Search results for: food analysis.

Authors: Farzaneh Khorram

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This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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Authors: Manjiri A. More, Manisha M. Bhosale

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Agriculture is the backbone of Indian economy and India is one of the world’s largest producers of Rice. Today, paddy crop is facing a severe problem of insect pests and is attacked by more than 100 species of insects, among those 20 species cause economic damage. Rice is the staple food of people of panhala tehasil, Kolhapur, Maharashtra, India. During June 2017 to September 2017 efforts were made to study the diversity of insect pests associated with the paddy crop in the study region. The collection and preservation of the specimens were done by following standard procedure and the identification was done with the help standard literature, taxonomic keys, and webography. In all, 6 species were recorded as pests of paddy in which order Lepidoptera was dominant with 2 species, while orders Diptera, Orthoptera, Hemiptera, and Coleoptera were represented by 1 species each respectively. The results of the present investigation will be helpful for formulating control strategies against these paddy pests.

Keywords: diversity, insect pests, Panhala, staple

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Authors: Halit Tutar, Omer Eren, Oguz Parlakay

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The demand for food and energy of mankind has been increasing every passing day. Renewable energy sources have been pushed to forefront since fossil fuels will be run out in the near future and their negative effects to the environment. As in every sector, the transport sector benefits from biofuel (biogas, bioethanol and biodiesel) one of the renewable energy sources as well. The edible oil crops are used in production of biodiesel. Utilizing edible oil crops as renewable energy source may raise a debate in the view of that there is a shortage in raw material of edible oil crops in Turkey. Researches related to utilization of non-edible oil crops as biodiesel raw materials have been recently increased, and especially studies related to their vegetative production and adaptation have been accelerated in Europe. In this review edible oil crops are compared to non-edible oil crops for biodiesel production in the sense of biodiesel production, some features of non-edible oil crops and their harmful emissions to environment are introduced. The data used in this study, obtained from articles, thesis, reports relevant to edible and non edible oil crops in biodiesel.

Keywords: biodiesel, edible oil crops, environmental impacts, renewable energy

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Authors: T. O. Ajewole, K. S. Olorunmiaye, D. A. Animasaun, M. Okpeku

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Drought impact on the production of food crops for the benefit of mankind cannot be overemphasized. This study shows the different kind of genes expressed at various level of drought regimes on Basella alba and rubra using a real-time PCR machine. The planting was done in the screen house while the gene expression study was carried out in the laboratory. Sandy-loamy soil was collected and four levels of drought regime was used as treatment and a control experiment was set up for the two vegetables. Drought interval of 5, 10, 15 and 20 days were used as treatments while a control experiment which was not starved of water at any point was also set up, five replicates were set up for each treatment. Stress was introduced at 12 Weeks after planting (WAP). From the result of this study, Basella alba shows the highest amplicon size of 34.6 and 52.32 for GmPCS5 and HVA1 respectively which by implication means these genes were expressed the more as the stress period interval increases.

Keywords: water stress, basella alba, basella rubra, HVA1

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Authors: Haftay Abraha Tadesse

