Search results for: construction methods

Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

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Authors: Daniel K. Gameti

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The paper explored the effects of active and passive entrepreneurship education methods on the venture creation intention of undergraduate students in Ghana. The study also examined the moderating effect of gender and negative personal characteristics (risk tolerance, stress tolerance and fear of failure) on students’ venture creation intention. Deductive approach was used in collecting quantitative data from 555 business students from one public university and one private university through self-administered questionnaires. Descriptive statistic was used to determine the dominant method of entrepreneurship education used in Ghana. Further, structural equation model was used to test four hypotheses. The results of the study show that the dominant method of education used in Ghana was lectures and the least method used was field trip. The study further revealed that passive methods of education are less effective compared to active methods which were statistically significant in venture creation intention among students. There was also statistical difference between male and female students’ venture creation intention but stronger among male students and finally, the only personal characteristics that influence students’ intention was stress tolerance because risk tolerance and fear of failure were statistically insignificant.

Keywords: entrepreneurship education, Ghana, moderating variables, venture creation intention, undergraduate students

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Authors: Roihatul Mutiah, Sukardiman, Aty Widyawaruyanti

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Calotropis gigantiea (L.) R. Br (Apocynaceae) commonly called as “Biduri” or “giant milk weed” is a well-known weed to many cultures for treating various disorders. Several studies reported that C.gigantea roots has anticancer activity. The main aim of this research was to isolate and identify an active marker compound of C.gigantea roots for quality control purpose of its extract in the development as anticancer natural product. The isolation methods was bioactivity guided column chromatography, TLC, and HPLC. Evaluated anticancer activity of there substances using MTT assay methods. Identification structure active compound by UV, 1HNMR, 13CNMR, HMBC, HMQC spectral and other references. The result showed that the marker active compound was identical as Calotropin.

Keywords: calotropin, Calotropis gigantea, anticancer, marker active

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Hadi Rezghimaleki, Masatoshi Kubouchi, Yoshihiko Arao

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The use of natural fiber composites (NFCs) is growing at a fast rate regarding industrial applications and principle researches due to their eco-friendly, renewable nature, and low density/costs. Drilling is one of the most important machining operations that are carried out on natural fiber composites. Delamination is a major concern in the drilling process of NFCs that affects the structural integrity and long-term reliability of the machined components. Flax fiber reinforced epoxy composite laminates were prepared by hot press technique. In this research, we evaluated drilling-induced delamination of flax/epoxy composites by X-ray computed tomography (CT), ultrasonic testing (UT), and optical methods and compared the results.

Keywords: natural fiber composites, flax/epoxy, X-ray CT, ultrasonic testing

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Authors: Liang Bai, Yandong Xiao, Haorang Wang, Songyang Lao

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The directedness of links is crucial to determine the controllability in complex networks. Even the edge directions can determine the controllability of complex networks. Obviously, for a given network, we wish to design its edge directions that make this network approach the optimal controllability. In this work, we firstly introduce two methods to enhance network by assigning edge directions. However, these two methods could not completely mitigate the negative effects of inaccessibility and dilations. Thus, to approach the optimal network controllability, the edge directions must mitigate the negative effects of inaccessibility and dilations as much as possible. Finally, we propose the edge direction for optimal controllability. The optimal method has been found to be successfully useful on real-world and synthetic networks.

Keywords: complex network, dynamics, network control, optimization

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Authors: B. F. Olanipekun, O. J. Oyelade, C. O. Osemobor

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Pigeon pea is a very good source of protein and micronutrient, but it is being underutilized in Nigeria because of several constraints. This research considered the effect of different processing methods on the quality attributes of pigeon pea used in bread production towards enhancing its utility. Pigeon pea was obtained at a local market and processed into the flour using three processing methods: soaking, sprouting and roasting and were used to bake bread in different proportions. Chemical composition and sensory attributes of the breads were thereafter determined. The highest values of protein and ash contents were obtained from 20 % substitution of sprouted pigeon pea in wheat flour and may be attributable to complex biochemical changes occurring during hydration, to invariably lead to protein constituent being broken down. Hydrolytic activities of the enzymes from the sprouted sample resulted in improvement in the constituent of total protein probably due to reduction in the carbohydrate content. Sensory qualities analyses showed that bread produced with soaked and roasted pigeon pea flours at 5 and 10% inclusion, respectively were mostly accepted than other blends, and products with sprouted pigeon pea flour were least accepted. The findings of this research suggest that supplementing wheat flour with sprouted pigeon peas have more nutritional potentials. However, with sensory analysis indices, the soaked and roasted pigeon peas up to 10% are majorly accepted, and also can improve the nutritional status. Overall, this will be very beneficial to population dependent on plant protein in order to combat malnutrition problems.

