Search results for: times series analysis

Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Rajiv Kumar Srivastava

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Manufacturing of complex products such as automobiles and computers requires a very large number of parts and sub-assemblies. The design of mechanisms for delivery of these materials to the point of assembly is an important manufacturing system and supply chain challenge. Different approaches to this problem have been evolved for assembly lines designed to make large volumes of standardized products. However, contemporary assembly systems are required to concurrently produce a variety of products using approaches such as mixed model production, and at times even mass customization. In this paper we examine the material supply approaches for variety production in moderate to large volumes. The conventional approach for material delivery to high volume assembly lines is to supply and stock materials line-side. However for certain materials, especially when the same or similar items are used along the line, it is more convenient to supply materials in kits. Kitting becomes more preferable when lines concurrently produce multiple products in mixed model mode, since space requirements could increase as product/ part variety increases. At times such kits may travel along with the product, while in some situations it may be better to have delivery and station-specific kits rather than product-based kits. Further, in some mass customization situations it may even be better to have a single delivery and assembly station, to which an entire kit is delivered for fitment, rather than a normal assembly line. Finally, in low-moderate volume assembly such as in engineered machinery, it may be logistically more economical to gather materials in an order-specific kit prior to launching final assembly. We have studied material supply mechanisms to support assembly systems as observed in case studies of firms with different combinations of volume and variety/ customization. It is found that the appropriate approach tends to be a hybrid between direct line supply and different kitting modes, with the best mix being a function of the manufacturing and supply chain environment, as well as space and handling considerations. In our continuing work we are studying these scenarios further, through the use of descriptive models and progressing towards prescriptive models to help achieve the optimal approach, capturing the trade-offs between inventory, material handling, space, and efficient line supply.

Keywords: assembly systems, kitting, material supply, variety production

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Authors: Muhammad Suhaib

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Requirements Analysis are the most important part of software Engineering for both system application development, and project requirements. Conflicts often arise during the requirements gathering and analysis phase. This research aims to identify conflicts during the requirements gathering phase in software development life cycle, Research, Development, and Technology converted the world into a global village. During requirements elicitation/gathering phase it’s very difficult to understand the main objective of stakeholders, after completion of requirements elicitation task final results are used for Software Requirements Specification (SRS), SRS is the highly important outcome of the requirements analysis phase. this is the foundation between the developers and stakeholders or customers, proposed methodology will be helpful to identify those conflicts in a very easy manner during the initial phase of the project.

Keywords: goal oriented requirements analysis, conflicts identification model, requirements analysis, requirements engineering

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Authors: Emeka Okonkwo

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The Information Technology (IT) has prevailed over all functions of strategic and operational management. The Internet (a product of information technology) has increasingly become a popular medium for marketing. This paper examines the potentials of Internet for tourism marketing. To achieve this, the paper x-rays the characteristics of tourism marketing and examines the application of the Internet in tourism marketing. It is argued that the use of Internet for tourism marketing will not only reach a broad audience and reduce the cost of transaction (by conventional methods used by travel agents in times past), but, will also alleviate the problems of identification, authentication and confirmation of travels/package tours by tourists as well as promotion of tourism industry.

