Search results for: variable precision rough sets theory

Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

Abstract:

In the description of the origin of life, there are still some open gaps, e.g., the formation of macromolecules cannot be fully explained so far. The Kauffman model proposes the existence of autocatalytic sets of macromolecules which mutually catalyze reactions leading to each other’s formation. Usually, this model is simulated in one well-stirred pot only, with a continuous inflow of small building blocks, from which larger molecules are created by a set of catalyzed ligation and cleavage reactions. This approach represents the picture of the primordial soup. However, the conditions on the early Earth must have differed geographically, leading to spatially different outcomes whether a specific reaction could be performed or not. Guided by this picture, the Kauffman model is simulated in a large number of containers in parallel, with neighboring containers being connected by diffusion. In each container, only a subset of the overall reaction set can be performed. Under specific conditions, this approach leads to a larger probability for the existence of an autocatalytic metabolism than in the original Kauffman model.

Keywords: agglomeration, autocatalytic set, differential equation, Kauffman model

Procedia PDF Downloads 53

Authors: A. Mansouri, F. Krim

Abstract:

This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

Procedia PDF Downloads 373

Authors: Lian Yang

Abstract:

Object-oriented programming (OOP) is the dominant programming paradigm in today’s software industry and it has literally enabled average software developers to develop millions of commercial strength software applications in the era of INTERNET revolution over the past three decades. On the other hand, the lack of strict mathematical model and domain constraint features at the language level has long perplexed the computer science academia and OOP engineering community. This situation resulted in inconsistent system qualities and hard-to-understand designs in some OOP projects. The difficulties with regards to fix the current situation are also well known. Although the power of OOP lies in its unbridled flexibility and enormously rich data modeling capability, we argue that the ambiguity and the implicit facade surrounding the conceptual model of a class and an object should be eliminated as much as possible. We listed the five major usage of class and propose to separate them by proposing new language constructs. By using well-established theories of set and FSM, we propose to apply certain simple, generic, and yet effective constraints at OOP language level in an attempt to find a possible solution to the above-mentioned issues regarding OOP. The goal is to make OOP more theoretically sound as well as to aid programmers uncover warning signs of irregularities and domain-specific issues in applications early on the development stage and catch semantic mistakes at runtime, improving correctness verifiability of software programs. On the other hand, the aim of this paper is more practical than theoretical.

Keywords: new language constructs, set theory, FSM theory, user defined value type, function groups, membership qualification attribute (MQA), check-constraint (CC)

Procedia PDF Downloads 235

Authors: Mirza Adil Ahmad Mughal

Abstract:

Transcendental analytics, in the critique of pure reason, combines space and time as conditions of the possibility of the phenomenon from the transcendental aesthetic with the pure magnitude-intuition notion. The property of continuity as a qualitative result of the additive magnitude brings the possibility of connecting with experience, even though only as a potential because of the a priori necessity from assumption, as syntheticity of the a priori task of a scientific method of philosophy given by Kant, which precludes the application of categories to something not empirically reducible to the content of such a category's corresponding and possible object. This continuity as the qualitative result of a priori constructed notion of magnitude lies as a fundamental assumption and property of, what in Microeconomic theory is called as, 'choice rules' which combine the potentially-empirical and practical budget-price pairs with preference relations. This latter result is the purest qualitative side of the choice rules', otherwise autonomously, quantitative nature. The theoretical, barring the empirical, nature of this qualitative result is a synthetic a priori truth, which, if at all, it should be, if the axiomatic structure of the economic theory is held to be correct. It has a potentially verifiable content as its possible object in the form of quantitative price-budget pairs. Yet, the object that serves the respective Kantian category is qualitative itself, which is utility. This article explores the validity of Kantian qualifications for this application of 'categories' to the economic structure of society.

