The assessment of examination questions is crucial in educational institutes since examination is one of the most common methods to evaluate students' achievement in specific course. Therefore, there is a crucial need to construct a balanced and high-quality exam, which satisfies different cognitive levels. Thus, many lecturers rely on Bloom's taxonomy cognitive domain, which is a popular framework developed for the purpose of assessing students' intellectual abilities and skills. Several works have been proposed to automatically handle the classification of questions in accordance with Bloom's taxonomy. Most of these works classify questions according to specific domain. As a result, there is a lack of technique of classifying questions that belong to the multi-domain areas. The aim of this paper is to present a classification model to classify exam questions based on Bloom's taxonomy that belong to several areas. This study proposes a method for classifying questions automatically, by extracting two features, TFPOS-IDF and word2vec. The purpose of the first feature was to calculate the term frequency-inverse document frequency based on part of speech, in order to assign a suitable weight for essential words in the question. The second feature, pre-trained word2vec, was used to boost the classification process. Then, the combination of these features was fed into three different classifiers; K-Nearest Neighbour, Logistic Regression, and Support Vector Machine, in order to classify the questions. The experiments used two datasets. The first dataset contained 141 questions, while the other dataset contained 600 questions. The classification result for the first dataset achieved an average of 71.1%, 82.3% and 83.7% weighted F1-measure respectively. The classification result for the second dataset achieved an average of 85.4%, 89.4% and 89.7% weighted F1-measure respectively. The finding from this study showed that the proposed method is significant in classifying questions from multiple domains based on Bloom's taxonomy.
'Causal' direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of 'causal' direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
Landfills are a source of groundwater pollution in Gaza Strip. This study focused on Deir Al Balah landfill, which is a unique sanitary landfill site in Gaza Strip (i.e., it has a lining system and a leachate recirculation system). The objective of this article is to assess the generated leachate quantity and percolation to the groundwater aquifer at a specific site, using the approaches of (i) the hydrologic evaluation of landfill performance model (HELP) and (ii) the water balance method (WBM). The results show that when using the HELP model, the average volume of leachate discharged from Deir Al Balah landfill during the period 1997 to 2007 was around, 6800 m3/year. Meanwhile, the average volume of leachate percolated through the clay layer was 550 m3/year, which represents around 8% of the generated leachate. Meanwhile, the WBM indicated that the average volume of leachate discharged from Deir Al Balah landfill during the same period was around 7660 m3/year--about half of which comes from the moisture content of the waste, while the remainder comes from the infiltration of precipitation and re-circulated leachate. Therefore, the estimated quantity of leachate to groundwater by these two methods was very close. However, compared with the measured leachate quantity, these results were overestimated and indicated a dangerous threat to the groundwater aquifer, as there was no separation between municipal, hazardous and industrial wastes, in the area.
Waste management can be regarded as a cross-cutting environmental 'mega-issue'. Sound waste management practices support the provision of basic needs for general health, such as clean air, clean water and safe supply of food. In addition, climate change mitigation efforts can be achieved through reduction of greenhouse gas emissions from waste management operations, such as landfills. Landfills generate landfill gas, especially methane, as a result of anaerobic degradation of the degradable components of municipal solid waste. Evaluating the mode of generation and collection of landfill gas has posted a challenge over time. Scientifically, landfill gas generation rates are presently estimated using numerical models. In this study the Intergovernmental Panel on Climate Change's Waste Model is used to estimate the methane generated from a Malaysian sanitary landfill. Key parameters of the model, which are the decay rate and degradable organic carbon, are analysed in two different approaches; the bulk waste approach and waste composition approach. The model is later validated using error function analysis and optimum decay rate, and degradable organic carbon for both approaches were also obtained. The best fitting values for the bulk waste approach are a decay rate of 0.08 y(-1) and degradable organic carbon value of 0.12; and for the waste composition approach the decay rate was found to be 0.09 y(-1) and degradable organic carbon value of 0.08. From this validation exercise, the estimated error was reduced by 81% and 69% for the bulk waste and waste composition approach, respectively. In conclusion, this type of modelling could constitute a sensible starting point for landfills to introduce careful planning for efficient gas recovery in individual landfills.
