Search results for: community based sports

Authors: Quervin Zacary M. Roldan, Gwyneth Gabrielle M. Fajardo, Carmela M. Maciar

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Alcohol in the Philippines is regarded as a part of their culture however, it is also stigmatized, as alcohol addiction is prevalent among Filipino Males leading them to develop Alcohol Use Disorder. With this, Discourses of alcohol consumption from Individuals recovering from AUD from different rehabilitation centers in the Philippines were analyzed in the study to explore how they ‘talk’ about their alcohol consumption. By utilizing the Foucauldian Discourse Analysis following the six steps by Carla Willig, four (4) major discourses were major construed by the recovering individuals of AUD which are: (1) Being alcohol-free was a dream, (2) Drinking alcohol turns you into a demon that will destroy your life, (3) Drinking alcohol as ‘doing’ drugs and (4) Alcohol is a temporary solution. These discourses construct alcohol consumption as something that is being referred to as a 'bad' substance which is both normalized and stigmatized in Philippine society.

Keywords: alcohol, alcohol consumption, alcohol-based beverages, psychological effects, discourse, alcohol use disorder, stigma

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Authors: Grzegorz Baranski, Piotr Kacejko, Konrad Pietrykowski, Mariusz Duk

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This paper discusses a model of a bus-driving scheme. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the mechanical energy recuperation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass. The research results show that fuel economy is impacted by kinetic energy recuperation.

Keywords: heavy duty vehicle, city bus, Japanese JE05 test cycle, kinetic energy, simulations

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Authors: Wenjuan Du

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The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.

Keywords: phase compensation method, power system small-signal stability, power system stabilizer

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

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Authors: Naci Büyükkaracığan

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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Ahmad Almajid

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The idea of unifying quantum mechanics with general relativity is still a dream for many researchers, as physics has only two paths, no more. Einstein's path, which is mainly based on particle mechanics, and the path of Paul Dirac and others, which is based on wave mechanics, the incompatibility of the two approaches is due to the radical difference in the initial assumptions and the mathematical nature of each approach. Logical thinking in modern physics leads us to two problems: - In quantum mechanics, despite its success, the problem of measurement and the problem of wave function interpretation is still obscure. - In special relativity, despite the success of the equivalence of rest-mass and energy, but at the speed of light, the fact that the energy becomes infinite is contrary to logic because the speed of light is not infinite, and the mass of the particle is not infinite too. These contradictions arise from the overlap of relativistic and quantum mechanics in the neighborhood of the speed of light, and in order to solve these problems, one must understand well how to move from relativistic mechanics to quantum mechanics, or rather, to unify them in a way different from Dirac's method, in order to go along with God or Nature, since, as Einstein said, "God doesn't play dice." From De Broglie's hypothesis about wave-particle duality, Léon Brillouin's definition of the new proper time was deduced, and thus the quantum Lorentz factor was obtained. Finally, using the Euler-Lagrange equation, we come up with new equations in quantum mechanics. In this paper, the two problems in modern physics mentioned above are solved; it can be said that this new approach to quantum mechanics will enable us to unify it with general relativity quite simply. If the experiments prove the validity of the results of this research, we will be able in the future to transport the matter at speed close to the speed of light. Finally, this research yielded three important results: 1- Lorentz quantum factor. 2- Planck energy is a limited case of Einstein energy. 3- Real quantum mechanics, in which new equations for quantum mechanics match and exceed Dirac's equations, these equations have been reached in a completely different way from Dirac's method. These equations show that quantum mechanics is a limited case of relativistic mechanics. At the Solvay Conference in 1927, the debate about quantum mechanics between Bohr, Einstein, and others reached its climax, while Bohr suggested that if particles are not observed, they are in a probabilistic state, then Einstein said his famous claim ("God does not play dice"). Thus, Einstein was right, especially when he didn't accept the principle of indeterminacy in quantum theory, although experiments support quantum mechanics. However, the results of our research indicate that God really does not play dice; when the electron disappears, it turns into amicable particles or an elastic medium, according to the above obvious equations. Likewise, Bohr was right also, when he indicated that there must be a science like quantum mechanics to monitor and study the motion of subatomic particles, but the picture in front of him was blurry and not clear, so he resorted to the probabilistic interpretation.