Keywords: categories of understanding, continuity, convexity, psyche, revealed preferences, synthetic a priori

Procedia PDF Downloads 94

Authors: Qi Wu, Dian-Yong Chen, Feng-Kun Guo, Gang Li

Abstract:

In the past decade, a growing number of new hadron states have been observed, which are dubbed as XYZ states in the heavy quarkonium mass regions. In this work, we present our study on the production of some new hadron states. In particular, we investigate the processes Υ(5S,6S)→ Zb (10610)/Zb (10650)π, Bc→ Zc (3900)/Zc (4020)π and Λb→ Pc (4312)/Pc (4440)/Pc (4457)K. (1) For the production of Zb (10610)/Zb (10650) from Υ(5S,6S) decay, two types of bottom-meson loops were discussed within a nonrelativistic effective field theory. We found that the loop contributions with all intermediate states being the S-wave ground state bottom mesons are negligible, while the loops with one bottom meson being the broad B₀* or B₁' resonance could provide the dominant contributions to the Υ(5S)→ Zb⁽'⁾ π. (2) For the production of Zc (3900)/Zc (4020) from Bc decay, the branching ratios of Bc⁺→ Z (3900)⁺ π⁰ and Bc⁺→ Zc (4020)⁺ π⁰ are estimated to be of order of 10⁽⁻⁴⁾ and 10⁽⁻⁷⁾ in an effective Lagrangian approach. The large production rate of Zc (3900) could provide an important source of the production of Zc (3900) from the semi-exclusive decay of b-flavored hadrons reported by D0 Collaboration, which can be tested by the exclusive measurements in LHCb. (3) For the production of Pc (4312), Pc (4440) and Pc (4457) from Λb decay, the ratio of the branching fraction of Λb→ Pc K was predicted in a molecular scenario by using an effective Lagrangian approach, which is weakly dependent on our model parameter. We also find the ratios of the productions of the branching fractions of Λb→ Pc K and Pc→ J/ψ p can be well interpreted in the molecular scenario. Moreover, the estimated branching fractions of Λb→ Pc K are of order 10⁽⁻⁶⁾, which could be tested by further measurements in LHCb Collaboration.

Keywords: effective Lagrangian approach, hadron loops, molecular states, new hadron states

Procedia PDF Downloads 128

Authors: D. M. Bassuney, W. A. Ibrahim, Medhat A. E. Moustafa

Abstract:

As awareness of the variable nature of food industrial wastewater and its environmental impact grows, a more stable treatment reactor is needed to treat such wastewater. In this paper, a performance of 5-compartment lab-scale Anaerobic Baffled Reactor (ABR) treating high strength wastewater with high pH variation was studied under three organic loading rates (OLRs). The reactor showed high COD removal efficiencies: 92.67, 97.44, and 98.19% corresponding to OLRs of 2.0, 3.0, and 4.8 KgCOD/m3 d, respectively. The first compartment showed a good buffering capacity and a distinct phase separation occurred in the ABR.

Keywords: anaerobic baffled reactor, food industrial wastewater, high strength wastewater, organic loading, pH

Procedia PDF Downloads 395

Authors: Catharina Lindberg, Cecilia Fagerstrom, Ania Willman

Abstract:

Patients in high-tech care environments are usually dependent on both formal/informal caregivers and technology, highlighting their vulnerability and challenging their autonomy. Autonomy presumes that a person has education, experience, self-discipline and decision-making capacity. Reference to autonomy in relation to patients in high-tech care environments could, therefore, be considered paradoxical, as in most cases these persons have impaired physical and/or metacognitive capacity. Therefore, to understand the prerequisites for patients to experience autonomy in high-tech care environments and to support them, there is a need to enhance knowledge and understanding of the concept of patient autonomy in this care context. The development of concepts and theories in a practice discipline such as nursing helps to improve both nursing care and nursing education. Theoretical development is important when clarifying a discipline, hence, a theoretical framework could be of use to nurses in high-tech care environments to support and defend the patient’s autonomy. A meta-synthesis was performed with the intention to be interpretative and not aggregative in nature. An amalgamation was made of the results from three previous studies, carried out by members of the same research group, focusing on the phenomenon of patient autonomy from a patient perspective within a caring context. Three basic approaches to theory development: derivation, synthesis, and analysis provided an operational structure that permitted the researchers to move back and forth between these approaches during their work in developing a theoretical framework. The results from the synthesis delineated that patient autonomy in a high-tech care context is: To be in control though trust, co-determination, and transition in everyday life. The theoretical framework contains several components creating the prerequisites for patient autonomy. Assumptions and propositional statements that guide theory development was also outlined, as were guiding principles for use in day-to-day nursing care. Four strategies used by patients to remain or obtain patient autonomy in high-tech care environments were revealed: the strategy of control, the strategy of partnership, the strategy of trust, and the strategy of transition. This study suggests an extended knowledge base founded on theoretical reasoning about patient autonomy, providing an understanding of the strategies used by patients to achieve autonomy in the role of patient, in high-tech care environments. When possessing knowledge about the patient perspective of autonomy, the nurse/carer can avoid adopting a paternalistic or maternalistic approach. Instead, the patient can be considered to be a partner in care, allowing care to be provided that supports him/her in remaining/becoming an autonomous person in the role of patient.

Keywords: autonomy, caring, concept development, high-tech care, theory development

Procedia PDF Downloads 201

Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

Abstract:

Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

Procedia PDF Downloads 256

Authors: Dmitry Fedoseyev

Abstract:

The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

Procedia PDF Downloads 51

Authors: S. K. Ashiquer Rahman

Abstract:

Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

Procedia PDF Downloads 51

Authors: Claudius Peter Van Wyk

Abstract:

Given the increasingly manifest phenomena, as described in complexity theory, of volatility, uncertainty, complexity and ambiguity (VUCA), Taleb's notion of 'antifragility, has a significant contribution to make to positive psychology applied to wellbeing. Antifragility is argued to be fundamentally different from the concepts of resiliency; as the ability to recover from failure, and robustness; as the ability to resist failure. Rather it describes the capacity to reorganise in the face of stress in such a way as to cope more effectively with systemic challenges. The concept, which has been applied in disciplines ranging from physics, molecular biology, planning, engineering, and computer science, can now be considered for its application in individual human and social wellbeing. There are strong correlations to Antonovsky's model of 'salutogenesis' in which an attitude and competencies are developed of transforming burdening factors into greater resourcefulness. We demonstrate, from the perspective of neuroscience, how technology measuring nervous system coherence can be coupled to acquired psychodynamic approaches to not only identify contextual stressors, utilise biofeedback instruments for facilitating greater coherence, but apply these insights to specific life stressors that compromise well-being. Employing an on-going case study with BMW South Africa, the neurological mapping is demonstrated together with 'reframing' and emotional anchoring techniques from neurolinguistic programming. The argument is contextualised in the discipline of psychoneuroimmunology which describes the stress pathways from the CNS and endocrine systems and their impact on immune function and the capacity to restore homeostasis.

Keywords: antifragility, complexity, neuroscience, psychoneuroimmunology, salutogenesis, volatility

Procedia PDF Downloads 371

Authors: Nouf M. Al-Ourfi, A. S. Bashammakh, M. S. El-Shahawi

Abstract:

The redox behavior of dianabol steroid (DS) on Nafion Multiwalled Carbon nano -tubes (MWCNT) composite film modified glassy carbon electrode (GCE) in various buffer solutions was studied using cyclic voltammetry (CV) and differential pulse- adsorptive cathodic stripping voltammetry (DP-CSV) and successfully compared with the results at non modified bare GCE. The Nafion-MWCNT composite film modified GCE exhibited the best electrochemical response among the two electrodes for the electro reduction of DS that was inferred from the EIS, CV and DP-CSV. The modified sensor showed a sensitive, stable and linear response in the concentration range of 5 – 100 nM with a detection limit of 0.08 nM. The selectivity of the proposed sensor was assessed in the presence of high concentration of major interfering species. The analytical application of the sensor for the quantification of DS in pharmaceutical formulations and biological fluids (urine) was determined and the results demonstrated acceptable recovery and RSD of 5%. Statistical treatment of the results of the proposed method revealed no significant differences in the accuracy and precision. The relative standard deviations for five measurements of 50 and 300 ng mL−1 of DS were 3.9 % and 1.0 %, respectively.