The increasing demand for network applications, such as teleconferencing, multimedia messaging and mobile TV, which have diverse requirements, has resulted in the introduction of Long Term Evolution (LTE) by the Third Generation Partnership Project (3GPP). LTE networks implement resource allocation algorithms to distribute radio resource to satisfy the bandwidth and delay requirements of users. However, the scheduling algorithm problem of distributing radio resources to users is not well defined in the LTE standard and thus considerably affects transmission order. Furthermore, the existing radio resource algorithm suffers from performance degradation under prioritised conditions because of the minimum data rate used to determine the transmission order. In this work, a novel downlink resource allocation algorithm that uses quality of service (QoS) requirements and channel conditions to address performance degradation is proposed. The new algorithm is formulated as an optimisation problem where network resources are allocated according to users' priority, whereas the scheduling algorithm decides on the basis of users' channel status to satisfy the demands of QoS. Simulation is used to evaluate the performance of the proposed algorithm, and results demonstrate that it performs better than do all other algorithms according to the measured metrics.
Workflow-based web service compositions (WB-WSCs) is one of the main composition categories in service oriented architecture (SOA). Eflow, polymorphic process model (PPM), and business process execution language (BPEL) are the main techniques of the category of WB-WSCs. Due to maturity of web services, measuring the quality of composite web services being developed by different techniques becomes one of the most important challenges in today's web environments. Business should try to provide good quality regarding the customers' requirements to a composed web service. Thus, quality of service (QoS) which refers to nonfunctional parameters is important to be measured since the quality degree of a certain web service composition could be achieved. This paper tried to find a deterministic analytical method for dependability and performance measurement using Colored Petri net (CPN) with explicit routing constructs and application of theory of probability. A computer tool called WSET was also developed for modeling and supporting QoS measurement through simulation.
Pulse Shaping Amplifier (PSA) is an essential component in nuclear spectroscopy system. This
amplifier has two functions; to shape the output pulse and performs noise filtering. In this paper,
we describe the procedure for the design and development of a pulse shaping amplifier which can
be used in a nuclear spectroscopy system. This prototype was developed using high performance
electronics devices and assembled on a FR4 type printed circuit board. Performance of this
prototype was tested by comparing it with an equivalent commercial spectroscopy amplifier (Model
Silena 7611). The test results showed that the performance of this prototype was comparable
to the commercial spectroscopic amplifier.
The continuing decline in fertility despite a contraction in contraceptive use in Peninsular Malaysia since the mid-1980s has triggered considerable interest in the reasons behind this phenomenon, such as increase in abortion, sterility, and out-of-wedlock pregnancy. Fertility decline has been attributed to rapid socioeconomic development, which can only influence fertility through the intermediate variables. Application of vital statistics, population census, and survey data of Peninsular Malaysia on Bongaarts's model vindicates that marriage postponement and contraceptive use are the 2 most important proximate determinants of fertility, but the effects are not uniform across the ethnic groups. For instance, the predicted total fertility rate for Chinese and Malays are 2.9 and 1.6, respectively, compared with the observed level of 3.0 and 1.9. Postpartum infecundability and abortion also play a part in explaining ethnic fertility differentials. The fertility inhibiting effects of these proximate determinants have significant implications on reproductive health and future population growth.
Huntington's disease (HD), a neurodegenerative disease, normally starts in the prime of adult life, followed by a gradual occurrence of characteristic psychiatric disturbances and cognitive and motor dysfunction. To the best of our knowledge, there is no treatment available to completely mitigate the progression of HD. Among various therapeutic approaches, exhaustive literature reports have confirmed the medicinal benefits of natural products in HD experimental models. Building on this information, this review presents a brief overview of the neuroprotective mechanism(s) of natural products against in vitro/in vivo models of HD. Relevant studies were identified from several scientific databases, including PubMed, ScienceDirect, Scopus, and Google Scholar. After screening through literature from 2005 to the present, a total of 14 medicinal plant species and 30 naturally isolated compounds investigated against HD based on either in vitro or in vivo models were included in the present review. Behavioral outcomes in the HD in vivo model showed that natural compounds significantly attenuated 3-nitropropionic acid (3-NP) induced memory loss and motor incoordination. The biochemical alteration has been markedly alleviated with reduced lipid peroxidation, increased endogenous enzymatic antioxidants, reduced acetylcholinesterase activity, and increased mitochondrial energy production. Interestingly, following treatment with certain natural products, 3-NP-induced damage in the striatum was ameliorated, as seen histologically. Overall, natural products afforded varying degrees of neuroprotection in preclinical studies of HD via antioxidant and anti-inflammatory properties, preservation of mitochondrial function, inhibition of apoptosis, and induction of autophagy.
