Search results for: classical methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15611

Search results for: classical methods

13421 Joint Training Offer Selection and Course Timetabling Problems: Models and Algorithms

Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

Abstract:

In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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13420 Tyrosine Rich Fraction as an Immunomodulatory Agent from Ficus Religiosa Bark

Authors: S. A. Nirmal, G. S. Asane, S. C. Pal, S. C. Mandal

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Objective: Ficus religiosa Linn (Moraceae) is being used in traditional medicine to improve immunity hence present work was undertaken to validate this use scientifically. Material and Methods: Dried, powdered bark of F. religiosa was extracted successively using petroleum ether and 70% ethanol in soxhlet extractor. The extracts obtained were screened for immunomodulatory activity by delayed type hypersensitivity (DTH), neutrophil adhesion test and cyclophosphamide-induced neutropenia in Swiss albino mice at the dose of 50 and 100 mg/kg, i.p. 70% ethanol extract showed significant immunostimulant activity hence subjected to column chromatography to produce tyrosine rich fraction (TRF). TRF obtained was screened for immunomodulatory activity by above methods at the dose of 10 mg/kg, i.p. Results: TRF showed potentiation of DTH response in terms of significant increase in the mean difference in foot-pad thickness and it significantly increased neutrophil adhesion to nylon fibers by 48.20%. Percentage reduction in total leukocyte count and neutrophil by TRF was found to be 43.85% and 18.72%, respectively. Conclusion: Immunostimulant activity of TRF was more pronounced and thus it has great potential as a source for natural health products.

Keywords: Ficus religiosa, immunomodulatory, cyclophosphamide, neutropenia

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13419 An Accurate Computation of 2D Zernike Moments via Fast Fourier Transform

Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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13418 The Advantages of Using DNA-Barcoding for Determining the Fraud in Seafood

Authors: Elif Tugce Aksun Tumerkan

Abstract:

Although seafood is an important part of human diet and categorized highly traded food industry internationally, it is remain overlooked generally in the global food security aspect. Food product authentication is the main interest in the aim of both avoids commercial fraud and to consider the risks that might be harmful to human health safety. In recent years, with increasing consumer demand for regarding food content and it's transparency, there are some instrumental analyses emerging for determining food fraud depend on some analytical methodologies such as proteomic and metabolomics. While, fish and seafood consumed as fresh previously, within advanced technology, processed or packaged seafood consumption have increased. After processing or packaging seafood, morphological identification is impossible when some of the external features have been removed. The main fish and seafood quality-related issues are the authentications of seafood contents such as mislabelling products which may be contaminated and replacement partly or completely, by lower quality or cheaper ones. For all mentioned reasons, truthful consistent and easily applicable analytical methods are needed for assurance the correct labelling and verifying of seafood products. DNA-barcoding methods become popular robust that used in taxonomic research for endangered or cryptic species in recent years; they are used for determining food traceability also. In this review, when comparing the other proteomic and metabolic analysis, DNA-based methods are allowing a chance to identification all type of food even as raw, spiced and processed products. This privilege caused by DNA is a comparatively stable molecule than protein and other molecules. Furthermore showing variations in sequence based on different species and founding in all organisms, make DNA-based analysis more preferable. This review was performed to clarify the main advantages of using DNA-barcoding for determining seafood fraud among other techniques.

Keywords: DNA-barcoding, genetic analysis, food fraud, mislabelling, packaged seafood

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13417 Political Economy of Electronic News Media in Pakistan

Authors: Asad Ullah Khalid

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This paper encompasses the application of the concept of political economy of mass media in Pakistan. The media has developed at a massive pace and now is considered as one of the vital parts in having better administration furthermore helps in conveying the issues identified with the government to the public. Albeit Pakistani media has gained much independence after 2003 but there are many social, political and economy factors which influence the content of the media. The study employs triangulation of quantitative and qualitative methods. In terms of methods, content analysis and interview method both are used. The content of Pakistani media is analyzed quantitatively and qualitatively. Moreover, interviews with various journalists are conducted, and their findings are disclosed in this paper. Pakistan's communication landscape is neither well documented nor well understood, leaving its public off guard with regards to reviewing the role and impact of news inflow, correspondence and media in political, economic and social life. It has been found out that on particular issues some media channels have strong affiliations with certain political parties, moreover reporting and coverage have also been affected by the factors like terrorism, state policies(written and verbal), advertising/economic and demographic factors like the composition of the population.