Keywords: pigeon pea, processing, protein, malnutrition

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Authors: J. Hajnys, M. Pagac, J. Petru, P. Stefek, J. Mesicek, J. Kratochvil

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The new progressive method of 3D metal printing SLM (Selective Laser Melting) is increasingly expanded into the normal operation. As a result, greater demands are placed on the surface quality of the parts produced in this way. The article deals with research of selected finishing methods (tumbling, face milling, sandblasting, shot peening and brushing) and their impact on the final surface roughness. The 20 x 20 x 7 mm produced specimens using SLM additive technology on the Renishaw AM400 were subjected to testing of these finishing methods by adjusting various parameters. Surface parameters of roughness Sa, Sz were chosen as the evaluation criteria and profile parameters Ra, Rz were used as additional measurements. Optical measurement of surface roughness was performed on Alicona Infinite Focus 5. An experiment conducted to optimize the surface roughness revealed, as expected, that the best roughness parameters were achieved through a face milling operation. Tumbling is particularly suitable for 3D printing components, as tumbling media are able to reach even complex shapes and, after changing to polishing bodies, achieve a high surface gloss. Surface quality after tumbling depends on the process time. Other methods with satisfactory results are shot peening and tumbling, which should be the focus of further research.

Keywords: additive manufacturing, selective laser melting, SLM, surface roughness, stainless steel

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Authors: Arjita Biswas, Sandeep Potnis

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Plastic roads (bituminous roads using waste plastic in the wearing course ) have now become familiar in the Road Construction Sector in India. With the Indian Road Congress Code (IRC SP: 98 -2013), many agencies are coming forward to implement Plastic Roads in India. This paper discuss and compare about the various properties of bituminous mix with 8% waste plastic and normal bituminous mix. This paper also signifies the performance of both the types of roads after 4 months of age under loading conditions. Experiments were carried out to evaluate its performance. The result shows improved performance of plastic roads.

Keywords: bituminous roads, experiments, performance, plastic roads

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Z. Abdollahnejad, M. Kheradmand, F. Pacheco-Torgal

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The use of bio-based admixtures on construction materials is a recent trend that is gaining momentum. However, to our knowledge, no studies have been reported concerning the use of biopolymers on hybrid cement based mortars. This paper reports experimental results regarding the study of the influence of mix design of 43 hybrid cement mortars containing two different biopolymers on its mechanical performance. The results show that the use of the biopolymer carrageenan is much more effective than the biopolymer xanthan concerning the increase in compressive strength. An optimum biopolymer content was found.

Keywords: waste reuse, fly ash, waste glass, hybrid cement, biopolymers, mechanical strength

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Authors: Sevde D. Karayel, Ediz Atmaca

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Supplier selection subject is vital because of development competitiveness and performance of firms which have right, rapid and with low cost procurement. Considering the fact that competition between firms is no longer on their supply chains, hence it is very clear that performance of the firms’ not only depend on their own success but also success of all departments in supply chain. For this purpose, firms want to work with suppliers which are cost effective, flexible in terms of demand and high quality level for customer satisfaction. However, diversification and redundancy of their expectations from suppliers, supplier selection problems need to be solved as a hard problem. In this study, supplier selection problem is discussed for critical piece, which is using almost all production of products in and has troubles with lead time from supplier, in a firm that produces medical devices. Analyzing policy in the current situation of the firm in the supplier selection indicates that supplier selection is made based on the purchasing department experience and other authorized persons’ general judgments. Because selection do not make based on the analytical methods, it is caused disruptions in production, lateness and extra cost. To solve the problem, AHP and TOPSIS which are multi-criteria decision making techniques, which are effective, easy to implement and can analyze many criteria simultaneously, are used to make a selection among alternative suppliers.

