A systematic technique for cost-effective CO<Subscript>2</Subscript> emission reduction in process plants

There has been growing interests to reduce the environmental impact caused by greenhouse gas emissions from process plants through various energy conservation strategies. CO₂ emissions are closely linked to energy generation, conversion, transmission and utilisation. Various studies on the design of energy-efficient processes, optimal mix of renewable energy and hybrid power system are driven to reduce reliance on fossil fuel as well as CO₂ emissions reduction. This paper presents a systematic technique in the form of graphical visualisation tool for cost-effective CO₂ emission reduction strategies in industry. The methodology is performed in four steps. The first step involves calculating the energy consumption of a process plant. This is followed by identification of potential strategies to reduce CO₂ emissions using the CO₂ management hierarchy as a guide. In the third step, the development of “Investment” versus “CO₂ Reduction” (ICO₂) plot is constructed to measure the optimal CO₂ emission reductions achieved from the implementation of possible CO₂ reduction strategies. The Systematic Hierarchical Approach for Resilient Process Screening (Wan Alwi and Manan in AIChE J 11:3981–3988, 2006) method is used in the fourth step via substitution or partial implementation of the various CO₂ reduction options in order to meet the cost-effective emission reduction within the desired investment limit or payback period (PP). An illustrative case study on a palm oil refinery plant has been used to demonstrate the implementation of the method in reduction of CO₂ emissions. The developed graphical tool provides an insight-based approach for systematic CO₂ emission reduction in the palm oil refinery considering both heat and power energy sources. Result shows that 31.2 % reduction in CO₂ emissions can be achieved with an investment of USD 38,212 and PP of 10 months based on the present energy prices in Malaysia.     

Optimum lipid production using agro-industrial wastewater treated microalgae as biofuel substrate

Abundant wastewater discharges from palm oil industries in tropical nations being a valuable resource of biodiesel need proper exploration. Research hinted that such wastewater as economical nutrient source or substrate can support the cultivation of microalgae. In this experiment, we have tested the growth and lipid production of five different microalgal strains in palm oil mill effluent (POME). POME as a biofuel substrate is demonstrated to be lucrative for microalgae-assisted lipids production. POME is rich in macro- and micronutrients can be used as a growth medium for algal growth in order to reduce the growth medium cost and environmental pollutions. Among the five microalgal strains tested, Chlorella sorokiniana revealed optimum biomass and lipid production. The productivity was evaluated in terms of chlorophyll content, growth rate, biomass, and lipid content, which discerned to be 0.099/day, 8.0 mg/L day and 2.68 mg/mg cell dry weight (CDW). Furthermore, in this study, an optimization study was carried out to enhance the microalgae to produce high lipid content using carbon-to-nitrogen ratio and different light/dark periods. The presence of nitrogen combined glucose (with a carbon-to-nitrogen ratio 100:7) as an alternative source to carbon displayed higher lipid production of 2.68 (mg/mg CDW) by C. sorokiniana. This study confirms that 8:16 h light/dark condition at C:TN ratio of 100:7 supported to produce high lipid content of 17 mg lipid/mg CDW. The above results revealed that POME could be a suitable growth media for the alga C. sorokiniana to improve the maximum lipid yield for biofuels production.     

Generative regular-freeform surface recognition for generating material removal volume from stock model

The present paper illustrates the development of generative surface recognition for regular and freeform. To obtain the final form of product, material removal volume generation from a stock model is also discussed. Only a few studies integrated the regular and freeform surfaces to provide a comprehensive definition of surface recognition as well as for the volumetric estimation of removal material in finishing and roughing operations. The current research deploys a comprehensive surface recognition approach that can recognise both regular and freeform surfaces based on the geometry as well as loop entity of a face. In contrast to the regular surface that can be categorised into a particular group of geometrical shape, such as cylindrical shape, the proposed approach enables the recognition of a freeform surface that cannot be defined as a generic geometrical shape. In addition, the new method also simplifies the existing surface recognition for regular surfaces. The material removal volumes created consist of machining volumes for finishing and roughing operations needed to be machined to obtain the final form of the product. The present research provides a unique user customisation feature that enables user to specify the volumetric thickness for material removal volume in the finishing operation as well as the size for the stock model. These estimated volumes are prepared for subsequent manufacturing applications, such as sequencing of machining operation.     

Effects of computer-based educational achievement test on test performance and test takers’ motivation

There has been an increasing interest in recent years in developing and using computer-based tests in educational assessment. To replace paper-based tests with computer-based ones, the standards for developing computerized-assessment (International Test Commission., 2004) requires equivalent test scores to be established for the new computer-based test and the conventional paper-based test. However, in most test mode comparability studies, the actual test items used have been identical, and yet significant differences have been found in test scores in paper-based and computer-based modes. This has been reported for several subjects, including science, languages and mathematics. The validity of using computer-based tests in educational assessment must therefore be questioned. This study involves a biology test and a biology motivation questionnaire using a Solomon four-group experimental design to examine the validity of the computer-based test and its effects on test performance and the motivation of test-takers. The findings provide supportive evidence for the validity of computer-based test in educational assessment.     

