Search results for: multi MPPT-inverter

Authors: Carl Eiselen, Stephen O’Hagan

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Background: Q fever, caused by the obligate intracellular bacterium Coxiella burnetii, is an infectious disease with variable systemic manifestations. Its potential to cause ocular complications has not been reported before in Australia. This case study explores the unusual presentation of asymptomatic acute multifocal retinitis (AMR) in a patient with acute Q fever endocarditis and hepatitis in rural Queensland, Australia. Case Presentation: A 48-year-old male gardener presented with flu-like symptoms, weight loss, and encephalopathy. Despite systemic malaise, he had no ocular symptoms. Laboratory investigations confirmed acute Q fever, and imaging studies identified hepatic involvement and endocarditis. The retinal screening revealed asymptomatic AMR, corroborated by fundus examination and SD-OCT. Following treatment with Doxycycline and hydroxychloroquine, both systemic and ocular manifestations improved. Discussion: This is the first documented case of asymptomatic AMR associated with Q fever. The patient’s lack of autoantibodies challenges the established understanding of Q fever endocarditis and suggests potential alternative mechanisms. Conclusion: This case report expands our understanding of the multi-systemic impact of Q fever, highlighting the need for comprehensive clinical evaluation and including retinal screening in the setting of acute infection. The disease's underlying mechanism for ocular involvement is not yet established.

Keywords: Coxiella Burnetti, Q fever, ocular manifestation, acute multifocal retintis, endocarditis

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Authors: Victor Oyewumi Ogunbiyi

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Food waste is recognised as one of the major global challenges in achieving a sustainable future. Currently, very little is known about the multi-stakeholder approach to food waste management downstream of the supply chain, particularly in the foodservice sector. In order to better understand and explain the complex issues of food waste, a qualitative study was conducted on the generation of food waste in food services (restaurants, catering, canteens, and local food vendors) and policy initiatives to mitigate it from the perspective of the stakeholders. A semi-structured interview approach and observation were used to collect data from some 32 selected stakeholders in Garki, Abuja, Nigeria. Thematic analysis was employed to analyse the data from the qualitative instrument adopted in this study. Results revealed that the attitude of stakeholders, poor environmental hygiene, poor food cooking skills and handling, and lack of communication are the major causes of food waste. This study identified seven policy initiatives: regulations, information and education campaigns, economic instruments, mobile applications, stakeholders’ collaboration, firm internal action, and training. Finally, we link policy initiatives to food waste mitigation to provide a response to the damaging shock of food waste.

Keywords: food waste, foodservices, emerging opportunities, policy initiatives, food waste prevention, multistakeholder. garki district-abuja

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Authors: Abdullah Bal, Sevdenur Bal

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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Niranjana Devi N.

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Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

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Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

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In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Raghunath Arnab

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The two-phase sampling which is also known as double sampling was introduced in 1938. In two-phase sampling, samples are selected in phases. In the first phase, a relatively large sample of size is selected by some suitable sampling design and only information on the auxiliary variable is collected. During the second phase, a sample of size is selected either from, the sample selected in the first phase or from the entire population by using a suitable sampling design and information regarding the study and auxiliary variable is collected. Evidently, two phase sampling is useful if the auxiliary information is relatively easy and cheaper to collect than the study variable as well as if the strength of the relationship between the variables and is high. If the sample is selected in more than two phases, the resulting sampling design is called a multi-phase sampling. In this article we will consider how one can use data collected at the first phase sampling at the stages of estimation of the parameter, stratification, selection of sample and their combinations in the second phase in a unified setup applicable to any sampling design and wider classes of estimators. The problem of the estimation of variance will also be considered. The variance of estimator is essential for estimating precision of the survey estimates, calculation of confidence intervals, determination of the optimal sample sizes and for testing of hypotheses amongst others. Although, the variance is a non-negative quantity but its estimators may not be non-negative. If the estimator of variance is negative, then it cannot be used for estimation of confidence intervals, testing of hypothesis or measure of sampling error. The non-negativity properties of the variance estimators will also be studied in details.

