The fracture behaviour represents the most critical issue in the automotive and aerospace engine fields. Thus, the objective of this study was to estimate and analyze the crack criteria by using the
Mathematical laws that were limited in E 1820 standard and the results affirmed by applying the numerical solutions of ANSYS to estimate the fracture toughness value KIC, besides the energy release rate of biomass composite. The specimens were prepared from different percentage of kenaf mat (KM) and unsaturated polyester resin (UP) 20% KM – 80% UP and 40% KM – 60% UP, respectively, as well the other composite properties which were calculated using the stress-strain data. The fracture characterizations of this composite were carried out using the compact tension (CT) specimen that was commonly used to determine Mode-I fracture properties. The fracture toughness has been found to be independent of pre-crack length. Meanwhile, the tests were performed at room temperature. The numerical simulations of the ANSYS model results demonstrated a good agreement between the experiments computed results of the fracture toughness. The fracture toughness KIC of 20% KM – 80% UP and 40% KM – 60% UP was equivalent to 0.76 MPa√m and 2.0 MPa√m, respectively. Thus, the fracture propagation is dependent on the fibre percentage of the composite. On the other hand, there are unlimited mechanisms of crack paths derived from randomly kenaf mat packs, particularly in the frontal process zone of crack tip.
Understanding rainfall trend can be a first step in the planning and management of water resources
especially at the basin scale. In this study, standard tests are used to examine rainfall trends based on monthly, seasonal and mean annual series at the Niger-South Basin, Nigeria, between 1948 and 2008. Rainfall variability index showed that the decade 2000s was the driest (-2.1), while 1950s was the wettest (+0.8), with the decade 1980s being the driest in the second half of the last century, whereas the year 1983 was the driest throughout the series. Over the entire basin, rainfall variability was generally low, but higher intra-monthly than inter-annually. Annual rainfall was dominated by August, contributing about 15%, while December contributed the least (0.7%). On a seasonal scale, July-August-September (JJA) contributed over 40% of the annual rainfall, while rainfall was lowest during December-January-February (DJF) (4.5%). The entire basin displayed negative trends but only 15% indicated significant changes (α ‹ 0.1), while the magnitudes of change varied between -3.75 and -0.25 mm/yr. Similarly, only JJA exhibited insignificant upward trend, while the rest showed negative trends. About eight months of the year showed reducing trends, but only January trend was significant. Annual downward trend was generally observed in the series. The trend during 1948–1977 was negative, but it was positive for the 1978–2008 period. Hence, water resources management planning may require construction of water storage facilities to reduce summer flooding and prevent possible future water scarcity in the basin.
Ocean offers an inexhaustible source of water which is not consumable by humans due to its high salinity.
Large amounts of energy are required for desalination, and producing it from fossil fuels can cause harm
to the environment. As such, solar energy can be used as an alternative energy source to provide cheap
consumable water. This paper aims to investigate the effects of design parameters on single slope solar
still evaporation rate under Malaysian conditions. Single sloped solar stills, with varying evaporator basin
thickness and condenser plate thickness at different separator heights, were fabricated and tested. The 0.5
mm evaporator basin thickness still set has the highest evaporated volume (250 ml), with evaporation
percentage of 25%, while the set with a 1 mm evaporator basin thickness has the lowest evaporation
percentage (5.65%) with 56.5 ml evaporated volume. Experimental results indicate that the single slope
solar still evaporation rate is very much influenced by climate parameters, namely solar intensity and
ambient temperature.
Sound is a form of wave vibrations that contributes significantly in our daily life. Plants may interact with sound around us but we cannot certainly sure their reaction because of their immobility. Thus, this study intends to find the significant effect between different types of acoustic patterns on the growth of plants. Mung bean or its scientific name, Vigna radiata was chosen as seed material in this experiment due to their short growth cycle. The plants were grown in six environmental chambers with proper ventilations. The chambers were placed on open field with ambient conditions. Mung beans were exposed to five different types of acoustic patterns (soprano, classical, nature, rock, Quranic recitation) with sound pressure level of 60 dB ± 10 dB and one chamber was kept without any acoustic exposure. The length of stem, number of leaves and length of roots were recorded on the 15th day of mung beans’ growth. Experimental results indicate that different types of acoustic patterns promoted the growth of different part of mung beans. Soprano had significant effect on the length of stem while Quranic recitation promoted the production of leaves. However, there is no significant evidence that acoustic exposure stimulates the length of roots.