Keywords: internet, marketing, tourism, tourism management

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Authors: Sultan Ben Jaber

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Optical properties of molecules exhibit dramatic changes when adsorbed close to nano-structure metallic surfaces such as gold and silver nanomaterial. This phenomena opened a wide range of research to improve conventional spectroscopies efficiency. A well-known technique that has an intensive focus of study is surface-enhanced Raman spectroscopy (SERS), as since the first observation of SERS phenomena, researchers have published a great number of articles about the potential mechanisms behind this effect as well as developing materials to maximize the enhancement. Infrared and Raman spectroscopy are complementary techniques; thus, surface-enhanced infrared absorption (SEIRA) also shows a noticeable enhancement of molecules in the mid-IR excitation on nonmetallic structure substrates. In the SEIRA, vibrational modes that gave change in dipole moments perpendicular to the nano-metallic substrate enhanced 200 times greater than the free molecule’s modes. SEIRA spectroscopy is promising for the characterization and identification of adsorbed molecules on metallic surfaces, especially at trace levels. IR reflection-absorption spectroscopy (IRAS) is a well-known technique for measuring IR spectra of adsorbed molecules on metallic surfaces. However, SEIRA spectroscopy sensitivity is up to 50 times higher than IRAS. SEIRA enhancement has been observed for a wide range of molecules adsorbed on metallic substrates such as Au, Ag, Pd, Pt, Al, and Ni, but Au and Ag substrates exhibited the highest enhancement among the other mentioned substrates. In this work, trace levels of 3,4-methylenedioxymethamphetamine (MDMA) have been detected using gold nanoparticles (AuNPs) substrates with surface-enhanced infrared absorption (SEIRA). AuNPs were first prepared and washed, then mixed with different concentrations of MDMA samples. The process of fabricating the substrate prior SEIRA measurements included mixing of AuNPs and MDMA samples followed by vigorous stirring. The stirring step is particularly crucial, as stirring allows molecules to be robustly adsorbed on AuNPs. Thus, remarkable SEIRA was observed for MDMA samples even at trace levels, showing the rigidity of our approach to preparing SEIRA substrates.

Keywords: surface-enhanced infrared absorption (SEIRA), gold nanoparticles (AuNPs), amphetamines, methylene dioxy- methamphetamine (MDMA), enhancement factor

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Authors: R. H. Begaydarova, B. Zh. Kultanov, B. T. Esilbaeva, G. E. Nasakaeva, Y. Yukhnevich, G. K. Alshynbekova, A. E. Dyusembaeva

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Background: The level of middle molecules of peptides (MMP) allows to evaluate the severity and prognosis of the disease and is a criterion for the effectiveness of the treatment. The detection the products of lipidperoxidation cascade, such as conjugated dienes, malondialdehyde in biological material, has an important role in the development of pathogenesis, the diagnosis and prognosis in different parasitic diseases. Purpose of the study was to evaluate the state of endogenous intoxication and indicators of lipid peroxidation in patients with giardiasis before and after treatment. Materials and methods: Endogenous intoxication was evaluated in patients with giardiasis in the level of middle molecules of peptides (MMP) in the blood. The amount of MMP and products of lipid peroxidation were determined in the blood of 198 patients with giardiasis, 129 of them were women (65%), 69 were men (35%). The MMP level was detected for comparison in the blood of 84 healthy volunteers. The lipid peroxidation were determined in 40 healthy men and women without giardiasis and history of chronic diseases. Data were processed by conventional methods of variation statistics, we calculated the arithmetic mean (M) and standard dispersion (m). t-test (t) was used to assess differences. Results: The level of MMP in the blood was significantly higher in patients with giardiasis in comparison with group of healthy men and women. MMP concentration in the blood of women with Giardia was 2.5 times greater than that of the comparison groups of women. The level of MMP exceeds more than 6 times in men with giardiasis. The decrease in the intensity of endogenous intoxication was two weeks after antigiardia therapy, both men and women. According to the study, a statistically significant increase in the level of all the studied parameters lipid peroxidation cascade was observed in the blood of men with giardiasis, with the exception of the total primary production (NGN). The treatment of giardiasis helped to stabilize the level of almost all metabolites of lipid peroxidation cascade. The exception was level of malondialdehyde, it was significantly elevated to compare with the control group and after treatment. Conclusion: Thus, the MMP level was significantly higher in blood of patients with giardiasis than in comparison group. This is evidence of severe endogenous intoxication caused by giardia infection. The accumulation of primary and secondary products of lipid peroxidation was observed in the blood of men and women. These processes tend to be more active in men than in women. Antigiardiasis therapy contributed to the normalization of almost all the studied indicators of lipid peroxidation in the blood of participants, except the level malondialdehyde in the blood of men.

Keywords: enzymes of antioxidant protection, giardiasis, blood, treatment

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Authors: James Newman

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Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Abdullah Al Faruque, Ram Balachandar

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Series of laboratory tests were carried out to study the extent of scour caused by a three-dimensional wall jets exiting from a square cross-section nozzle and into a non-cohesive sand beds. Previous observations have indicated that the effect of the tailwater depth was significant for densimetric Froude number greater than ten. However, the present results indicate that the cut off value could be lower depending on the value of grain size-to-nozzle width ratio. Numbers of equations are drawn out for a better scaling of numerous scour parameters. Also suggested the empirical prediction of scour to predict the scour centre line profile and plan view of scour profile at any particular time.

