Search results for: laboratory classes

Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

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When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: Degree of coverage, deposition of liquid, nozzle, spraying.

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Authors: S. J. Mitchual, K. Frimpong-Mensah, N. A. Darkwa

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The fuel potential of six tropical hardwood species namely: Triplochiton scleroxylon, Ceiba pentandra, Aningeria robusta, Terminalia superba, Celtis mildbreadii and Piptadenia africana were studied. Properties studied included species density, gross calorific value, volatile matter, ash content, organic carbon and elemental composition. Fuel properties were determined using standard laboratory methods. The result indicates that the gross calorific value (GCV) of the species ranged from 20.16 to 22.22 MJ/kg and they slightly varied from each other. Additionally, the GCV of the biomass materials were higher than that of other biomass materials like; wheat straw, rice straw, maize straw and sugar cane. The ash and volatile matter content varied from 0.6075 to 5.0407%, and 75.23% to 83.70% respectively. The overall rating of the properties of the six biomass materials suggested that Piptadenia africana has the best fuel property to be used as briquettes and Aningeria robusta the worse. This study therefore suggests that a holistic assessment of a biomass material needs to be done before selecting it for fuel purpose.

Keywords: Ash content, Briquette, Calorific value, Elemental composition, Species, Volatile matter.

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Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

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In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during fluctuations in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain a balanced power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: Droop control, droop characteristic, grid-connected inverter, microgrid, power control.

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Authors: M. Analoui, M. Fadavi Amiri

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The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Keywords: Feature reduction, genetic algorithm, pattern classification, nearest neighbor rule classifiers (k-NNR).

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Authors: John McCullagh, Jaclyn Munge, NivanWeerakkody, Kerrie Gamble

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The aim of this study was to evaluate the effect of preexercise glycerol hyperhydration on endurance performance in a heat chamber designed to simulate the World Championship Distance (WCD) duathlon (10km run, 40km ride, 5 km run). Duathlons are often performed in hot and humid conditions and as a result hydration is a major issue. Glycerol enhances the body’s capacity for fluid retention by inducing hyperhydration, which is theorized to improve thermoregulatory and cardiovascular responses, and thereby improve performance. Six well-trained athletes completed the testing protocol in a heat chamber at the La Trobe University Exercise Physiology Laboratory. Each testing session was approximately 4.5 hours in duration (2 hours of pre-exercise glycerol hyper-hydration followed by approximately 2.5 hours of exercise). The results showed an increased water retention pre-exercise and an improved overall performance of 2.04% was achieved by subjects ingesting the glycerol solution.

Keywords: Endurance performance, glycerol hyperhydration, heat chamber.

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Authors: Tahany W. Sadak, Fouly, A. Anwer, M. Rizk

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The current investigation presents a study on the hydraulic performance of an electro-hydraulic servo solenoid valve controlled linear piston used in hydraulic systems. Advanced methods have been used to measure and record laboratory experiments, to ensure accurate analysis and evaluation. Experiments have been conducted under different values of temperature (28, 40 and 50 °C), supply pressure (10, 20, 30, 40 and 50 bar), system stiffness (32 N/mm), and load (0.0 & 5560 N). It is concluded that increasing temperature of hydraulic oil increases the quantity of flow rate, so it achieves an increase of the quantity of flow by 5.75 % up to 48.8 % depending on operating conditions. The values of pressure decay at low temperature are less than the values at high temperature. The frequency increases with the increase of the temperature. When we connect the springs to the system, it decreases system frequency. These results are very useful in the process of packing and manufacturing of fluid products, where the properties are not affected by 50 °C, so energy and time are saved.

Keywords: Electro Hydraulic Servo Valve, fluid power control system, system stiffness, static and dynamic performance.

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Authors: M. D. Stelescu, E. Manaila, G. Craciun, D. Ighigeanu

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The goal of the paper is to present the results regarding the influence of the irradiation dose and amount of multifunctional monomer trimethylol-propane trimethacrylate (TMPT) on ethylene-propylene-diene terpolymer rubber (EPDM) mixtures irradiated in electron beam. Blends, molded on an electrically heated laboratory roller mill and compressed in an electrically heated hydraulic press, were irradiated using the ALID 7 of 5.5 MeV linear accelerator in the dose range of 22.6 kGy to 56.5 kGy in atmospheric conditions and at room temperature of 25 °C. The share of cross-linking and degradation reactions was evaluated by means of sol-gel analysis, cross-linking density measurements, FTIR studies and Charlesby-Pinner parameter (p₀/q₀) calculations. The blends containing different concentrations of TMPT (3 phr and 9 phr) and irradiated with doses in the mentioned range have present the increasing of gel content and cross-linking density. Modified and new bands in FTIR spectra have appeared, because of both cross-linking and chain scission reactions.

