Abstract: Computing with Words (CWW) and Possibilistic Relational Universal Fuzzy (PRUF) are the two concepts which widely represent and measure the vaguely defined natural phenomenon. In this paper, we study the positional alteration of the phrases by which the impact of a natural language proposition gets affected and/or modified. We observe the gradations due to sensitivity/feeling of a statement towards the positional alterations. We derive the classification and modification of the meaning of words due to the positional alteration. We present the results with reference to set theoretic interpretations.
Abstract: This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.
Abstract: The earliest theories of sloshing waves and solitary waves based on potential theory idealisations and irrotational flow have been extended to be applicable to more realistic domains. To this end, the computational fluid dynamics (CFD) methods are widely used. Three-dimensional CFD methods such as Navier-Stokes solvers with volume of fluid treatment of the free surface and Navier-Stokes solvers with mappings of the free surface inherently impose high computational expense; therefore, considerable effort has gone into developing depth-averaged approaches. Examples of such approaches include Green–Naghdi (GN) equations. In Cartesian system, GN velocity profile depends on horizontal directions, x-direction and y-direction. The effect of vertical direction (z-direction) is also taken into consideration by applying weighting function in approximation. GN theory considers the effect of vertical acceleration and the consequent non-hydrostatic pressure. Moreover, in GN theory, the flow is rotational. The present study illustrates the application of GN equations to propagation of sloshing waves and solitary waves. For this purpose, GN equations solver is verified for the benchmark tests of Gaussian hump sloshing and solitary wave propagation in shallow basins. Analysis of the free surface sloshing of even harmonic components of an initial Gaussian hump demonstrates that the GN model gives predictions in satisfactory agreement with the linear analytical solutions. Discrepancies between the GN predictions and the linear analytical solutions arise from the effect of wave nonlinearities arising from the wave amplitude itself and wave-wave interactions. Numerically predicted solitary wave propagation indicates that the GN model produces simulations in good agreement with the analytical solution of the linearised wave theory. Comparison between the GN model numerical prediction and the result from perturbation analysis confirms that nonlinear interaction between solitary wave and a solid wall is satisfactorilly modelled. Moreover, solitary wave propagation at an angle to the x-axis and the interaction of solitary waves with each other are conducted to validate the developed model.
Abstract: Tropaeolum majus L. is a native plant to South and Central America, used since ancient times by our ancestors to combat different diseases. Glucotropaeolonin is one of its main components, which when hydrolyzed, forms benzyl isothiocyanate (BIT) that promotes cellular apoptosis (programmed cell death in cancer cells). Therefore, the present research aims to evaluate the effect of the pressure and temperature of BIT extraction by supercritical CO2 from Tropaeolum majus L. The extraction was carried out in a supercritical fluid extractor equipment Speed SFE BASIC Brand: Poly science, the leaves of Tropaeolum majus L. were ground for one hour and lyophilized until obtaining a humidity of 6%. The extraction with supercritical CO2 was carried out with pressures of 200 bar and 300 bar, temperatures of 50°C, 60°C and 70°C, obtained by the conjugation of these six treatments. BIT was identified by thin layer chromatography using 98% BIT as the standard, and as the mobile phase hexane: dichloromethane (4:2). Subsequently, BIT quantification was performed by high performance liquid chromatography (HPLC). The highest yield of oleoresin by supercritical CO2 extraction was obtained pressure 300 bar and temperature at 60°C; and the higher content of BIT at pressure 200 bar and 70°C for 30 minutes to obtain 113.615 ± 0.03 mg BIT/100 g dry matter was obtained.
Abstract: Over recent years, web development has changed significantly. Driven largely by the rise of trends like mobiles, the world of development is rapidly evolving. The rise of the Internet makes web applications crucial nowadays. The web application has been an interface for a company and one of the ways they present their portfolio to the client. On the other hand, the web has become part of the file management system which takes over the role of paper. Due to high demand in web applications, developers are required to develop a web application that are cost-effective, secure and well coded. A framework has been proposed to develop an application rather than using library style development. The framework is helping the developer in creating the structure of a web automatically. This paper will compare the advantages and disadvantages of web development using framework against library-style development. This comparison is based on a previous research paper focusing on two main indicators, which are the impact to management and impact to the developer.
Abstract: Crop yield prediction is a paramount issue in
agriculture. The main idea of this paper is to find out efficient
way to predict the yield of corn based meteorological records.