Keywords: dianabol steroid, determination, modified GCE, urine

Procedia PDF Downloads 279

Authors: Mouli Banga, Chaya Ravindra

Abstract:

Wound classification is a crucial step in wound diagnosis. An effective classifier can aid wound specialists in identifying wound types with reduced financial and time investments, facilitating the determination of optimal treatment procedures. This study presents a deep neural network-based classifier that leverages wound images and their corresponding locations to categorize wounds into various classes, such as diabetic, pressure, surgical, and venous ulcers. By incorporating a developed body map, the process of tagging wound locations is significantly enhanced, providing healthcare specialists with a more efficient tool for wound analysis. We conducted a comparative analysis between two prominent convolutional neural network models, ResNet50 and MobileNetV2, utilizing a dataset of 730 images. Our findings reveal that the RestNet50 outperforms MovileNetV2, achieving an accuracy of approximately 90%, compared to MobileNetV2’s 83%. This disparity highlights the superior capability of ResNet50 in the context of this dataset. The results underscore the potential of integrating deep learning with spatial data to improve the precision and efficiency of wound diagnosis, ultimately contributing to better patient outcomes and reducing healthcare costs.

Keywords: wound classification, MobileNetV2, ResNet50, multimodel

Procedia PDF Downloads 18

Authors: Hyun-Woo Cho

Abstract:

The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

Procedia PDF Downloads 550

Authors: Jan Doutreloigne

Abstract:

This paper describes two methods for the reduction of the peak input current during the boosting of Dickson charge pumps. Both methods are implemented in the fully integrated Dickson charge pumps of a high-voltage display driver chip for smart-card applications. Experimental results reveal good correspondence with Spice simulations and show a reduction of the peak input current by a factor of 6 during boosting

Keywords: bi-stable display driver, Dickson charge pump, high-voltage generator, peak current reduction, sub-pump boosting, variable frequency boosting

Procedia PDF Downloads 452

Authors: Noelene Rose

Abstract:

The DSM has been plagued with conceptual issues since its inception, not least discriminant validity and comorbidity issues. An attempt to remain a-theoretical in the divide between the psycho-dynamicists and the behaviourists contributed to much of this, in particular relating to the Personality Disorders. With the DSM-5, although the criterion have remained unchanged, major conceptual and structural directions have been flagged and proposed in section III. The biggest changes concern the Personality Disorders. While Narcissistic Personality Disorder (NPD) was initially tagged for removal, instead the addition of section III proposes a move away from a categorical approach to a more dimensional approach, with a measure of Global Function of Personality. This global measure is an assessment of impairment of self-other relations; a measure of trait narcissism. In the same way mainstream psychology has struggled in its diagnosis of narcissism, so too in its treatment. Kohut’s self psychology represents the most significant inroad in theory and treatment for the narcissistic disorders. Kohut had moved away from a categorical system, towards disorders of the self. According to this theory, disorders of the self are the result of childhood trauma (impaired attunement) resulting in a developmental arrest. Self-psychological, Psychodynamic treatment of narcissism, however, is expensive, in time and money and outside the awareness or access of most people. There is more than a suggestion that narcissism is on the increase, created in trauma and worsened by a fearful world climate. A dimensional model of narcissism, from mild to severe, requires cut off points for diagnosis. But where do we draw the line? Mainstream psychology is inclined to set it high when there is some degree of impairment in functioning in daily life. Transpersonal Psychology is inclined to set it low, with the concept that we all have some degree of narcissism and that it is the point and the path of our life journey to transcend our focus on our selves. Mainstream psychology stops its focus on trait narcissism with a healthy level of self esteem, but it is at this point that Transpersonal Psychology can complement the discussion. From a Transpersonal point of view, failure to begin the process of self-transcendence will also create emotional symptoms of meaning or purpose, often later in our lives, and is also conceived of as a developmental arrest. The maps for this transcendence are hidden in plain sight; in the chakras of kundalini yoga, in the sacraments of the Catholic Church, in the Kabbalah tree of life of Judaism, in Maslow’s hierarchy of needs, to name a few. This paper outlines some proposed research exploring the use of daily practices that can be incorporated into the therapy room; practices that utilise meditation, visualisation and imagination: that are informed by spiritual technology and guided by the psychodynamic theory of Self Psychology.

