Search results for: hyperbolic sine function

Authors: Michelle Micah Augustine

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Soap opera narrative creates a sense of community. Uzalo is a South African local soap opera television series. It is unique because Uzalo tells the story of black people and their everyday struggle centered in KwaMashu township community, which is an excellent example of how moving image culture has contributed in portraying township community that was once marginalized by the apartheid regime in contemporary South Africa. While soap opera importance and promotion of social change and behaviours have been extensively studied throughout history, little research has examined the importance of space and place in its narrative. This study explored the conventional community space and place, the core elements that drive soap opera narrative. By means of qualitative content analysis, the study investigated the construction of public meeting places in Uzalo, using a purposive sampling technique to collect data by choosing episodes. The result indicates that characters convergence in public meeting places in soap opera creates disequilibrium which drives the narrative; reveals that construction of a public meeting place is an important way of creating a minimum of homogeneousness among disparate characters, gives a sense of unified experience drawing on the notion of the particular characteristics or attitude generated from such place. The result shows that the use of camera angles, movements, editing, music and usual tricks (mise-en-scene) applied in the narrative setting function as a guide for viewers comprehension of emotional responses of the story and to connect with the space in which the narrative is set.

Keywords: community, narrative, place, space, soap opera

Procedia PDF Downloads 147

Authors: Rahil Sahragard, Mahmoud Hatami, Rostam Bahadori Khalili

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Diabetes is one of the most important health problems in the world and a chronic disease requiring continuous care and therefore, it is necessary for patients to undergo self-care and nutrition education. This study was conducted to evaluate the effect of nutrition education on the metabolic control of diabetic patients in Tehran in 2015. An experimental study was conducted on 100 patients who had previously been approved by a specialist physician for diabetes and at least one year after their onset. At first, patients without any knowledge of the educational program were selected as sample and from them a checklist containing demographic and specific information about diabetes was filled and were taken three fasting blood glucose and three times fasting blood glucose (5 p.m.) Then, the patients received face-to-face training in the same conditions for 2 weeks in a Mehregan hospital of Tehran, and received 3 months of training, while they were fully monitored and during this time, samples that had a cold or blood pressure-related disease or were admitted to the hospital were excluded from the study. After the end of the study, the checklist was filled again and 3 fasting blood glucose and 3 fasting blood glucose samples were taken, the results were statistically analyzed by MC Nemar's statistical test. The research findings were performed on 100 patients 41.7% male and 58.3% women, the range of age was between 22 and 60 years old, with a duration of diabetes ranging from 1 to 15 years. Abnormal fasting blood glucose from 95% to 48.3% (P <0.0001) and non-fasting blood glucose decreased from 91.6% to 71.2% (P <0.001). Research has shown that training on blood glucose control has been successful, therefore, it is recommended that more research is done in the field of education to help patients with diabetes more comfortable.

Keywords: nutrition education, diabetes, function, insulin, chronic, metabolic control

Procedia PDF Downloads 138

Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

Procedia PDF Downloads 469

Authors: Gregory Chown, Benjamin Infantolino, Christopher Wise, Rachel Holmes, Samantha O'Donnell, Katelyn Pfeiffer, Victoria Ward

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Background: There is a lack of understanding of how Kinesio Tape® physiologically works. Furthermore, few studies compare Kinesio Tape® to other forms of taping. The research question is: Does Kinesio Tape® cause a difference in muscle facilitation, inhibition, and pain, between Kinesio Tape® and no tape for collegiate athletes with self-reported shoulder pain? Method: This quantitative non-randomized design used a convenience sampling method. There were eleven participants with self-reported shoulder pain who were athletes on the men’s and women’s lacrosse and tennis teams. Participants attended one 30-45 minute session for data collection. Each participant received all three taping conditions and performed four repetitions of 120 degrees of active shoulder flexion for the three separate trials (no tape, Kinesio Tape® inhibition, and Kinesio Tape® facilitation). Surface electromyography (sEMG) electrodes were placed on the anterior deltoid, supraspinatus, and lower trapezius to measure muscle facilitation and inhibition. Each participant completed the visual analogue scale (VAS) before and after each trial to measure pain. Results: No statistical significance was found for pain scores on the VAS between the taping methods of facilitation, inhibition, and no tape (p = .118). No statistical significance was found for the percentage of change in muscle function for each taping method; Anterior deltoid (p = .993), supraspinatus (p = .997) and lower trapezius (p = .922). Conclusion: Based on the results, Kinesio Tape® appears to not have an effect on muscle function or pain when utilizing the facilitation or inhibition taping method when compared to no tape.