The prediction models used in this paper can be classified into
model-driven approaches and data-driven approaches, according to
the different modeling methodologies. The model-driven approaches are based on crop mechanistic
modeling. They describe crop growth in interaction with their
environment as dynamical systems. But the calibration process of
the dynamic system comes up with much difficulty, because it
turns out to be a multidimensional non-convex optimization problem.
An original contribution of this paper is to propose a statistical
methodology, Multi-Scenarios Parameters Estimation (MSPE), for the
parametrization of potentially complex mechanistic models from a
new type of datasets (climatic data, final yield in many situations).
It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction
is free of the complex biophysical process. But it has some strict
requirements about the dataset.
A second contribution of the paper is the comparison of these
model-driven methods with classical data-driven methods. For this
purpose, we consider two classes of regression methods, methods
derived from linear regression (Ridge and Lasso Regression, Principal
Components Regression or Partial Least Squares Regression) and
machine learning methods (Random Forest, k-Nearest Neighbor,
Artificial Neural Network and SVM regression).
The dataset consists of 720 records of corn yield at county scale
provided by the United States Department of Agriculture (USDA) and
the associated climatic data. A 5-folds cross-validation process and
two accuracy metrics: root mean square error of prediction(RMSEP),
mean absolute error of prediction(MAEP) were used to evaluate the
crop prediction capacity.
The results show that among the data-driven approaches, Random
Forest is the most robust and generally achieves the best prediction
error (MAEP 4.27%). It also outperforms our model-driven approach
(MAEP 6.11%). However, the method to calibrate the mechanistic
model from dataset easy to access offers several side-perspectives.
The mechanistic model can potentially help to underline the stresses
suffered by the crop or to identify the biological parameters of interest
for breeding purposes. For this reason, an interesting perspective is
to combine these two types of approaches.
Abstract: The global concern about climate change has been increasing, since the emission of gases from human activities contributes to the greenhouse effect in the atmosphere, indicating significant impacts to the planet in the coming years. The study of precipitation regime is fundamental for the development of research in several areas. Among them are hydrology, agriculture, and electric sector. Using the climatic projections of the models belonging to the CMIP5, the main objective of the paper was to present an analysis of the impacts of climate change without rainfall in the Uruguay River basin. After an analysis of the results, it can be observed that for the future climate, there is a tendency, in relation to the present climate, for larger numbers of dry events, mainly in the winter months, changing the pluviometric regime for wet summers and drier winters. Given this projected framework, it is important to note the importance of adequate management of the existing water sources in the river basin, since the value of rainfall is reduced for the next years, it may compromise the dynamics of the ecosystems in the region. Facing climate change is fundamental issue for regions and cities all around the world. Society must improve its resilience to phenomenon impacts, and spreading the knowledge among decision makers and citizens is also essential. So, these research results can be subsidies for the decision-making in planning and management of mitigation measures and/or adaptation in south Brazil.
Abstract: The transition of a student with a disability from school to work is the most crucial phase while moving from the stage of adolescence into early adulthood. In this process, young individuals face various difficulties and challenges in order to accomplish the next venture of life successfully. In this respect, this paper aims to examine the challenges encountered by the individuals with intellectual disabilities in transition to work in Saudi Arabia. For this purpose, this study has undertaken a qualitative research-based methodology; wherein interpretivist philosophy has been followed along with inductive approach and exploratory research design. The data for the research has been gathered with the help of semi-structured interviews, whose findings are analysed with the help of thematic analysis. Semi-structured interviews were conducted with parents of persons with intellectual disabilities, officials, supervisors and specialists of two vocational rehabilitation centres providing training to intellectually disabled students, in addition to that, directors of companies and websites in hiring those individuals. The total number of respondents for the interview was 15. The purposive sampling method was used to select the respondents for the interview. This sampling method is a non-probability sampling method which draws respondents from a known population and allows flexibility and suitability in selecting the participants for the study. The findings gathered from the interview revealed that the lack of awareness among their parents regarding the rights of their children who are intellectually disabled; the lack of adequate communication and coordination between various entities; concerns regarding their training and subsequent employment are the key difficulties experienced by the individuals with intellectual disabilities. Training in programmes such as bookbinding, carpentry, computing, agriculture, electricity and telephone exchange operations were involved as key training programmes. The findings of this study also revealed that information technology and media were playing a significant role in smoothing the transition to employment of individuals with intellectual disabilities. Furthermore, religious and cultural attitudes have been identified to be restricted for people with such disabilities in seeking advantages from job opportunities. On the basis of these findings, it can be implied that the information gathered through this study will serve to be highly beneficial for Saudi Arabian schools/ rehabilitation centres for individuals with intellectual disability to facilitate them in overcoming the problems they encounter during the transition to work.
