Search results for: linear code

Authors: Seyed Abolhasan Naeini, Elham Ghanbari Alamooti

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Static stability of soil slopes using numerical simulation by a finite element code, ABAQUS, has been investigated, and safety factors of the slopes achieved in the case of static load of a 10-storey building. The embankments have the same soil condition but different loading distance from the slope heel. The numerical method for estimating safety factors is 'Strength Reduction Method' (SRM). Mohr-Coulomb criterion used in the numerical simulations. Two steps used for measuring the safety factors of the slopes: first is under gravity loading, and the second is under static loading of a building near the slope heel. These safety factors measured from SRM, are compared with the values from Limit Equilibrium Method, LEM. Results show that there is good agreement between SRM and LEM. Also, it is seen that by increasing the distance from slope heel, safety factors increases.

Keywords: limit equilibrium method, static stability, soil slopes, strength reduction method

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Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

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India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Ishrar Tabassum, Jay Andrew Saptok, Khalid Raihan Kabir, Elmee Tabassum

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The purpose of this study is to bring light to the current state of the working environments in the corporate environment and other such institutions with a particular focus on the Bangladesh National Building Code (BNBC) and its guidelines for accommodating the physically disabled. Data were collected via semi-formal interviews, site visits and focus groups conducted using a preset questionnaire as the guidelines. After conducting surveys at corporate offices of 20 organizations from major commercial sectors in Dhaka city, the auditing showed many inadequacies, as aside from the larger corporate offices, the offices have little to no accessibility for the physically disabled. This study hopes to shed light on the fact that the existing BNBCs lack of emphasis on ensuring the accessibility of the handicapped in corporate buildings in the hope that, in the future, the physically disabled will have greater opportunities at being productive members of the workforce.

Keywords: person with disability, PWD, corporate buildings, Dhaka City

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Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Tondani Mudau, Sherine B. Van Wyk, Zuhayr Kafaar, Janan Dietrich

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Female adolescents residing in a patriarchal society such as South Africa are more inclined to embrace feminine ideologies. Internalizing these ideologies may expose female adolescents to mental health challenges such as depression and anxiety. This study explored whether the internalisation of adolescent femininity ideologies namely, objectified relationship with own body (ORB) and inauthentic self in relationships (ISR) predicted anxiety and depression in late female adolescents at Stellenbosch University. The sample of the study consisted of 1451 (18-24) female undergraduate and postgraduate students enrolled at Stellenbosch University. The mean age of the participants was 20 (SD=1.46), and most participants (39.7%) were first-year students. The study employed a cross-sectional quantitative research design. Data was collected through an online self-completion survey, the survey consisted of three sections, the first section asked biographical questions regarding age, gender, race and family background. The second section measured the internalisation of feminine ideologies by using the adolescent femininity ideology scale which has two subscales namely inauthentic self in relationship with others (ISR) and objectified relationship with one’s own body (ORB). The ISR scale had the Cronbach Alpha of 0.76, and the ORB scale had the Cronbach Alpha of 0.83. The third section measured mental health (depression and anxiety) by using the Hopkins Symptoms 25-checklist which had the Cronbach Alpha of 0.93. Data were analysed through multiple linear regression from IBM SPSS (Statistical Package for the Social Sciences Version 24). The overall results of the multiple linear regression showed that The AFIS combination accounted for 14% for anxiety as measured by the Hopkins Symptoms Checklist R² = .142, F (2, 682) = 56.431, p < .001. The combination also accounted for 24% for depression as measured by the Hopkins Symptoms Checklist R² = .239, F (2, 682) = 106.971, p < .0. The findings in this study affirm the objectification and feminist theory contentions that internalising femininity ideologies (ISR and ORB) predict negative mental health in female adolescents.

Keywords: adolescents, anxiety, depression, feminine ideologies, inauthentic self, mental health, self-objectification, South Africa

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Authors: Mohammed Husein Mohammad Rashid

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For a bounded linear operator T acting on a complex infinite dimensional Hilbert space ℋ, we say that T is ∗-class A operator (abbreviation T∈A*) if |T²|≥ |T*|². In this article, we prove the following assertions:(i) we establish some conditions which imply the normality of ∗-class A; (ii) we consider ∗-class A operator T ∈ ℬ(ℋ) with reducing kernel such that TX = XS for some X ∈ ℬ(K, ℋ) and prove the Fuglede-Putnam type theorem when adjoint of S ∈ ℬ(K) is dominant operators; (iii) furthermore, we extend the asymmetric Putnam-Fuglede theorem the class of ∗-class A operators.