Keywords: narcissism, self-psychology, self-practice, self-transcendence

Procedia PDF Downloads 257

Authors: Agnes Utari Widyaningdyah

Abstract:

This study investigates the relationship between strategy, intellectual capital (IC) disclosure, and the firm’s performance by considering business competition as a moderating variable. The secondary sectors manufacturing firms in the Jakarta Stock Industrial Classification as sample because this group represents a knowledge-intensive firm according to the OECD (Organization for Economic Cooperation and Development) criteria. Using path analysis, this study reveals that there is a significant influence of strategy toward IC disclosure. Firms with differentiation strategy tend to withhold its strategic information included IC because of afraid in losing their competitive advantage. The results also indicate that firms are more likely to withhold information about IC if they perceive that current or potential competition is strong. However, firms should consider that IC disclosure is a positive signal to the investor.

Keywords: strategy, IC disclosure, market performance, business competition

Procedia PDF Downloads 288

Authors: Siddhant Rao

Abstract:

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: breast cancer, mitotic count, machine learning, convolutional neural networks

Procedia PDF Downloads 216

Authors: D. K. Rao, M. G. M. Khan, K. G. Reddy

Abstract:

The focus of this paper is to develop a technique of solving a combined problem of determining Optimum Strata Boundaries (OSB) and Optimum Sample Size (OSS) of each stratum, when the population understudy is skewed and the study variable has a Pareto frequency distribution. The problem of determining the OSB is formulated as a Mathematical Programming Problem (MPP) which is then solved by dynamic programming technique. A numerical example is presented to illustrate the computational details of the proposed method. The proposed technique is useful to obtain OSB and OSS for a Pareto type skewed population, which minimizes the variance of the estimate of population mean.

Keywords: stratified sampling, optimum strata boundaries, optimum sample size, pareto distribution, mathematical programming problem, dynamic programming technique

Procedia PDF Downloads 447

Authors: Akhtar Rasool, Tasneem Zahra Rizvi

Abstract:

In this study, a series of the cadmium sulphide quantum dots/polyaniline nanocomposites with varying compositions were prepared by in-situ polymerization technique and were characterized using X-ray diffraction and Fourier transform infrared spectroscopy. The surface morphology was studied by scanning electron microscopy. UV-Visible spectroscopy was used to find out the energy band gap of the nanoparticles and the nanocomposites. Temperature dependence of DC electrical conductivity and temperature and frequency dependence of AC conductivity were investigated to study the charge transport mechanism in the nanocomposites. DC conductivity was found to be a typical for a semiconducting behavior following Mott’s 1D variable range hoping model. The frequency dependent AC conductivity followed the universal power law.

Keywords: conducting polymers, nanocomposites, polyaniline composites, quantum dots

Procedia PDF Downloads 249

Authors: Laxman H. Surwase, Lalit V. Sonawane, Bhagwat N. Poul

Abstract:

A simple stability indicating high performance liquid chromatographic method has been developed for the simultaneous determination of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical dosage form using reverse phase Zorbax Eclipse Plus C8 column (250mm×4.6mm), with mobile phase phosphate buffer (0.05M KH2PO4): acetonitrile (55:45v/v) pH 3.5 adjusted with ortho-phosphoric acid, the flow rate was 1.0 mL/min and the detection was carried at 212 nm. The retention times of Levosalbutamol Sulphate and Ipratropium Bromide were 2.2007 and 2.6611 min respectively. The correlation coefficient of Levosalbutamol Sulphate and Ipratropium Bromide was found to be 0.997 and 0.998.Calibration plots were linear over the concentration ranges 10-100µg/mL for both Levosalbutamol Sulphate and Ipratropium Bromide. The LOD and LOQ of Levosalbutamol Sulphate were 2.520µg/mL and 7.638µg/mL while for Ipratropium Bromide was 1.201µg/mL and 3.640 µg/mL. The accuracy of the proposed method was determined by recovery studies and found to be 100.15% for Levosalbutamol Sulphate and 100.19% for Ipratropium Bromide respectively. The method was validated for accuracy, linearity, sensitivity, precision, robustness, system suitability. The proposed method could be utilized for routine analysis of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical capsule dosage form.

Keywords: levosalbutamol sulphate, ipratropium bromide, RP-HPLC, phosphate buffer, acetonitrile

Procedia PDF Downloads 342

Authors: Maria Lina Garrido

Abstract:

This paper aims to reflect upon instruction in English classes with the specific purpose of reading comprehension development, having as its paradigm the considerations presented by William Grabe, in his book Reading in a Second Language: Moving from theory to practice. His concerns regarding the connection between research findings and instructional practices have stimulated the present author to re-evaluate both her long practice as an English reading teacher and as the author of two reading textbooks for graduate students. Elements of the reading process such as linguistic issues, prior knowledge, reading strategies, critical evaluation, and motivation are the main foci of this analysis as far as the activities developed in the classroom are concerned. The experience with university candidates on postgraduate courses with different levels of English knowledge in Bahia, Brazil, has definitely demanded certain adjustments to this author`s classroom setting. Word recognition based on cognates, for example, has been emphasized given the fact that academic texts use many Latin words which have the same roots as the Brazilian Portuguese lexicon. Concerning syntactic parsing, the tenses/verbal aspects, modality and linking words are included in the curriculum, but not with the same depth as the general English curricula. Reading strategies, another essential predictor for developing reading skills, have been largely stimulated in L2 classes in order to compensate for a lack of the appropriate knowledge of the foreign language. This paper presents results that demonstrate that this author`s teaching practice is compatible with the implications and instruction concerning the reading process outlined by Grabe, however, it admits that each class demands specific instructions to meet the needs of that particular group.

Keywords: classroom practice, instructional activities, reading comprehension, reading skills

Procedia PDF Downloads 455

Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

Abstract:

Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

Procedia PDF Downloads 69

Authors: Christoph Linse, Thomas Martinetz

Abstract:

Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

Procedia PDF Downloads 84

Authors: Peter Thissen

Abstract:

In this work, we report about the influence of the chemical potential of water on the carbonation reaction of wollastonite (CaSiO3) as model surface of cement and concrete. Total energy calculations based on density functional theory (DFT) combined with kinetic barrier predictions based on nudge elastic band (NEB) method show that the exposure of the water-free wollastonite surface to CO2 results in a barrier-less carbonation. CO2 reacts with the surface oxygen and forms carbonate (CO32-) complexes together with a major reconstruction of the surface. The reaction comes to a standstill after one carbonate monolayer has been formed. In case one water monolayer is covering the wollastonite surface, the carbonation is no more barrier-less, yet ending in a localized monolayer. Covered with multilayers of water, the thermodynamic ground state of the wollastonite completely changes due to a metal-proton exchange reaction (MPER, also called early stage hydration) and Ca2+ ions are partially removed from solid phase into the H2O/wollastonite interface. Mobile Ca2+ react again with CO2 and form carbonate complexes, ending in a delocalized layer. By means of high resolution time-of-flight secondary-ion mass-spectroscopy images (ToF-SIMS), we confirm that hydration can lead to a partially delocalization of Ca2+ ions on wollastonite surfaces. Finally, we evaluate the impact of our model surface results by means of Low Energy Ion Scattering (LEIS) spectroscopy combined with careful discussion about the competing reactions of carbonation vs. hydration.