Abstract: The physical effects of upstream flow obstructions such
as vegetation on cross-ventilation phenomena of a building are
important for issues such as indoor thermal comfort. Modelling such
effects in Computational Fluid Dynamics simulations may also be
challenging. The aim of this work is to establish the cross-ventilation
jet behaviour in such complex terrain conditions as well as to provide
guidelines on the implementation of CFD numerical simulations in
order to model complex terrain features such as vegetation in an
efficient manner. The methodology consists of onsite measurements
on a test cell coupled with numerical simulations. It was found
that the cross-ventilation flow is highly turbulent despite the very
low velocities encountered internally within the test cells. While no
direct measurement of the jet direction was made, the measurements
indicate that flow tends to be reversed from the leeward to the
windward side. Modelling such a phenomenon proves challenging
and is strongly influenced by how vegetation is modelled. A solid
vegetation tends to predict better the direction and magnitude of the
flow than a porous vegetation approach. A simplified terrain model
was also shown to provide good comparisons with observation. The
findings have important implications on the study of cross-ventilation
in complex terrain conditions since the flow direction does not remain
trivial, as with the traditional isolated building case.
Abstract: Accurate determination of wind turbine performance is necessary for economic operation of a wind farm. At present, the procedure to carry out the power performance verification of wind turbines is based on a standard of the International Electrotechnical Commission (IEC). In this paper, nonparametric statistical inference is applied to designing a simple, inexpensive method of verifying the power performance of a wind turbine. A statistical test is explained, examined, and the adequacy is tested over real data. The methods use the information that is collected by the SCADA system (Supervisory Control and Data Acquisition) from the sensors embedded in the wind turbines in order to carry out the power performance verification of a wind farm. The study has used data on the monthly output of wind farm in the Republic of Macedonia, and the time measuring interval was from January 1, 2016, to December 31, 2016. At the end, it is concluded whether the power performance of a wind turbine differed significantly from what would be expected. The results of the implementation of the proposed methods showed that the power performance of the specific wind farm under assessment was acceptable.
Abstract: Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.
Abstract: The use of nanostructured semiconducting material to catalyze degradation of environmental pollutants still receives much attention to date. One of the desired characteristics for pollutant degradation under ultra-violet visible light is the materials with extended carrier charge separation that allows for electronic transfer between the catalyst and the pollutants. In this work, zinc oxide n-type semiconductor vertically aligned structures were fabricated on silicon (100) substrates using the chemical bath deposition method. The as-synthesized structures were treated with nickel and sulphur. X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy were used to characterize the phase purity, structural dimensions and elemental composition of the obtained structures respectively. Photoluminescence emission measurements showed a decrease in both the near band edge emission as well as the defect band emission upon addition of nickel and sulphur with different concentrations. This was attributed to increased charger-carrier-separation due to the presence of Ni-S material on ZnO surface, which is linked to improved charge transfer during photocatalytic reactions.
Abstract: In recent decades, there have been significant developments in the European Union in the field of collective consumer redress. South East European countries (SEE) covered by this paper, in line with their EU accession priorities and duties under Stabilisation and Association Agreements, have to harmonize their national laws with the relevant EU acquis for consumer protection (Chapter 28: Health and Consumer). In these countries, only minimal compliance is achieved. SEE countries have introduced rudimentary collective redress mechanisms, with modest enforcement of collective redress and case law. This paper is based on comprehensive interdisciplinary research conducted for SEE countries on common principles for injunctive and compensatory collective redress mechanisms, emphasizing cross-national comparisons, underlining issues of commonality and difference aiming to develop recommendations for an adequate enforcement of collective redress. SEE countries are recognized by the sectoral approach for regulating collective redress contrary to the majority of EU Member States with having adopted horizontal approach to collective redress. In most SEE countries, the laws do not recognize compensatory but only injunctive collective redress in consumer protection. All responsible stakeholders for implementation of collective redress in SEE countries, lack information and awareness on collective redress mechanisms and the way they function in practice. Therefore, specific actions are needed in these countries to make the whole system of collective redress for consumer protection operational and efficient. Taking into consideration the various designated stakeholders in collective redress in each SEE countries, there is a need of their mutual coordination and cooperation in order to develop consumer protection system and policies. By putting into practice the national collective redress mechanisms, effective access to justice for all consumers, the principle of rule of law will be secured and appropriate procedural guarantees to avoid abusive litigation will be ensured.
