Abstract: Lipsticks constitute a significant source of transfer evidence, and can, therefore, provide corroborative or inclusionary evidence in criminal investigation. This study aimed to determine the uniqueness and persistence of different lipstick smears using Thin Layer Chromatography (TLC), and Gas Chromatography with a Flame Ionisation Detector (GC-FID). In this study, we analysed lipstick smears retrieved from tea cups exposed to the environment for up to four weeks. The n-alkane content of each sample was determined using GC-FID, while TLC was used to determine the number of bands, and retention factor of each band per smear. This study shows that TLC gives more consistent results over a 4-week period than GC-FID. It also proposes a maximum exposure time of two weeks for the analysis of lipsticks left in the open using GC-FID. Finally, we conclude that neither TLC nor GC-FID can distinguish lipstick evidence recovered from hypothetical crime scenes.
Abstract: Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.
Abstract: Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.
Abstract: In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.
Abstract: This paper appraises the performances of two control scenarios, for doubly fed induction generator (DFIG) operating in wind generation system (WGS), which are the direct decoupled control (DDC) and indirect decoupled control (IDC). Both control scenarios studied combines vector control and Maximum Power Point Tracking (MPPT) control theory so as to maximize the captured power through wind turbine. Modeling of DFIG based WGS and details of both control scenarios have been presented, a proportional integral controller is employed in the active and reactive power control loops for both control methods. The performance of the both control scenarios in terms of power reference tracking and robustness against machine parameters inconstancy has been shown, analyzed and compared, which can afford a reference to the operators and engineers of a wind farm. All simulations have been implemented via MATLAB/Simulink.
Abstract: Children in today’s world need attention and care even with their physique as obesity is also at the increased. Several factors can be responsible for obesity in children and adequate attention is paramount in other not to accommodate it into adolescent period. This study investigated perceived determinants of obesity among primary school pupils in Eti Osa Local Government area of Lagos State. Descriptive survey research design was used and population was all obese pupils in Eti Osa Local Government Area of Lagos State. 92 pupils were selected from randomly picked 12 primary schools while purposive sampling technique was used to pick primary 4-6 pupils. With the aid of body mass index (BMI) and age percentile chart the obese pupils were selected. The instrument for the study was a self-developed and structured questionnaire on perceived determinant of obesity. The questionnaire was divided into three sections. The Cronbach’s Alpha reliability coefficient of 0.74 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated coded and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X2). Findings of this study revealed that physical activities and parental influences were determinant of obesity. Physical activity is essential in reducing the rate of obesity in Eti Osa Local Government Area both at home and within the school environment. Primary schools need to create more playing ground for pupils to exercise themselves. Parents need to cater for their children diet ensuring not just the quantity but the quality as well.
Abstract: This article identifies the conceptual representations of 128 students enrolled in elementary pre-service teachers’ education in the Province of Quebec, Canada (ages 19-24). To construct their conceptual representations relatively to notions of heat and temperature, we use a qualitative research approach. For that, we distributed them a questionnaire including four questions. The result demonstrates that these students tend to view the temperature as a measure of the hotness of an object or person. They also related the sensation of cold (or warm) to the difference in temperature, and for their majority, the physical change of the matter does not require a constant temperature. These representations are inaccurate relatively to the scientific views, and we will see that they are relevant to the design of teaching strategies based on conceptual conflict.
Abstract: In order to reduce the number of deaths due to heart
problems, we propose the use of Hierarchical Temporal Memory
Algorithm (HTM) which is a real time anomaly detection algorithm.
HTM is a cortical learning algorithm based on neocortex used for
anomaly detection. In other words, it is based on a conceptual theory
of how the human brain can work. It is powerful in predicting unusual
patterns, anomaly detection and classification. In this paper, HTM
have been implemented and tested on ECG datasets in order to detect
cardiac anomalies. Experiments showed good performance in terms
of specificity, sensitivity and execution time.