Keywords: AHP-TOPSIS methods, multi-criteria decision making, supplier selection problem, supply chain management

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Authors: Justina Jor, Mahmud Pinga

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Climate change has become a significant worldwide environmental challenge with extensive implications, compelling both governments and non-governmental organizations to remain vigilant, as it seemingly impacts various sectors of the global economy, including education. The study investigates the implementation of smart climate change measures for effective primary school management in Benue State, Nigeria. Theorized by the diffusion of innovations, the study was guided by two research questions, and two null hypotheses were formulated and tested. The study used a descriptive survey design. The population comprised 12,364 teachers from 2,721 primary schools, with a sample of 618 teachers from 136 schools selected through a multistage sampling procedure. Smart climate change measures questionnaire (SCCMQ) and key informant interview (KII) were used for data collection. The data collected were analyzed using mean and standard deviation to answer the research questions, while the Chi-square (χ2) test of goodness-of-fit was used to test the hypotheses at a 0.05 level of significance, with qualitative data analyzed using simple percentages, tables, and bar charts. The findings highlight the significant positive impact of green building practices on the efficient administration of primary schools in Benue State, Nigeria. The crucial integration of environmentally sustainable construction methods is emphasized for enhancing overall management in these educational institutions. In addition, the research demonstrates a favorable impact on the adoption of renewable energy solutions and effective school management. The utilization of renewable energy not only aligns with eco-friendly practices but also contributes to the overall operational efficiency and sustainability of primary schools in the region. The study recommends that educational authorities and policymakers prioritize integrating green building practices and renewable energy solutions, pointing towards the prospect of improved governance and functionality for primary education facilities not only in Benue but throughout Nigeria.

Keywords: smart, climate change, effective management, green building, renewable energy

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Authors: Michael Barker

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Men’s rights activists are largely antifeminism. Evaluation of men’s rights discourses, however, shows that men’s rights’ goals would be better achieved by working with feminism. Discussion of men’s rights discourses, though, is prone to confusion because there is no commonly used men’s rights language. In the presentation ‘male sexism’, ‘matriarchy’ and ‘masculism’ will be unpacked as part of a suggested men’s rights language. Once equipped with a men’s rights vocabulary, sustained philosophical assessment of the extent to which several categories of male disadvantages are wrongful will be offered. Following this, conditions that cause each category of male sexism will be discussed. It shall be argued that male sexism is caused more so by matriarchy than by patriarchy or by feminism. In closing, the success at which various methods address the categories of male sexism will be contrasted. Ultimately, it will be shown that male disadvantages are addressed more successfully by methods that work with, than against, feminism.

Keywords: gender studies, feminism, patriarchy, men’s rights, male sexism, matriarchy, masculism

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Authors: Ali Mohammadi

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The basis for the construction of any project is a map, a map where the surveyor can determine the coordinates of the points on the ground by using the coordinates and using the total station, projects such as dams, roads, tunnels and pipelines, if the base points are determined using GPS prepared can create challenges for the surveyor to control. First, we will examine some map projection on which the maps are designed, and a summary of their differences and the challenges that surveyors face in order to control them, because in order to build projects, we need real lengths and angles, so we have to use coordinates that provide us with the results of the calculations. We will examine some examples to understand the concept of localization so that the surveyor knows if he is facing a challenge or not and if he is faced with this challenge, how should he solve this problem.

Keywords: UTM, scale factor, cartesian, traverse

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: N. Guruprasad

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This paper presents a modification of approximation method for transportation problems. The initial basic feasible solution can be computed using either Russel's or Vogel's approximation methods. Russell’s approximation method provides another excellent criterion that is still quick to implement on a computer (not manually) In most cases Russel's method yields a better initial solution, though it takes longer than Vogel's method (finding the next entering variable in Russel's method is in O(n1*n2), and in O(n1+n2) for Vogel's method). However, Russel's method normally has a lesser total running time because less pivots are required to reach the optimum for all but small problem sizes (n1+n2=~20). With this motivation behind we have incorporated a variation of the same – what we have proposed it has TMC (Total Modified Cost) to obtain fast and efficient solutions.