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Background: Staphylococcus is a genus of worldwide distributed bacteria correlated to several infectious of different sites in humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. Objective: The objective of this study was to determine the isolates, antimicrobial susceptibility patterns and Public Health Significance of Staphylococcus aureus in raw meat from butchery and abattoir houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from April to October 2019. Socio-demographic data and Public Health Significance were collected using a predesigned questionnaire. The raw meat samples were collected aseptically in the butchery and abattoir houses and transported using an ice box to Mekelle University, College of Veterinary Sciences, for isolating and identification of Staphylococcus aureus. Antimicrobial susceptibility tests were determined by the disc diffusion method. Data obtained were cleaned and entered into STATA 22.0 and a logistic regression model with odds ratio was calculated to assess the association of risk factors with bacterial contamination. A P-value < 0.05 was considered statistically significant. Results: In the present study, 88 out of 250 (35.2%) were found to be contaminated with Staphylococcus aureus. Among the raw meat specimens, the positivity rate of Staphylococcus aureus was 37.6% (n=47) and (32.8% (n=41), butchery and abattoir houses, respectively. Among the associated risks, factories not using gloves reduces risk was found to (AOR=0.222; 95% CI: 0.104-0.473), Strict Separation b/n clean & dirty (AOR= 1.37; 95% CI: 0.66-2.86) and poor habit of hand washing (AOR=1.08; 95%CI: 0.35 3.35) was found to be statistically significant and have associated with Staphylococcus aureus contamination. All isolates of thirty-seven of Staphylococcus aureus were checked and displayed (100%) sensitive to doxycycline, trimethoprim, gentamicin, sulphamethoxazole, amikacin, CN, Co trimoxazole and nitrofurantoi. Whereas the showed resistance to cefotaxime (100%), ampicillin (87.5%), Penicillin (75%), B (75%), and nalidixic acid (50%) from butchery houses. On the other hand, all isolates of Staphylococcus aureus isolate 100% (n= 10) showed sensitive chloramphenicol, gentamicin and nitrofurantoin, whereas they showed 100% resistance of Penicillin, B, AMX, ceftriaxone, ampicillin and cefotaxime from abattoirs houses. The overall multi-drug resistance pattern for Staphylococcus aureus was 90% and 100% of butchery and abattoir houses, respectively. Conclusion: 35.3% Staphylococcus aureus isolated were recovered from the raw meat samples collected from the butchery and abattoirs houses. More has to be done in the development of hand washing behavior and availability of safe water in the butchery houses to reduce the burden of bacterial contamination. The results of the present finding highlight the need to implement protective measures against the levels of food contamination and alternative drug options. The development of antimicrobial resistance is nearly always a result of repeated therapeutic and/or indiscriminate use of them. Regular antimicrobial sensitivity testing helps to select effective antibiotics and to reduce the problems of drug resistance development towards commonly used antibiotics.

Keywords: abattoir house, AMR, butchery house, S. aureus

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Authors: S. W. Liu, J. H. Lv, W. Z. Wang

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In recent years, the failure accidents in petrochemical industry have been frequent, and have posed great security problems in personnel and property. The improvement of petrochemical safety is highly requested in order to prevent re-occurrence of severe accident. This study focuses on surveying the failure cases occurred in petrochemical field, which were extracted from journals of engineering failure, including engineering failure analysis and case studies in engineering failure analysis. The relation of failure mode, failure mechanism, type of components, and type of materials was analyzed in this study. And the analytical results showed that failures occurred more frequently in vessels and piping among the petrochemical equipment. Moreover, equipment made of carbon steel and stainless steel accounts for the majority of failures compared to other materials. This may be related to the application of the equipment and the performance of the material. In addition, corrosion failures were the largest in number of occurrence in the failure of petrochemical equipment, in which stress corrosion cracking accounts for a large proportion. This may have a lot to do with the service environment of the petrochemical equipment. Therefore, it can be concluded that the corrosion prevention of petrochemical equipment is particularly important.

Keywords: cases analysis, corrosion, failure, petrochemical industry

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Authors: Weeam Abdulrahman, Gawaher Al-Madwary, Fatima Al-Ammari, Razan Mohammad

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This research discusses the AI features in Replika which is a dialog with a customized characters application, interaction and communication with AI in different ways that is provided for the user. spreading a survey with questions on how the AI worked is one approach of exposing the app to others to utilize and also we made an analysis that provides us with the conclusion of our research as a result, individuals will be able to try out the app. In the methodology we explain each page that pops up in the screen while using replika and Specify each part and icon.

Keywords: Replika, AI, artificial intelligence, dialog app

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Authors: Abdollah Ghasempour, Mohammad Reza Kavianpour, Majid Galoie

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This study has investigated the fundamental parameters which have effective role on energy dissipation of nappe flows on stepped chutes in order to estimate an empirical relationship using dimensional analysis. To gain this goal, comprehensive experimental study on some large-scale physical models with various step geometries, slopes, discharges, etc. were carried out. For all models, hydraulic parameters such as velocity, pressure, water depth, flow regime and etc. were measured precisely. The effective parameters, then, could be determined by analysis of experimental data. Finally, a dimensional analysis was done in order to estimate an empirical relationship for evaluation of energy dissipation of nappe flows on stepped chutes. Because of using the large-scale physical models in this study, the empirical relationship is in very good agreement with the experimental results.