Keywords: Electron beam irradiation, EPDM rubber, crosslinking density, gel fraction.

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Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

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In wastewater treatment processes, aeration introduces air into a liquid. In these systems, air is introduced by different devices submerged in the wastewater. Smaller bubbles result in more bubble surface area per unit of volume and higher oxygen transfer efficiency. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. The principle of jet pumps is their ability to transfer energy of one fluid, called primary or motive, into a secondary fluid or gas. These pumps have no moving parts and are able to work in remote areas under extreme conditions. The objective of this work is to study experimentally the characteristics of the jet pump and the size of air bubbles in the laboratory water tank. The effect of flow rate ratio on pump performance is investigated in order to have a better understanding about pump behavior under various conditions, in order to determine the efficiency of receiving air bubbles different sizes. The experiments show that we should take care when increasing the flow rate ratio while seeking to decrease bubble size in the outlet flow. This study will help improve and extend the use of the jet pump in many practical applications.

Keywords: Jet pump, air bubbles size, retention time.

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Authors: Kraipat Cheenkachorn, Piyawat Jintanatham, Sarun Rattanaprapa

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In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.

Keywords: papaya, microwave-vacuum drying, effective diffusivity, Page's model

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Authors: Junko Hara, Yoshishige Kawabe, Takeshi Komai, Chihiro Inoue

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The chemical degradation of dieldrin in ferric sulfide and iron powder aqueous suspension was investigated in laboratory batch type experiments. To identify the reaction mechanism, reduced copper was used as reductant. More than 90% of dieldrin was degraded using both reaction systems after 29 days. Initial degradation rate of the pesticide using ferric sulfide was superior to that using iron powder. The reaction schemes were completely dissimilar even though the ferric ion plays an important role in both reaction systems. In the case of metallic iron powder, dieldrin undergoes partial dechlorination. This reaction proceeded by reductive hydrodechlorination with the generation of H+, which arise by oxidation of ferric iron. This reductive reaction was accelerated by reductant but mono-dechlorination intermediates were accumulated. On the other hand, oxidative degradation was observed in the reaction with ferric sulfide, and the stable chemical structure of dieldrin was decomposed into water-soluble intermediates. These reaction intermediates have no chemical structure of drin class. This dehalogenation reaction assumes to occur via the adsorbed hydroxyl radial generated on the surface of ferric sulfide.

Keywords: Dieldrin, kinetics, pesticide residue, soil remediation

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Authors: Sotirios N. Raptis

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The paper links social needs to social classes by the creation of cohorts of public services matched as causes to other ones as effects using cause-effect (CE) models. It then compares these associations using CE and typical regression methods (LR, ARMA). The paper discusses such public service groupings offered in Scotland in the long term to estimate the risk of multiple causes or effects that can ultimately reduce the healthcare cost by linking the next services to the likely causes of them. The same generic goal can be achieved using LR or ARMA and differences are discussed. The work uses Health and Social Care (H&Sc) public services data from 11 service packs offered by Public Health Services (PHS) Scotland that boil down to 110 single-attribute year series, called ’factors’. The study took place at Macmillan Cancer Support, UK and Abertay University, Dundee, from 2020 to 2023. The paper discusses CE relationships as a main method and compares sample findings with Linear Regression (LR), ARMA, to see how the services are linked. Relationships found were between smoking-related healthcare provision, mental-health-related services, and epidemiological weight in Primary-1-Education Body-Mass-Index (BMI) in children as CE models. Insurance companies and public policymakers can pack CE-linked services in plans such as those for the elderly, low-income people, in the long term. The linkage of services was confirmed allowing more accurate resource planning.

Keywords: Probability, regression, cause-effect cohorts, data frames, services, prediction.

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include the cost of infrastructure, personnel, and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion, and various indirect costs in terms of air transport. This research aims to predict the probabilistic crash prediction of vehicles using Machine Learning due to natural and structural reasons by excluding spontaneous reasons, like overspeeding, etc., in the United States. These factors range from meteorological elements such as weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity, to human-made structures, like road structure components such as Bumps, Roundabouts, No Exit, Turning Loops, Give Away, etc. The probabilities are categorized into ten distinct classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes in all states collected by the US government. The probability of the crash was determined by employing Multinomial Expected Value, and a classification label was assigned accordingly. We applied three classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-depth insights through exploratory data analysis.

Keywords: Road safety, crash prediction, exploratory analysis, machine learning.