Keywords: political economy, news media, Pakistan, electronic news media, journalism, mass media

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13416 Evaluation of Diagnostic Values of Culture, Rapid Urease Test, and Histopathology in the Diagnosis of Helicobacter pylori Infection and in vitro Effects of Various Antimicrobials against Helicobacter pylori

Authors: Recep Kesli, Huseyin Bilgin, Yasar Unlu, Gokhan Gungor

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Aim: The aim of this study, was to investigate the presence of Helicobacter pylori (H. pylori) infection by culture, histology, and RUT (Rapid Urease Test) in gastric antrum biopsy samples taken from patients presented with dyspeptic complaints and to determine resistance rates of amoxicillin, clarithromycin, levofloxacin and metronidazole against the H. pylori strains by E-test. Material and Methods: A total of 278 patients who admitted to Konya Education and Research Hospital Department of Gastroenterology with dyspeptic complaints, between January 2011-July 2013, were included in the study. Microbiological and histopathological examinations of biopsy specimens taken from antrum and corpus regions were performed. The presence of H. pylori in biopsy samples was investigated by culture (Portagerm pylori-PORT PYL, Pylori agar-PYL, GENbox microaer, bioMerieux, France), histology (Giemsa, Hematoxylin and Eosin staining), and RUT(CLOtest, Cimberly-Clark, USA). Antimicrobial resistance of isolates against amoxicillin, clarithromycin, levofloxacin, and metronidazole was determined by E-test method (bioMerieux, France). As a gold standard in the diagnosis of H. pylori; it was accepted that the culture method alone was positive or both histology and RUT were positive together. Sensitivity and specificity for histology and RUT were calculated by taking the culture as a gold standard. Sensitivity and specificity for culture were also calculated by taking the co-positivity of both histology and RUT as a gold standard. Results: H. pylori was detected in 140 of 278 of patients with culture and 174 of 278 of patients with histology in the study. H. pylori positivity was also found in 191 patients with RUT. According to the gold standard criteria, a false negative result was found in 39 cases by culture method, 17 cases by histology, and 8 cases by RUT. Sensitivity and specificity of the culture, histology, and RUT methods of the patients were 76.5 % and 88.3 %, 87.8 % and 63 %, 94.2 % and 57.2 %, respectively. Antibiotic resistance was investigated by E-test in 140 H. pylori strains isolated from culture. The resistance rates of H. pylori strains to the amoxicillin, clarithromycin, levofloxacin, and metronidazole was detected as 9 (6.4 %), 22 (15.7 %), 17 (12.1 %), 57 (40.7 %), respectively. Conclusion: In our study, RUT was found to be the most sensitive, culture was the most specific test between culture, histology, and RUT methods. Although we detected the specificity of the culture method as high, its sensitivity was found to be quite low compared to other methods. The low sensitivity of H. pylori culture may be caused by the factors affect the chances of direct isolation such as spoild bacterium, difficult-to-breed microorganism, clinical sample retrieval, and transport conditions.

Keywords: antimicrobial resistance, culture, histology, H. pylori, RUT

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13415 Application of Electrical Resistivity, Induced Polarization and Statistical Methods in Chichak Iron Deposit Exploration

Authors: Shahrzad Maghsoodi, Hamid Reza Ranazi

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This paper is devoted to exploration of Chichak (hematite) deposit, using electrical resistivity, chargeability and statistical methods. Chichak hematite deposit is located in Chichak area west Azarbaijan, northwest of Iran. There are some outcrops of hematite bodies in the area. The goal of this study was to identify the depth, thickness and shape of these bodies and to explore other probabile hematite bodies. Therefore nine profiles were considered to be surveyed by RS and IP method by utilizing an innovative electrode array so called CRSP (Combined Resistivity Sounding and Profiling). IP and RS sections were completed along each profile. In addition, the RS and IP data were analyzed and relation between these two variables was determined by statistical tools. Finally, hematite bodies were identified in each of the sections. The results showed that hematite bodies have a resistivity lower than 125 Ωm and very low chargeability, lower than 8 mV⁄V. After geophysical study some points were proposed for drilling, results obtained from drilling confirm the geophysical results.

