This paper presents a forecasting study of municipal solid waste generation (MSWG) rate and potential of its recyclable components in Kuala Lumpur (KL), the capital city of Malaysia. The generation rates and composition of solid wastes of various classes such as street cleansing, landscape and garden, industrial and constructional, institutional, residential and commercial are analyzed. The past and present trends are studied and extrapolated for the coming years using Microsoft office 2003 Excel spreadsheet assuming a linear behavior. The study shows that increased solid waste generation of KL is alarming. For instance, the amount of daily residential SWG is found to be about 1.62 kg/capita; with the national average at 0.8-0.9 kg/capita and is expected to be increasing linearly, reaching to 2.23 kg/capita by 2024. This figure seems reasonable for an urban developing area like KL city. It is also found that, food (organic) waste is the major recyclable component followed by mix paper and mix plastics. Along with estimated population growth and their business activities, it has been observed that the city is still lacking in terms of efficient waste treatment technology, sufficient fund, public awareness, maintaining the established norms of industrial waste treatment etc. Hence it is recommended that the concerned authority (DBKL) shall view this issue seriously.
Rainfall-runoff processes in a small oil palm catchment (8.2 ha) in Johor, Malaysia were examined. Storm hydrographs show rapid responses to rainfall with a short time to peak. The estimated initial hydrologic loss for the oil palm catchment is 5 mm. Despite the low initial loss, the catchment exhibits a high proportion of baseflow, approximately 54% of the total runoff. On an event basis, the stormflow response factor and runoff coefficient ranges from 0.003 to 0.21, and 0.02 to 0.44, respectively. Peakflow and stormflow volume were moderately correlated with rainfall. The hydrographs were satisfactorily modelled using the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). The efficiency indexes of the calibration and validation exercises are 0.81 and 0.82, respectively. Based on these preliminary findings, it could be suggested that an oil palm plantation would be able to serve reasonably well in regulating basic hydrological functions.
The current study aims to verify the existing equations for incipient motion for a rigid rectangular channel. Data from experimental work on incipient motion from a rectangular flume with two different widths, namely 0.3 and 0.6 m, were compared with the critical velocity value predicted by the equations of Novak & Nalluri and El-Zaemey. The equation by El-Zaemey performed better with an average discrepancy ratio value of 1.06 compared with the equation by Novak & Nalluri with an average discrepancy ratio value of 0.87. However, as the sediment deposit thickness increased, the equation by El-Zaemey became less accurate. A plot on the Shields Diagram using the experimental data had shown the significant effect of the sediment deposit thickness where, as the deposit becomes thicker, the dimensionless shear stress θ value also increased. A new equation had been proposed by incorporating the sediment deposit thickness. The new equation gave improved prediction with an average discrepancy ratio value of 1.02.
Researchers can adopt one of many different measures of central tendency to examine the effect of a treatment variable across groups. These include least squares means, trimmed means, M-estimators and medians. In addition, some methods begin with a preliminary test to determine the shapes of distributions before adopting a particular estimator of the typical score. We compared a number of recently developed adaptive robust methods with respect to their ability to control Type I error and their sensitivity to detect differences between the groups when data were non-normal and heterogeneous, and the design was unbalanced. In particular, two new approaches to comparing the typical score across treatment groups, due to Babu, Padmanabhan, and Puri, were compared to two new methods presented by Wilcox and by Keselman, Wilcox, Othman, and Fradette. The procedures examined generally resulted in good Type I error control and therefore, on the basis of this critetion, it would be difficult to recommend one method over the other. However, the power results clearly favour one of the methods presented by Wilcox and Keselman; indeed, in the vast majority of the cases investigated, this most favoured approach had substantially larger power values than the other procedures, particularly when there were more than two treatment groups.
This paper presents a theoretical development and critical analysis of the burst frequency equations for capillary valves on a microfluidic compact disc (CD) platform. This analysis includes background on passive capillary valves and the governing models/equations that have been developed to date. The implicit assumptions and limitations of these models are discussed. The fluid meniscus dynamics before bursting is broken up into a multi-stage model and a more accurate version of the burst frequency equation for the capillary valves is proposed. The modified equations are used to evaluate the effects of various CD design parameters such as the hydraulic diameter, the height to width aspect ratio, and the opening wedge angle of the channel on the burst pressure.
The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.
This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon's 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results.