Keywords: nappe flow, energy dissipation, stepped chute, dimensional analysis

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Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

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In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

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Authors: Da-Ming Huang, Ya-Ting Tsai, Shyh-Hau Wang

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Ultrasound signals backscattered from the soft tissues are mainly depending on the size, density, distribution, and other elastic properties of scatterers in the interrogated sample volume. The quantitative analysis of ultrasonic backscattering is frequently implemented using the statistical approach due to that of backscattering signals tends to be with the nature of the random variable. Thus, the statistical analysis, such as Nakagami statistics, has been applied to characterize the density and distribution of scatterers of a sample. Yet, the accuracy of statistical analysis could be readily affected by the receiving signals associated with the nature of incident ultrasound wave and acoustical properties of samples. Thus, in the present study, efforts were made to explore such effects as the ultrasound operational modes and attenuation of biological tissue on the estimation of corresponding Nakagami statistical parameter (m parameter). In vitro measurements were performed from healthy and pathological fibrosis porcine livers using different single-element ultrasound transducers and duty cycles of incident tone burst ranging respectively from 3.5 to 7.5 MHz and 10 to 50%. Results demonstrated that the estimated m parameter tends to be sensitively affected by the use of ultrasound operational modes as well as the tissue attenuation. The healthy and pathological tissues may be characterized quantitatively by m parameter under fixed measurement conditions and proper calibration.

Keywords: ultrasound backscattering, statistical analysis, operational mode, attenuation

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Authors: Kun-Peng Jin, Jin Liang, Ti-Jun Xiao

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In this work, we are concerned with the dynamic behaviors of solutions to some coupled systems with infinite memory, which consist of two partial differential equations where only one partial differential equation has damping. Such coupled systems are good mathematical models to describe the deformation and stress characteristics of some viscoelastic materials affected by temperature change, external forces, and other factors. By using the theory of operator semigroups, we give wellposedness results for the Cauchy problem for these coupled systems. Then, with the help of some auxiliary functions and lemmas, which are specially designed for overcoming difficulties in the proof, we show that the solutions of the coupled systems decay to zero in a strong way under a few basic conditions. The results in this dynamic analysis of coupled systems are generalizations of many existing results.

Keywords: dynamic analysis, coupled system, infinite memory, damping.

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Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Sevilay Çankaya

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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

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Authors: Montri Meenium

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The purpose of this research was to examine youths’ analysis and evaluation of three protagonists, one female and two males involved in sexual relationship in the stage play “Kaki” held by the Faculty of Liberal Arts, Prince of Songkla University. The interviews were conducted with 10 youths in the production team and 10 audience youths, totalling 20. The findings, which were presented in the form of a descriptive analysis, showed that all the 10 youths in the production team and the 10 audience youths did not accept the behaviour of the protagonists: the female who committed adultery and the males who were corrupted by power, had sexual relationship with a married woman and deceived people. The youths, however, knew that such behaviour resulted from being overpowered by human passion, especially infatuation, which was in accordance with the theme of the play. It was suggested that the story twines ideology or points of view that defy moral and ethics, prompting questions to be asked. Hence, the stage play can be used as an instrument to develop critical thinking in youths.

Keywords: descriptive analysis, protagonists, youths, stage-play

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: Bilal Ashraf, Qianxiao Zhang

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This study empirically investigated the linkage amid financial development and its important determinants such as information and communication technology, natural resource rents, economic growth, current account balance, and gross savings in 107 economies. This paper preferred to employ the second-generation unit root tests to handle the issues of slope heterogeneity and “cross-sectional dependence” in panel data. The “Kao, Pedroni, and Westerlund tests” confirm the long-lasting connections among the variables under study, while the significant endings of “cross-sectionally augmented autoregressive distributed lag (CS-ARDL)” exposed that NRR, CAB, and S negatively affected the financial development while ICT and EG stimulates the procedure of FD. Further, the robustness analysis's application of FGLS supports the appropriateness and applicability of CS-ARDL. Finally, the findings of “DH causality analysis” endorse the bidirectional causality linkages amongst research factors. Based on the study's outcomes, we suggest some policy suggestions that empower the process of financial development, globally.