Keywords: densimetric froude number, jets, nozzle, sand, scour, tailwater, time

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Authors: Jelena S. Kiurski, Vesna S. Kecić, Snežana M. Aksentijević

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The identification and evaluation of organic and inorganic pollutants were performed in a flexographic facility in Novi Sad, Serbia. Air samples were collected and analyzed in situ, during 4-hours working time at five sampling points by the mobile gas chromatograph and ozonometer at the printing of collagen casing. Experimental results showed that the concentrations of isopropyl alcohol, acetone, total volatile organic compounds and ozone varied during the sampling times. The highest average concentrations of 94.80 ppm and 102.57 ppm were achieved at 200 minutes from starting the production for isopropyl alcohol and total volatile organic compounds, respectively. The mutual dependences between target hazardous and microclimate parameters were confirmed using a multiple linear regression model with software package STATISTICA 10. Obtained multiple coefficients of determination in the case of ozone and acetone (0.507 and 0.589) with microclimate parameters indicated a moderate correlation between the observed variables. However, a strong positive correlation was obtained for isopropyl alcohol and total volatile organic compounds (0.760 and 0.852) with microclimate parameters. Higher values of parameter F than F_critical for all examined dependences indicated the existence of statistically significant difference between the concentration levels of target pollutants and microclimates parameters. Given that, the microclimate parameters significantly affect the emission of investigated gases and the application of eco-friendly materials in production process present a necessity.

Keywords: flexographic printing, indoor air, multiple regression analysis, pollution emission

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Authors: Atoui Oussama, Maazoun Azer, Belkassem Bachir, Pyl Lincy, Lecompte David

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For many decades, researchers have been focused on understanding the dynamic behavior of different structures and materials subjected to fragment impact or blast loads separately. The explosion mechanics, as well as the impact physics studies dealing with the numerical modeling of the response of protective structures under the synergistic effect of a blast wave and the impact of fragments, are quite limited in the literature. This article numerically evaluates the nonlinear dynamic behavior and damage mechanisms of Aluminum plates EN AW-1050A- H24 under different combined loading scenarios varied by the sequence of the applied loads using the commercial software LS-DYNA. For one hand, with respect to the terminal ballistic field investigations, a Lagrangian (LAG) formulation is used to evaluate the different failure modes of the target material in case of a fragment impact. On the other hand, with respect to the blast field analysis, an Arbitrary Lagrangian-Eulerian (ALE) formulation is considered to study the fluid-structure interaction (FSI) of the shock wave and the plate in case of a blast loading. Four different loading scenarios are considered: (1) only blast loading, (2) only fragment impact, (3) blast loading followed by a fragment impact and (4) a fragment impact followed by blast loading. From the numerical results, it was observed that when the impact load is applied to the plate prior to the blast load, it suffers more severe damage due to the hole enlargement phenomenon and the effects of crack propagation on the circumference of the damaged zone. Moreover, it was found that the hole from the fragment impact loading was enlarged to about three times in diameter as compared to the diameter of the projectile. The validation of the proposed computational model is based in part on previous experimental data obtained by the authors and in the other part on experimental data obtained from the literature. A good correspondence between the numerical and experimental results is found.

Keywords: computational analysis, combined loading, explosion mechanics, hole enlargement phenomenon, impact physics, synergistic effect, terminal ballistic

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Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

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Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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Authors: Chien-Ju Chen, Chia-Jui Yu, Jyun-Hao Liao, Chia-Ching Wu, Meng-Chyi Wu

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A 64 × 64 GaN-based micro-light-emitting diode array (μLEDA) with 20 μm in pixel size and 40 μm in pitch by flip-chip bonding (FCB) is demonstrated in this study. Besides, an underfilling (UF) technology is applied to the process for improving the uniformity of device. With those configurations, good characteristics are presented, operation voltage and series resistance of a pixel in the 450 nm flip chip μLEDA are 2.89 V and 1077Ω (4.3 mΩ-cm²) at 25 A/cm², respectively. The μLEDA can sustain higher current density compared to conventional LED, and the power of the device is 9.5 μW at 100 μA and 0.42 mW at 20 mA.