In this study, the interactive effects of feed flow rate (QF) and up-flow velocity (V up) on the performance of an up-flow anaerobic sludge fixed film (UASFF) reactor treating palm oil mill effluent (POME) were investigated. Long-term performance of the UASFF reactor was first examined with raw POME at a hydraulic loading rate (HRT) of 3 d and an influent COD concentration of 44300 mg/l. Extreme reactor instability was observed after 25 d. Raw POME was then chemically pretreated and used as feed. Anaerobic digestion of pretreated POME was modeled and analyzed with two operating variables, i.e. feed flow rate and up-flow velocity. Experiments were conducted based on a central composite face-centered design (CCFD) and analyzed using response surface methodology (RSM). The region of exploration for digestion of the pretreated POME was taken as the area enclosed by the feed flow rate (1.01, 7.63 l/d) and up-flow velocity (0.2, 3 m/h) boundaries. Twelve dependent parameters were either directly measured or calculated as response. These parameters were total COD (TCOD) removal, soluble COD (SCOD) removal, effluent pH, effluent total volatile fatty acid (TVFA), effluent bicarbonate alkalinity (BA), effluent total suspended solids (TSS), CH4 percentage in biogas, methane yield (Y M), specific methanogenic activity (SMA), food-to-sludge ratio (F/M), sludge height in the UASB portion and solid retention time (SRT). The optimum conditions for POME treatment were found to be 2.45 l/d and 0.75 m/h for QF and V up, respectively (corresponding to HRT of 1.5 d and recycle ratio of 23.4:1). The present study provides valuable information about interrelations of quality and process parameters at different values of the operating variables.
Delay Tolerant Network (DTN) multi-copy routing protocols are privileged to create and transmit multiple copies of each message that causes congestion and some messages are dropped. This process is known as reactive drop because messages were dropped re-actively to overcome buffer overflows. The existing reactive buffer management policies apply a single metric to drop source, relay and destine messages. Hereby, selection to drop a message is dubious because each message as source, relay or destine may have consumed dissimilar magnitude of network resources. Similarly, DTN has included time to live (ttl) parameter which defines lifetime of message. Hence, when ttl expires then message is automatically destroyed from relay nodes. However, time-to-live (ttl) is not applicable on messages reached at their destinations. Moreover, nodes keep replicating messages till ttl expires even-though large number of messages has already been dispersed. In this paper, we have proposed Priority Queue Based Reactive Buffer Management Policy (PQB-R) for DTN under City Based Environments. The PQB-R classifies buffered messages into source, relay and destine queues. Moreover, separate drop metric has been applied on individual queue. The experiment results prove that proposed PQB-R has reduced number of messages transmissions, message drop and increases delivery ratio.
The study examines the effect of price perception and price appearance on Gen Y's repurchase intention towards snack products of small and medium-sized enterprises (SMEs), along with the mediating roles of consumers' brand experience and preference. A survey method for data collection in the study used with a structured questionnaire, in which the respondents were requested to give their responses to the experiment conducted on local specialty snack products produced by SMEs. Covariance-based structural equation modeling (CB-SEM) was used to analyze the hypothesized relationships in the research model. The findings show that all the direct effects in the proposed model have a significant effect, except for the relationship between price perception and brand preference that there is no significant effect. Similarly, the mediating roles of consumer brand experience and consumer-based brand preference proved to have a significant effect. Finally, the implications of this study will be discussed further.
