Search results for: Quaternion vector measure

Authors: Harleen Kaur

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Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.

Keywords: Data Mining Community, Knowledge Discovery inDatabases (KDD), Interestingness, Subjective Measures, Actionability.

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: Corporate reputation, fuzzy logic, fuzzy model, stock market investors.

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: Equivalent Martingale Measure, European Put Option, Girsanov Theorem, Martingales, Monte Carlo method, option price valuation, option price valuation formula.

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Authors: Sultan Alotaibi, Dmitri Roussinov

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Many governments recently started to change the ways of providing their services by allowing their citizens to access services from anywhere without the need of visiting the location of the service provider. Mobile government (M-government) is one of the techniques that fulfill that goal. It has been adopted by many governments. M-government can be defined as an implementation of Electronic Government (E-Government) by using mobile technology with the aim of improving service delivery to citizens, businesses and all government agencies. There have been several research projects developing models to understand the behavior of individuals towards the adoption of m-government. This paper proposes a model for adoption of m-government services in Saudi Arabia by extending Technology Acceptance Model (TAM) by introducing external factors. This paper also reports on the development of a survey instrument designed to measure user perception of mobile government acceptance. A survey instrument has been developed by using existing scales from prior instruments and a pilot study has been conducted by distributing the survey to 33 participants. As a result, a survey instrument has been refined to retain 43 items. The results also showed that the reliabilities of all the scales in the survey instrument are above the levels acceptable in current academic research, thus the instruments developed by us are capable of analyzing the factors in M-government adoption.

Keywords: TAM, m-government, e-government, model, acceptance.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.

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Authors: Niaz Gharavi, Hexin Zhang

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The shear modulus of a timber beam can be determined using torsion test or shear field test method. The shear field test method is based on shear distortion measurement of the beam at the zone with the constant transverse load in the standardized four-point bending test. The current code of practice advises using two metallic arms act as an instrument to measure the diagonal displacement of the constructing square. The size and the position of the constructing square might influence the shear modulus determination. This study aimed to investigate the size and the position effect of the square in the shear field test method. A binocular stereo vision system has been employed to determine the 3D displacement of a grid of target points. Six glue laminated beams were produced and tested. Analysis of Variance (ANOVA) was performed on the acquired data to evaluate the significance of the size effect and the position effect of the square. The results have shown that the size of the square has a noticeable influence on the value of shear modulus, while, the position of the square within the area with the constant shear force does not affect the measured mean shear modulus.

Keywords: Shear field test method, structural-sized test, shear modulus of Glulam beam, photogrammetry approach.

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Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: Area-based traffic, car-following model, micro-simulation, stochastic modeling.

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Authors: G. Tamilpavai, C. Vishnuppriya

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Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.

Keywords: Bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM.

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Authors: Futoshi Kakuta, Takashi Ishida

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Sewage sludge is a biomass resource that can create a solid fuel and electricity. Utilizing sewage sludge as a renewable energy can contribute to the reduction of greenhouse gases. In Japan, the "National Plan for the Promotion of Biomass Utilization" and the “Priority Plan for Social Infrastructure Development" were approved at cabinet meetings in December 2010 and August 2012, respectively, to promote the energy utilization of sewage sludge. This study investigated costs and greenhouse gas emission in different sewage sludge treatments with technologies for energy from sewage sludge. Expenses were estimated based on capital costs and O&M costs including energy consumption of solid fuel plants and biogas power generation plants for sewage sludge. Results showed that the cost of sludge digestion treatment with solid fuel technologies was 8% lower than landfill disposal. The greenhouse gas emission of sludge digestion treatment with solid fuel technologies was also 6,390t as CO2 smaller than landfill disposal. Biogas power generation reduced the electricity of a wastewater treatment plant by 30% and the cost by 5%.

Keywords: Global warming counter measure, energy technology, solid fuel production, biogas.

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Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure Mapping Systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of pressure sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the user's needs. 

Keywords: cushion, image processing, pressure mapping system, wheelchair

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Authors: Abdul Wasy, Balakrishnan G., Yi Qi Wang, Atta Ur Rehman, Jung Il Song

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Vickers indentation is used to measure the hardness of materials. In this study, numerical simulation of Vickers indentation experiment was performed for Diamond like Carbon (DLC) coated materials. DLC coatings were deposited on stainless steel 304 substrates with Chromium buffer layer using RF Magnetron and T-shape Filtered Cathodic Vacuum Arc Dual system The objective of this research is to understand the elastic plastic properties, stress strain distribution, ring and lateral crack growth and propagation, penetration depth of indenter and delamination of coating from substrate with effect of buffer layer thickness. The effect of Poisson-s ratio of DLC coating was also analyzed. Indenter penetration is more in coated materials with thin buffer layer as compared to thicker one, under same conditions. Similarly, the specimens with thinner buffer layer failed quickly due to high residual stress as compared to the coated materials with reasonable thickness of 200nm buffer layer. The simulation results suggested the optimized thickness of 200 nm among the prepared specimens for durable and long service.