Keywords: GaN, micro-light-emitting diode array(μLEDA), flip-chip bonding, underfilling

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Authors: Fatih Sonmez

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease and it is the most common form of dementia that affects aged people. Acetylcholinesterase is a hydrolase involved in the termination of impulse transmission at cholinergic synapses by rapid hydrolysis of the neurotransmitter ACh in the central and peripheral nervous system. Carvacrol (5-iso-propyl-2-methyl-phenol) is a main bioactive monoterpene isolated from many medicinal herbs, such as Thymus vulgaris, Monarda punctate and Origanum vulgare spp. It is known that carvacrol has been widely used as an active anti-inflammatory ingredient, which can inhibit the isoproterenol induced inflammation in myocardial infarcted rats. In this paper, a series of 12 carvacrol substituted carbamate derivatives (2a-l) was synthesized and their inhibitory activities on AChE and BuChE were evaluated. Among them, 2d exhibited the strongest inhibition against AChE with an IC50 value of 2.22 µM, which was 130-fold more than that of carvacrol (IC50 = 288.26 µM).

Keywords: Acetylcholinesterase, Butyrylcholinesterase, Carbamate, Carvacrol

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Hassan Athari, Alireza Ruhi Sales, Amin Pourafshar, Seyyed Mehdi Pestei, Marc. A. Rosen

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In order to achieve high efficiency and high specific work with lower emissions, the use of advanced gas turbine cycles for power generation is useful and advantageous. Here, evaporative inlet air cooling is analyzed thermodynamically in the form of air film blade cooling of gas turbines. As the ambient temperature increases during summer months, the performance of gas turbines particularly the output power and energy efficiency are significantly decreased. The utilization of evaporative inlet cooling in gas turbine cycles increases gas turbine performance, which can assist to solve the problem in meeting the increasing demands for electrical power and offsetting shortages during peak load times. In the present research, because of the importance of turbine blade cooling, the turbine is investigated with cold compressed air used for cooling the turbine blades. The investigation of the basic and modified cycles shows that, by adding an evaporative cooler to a simple gas turbine cycle, for a turbine inlet temperature of 1400 °C, an ambient temperature of 45 °C and a relative humidity of 15%, the specific work can reach 331 (kJ/kg air), while the maximum specific work of a simple cycle for the same conditions is 273.7 (kJ/kg air). The exergy results reveal that the highest exergy destruction occurs in the combustion chamber, where the large temperature differences and highly exothermic chemical reactions are the main sources of the irreversibility.

Keywords: energy, exergy, wet compression, air-film cooling blade, gas turbine

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Authors: Zainurrasyid Abdullah, Mohamed Fadzlee Sulaiman, Muhammad Fadzlan Zainal, M. Zabri Adil Talib, Aswami Fadillah M. Ariffin

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The Onion Router (Tor) browser is a well-known tool and widely used by people who seeking for web anonymity when browsing the internet. Criminals are taking this advantage to be anonymous over the internet. Accessing the dark web could be the significant reason for the criminal in order for them to perform illegal activities while maintaining their anonymity. For a digital forensic analyst, it is crucial to extract the trail of evidence in proving that the criminal’s computer has used Tor browser to conduct such illegal activities. By applying the digital forensic methodology, several techniques could be performed including application analysis, memory analysis, and registry analysis. Since Windows 10 is the latest operating system released by Microsoft Corporation, this study will use Windows 10 as the operating system platform that running Tor browser. From the analysis, significant artifacts left by Tor browser were discovered such as the execution date, application installation date and browsing history that can be used as an evidence. Although Tor browser was designed to achieved anonymity, there is still some trail of evidence can be found in Windows 10 platform that can be useful for investigation.