Working in a virtual team presents many challenges. Communication is one of the most important challenges, especially when a virtual team includes members from different countries and background. Virtual project management enables organizations to save on resources such as cost and time. Organizations often struggle with poor communication in their geographically dispersed teams and ineffective communication have been identified as one of the main causes project failure. The aim of this study is to determine the most critical barriers to effective communication in virtual teams. A mixed method of data collection was adopted using semi structured interview with communication and construction experts, and questionnaire approach with construction companies that are G5-G7 rated. Data were analyzed using pareto and exploratory factor analysis for the development of a strategy for enhancement of communication management within virtual teams. The result shows that lack of trust and misunderstanding are the most important barrier to communication within virtual teams. However, managing communication process has been identified to have more impact on the barriers, while planning communication has the least impact. Establishing rule for response and changing focus from individual to group were identified as the two most important factors required in order to sustain trust within virtual teams.
This paper seeks to clarify Building Information Modelling (BIM) and its implementation in Malaysia.
Most developed countries that have implemented BIM in the construction industry have found it effective. This paper reviews existing literature on the implementation of BIM and examines the implementation strategies that have been developed. The review highlights numerous advantages of BIM in construction, which include, among others, reducing cost, time, carbon burden and capital cost. BIM can also help increase broader efficiencies and improve coordination and communication between each party. However, implementing BIM is complicated and requires efforts from both the government and the private sector. While the implementation of BIM may reduce costs in developed countries, it may not do so in developing countries; in Malaysia, for instance, costs act as an initial barrier. Other obstacles to implementing BIM in Malaysia include application system requirements and lack of knowledge and readiness to change. To facilitate its implementation in the construction industry, the Malaysian government needs to hold seminars to promote a better understanding of BIM. They may also introduce a properly structured BIM course by preparing a standard code of practices and guidelines for BIM in the education sector.
Tractor rollover occurs when a tractor tips sideways or backwards and overturns, potentially crushing the operator. Rollovers are typically considered to occur more frequently during a sharp turn at a high speed on sloping terrains, although data show that rollovers do occur on flat land after hitting obstacles or through inappropriate use and hitching of implements. It is important to highlight that tractor overturns are the major cause of death in farm operations. The overturns are as a result of interactions between the tractor operator, the tractor and the environment. A review of the relevant literature reveals that more than 800 people are killed each year in tractor accidents, and for every person killed, at least 40 others are injured. This paper focuses on tractor overturns because they account for more than half of all the tractor-related deaths. In addition, farm tractor operational safety principles are also highlighted.
The motion resistances of 660 mm pneumatic and rigid bicycle wheels of the same rim diameter were measured experimentally using the developed tractor-towed single non-lug narrow wheel motion resistance test rig for traction studies. The motion resistances measured were taken to be the towing forces determined in real time using Mecmesin Basic Force Gauge (BFG 2500). The test variables included two test surfaces [tilled and wet (mud) surfaces], the dynamic load and the towing velocity. The tyre inflation pressure of 414 kPa was chosen to make the surface synonymous with that of the rigid wheel. Motion resistance ratios of the two wheels were determined empirically and through semi-empirical approach. The motion resistances of the rigid wheel were found to be greater than those of the pneumatic wheel for both surfaces. Consequently, the motion resistance ratios of the rigid wheel were greater than those obtained
from the pneumatic wheel. Analysis of variance showed that there were significant differences between the means of the motion resistance measured on the test surfaces, as well as between the two wheels and their interactions with the test surfaces. The motion resistance ratio exhibited a linear relationship with the towing velocity, while the relationship with the dynamic load was quadratic. However, such a relationship is either direct or inverse with the respective variables. The motion resistance ratio models for the pneumatic and rigid wheels showed that on different test conditions of the dynamic loads and the towing velocities, the relationships between the motion resistance ratio and the dynamic load, and motion resistance with dynamic load were also different.
The unified protocols are unified in application interface, models, and seamless. They generate one
standard protocol, one world called IEC 61850. IEC 61850 integrate the security, interoperability,
modelling, mapping to a substation, and reliability. Presently, the more expensive fiber based Ethernet
LAN is the most prevalent technology for medium and low voltage distribution substations. To
circumvent this problem Wireless Local Area Network (WLAN) has been investigated for its suitability
for applications that are compliant to IEC 61850: automation and metering; control and monitoring; and
over-current protection. In this paper the IEEE 802.11n WLAN is studied when used in various IEC
61850 supported applications for substation automation. It also discusses the benefits of using GOOSE
message to protect and control applications and the use of IEC 61850.