Keywords: Thin film, buffer layer. Diamond like Carbon, Vickers indentation, Poisson's ratio, Finite element.

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Authors: Fabian Horn, Reinhard Guthke

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In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.

Keywords: bottom-up approach, gene clusters, melting temperature, metabolic pathway, microarray probe design, probe selection

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: Bio-signals, DC Component, Doppler Effect, ellipse fitting, radar, SDR.

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision.

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Authors: M. A. Hassan, M. H. Sakinah, K. Kadirgama, D. Ramasamy, M. M. Noor, M. M. Rahman

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Tribological properties that include nanoparticles are an alternative to improve the tribological behaviour of lubricating oil, which has been investigated by many researchers for the past few decades. Various nanostructures can be used as additives for tribological improvement. However, this also depends on the characteristics of the nanoparticles. In this study, tribological investigation was performed to examine the effect of CuO nanoparticles on the tribological behaviour of Syntium 800 SL 10W−30. Three parameters used in the analysis using the wear tester (piston ring) were load, revolutions per minute (rpm), and concentration. The specifications of the nanoparticles, such as size, concentration, hardness, and shape, can affect the tribological behaviour of the lubricant. The friction and wear experiment was conducted using a tribo-tester and the Response Surface Methodology method was used to analyse any improvement of the performance. Therefore, two concentrations of 40 nm nanoparticles were used to conduct the experiments, namely, 0.005 wt % and 0.01 wt % and compared with base oil 0 wt % (control). A water bath sonicator was used to disperse the nanoparticles in base oil, while a tribo-tester was used to measure the coefficient of friction and wear rate. In addition, the thermal properties of the nanolubricant were also measured. The results have shown that the thermal conductivity of the nanolubricant was increased when compared with the base oil. Therefore, the results indicated that CuO nanoparticles had improved the tribological behaviour as well as the thermal properties of the nanolubricant oil.

Keywords: Concentration, improvement, tribological, Copper (II) oxide, nanolubricant.

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Authors: Dariush Semnani, Mohammad Sheikhzadeh

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Circular knitting machine makes the fabric with more than two knitting tools. Variation of yarn tension between different knitting tools causes different loop length of stitches duration knitting process. In this research, a new intelligent method is applied to control loop length of stitches in various tools based on ideal shape of stitches and real angle of stitches direction while different loop length of stitches causes stitches deformation and deviation those of angle. To measure deviation of stitch direction against variation of tensions, image processing technique was applied to pictures of different fabrics with constant front light. After that, the rate of deformation is translated to needed compensation of loop length cam degree to cure stitches deformation. A fuzzy control algorithm was applied to loop length modification in knitting tools. The presented method was experienced for different knitted fabrics of various structures and yarns. The results show that presented method is useable for control of loop length variation between different knitting tools based on stitch deformation for various knitted fabrics with different fabric structures, densities and yarn types.

Keywords: Circular knitting, Radon transformation, Knittedfabric, Regularity, Fuzzy control

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Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: Curvelet transform, image enhancement, CBCT, image denoising.

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Authors: A. Gagat-Matuła

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The aim of this article is to present a relation between family relationships and styles of approach to coping with stress among young people from migrant families with cerebral palsy. The study involved 70 persons (with cerebral palsy in the standard intellectual capacity) from families, in which at least one of parents is a migrant. To measure the level of communication in the family, the Family Relationships Questionnaire (FRQ) was employed, while the styles of coping with stress was investigated with the CISS Questionnaire. The relation between family relationships and styles of coping with stressful situations of the respondents was investigated. It was shown that there is an affiliation between the emotion-oriented style of coping with the stress and the variable of “communication in my family”. Moreover, it was demonstrated that there is a linkage between the task-oriented style of coping with the stress and the variable of “maternal control in mother-child relationship”. Young people with CP subjected to overprotection and control from their mothers in problem situations tend to focus on their own emotions instead of trying to undertake constructive actions. Excessive control in daily life by mothers results in passivity and a lack of motivation to cope with difficult situations.

Keywords: Young people with cerebral palsy, family relationships, styles of coping with stress, migration.