Applied Genetic Algorithm for Solving Rich VRP

In this article, we present a study of the effectiveness of a genetic algorithm (GA) to solve a combinatorial problem, that is, a vehicle routing problem (VRP). We propose a new selection method, called “rank and select,” based on selection rate, and we compare it with roulette wheel selection. In this article, we use two types of crossover method and two types of mutation method. These are applied for comparing the best fitness at the end of a generation. The problem solved in this study is how to generate feasible route combinations for a rich VRP and meet all the requirements with an optimum solution. Initial test results show that the route produced by the GA was effectively used for solving rich VRP and especially for a large number of customers, depots, and vehicles. Fuel consumption by proposed routes was lower by about 20.38% compared to that of an existing route.     

Fuzzy logic-based pre-classifier for tropical wood species recognition system

Classifying tropical wood species poses a considerable economic challenge and failure to classify the wood species accurately can have significant effects on timber industries. The problem of wood recognition is compounded with the nonlinearities of the features among the similar wood species. Besides that, large wood databases presented a problem of large processing time especially for online wood recognition system. In view of these problems, we propose the use of fuzzy logic-based pre-classifier as a means of treating uncertainty to improve the classification accuracy of tropical wood recognition system. The pre-classifier serve as a clustering mechanism for the large database simplifying the classification process making it more efficient. The use of the fuzzy logic-based pre-classifier has managed to increase the accuracy of the wood recognition system by 4 % and reduce the processing time for training and testing by more than 75 % and 26 % respectively.     

An adaptive and efficient dimension reduction model for multivariate wireless sensor networks applications

Wireless sensor networks (WSNs) applications are growing rapidly in various fields such as environmental monitoring, health care management, and industry control. However, WSN's are characterized by constrained resources especially; energy which shortens their lifespan. One of the most important factors that cause a rapid drain of energy is radio communication of multivariate data between nodes and base station. Besides, the dynamic changes of environmental variables pose a need for an adaptive solution that cope with these changes over the time. In this paper, a new adaptive and efficient dimension reduction model (APCADR) is proposed for hierarchical sensor networks based on the candid covariance-free incremental PCA (CCIPCA). The performance of the model is evaluated using three real sensor networks datasets collected at Intel Berkeley Research Lab (IBRL), Great St. Bernard (GSB) area, and Lausanne Urban Canopy Experiments (LUCE). Experimental results show 33.33% and 50% reduction of multivariate data in dynamic and static environments, respectively. Results also show that 97–99% of original data is successfully approximated at cluster heads in both environment types. A comparison with the multivariate linear regression model (MLR) and simple linear regression model (SLR) shows the advantage of the proposed model in terms of efficiency, approximation accuracy, and adaptability with dynamic environmental changes.     

Chemical composition, in vitro cytotoxic and antioxidant activities of the essential oil and major constituents of Cymbopogon jawarancusa (Kashmir)

The chemical composition of the hydrodistillate of aerial parts of Cymbopogon jawarancusa, a natural grass considered as major forage for animal nutrition, used in food because of the presence of sufficient concentration of minerals like calcium and potassium was analysed by capillary GC–FID, GC–MS and ¹³C NMR. Seventeen constituents representing 97.8% of the total oil with piperitone (58.6%) and elemol (18.6%) as major constituents were identified. In vitro cytotoxicity of the oil and its constituents on human cancer cell lines THP-1 (leukemia), A-549 (lung), HEP-2 (liver) and IGR-OV-1 (ovary) was evaluated by Sulphorhodamine-B assay. The oil was found to be more potent than its components against cancer cell lines tested with IC₅₀ of 6.5 μg/ml (THP-1), 6.3 μg/ml (A-549), 7.2 μg/ml (HEP-2) and 34.4 μg/ml (IGR-OV-1). Antioxidant activity of oil and its constituents was evaluated by DPPH assay. In conclusion, the results demonstrate potent cytotoxic and antioxidant effects of oil, and its components like piperitone, α-pinene, β-caryophyllene and β-elemene.     

Effect of cobalt-60 γ radiation on the physical and chemical properties of poly(ethylene terephthalate) polymer

The structural, optical, and morphological properties of Co⁶⁰ γ irradiation on poly(ethylene terephthalate) polymer samples were studied with X-ray diffraction (XRD), ultraviolet–visible spectroscopy, scanning electron microscopy (SEM), and Raman spectroscopy. The diffraction pattern of virgin sample showed that the polymer was semicrystalline in nature. However, because of irradiation, the crystallinity decreased up to a dose level of 110 kGy and increased up to 300 kGy. The crystallite size, strain, and dislocation were calculated from the XRD data, and the crystallite size decreased from 291.07 to 346.90 Å. The absorption edge shifted from 315 to 330 nm, and the band gap of the samples decreased from 3.79 to 3.66 eV. The SEM micrographs showed radial bulging along with inhomogeneous liner exfoliation, and also, a rocky shape pattern with different sizes was observed. A significant change was found in the Raman spectra of the γ-irradiated polymer at the highest dose. The results of the structural, optical, and morphological studies show recovery characteristics at the highest dose level of 300 kGy. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012