Keywords: Kinesio tape, muscle facilitation, muscle inhibition, pain

Procedia PDF Downloads 190

Authors: Argyris Karapetsas, Maria Bampou, Andriani Mitropoulou

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The aim of the present work is to study the role of brain function in social awareness processing. Mind controls all the psychosomatic functions. Mind’s functioning enables individual not only to recognize one's own self and propositional attitudes, but also to assign such attitudes to other individuals, and to consider such observed mental states in the elucidation of behavior. Participants and Methods: Twenty (n=20) undergraduate students (mean age 18 years old) were involved in this study. Students participated in a clinical assessment, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Assessment included both electrophysiological (i.e.Event Related Potentials (ERPs) esp.P300 waveform) and neuropsychological tests (Raven's Progressive Matrices (RPM) and Sally-Anne test). Results: Initial assessment’s results confirmed statistically significant differences between the males and females, as well as in score performance to the tests applied. Strong correlations emerged between prefrontal lobe functioning, RPM, Sally-Anne test and P300 latencies. Also, significant dysfunction of mind has been found, regarding its three dimensions (straight, circular and helical). At the end of the assessment, students received consultation and appropriate guidelines in order to improve their intrapersonal and interpersonal skills. Conclusions: Mind and social awareness phenomena play a vital role in human development and may act as determinants of the quality of one’s own life. Meanwhile, brain function is highly correlated with social awareness and it seems that different set of brain structures are involved in social behavior.

Keywords: brain activity, emotions, ERP's, social awareness

Procedia PDF Downloads 193

Authors: Amani Waheed, Mostafa Kofi, Shaymaa Attia, Soha Younis, Basma Abdel Hadi

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Background: Exposure to pesticides is one of the most important occupational risks among farmers in developing countries. Along with the wide use of pesticides in the world, the concerns over their health impacts are rapidly growing. Objective: To investigate thyroid and reproductive hormones and fasting blood glucose levels among farmers chronically exposed to pesticide from East Almnaif district, Ismailia governorate. Methods: An analytical cross-sectional study was conducted on 43 farmers with active involvement pesticides handling and 43 participants not occupationally exposed to pesticides as the control group. A structured interview questionnaire measuring the sociodemographic characteristics, pesticides exposure characteristics, and safety measures was used. General examination including measurements of height, weight, and blood pressure was done. Moreover, levels of plasma cholinesterase enzyme (PChE), glucose, as well as reproductive and thyroid hormones (TSH, T4, and testosterone) were determined. Results: There were no statistically significant differences between both groups regarding their age, educational level, smoking status, and body mass index. The mean duration of exposure was 20.60 11.06 years. Majority of farmers (76.7%) did not use any personal protective equipment (PPE) during pesticides handling. The mean systolic blood pressure among exposed farmers was greater (134.88 17.18 mm Hg) compared to control group (125 14.69 mm Hg) with statistically significant difference (p = 0.003). The mean diastolic blood pressure was higher (84.02 8.69 mm Hg) compared to control group (78.79 8.98 mm Hg) with statistically significant difference (p = 0.006). The pesticide exposed farmers had statistically significant lower level of PChE (3969.93 1841U/L) than control group (4879.29 1950.08 U/L). Additionally, TSH level was significantly higher in exposed farmers (median =1.39µIU/ml) compared to controls (median = 0.91 µIU/ml) (p=0.032). While, the exposed group had a lower T4 level (6.91 1.91 µg/dl) compared to the control group (7.79 2.10µg/dl), with the statistically significant difference between the two groups (p = 0.045). The exposed group had significantly lower level of testosterone hormone (median=3.37 ng/ml) compared to the control group (median= 6.22 ng/ml) (p=0.003). While, the exposed farmers had statistically insignificant higher level of fasting blood glucose (median =89 mg/dl) than the controls (median=88 mg/dl). Furthermore, farmers who did not use PPE had statistically significant lower level of T4 (6.57 1.81µg/dl) than farmers who used PPE during handling of pesticides (8.01 1.89 µg/dl). Conclusion: Chronic exposure to pesticides exerts disturbing action on reproductive function and thyroid function of the male farmers.