Keywords: auxiliary information, two-phase sampling, varying probability sampling, unbiased estimators

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Authors: Shreyansh Bharadwaj, Raghavendra Kollipara, Sijoy C. D., R. K. Mittal

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Utilizing the Lorentz force to propel an electrically conductive plunger through a solenoid represents a fundamental application in electromagnetism. The parameters of the solenoid significantly influence the force exerted on the plunger, impacting its response. A parametric study has been done to understand the effect of these parameters on the force acting on the plunger. This study is done to determine the most optimal combination of parameters to obtain the fast response. Analysis has been carried out using an algorithm capable of simulating the scenario of a plunger undergoing acceleration within a solenoid. Authors have conducted an analysis focusing on several key configuration parameters of the solenoid. These parameters include the inter-layer gap (in the case of a multi-turn solenoid), different conductor diameters, varying numbers of turns, and diverse numbers of layers. Primary objective of this paper is to discern how alterations in these parameters affect the force applied to the plunger. Through extensive numerical simulations, a dataset has been generated and utilized to construct informative plots. These plots provide visual representations of the relationships between the solenoid configuration parameters and the resulting force exerted on the plunger, which can further be used to deduce scaling laws. This research endeavors to offer valuable insights into optimizing solenoid configurations for enhanced electromagnetic acceleration, thereby contributing to advancements in electromagnetic propulsion technology.

Keywords: Lorentz force, solenoid configuration, electromagnetic acceleration, parametric analysis, simulation

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Authors: James V. Luisi

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Understanding consciousness requires a synthesis of ideas from multiple disciplines, including obvious ones like psychology, biology, evolution, neurology, and neuroscience, as well as less obvious ones like protozoology, botany, entomology, carcinology, herpetology, mammalogy, and computer sciences. Furthermore, to incorporate the necessary backdrop, it is best presented in a theme of Eastern philosophy, specifically leveraging the teachings of Buddhism for its relevance to early thought on consciousness. These ideas are presented as a multi-level framework that illustrates the various aspects of consciousness within a tapestry of foundational and dependent building blocks as to how living organisms evolved to understand elements of their reality sufficiently to survive, and in the case of Homo sapiens, eventually move beyond meeting the basic needs of survival, but to also achieve survival of the species beyond the eventual fate of our planet. This is not a complete system of thought, but just a framework of consciousness gathering some of the key elements regarding the evolution of consciousness and the advent of free will, and presenting them in a unique way that encourages readers to continue the dialog and thought process as an experience to enjoy long after reading the last page. Readers are encouraged to think for themselves about the issues raised herein and to question every facet presented, as much further exploration is needed. Needless to say, this subject will remain a rapidly evolving one for quite some time to come, and it is probably in the interests of everyone to at least consider attaining both an ability and willingness to participate in the dialog.

Keywords: consciousness, sentience, intelligence, artificial intelligence, Buddhism

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: S. H. Atef, N. H. Mahmoud, S. Abdrahman, A. Fattoh

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Background: The aim of the study is to assess the diagnostic value of fibrotest and hyaluronic acid in discriminate between insignificant and significant fibrosis. Also, to find out if these parameters could replace liver biopsy which is currently used for selection of chronic hepatitis C patients eligible for antiviral therapy. Study design: This study was conducted on 52 patients with HCV RNA detected by polymerase chain reaction (PCR) who had undergone liver biopsy and attending the internal medicine clinic at Ain Shams University Hospital. Liver fibrosis was evaluated according to the METAVIR scoring system on a scale of F0 to F4. Biochemical markers assessed were: alpha-2 macroglobulin (α2-MG), apolipoprotein A1 (Apo-A1), haptoglobin, gamma-glutamyl transferase (GGT), total bilirubin (TB) and hyaluronic acid (HA). The fibrotest score was computed after adjusting for age and gender. Predictive values and ROC curves were used to assess the accuracy of fibrotest and HA results. Results: For fibrotest, the observed area under curve for the discrimination between minimal or no fibrosis (F0-F1) and significant fibrosis (F2-F4) was 0.6736 for cutoff value 0.19 with sensitivity of 84.2% and specificity of 85.7%. For HA, the sensitivity was 89.5% and specificity was 85.7% and area under curve was 0.540 at the best cutoff value 71 mg/dL. Multi-use of both parameters, HA at 71 mg/dL with fibrotest score at 0.22 give a sensitivity 89.5%, specificity 100 and efficacy 92.3% (AUC 0.895). Conclusion: The use of both fibrotest score and HA could be as alternative to biopsy in most patients with chronic hepaitis C putting in consideration some limitations of the proposed markers in evaluating liver fibrosis.