Abstract: Biscuit is one of the most consumed cereal foods in Nigeria and research has shown that locally available tropical crops like cassava, sweet potato can be made into flour and used in the production of biscuits and other pastries. This study investigates some quality parameters in biscuits made from blends of wheat, cassava and carrot flour. The values of result of samples increased with increasing percentage substitution of cassava and carrot flour in some quality parameter like fiber, ash, gluten content, and carbohydrate. The protein content reduced significantly (P < 0.05) with increasing percentage substitution of cassava and carrot flour which ranged from 14.80% to 11.80% compared with the control sample which had 15.60%. There was a recorded significant increase (P < 0.05) in some mineral composition such as calcium, magnesium, sodium, iron, phosphorus, and vitamin A and C composition as the percentage substitution of cassava and carrot flour increased. During storage stability test, samples stored in the fridge and freezer were found to be the best storage location to preserve the sensory attributes and inhibit microbial growth when compared with storage under the sun and on the shelf. Biscuit made with blends of wheat, cassava and carrot flour can therefore serve as an alternative to biscuits made from 100% wheat flour, as they are richer in vitamin A, vitamin C, carbohydrate, dietary fiber and some essential minerals.
Abstract: This article presents a study of the effect of
a contra-rotating component on the efficiency of centrifugal
compressors. A contra-rotating centrifugal compressor (CRCC) is
constructed using two independent rotors, rotating in the opposite
direction and replacing the single rotor of a conventional centrifugal
compressor (REF). To respect the geometrical parameters of the REF
one, two rotors of the CRCC are designed, based on a single rotor
geometry, using the hub and shroud length ratio parameter of the
meridional contour. Firstly, the first rotor is designed by choosing
a value of length ratio. Then, the second rotor is calculated to be
adapted to the fluid flow of the first rotor according aerodynamics
principles. In this study, four values of length ratios 0.3, 0.4, 0.5, and
0.6 are used to create four configurations CF1, CF2, CF3, and CF4
respectively. For comparison purpose, the circumferential velocity at
the outlet of the REF and the CRCC are preserved, which means that
the single rotor of the REF and the second rotor of the CRCC rotate
with the same speed of 16000rpm. The speed of the first rotor in this
case is chosen to be equal to the speed of the second rotor. The CFD
simulation is conducted to compare the performance of the CRCC
and the REF with the same boundary conditions. The results show
that the configuration with a higher length ratio gives higher pressure
rise. However, its efficiency is lower. An investigation over the entire
operating range shows that the CF1 is the best configuration in this
case. In addition, the CRCC can improve the pressure rise as well
as the efficiency by changing the speed of each rotor independently.
The results of changing the first rotor speed show with a 130% speed
increase, the pressure ratio rises of 8.7% while the efficiency remains
stable at the flow rate of the design operating point.
Abstract: Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.
Abstract: In the present work, a remediation bioprocess based on the use of a local isolate of the microalgae Chlorella vulgaris immobilized in alginate beads is proposed. This process was shown to be effective for the reduction of several chemical and microbial contaminants present in Cildáñez stream, a water course that is part of the Matanza-Riachuelo Basin (Buenos Aires, Argentina). The bioprocess, involving the culture of the microalga in autotrophic conditions in a stirred-tank bioreactor supplied with a marine propeller for 6 days, allowed a significant reduction of Escherichia coli and total coliform numbers (over 95%), as well as of ammoniacal nitrogen (96%), nitrates (86%), nitrites (98%), and total phosphorus (53%) contents. Pb content was also significantly diminished after the bioprocess (95%). Standardized cytotoxicity tests using Allium cepa seeds and Cildáñez water pre- and post-remediation were also performed. Germination rate and mitotic index of onion seeds imbibed in Cildáñez water subjected to the bioprocess was similar to that observed in seeds imbibed in distilled water and significantly superior to that registered when untreated Cildáñez water was used for imbibition. Our results demonstrate the potential of this simple and cost-effective technology to remove urban-water contaminants, offering as an additional advantage the possibility of an easy biomass recovery, which may become a source of alternative energy.