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Authors: Bhausaheb L. Pangarkar, M. G. Sane, Saroj B. Parjane, Rajendra M. Abhang, Mahendra Guddad

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Vacuum membrane distillation (VMD) process can be used for water purification or the desalination of salt water. The process simply consists of a flat sheet hydrophobic micro porous PTFE membrane and diaphragm vacuum pump without a condenser for the water recovery or trap. The feed was used aqueous NaCl solution. The VMD experiments were performed to evaluate the heat and mass transfer coefficient of the boundary layer in a membrane module. The only operating parameters are feed inlet temperature, and feed flow rate were investigated. The permeate flux was strongly affected by the feed inlet temperature, feed flow rate, and boundary layer heat transfer coefficient. Since lowering the temperature polarization coefficient is essential enhance the process performance considerable and maximizing the heat transfer coefficient for maximizes the mass flux of distillate water. In this paper, the results of VMD experiments are used to measure the boundary layer heat transfer coefficient, and the experimental results are used to reevaluate the empirical constants in the Dittus- Boelter equation.

Keywords: Desalination, heat and mass transfer coefficient, temperature polarization, membrane distillation

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: Travel characteristics analysis, transportation choice, travel sharing rate, neural network model, traffic resource allocation.

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Authors: D.Y. Su, C.C. Liu, C.M. Chiang, W. Wang

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This study aims to discuss the effect of illumination and the color temperature of the lighting source under the office lighting environment on human psychological and physiological responses. In this study, 21 healthy participants were selected, and the Ryodoraku measurement system was utilized to measure their skin resistance change.The findings indicated that the effect of the color temperature of the lighting source on human physiological responses is significant within 90 min after turning the lights on; while after 90 min the effect of illumination on human physiological responses is higher than that of the color temperature. Moreover, the cardiovascular, digestive and endocrine systems are prone to be affected by the indoor lighting environment. During the long-term exposure to high intensity of illumination and high color temperature (2000Lux -6500K), the effect on the psychological responses turned moderate after the human visual system adopted to the lighting environment. However, the effect of the Ryodoraku value on human physiological responses was more significant with the increase of perceptive time. The effect of long time exposure to a lighting environment on the physiological responses is greater than its effect on the psychological responses. This conclusion is different from the traditional public viewpoint that the effect on the psychological responses is greater.

Keywords: Autonomic nervous system, Human responses, Office Lighting Environment, Ryodoraku, Meridian

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Authors: Abiodun M. Aibinu, Athaur Rahman Najeeb, Momoh J. E. Salami, Amir A. Shafie

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An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. This method is suitable for problems in which the image can be modeled by explicit known source functions with a few adjustable parameters. Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. In this paper, five of the suggested method of evaluating the model order have been evaluated, these are: The Final Prediction Error (FPE), Akaike Information Criterion (AIC), Residual Variance (RV), Minimum Description Length (MDL) and Hannan and Quinn (HNQ) criterion. These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). The result for each criterion is compared to result obtained by the use of a fixed order technique and three measures of similarity were evaluated. Result obtained shows that the use of MDL gives the highest measure of similarity to that use by a fixed order technique.

Keywords: Autoregressive Moving Average (ARMA), MagneticResonance Imaging (MRI), Parametric modeling, Transient Error.

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Authors: M. Amir Abas, M. Dahlui

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This paper presents the investigation results of UV measurement at different level of altitudes and the development of a new portable instrument for measuring UV. The rapid growth of industrial sectors in developing countries including Malaysia, brings not only income to the nation, but also causes pollution in various forms. Air pollution is one of the significant contributors to global warming by depleting the Ozone layer, which would reduce the filtration of UV rays. Long duration of exposure to high to UV rays has many devastating health effects to mankind directly or indirectly through destruction of the natural resources. This study aimed to show correlation between UV and altitudes which indirectly can help predict Ozone depletion. An instrument had been designed to measure and monitors the level of UV. The instrument comprises of two main blocks namely data logger and Graphic User Interface (GUI). Three sensors were used in the data logger to detect changes in the temperature, humidity and ultraviolet. The system has undergone experimental measurement to capture data at two different conditions; industrial area and high attitude area. The performance of the instrument showed consistency in the data captured and the results of the experiment drew a significantly high reading of UV at high altitudes.

Keywords: Ozone Layer, Monitoring, Global Warming, Measurement, Ultraviolet

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Authors: Ghada Badr, Arwa Alturki

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The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: Alignment, RNA secondary structure, pairwise, component-based, data mining.