Keywords: fuglede-putnam theorem, normal operators, ∗-class a operators, dominant operators

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Authors: Prateek Singh, Dilshad Ahmad

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Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.

Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish

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Authors: Akram Sadat Jafari Roodbandi, Farzaneh Akbari, Vafa Feyzi, Zahra Zare, Zohreh Foroozanfar

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Introduction: Circadian rhythm or sleep-awake cycle in 24 hours is one of the important factors affecting the physiological and psychological characteristics in humans that contribute to biochemical, physiological and behavioral processes and helps people to set up brain and body for sleep or active awakening during certain hours. The purpose of this study was to investigate the relationship between the characteristics of circadian rhythms on the sleep quality and sleepiness according to their demographic characteristics such as age. Methods: This cross-sectional descriptive-analytic study was carried out among the general population of Kerman, aged 15-84 years. After dividing the age groups into 10-year demographic characteristics questionnaire, the type of circadian questionnaire, Pittsburgh sleep quality questionnaire and Euporth sleepiness questionnaire were completed in equal numbers between men and women of that age group. Using cluster sampling with effect design equal 2, 1300 questionnaires were distributed during the various hours of 24 hours in public places in Kerman city. Data analysis was done using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: In this study, 1147 subjects were included in the study, 584 (50.9%) were male and the rest were women. The mean age was 39.50 ± 15.38. 133 (11.60%) subjects from the study participants had sleepiness and 308 (26.90%) subjects had undesirable sleep quality. Using linear regression test, sleep quality was the significant correlation with sex, hours needed for sleep at 24 hours, chronic illness, sleepiness, and circadian rhythm amplitude. Sleepiness was the meaningful relationship with marital status, sleep-wake schedule of other family members and the stability of circadian rhythm. Both women and men, with age, decrease the quality of sleep and increase the rate of sleepiness. Conclusion: Age, sex, and type of circadian people, the need for sleep at 24 hours, marital status, sleep-wake schedule of other family members are significant factors related to the sleep quality and sleepiness and their adaptation to night shift work.

Keywords: circadian type, sleep quality, sleepiness, age, shift work

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Authors: Rezvan Ravanfar Haghighi, V. C. Vani, Suresh Perumal, Sabyasachi Chatterjee, Pratik Kumar

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X-ray attenuation coefficient [µ(E)] of any substance, for energy (E), is a sum of the contributions from the Compton scattering [ μCom(E)] and photoelectric effect [µPh(E)]. In terms of the, electron density (ρe) and the effective atomic number (Zeff) we have µCom(E) is proportional to [(ρe)fKN(E)] while µPh(E) is proportional to [(ρeZeffx)/Ey] with fKN(E) being the Klein-Nishina formula, with x and y being the exponents for photoelectric effect. By taking the sample's HU at two different excitation voltages (V=V1, V2) of the CT machine, we can solve for X=ρe, Y=ρeZeffx from these two independent equations, as is attempted in DECT inversion. Since µCom(E) and µPh(E) are both energy dependent, the coefficients of inversion are also dependent on (a) the source spectrum S(E,V) and (b) the detector efficiency D(E) of the CT machine. In the present paper we tabulate these coefficients of inversion for different practical manifestations of S(E,V) and D(E). The HU(V) values from the CT follow: <µ(V)>=<µw(V)>[1+HU(V)/1000] where the subscript 'w' refers to water and the averaging process <….> accounts for the source spectrum S(E,V) and the detector efficiency D(E). Linearity of μ(E) with respect to X and Y implies that (a) <µ(V)> is a linear combination of X and Y and (b) for inversion, X and Y can be written as linear combinations of two independent observations <µ(V1)>, <µ(V2)> with V1≠V2. These coefficients of inversion would naturally depend upon S(E, V) and D(E). We numerically investigate this dependence for some practical cases, by taking V = 100 , 140 kVp, as are used for cardiological investigations. The S(E,V) are generated by using the Boone-Seibert source spectrum, being superposed on aluminium filters of different thickness lAl with 7mm≤lAl≤12mm and the D(E) is considered to be that of a typical Si[Li] solid state and GdOS scintilator detector. In the values of X and Y, found by using the calculated inversion coefficients, errors are below 2% for data with solutions of glycerol, sucrose and glucose. For low Zeff materials like propionic acid, Zeffx is overestimated by 20% with X being within1%. For high Zeffx materials like KOH the value of Zeffx is underestimated by 22% while the error in X is + 15%. These imply that the source may have additional filtering than the aluminium filter specified by the manufacturer. Also it is found that the difference in the values of the inversion coefficients for the two types of detectors is negligible. The type of the detector does not affect on the DECT inversion algorithm to find the unknown chemical characteristic of the scanned materials. The effect of the source should be considered as an important factor to calculate the coefficients of inversion.