Abstract: Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O2 concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model. Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO2/NOx ratio etc.
Abstract: The under passing tunnels are strongly influenced by the soils around. There are some complexities in the specification of real soil behavior, owing to the fact that lots of uncertainties exist in soil properties, and additionally, inappropriate soil constitutive models. Such mentioned factors may cause incompatible settlements in numerical analysis with the obtained values in actual construction. This paper aims to report a case study on a specific tunnel constructed by NATM. The tunnel has a depth of 11.4 m, height of 12.2 m, and width of 14.4 m with 2.5 lanes. The numerical modeling was based on a 2D finite element program. The soil material behavior was modeled by hardening soil model. According to the field observations, the numerical estimated settlement at the ground surface was approximately four times more than the measured one, after the entire installation of the initial lining, indicating that some unknown factors affect the values. Consequently, the geotechnical parameters are accurately revised by a numerical back-analysis using laboratory and field test data and based on the obtained monitoring data. The obtained result confirms that typically, the soil parameters are conservatively low-estimated. And additionally, the constitutive models cannot be applied properly for all soil conditions.
Abstract: Assessing several individuals intensively over time
yields intensive longitudinal data (ILD). Even though ILD provide
rich information, they also bring other data analytic challenges. One
of these is the increased occurrence of missingness with increased
study length, possibly under non-ignorable missingness scenarios.
Multiple imputation (MI) handles missing data by creating several
imputed data sets, and pooling the estimation results across imputed
data sets to yield final estimates for inferential purposes. In this
article, we introduce dynr.mi(), a function in the R package,
Dynamic Modeling in R (dynr). The package dynr provides a suite
of fast and accessible functions for estimating and visualizing the
results from fitting linear and nonlinear dynamic systems models in
discrete as well as continuous time. By integrating the estimation
functions in dynr and the MI procedures available from the R
package, Multivariate Imputation by Chained Equations (MICE), the
dynr.mi() routine is designed to handle possibly non-ignorable
missingness in the dependent variables and/or covariates in a
user-specified dynamic systems model via MI, with convergence
diagnostic check. We utilized dynr.mi() to examine, in the context
of a vector autoregressive model, the relationships among individuals’
ambulatory physiological measures, and self-report affect valence
and arousal. The results from MI were compared to those from
listwise deletion of entries with missingness in the covariates.
When we determined the number of iterations based on the
convergence diagnostics available from dynr.mi(), differences in
the statistical significance of the covariate parameters were observed
between the listwise deletion and MI approaches. These results
underscore the importance of considering diagnostic information in
the implementation of MI procedures.
Abstract: Pile load tests should be applied to check the bearing capacity calculations and to determine the settlement of the pile corresponding to test load. Strain gauges can be installed into pile in order to determine the shaft resistance of the piles for every soil layer respectively. Detailed results can be obtained by means of strain gauges placed at certain levels into test piles. In the scope of this study, pile load test data obtained from two different projects are examined. Instrumented static pile load tests were applied on totally 7 test bored piles of different diameters (80 cm, 150 cm, and 200 cm) and different lengths (between 30-76 m) in two different project site. Settlement analysis of test piles is done by using some of load transfer methods and finite element method. Plaxis 3D which is a three-dimensional finite element program is also used for settlement analysis of the test piles. In this study, firstly bearing capacity of test piles are determined and compared with strain gauge data which is required for settlement analysis. Then, settlement values of the test piles are estimated by using load transfer methods developed in recent years and finite element method. The aim of this study is to show similarities and differences between the results obtained from settlement analysis methods and instrumented pile load tests.