Keywords: chronic occupational pesticide exposure, Diabetes mellitus, male reproductive hormones, thyroid function

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Authors: Hamid Reza Khodaei, Behnaz Mahdavi, Alireza Banitaba

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Nitric oxide (NO) plays an important role in all sexual activities of animals. It is made in body from NO syntheses enzyme and L-arginin molecule. NO can make band with sulfur-iron complexes and due to production of steroid sexual hormones related to enzymes which have this complex, NO can change the activity of these enzymes. NO affects many cells including endothelial cells of veins, macrophages and mast cells. These cells are found in testis leydig cells and therefore are important source of NO in testis tissue. Minimizing damages to sperm at the time of sperm freezing and thawing is really important. The goal of this study was to determine the function of NO before freezing and its effects on quality and viability of sperms after thawing and incubation. 4 Holstein bulls were selected from the age of 4, and artificial insemination was done for 3 weeks (2 times a week). Treatments were 0, 10, 50 and 100 nm of sodium nitroprusside (SNP). Data analysis was performed by SAS98 program. Also, mean comparison was done using Duncan's multiple ranges test (P<0.05). Concentrations used were found to increase motility and viability of spermatozoa at 1, 2 and 3 hours after thawing significantly (P<0.05) but there was no significant difference at zero time. SNP levels reduced the amount of lipid peroxidation in sperm membrane, increased acrosome health and improved samples membranes especially in 50 and 100 nm treatments. According to results, adding SNP to semen diluents increases motility and viability of spermatozoa. Also, it reduces lipid peroxidation in sperm membrane and improves sperm function.

Keywords: sperm motility, nitric oxide, lipid peroxidation, spermatozoa

Procedia PDF Downloads 659

Authors: Mark-Adam Kellerman

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Proteins are capable of exploring vast mutational spaces. This makes it difficult for protein engineers to devise rational methods to improve stability and function via mutagenesis. Deciding which residues to mutate requires knowledge of the characteristics they elicit. We probed the characteristics of residues in granulocyte-colony stimulating factor (G-CSF) using a thermal melt (from 295K to 323K) to denature it in a 700 MHz Bruker spectrometer. These characteristics included dynamics, micro-environmental changes experienced/ induced during denaturing and structure-function relationships. 15N-1H HSQC experiments were performed at 2K increments along with this thermal melt. We observed that dynamic residues that also undergo a lot of change in their microenvironment were predominantly in unstructured regions. Moreover, we were able to identify four residues (G4, A6, T133 and Q134) that we class as high priority targets for mutagenesis, given that they all appear in both the top 10% of measures for environmental changes and dynamics (∑Δ and ∆PI). We were also able to probe these NMR observables and combine them with molecular dynamics (MD) to elucidate what appears to be an opening motion of G-CSFs binding site III. V48 appears to be pivotal to this opening motion, which also seemingly distorts the loop region between helices A and B. This observation is in agreement with previous findings that the conformation of this loop region becomes altered in an aggregation-prone state of G-CSF. Hence, we present here an approach to profile the characteristics of residues in order to highlight their potential as rational mutagenesis targets and their roles in important conformational changes. These findings present not only an opportunity to effectively make biobetters, but also open up the possibility to further understand epistasis and machine learn residue behaviours.