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Authors: Inaki Maulida Hakim, T. Yuri M. Zagloel, Astari Wulandari

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Six sigma is a framework that is used to identify inefficiency so that the cause of inefficiency will be known and right improvement to overcome cause of inefficiency can be conducted. This paper presents result of implementing six sigma to improve piston assembly line in Manufacturing Laboratory, Universitas Indonesia. Six sigma framework will be used to analyze the significant factor of inefficiency that needs to be improved which causes bottleneck in assembly line. After analysis based on six sigma framework conducted, line balancing method was chosen for improvement to overcome causative factor of inefficiency which is differences time between workstation that causes bottleneck in assembly line. Then after line balancing conducted in piston assembly line, the result is increase in efficiency. Efficiency is shown in the decreasing of Defects per Million Opportunities (DPMO) from 900,000 to 700,000, the increasing of level of labor productivity from 0.0041 to 0.00742, the decreasing of idle time from 121.3 seconds to 12.1 seconds, and the increasing of output, which is from 1 piston in 5 minutes become 3 pistons in 5 minutes.

Keywords: Assembly line, efficiency, improvement, line balancing, productivity, six sigma, workstation.

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Authors: Abdelsalam A. Ahmed

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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is derived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: Permanent magnet synchronous motor, mode predictive control, optimization of DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP.

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Authors: Jiakai Li, Gursel Serpen, Steven Selman, Matt Franchetti, Mike Riesen, Cynthia Schneider

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This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Keywords: Bayesian network classifier, renal transplantation, graft survival period, United Network for Organ Sharing

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Authors: M. D. Stelescu, E. Manaila, G. Pelin, M. Georgescu, M. Sonmez

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This paper presents studies on the development and characterization of nanocomposites based on ethylene-propylene terpolymer rubber (EPDM), chlorobutyl rubber (IIR-Cl) and organically modified montmorillonite (OMMT). Mixtures were made containing 0, 3 and 6 phr (parts per 100 parts rubber) OMMT, respectively. They were obtained by melt intercalation in an internal mixer - Plasti-Corder Brabender, in suitable blending parameters, at high temperature for 11 minutes. Curing agents were embedded on a laboratory roller at 70-100 ºC, friction 1:1.1, processing time 5 minutes. Rubber specimens were obtained by compression, using a hydraulic press at 165 ºC and a pressing force of 300 kN. Curing time, determined using the Monsanto rheometer, decreases with the increased amount of OMMT in the mixtures. At the same time, it was noticed that mixtures containing OMMT show improvement in physical-mechanical properties. These types of nanocomposites may be used to obtain rubber seals for the space application or for other areas of application.

Keywords: Chlorobutyl rubber, ethylene-propylene-diene terpolymers, montmorillonite, rubber seals, space application.

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Authors: A. Majid Bahari, Kourosh Hejazi

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Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stress Model (ASM). In order to account for turbulent scalar fluxes, general gradient diffusion hypothesis has been used along with Boussinesq gradient diffusion hypothesis with a variable turbulent Schmidt number and additional empirical constant c3ε.To simulate buoyant flow domain a 2D vertical numerical model (WISE, Width Integrated Stratified Environments), based on Reynolds- Averaged Navier-Stokes (RANS) equations, has been deployed and the model has been further developed for different k-ε turbulence closures. Results are compared against measured laboratory values of a saline gravity current to explore the efficient turbulence model.

Keywords: Buoyant flows, Buoyant k-ε turbulence model, saline gravity current.

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Authors: Mehdi Seifollahi, Ashkan Forootan, Sajjad Bahrami Reyhan

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Due to the complexity of olefinic plants, various environmental pollutants exist such as NO_x, CO₂, Tar Water, and most importantly Spent Caustic. In this paper, instead of investigating ways of treating this pollutant, we evaluated the production in relation to plant’s variable items. We primarily discussed the factors affecting the quality of the output spent caustic such as impurities in the feed of olefin plant, the amount of injected dimethyl disulfide (DMDS) in furnaces, variation in feed composition, differences among gas temperatures and the concentration of caustic solution at the bottom of the tower. The results of the laboratory proved that in the formation of Red Oil, 1,3butadiene and acetaldehyde followed free radical and aldol condensation mechanism respectively. By increasing the injection rate of DMDS, Mercaptide amount increases in the effluent. In addition, pyrolysis gasoline accumulation is directly related to caustic concentration in the tower. Increasing naphtenes in the liquid feed augments the amount of 1,3butadiene, as one of the sources of Red Oil formation. By increasing the oxygenated compound in the feed, the rate of acetaldehyde formation, as the main source of Red Oil formation, increases.