Keywords: lorentz quantum factor, new, planck’s energy as a limiting case of einstein’s energy, real quantum mechanics, new equations for quantum mechanics

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Authors: Sidra Shabbir, Ayesha Manzoor, Mehreen Sirshar

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The use of the network communication has imposed serious threats to the security of assets over the network. Network security is getting more prone to active and passive attacks which may result in serious consequences to data integrity, confidentiality and availability. Various cryptographic techniques have been proposed in the past few years to combat with the concerned problem by ensuring quality but in order to have a fully secured network; a framework of new cryptosystem was needed. This paper discusses certain cryptographic techniques which have shown far better improvement in the network security with enhanced quality assurance. The scope of this research paper is to cover the security pitfalls in the current systems and their possible solutions based on the new cryptosystems. The development of new cryptosystem framework has paved a new way to the widespread network communications with enhanced quality in network security.

Keywords: cryptography, network security, encryption, decryption, integrity, confidentiality, security algorithms, elliptic curve cryptography

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Authors: Yehudit Dror

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Parallelism¬, or as it is called in Arabic, al-muqābala, occupies a central position in the rhetorical discipline of ʻilm al-bayān. Parallelism is used as a figure of textual ornamentation or embellishment and can be divided into several types that are based on the semantics of parallelism and its formative structure. Parallelism in Arabic has received a considerable amount of attention from the Arab rhetorician, which enables understanding the essence of parallelism in Arabic – its types, structure and meaning. However, there are some lacunae in their descriptions concerning the function and thematic restrictions of parallelism in the Qur’ān. In my presentation, which focuses on grammatical parallelism where the two stichos of the parallelism are the same with respect to syntax and morphology, I will show that parallelism has some important roles in the textual arrangement; it may, for example, conclude a thematic section, indicate a turning point in the text or to clarify what has been said previously. In addition, it will be shown that parallelism is not used randomly in the Qurʼān but rather is restricted to repeated themes which carry the most important messages of the Qurʼān, such as God's Might or behavioral patterns of the believers and the non-believers; or it can be used as a stylistic device.

Keywords: grammatical parallelism, half-line, symmetry, Koran

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: F. Varga, Z. Liber, J. Jakše, A. Turudić, Z. Šatović, I. Radosavljević, N. Jeran, M. Grdiša