Keywords: protein engineering, rational mutagenesis, NMR, molecular dynamics

Procedia PDF Downloads 255

Authors: Pallab Datta, Jyotirmoy Chatterjee, Santanu Dhara

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Over the past few years, phosphorous containing polymers have received widespread attention for applications such as high performance optical fibers, flame retardant materials, drug delivery and tissue engineering. Being pentavalent, phosphorous can exist in different chemical environments in these polymers which increase their versatility. In human biochemistry, phosphorous based compounds exert their functions both in soluble and insoluble form occurring as inorganic or as organophosphorous compounds. Specifically in case of biomacromolecules, phosphates are critical for functions of DNA, ATP, phosphoproteins, phospholipids, phosphoglycans and several coenzymes. Inspired by the role of phosphorous in functional biomacromolecules, design and synthesis of biomimetic materials are thus carried out by several authors to study macromolecular function or as substitutes in clinical tissue regeneration conditions. In addition, many regulatory signals of the body are controlled by phoshphorylation of key proteins present either in form of growth factors or matrix-bound scaffold proteins. This inspires works on synthesis of phospho-peptidomimetic amino acids for understanding key signaling pathways and this is extended to obtain molecules with potentially useful biological properties. Apart from above applications, phosphate groups bound to polymer backbones have also been demonstrated to improve function of osteoblast cells and augment performance of bone grafts. Despite the advantages of phosphate grafting, however, there is limited understanding on effect of degree of phosphorylation on macromolecular physicochemical and/or biological properties. Such investigations are necessary to effectively translate knowledge of macromolecular biochemistry into relevant clinical products since they directly influence processability of these polymers into suitable scaffold structures and control subsequent biological response. Amongst various techniques for fabrication of biomimetic scaffolds, nanofibrous scaffolds fabricated by electrospinning technique offer some special advantages in resembling the attributes of natural extracellular matrix. Understanding changes in physico-chemical properties of polymers as function of phosphorylation is therefore going to be crucial in development of nanofiber scaffolds based on phosphorylated polymers. The aim of the present work is to investigate the effect of phosphorous grafting on the electrospinning behavior of polymers with aim to obtain biomaterials for bone regeneration applications. For this purpose, phosphorylated derivatives of two polymers of widely different electrospinning behaviors were selected as starting materials. Poly(vinyl alcohol) is a conveniently electrospinnable polymer at different conditions and concentrations. On the other hand, electrospinning of chitosan backbone based polymers have been viewed as a critical challenge. The phosphorylated derivatives of these polymers were synthesized, characterized and electrospinning behavior of various solutions containing these derivatives was compared with electrospinning of pure poly (vinyl alcohol). In PVA, phosphorylation adversely impacted electrospinnability while in NMPC, higher phosphate content widened concentration range for nanofiber formation. Culture of MG-63 cells on electrospun nanofibers, revealed that degree of phosphate modification of a polymer significantly improves cell adhesion or osteoblast function of cultured cells. It is concluded that improvement of cell response parameters of nanofiber scaffolds can be attained as a function of controlled degree of phosphate grafting in polymeric biomaterials with implications for bone tissue engineering applications.

Keywords: bone regeneration, chitosan, electrospinning, phosphorylation

Procedia PDF Downloads 222

Authors: Vaikunthan Rajaratnam

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Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

Procedia PDF Downloads 317

Authors: Abdul Hakim Khan

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The aim of the present paper is to study the Banach Space and Combinatorial Algebraic Structure of R. It is further aimed to study algebraic structure of set of all q-extension of classical formula and function for 0 < q < 1.

Keywords: integral functions, q-extensions, q numbers of metric space, algebraic structure of r and banach space

Procedia PDF Downloads 580

Authors: Lina Wu, Ye Li, Jia Liu

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We are interested in solving Liouville-type problems to explore constancy properties for maps or differential forms on Riemannian manifolds. Geometric structures on manifolds, the existence of constancy properties for maps or differential forms, and energy growth for maps or differential forms are intertwined. In this article, we concentrate on discovery of solutions to Liouville-type problems where manifolds are Euclidean spaces (i.e. flat Riemannian manifolds) and maps become real-valued functions. Liouville-type results of vanishing properties for functions are obtained. The original work in our research findings is to extend the q-energy for a function from finite in L^q space to infinite in non-L^q space by applying p-balanced technique where q = p = 2. Calculation skills such as Hölder's Inequality and Tests for Series have been used to evaluate limits and integrations for function energy. Calculation ideas and computational techniques for solving Liouville-type problems shown in this article, which are utilized in Euclidean spaces, can be universalized as a successful algorithm, which works for both maps and differential forms on Riemannian manifolds. This innovative algorithm has a far-reaching impact on research work of solving Liouville-type problems in the general settings involved with infinite energy. The p-balanced technique in this algorithm provides a clue to success on the road of q-energy extension from finite to infinite.