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Authors: Arpan Paul, Joy Sen

Abstract:

Livability is a holistic concept whose factors include many complex characteristics and levels of interrelationships among them. It has been considered as people’s need for public amenities and is recognized as a major element to create social welfare. The concept and principles of livability are essential for recognizing the significance of community well-being. The attributes and dimensions of livability are also important aspects to measure the overall quality of environment. Livability potential is mainly considered as the capacity to develop into the overall well-being of an urban area in future. The intent of the present study is to identify the prime factors to evaluate livability potential within a metropolis. For ground level case study, the paper has selected Kolkata Metropolitan Area (KMA) as it has wide physical, social, and economic variations within it. The initial part of the study deals with detailed literature review on livability and its significance of evaluating its potential within a metropolis. The next segment is dedicated for identifying the primary factors which would evaluate livability potential within a metropolis. In pursuit of identifying primary factors, which have a direct impact on urban livability, this study delineates the metropolitan area into various clusters, having their distinct livability potential. As a final outcome of the study, variations of livability potential of those selected clusters are highlighted to explain the complexity of the metropolitan development.

Keywords: Livability potential, metropolis, Kolkata Metropolitan Area (KMA), well-being.

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Authors: Camilo Aldana, Sara Cabra, Carlos A. Ospina, Fredy Carvajal, Fernando Rodríguez

Abstract:

It has been proven that early establishment of microbial flora in digestive tract of ruminants, has a beneficial effect on their health condition and productivity. A probiotic compound, made from five bacteria isolated from adult bovine cattle, was dosed to 15 Holstein newborn calves in order to measure its capacity of improving body weight gain and reduce diarrhea incidence. The test was performed in the municipality of Cajicá (Colombia), at 2580 m.a.s.l., throughout rainy season, with environmental temperature that oscillated between 4 to 25 °C. Five calves were allotted to control (no addition of probiotic). Treatments 1, and 2 (5 calves per group) received 10 ml Probiotic mix 1 and 2, respectively. Probiotic mixes 1 and 2 where similar in microbial composition but different in production process. Probiotics were added to the morning milk and dosed on a daily basis by a month and then on a weekly basis for three additional months. Diarrhea incidence was measured by observance of number of animals affected in each group; each animal was weighed up on a daily basis for obtaining weight gain and rumen fluid samples were extracted with oro-esophageal catheter for determining level of fiber and grain consumption.

Keywords: Calve, diarrhea, probiotic, rumen microorganisms.

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Authors: Armando Cartenì, Ilaria Henke

Abstract:

Recently, the Italian government has approved a new law for public contracts and has been laying the groundwork for restarting a planning phase. The government has adopted the indications given by the European Commission regarding the estimation of the external costs within the Cost-Benefit Analysis, and has been approved the ‘Guidelines for assessment of Investment Projects’. In compliance with the new Italian law, the aim of this research was to perform a feasibility study applying quantitative methods regarding the revamping of an Italian tourist railway line. A Cost-Benefit Analysis was performed starting from the quantification of the passengers’ demand potentially interested in using the revamped rail services. The benefits due to the external costs reduction were also estimated (quantified) in terms of variations (with respect to the not project scenario): climate change, air pollution, noises, congestion, and accidents. Estimations results have been proposed in terms of the Measure of Effectiveness underlying a positive Net Present Value equal to about 27 million of Euros, an Internal Rate of Return much greater the discount rate, a benefit/cost ratio equal to 2 and a PayBack Period of 15 years.

Keywords: Cost-benefit analysis, evaluation analysis, demand management, external cost, transport planning, quality.

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Authors: Isaac O. Asante, Yushi Jiang, Hailin Tao

Abstract:

Livestreaming marketing, the new electronic commerce element, has become an optional marketing channel following the COVID-19 pandemic, and many sellers are leveraging the features presented by livestreaming to increase sales. This study was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during livestreaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study presents a way of measuring interactions in livestreaming commerce and proposes a way to manually gather data on consumer behaviors in livestreaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: Livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness.

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Authors: Dayang Nailul Munna Abang Abdullah, Francine Rozario

Abstract:

The main objectives of this study were to identify attributes that influence customer satisfaction and determine their relationships with customer satisfaction. The variables included in this research are place/ambience, food quality and service quality as independent variables and customer satisfaction as the dependent variable. A survey questionnaire which consisted of three parts to measure demographic factors, independent variables, and dependent variables was constructed based on items determined by past research. 149 respondents from one of the well known hotel in Kuala Lumpur, MALAYSIA were selected as a sample. Psychometric testing was conducted to determine the reliability and validity of the questionnaire. From the findings, there were positive significant relationship between place/ambience (r=0.563**, p=0.000) and service quality (r=0.544**, p=0.000) with customer satisfaction. However, although relationship between food quality and customer satisfaction was significant, it was in the negative direction (r=- 0.268**, p=0.001). New findings were discovered after conducting this research and previous research findings were strengthened by the results of this research. Future researchers could concentrate on determining attributes that influence customer satisfaction when cost/price is not a factor and reasons for place/ambience is currently becoming the leading factor in determining customer satisfaction.

Keywords: Ambience, Customer Satisfaction, Food Quality, Service Quality.

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