Keywords: attenuation coefficient, computed tomography, photoelectric effect, source spectrum

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Authors: Hadi Ghasemi, Mark Leonard, Spiliopoulos Spiro, Phil Cummins, Mathew Moihoi, Felix Taranu, Eric Buri, Chris Mckee

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In this study the level of seismic hazard in terms of Peak Ground Acceleration (PGA) was calculated for return period of 475 years, using modeled seismic sources and assigned ground-motion equations. The calculations were performed for bedrock site conditions (Vs30=760 m/s). From the results it is evident that the seismic hazard reaches its maximum level (i.e. PGA≈1g for 475 yr return period) at the Huon Peninsula and southern New Britain regions. Disaggregation analysis revealed that moderate to large earthquakes occurring along the New Britain Trench mainly control the level of hazard at these locations. The open-source computer program OpenQuake developed by Global Earthquake Model foundation was used for the seismic hazard computations. It should be emphasized that the presented results are still preliminary and should not be interpreted as our final assessment of seismic hazard in PNG.

Keywords: probabilistic seismic hazard assessment, Papua New Guinea, building code, OpenQuake

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Authors: Amjad Nusayr

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Software security is a general term used to any type of software architecture or model in which security aspects are incorporated in this architecture. These aspects are not part of the main logic of the underlying program. Software security can be achieved using a combination of approaches, including but not limited to secure software designs, third part component validation, and secure coding practices. Memory safety is one feature in software security where we ensure that any object in memory has a valid pointer or a reference with a valid type. Aspect-Oriented Programming (AOP) is a paradigm that is concerned with capturing the cross-cutting concerns in code development. AOP is generally used for common cross-cutting concerns like logging and DB transaction managing. In this paper, we introduce the concepts that enable AOP to be used for the purpose of memory and type safety. We also present ideas for extending AOP in software security practices.

Keywords: aspect oriented programming, programming languages, software security, memory and type safety

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Authors: Samuel J. Ahmad, Michael Zhu, Andrew J. Kobets

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Segmentation tools continue to advance, evolving from manual methods to automated contouring technologies utilizing convolutional neural networks. These techniques have evaluated ventricular and hemorrhagic volumes in the past but may be applied in novel ways to assess posterior fossa-associated pathologies such as Chiari malformations. Herein, we summarize literature pertaining to segmentation in the context of this and other posterior fossa-based diseases such as trigeminal neuralgia, hemifacial spasm, and posterior fossa syndrome. A literature search for volumetric analysis of the posterior fossa identified 27 papers where semi-automated, automated, manual segmentation, linear measurement-based formulas, and the Cavalieri estimator were utilized. These studies produced superior data than older methods utilizing formulas for rough volumetric estimations. The most commonly used segmentation technique was semi-automated segmentation (12 studies). Manual segmentation was the second most common technique (7 studies). Automated segmentation techniques (4 studies) and the Cavalieri estimator (3 studies), a point-counting method that uses a grid of points to estimate the volume of a region, were the next most commonly used techniques. The least commonly utilized segmentation technique was linear measurement-based formulas (1 study). Semi-automated segmentation produced accurate, reproducible results. However, it is apparent that there does not exist a single semi-automated software, open source or otherwise, that has been widely applied to the posterior fossa. Fully-automated segmentation via such open source software as FSL and Freesurfer produced highly accurate posterior fossa segmentations. Various forms of segmentation have been used to assess posterior fossa pathologies and each has its advantages and disadvantages. According to our results, semi-automated segmentation is the predominant method. However, atlas-based automated segmentation is an extremely promising method that produces accurate results. Future evolution of segmentation technologies will undoubtedly yield superior results, which may be applied to posterior fossa related pathologies. Medical professionals will save time and effort analyzing large sets of data due to these advances.