Keywords: computation, efficiency, modified cost, Russell’s approximation method, transportation, Vogel’s approximation method

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Authors: Tomohiko Utsuki

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Currently, brain resuscitation becomes increasingly important due to revising various clinical guidelines pertinent to emergency care. In brain resuscitation, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) is required for stabilizing physiological state of brain, and is described as the essential treatment points in many guidelines of disorder and/or disease such as brain injury, stroke, and encephalopathy. Thus, an integrated control system of BT, ICP, and CBF will greatly contribute to alleviating the burden on medical staff and improving treatment effect in brain resuscitation. In order to develop such a control system, models related to BT, ICP, and CBF are required for control simulation, because trial and error experiments using patients are not ethically allowed. A static model of cerebral blood circulation from intracranial arteries and vertebral artery to jugular veins has already constructed and verified. However, it is impossible to represent the pooling of blood in blood vessels, which is one cause of cerebral hypertension in this model. And, it is also impossible to represent the pulsing motion of blood vessels caused by blood pressure change which can have an affect on the change of cerebral tissue pressure. Thus, a dynamic model of cerebral blood circulation is constructed in consideration of the elasticity of the blood vessel and the inertia of the blood vessel wall. The constructed dynamic model was numerically analyzed using the normal data, in which each arterial blood flow in cerebral blood circulation, the distribution of blood pressure in the Circle of Willis, and the change of blood pressure along blood flow were calculated for verifying against physiological knowledge. As the result, because each calculated numerical value falling within the generally known normal range, this model has no problem in representing at least the normal physiological state of the brain. It is the next task to verify the accuracy of the present model in the case of disease or disorder. Currently, the construction of a migration model of extracellular fluid and a model of heat transfer in cerebral tissue are in progress for making them parts of an integrated model of brain physiological state, which is necessary for developing an future integrated control system of BT, ICP and CBF. The present model is applicable to constructing the integrated model representing at least the normal condition of brain physiological state by uniting with such models.

Keywords: dynamic model, cerebral blood circulation, brain resuscitation, automatic control

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Authors: Victor S. Klimin, Alexey A. Rezvan, Maxim S. Solodovnik, Oleg A. Ageev

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In this paper, the problems of existing methods of profiling and surface modification of nanoscale arsenide-gallium structures are analyzed. The use of a combination of methods of local anodic oxidation and plasma chemical etching to solve this problem is considered. The main features that make this technology one of the promising areas of modification and profiling of near-surface layers of solids are demonstrated. In this paper, we studied the effect of formation stress and etching time on the geometrical parameters of the etched layer and the roughness of the etched surface. Experimental dependences of the thickness of the etched layer on the time and stress of formation were obtained. The surface analysis was carried out using atomic force microscopy methods, the corresponding profilograms were constructed from the obtained images, and the roughness of the etched surface was studied accordingly. It was shown that at high formation voltage, the depth of the etched surface increased, this is due to an increase in the number of active particles (oxygen ions and hydroxyl groups) formed as a result of the decomposition of water molecules in an electric field, during the formation of oxide nanostructures on the surface of gallium arsenide. Oxide layers were used as negative masks for subsequent plasma chemical etching by the STE ICPe68 unit. BCl₃ was chosen as the chlorine-containing gas, which differs from analogs in some parameters for the effect of etching of nanostructures based on gallium arsenide in the low-temperature plasma. The gas mixture of reaction chamber consisted of a buffer gas NAr = 100 cm³/min and a chlorine-containing gas NBCl₃ = 15 cm³/min at a pressure P = 2 Pa. The influence of these methods modes, which are formation voltage and etching time, on the roughness and geometric parameters, and corresponding dependences are demonstrated. Probe nanotechnology was used for surface analysis.

Keywords: nanostructures, GaAs, plasma chemical etching, modification structures

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Authors: Irtaza M. Syed, Kaameran Raahemifar

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This paper presents comparative analysis of photovoltaic systems (PVS) and proposes practical techniques to improve operational efficiency of the PVS. The best engineering and construction practices for PVS are identified and field oriented recommendation are made. Comparative analysis of central and string inverter based, as well as 600 and 1000 VDC PVS are performed. In addition, direct current (DC) and alternating current (AC) photovoltaic (PV) module based systems are compared. Comparison shows that 1000 V DC String Inverters based PVS is the best choice.