Keywords: differential forms, holder inequality, Liouville-type problems, p-balanced growth, p-harmonic maps, q-energy growth, tests for series

Procedia PDF Downloads 237

Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao

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An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.

Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.

Procedia PDF Downloads 151

Authors: Y. S. Zhou, C. R. Li, L. L. Tang, C. X. Gao, D. J. Wang, Y. Y. Guo

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Triangular trihedral corner reflector (CR) has been widely used as point target for synthetic aperture radar (SAR) calibration and image quality assessment. The additional “tip” of the triangular plate does not contribute to the reflector’s theoretical RCS and if it interacts with a perfectly reflecting ground plane, it will yield an increase of RCS at the radar bore-sight and decrease the accuracy of SAR calibration and image quality assessment. Regarding this problem, two types of CRs were manufactured. One was the hexagonal trihedral CR. It is a self-illuminating CR with relatively small plate edge length, while large edge length usually introduces unexpected edge diffraction error. The other was the triangular trihedral CR with extended bottom plate which considers the effect of ‘tip’ into the total RCS. In order to assess the performance of the two types of new CRs, flight campaign over the National Calibration and Validation Site for High Resolution Remote Sensors was carried out. Six hexagonal trihedral CRs and two bottom-extended trihedral CRs, as well as several traditional triangular trihedral CRs, were deployed. KOMPSAT-5 X-band SAR image was acquired for the performance analysis of the hexagonal trihedral CRs. C-band airborne SAR images were acquired for the performance analysis of the bottom-extended trihedral CRs. The analysis results showed that the impulse response function of both the hexagonal trihedral CRs and bottom-extended trihedral CRs were much closer to the ideal sinc-function than the traditional triangular trihedral CRs. The flight campaign results validated the advantages of new types of CRs and they might be useful in the future SAR calibration mission.

Keywords: synthetic aperture radar, calibration, corner reflector, KOMPSAT-5

Procedia PDF Downloads 276

Authors: Gerard Bray, Derek Mao, Arya Bahadori, Sachinka Ranasinghe

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The EAU currently recommends partial nephrectomy as the preferred management for localised cT1 renal tumours, irrespective of surgical approach. With the advent of robotic assisted partial nephrectomy, there is growing evidence that warm ischaemia time may be reduced compared to the traditional laparoscopic approach. There is still no clear differences between the two approaches with regards to other peri-operative and oncological outcomes. Current limitations in the field denote the lack of single surgeon series to compare the two approaches as other studies often include multiple operators of different experience levels. To the best of our knowledge, this study is the first single surgeon series comparing peri-operative outcomes of robotic assisted and laparoscopic PN. The current study aims to reduce intra-operator bias while maintaining an adequate sample size to assess the differences in outcomes between the two approaches. We retrospectively compared patient demographics, peri-operative outcomes, and renal function derangements of all partial nephrectomies undertaken by a single surgeon with experience in both laparoscopic and robotic surgery. Warm ischaemia time, length of stay, and acute renal function deterioration were all significantly reduced with robotic partial nephrectomy, compared to laparoscopic nephrectomy. This study highlights the benefits of robotic partial nephrectomy. Further prospective studies with larger sample sizes would be valuable additions to the current literature.