Keywords: Hematite deposit, Iron exploration, Electrical resistivity, Chargeability, Iran, Chichak, Statistical, CRSP electrodes array

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13414 An Approach to Automate the Modeling of Life Cycle Inventory Data: Case Study on Electrical and Electronic Equipment Products

Authors: Axelle Bertrand, Tom Bauer, Carole Charbuillet, Martin Bonte, Marie Voyer, Nicolas Perry

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The complexity of Life Cycle Assessment (LCA) can be identified as the ultimate obstacle to massification. Due to these obstacles, the diffusion of eco-design and LCA methods in the manufacturing sectors could be impossible. This article addresses the research question: How to adapt the LCA method to generalize it massively and improve its performance? This paper aims to develop an approach for automating LCA in order to carry out assessments on a massive scale. To answer this, we proceeded in three steps: First, an analysis of the literature to identify existing automation methods. Given the constraints of large-scale manual processing, it was necessary to define a new approach, drawing inspiration from certain methods and combining them with new ideas and improvements. In a second part, our development of automated construction is presented (reconciliation and implementation of data). Finally, the LCA case study of a conduit is presented to demonstrate the feature-based approach offered by the developed tool. A computerized environment supports effective and efficient decision-making related to materials and processes, facilitating the process of data mapping and hence product modeling. This method is also able to complete the LCA process on its own within minutes. Thus, the calculations and the LCA report are automatically generated. The tool developed has shown that automation by code is a viable solution to meet LCA's massification objectives. It has major advantages over the traditional LCA method and overcomes the complexity of LCA. Indeed, the case study demonstrated the time savings associated with this methodology and, therefore, the opportunity to increase the number of LCA reports generated and, therefore, to meet regulatory requirements. Moreover, this approach also presents the potential of the proposed method for a wide range of applications.

Keywords: automation, EEE, life cycle assessment, life cycle inventory, massively

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13413 Main Tendencies of Youth Unemployment and the Regulation Mechanisms for Decreasing Its Rate in Georgia

Authors: Nino Paresashvili, Nino Abesadze

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The modern world faces huge challenges. Globalization changed the socio-economic conditions of many countries. The current processes in the global environment have a different impact on countries with different cultures. However, an alleviation of poverty and improvement of living conditions is still the basic challenge for the majority of countries, because much of the population still lives under the official threshold of poverty. It is very important to stimulate youth employment. In order to prepare young people for the labour market, it is essential to provide them with the appropriate professional skills and knowledge. It is necessary to plan efficient activities for decreasing an unemployment rate and for developing the perfect mechanisms for regulation of a labour market. Such planning requires thorough study and analysis of existing reality, as well as development of corresponding mechanisms. Statistical analysis of unemployment is one of the main platforms for regulation of the labour market key mechanisms. The corresponding statistical methods should be used in the study process. Such methods are observation, gathering, grouping, and calculation of the generalized indicators. Unemployment is one of the most severe socioeconomic problems in Georgia. According to the past as well as the current statistics, unemployment rates always have been the most problematic issue to resolve for policy makers. Analytical works towards to the above-mentioned problem will be the basis for the next sustainable steps to solve the main problem. The results of the study showed that the choice of young people is not often due to their inclinations, their interests and the labour market demand. That is why the wrong professional orientation of young people in most cases leads to their unemployment. At the same time, it was shown that there are a number of professions in the labour market with a high demand because of the deficit the appropriate specialties. To achieve healthy competitiveness in youth employment, it is necessary to formulate regional employment programs with taking into account the regional infrastructure specifications.