Abstract: Corporate governance has become a crucial issue in both the business and academic world as a result of world-wide financial scandals and lack of trust in corporate practices. There is no doubt that in order to thrive and attain growth in the market, a company must earn the trust of its stakeholders by consistently delivering on its commitments. Directors of the companies thus comprehend the importance of upfront communication with relevant stakeholders to increase their confidence. The authors of this article argue that practicing good corporate governance is not enough in this highly competitive market place; corporate leaders need to market their good corporate governance practices in order to make the company more attractive to investors. This article also contends that the strength of corporate governance relies wholly upon the extent to which it is communicated simply, effectively and unceasingly to its stakeholders. The main objective of this study, therefore, is to explore the importance of branding good corporate governance in order to increase corporate brand equity, attract investors, and capture market share. A structured questionnaire comprising three sections and a total of 34 questions was prepared and surveyed by the authors among respondents residing in Bangladesh and who also have an academic and corporate background, to investigate the potential impact of branding good corporate governance in the market place. High mean values for individual questions and overall section depict that communicating and branding good corporate governance to the stakeholders will not only boost the investors’ confidence but also increase the corporate brand equity, yielding both profitable and sustainable business environment.
Abstract: With the rapid development of modern communication,
diagnosing the fiber-optic quality and faults in real-time is widely
focused. In this paper, a Labview-based system is proposed for
fiber-optic faults detection. The wavelet threshold denoising method
combined with Empirical Mode Decomposition (EMD) is applied to
denoise the optical time domain reflectometer (OTDR) signal. Then
the method based on Gabor representation is used to detect events.
Experimental measurements show that signal to noise ratio (SNR)
of the OTDR signal is improved by 1.34dB on average, compared
with using the wavelet threshold denosing method. The proposed
system has a high score in event detection capability and accuracy.
The maximum detectable fiber length of the proposed Labview-based
system can be 65km.
Abstract: The β-glucan produced by Ophiocordyceps dipterigena BCC 2073 is a (1, 3)-β-D-glucan with highly branching O-6-linkedside chains that is resistant to acid hydrolysis (by hydrochloric acid and porcine pancreatic alpha-amylase). This β-glucan can be utilized as a prebiotic due to its advantageous structural and biological properties. The effects of using this β-glucan as the sole carbon source for the in vitro growth of two probiotic bacteria (L. acidophilus BCC 13938 and B. animalis ATCC 25527) were investigated. Compared with the effect of using 1% glucose or fructo-oligosaccharide (FOS) as the sole carbon source, using 1% β-glucan for this purpose showed that this prebiotic supported and stimulated the growth of both types of probiotic bacteria and induced them to produce the highest levels of metabolites during their growth. The highest levels of lactic and acetic acid, 10.04 g·L-1 and 2.82 g·L-1, respectively, were observed at 2 h of cultivation using glucose as the sole carbon source. Furthermore, the fermentation broth obtained using 1% β-glucan as the sole carbon source had greater antibacterial activity against selected pathogenic bacteria (B. subtilis TISTR 008, E. coli TISTR 780, and S. typhimurium TISTR 292) than did the broths prepared using glucose or FOS as the sole carbon source. The fermentation broth obtained by growing L. acidophilus BCC 13938 in the presence of β-glucan inhibited the growth of B. subtilis TISTR 008 by more than 70% and inhibited the growth of both S. typhimurium TISTR 292 and E. coli TISTR 780 by more than 90%. In conclusion, O. dipterigena BCC 2073 is a potential source of a β-glucan prebiotic that could be used for commercial production in the near future.
Abstract: The near-field synthetic aperture radar (SAR) imaging
is an advanced nondestructive testing and evaluation (NDT&E)
technique. This paper investigates the complex-valued signal
processing related to the near-field SAR imaging system, where
the measurement data turns out to be noncircular and improper,
meaning that the complex-valued data is correlated to its complex
conjugate. Furthermore, we discover that the degree of impropriety
of the measurement data and that of the target image can be highly
correlated in near-field SAR imaging. Based on these observations, A
modified generalized sparse Bayesian learning algorithm is proposed,
taking impropriety and noncircularity into account. Numerical results
show that the proposed algorithm provides performance gain, with the
help of noncircular assumption on the signals.