Numerical studies of blood flow system of aorta coronary sinus conduit were carried out using ANSYSTMCFD simulation. A different model of conduit, which differs in the inlet diameter, was investigated. Theinvestigated inlet diameters are 3 mm, 4 mm and 5 mm. Pressure drop from 80 mmHg to 15 mmHgwas achieved for all the models. The comparison chart was produced to compare the pattern of pressurereduction as well as velocity distribution in each model. From the analysis of coronary sinus conduit,it was found that a narrow tube needs to be incorporated into the conduit produced. This is to inducea venturi effect to reduce the pressure drop of blood within a specific throat length. As conclusion, amodel of 3 mm inlet and a throat diameter of 1.13 mm show satisfactory result for pressure reductionfrom 80 mmHg to 15 mmHg. This particular model also has a lower peak velocity at the inlet zone ofthe throat section, which is more preferable in terms of Reynolds number.
The preparation of tamarind fruit seed granular activated carbon (TSAC) by microwave induced chemical activation for the adsorptive treatment of semi-aerobic landfill leachate has been attempted. The chemical and physical properties of TSAC were examined. A series of column tests were performed to determine the breakthrough characteristics, by varying the operational parameters, hydraulic loading rate (5-20 mL/min) and adsorbent bed height (15-21 cm). Ammonical nitrogen and chemical oxygen demand (COD), which provide a prerequisite insight into the prediction of leachate quality was quantified. Results illustrated an encouraging performance for the adsorptive removal of ammonical nitrogen and COD, with the highest bed capacity of 84.69 and 55.09 mg/g respectively, at the hydraulic loading rate of 5 mL/min and adsorbent bed height of 21 cm. The dynamic adsorption behavior was satisfactory described by the Thomas and Yoon-Nelson models. The findings demonstrated the applicability of TSAC for the adsorptive treatment of landfill leachate.
Poly(ethyl hydrazide)-grafted oil palm empty fruit bunch fibre (peh-g-opefb) was successfully prepared by heating poly(methyl acrylate)-grafted opefb (pma-g-opefb) at 60 °C for 4 h with a solution of hydrazine hydrate (15% v/v) in ethanol. The Fourier transform infrared spectrum of the product shows a secondary amine peak at 3267 cm⁻¹, with amide carbonyl peaks at 1729 cm⁻¹ and 1643 cm⁻¹. The chelating ability of peh-g-opefb was tested with copper ion in aqueous solution. A batch adsorption study revealed that maximum adsorption of copper ion was achieved at pH 5. An isotherm study showed the adsorption follows a Langmuir model, with a maximum adsorption capacity of 43.48 mg g-1 at 25 °C. A kinetic study showed that the adsorption of copper ion rapidly reaches equilibrium and follows a pseudo-second-order kinetic model, with a constant rate of 7.02 × 10⁻⁴ g mg⁻¹ min⁻¹ at 25 °C. The Gibbs free energy, ∆G⁰, value is negative, indicating a spontaneous sorption process. Entropy, ∆S⁰, gives a positive value, indicating that the system is becoming increasingly disordered after the adsorption of copper ion. A positive enthalpy value, ∆H⁰, shows that the endothermic process takes place during the adsorption and is more favourable at high temperatures.
Prenatal Ultrasound (US) is commonly used as a routine procedure on pregnant women. It is generally perceived as a safe procedure due to the use of non-ionizing radiation. However, the neurotoxicity of diagnostic prenatal US was detected to have a correlation with high susceptibility to early developing fetus. This research involved in vivo experimental model by using 3(rd) trimester pregnant Oryctolagus cuniculus and exposing them to US exposures for 30, 60, and 90 minutes at their gestational day (GD) 28-29. The output power and intensities, spatial peak temporal average intensity (ISPTA) of US were varied from 0.4 to 0.7 W and 0.13 to 0.19 W/cm(2) respectively were tested initially in free-field, water. Haematological analysis was carried out to detect any changes in blood constituents. Statistically significant differences were detected in red blood cell (RBC) count (P<0.001), haemoglobin (Hb) concentration (P<0.001) and also platelet (PLT) count (P<0.001) in newborn of Oryctolagus cuniculus. These findings indicate the possibility of US heating in causing defects on studied animal.