Keywords: unemployment, analysis, methods, tendencies, regulation mechanisms

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13412 The Significance of Picture Mining in the Fashion and Design as a New Research Method

Authors: Katsue Edo, Yu Hiroi

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T Increasing attention has been paid to using pictures and photographs in research since the beginning of the 21th century in social sciences. Meanwhile we have been studying the usefulness of Picture mining, which is one of the new ways for a these picture using researches. Picture Mining is an explorative research analysis method that takes useful information from pictures, photographs and static or moving images. It is often compared with the methods of text mining. The Picture Mining concept includes observational research in the broad sense, because it also aims to analyze moving images (Ochihara and Edo 2013). In the recent literature, studies and reports using pictures are increasing due to the environmental changes. These are identified as technological and social changes (Edo et.al. 2013). Low price digital cameras and i-phones, high information transmission speed, low costs for information transferring and high performance and resolution of the cameras of mobile phones have changed the photographing behavior of people. Consequently, there is less resistance in taking and processing photographs for most of the people in the developing countries. In these studies, this method of collecting data from respondents is often called as ‘participant-generated photography’ or ‘respondent-generated visual imagery’, which focuses on the collection of data and its analysis (Pauwels 2011, Snyder 2012). But there are few systematical and conceptual studies that supports it significance of these methods. We have discussed in the recent years to conceptualize these picture using research methods and formalize theoretical findings (Edo et. al. 2014). We have identified the most efficient fields of Picture mining in the following areas inductively and in case studies; 1) Research in Consumer and Customer Lifestyles. 2) New Product Development. 3) Research in Fashion and Design. Though we have found that it will be useful in these fields and areas, we must verify these assumptions. In this study we will focus on the field of fashion and design, to determine whether picture mining methods are really reliable in this area. In order to do so we have conducted an empirical research of the respondents’ attitudes and behavior concerning pictures and photographs. We compared the attitudes and behavior of pictures toward fashion to meals, and found out that taking pictures of fashion is not as easy as taking meals and food. Respondents do not often take pictures of fashion and upload their pictures online, such as Facebook and Instagram, compared to meals and food because of the difficulty of taking them. We concluded that we should be more careful in analyzing pictures in the fashion area for there still might be some kind of bias existing even if the environment of pictures have drastically changed in these years.

Keywords: empirical research, fashion and design, Picture Mining, qualitative research

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13411 Training of Future Computer Science Teachers Based on Machine Learning Methods

Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

Abstract:

The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

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13410 Image Segmentation: New Methods

Authors: Flaurence Benjamain, Michel Casperance

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We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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13409 Improved Super-Resolution Using Deep Denoising Convolutional Neural Network

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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13408 Comparing the Efficacy of Minimally Supervised Home-Based and Closely Supervised Gym Based Exercise Programs on Weight Reduction and Insulin Resistance after Bariatric Surgery

Authors: Haleh Dadgostar, Sara Kaviani, Hanieh Adib, Ali Mazaherinezhad, Masoud Solaymani-Dodaran, Fahimeh Soheilipour, Abdolreza Pazouki

Abstract:

Background and Objectives: Effectiveness of various exercise protocols in weight reduction after bariatric surgery has not been sufficiently explored in the literature. We compared the effect of minimally supervised home-based and closely supervised Gym based exercise programs on weight reduction and insulin resistance after bariatric surgery. Methods: Women undergoing gastric bypass surgery were invited to participate in an exercise program and were randomly allocated into two groups. They were either offered a minimally supervised home-based (MSHB) or closely supervised Gym-based (CSGB) exercise program. The CSGB protocol constitute two sessions per week of training under ACSM guidelines. In the MSHB protocol participants received a notebook containing a list of recommended aerobic and resistance exercises, a log to record their activity and a schedule of follow up phone calls and clinic visits. Both groups received a pedometer. We measured their weight, BMI, lipid profile, FBS, and insulin level at the baseline and after 20 weeks of exercise and were compared at the end of the study. Results: A total of 80 patients completed our study (MSHB=38 and CSGB=42). The baseline comparison showed that the two groups are similar. Using the ANCOVA method of analysis the mean change in BMI (covariate: BMI at the beginning of the study) was slightly better in CSGB compared with the MSHB (between-group mean difference: 3.33 (95%CI 4.718 to 1.943, F: 22.844 p < 0.001)). Conclusion: Our results showed that both MSHB and CSGB exercise methods are somewhat equally effective in improvement of studied factors in the two groups. With considerably lower costs of Minimally Supervised Home Based exercise programs, these methods should be considered when adequate funding are not available.