Keywords: partial nephrectomy, robotic assisted partial nephrectomy, warm ischaemia time, peri-operative outcomes

Procedia PDF Downloads 142

Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

Procedia PDF Downloads 101

Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

Procedia PDF Downloads 171

Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

Procedia PDF Downloads 462

Authors: Rigas Dimakopoulos, Marianna Papadopoulou, Roser Pons

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Background: Participation in family, recreational activities and self-care is an integral part of health. It is also the main outcome of rehabilitation services for children and adolescents with motor disabilities. There are currently no tools in Greek to assess participation in young children. Purpose: To culturally adapt and validate the Greek version of the Child Engagement in Daily Living (CEDL). Method: The CEDL was cross-culturally translated into Greek using forward-backward translation, review by the expert committee, pretest application and final review. Internal consistency was evaluated using the Cronbach alpha and test-retest reliability using the intra-class correlation coefficient (ICC). Parents of children aged 18 months to 5 years and with motor disabilities were recruited. Participants completed the CEDL and the children’s gross motor function was classified using the Gross Motor Function Classification System (GMFCS). Results: Eighty-three children were included, GMFCS I-V. Mean ± standard deviation of the CEDL domains “frequency of participation” “enjoyment of participation” and “self-care” were 58.4±14.0, 3.8±1.0 and 49.9±24, respectively. Internal consistency of all domains was high; Cronbach alpha for “frequency of participation” was 0.83, for “enjoyment of participation” was 0.76 and for “self-care” was 0.92. Test-retest reliability (ICC) was excellent for the “self-care” (0.95) and good for “frequency of participation” and “enjoyment of participation” domains (0.90 and 0.88, respectively). Conclusion: The Greek CEDL has good reliability. It can be used to evaluate participation in Greek young children with motor disabilities GMFCS levels I-V.

Keywords: participation, child, disabilities, child engagement in daily living

Procedia PDF Downloads 175

Authors: A. K. Borah, A. K. Singh

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In this paper we deal building blocks of the computer simulation of the multiphase flows. Whole simulation procedure can be viewed as two super procedures; The implementation of VOF method and the solution of Navier Stoke’s Equation. Moreover, a sequential code for a Navier Stoke’s solver has been studied.

Keywords: Bi-conjugate gradient stabilized (Bi-CGSTAB), ILUT function, krylov subspace, multifluid flows preconditioner, simple algorithm

Procedia PDF Downloads 528

Authors: S. M. Samkeyat Shohan

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This study is mainly focused on the determination and analysis of the photolysis rate of atmospheric, specifically tropospheric, ozone as function of cloud properties through-out the year 2007. The observational basis for ozone concentrations and cloud properties are the measurement data set of the Global Ozone Monitoring Experiment-2 (GOME-2) sensor on board the polar orbiting Metop-A satellite. Two different spectral ranges are used; ozone total column are calculated from the wavelength window 325 – 335 nm, while cloud properties, such as cloud top height (CTH) and cloud optical thick-ness (COT) are derived from the absorption band of molecular oxygen centered at 761 nm. Cloud fraction (CF) is derived from measurements in the ultraviolet, visible and near-infrared range of GOME-2. First, ozone concentrations above clouds are derived from ozone total columns, subtracting the contribution of stratospheric ozone and filtering those satellite measurements which have thin and low clouds. Then, the values of ozone photolysis derived from observations are compared with theoretical modeled results, in the latitudinal belt 5˚N-5˚S and 20˚N - 20˚S, as function of CF and COT. In general, good agreement is found between the data and the model, proving both the quality of the space-borne ozone and cloud properties as well as the modeling theory of ozone photolysis rate. The found discrepancies can, however, amount to approximately 15%. Latitudinal seasonal changes of photolysis rate of ozone are found to be negatively correlated to changes in upper-tropospheric ozone concentrations only in the autumn and summer months within the northern and southern tropical belts, respectively. This fact points to the entangled roles of temperature and nitrogen oxides in the ozone production, which are superimposed on its sole photolysis induced by thick and high clouds in the tropics.

Keywords: cloud properties, photolysis rate, stratospheric ozone, tropospheric ozone

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Authors: Rukiye Pinar Boluktas