Keywords: determinants of financial developments, CS-ARDL, financial development, global sample, causality analysis

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Authors: Lim Yi Wei

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Structural equation modelling (SEM) is well-known in statistics due to its flexibility and accessibility. It plays an increasingly important role in the development of the education field. The number of research publications using SEM in education has increased in recent decades. However, there is a lack of scientific review conducted on SEM in education. The purpose of this study is to investigate research trends related to SEM in education. The researcher will use Vosviewer, Datawrapper, and SciMAT to do bibliometric analysis on 5549 papers that have been published in the Scopus database in the last five years. The result will show the publication trends of the most cited documents, the top contributing authors, countries, institutions, and journals in the research field. It will also look at how they relate to each other in terms of co-citation, collaboration, and co-occurrence of keywords. This study will benefit researchers and practitioners by identifying research trends and the current state of SEM in education.

Keywords: structural equation modeling, education, bibliometric analysis, Vosviewer

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Authors: Eric Mxolisi Mkhondo

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Geometrical deviations and interaction of mechanical parts influences the performance of miniature systems.These deviations tend to cause costly problems during assembly due to imperfections of components, which are invisible to a naked eye.They also tend to cause unsatisfactory performance during operation due to deformation cause by environmental conditions.One of the effective tools to manage the deviations and interaction of parts in the system is tolerance analysis.This is a quantitative tool for predicting the tolerance variations which are defined during the design process.Traditional tolerance analysis assumes that the assembly is static and the deviations come from the manufacturing discrepancies, overlooking the functionality of the whole system and deformation of parts due to effect of environmental conditions. This paper presents an integrated tolerance analysis approach for miniature system in operation.In this approach, a computer-aided design (CAD) model is developed from system’s specification.The CAD model is then used to specify the geometrical and dimensional tolerance limits (upper and lower limits) that vary component’s geometries and sizes while conforming to functional requirements.Worst-case tolerances are analyzed to determine the influenced of dimensional changes due to effects of operating temperatures.The method is used to evaluate the nominal conditions, and worse case conditions in maximum and minimum dimensions of assembled components.These three conditions will be evaluated under specific operating temperatures (-40°C,-18°C, 4°C, 26°C, 48°C, and 70°C). A case study on the mechanism of a zoom lens system is used to illustrate the effectiveness of the methodology.

Keywords: geometric dimensioning, tolerance analysis, worst-case analysis, zoom lens mechanism

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Authors: Nishaben Dholakiya, Anirban Roy, Ranjan Dey

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The unprecedented rise in global temperatures has triggered complex changes in marine ecosystems, necessitating a deeper understanding of seawater's thermophysical properties by experimentally measuring ultrasonic velocity and density at varying temperatures and salinity. This study investigates the critical relationship between temperature variations and molecular-level interactions in Arabian Sea surface waters, specifically focusing on internal pressure (π) and cohesion energy density (CED) as key indicators of ecosystem disruption. Our experimental findings reveal that elevated temperatures significantly reduce internal pressure, weakening the intermolecular forces that maintain seawater's structural integrity. This reduction in π correlates directly with decreased habitat stability for marine organisms, particularly affecting pressure-sensitive species and their physiological processes. Similarly, the observed decline in cohesion energy density at higher temperatures indicates a fundamental shift in water molecule organization, impacting the dissolution and distribution of vital nutrients and gases. These molecular-level changes cascade through the ecosystem, affecting everything from planktonic organisms to complex food webs. By employing advanced machine learning techniques, including Stacked Ensemble Machine Learning (SEML) and AdaBoost (AB), we developed highly accurate predictive models (>99% accuracy) for these thermophysical parameters. The results provide crucial insights into the mechanistic relationship between climate warming and marine ecosystem degradation, offering valuable data for environmental policymaking and conservation strategies. The novelty of this research serves as no such thermodynamic investigation has been conducted before in literature, whereas this research establishes a quantitative framework for understanding how molecular-level changes in seawater properties directly influence marine ecosystem stability, emphasizing the urgent need for climate change mitigation efforts.

Keywords: thermophysical properties, Arabian Sea, internal pressure, cohesion energy density, machine learning

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Bo Hyun Kim, Sarng Woo Karng

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In constructing a hydrogen refueling station, minimizing the volume and reducing the number of banks enable lessening the construction cost. This study aims at performing the dynamic simulation on 250 kg/day of a refueling station for light-duty vehicles. The primary compressor boosts hydrogen from a tube trailer of 250 to 480 bar and stores it in a medium-pressure bank. Then, additional compression of hydrogen from 480 to 900 bar is carried out and stored in a high-pressure bank. Economic analysis was conducted considering the amount of electricity consumed by compression corresponding to the volume and the number of banks (cascade system) in charging mode. NIST REFPROP was selected as the equation of state on the ASPEN HYSYS for thermodynamic analysis of the tube-trailer, the compressors, the chillers, and the banks. Compared to a single high-pressure bank system of 3000 L, the volume of the cascade high-pressure banks (bank1: 250 L and bank 2: 1850 L) was reduced by 30%, and the power consumption of the chiller for precooling was also decreased by 16%.