Keywords: postoperative exercise, insulin resistance, bariatric surgery, morbid obesity

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13407 Review of Hydrologic Applications of Conceptual Models for Precipitation-Runoff Process

Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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13406 Correlation Between Political Awareness and Political Participation for University Students: An Applied Study

Authors: Rana Mohamed Abd El Aal

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This is an exploratory study that aims to answer the question of whether and to what extent the prevailing political culture with a special focus to the factor of political awareness for Egyptian university students is influential in shaping their participatory behavior; more precisely in four main Universities ;(Cairo University- BaniSwif University- BUE University- Suez Canal University). To ensure the validity of my results, I deployed a number of different data collection methods: the collection, analysis, integration of both quantitative and qualitative methods; for investigating two main hypothesis H1: There is a positive relation between the political awareness level and political participation for university students, H2: There is a positive relation between political values in the society and the level of political participation of university students. The study reveals that though the sample represented the portion of political science students in different Universities, the level of political awareness and political participation was low with a statistically significant relationship; also, the patterns of values in Egyptian culture affects significantly the level of participation in the different universities. Therefore; the study using SWOT analysis recommends some policies for increasing the level of awareness and integrating youth in the political process.

Keywords: political awareness, political participation, civic culture, citizenship, egyptian universities, political knowledge

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13405 Short Arc Technique for Baselines Determinations

Authors: Gamal F.Attia

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The baselines are the distances and lengths of the chords between projections of the positions of the laser stations on the reference ellipsoid. For the satellite geodesy, it is very important to determine the optimal length of orbital arc along which laser measurements are to be carried out. It is clear that for the dynamical methods long arcs (one month or more) are to be used. According to which more errors of modeling of different physical forces such as earth's gravitational field, air drag, solar radiation pressure, and others that may influence the accuracy of the estimation of the satellites position, at the same time the measured errors con be almost completely excluded and high stability in determination of relative coordinate system can be achieved. It is possible to diminish the influence of the errors of modeling by using short-arcs of the satellite orbit (several revolutions or days), but the station's coordinates estimated by different arcs con differ from each other by a larger quantity than statistical zero. Under the semidynamical ‘short arc’ method one or several passes of the satellite in one of simultaneous visibility from both ends of the chord is known and the estimated parameter in this case is the length of the chord. The comparison of the same baselines calculated with long and short arcs methods shows a good agreement and even speaks in favor of the last one. In this paper the Short Arc technique has been explained and 3 baselines have been determined using the ‘short arc’ method.

Keywords: baselines, short arc, dynamical, gravitational field

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13404 The Findings EEG-LORETA about Epilepsy

Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

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13403 The Comparative Electroencephalogram Study: Children with Autistic Spectrum Disorder and Healthy Children Evaluate Classical Music in Different Ways