Keywords: photovoltaic module, photovoltaic systems, operational efficiency improvement, comparative analysis

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

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Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Rafal Sochaczewski, Marcin Szlachetka, Miroslaw Wendeker

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Increasing requirements to reduce exhaust emissions and fuel consumption while increasing the power factor is increasingly becoming applicable to internal combustion engines intended for aircraft applications. As a result, intensive research work is underway to develop a diesel-powered unit for aircraft propulsion. Due to a number of advantages, such as lack of the head (lower heat loss) and timing system, opposite movement of pistons conducive to balancing the engine, the two-stroke compression-ignition engine with the opposite pistons has been developed and upgraded. Of course, such construction also has drawbacks. The main one is the necessity of using a gear connecting two crankshafts or a complicated crank system with one shaft. The peculiarity of the arrangement of pistons with sleeves, as well as the fulfillment of rigorous requirements, makes it necessary to apply the most modern technologies and constructional solutions. In the case of the fuel supply system, it was decided to use common rail system elements. The paper presents an analysis of the possibility of using a common rail pump to supply an aircraft compression-ignition engine. It is an engine with a two-stroke cycle, three cylinders, opposing pistons, and 100 kW power. Each combustion chamber is powered by two injectors controlled by electromagnetic valves. In order to assess the possibility of using a common rail pump, four high-pressure pumps were tested on a bench. They are piston pumps differing in the number and geometry of the pumping sections. The analysis included the torque on the pump drive shaft and the power needed to drive the pump depending on the rotational speed, pumping pressure and fuel dispenser settings. The research allowed to optimize the engine power supply system depending on the fuel demand and the way the pump is mounted on the engine. Acknowledgment: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A.’ and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish Nation-al Centre for Research and Development.

Keywords: diesel engine, fuel pump, opposing pistons, two-stroke

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Authors: Raminder Kaur

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This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

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Authors: Paloma Mendes Saldanha

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Access to information is a prerequisite for democracy while also guiding the material construction of fundamental rights. The exercise of citizenship requires knowing, understanding, questioning, advocating for, and securing rights and responsibilities. In other words, it goes beyond mere active electoral participation and materializes through awareness and the struggle for rights and responsibilities in the various spaces occupied by the population in their daily lives. In times of hyper-cultural connectivity, active citizenship is shaped through ethical trust processes, most often established between humans and algorithms. Automated decisions, so prevalent in various everyday situations, such as purchase preference predictions, virtual voice assistants, reduction of accidents in autonomous vehicles, content removal, resume selection, etc., have already found their place as a normalized discourse that sometimes does not reveal or make clear what violations of fundamental rights may occur when algorithmic explainability is lacking. In other words, technological and market development promotes a normalization for the use of automated decisions while silencing possible restrictions and/or breaches of rights through a culturally modeled, unethical, and unexplained trust process, which hinders the possibility of the right to a healthy, transparent, and complete exercise of citizenship. In this context, the article aims to identify the violations caused by the absence of algorithmic explainability in the exercise of citizenship through the construction of an unethical and silent trust process between humans and algorithms in automated decisions. As a result, it is expected to find violations of constitutionally protected rights such as privacy, data protection, and transparency, as well as the stipulation of algorithmic explainability as a fundamental right in the exercise of Brazilian citizenship in the era of virtualization, facing a threefold foundation called trust: culture, rules, and systems. To do so, the author will use a bibliographic review in the legal and information technology fields, as well as the analysis of legal and official documents, including national documents such as the Brazilian Federal Constitution, as well as international guidelines and resolutions that address the topic in a specific and necessary manner for appropriate regulation based on a sustainable trust process for a hyperconnected world.