Keywords: Calcium-silicate, carbonation, hydration, metal-proton exchange reaction

Procedia PDF Downloads 359

Authors: Fatima Zehra Allahverdi, Nukhet Bayer

Abstract:

Objective: Three questions were formulated to examine stressful working units (intensive care units, emergency unit nurses) utilizing the self-perception theory and social support theory. This study provides a distinctive input by inspecting the combination of variables regarding stressful working environments. Method: The descriptive research was conducted with the participation of 400 nurses working at Ankara City Hospital. The study used Multivariate Analysis of Variance (MANOVA), regression analysis, and a mediation model. Hypothesis one used MANOVA followed by a Scheffe post hoc test. Hypothesis two utilized regression analysis using a hierarchical linear regression model. Hypothesis three used a mediation model. Result: The study utilized mediation analyses. Findings supported the hypotheses that intensive care units have significantly high scores in virtual communication and virtual tolerance. The number of years on the job, virtual communication, virtual tolerance, and phubbing significantly predicted 51% of the variance of perception of addiction. Interestingly, the number of years on the job, while significant, was negatively related to perception of addiction. Conclusion: The reasoning behind these findings and the lack of significance in the emergency unit is discussed. Around 7% of the variance of phubbing was accounted for through working in intensive care units. The model accounted for 26.80 % of the differences in the perception of addiction.

Keywords: phubbing, social media, working units, years on the job, stress

Procedia PDF Downloads 47

Authors: Navab Karimi, Tohid Alizadeh

Abstract:

An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

Procedia PDF Downloads 68

Authors: Feng Xu, Zhaozhi Liu, Junhua Xu, Xiaolong Tang, Dunwen Zuo

Abstract:

Chemical vapor deposition (CVD) diamond coated cutting tool has excellent cutting performance, it is the most ideal tool for the processing of nonferrous metals and alloys, composites, nonmetallic materials and other difficult-to-machine materials efficiently and accurately. Depositing CVD diamond coating on the cemented carbide with high cobalt content can improve its toughness and strength, therefore, it is very important to research on the preparation technology and cutting properties of CVD diamond coated cemented carbide cutting tool with high cobalt content. The preparation technology of boron-doped diamond (BDD) coating has been studied and the coated drills were prepared. BDD coating were deposited on the drills by using the optimized parameters and the SEM results show that there are no cracks or collapses in the coating. Cutting tests with the prepared drills against the silumin and aluminum base printed circuit board (PCB) have been studied. The results show that the wear amount of the coated drill is small and the machined surface has a better precision. The coating does not come off during the test, which shows good adhesion and cutting performance of the drill.

Keywords: cemented carbide with high cobalt content, CVD boron-doped diamond, cutting test, drill

Procedia PDF Downloads 432

Authors: Elham Delzendeh, Song Wu, Mustafa Al-Adhami, Rima Alaaeddine

Abstract:

Over the last 15 years, prediction of energy consumption has become a common practice and necessity at different stages of the building’s lifecycle, particularly, at the design and post-occupancy stages for planning and maintenance purposes. This is due to the ever-growing response of governments to address sustainability and reduction of CO₂ emission in the building sector. However, there is a level of uncertainty in the estimation of energy consumption in buildings. The accuracy of energy consumption predictions is directly related to the precision of the initial inputs used in the energy assessment process. In this study, multiple cases of large non-residential buildings at design, construction, and post-occupancy stages are investigated. The energy consumption process and inputs, and the actual and predicted energy consumption of the cases are analysed. The findings of this study have pointed out and evidenced various parameters that cause uncertainty in the prediction of energy consumption in buildings such as modelling, location data, and occupant behaviour. In addition, unavailability and insufficiency of energy-consumption-related inputs at different stages of the building’s lifecycle are classified and categorized. Understanding the roots of uncertainty in building energy analysis will help energy modellers and energy simulation software developers reach more accurate energy consumption predictions in buildings.

Keywords: building lifecycle, efficiency, energy analysis, energy performance, uncertainty

Procedia PDF Downloads 131

Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

Procedia PDF Downloads 371