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According to 2015 statistics, in Turkey, 46% of older people live alone in their homes, 55% have poor health perceptions, 18% face poverty, and 43% are unhappy. Prevalence of depression is between 14% and 20%. In 2013, rate of suicide was 6.5. However, the most of older people prefer to live in their community although they are lonely, they face poverty, and face limitations as a result of chronic diseases and disabilities. Community based care for older people is also encouraged by Ministry of Health as it is more cost-effective. Music therapy is a simple, effective, safe, and nonpharmacologic intervention that may be used to decrease depression and to improve cognition, and health related quality of life (HRQOL). In Turkish culture, music is typically described as ‘food for soul’. This study aimed to investigate the effect of Turkish classical music songs in 32 community dwelling older people. Participants were received interventions two or three times per week, 50-60 min per session, for 8 weeks at a day health center. Each intervention session started listening music for 15-20 min to get remember songs, then followed singing songs as a group. Participants were assessed at baseline (week 0), and two follow-up at month 1 and month 2. Compared to baseline, at two follow-up, we observed that cognition improved, depression decreased, and SF-36 scores, including 8 domains and two summary scores increased. We conclude that an intervention comprising listening and singing Turkish classical music improve cognition, depression and HRQOL in older people.

Keywords: cognitive function, depression, elderly, quality of life, Turkish classical music

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Marzieh Imani

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Antoni Gaudi and Santiago Calatrava have reputation for designing bio-inspired creative and technical buildings. Even though they have followed different independent approaches towards design, the source of bio-inspiration seems to be common. Taking a closer look at their projects reveals that Calatrava has been influenced by Gaudi in terms of interpreting nature and applying natural principles into the design process. This research firstly discusses the dialogue between Biomimicry and architecture. This review also explores human/nature discourse during the history by focusing on how nature revealed itself to the fine arts. This is explained by introducing naturalism and romantic style in architecture as the outcome of designers’ inclination towards nature. Reviewing the literature, theoretical background and practical illustration of nature have been included. The most dominant practical aspects of imitating nature are form and function. Nature has been reflected in architectural science resulted in shaping different architectural styles such as organic, green, sustainable, bionic, and biomorphic. By defining a set of common aspects of Gaudi and Calatrava‘s design approach and by considering biomimetic design categories (organism, ecosystem, and behaviour as the main division and form, function, process, material, and construction as subdivisions), Gaudi’s and Calatrava’s project have been analysed. This analysis explores if their design approaches are equivalent or different. Based on this analysis, Gaudi’s architecture can be recognised as biomorphic while Calatrava’s projects are literally biomimetic. Referring to these architects, this review suggests a new set of principles by which a bio-inspired project can be determined either biomorphic or biomimetic.

Keywords: biomimicry, Calatrava, Gaudi, nature

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Kassim A. Jassim

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In the present paper, we introduce and discuss a new class Kp(λ,α) of meromorphic multivalent functions in the punctured unit disk U*={z∈¢:0<|z|<1} defined by Ruscheweyh derivative. We obtain some sufficient conditions for the functions belonging to the class Kp(λ,α).

Keywords: meromorphic multivalent function, Ruscheweyh derivative, hadamard product

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Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

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The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

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Authors: Siamak Samani, Nadereh Sohrabi

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Psychological nano-therapy is a new method based on systems theory. According to the theory, systems with severe dysfunctions are resistant to changes. Psychological nano-therapy helps the therapists to break this ice. Two key concepts in psychological nano-therapy are nano-functions and nano-behaviors. The most important step in psychological nano-therapy in family therapy is selecting the most effective nano-function and nano-behavior. The aim of this study was to check the effectiveness of psychological nano-therapy for family therapy. One group pre-test-post-test design (quasi-experimental Design) was applied for research. The sample consisted of ten families with severe marital conflict. The important character of these families was resistance for participating in family therapy. In this study, sending respectful (nano-function) text massages (nano-behavior) with cell phone were applied as a treatment. Cohesion/respect sub scale from self-report family processes scale and family readiness for therapy scale were used to assess all family members in pre-test and post-test. In this study, one of family members was asked to send a respectful text massage to other family members every day for a week. The content of the text massages were selected and checked by therapist. To compare the scores of families in pre-test and post-test paired sample t-test was used. The results of the test showed significant differences in both cohesion/respect score and family readiness for therapy between per-test and post-test. The results revealed that these families have found a better atmosphere for participation in a complete family therapy program. Indeed, this study showed that psychological nano-therapy is an effective method to make family readiness for therapy.

Keywords: family therapy, family conflicts, nano-therapy, family readiness

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

Procedia PDF Downloads 226