Keywords: artificial intelligence, ethics, citizenship, trust

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Authors: Lamzira Ebralidze, Aleksandre Tsertsvadze, Dali Berashvili, Aliosha Bakuridze

Abstract:

Nowadays, there is an increasing demand for biologically active substances from vegetable, animal, and mineral resources. In terms of the use of natural compounds, pharmaceutical, cosmetic, and nutrition industry has big interest. The biggest drawback of conventional extraction methods is the need to use a large volume of organic extragents. The removal of the organic solvent is a multi-stage process. And their absolute removal cannot be achieved, and they still appear in the final product as impurities. A large amount of waste containing organic solvent damages not only human health but also has the harmful effects of the environment. Accordingly, researchers are focused on improving the extraction methods, which aims to minimize the use of organic solvents and energy sources, using alternate solvents and renewable raw materials. In this context, green extraction principles were formed. Green Extraction is a need of today’s environment. Green Extraction is the concept, and it totally corresponds to the challenges of the 21st century. The extraction of biologically active compounds based on green extraction principles is vital from the view of preservation and maintaining biodiversity. Novel technologies of green extraction are known, such as "cold methods" because during the extraction process, the temperature is relatively lower, and it doesn’t have a negative impact on the stability of plant compounds. Novel technologies provide great opportunities to reduce or replace the use of organic toxic solvents, the efficiency of the process, enhance excretion yield, and improve the quality of the final product. The objective of the research is the development of green technologies of flavonoids containing preparations. Methodology: At the first stage of the research, flavonoids containing preparations (Tincture Herba Leonuri, flamine, rutine) were prepared based on conventional extraction methods: maceration, bismaceration, percolation, repercolation. At the same time, the same preparations were prepared based on green technologies, microwave-assisted, UV extraction methods. Product quality characteristics were evaluated by pharmacopeia methods. At the next stage of the research technological - economic characteristics and cost efficiency of products prepared based on conventional and novel technologies were determined. For the extraction of flavonoids, water is used as extragent. Surface-active substances are used as co-solvent in order to reduce surface tension, which significantly increases the solubility of polyphenols in water. Different concentrations of water-glycerol mixture, cyclodextrin, ionic solvent were used for the extraction process. In vitro antioxidant activity will be studied by the spectrophotometric method, using DPPH (2,2-diphenyl-1- picrylhydrazyl) as an antioxidant assay. The advantage of green extraction methods is also the possibility of obtaining higher yield in case of low temperature, limitation extraction process of undesirable compounds. That is especially important for the extraction of thermosensitive compounds and maintaining their stability.

Keywords: extraction, green technologies, natural resources, flavonoids

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Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

Abstract:

Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

Procedia PDF Downloads 340

Authors: Mekonen G., Sileshi M., Melkamu M.

Abstract:

Recharge estimation is important for the assessment and management of groundwater resources effectively. This study applied the soil moisture balance and Baseflow separation methods to estimate groundwater recharge in the Fetam Catchment. It is one of the major catchments understudied from the different catchments in the upper Blue Nile River basin. Surface water has been subjected to high seasonal variation; due to this, groundwater is a primary option for drinking water supply to the community. This research has been conducted to estimate groundwater recharge by using fifteen years of River flow data for the Baseflow separation and ten years of daily meteorological data for the daily soil moisture balance recharge estimating method. The recharge rate by the two methods is 170.5 and 244.9mm/year daily soil moisture and baseflow separation method, respectively, and the average recharge is 207.7mm/year. The average value of annual recharge in the catchment is almost equal to the average recharge in the country, which is 200mm/year. So, each method has its own limitations, and taking the average value is preferable rather than taking a single value. Baseflow provides overestimated result compared to the average of the two, and soil moisture balance is the list estimator. The recharge estimation in the area also should be done by other recharge estimation methods.

Keywords: groundwater, recharge, baseflow separation, soil moisture balance, Fetam catchment

Procedia PDF Downloads 338

Authors: Eugene Benilov, Mikhail Benilov

Abstract:

The Enskog-Vlasov (EV) equation is a widely used semi-phenomenological model of gas/liquid phase transitions. We show that it does not generally conserve energy, although there exists a restriction on its coefficients for which it does. Furthermore, if an energy-preserving version of the EV equation satisfies an H-theorem as well, it can be used to rigorously derive the so-called Maxwell construction which determines the parameters of liquid-vapor equilibria. Finally, we show that the EV model provides an accurate description of the thermodynamics of noble fluids, and there exists a version simple enough for use in applications.

Keywords: Enskog collision integral, hard spheres, kinetic equation, phase transition

Procedia PDF Downloads 130