Keywords: chiari, posterior fossa, segmentation, volumetric

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Authors: Hugo Rodríguez

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Migrations of researchers, scientists, and inventors are a widespread phenomenon in modern times. In some cases, migrants stay linked to research groups in their countries of origin, either out of their own conviction or because of government policies. We examine different linear models of technological development (using the Ordinary Least Squares (OLS) technique) in eight selected countries and find that the collaborations between resident and nonresident patent applicants correlate with different levels of performance of the technological policies in three different scenarios. Therefore, the reinforcement of that link must be considered a powerful tool for technological development.

Keywords: development, collaboration, patents, technology

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Authors: Laribi-Habchi Hasiba, Bouanane-Darenfed Amel, Drouiche Nadjib, Pausse André, Mameri Nabil

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Chitin, a linear 1, 4-linked N-acetyl-d-glucosamine (GlcNAc) polysaccharide is the major structural component of fungal cell walls, insect exoskeletons and shells of crustaceans. It is one of the most abundant naturally occurring polysaccharides and has attracted tremendous attention in the fields of agriculture, pharmacology and biotechnology. Each year, a vast amount of chitin waste is released from the aquatic food industry, where crustaceans (prawn, crab, Shrimp and lobster) constitute one of the main agricultural products. This creates a serious environmental problem. This linear polymer can be hydrolyzed by bases, acids or enzymes such as chitinase. In this context an extracellular chitinase (ChiA-65) was produced and purified from a newly isolated LHH100. Pure protein was obtained after heat treatment and ammonium sulphate precipitation followed by Sephacryl S-200 chromatography. Based on matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS) analysis, the purified enzyme is a monomer with a molecular mass of 65,195.13 Da. The sequence of the 27 N-terminal residues of the mature ChiA-65 showed high homology with family-18 chitinases. Optimal activity was achieved at pH 4 and 75◦C. Among the inhibitors and metals tested p-chloromercuribenzoic acid, N-ethylmaleimide, Hg2+ and Hg + completelyinhibited enzyme activity. Chitinase activity was high on colloidal chitin, glycol chitin, glycol chitosane, chitotriose and chitooligosaccharide. Chitinase activity towards synthetic substrates in the order of p-NP-(GlcNAc) n (n = 2–4) was p-NP-(GlcNAc)2> p-NP-(GlcNAc)4> p-NP-(GlcNAc)3. Our results suggest that ChiA-65 preferentially hydrolyzed the second glycosidic link from the non-reducing end of (GlcNAc) n. ChiA-65 obeyed Michaelis Menten kinetics the Km and kcat values being 0.385 mg, colloidal chitin/ml and5000 s−1, respectively. ChiA-65 exhibited remarkable biochemical properties suggesting that this enzyme is suitable for bioconversion of chitin waste.

Keywords: Bacillus licheniformis LHH100, characterization, extracellular chitinase, purification

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Authors: Liu M. Hanmin

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Wong Kar-Wai’s multi-genre film 2046, world premiered in 2004, comes with a vibrant mediascape made up of multiple named languages, code-switching, intertitles, news footage from the real world, and extra-linguistic means of communication. In film- and multilingual studies it is still a challenge to incorporate non-languages into an analytical framework with conventional languages. This paper uses translanguaging theory to read silent practices in Wong Kar-Wai’ 2046. Two scenes that feature the silence experience the most are taken as case studies. In these two scenes, we can identify two tropes of intersemiotic relationships that are co-articulated by silence: patriarchy and unfinished romance, respectively. The conclusion argues that silence in Wong Kar-Wai’s 2046 exerts multimodal agency by ‘speaking’ directly to the audience and in mutual directions to characters. Thereby, it moves beyond the passive role of merely accentuating or assisting the aural register of a film.