Keywords: light-duty vehicles, economic analysis, cascade system, hydrogen refueling station

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Authors: Muhammad Luqman, Yusuf Kurniawan

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S-Boxes is one of the linear parts of the cryptographic algorithm. The existence of S-Box in the cryptographic algorithm is needed to maintain non-linearity of the algorithm. Nowadays, modern cryptographic algorithms use an S-Box as a part of algorithm process. Despite the fact that several cryptographic algorithms today reuse theoretically secure and carefully constructed S-Boxes, there is an evaluation characteristic that can measure security properties of S-Boxes and hence the corresponding primitives. Analysis of an S-Box usually is done using manual mathematics calculation. Several S-Boxes are presented as a Truth Table without any mathematical background algorithm. Then, it’s rather difficult to determine the strength of Truth Table S-Box without a mathematical algorithm. A comprehensive analysis should be applied to the Truth Table S-Box to determine the characteristic. Several important characteristics should be owned by the S-Boxes, they are Nonlinearity, Balancedness, Algebraic degree, LAT, DAT, differential delta uniformity, correlation immunity and global avalanche criterion. Then, a comprehensive tool will be present to automatically calculate the characteristics of S-Boxes and determine the strength of S-Box. Comprehensive analysis is done on a deterministic process to produce a sequence of S-Boxes characteristic and give advice for a better S-Box construction.

Keywords: cryptographic properties, Truth Table S-Boxes, S-Boxes characteristic, deterministic process

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Authors: Lazhar Belkhiri, Ammar Tiri, Lotfi Mouni

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Water resources present to the public order of the world a very important problem for the protection and management of water quality given the complexity of water quality data sets. In this study, the water quality index (WQI) and irrigation water quality index (IWQI) were calculated in order to evaluate the surface water quality for drinking and irrigation purposes based on nine hydrochemical parameters. In order to separate the variables that are the most responsible for the spatial differentiation, the discriminant analysis (DA) was applied. The results show that the surface water quality for drinking is poor quality and very poor quality based on WQI values, however, the values of IWQI reflect that this water is acceptable for irrigation with a restriction for sensitive plants. Consequently, the discriminant analysis DA method has shown that the following parameters pH, potassium, chloride, sulfate, and bicarbonate are significant discrimination between the different stations with the spatial variation of the surface water quality, therefore, the results obtained in this study provide very useful information to decision-makers

Keywords: surface water quality, drinking and irrigation purposes, water quality index, discriminant analysis

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Authors: Y. H. Tshela Ntumba, A. Przepiórkowska, M. Prochoń

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Polymeric materials have become an integral part of every aspect of today's industry. They have wide applications, inter alia, in areas such as medicine, food industry and agriculture. In agriculture, for example, they are used for the production of pots, irrigation systems and for soil mulching. The aim of this study was the attempt to produce a biodecomposable agricultural mat, by coating cotton fabric with a blend of carboxylated styrene-butadiene latex (LBSK) containing the enzymatic hydrolyzate of keratin from cattle hair, which would serve as a material for mulching. The production of such material allows the beneficial management of burdensome tannery waste constituted by keratin from cattle hair and at the same time, the production of agricultural mats that much faster undergo decomposition than commonly used polyethylene mats.

Keywords: agricultural mat, biodecomposition, biodegradation, carboxylated butadiene-styrene latex, cellulosic-elastomeric material, keratin hydrolyzate, mulching, protein hydrolyzate

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Authors: Jihye Jeon

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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

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Authors: Ruichong Zhang

Abstract:

This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time-frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses.