Authors: Galina Portnova, Kseniya Gladun

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In our EEG experiment participated 27 children with ASD with the average age of 6.13 years and the average score for CARS 32.41 and 25 healthy children (of 6.35 years). Six types of musical stimulation were presented, included Gluck, Javier-Naida, Kenny G, Chopin and other classic musical compositions. Children with autism showed orientation reaction to the music and give behavioral responses to different types of music, some of them might assess stimulation by scales. The participants were instructed to remain calm. Brain electrical activity was recorded using a 19-channel EEG recording device, 'Encephalan' (Russia, Taganrog). EEG epochs lasting 150 s were analyzed using EEGLab plugin for MatLab (Mathwork Inc.). For EEG analysis we used Fast Fourier Transform (FFT), analyzed Peak alpha frequency (PAF), correlation dimension D2 and Stability of rhythms. To express the dynamics of desynchronizing of different rhythms we've calculated the envelope of the EEG signal, using the whole frequency range and a set of small narrowband filters using Hilbert transformation. Our data showed that healthy children showed similar EEG spectral changes during musical stimulation as well as described the feelings induced by musical fragments. The exception was the ‘Chopin. Prelude’ fragment (no.6). This musical fragment induced different subjective feeling, behavioral reactions and EEG spectral changes in children with ASD and healthy children. The correlation dimension D2 was significantly lower in autists compared to healthy children during musical stimulation. Hilbert envelope frequency was reduced in all group of subjects during musical compositions 1,3,5,6 compositions compared to the background. During musical fragments 2 and 4 (terrible) lower Hilbert envelope frequency was observed only in children with ASD and correlated with the severity of the disease. Alfa peak frequency was lower compared to the background during this musical composition in healthy children and conversely higher in children with ASD.

Keywords: electroencephalogram (EEG), emotional perception, ASD, musical perception, childhood Autism rating scale (CARS)

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13402 Mine Project Evaluations in the Rising of Uncertainty: Real Options Analysis

Authors: I. Inthanongsone, C. Drebenstedt, J. C. Bongaerts, P. Sontamino

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The major concern in evaluating the value of mining projects related to the deficiency of the traditional discounted cash flow (DCF) method. This method does not take uncertainties into account and, hence it does not allow for an economic assessment of managerial flexibility and operational adaptability, which are increasingly determining long-term corporate success. Such an assessment can be performed with the real options valuation (ROV) approach, since it allows for a comparative evaluation of unforeseen uncertainties in a project life cycle. This paper presents an economic evaluation model for open pit mining projects based on real options valuation approach. Uncertainties in the model are caused by metal prices and cost uncertainties and the system dynamics (SD) modeling method is used to structure and solve the real options model. The model is applied to a case study. It can be shown that that managerial flexibility reacting to uncertainties may create additional value to a mining project in comparison to the outcomes of a DCF method. One important insight for management dealing with uncertainty is seen in choosing the optimal time to exercise strategic options.

Keywords: DCF methods, ROV approach, system dynamics modeling methods, uncertainty

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13401 The Effect of Different Surface Cleaning Methods on Porosity Formation and Mechanical Property of AA6xxx Aluminum Gas Metal Arc Welds

Authors: Fatemeh Mirakhorli

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Porosity is the main issue during welding of aluminum alloys, and surface cleaning has a critical influence to reduce the porosity level by removing the oxidized surface layer before fusion welding. Developing an optimum and economical surface cleaning method has an enormous benefit for aluminum welding industries to reduce costs related to repairing and repeating welds as well as increasing the mechanical properties of the joints. In this study, several mechanical and chemical surface cleaning methods were examined for butt joint welding of 2 mm thick AA6xxx alloys using ER5556 filler metal. The effects of each method on porosity formation and tensile properties are evaluated. It has been found that, compared to the conventional mechanical cleaning method, the use of chemical cleaning leads to an important reduction in porosity level even after a significant delay between cleaning and welding. The effect of the higher porosity level in the fusion zone to reduce the tensile strength of the welds is shown.

Keywords: gas metal arc welding (GMAW), aluminum alloy, surface cleaning, porosity formation, mechanical property

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13400 Large-Scale Screening for Membrane Protein Interactions Involved in Platelet-Monocyte Interactions

Authors: Yi Sun, George Ed Rainger, Steve P. Watson

Abstract:

Background: Beyond the classical roles in haemostasis and thrombosis, platelets are important in the initiation and development of various thrombo-inflammatory diseases. In atherosclerosis and deep vein thrombosis, for example, platelets bridge monocytes with endothelium and form heterotypic aggregates with monocytes in the circulation. This can alter monocyte phenotype by inducing their activation, stimulating adhesion and migration. These interactions involve cell surface receptor-ligand pairs on both cells. This list is likely incomplete as new interactions of importance to platelet biology are continuing to be discovered as illustrated by our discovery of PEAR-1 binding to FcεR1α. Results: We have developed a highly sensitive avidity-based assay to identify novel extracellular interactions among 126 recombinantly-expressed platelet cell surface and secreted proteins involved in platelet aggregation. In this study, we will use this method to identify novel platelet-monocyte interactions. We aim to identify ligands for orphan receptors and novel partners of well-known proteins. Identified interactions will be studied in preliminary functional assays to demonstrate relevance to the inflammatory processes supporting atherogenesis. Conclusions: Platelet-monocyte interactions are essential for the development of thromboinflammatory disease. Up until relatively recently, technologies only allow us to limit our studies on each individual protein interaction at a single time. These studies propose for the first time to study the cell surface platelet-monocyte interactions in a systematic large-scale approach using a reliable screening method we have developed. If successful, this will likely to identify previously unknown ligands for important receptors that will be investigated in details and also provide a list of novel interactions for the field. This should stimulate studies on developing alternative therapeutic strategies to treat vascular inflammatory disorders such as atherosclerosis, DVT and sepsis and other clinically important inflammatory conditions.

Keywords: membrane proteins, large-scale screening, platelets, recombinant expression

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13399 Effect of Open-Ended Laboratory toward Learners Performance in Environmental Engineering Course: Case Study of Civil Engineering at Universiti Malaysia Sabah

Authors: N. Bolong, J. Makinda, I. Saad

Abstract:

Laboratory activities have produced benefits in student learning. With current drives of new technology resources and evolving era of education methods, renewal status of learning and teaching in laboratory methods are in progress, for both learners and the educators. To enhance learning outcomes in laboratory works particularly in engineering practices and testing, learning via hands-on by instruction may not sufficient. This paper describes and compares techniques and implementation of traditional (expository) with open-ended laboratory (problem-based) for two consecutive cohorts studying environmental laboratory course in civil engineering program. The transition of traditional to problem-based findings and effect were investigated in terms of course assessment student feedback survey, course outcome learning measurement and student performance grades. It was proved that students have demonstrated better performance in their grades and 12% increase in the course outcome (CO) in problem-based open-ended laboratory style than traditional method; although in perception, students has responded less favorable in their feedback.

Keywords: engineering education, open-ended laboratory, environmental engineering lab

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13398 Transfer Rate of Organic Water Contaminants through a Passive Sampler Membrane of Polyethersulfone (PES)

Authors: Hamidreza Sharifan, Audra Morse

Abstract:

Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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13397 Flavonoids: Essential Players in Nutrition

Authors: D. Baranova, E. Neborak

Abstract:

Polyphenols, particularly flavonoids like quercetin, fisetin, and kaempferol, have gained significant attention in nutrition due to their antioxidant, senolytic, and anti-inflammatory properties. These compounds are commonly found in various plant-based foods and are represented by diverse subclasses, each with unique health benefits. Understanding their absorption, metabolism, and bioactivity within the human body is crucial for unlocking their full potential. Quercetin, for instance, exists in multiple forms, impacting its solubility and absorption in the intestine. Its intake, often derived from sources like apples, is affected by cooking methods, with medium heat retaining its potency. Fisetin, also present in fruits and vegetables, demonstrates neuroprotective qualities and stability under varied conditions compared to quercetin. Similarly, kaempferol, found in fruits and vegetables, displays antioxidative effects but is influenced by cooking techniques, with specific methods preserving its polyphenolic content better. Overall, these polyphenols offer promising health benefits, yet their optimal dosage and specific dietary recommendations warrant further research to harness their full nutritional potential.