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Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.; Asteraceae), a source of the commercially dominant plant insecticide pyrethrin, is a species endemic to the eastern Adriatic. Genetic diversity of T. cinerariifolium was previously studied using amplified fragment length polymorphism (AFLP) markers. However, microsatellite markers (single sequence repeats - SSRs) are more informative because they are codominant, highly polymorphic, locus-specific, and more reproducible, and thus are most often used to assess the genetic diversity of plant species. Dalmatian pyrethrum is an outcrossing diploid (2n = 18) whose large genome size and high repeatability have prevented the success of the traditional approach to SSR markers development. The advent of next-generation sequencing combined with the specifically developed method recently enabled the development of, to the author's best knowledge, the first set of SSRs for genomic characterization of Dalmatian pyrethrum, which is essential from the perspective of plant genetic resources conservation. To evaluate the effectiveness of the developed SSR markers in genetic differentiation of Dalmatian pyrethrum populations, a preliminary genetic diversity study was conducted on 30 individuals from three geographically distinct natural populations in Croatia (northern Adriatic island of Mali Lošinj, southern Adriatic island of Čiovo, and Mount Biokovo) based on 12 SSR loci. Analysis of molecular variance (AMOVA) by randomization test with 10,000 permutations was performed in Arlequin 3.5. The average number of alleles per locus, observed and expected heterozygosity, probability of deviations from Hardy-Weinberg equilibrium, and inbreeding coefficient was calculated using GENEPOP 4.4. Genetic distance based on the proportion of common alleles (DPSA) was calculated using MICROSAT. Cluster analysis using the neighbor-joining method with 1,000 bootstraps was performed with PHYLIP to generate a dendrogram. The results of the AMOVA analysis showed that the total SSR diversity was 23% within and 77% between the three populations. A slight deviation from Hardy-Weinberg equilibrium was observed in the Mali Lošinj population. Allele richness ranged from 2.92 to 3.92, with the highest number of private alleles observed in the Mali Lošinj population (17). The average observed DPSA between 30 individuals was 0.557. The highest DPSA (0.875) was observed between several pairs of Dalmatian pyrethrum individuals from the Mali Lošinj and Mt. Biokovo populations, and the lowest between two individuals from the Čiovo population. Neighbor-joining trees, based on DPSA, grouped individuals into clusters according to their population affiliation. The separation of Mt. Biokovo clade was supported (bootstrap value 58%), which is consistent with the previous study on AFLP markers, where isolated populations from Mt. Biokovo differed from the rest of the populations. The developed SSR markers are an effective tool for assessing the genetic diversity and structure of natural Dalmatian pyrethrum populations. These preliminary results are encouraging for a future comprehensive study with a larger sample size across the species' range. Combined with the biochemical data, these highly informative markers could help identify potential genotypes of interest for future development of breeding lines and cultivars that are both resistant to environmental stress and high in pyrethrins. Acknowledgment: This work has been supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) insecticidal potential’- (PyrDiv) (IP-06-2016-9034) and by project KK.01.1.1.01.0005, Biodiversity and Molecular Plant Breeding, at the Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia.

Keywords: Asteraceae, genetic diversity, genomic SSRs, NGS, pyrethrum, Tanacetum cinerariifolium

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Authors: H. Cha, J. Kim, D. Kim, J. Shin, K. Lee

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Since 1980's, the rapid economic growth resulted in so many aged apartment buildings in South Korea. Nevertheless, there is insufficient maintenance practice of buildings. In this study, to facilitate the building maintenance the authors classified the building defects into three levels according to their level of performance and developed a mobile application tool based on each level's appropriate feedback. The feedback structure consisted of 'Maintenance manual phase', 'Online feedback phase', 'Repair work phase of the specialty contractors'. In order to implement each phase the authors devised the necessary database for each phase and created a prototype system that can develop on its own. The authors expect that the building users can easily maintain their buildings by using this application.

Keywords: building defect, maintenance practice, mobile application, system algorithm

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: rubber bumper, data acquisition, finite element analysis, support vector regression

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Authors: Shirin Arefi

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In Iran, women and girls are treated as second class citizens and suffer from many discrimination and inequality such as compulsory Hejab, a phenomena which has required all women to wear the hijab head-covering since the 1979 Islamic revolution. Now, the crackdown of new government has caused a massive uproar in the country. The morality police also continue to curb the choices of women, and the latest unfortunate incidents accelerate the hardened rules. The author is going to survey the views and of women against compulsory Hejab and morality and chastity police arrests. The methodology is a qualitative one in which narratives of them are coded based on grounded theory and horizons of the process is explained by phenomenological research as well. The findings and results will show the current attitudes of women of Hejab and their reactions against morality police behaviors.

Keywords: compulsory hejab, morality police, people, arrest

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Authors: Nurazean Maarop, Noorjan Mohd Mustapha, Rasimah Yusoff, Roslina Ibrahim, Norziha Megat Mohd Zainuddin

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The goal of this study is to identify success factors that could influence the ISMS self-implementation in government sector from qualitative perspective. This study is based on a case study in one of the Malaysian government agency. Semi-structured interviews involving five key informants were conducted to examine factors addressed in the conceptual framework. Subsequently, thematic analysis was executed to describe the influence of each factor on the success implementation of ISMS. The result of this study indicates that management commitment, implementer commitment and implementer competency are part of the success factors for ISMS self-implementation in Malaysian Government Sector.