Keywords: translanguaging, Wong Kar-Wai, multimodality, semiotics, inter semiotics, Hong Kong media, film culture

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Authors: A. Belay, B. Kebede

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The concentration- and temperature-dependent refractive indices of solutions extracted from defective and non-defective coffee beans have been investigated using a He–Ne laser. The refractive index has a linear relationship with the presumed concentration of the coffee solutions in the range of 0.5–3%. Higher and lower values of refractive index were obtained for immature and non-defective coffee beans, respectively. The Refractive index of bean extracts can be successfully used to separate defective from non-defective beans.

Keywords: coffee extract, refractive index, temperature dependence

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Authors: Roya Khajepour, Alireza B. Novinzadeh

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In this paper, the spherical robot is modeled using the Band-Graph approach. This breed of robots is typically employed in expedition missions to unknown territories. Its motion mechanism is based on convection of a fluid in a set of three donut vessels, arranged orthogonally in space. This robot is a non-linear, non-holonomic system. This paper utilizes the Band-Graph technique to derive the torque generation mechanism in a spherical robot. Eventually, this paper describes the motion of a sphere due to the exerted torque components.

Keywords: spherical robot, Band-Graph, modeling, torque

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Authors: Shehu Isyaku

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The general objective of the study was to investigate ‘the relationship between the external business environment and the sustainability of micro, small and medium enterprises (MSMEs) in Jigawa state’, Nigeria. Specifically, the study was to examine the relationship between 1) the economic environment, 2) the social environment, 3) the technological environment, and 4) the political environment and the sustainability of MSMEs in Jigawa state, Nigeria. The study was drawn on Resource-Based View (RBV) Theory and Knowledge-Based View (KBV). The study employed a descriptive cross-sectional survey design. A researcher-made questionnaire was used to collect data from the 350 managers/owners who were selected using stratified, purposive and simple random sampling techniques. Data analysis was done using means and standard deviations, factor analysis, Correlation Coefficient, and Pearson Linear Regression analysis. The findings of the study revealed that the sustainability potentials of the managers/owners were rated as high potential (economic, environmental, and social sustainability using 5 5-point Likert scale. Mean ratings of effectiveness of the external business environment were; as highly effective. The results from the Pearson Linear Regression Analysis rejected the hypothesized non-significant effect of the external business environment on the sustainability of MSMEs. Specifically, there is a positive significant relationship between 1) economic environment and sustainability; 2) social environment and sustainability; 3) technological environment and sustainability and political environment and sustainability. The researcher concluded that MSME managers/owners have a high potential for economic, social and environmental sustainability and that all the constructs of the external business environment (economic environment, social environment, technological environment and political environment) have a positive significant relationship with the sustainability of MSMEs. Finally, the researcher recommended that 1) MSME managers/owners need to develop marketing strategies and intelligence systems to accumulate information about the competitors and customers' demands, 2) managers/owners should utilize the customers’ cultural and religious beliefs as an opportunity that should be utilized while formulating business strategies.

Keywords: business environment, sustainability, small and medium enterprises, external business environment

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Authors: Veljko Turanjanin

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In this article, an author deals with the issue of life imprisonment. Life imprisonment represents a new sentence in the Serbian legislature, in addition to the standard one, imprisonment. The author elaborated on judgments of the European Court of Human Rights (ECtHR), imposing the possibility of parole for the person sentenced to life imprisonment, emphasizing rehabilitation as the primary goal of penalties. According to the ECtHR, life imprisonment without parole is not permitted. The right to rehabilitation is very strictly set in the ECtHR jurisprudence. Life imprisonment represents a new sentence in the Serbian legislature, in addition to the standard one, imprisonment. The legislator provided the possibility of parole for most criminal offenses after 27 years in prison, while for some of them, a possibility of parole is explicitly prohibited. The author points out the shortcomings of the legal solution that exists in Serbia, which flagrantly threatens to violate the human rights of the offenders.

Keywords: European Court of Human Rights, life imprisonment, parole, rehabilitation

Procedia PDF Downloads 102

Authors: Kohei Inoue, Kenji Hara, Kiichi Urahama

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We describe a relationship between integral images and differential images. First, we derive a simple difference filter from conventional integral image. In the derivation, we show that an integral image and the corresponding differential image are related to each other by simultaneous linear equations, where the numbers of unknowns and equations are the same, and therefore, we can execute the integration and differentiation by solving the simultaneous equations. We applied the relationship to an image fusion problem, and experimentally verified the effectiveness of the proposed method.