Keywords: artifacts analysis, digital forensics, forensic analysis, memory analysis, registry analysis, tor browser, Windows 10

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Authors: Sajeda Elbashabsheh, Kamel Al-Khaled

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This paper applies a modified Laplace Adomian decomposition method to solve the time-fractional JaulentMiodek system. The method produce convergent series solutions with easily compatible components. This paper considers the Caputo fractional derivative. The effectiveness and applicability of the method are demonstrated by comparing its results with those of prior studies. Results are presented in tables and figures. These solutions might be imperative and significant for the explanation of some practical physical phenomena. All computations and figures in the work are done using MATHEMATICA. The numerical results demonstrate that the current methods are effective, reliable, and simple to i implement for nonlinear fractional partial differential equations.

Keywords: approximate solutions, Jaulent-Miodek system, Adomian decomposition method, solitons

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Authors: Laura Mclean

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A recurring point of interest in computational phylogenetic analysis of Indo-European family trees is the inference of a Germano-Italo-Celtic clade in some versions of the trees produced. The presence of this clade in the models is intriguing as there is little evidence for innovations shared among Germanic, Italic, and Celtic, the evidence generally used in the traditional method to construct a subgroup. One source of this unexpected outcome could be the input to the models. The datasets in the various models used so far, for the most part, take as their basis the Swadesh list, a list compiled by Morris Swadesh and then revised several times, containing up to 207 words that he believed were resistant to change among languages. The judgments made by Swadesh for this list, however, were subjective and based on his intuition rather than rigorous analysis. Some scholars used the Swadesh 200 list as the basis for their Indo-European dataset and made cognacy judgements for each of the words on the list. Another dataset is largely based on the Swadesh 207 list as well although the authors include additional lexical and non-lexical data, and they implement ‘split coding’ to deal with cases of polymorphic characters. A different team of scholars uses a different dataset, IECoR, which combines several different lists, one of which is the Swadesh 200 list. In fact, the Swadesh list is used in some form in every study surveyed and each dataset has three words that, when they are coded as cognates, seemingly contribute to the inference of a Germano-Italo-Celtic clade which could happen due to these clades sharing three words among only themselves. These three words are ‘fish’, ‘flower’, and ‘man’ (in the case of ‘man’, one dataset includes Lithuanian in the cognacy coding and removes the word ‘man’ from the screened data). This collection of cognates shared among Germanic, Italic, and Celtic that were deemed important enough to be included on the Swadesh list, without the ability to account for possible reasons for shared cognates that are not shared innovations, gives an impression of affinity between the Germanic, Celtic, and Italic branches without adequate methodological support. However, by changing how cognacy is defined (ie. root cognates, borrowings vs inherited cognates etc.), we will be able to identify whether these three cognates are significant enough to infer a clade for Germanic, Celtic, and Italic. This paper examines the question of what definition of cognacy should be used for phylogenetic datasets by examining the Germano-Italo-Celtic clade as a case study and offers insights into the reconstruction of a Germano-Italo-Celtic clade.

Keywords: historical, computational, Italo-Celtic, Germanic

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Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

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While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

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Authors: Mohamed Elkhouli

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This research sets out to identify some social factors or variables that may need to be controlled in order to decrease the volume of unemployed in Egypt. As well as, it comes to investigate the relationship between a set of social variables and unemployment issue in Egypt in the sake of determining the most important social variables influencing the rise of unemployed during the time series targeted (2002-2012). Highlighting the unemployment issue is becoming an increasingly important topic in all countries throughout the world resulting from expand their globalization efforts. In general, the study tries to determine what the most social priorities are likely to adopt seriously by the Egypt's government in order to solve the unemployed problem. The results showed that the low value for both of small projects and the total value of disbursed social security respectively have significant impact on increasing the No. of unemployed in Egypt, according to the target period by the current study.

Keywords: Egypt, social status, unemployment, unemployed

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Authors: J. R. Wang, H. T. Lin, Y. Chiang, H. C. Chen, C. Shih

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Kuosheng Nuclear Power Plant (NPP) is located on the northern coast of Taiwan. Its nuclear steam supply system is a type of BWR/6 designed and built by General Electric on a twin unit concept. First, the methodology of Kuosheng NPP SPU (Stretch Power Uprate) safety analysis TRACE/SNAP model was developed in this research. Then, in order to estimate the safety of Kuosheng NPP under the more severe condition, the SBO (Station Blackout) + LOCA (Loss-of-Coolant Accident) transient analysis of Kuosheng NPP SPU TRACE/SNAP model was performed. Besides, the animation model of Kuosheng NPP was presented using the animation function of SNAP with TRACE/SNAP analysis results.