Keywords: polyphenols, flavonoids, absorption, quercetin, kaempferol, fisetin, senolytics, absorption, cooking method

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13396 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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13395 Sustainable Renovation and Restoration of the Rural — Based on the View Point of Psychology

Authors: Luo Jin China, Jin Fang

Abstract:

Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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13394 System Identification in Presence of Outliers

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

Abstract:

The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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13393 Experimental and Theoretical Characterization of Supramolecular Complexes between 7-(Diethylamino)Quinoline-2(1H)-One and Cucurbit[7] Uril

Authors: Kevin A. Droguett, Edwin G. Pérez, Denis Fuentealba, Margarita E. Aliaga, Angélica M. Fierro

Abstract:

Supramolecular chemistry is a field of growing interest. Moreover, studying the formation of host-guest complexes between macrocycles and dyes is highly attractive due to their potential applications. Examples of the above are drug delivery, catalytic process, and sensing, among others. There are different dyes of interest in the literature; one example is the quinolinone derivatives. Those molecules have good optical properties and chemical and thermal stability, making them suitable for developing fluorescent probes. Secondly, several macrocycles can be seen in the literature. One example is the cucurbiturils. This water-soluble macromolecule family has a hydrophobic cavity and two identical carbonyl portals. Additionally, the thermodynamic analysis of those supramolecular systems could help understand the affinity between the host and guest, their interaction, and the main stabilization energy of the complex. In this work, two 7-(diethylamino) quinoline-2 (1H)-one derivative (QD1-2) and their interaction with cucurbit[7]uril (CB[7]) were studied from an experimental and in-silico point of view. For the experimental section, the complexes showed a 1:1 stoichiometry by HRMS-ESI and isothermal titration calorimetry (ITC). The inclusion of the derivatives on the macrocycle lends to an upward shift in the fluorescence intensity, and the pKa value of QD1-2 exhibits almost no variation after the formation of the complex. The thermodynamics of the inclusion complexes was investigated using ITC; the results demonstrate a non-classical hydrophobic effect with a minimum contribution from the entropy term and a constant binding on the order of 106 for both ligands. Additionally, dynamic molecular studies were carried out during 300 ns in an explicit solvent at NTP conditions. Our finding shows that the complex remains stable during the simulation (RMSD ~1 Å), and hydrogen bonds contribute to the stabilization of the systems. Finally, thermodynamic parameters from MMPBSA calculations were obtained to generate new computational insights to compare with experimental results.

Keywords: host-guest complexes, molecular dynamics, quinolin-2(1H)-one derivatives dyes, thermodynamics

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13392 Anti Oxidant Ayurvedic Rasyan Herbs Concept to Disease Managment

Authors: Mohammed Khalil Ur Rahman, Khanita Aammatullh

Abstract:

Rasayana is one of the eight clinical specialities of classical Ayurveda The disease preventive and health promotive approach of ‘Ayurveda’, which takes into consideration the whole body, mind and spirit while dealing with the maintenance of health, promotion of health and treating ailments is holistic and finds increasing acceptability in many regions of the world. Ancient Ayurvedic physicians had developed certain dietary and therapeutic measures to arrest/delay ageing and rejuvenating whole functional dynamics of the body system. This revitalization and rejuvenation is known as the ‘Rasayan chikitsa’ (rejuvenation therapy). Traditionally, Rasayana drugs are used against a plethora of seemingly diverse disorders with no pathophysiological connections according to modern medicine. Though, this group of plants generally possesses strong antioxidant activity, only a few have been investigated in detail. Over about 100 disorders like rheumatoid arthritis, hemorrhagic shock, CVS disorders, cystic fibrosis, metabolic disorders, neurodegenerative diseases, gastrointestinal ulcerogenesis and AIDS have been reported as reactive oxygen species mediated. In this review, the role of free radicals in these diseases has been briefly reviewed. ‘Rasayana’ plants with potent antioxidant activity have been reviewed for their traditional uses, and mechanism of antioxidant action. Fifteen such plants have been dealt with in detail and some more plants with less work have also been reviewed briefly The Rasayanas are rejuvenators, nutritional supplements and possess strong antioxidant activity. They also have antagonistic actions on the oxidative stressors, which give rise to the formation of different free radicals. Ocimum sanctum, Tinospora cordifolia, Emblica officinalis, Convolvulus pluricaulis, Centella asiatica, Bacopa monniera, Withania somnifera, Triphala rasayana, Chyawanprash, Brahma rasayana are very important rasayanas which are described in ayurveda and proved by new researches.

Keywords: rasayana, antioxidant activity, Bacopa monniera, Withania somnifera Triphala, chyawanprash

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