Keywords: Olefin, spent caustic, red oil, caustic wash tower.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: Seyed Abolhasan Naeini, M. Mortezaee

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Various factors such as the method of installation, the pile type, the pile material and the pile shape, can affect the final bearing capacity of a pile executed in the soil; among them, the method of installation is of special importance. The physical modeling is among the best options in the laboratory study of the piles behavior. Therefore, the current paper first presents and reviews the frustum confining vessel (FCV) as a suitable tool for physical modeling of deep foundations. Then, by describing the loading tests of two open-ended and closed-end steel piles, each of which has been performed in two methods, “with displacement" and "without displacement", the effect of end conditions and installation method on the final bearing capacity of the pile is investigated. The soil used in the current paper is silty sand of Firuzkuh, Iran. The results of the experiments show that in general the without displacement installation method has a larger bearing capacity in both piles, and in a specific method of installation the closed ended pile shows a slightly higher bearing capacity.

Keywords: physical modeling, frustum confining vessel, pile, bearing capacity, installation method

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Authors: Wael M Albadri, Hassnen M Jafer, Ehab H Sfoog

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Relationship between undrained shear strength (Su) and over consolidation ratio (OCR) of clay soil (marine clay) is very important in the field of geotechnical engineering to estimate the settlement behaviour of clay and to prepare a small scale physical modelling test. In this study, a relationship between shear strength and OCR parameters was determined using the laboratory vane shear apparatus and the fully automatic consolidated apparatus. The main objective was to establish non-linear correlation formula between shear strength and OCR and comparing it with previous studies. Therefore, in order to achieve this objective, three points were chosen to obtain 18 undisturbed samples which were collected with an increasing depth of 1.0 m to 3.5 m each 0.5 m. Clay samples were prepared under undrained condition for both tests. It was found that the OCR and shear strength are inversely proportional at similar depth and at same undrained conditions. However, a good correlation was obtained from the relationships where the R2 values were very close to 1.0 using polynomial equations. The comparison between the experimental result and previous equation from other researchers produced a non-linear correlation which has a similar pattern with this study.

Keywords: Shear strength, over-consolidation ratio, vane shear test, clayey soil.

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Authors: Pragya Paneru

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This paper explores altogether 10 primary teachers’ views on gender representation in primary level textbooks. Data were collected from the teachers who taught in private schools in the Kailali and Kathmandu districts. This research uses a semi-structured interview method to obtain information regarding teachers’ attitudes toward gender representations in textbook contents. The interview data were analysed by using critical skills of qualitative research. The findings revealed that most of the teachers were unaware and regarded gender issues as insignificant to discuss in primary-level classes. Most of them responded to the questions personally and claimed that there were no gender issues in their classrooms. Some of the teachers connected gender issues with contexts other than textbook representations such as school discrimination in the distribution of salary among male and female teachers, school practices of awarding girls rather than boys as the most disciplined students, following girls’ first rule in the assembly marching, encouraging only girls in the stage shows, and involving students in gender-specific activities such as decorating works for girls and physical tasks for boys. The interview also revealed teachers’ covert gendered attitudes in their remarks. Nevertheless, most of the teachers accepted that gender-biased contents have an impact on learners and this problem can be solved with more gender-centred research in the education field, discussions, and training to increase awareness regarding gender issues. Agreeing with the suggestion of teachers, this paper recommends proper training and awareness regarding how to confront gender issues in textbooks.

Keywords: Content analysis, gender equality, school education, critical awareness.

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Authors: A. Salsabili, M.Aghajani Mir, S.Saheri, Noor Ezlin Ahmad Basri

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The main aims in this research are to study the solid waste generation in the Faculty of Engineering and Built Environment in the UKM and at the same time to determine composition and some of the waste characteristics likewise: moisture content, density, pH and C/N ratio. For this purpose multiple campaigns were conducted to collect the wastes produced in all hostels, faculties, offices and so on, during 24th of February till 2nd of March 2009, measure and investigate them with regard to both physical and chemical characteristics leading to highlight the necessary management policies. Research locations are Faculty of Engineering and the Canteen nearby that. From the result gained, the most suitable solid waste management solution will be proposed to UKM. The average solid waste generation rate in UKM is 203.38 kg/day. The composition of solid waste generated are glass, plastic, metal, aluminum, organic and inorganic waste and others waste. From the laboratory result, the average moisture content, density, pH and C/N ratio values from the solid waste generated are 49.74%, 165.1 kg/m3, 5.3, and 7:1 respectively. Since, the food waste (organic waste) were the most dominant component, around 62% from the total waste generated hence, the most suitable solid waste management solution is composting.