Keywords: TRACE, safety analysis, BWR/6, severe accident

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Authors: Athena Nguyen, Rojin Belganeh

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Detecting and identifying differences in like polymer materials are key factors in deformulation, comparative analysis as well as reverse engineering. Pyrolysis-GC/MS is an easy solid sample introduction technique which expands the application areas of gas chromatography and mass spectrometry. The Micro-furnace pyrolyzer is directly interfaced with the GC injector preventing any potential of cold spot, carryover, and cross contamination. This presentation demonstrates the study of two similar polymers by performing different mode of operations in the same system: Evolve gas analysis (EGA), Flash pyrolysis, Thermal desorption analysis, and Heart-cutting analysis. Unknown polymer materials and their chemical compositions are identified.

Keywords: gas chromatography/mass spectrometry, pyrolysis, pyrolyzer, thermal desorption-GC/MS

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Authors: Bernhard Widhalm, Cornelia Rieder-Gradinger, Ewald Srebotnik

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Pine wood (Pinus sylvestris L.) is the basic raw material for the production of Oriented Strand Boards (OSB) and the major source of volatile organic compounds, especially terpenes (like α- and β-pinene). To lower the total emission level of OSB, terpene metabolising microorganisms were therefore applied onto pine wood strands for the production of emission-reduced boards. Suitable microorganisms were identified during preliminary tests under laboratory conditions. At first, their terpene degrading potential was investigated in liquid culture, followed by laboratory tests using unsterile pine wood particles and strands. The main focus was laid on an adoptable terpene reduction in a short incubation time. An optimised bacterial mixture of Pseudomonas putida and Pseudomonas fluorescens showed the best results and was therefore used for further experiments on a larger scale. In an industry-compatible testing procedure, pine wood strands were incubated with the bacterial mixture for a period of 2 to 4 days. Incubation time was stopped by drying the strands. OSB were then manufactured from the pre-treated strands and emissions were measured by means of SPME/GC-MS analysis. Bacterial pre-treatment of strands resulted in a reduction of α-pinene- and β-pinene-emissions from OSB by 40% and 70%, respectively, even after only 2 days of incubation. The results of the investigation provide a basis for the application of microbial treatment within the industrial OSB production line, where shortest possible incubation times are required. For this purpose, the performance of the bacterial mixture will have to be further optimised.

Keywords: GC-MS, OSB, Pseudomonas sp., terpene degradation

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Authors: Poornima Khadanga, Gaurav Pawar, Madhavi Rairikar

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Background: The COVID 19 pandemic, with its unparalleled mental health repercussions, has impacted people globally and has catalyzed a Mental Health pandemic among the youth. The detrimental effects on mental health needs to be pondered at the earliest. Aims: To study the behavioral problems among children and adolescents visiting Psychiatry Outpatient Department Tertiary Health Care during COVID pandemic and its correlation with socio-demographic profiles. Methods: A cross sectional study was conducted by interviewing 120 participants between 4 to 17 years of age and their parents, visiting Psychiatry OPD. Behavioral problems were assessed using the Strength and Difficulties Questionnaire and diagnosed by DSM-5. Statistical analysis was done by SPSS-21. Results: Male participants showed significant association with conduct (t=2.36, p=0.02) and hyperactive problems (t=5.07, p<0.05). Increase in screen time showed a positive correlation with conduct problems (r=0.22. p=0.02). Attention Deficit Hyperkinetic Disorder (18.3%) was the most commonly diagnosed psychiatric illness. Total difficulty score was significantly associated with difficult temperament (F=68.69, p<0.05). Conclusion: The study brings to light the pattern of behavioral problems that emerged during recent times of uncertainties among the young ones, including those with special needs. The increase in disruptive behaviors with increase screen time needs to be addressed at the earliest.