Abstract: The choice evaluation between oil-immersed and dry-type transformers is often controlled by cost, location, and application. This paper compares the electrical performance of liquid- filled and dry-type transformers, which will assist the customer to choose the right and efficient ones for particular applications. An accurate assessment of the time-average flux density, electric field intensity and voltage distribution in an oil-insulated and a dry-type transformer have been computed and investigated. The detailed transformer modeling and analysis has been carried out to determine electrical parameter distributions. The models of oil-immersed and dry-type transformers are developed and solved by using the finite element method (FEM) to compare the electrical parameters. The effects of non-uniform and non-coherent voltage gradient, flux density and electric field distribution on the power losses and insulation properties of transformers are studied in detail. The results show that, for the same voltage and kilo-volt-ampere (kVA) rating, oil-immersed transformers have better insulation properties and less hysteresis losses than the dry-type.
Abstract: A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.
Abstract: With recent trends in Big Data and advancements
in Information and Communication Technologies, the healthcare
industry is at the stage of its transition from clinician oriented to
technology oriented. Many people around the world die of cancer
because the diagnosis of disease was not done at an early stage.
Nowadays, the computational methods in the form of Machine
Learning (ML) are used to develop automated decision support
systems that can diagnose cancer with high confidence in a timely
manner. This paper aims to carry out the comparative evaluation
of a selected set of ML classifiers on two existing datasets: breast
cancer and cervical cancer. The ML classifiers compared in this study
are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest
Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and
Artificial Neural Networks (ANN). The evaluation is carried out based
on standard evaluation metrics Precision (P), Recall (R), F1-score and
Accuracy. The experimental results based on the evaluation metrics
show that ANN showed the highest-level accuracy (99.4%) when
tested with breast cancer dataset. On the other hand, when these
ML classifiers are tested with the cervical cancer dataset, Ensemble
(Bagged Tree) technique gave better accuracy (93.1%) in comparison
to other classifiers.
Abstract: The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.
Abstract: Induction assisted single point incremental forming
(IASPIF) is a flexible method and can be simply utilized to
form a high strength alloys. Due to the interaction between the
mechanical and thermal properties during IASPIF an evaluation for
the process is necessary to be performed analytically. Therefore, a
numerical simulation was carried out in this paper. The numerical
analysis was operated at both room and elevated temperatures
then compared with experimental results. Fully coupled dynamic
temperature displacement explicit analysis was used to simulated the
hot single point incremental forming. The numerical analysis was
indicating that during hot single point incremental forming were a
combination between complicated compression, tension and shear
stresses. As a result, the equivalent plastic strain was increased
excessively by rising both the formed part depth and the heating
temperature during forming. Whereas, the forming forces were
decreased from 5 kN at room temperature to 0.95 kN at elevated
temperature. The simulation shows that the maximum true strain was
occurred in the stretching zone which was the same as in experiment.
Abstract: Emotion dysregulation has been linked to psychopathology in general and, in particular, to substance abuse and other addiction-related disorders, such as eating disorders, impulsive disorder, and gambling. It has been proposed that a lessening of the difficulties in emotion regulation can have a significant positive impact on the treatment of these disorders. The present study explores the association between the progress in the Change & Grow® therapeutic model (5 stages of treatment), and the decrease in the difficulties related to emotion regulation. The Change & Grow® model has five stages of treatment according to the model’s five principles (Truth, Acceptance, Gratitude, Love and Responsibility) and incorporates different therapeutic approaches such as positive psychology, cognitive and behavioral therapy and third generation therapies. The main objective is to understand the impact of the presented therapeutic model on difficulties in emotion regulation in patients with addiction-related disorders. The exploratory study has a cross-sectional design. Participants were 44 (15 women and 29 men) Portuguese patients in the residential Villa Ramadas International Treatment Centre. The instrument used was the Portuguese version of the Difficulties in Emotion Regulation Scale (DERS), which measures six dimensions of emotion regulation (Strategies, Non-acceptance, Awareness, Impulse, Goals, and Clarity). The mean rank scores for both the DERS total score and the Impulse subscale showed statistically significant differences according to Stage of Treatment/Principles. Furthermore, Stage of Treatment/Principles held a negative correlation with the scores of the Non-acceptance and Impulse subscales, as well as the DERS total score. The results indicate that the Change & Grow® model seems to have an impact in lessening the patient’s difficulties in emotion regulation. The Impulse dimension suffered the greater impact, which supports the well-known relevance of impulse control, or related difficulties, in addiction-related disorders.
Abstract: The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM2.5, PM10, NOx, and SO2. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NOx and SO2 reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.