Keywords: Solid Waste, Waste Management, Characterizationand Composition

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Authors: J. Siame, H. Kasaini

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The proof of concept experiments were conducted to determine the feasibility of using small amounts of Dissolved Sulphur (DS) from the gaseous phase to precipitate platinum ions in chloride media. Two sets of precipitation experiments were performed in which the source of sulphur atoms was either a thiosulphate solution (Na2S2O3) or a sulphur dioxide gas (SO2). In liquid-liquid (L-L) system, complete precipitation of Pt was achieved at small dosages of Na2S2O3 (0.01 – 1.0 M) in a time interval of 3-5 minutes. On the basis of this result, gas absorption tests were carried out mainly to achieve sulphur solubility equivalent to 0.018 M. The idea that huge amounts of precious metals could be recovered selectively from their dilute solutions by utilizing the waste SO2 streams at low pressure seemed attractive from the economic and environmental point of views. Therefore, mass transfer characteristics of SO2 gas associated with reactive absorption across the gas-liquid (G-L) interface were evaluated under different conditions of pressure (0.5 – 2 bar), solution temperature ranges from 20 – 50 oC and acid strength (1 – 4 M, HCl). This paper concludes with information about selective precipitation of Pt in the presence of cations (Fe2+, Co2+, and Cr3+) in a CSTR and recommendation to scale up laboratory data to industrial pilot scale operations.

Keywords: CSTR, diffusivity, platinum, selective precipitation, sulphur dioxide, thiosulphate.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Shafiq Alam, Mirza Hossain, Hesam Hassan Nejad

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Impurity metals such as manganese and cadmium from high-tenor cobalt electrolyte solution were selectively removed by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters such as pH, organic concentration, O/A ratio, kinetics etc. were investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities removal process for the production of pure cobalt with less trouble in the electrowinning circuit.

Keywords: Manganese, Cadmium, Cobalt, D2EHPA, Solvent extraction.

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Authors: Anna Romanova, Mojtaba Mahmoodian, Upul Chandrasekara, Morteza A. Alani

Abstract:

Corrosion of concrete sewer pipes induced by sulphuric acid attack is a recognised problem worldwide, which is not only an attribute of countries with hot climate conditions as thought before. The significance of this problem is by far only realised when the pipe collapses causing surface flooding and other severe consequences. To change the existing post-reactive attitude of managing companies, easy to use and robust models are required to be developed which currently lack reliable data to be correctly calibrated. This paper focuses on laboratory experiments of establishing concrete pipe corrosion rate by submerging samples in to 0.5pH sulphuric acid solution for 56 days under 10ºC, 20ºC and 30ºC temperature regimes. The result showed that at very early stage of the corrosion process the samples gained overall mass, at 30ºC the corrosion progressed quicker than for other temperature regimes, however with time the corrosion level for 10ºC and 20ºC regimes tended towards those at 30ºC. Overall, at these conditions the corrosion rates of 10 mm/year, 13,5 mm/year and 17 mm/year were observed.

Keywords: Sewer pipes, concrete corrosion, sulphuric acid, concrete coupons, corrosion rate.

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Authors: Ibrahim A. Akasha, Lydia Campbell, Stephen R. Euston

Abstract:

Date palm (Phoenix dactylifera L.) seeds are waste streams which are considered a major problem to the food industry. They contain potentially useful protein (10-15% of the whole date-s weight). Global production, industrialisation and utilisation of dates are increasing steadily. The worldwide production of date palm fruit has increased from 1.8 million tons in 1961 to 6.9 million tons in 2005, thus from the global production of dates are almost 800.000 tonnes of date palm seeds are not currently used [1]. The current study was carried out to convert the date palm seeds into useful protein powder. Compositional analysis showed that the seeds were rich in protein and fat 5.64 and 8.14% respectively. We used several laboratory scale methods to extract proteins from seed to produce a high protein powder. These methods included simple acid or alkali extraction, with or without ultrafiltration and phenol trichloroacetic acid with acetone precipitation (Ph/TCA method). The highest protein content powder (68%) was obtained by Ph/TCA method with yield of material (44%) whereas; the use of just alkali extraction gave the lowest protein content of 8%, and a yield of 32%.

Keywords: Date palm seed, Phoenix dactylifera L., extraction of date palm seed protein

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Authors: Kamal K.Bharadwaj, Rekha Kandwal

Abstract:

An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Keywords: Cumulative learning, clustering, data mining, hierarchical production rules.

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

Abstract:

With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: Dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation; pressure drop.

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