Keywords: behavioral problems, pandemic, screen time, temperament

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Authors: Jana Stepanovska, Roman Matejka, Jozef Rosina, Marta Vandrovcova, Lucie Bacakova

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The aim of this study was to develop a system for mechanical and also electrical stimulation controlling in vitro osteogenesis under conditions more similar to the in vivo bone microenvironment than traditional static cultivation, which would achieve good adhesion, growth and other specific behaviors of osteogenic cells in cultures. An engineered culture system for mechanical stimulation of the mesenchymal stem cells on the charged surface was designed. The bioreactor allows efficient mechanical loading inducing an electrical response and perfusion of the culture chamber with seeded cells. The mesenchymal stem cells were seeded to specific charged materials, like polarized hydroxyapatite (Hap) or other materials with piezoelectric and ferroelectric features, to create electrical potentials for stimulating of the cells. The material of the matrix was TiNb alloy designed for these purposes, and it was covered by BaTiO3 film, like a kind of piezoelectric material. The process of mechanical stimulation inducing electrical response is controlled by measuring electrical potential in the chamber. It was performed a series of experiments, where the cells were seeded, perfused and stimulated up to 48 hours under different conditions, especially pressure and perfusion. The analysis of the proteins expression was done, which demonstrated the effective mechanical and electrical stimulation. The experiments demonstrated effective stimulation of the cells in comparison with the static culture. This work was supported by the Ministry of Health, grant No. 15-29153A and the Grant Agency of the Czech Republic grant No. GA15-01558S.

Keywords: charged surface, dynamic cultivation, electrical stimulation, ferroelectric layers, mechanical stimulation, piezoelectric layers

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Authors: Marzieh Sayyad, Mohsen Salesi

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Metabolic syndrome (MetS), a collection of cardiometabolic risk factors, is linked to the development of cardiovascular disease (CVD) and diabetes. The prevalence of MetS is on the rise with more women affected than men. The goal of this study was to compare the effects of resistance and aerobic exercise training on metabolic syndrome components in non-athlete, middle-aged woman. 51 non-athlete overweight female participated voluntarily in this study. Participants were divided randomly into three groups including resistance, aerobic and control group (number of each group 17). 24 hours before the beginning of training program, the blood sample was taken in fasting state. The two training groups participated in sport activities for eight weeks, three times a week duration 60-90 minutes. Two days following the end of the 8th week, all the measurements were performed similar to the pretest phase. The data was analyzed using one-way analysis of variance. The results showed that aerobic exercise training significantly decreased weight (p=.05), triglyceride (p<0.01) and systolic blood pressure (p<0.02) and HDL-c (p<0.01) was significantly increased. Also in resistance exercise training group TG decreased significantly (p<0.01) and HDL-c (p<0.05) was significantly increased. This study demonstrated that a regular physical activity program improved several metabolic and physiological parameters in healthy, previously sedentary subjects with the metabolic syndrome. In conclusion, it seems that this type of training can be efficient, safe and inexpensive way in order to reduce and prevent metabolic syndrome.

Keywords: aerobic exercise, metabolic syndrome, overweight sedentary female, resistance exercise

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Authors: Franziska Köhler-Dauner, Inka Mayer, Lara Hart, Ute Ziegenhain, Jörg M. Fegert

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Preventive isolation and social distancing strategies during the SARS-CoV-2 pandemic have confronted families with a variety of different restrictions and stresses. Especially during this stressful time, children need a stable parental home to avoid developmental disorders. Additional risk factors such as maternal childhood abuse and neglect (CM) experiences may influence mothers' psychosomatic health (pG) and children's physical well-being (kW) during times of increased stress. Our aim was to analyse the interaction between maternal CM, maternal pG and children's kW during the pandemic. Mothers from a well-documented birth cohort to study transgenerational transmission of CM, were included in an online 'pandemic' survey assessing maternal pG and children's physical health during the pandemic. Our mediation analysis showed a significant positive association between the extent of maternal CM experiences, mothers' psychosomatic symptoms and their children's kW. Maternal psychosomatic symptoms significantly mediate the interaction between CM and children's kW; the direct effect remains non-significant when maternal psychosomatic symptoms are included as mediators. Maternal CM appears to be a relevant risk factor for maternal pG and children's kW during the pandemic. Maternal CM experiences seem to influence the way parents cope with stressful situations and increase the risk of suffering from depressive symptoms. The latter also affect their children's kW. Our findings underline the importance of carefully assessing the specific situation of families with children and offering individually adapted help to help families survive the pandemic.