As with all membrane processes, turbulence, as promoted by aeration in submerged membrane bioreactors (MBRs) or pumping in sidestream (SS) systems to produce somewhat higher effective cross-flow velocities, increases mass transfer and reduces fouling. This is manifested in an elevated critical flux, the flux at which the membrane permeability is sustained. However, the non-Newtonian nature of the sludge makes precise rheological characterisation difficult. In this study, a calculation of the appropriate hydrodynamics parameters for a SS MBR configuration is presented. Optimisation of the aeration in a submerged MBR system has been attained by defining the minimum air velocity required for Taylor bubble formation.
Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.
Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17 degrees C to 32 degrees C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years. The model shows that the temperature dependent starvation mortality is an important factor that influences fish population densities. It also shows high fish population densities at some temperature ranges when this consumption need is minimum. Several sensitivity analyses involving variations in temperature terms, food resources and water levels are conducted to ascertain the relative importance of temperature dependence terms.
A significant breakthrough and progress have been made in the study of the kinetics of microbial transformation in sewers under aerobic and under changing aerobic/anaerobic conditions. Fundamental knowledge on anoxic kinetics of wastewater is still lacking, so it is not now possible to apply an integrated approach to municipal wastewater treatment incorporating sewer networks as a bio-chemical reactor. This paper presents the results of studies on determining half saturation constants for nitrate, KNO3, and nitrite, KNO2, in raw wastewater. The average values of KNO3 and KNO2, determined from experiments conducted on 7 different wastewater samples were found to be 0.76 gNO3-N/m3 and 0.33 gNO2-N/m3 respectively.
Recent efforts to promote child survival and development internationally have focused new attention on the importance of the household as a mediator of both environmental risks and programmatic interventions to promote better health. In this paper, we introduce a theoretical framework, the 'developmental niche,' derived from studies of children's behavior and development in different cultural contexts, as a tool for analyzing the household production of health. The developmental niche is conceptualized in terms of three basic components: (1) the physical and social settings of the child's everyday life; (2) culturally regulated customs of child care and child rearing; and (3) the psychology of the caretakers. The relevance of each of these components to the household production of health is illustrated through examples from research in several cultures, including Malaysia, Kenya, Bangladesh, India, and the U.S. Further discussion centers on three corollaries of the developmental niche framework that point to the interactive relationships among the three components, between the niche and the larger environment, and between the niche and the child (or any individual seen from a developmental perspective). It is suggested that this approach is useful for identifying and collecting relevant information on household-level factors that affect health outcomes, and thus for organizing more effective interventions. At a theoretical level, the developmental niche framework also facilitates understanding processes of mutual adaptation between the individual and the environment as they are filtered through the constraints of household settings, customs and caretaker psychologies.
Dispersal-assembly theories of species coexistence posit that environmental factors play no role in explaining community diversity and structure. Dispersal-assembly theories shed light on some aspects of community structure such as species-area and species-abundance relationships. However, species' environmental associations also affect these measures of community structure. Measurements of species' niche breadth and overlap address this influence. Using a new continuous measure of niche and a dispersal-assembly null model that maintains species' niche breadth and aggregation, we tested two hypotheses assessing the effects of habitat heterogeneity on the ability of dispersal-assembly theories to explain community niche structure. We found that in both homogenous and heterogeneous environments dispersal-assembly theories cannot fully explain observed niche structure. The performance of the dispersal-assembly null models was particularly poor in heterogeneous environments. These results indicate that non-dispersal based mechanisms are in part responsible for observed community structure and measures of community structure which include species' environmental associations should be used to test theories of species diversity.
The prediction models of MWQI in mangrove and estuarine zones were constructed. The 2011-2015 data employed in this study entailed 13 parameters from six monitoring stations in West Malaysia. Spatial discriminant analysis (SDA) had recommended seven significant parameters to develop the MWQI which were DO, TSS, O&G, PO4, Cd, Cr and Zn. These selected parameters were then used to develop prediction models for the MWQI using artificial neural network (ANN) and multiple linear regressions (MLR). The SDA-ANN model had higher R2 value for training (0.9044) and validation (0.7113) results than SDA-MLR model and was chosen as the best model in mangrove estuarine zone. The SDA-ANN model had also demonstrated lower RMSE (5.224) than the SDA-MLR (12.7755). In summary, this work suggested that ANN was an effective tool to compute the MWQ in mangrove estuarine zone and a powerful alternative prediction model as compared to the other modelling methods.