Having cooperation between multiple autonomous devices against one task is difficult due to each
device having their own decision management based on self-deterministic protocol. Within the selfdeterministic
protocol, a formation management task should be considered along another task in order
to provide cooperation and consideration between the operating autonomous devices. In this research,
a compound learning control system for formation management of multiple control agents is proposed
by managing coordination between multiple autonomous agents along with other tasks simultaneously
in an operation. A series of simulation based on an autonomous robot was conducted to evaluate the
effectiveness of learning through compound knowledge for providing consideration among achieving
goals or coordination configuration against partner robot. The proposed system was able to provide
consideration in coordination among operating partners in a task of achieving goal.
Plurality voter is one of the commonest voting methods for decision making in highly-reliable applications in which the reliability and safety of the system is critical. To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. The asymptotic analysis of the new proposed algorithm has demonstrated that it has a time complexity of O(log n) which is less than time complexity of sequential plurality algorithm, i.e. O (n log n).
Malaysia is a tropical country and it is subjected to flooding in both the urban and rural areas. Flood
modelling can help to reduce the impacts of flood hazard by taking extra precautions. HEC-RAS model was used to predict the flood levels at selected reach of the Langat River with a total length of 34.4 km. The Langat River is located in the state of Selangor, Malaysia and it is subjected to regular flooding. The selected reach of the Langat River has insufficient data and a methodology was proposed to overcome this particular problem. Since complete floodplain data for the area are not available, the modelling therefore assumed vertical walls at the left and right banks of the Langat River and all the predicted flood levels above the banks were based on this assumption. The HECRAS model was calibrated and the values of Manning’s coefficients of roughness for the Langat River were found to range from 0.04 to 0.10. The discharge values were calculated for 5, 10, 25, 50, and 100 year return periods and the maximum predicted flood depth ranged from 2.1m to 7.8m. Meanwhile, the model output was verified using the historical record and the error between the recorded and predicted water levels was found to range from 3% to 15%.
In this study, nitrogen doped titanium dioxide-based dye-sensitised solar cell was successfully fabricated
using screen printing technique to discover the optimisation of process parameters for the solar cell
efficiency using response surface methodology (RSM). Parameter optimisation has been a major concern
in solar cell fabrication. The selected parameters were: nitrogen concentration (15-25 mg of urea), the
film thickness (25-60 µm) and dye loading time (12-24 hours), the optimum condition which yields the
highest efficiency of 3.5% was at 15 mg nitrogen concentration, 25 µm film thickness and 24-hours dye
loading time. Film thickness was found to have a significant influence on efficiency while the loading
time exceeding 18 hours has the least significant effect.
There are many variables involved in the real life problem so it is difficult to choose an efficient model out of all possible models relating to analytical factors. Interaction terms affecting the model also need to be addressed because of its vital role in the actual dataset. The current study focused on efficient model selection for collector efficiency of solar dryer. For this purpose, collector efficiency of solar dryer was used as a dependent variable with time, inlet temperature, collector average temperature and solar radiation as independent variables. Hybrid of the least absolute shrinkage and selection operator (LASSO) and robust regression were proposed for the identification of efficient model selection. The comparison was made with the ordinary least square (OLS) after performing a multicollinearity and coefficient test and with a ridge regression analysis. The final selected model was obtained using eight selection criteria (8SC). To forecast the efficient model, the mean absolute percentage error (MAPE) was used. As compared to other methods, the proposed method provides a more efficient model with minimum MAPE.
Solar drier is considered to be an important product used in the internet of things (IoT). It is used to dry different kinds of products used in agriculture or aquaculture. There are many factors that have different effects on the drying of items in the solar drier. The current study focused on the removal of the moisture ratio in the drying process for seaweed using solar drier. For this purpose, a dataset containing 1924 observations was used to study the effect of six different independent variables on the dependent variable. Moisture ratio removal (%) was considered to be dependent variable with ambient temperature, chamber temperature, collector temperature, chamber relative humidity, ambient relative humidity and solar radiation as independent variables. All possible models were used in the analysis till fifth order interaction terms. Hybrid model of LASSO with bisquare M was proposed for efficient selection of the model. The procedure based on four phases was used for efficient model selection and a comparison was made with other existing sparse and robust regression techniques. The result indicates that the proposed technique is better than other existing techniques in terms of mean squared error (MSE) and mean absolute percentage error (MAPE).
