improve the reliability of the turbine design, which included the use of Computational Fluid Dynamics (CFD) models and Finite Element Analysis (FEA). The primary objective is to guarantee that the aerodynamically optimised blade profile could efficiently withstand mechanical stress. The multidisciplinary optimisation approach is successful in reducing total equivalent pressures from 49.72 MPa to 41.73 MPa while keeping the turbine's overall efficiency at an impressive level of 80.95%. These Results highlight the effectiveness of using a multidisciplinary optimization method to successfully improve the efficiency of a turbine blade profile while simultaneously ensuring its ability to withstand the needed mechanical loads. Using a multidisciplinary optimisation method, the turbine maintains an impressively high efficiency of approximately 83%, with only a marginal reduction of 1.8% compared to the efficiency achieved solely through aerodynamic blade optimisation
The relationship between logistics capabilities and customer attitudes towards online purchasing among consumers in Malaysia
Full text linkOnline purchasing in Malaysia is demonstrating significant consumer growth. However, customer’s attitude will ultimately determine if a transaction is made and whether to purchase online in the future. The issue is that consumer fears in online purchasing because of late in delivery, non-receipt of products, inaccurate information on delivery time, and poor after sales services. Hence, this study focusses on examining the relationship between logistics capabilities and customer attitudes towards online purchasing among consumers in Malaysia. To achieve the research objective, this study used quantitative approach and a survey was conducted among 384 consumers at the age of 18 years and above in Malaysia with a response rate of 100% where questionnaire-based survey was utilized. Data collected were analysed using descriptive and correlation analysis. The results show that delivery speed, shipment tracking, information quality, and after sales services has a statistically significant positive relationship with customer positive attitudes towards online purchasing. Meanwhile, delivery speed, shipment tracking, and information quality has no statistically significant relationship with customer negative attitude towards online purchasing, whereas there is statistically significant negative relationship between after sales services and customer negative attitude towards online purchasing. Therefore, this study contributes valuable insight and a comprehensive understanding for marketers, e-retailers, and logistics service providers on the relationship between logistics capabilities and customer online purchasing attitudes in Malaysia where logistics capabilities tend to improve customer positive attitudes towards online purchasin