Keywords: site nonlinearity, site amplification, site damping, Hilbert-Huang Transform (HHT), liquefaction, 2001 Nisqually Earthquake

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Authors: Suman Bala, Sunil Kamboj, Vipin Saini

Abstract:

Quantitative Structure Activity Relationship (QSAR) analysis has been developed to relate antifungal activity of novel substituted 1,3,4-oxadiazole against Candida albicans and Aspergillus niger using computer assisted multiple regression analysis. The study has shown the better relationship between antifungal activities with respect to various descriptors established by multiple regression analysis. The analysis has shown statistically significant correlation with R² values 0.932 and 0.782 against Candida albicans and Aspergillus niger respectively. These derivatives were further subjected to molecular docking studies to investigate the interactions between the target compounds and amino acid residues present in the active site of glucosamine-6-phosphate synthase. All the synthesized compounds have better docking score as compared to standard fluconazole. Our results could be used for the further design as well as development of optimal and potential antifungal agents.

Keywords: 1, 3, 4-oxadiazole, QSAR, multiple linear regression, docking, glucosamine-6-phosphate synthase

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Authors: Minseo Jo

Abstract:

The purpose of this paper is to examine the factors in the hedonic price models, that has significance impact in determining the price of apartments. There are many variables employed in the hedonic price models and their effectiveness vary differently according to the researchers and the regions they are analysing. In order to consider various conditions, the meta-regression analysis has been selected for the study. In this paper, four meta-independent variables, from the 65 hedonic price models to analysis. The factors that influence the prices of apartments, as well as including factors that influence the prices of apartments, regions, which are divided into two of the research performed, years of research performed, the coefficients of the functions employed. The covariance between the four meta-variables and p-value of the coefficients and the four meta-variables and number of data used in the 65 hedonic price models have been analyzed in this study. The six factors that are most important in deciding the prices of apartments are positioning of apartments, the noise of the apartments, points of the compass and views from the apartments, proximity to the public transportations, companies that have constructed the apartments, social environments (such as schools etc.).

Keywords: hedonic price model, housing price, meta-regression analysis, characteristics

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Authors: Beyza Sukran Isik, Gokce Altin, Ipek Yalcinkaya, Evren Demircan, Asli Can Karaca, Beraat Ozcelik

Abstract:

Turmeric (Curcuma longa L.), is used as a food additive (spice), preservative and coloring agent in Asian countries, including China and South East Asia. It is also considered as a medicinal plant. Traditional Indian medicine evaluates turmeric powder for the treatment of biliary disorders, rheumatism, and sinusitis. It has rich polyphenol content. Turmeric has yellow color mainly because of the presence of three major pigments; curcumin 1,7-bis(4-hydroxy-3-methoxyphenyl)-1, 6-heptadiene-3,5-dione), demethoxy-curcumin and bis demothoxy-curcumin. These curcuminoids are recognized to have high antioxidant activities. Curcumin is the major constituent of Curcuma species. Method: To prepare turmeric tea, 0.5 gram of turmeric powder was brewed with 250 ml of water at 90°C, 10 minutes. 500 grams of fresh turmeric washed and shelled prior to squeezing. Both turmeric tea and turmeric juice pass through 45 lm filters and stored at -20°C in the dark for further analyses. Curcumin was extracted from 20 grams of turmeric powder by 70 ml ethanol solution (95:5 ethanol/water v/v) in a water bath at 80°C, 6 hours. Extraction was contributed for 2 hours at the end of 6 hours by addition of 30 ml ethanol. Ethanol was removed by rotary evaporator. Remained extract stored at -20°C in the dark. Total phenolic content and phenolic profile were determined by spectrophotometric analysis and ultra-fast liquid chromatography (UFLC), respectively. Results: The total phenolic content of ethanolic extract of turmeric, turmeric juice, and turmeric tea were determined 50.72, 31.76 and 29.68 ppt, respectively. The ethanolic extract of turmeric, turmeric juice, and turmeric tea have been injected into UFLC and analyzed for curcumin contents. The curcumin content in ethanolic extract of turmeric, turmeric juice, and turmeric tea were 4067.4, 156.7 ppm and 1.1 ppm, respectively. Significance: Turmeric is known as a good source of curcumin. According to the results, it can be stated that its tea is not sufficient way for curcumin consumption. Turmeric juice can be preferred to turmeric tea for higher curcumin content. Ethanolic extract of turmeric showed the highest content of turmeric in both spectrophotometric and chromatographic analyses. Nonpolar solvents and carriers which have polar binding sites have to be considered for curcumin consumption due to its nonpolar nature.

Keywords: phenolic compounds, spectrophotometry, turmeric, UFLC

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