Keywords: ISMS success factors, IT project management, IS success, information security

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Authors: Felipe B. Martinez, Imelda C. Galera

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This paper presents an update on the physico-chemical properties of the Taal Lake for local government officials and representatives of non-government organizations by monitoring and evaluating a total of nine (9) water quality parameters. The study further shows that the Taal Lakes surface temperature, pH, total dissolved solids, total suspended solids, color, and dissolved oxygen content conform to the standards set by the Department of Environment and Natural resources (DENR); while phosphate, chlorine, and 5-Day 20°C BOD are below the standard. Likewise, the T-test result shows no significant difference in the overall average of the two sites at the Taal Lake (P > 0.05). Based on the data, the Lake is safe for primary contact recreation such as bathing, swimming and skin diving, and can be used for aqua culture purposes.

Keywords: cool dry season, hot dry season, rainy season, Taal Lake, water quality

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Authors: A. Ramachandra Reddy, V. Murugan, Prema Kumari

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Residual solvents in Pharmaceutical samples are monitored using gas chromatography with headspace (GC-HS). Based on current regulatory and compendial requirements, measuring the residual solvents are mandatory for all release testing of active pharmaceutical ingredients (API). Generally, isopropyl alcohol is used as the residual solvent in proline and tryptophan; methanol in cysteine monohydrate hydrochloride, glycine, methionine and serine; ethanol in glycine and lysine monohydrate; acetic acid in methionine. In order to have a single method for determining these residual solvents (isopropyl alcohol, ethanol, methanol and acetic acid) in all these 7 amino acids a sensitive and simple method was developed by using gas chromatography headspace technique with flame ionization detection. During development, no reproducibility, retention time variation and bad peak shape of acetic acid peaks were identified due to the reaction of acetic acid with the stationary phase (cyanopropyl dimethyl polysiloxane phase) of column and dissociation of acetic acid with water (if diluent) while applying temperature gradient. Therefore, dimethyl sulfoxide was used as diluent to avoid these issues. But most the methods published for acetic acid quantification by GC-HS uses derivatisation technique to protect acetic acid. As per compendia, risk-based approach was selected as appropriate to determine the degree and extent of the validation process to assure the fitness of the procedure. Therefore, Total error concept was selected to validate the analytical procedure. An accuracy profile of ±40% was selected for lower level (quantitation limit level) and for other levels ±30% with 95% confidence interval (risk profile 5%). The method was developed using DB-Waxetr column manufactured by Agilent contains 530 µm internal diameter, thickness: 2.0 µm, and length: 30 m. A constant flow of 6.0 mL/min. with constant make up mode of Helium gas was selected as a carrier gas. The present method is simple, rapid, and accurate, which is suitable for rapid analysis of isopropyl alcohol, ethanol, methanol and acetic acid in amino acids. The range of the method for isopropyl alcohol is 50ppm to 200ppm, ethanol is 50ppm to 3000ppm, methanol is 50ppm to 400ppm and acetic acid 100ppm to 400ppm, which covers the specification limits provided in European pharmacopeia. The accuracy profile and risk profile generated as part of validation were found to be satisfactory. Therefore, this method can be used for testing of residual solvents in amino acids drug substances.

Keywords: amino acid, head space, gas chromatography, total error

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: Egboja Simon Oga

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One of the most important keys to the success of a nation is to ensure steady development and national economic self-sufficiency and independence. It is therefore in this regard that this paper is designed to identify food security to be crucial to all nations’ effort toward sustainable national development. Nigeria as a case study employed various effort by the successive government towards food security. Emphasis were placed on the extent to which government has boosted food security situation on the basis of the identified limitations, conclusion was drawn, recommendation/suggestions proffered, that subsidization of the process of farm inputs like fertilizer, improved seeds and agrochemical, education of farmers on modern methods of farming through extension services, improvisation of village-based food storage mechanism and provision of infrastructural facilities in rural areas to facilitate the preservation and easy evacuation of farm produces are necessary.