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechanisms are unknown. Here, a novel application of a method for predicting disease occurrence that combines machine learning and statistics is used to identify the key spatial scales that define the relationship between zoonotic malaria cases and environmental change. Using data from satellite imagery, a case-control study, and a cross-sectional survey, predictive models of household-level occurrence of P. knowlesi were fitted with 16 variables summarized at 11 spatial scales simultaneously. The method identified a strong and well-defined peak of predictive influence of the proportion of cleared land within 1 km of households on P. knowlesi occurrence. Aspect (1 and 2 km), slope (0.5 km) and canopy regrowth (0.5 km) were important at small scales. By contrast, fragmentation of deforested areas influenced P. knowlesi occurrence probability most strongly at large scales (4 and 5 km). The identification of these spatial scales narrows the field of plausible mechanisms that connect land use change and P. knowlesi, allowing for the refinement of disease occurrence predictions and the design of spatially-targeted interventions.
Groundwater is the main source of water in the Kingdom of Saudi Arabia (KSA). A larger part of groundwater is founded in alluvial (unconfined) aquifers. Prediction of water table elevations in
unconfined aquifers is very useful in water resources planning and management. During the last two
decades, many aquifers in different regions of the KSA experienced significant groundwater decline.
The declines in these aquifers raised concerns over the quantity and quality of groundwater, as well
as concerns over the planning and management policies used in KSA. The main objective of this study was to predict water table fluctuations and to estimate the annual change in water table at an alluvial aquifer at wadi Hada Al Sham near Makkah, KSA. The methodology was achieved using numerical groundwater model (MODFLOW). The model was calibrated and then used to predict water table elevations due to pumping for a period of 5 years. The output of the model was found to be in agreement with the previous records. Moreover, the simulation results also show reasonable declination of water table elevations in the study area during the study period.
Poor water quality is a serious problem in the world which threatens human health, ecosystems, and plant/animal life. Prediction of surface water quality is a main concern in water resource and environmental systems. In this research, the support vector machine and two methods of artificial neural networks (ANNs), namely feed forward back propagation (FFBP) and radial basis function (RBF), were used to predict the water quality index (WQI) in a free constructed wetland. Seventeen points of the wetland were monitored twice a month over a period of 14 months, and an extensive dataset was collected for 11 water quality variables. A detailed comparison of the overall performance showed that prediction of the support vector machine (SVM) model with coefficient of correlation (R(2)) = 0.9984 and mean absolute error (MAE) = 0.0052 was either better or comparable with neural networks. This research highlights that the SVM and FFBP can be successfully employed for the prediction of water quality in a free surface constructed wetland environment. These methods simplify the calculation of the WQI and reduce substantial efforts and time by optimizing the computations.
This study aims to predict and estimate unmeasured terrestrial gamma dose rate (TGDR) using statistical analysis methods to derive a model from the actual measurement based on geological formation and soil type. The measurements of TGDR were conducted in the state of Johor with a total of 3873 measured points which covered all geological formations, soil types and districts. The measurements were taken 1 m above the soil surface using NaI [Ti] detector. The measured gamma dose rates ranged from 9 nGy h(-1) to 1237 nGy h(-1) with a mean value of 151 nGy h(-1). The data have been normalized to fit a normal distribution. Tests of significance were conducted among all geological formations and soil types, using the unbalanced one way ANOVA. The results indicated strong significant differences due to the different geological formations and soil types present in Johor State. Pearson Correlation was used to measure the relations between gamma dose rate based on geological formation and soil type (D(G,S)) with the gamma dose rate based on geological formation (D(G)) or soil type (D(s)). A very good correlation was found between D(G,S) and D(G) or D(G,S) and D(s). A total of 118 pairs of geological formations and soil types were used to derive the statistical contribution of geological formations and soil types to gamma dose rates. The contribution of the gamma dose rate from geological formation and soil type were found to be 0.594 and 0.399, respectively. The null hypotheses were accepted for 83% of examined data, therefore, the model could be used to predict gamma dose rates based on geological formation and soil type information.