Keywords: integral images, differential images, differential filters, image fusion

Procedia PDF Downloads 503

Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

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Authors: S. Aditya, K. T. Nideesh, N. Guruprasad

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Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost.

Keywords: NW method, optimum utilization, transportation problem, Vogel’s approximation method

Procedia PDF Downloads 434

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

Procedia PDF Downloads 117

Authors: Maor Farid, Oleg Gendelman

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Equivalent mechanical model of liquid sloshing in partially-filled cylindrical vessel is treated in the cases of free oscillations and of horizontal base excitation. The model is designed to cover both the linear and essentially nonlinear sloshing regimes. The latter fluid behaviour might involve hydraulic impacts interacting with the inner walls of the tank. These impulsive interactions are often modeled by high-power potential and dissipation functions. For the sake of analytical description, we use the traditional approach by modeling the impacts with velocity-dependent restitution coefficient. This modelling is similar to vibro-impact nonlinear energy sink (VI NES) which was recently explored for its vibration mitigation performances and nonlinear response regimes. Steady-state periodic regimes and chaotic strongly modulated responses (CSMR) are detected. Those dynamical regimes were described by the system's slow motion on the slow invariant manifold (SIM). There is a good agreement between the analytical results and numerical simulations. Subsequently, Finite-Element (FE) method is used to determine and verify the model parameters and to identify dominant dynamical regimes, natural modes and frequencies. The tank failure modes are identified and critical locations are identified. Mathematical relation is found between degrees-of-freedom (DOFs) motion and the mechanical stress applied in the tank critical section. This is the prior attempt to take under consideration large-amplitude nonlinear sloshing and tank structure elasticity effects for design, regulation definition and resistance analysis purposes. Both linear (tuned mass damper, TMD) and nonlinear (nonlinear energy sink, NES) passive energy absorbers contribution to the overall system mitigation is firstly examined, in terms of both stress reduction and time for vibration decay.

Keywords: nonlinear energy sink (NES), reduced-order modelling, liquid sloshing, vibration mitigation, vibro-impact dynamics

Procedia PDF Downloads 144

Authors: O. Hinrichs, H. Franz, G. Reiter

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Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

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Authors: Changshan Zhang, Zhijin Yu, Shixing Fan

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A comprehensive hazard evaluation for coal self-heating in composite long-wall gobs is heavily dependent on computational simulation. In this study, the spatial distributions of cracks which caused significant air leakage were simulated by universal distinct element code (UDEC) simulation. Based on the main routes of air leakage and characteristics of coal self-heating, a computational fluid dynamics (CFD) modeling was conducted to model the coal spontaneous combustion dangerous area in composite long-wall gobs. The results included the oxygen concentration distributions and temperature profiles showed that the numerical approach is validated by comparison with the test data. Furthermore, under the conditions of specific engineering, the major locations where some techniques for extinguishing and preventing long-wall gob fires need to be put into practice were also examined.

Keywords: computational simulation, UDEC simulation, coal self-heating, CFD modeling, long-wall gobs

Procedia PDF Downloads 308

Authors: Cristina-Maria Păcurar

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The paper presents an original Python-based application that outlines the advantages of combining some elementary notions of mathematics with the study of a programming language. The application support refers to some of the first lessons of analytic geometry, meaning conics and quadrics and their reduction to a standard form, as well as some related notions. The chosen programming language is Python, not only for its closer to an everyday language syntax – and therefore, enhanced readability – but also for its highly reusable code, which is of utmost importance for a mathematician that is accustomed to exploit already known and used problems to solve new ones. The purpose of this paper is, on one hand, to support the idea that one of the most appropriate means to initiate one into programming is throughout mathematics, and reciprocal, one of the most facile and handy ways to assimilate some basic knowledge in the study of mathematics is to apply them in a personal project. On the other hand, besides being a mean of learning both programming and analytic geometry, the application subject to this paper is itself a useful tool for it can be seen as an independent original Python package for analytic geometry.

Keywords: analytic geometry, conics, python, quadrics

Procedia PDF Downloads 287