Keywords: food, governance, development, security

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Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

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Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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Authors: A. Kavita Murugkar, B. Anurag Kashyap

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With the Rights for Persons with Disabilities Act (RPWD Act) 2016, the Indian government has made it mandatory for all establishments, including Heritage Sites, to be accessible for People with Disabilities. However, recent access audit surveys done under the Accessible India Campaign by Ministry of Culture indicate that there are very few accessibility measures provided in the Heritage sites for people with disabilities. Though there are some measures for the mobility impaired, surveys brought out that there are almost no provisions for people with vision impairment (PwVI) in heritage sites thus depriving them of a reasonable physical & intellectual access that facilitates an enjoyable experience and enriching interpretation of the Heritage Site. There is a growing need to develop multisensory interpretative tools that can help the PwVI in perceiving heritage sites in the absence of vision. The purpose of this research was to examine the usability of an audio-tactile model as a haptic and sound-based strategy for augmenting the perception and experience of PwVI in a heritage site. The first phase of the project was a multi-stage phenomenological experimental study with visually impaired users to investigate the design parameters for developing an audio-tactile model for PwVI. The findings from this phase included user preferences related to the physical design of the model such as the size, scale, materials, details, etc., and the information that it will carry such as braille, audio output, tactile text, etc. This was followed by the second phase in which a working prototype of an audio-tactile model is designed and developed for a heritage site based on the findings from the first phase of the study. A nationally listed heritage site from the author’s city was selected for making the model. The model was lastly tested by visually impaired users for final refinements and validation. The prototype developed empowers People with Vision Impairment to navigate independently in heritage sites. Such a model if installed in every heritage site, can serve as a technological guide for the Person with Vision Impairment, giving information of the architecture, details, planning & scale of the buildings, the entrances, location of important features, lifts, staircases, and available, accessible facilities. The model was constructed using 3D modeling and digital printing technology. Though designed for the Indian context, this assistive technology for the blind can be explored for wider applications across the globe. Such an accessible solution can change the otherwise “incomplete’’ perception of the disabled visitor, in this case, a visually impaired visitor and augment the quality of their experience in heritage sites.

Keywords: accessibility, architectural perception, audio tactile model , inclusive heritage, multi-sensory perception, visual impairment, visitor experience

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Authors: Melese Wondatir

Abstract:

Flooding ranks among the most destructive natural disasters, impacting millions of individuals globally and resulting in substantial economic, social, and environmental repercussions. This study's objective was to create a comprehensive model that assesses the Nile River basin's susceptibility to flood damage and improves existing flood risk management strategies. Authorities responsible for enacting policies and implementing measures may benefit from this research to acquire essential information about the flood, including its scope and susceptible areas. The identification of severe flood damage locations and efficient mitigation techniques were made possible by the use of geospatial data. Slope, elevation, distance from the river, drainage density, topographic witness index, rainfall intensity, distance from road, NDVI, soil type, and land use type were all used throughout the study to determine the vulnerability of flood damage. Ranking elements according to their significance in predicting flood damage risk was done using the Analytic Hierarchy Process (AHP) and geospatial approaches. The analysis finds that the most important parameters determining the region's vulnerability are distance from the river, topographic witness index, rainfall, and elevation, respectively. The consistency ratio (CR) value obtained in this case is 0.000866 (<0.1), which signifies the acceptance of the derived weights. Furthermore, 10.84m2, 83331.14m2, 476987.15m2, 24247.29m2, and 15.83m2 of the region show varying degrees of vulnerability to flooding—very low, low, medium, high, and very high, respectively. Due to their close proximity to the river, the northern-western regions of the Nile River basin—especially those that are close to Sudanese cities like Khartoum—are more vulnerable to flood damage, according to the research findings. Furthermore, the AUC ROC curve demonstrates that the categorized vulnerability map achieves an accuracy rate of 91.0% based on 117 sample points. By putting into practice strategies to address the topographic witness index, rainfall patterns, elevation fluctuations, and distance from the river, vulnerable settlements in the area can be protected, and the impact of future flood occurrences can be greatly reduced. Furthermore, the research findings highlight the urgent requirement for infrastructure development and effective flood management strategies in the northern and western regions of the Nile River basin, particularly in proximity to major towns such as Khartoum. Overall, the study recommends prioritizing high-risk locations and developing a complete flood risk management plan based on the vulnerability map.