Application of the Internet of things (IoT) for data collection in solar drying can be very efficient in collecting big data of drying parameters. There are many variables involved so it is hard to find a model to predict the moisture content of the food product during drying. In model building, interaction terms should be incorporated because they also contribute to the model. Eight selection criteria (8SC) is a very useful method in model building. This study applied ordinary least squares (OLS) regression and ridge regression with 8SC in model building to predict the moisture content of drying fish. A total of eighty models were considered in this study. One best model was chosen each from OLS regression and ridge regression. M78.7.3 with a total of eleven independent variables was the best OLS model after conducting multicollinearity and coefficient test. Next, the best ridge model M56.0.0 was obtained after the coefficient test. The mean absolute percentage error (MAPE) was used to measure the accuracy of the prediction model. For OLS model M78.7.3, the MAPE value was 15.7342. The MAPE value for ridge model M56.0.0 was 17.4054. From the MAPE value, OLS model M78.7.3 provided a better estimation than the ridge model M56.0.0. However, OLS model M78.7.3 violated the normality assumptions of residuals. This is highly caused by the outlier problem. So, due to non- normality of the residuals and presence of outliers in the dataset, ridge regression is preferred for the best forecast model.
Exoskeleton Robot is one of the most significant examples of human-oriented robotic devices.
Nevertheless, the main challenge remains the complexity of their mechanical design and human-robot interfaces. This paper is an outcome of a research to model and to simulate the support of mobility of an elderly people using exoskeleton. Exoskeleton is developed in order to complement the corporal deficiencies of an elderly person in standing up and sitting down. When the natural joint torques is integrated with the exoskeleton’s torque the result is in an overall torque that is comparable to that of a physically normal person. This work focuses on standing-up and sitting-down movements. Appropriate simulation models are formulated and their performances examined against measured data. The results with PID control show that at different speed of standing up and sitting down, the joint torques can be compromised. This is done within allowable limits.
The issue of classifying objects into groups when measured variables in an experiment are mixed has attracted the attention of statisticians. The Smoothed Location Model (SLM) appears to be a popular classification method to handle data containing both continuous and binary variables simultaneously. However, SLM is infeasible for a large number of binary variables due to the occurrence of numerous empty cells. Therefore, this study aims to construct new SLMs by integrating SLM with two variable extraction techniques, Principal Component Analysis (PCA) and two types of Multiple Correspondence Analysis (MCA) in order to reduce the large number of mixed variables, primarily the binary ones. The performance of the newly constructed models, namely the SLM+PCA+Indicator MCA and SLM+PCA+Burt MCA are examined based on misclassification rate. Results from simulation studies for a sample size of n=60 show that the SLM+PCA+Indicator MCA model provides perfect classification when the sizes of binary variables (b) are 5 and 10. For b=20, the SLM+PCA+Indicator MCA model produces misclassification rates of 0.3833, 0.6667 and 0.3221 for n=60, n=120 and n=180, respectively. Meanwhile, the SLM+PCA+Burt MCA model provides a perfect classification when the sizes of the binary variables are 5, 10, 15 and 20 and yields a small misclassification rate as 0.0167 when b=25. Investigations into real dataset demonstrate that both of the newly constructed models yield low misclassification rates with 0.3066 and 0.2336 respectively, in which the SLM+PCA+Burt MCA model performed the best among all the classification methods compared. The findings reveal that the two new models of SLM integrated with two variable extraction techniques can be good alternative methods for classification purposes in handling mixed variable problems, mainly when dealing with large binary variables.
The major aim of this research was to investigate the addition of BPSC on the physical and rheological properties of asphalt binder. In this study, addition of five different percentages of BPSC compositions were studied, namely (2, 4, 6 and 8%). The impact of modifier on the rheological and physical properties was determined using conventional tests, such as softening point, ductility and penetration, and measurements from a dynamic shear rheometer. Based on the results, it was observed that the addition of BPSC has a significant impact on the rheological properties of asphalt binder and would improve rutting resistance at high temperatures. Meanwhile, results related to physical properties indicated that a decrease in penetration and increase in softening points results in stiffness of BPSC. The results showed that BPSC reduced temperature susceptibility and increased stiffness and elastic behaviour in comparison to unmodified asphalt binder. This means BPSC would increase the resistance of permanent deformation (rutting). Finally, BPSC could be considered as an appropriate additive to modify the properties of asphalt binder.
This paper presents a mathematical approach to solve railway rescheduling problems. The approach assumes that the trains are able to resume their journey after a given time frame of disruption whereby The train that experiences disruption and trains affected by the incident are rescheduled. The approach employed mathematical model to prioritise certain types of train according the railway operator’s requirement. A pre-emptive goal programming model was adapted to find an optimal solution that satisfies the operational constraints and the company’s stated goals. Initially, the model minimises the total service delay of all trains while adhering to the minimum headway requirement and track capacity. Subsequently, it maximises the train service reliability by only considering the trains with delay time window of five minutes or less. The model uses MATLAB R2014a software which automatically generates the optimal solution of the problem based on the input matrix of constraints. An experiment with three incident scenarios on a double-track railway of local network was conducted to evaluate the performance of the proposed model. The new provisional timetable was produced in short computing time and the model was able to prioritise desired train schedule.