It is an essential task to estimate the remaining useful life (RUL) of machinery in the mining sector aimed at ensuring the production and the customer's satisfaction. In this study, a conceptual framework was used to determine the RUL under the reliability analysis in a frailty model. The proposed framework was implemented on a Komatsu PC-1250 excavator from the Sungun copper mine. Also, the Weibull-frailty model was selected to describe the failure behavior and compare it with the classical-exponential model. The frailty model was also used to evaluate the impact of unobserved environmental conditions on the RUL values. Both applied models were fitted to the obtained data from 80 operational hours of the Komatsu PC-1250 excavator. Plotting the results from the reliability analysis of two models demonstrated that the mine system with the frailty model performs better than the classical model before reaching the reliability of 80%. Besides, the frailty model shows a coherent with the operational time of the excavator, while the classical model demonstrates a sinusoid variation. The obtained results may be used for the development of maintenance, preventive repairs planning, and the spare parts replacement intervals.
For patients with acute respiratory distress syndrome (ARDS), mechanical ventilation (MV) is an essential therapy in the intensive care unit (ICU). Suboptimal PEEP levels in MV can cause ventilator induced lung injury, which is associated with increased mortality, extended ICU stay, and high cost. The ability to predict the outcome of respiratory mechanics in response to changes in PEEP would thus provide a critical advantage in personalising and improving care. Testing the potentially dangerous high pressures would not be required to assess their impact. A nonlinear autoregressive (NARX) model was used to predict airway pressure in 19 data sets from 10 mechanically ventilated ARDS patients. Patient-specific NARX models were identified from pressure and flow data over one, two, three, or four adjacent PEEP levels in a recruitment manoeuvre. Extrapolation of NARX model elastance functions allowed prediction of patient responses to PEEP changes to higher or lower pressures. NARX model predictions were more successful than those using a well validated first order model (FOM). The most clinically important results were for extrapolation up one PEEP step of 2cmH2O from the highest PEEP in the training data. When the NARX model was trained on one PEEP level, the mean RMS residual for the extrapolation PEEP level was 0.52 (90% CI: 0.47-0.57) cmH2O, compared to 1.50 (90% CI: 1.38-1.62) cmH2O for the FOM. When trained on four PEEP levels, the NARX result was 0.50 (90% CI: 0.42-0.58) cmH2O, and was 1.95 (90% CI: 1.71-2.19) cmH2O for the FOM. The results suggest that a full recruitment manoeuvre may not be required for the NARX model to obtain a useful estimate of the pressure waveform at higher PEEP levels. The methodology could thus allow clinicians to make informed decisions about ventilator PEEP settings while reducing the risk associated with high PEEP, and subsequent high peak airway pressures.
Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.
With the rapid development of technology, mobile phones have become an essential tool in terms of crime fighting and criminal investigation. However, many mobile forensics investigators face difficulties with the investigation process in their domain. These difficulties are due to the heavy reliance of the forensics field on knowledge which, although a valuable resource, is scattered and widely dispersed. The wide dispersion of mobile forensics knowledge not only makes investigation difficult for new investigators, resulting in substantial waste of time, but also leads to ambiguity in the concepts and terminologies of the mobile forensics domain. This paper developed an approach for mobile forensics domain based on metamodeling. The developed approach contributes to identify common concepts of mobile forensics through a development of the Mobile Forensics Metamodel (MFM). In addion, it contributes to simplifying the investigation process and enables investigation teams to capture and reuse specialized forensic knowledge, thereby supporting the training and knowledge management activities. Furthermore, it reduces the difficulty and ambiguity in the mobile forensics domain. A validation process was performed to ensure the completeness and correctness of the MFM. The validation was conducted using two techniques for improvements and adjustments to the metamodel. The last version of the adjusted metamodel was named MFM 1.2.
Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning.
Conventional seismic rehabilitation methods may not be suitable for some buildings owing to their high cost and time-consuming foundation work. In recent years, viscoelastic dampers (VEDs) have been widely used in many mid- and high-rise buildings. This study introduces a viscoelastic passive control system called rotary rubber braced damper (RRBD). The RRBD is an economical, lightweight, and easy-to-assemble device. A finite element model considering nonlinearity, large deformation, and material damage is developed to conduct a parametric study on different damper sizes under pushover cyclic loading. The fundamental characteristics of this VED system are clarified by analyzing building structures under cyclic loading. The result show excellent energy absorption and stable hysteresis loops in all specimens. Additionally, by using a sinusoidal shaking table test, the effectiveness of the RRBD to manage the response displacement and acceleration of steel frames is considered. The RRBD functioned at early stages of lateral displacement, indicating that the system is effective for all levels of vibration. Moreover, the proposed damper shows significantly better performance in terms of the column compression force resulting from the brace action compared to chevron bracing (CB).