Keywords: analytic hierarchy process, Blue Nile Basin, geospatial techniques, flood vulnerability, multi-criteria decision making

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Authors: M. Pappa, C. Efstathiou, G. Livanos, P. Xidas, D. Vakondios, E. Maravelakis, M. Zervakis, A. Antoniadis

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The choice of cutting tools in manufacturing processes is an essential parameter on which the required manufacturing time, the consumed energy and the cost effort all depend. If the number of tool changing times could be minimized or even eliminated by using a single convex tool providing multiple profiles, then a significant benefit of time and energy saving, as well as tool cost, would be achieved. A typical machine contains a variety of tools in order to deal with different curvatures and material removal rates. In order to minimize the required cutting tool changes, Actively Deformable micro-Cutters (ADmC) will be developed. The design of the Actively Deformable micro-Cutters will be based on the same cutting technique and mounting method as that in typical cutters.

Keywords: deformable cutters, cutting tool, milling, turning, manufacturing

Procedia PDF Downloads 452

Authors: Sonu Gandhi, Neena Capalash, Prince Sharma, C. Raman Suri

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A sensitive chemiluminescence immunoassay (CIA) for heroin and its major metabolites is reported. The method is based on the competitive reaction of horseradish peroxidase (HRP)-labeled anti-MAM antibody and free drug in spiked urine samples. A hapten-protein conjugate was synthesized by using acidic derivative of monoacetyl morphine (MAM) coupled to carrier protein BSA and was used as an immunogen for the generation of anti-MAM (monoacetyl morphine) antibody. A high titer of antibody (1:64,0000) was obtained and the relative affinity constant (Kaff) of antibody was 3.1×107 l/mol. Under the optimal conditions, linear range and reactivity for heroin, mono acetyl morphine (MAM), morphine and codeine were 0.08, 0.09, 0.095 and 0.092 ng/mL respectively. The developed chemiluminescence inhibition assay could detect heroin and its metabolites in standard and urine samples up to 0.01 ng/ml.

Keywords: heroin, metabolites, chemiluminescence immunoassay, horse radish peroxidase

Procedia PDF Downloads 270

Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume

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Climate change and its effects on low external temperatures in winter require great consumption of energy to improve the greenhouse microclimate and increase agricultural production. To reduce the amount of energy consumed, a solar system has been developed to heat an agricultural greenhouse. This system is based on a transfer fluid that will circulate inside the greenhouse through a solar copper coil positioned on the roof of the greenhouse. This thermal energy accumulated during the day will be stored to be released during the night to improve the greenhouse’s microclimate. The use of this solar heating system has resulted in an average increase in the greenhouse’s indoor temperature of 8.3°C compared to the outdoor environment. This improved temperature has created a more favorable climate for crops and has subsequently had a positive effect on their development, quality, and production.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

Procedia PDF Downloads 89

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 106

Authors: Hayrettin Eroglu, Oguz Aksakal

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In this study, it is analysed that which decontamination products are more effective and how decontamination process should be performed in the case of contamination of radioactive 99mTc which is the most common radioactive element used in nuclear applications dealing with the human body or the environment. Based on the study, it is observed that existing radioactive washers are less effective than expected, alcohol has no effect on the decontamination of 99mTc, and temperature and pH are the most important factors. In the light of the analysis, it is concluded that the most effective decontamination product is DM-D (Decontamination Material-D). When the effect of DM-D on surfaces is analysed, it is observed that decontamination is very fast on scrubs and formica with both DM-D and water, and although DM-D is very effective on skin, it is not effective on f ceramic tiles and plastic floor covering material. Also in this study, the effectiveness of different molecular groups in the decontaminant was investigated. As a result, the acetate group has been observed as the most effective component of the decontaminant.

Keywords: contamination, radioactive, technetium, decontamination

Procedia PDF Downloads 405

Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

Procedia PDF Downloads 274