Keywords: pandemic, maternal health, child health, abuse, neglect, maternal experiences

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Authors: Jose Luis Solleiro, Rosario Castanon, Laura Elena Martinez

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The State of Mexico is an administrative entity of Mexico, and it is one of the most important territories due to its great economic and social impact for the whole country, especially since it contributes with more than eight of the national Gross Domestic Product (GDP). The State of Mexico has a population of over seventeen million people and host very important business and productive industries such as Automotive, Chemicals, Pharmaceutical, and Agri-food. In 2017, the State Development Plan (Plan Estatal de Desarrollo in Spanish) which is a policy document that rules State's economic actions and integrates the bases for sectoral and regional programs to achieve regional development), raised innovation as a key aspect to boost competitiveness and productivity of the State of Mexico. Therefore, in line with this proposal, in 2018 the Mexican Council for Science and Technology (COMECYT for its acronym in Spanish), an institution in charge of promoting public science and technology policies in the State of Mexico, took actions towards building up the State´s Innovation System. Hence, the main objective of this paper is to review and analyze the process to create RIS in the State of Mexico. We focus on the key elements of the process, the diverse actors that were involved in it, the activities that were carried out and the identification of the challenges, findings, successes, and failures of the intended exercise. The methodology used to analyze the structure of the Innovation System of the State of Mexico is based on two elements: the case study and the research-action approach. The main objective of the paper, the case study was based on semi-structured interviews with key actors who have participated in the process of launching the RIS of the State of Mexico. Additionally, we analyzed the information reports and other documents that were elaborated during the process of shaping the State's innovation system. Finally, the results obtained in the process were also examined. The relevance of this investigation fundamentally rests in two elements: 1) keeping documental record of the process of building a RIS in Mexico; and 2) carrying out the analysis of this case study recognizing the importance of knowledge extraction and dissemination, so that lessons on this matter may be useful for similar experiences in the future. We conclude that in Mexico, documentation and analysis efforts related to the formation of RIS and interaction processes between innovation ecosystem actors are scarce, so documents like are of great importance, especially since it generates a series of findings and recommendations for the building of RIS.

Keywords: regional innovation systems, innovation, development, competitiveness

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Authors: O. B. Urhibo, D. Imhonopi, T. George

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The global rate of decline in entrepreneurial activities, and the prevalence in Africa, especially Nigeria, is more worrisome. In recent times, these problems, such as the lack of accessibility and utilization of financial incentives needed to promote entrepreneurial activities, have led to a decrease in entrepreneurial activities. The causes of the decline have been evaluated from a different perspective and have further confirmed the relevance and need for the sustainability of the Fashion industry. With the increasing rate of unemployment and poverty in Nigeria and the literature gap in the social context, this study investigated the patterns of sustainable financial incentives utilisation among fashion design entrepreneurs in Nigeria through a qualitative approach. The Eastern part of Nigeria was considered in this study because of the high rate of market activity for textile and clothing firms. Specifically, Delta state was considered in this study. A purposive sampling technique was used to select key informants consisting of twelve (12) executives of the associations (i.e., Fashion Designer & Exhibitors Association, Delta Fashion Designers, and Fashion Designers Association of Nigeria for the interview sessions. Four themes emanate from the thematic analysis -lack of sufficient collateral, difficulties and duration of loan application processes, unacceptable business proposal/plan, and the absence of audited financial accounts were found to be the patterns of sustainable financial incentives utilisation among fashion design entrepreneurs in Nigeria. The promotion of sustainable patterns and supports has been suggested to reduce the challenges of sustainable financial incentives utilisation among fashion design entrepreneurs.

Keywords: entrepreneurship, fashion design, financial incentives, patterns, sustainability, utilisation

Procedia PDF Downloads 75