Keywords: fibrotest, liver fibrosis, HCV RNA, biochemical markers

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Authors: Gaoyuan Wang, Tian Chen

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China’s emission peak and carbon neutrality strategies lead to the transformation of development patterns and call for new green urban design thinking. This paper begins by revealing the evolution of green urban design thinking during the periods of carbon enlightenment, carbon dependency, and carbon decoupling from the perspective of the energy transition. Combined with the current energy situation, national strengths, and technological trends, the emergence of green urban design towards carbon neutrality becomes inevitable. Based on the preliminary analysis of its connotation, the characteristics of the new type of green urban design are generalized as low-carbon orientation, carbon-related objects, carbon-reduction means, and carbon-control patterns. Its theory is briefly clarified in terms of the human-earth synergism, quality-energy interconnection, and form-flow interpromotion. Then, its mechanism is analyzed combined with the core tasks of carbon neutrality, and the scope of design issues is defined, including carbon flow mapping, carbon source regulation, carbon sink construction, and carbon emission management. Finally, a multi-scale spatial response system is proposed across the region, city, cluster, and neighborhood level. The discussion aims to provide support for the innovation of green urban design theories and methods in the context of peak neutrality.

Keywords: carbon neutrality, green urban design, energy transition, theoretical exploration

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Authors: Manana Kvetenadze, Dali Nikolaishvili

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The study revealed the territorial changes of Georgia before the Soviet and Post-Soviet periods. This includes the estimation of the country's borders, its administrative-territorial arrangement change as well as the establishment of territorial losses. Georgia’s old and new borders marked on the map are of great interest. The new boundary shows the condition of 1922 year, following the Soviet period. Neither on this map nor in other works Ivane Javakhishvili talks about what he implies in the old borders, though it is evident that this is the Pre-Soviet boundary until 1921 – i.e., before the period when historical Tao, Zaqatala, Lore, Karaia represented the parts of Georgia. According to cartometric-geographical terms, the work presents detailed analysis of Georgia’s borders, along with this the comparison of research results has been carried out: 1) At the boundary line on Soviet topographic maps, the maps of 100,000; 50,000 and 25,000 scales are used; 2) According to Ivane Javakhishvili’s work ('The borders of Georgia in terms of historical and contemporary issues'). During that research, we used multi-disciplined methodology and software. We used Arc GIS for Georeferencing maps, and after that, we compare all post-Soviet Union maps, in order to determine how the borders have changed. During this work, we also use many historical data. The features of the spatial distribution of the territorial administrative units of Georgia, as well as the distribution of administrative-territorial units of the objects depicted on the map, have been established. The results obtained are presented in the forms of thematic maps and diagrams.

Keywords: border, GIS, georgia, historical cartography, old maps

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Authors: Osama M. Darwesh, Sahar H. Hassan, Abd El-Raheem R. El-Shanshoury, Shawky Z. Sabae

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Nanotechnology as multidisciplinary technology is growing rapidly with important applications in several sectors. Also, nanobiotechnology is known for the use of microorganisms for the synthesis of targeted nanoparticles. The present study deals with the green synthesis of silver nanoparticles using aquatic bacteria and the development of a biogenic nanocomposite for environmental applications. Twenty morphologically different colonies were isolated from the collected water samples from eight different locations at the Rosetta branch of the Nile Delta, Egypt. The obtained results illustrated that the most effective bacterial isolate (produced the higher amount of AgNPs after 24 h of incubation time) is isolate R3. Bacillus tequilensis was the strongest extracellular bio-manufactory of AgNPs. Biosynthesized nanoparticles had a spherical shape with a mean diameter of 2.74 to 28.4 nm. The antimicrobial activity of silver nanoparticles against many pathogenic microbes indicated that the produced AgNPs had high activity against all tested multi-antibiotic resistant pathogens. Also, the stabilized prepared AgNPs-SA nanocomposite has greater catalytic activity for the decolourization of some dyes like Methylene blue (MB) and Crystal violet. Such results represent a promising stage for producing eco-friendly, cost-effective, and easy-to-handle devices for the bioremediation of contaminated industrial wastewater.

Keywords: bioremediation, AgNPs, AgNPs-SA nanocomposite, Bacillus tequilensis, nanobiotechnology

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Rajeev jain, D. C. Tiwari, Praveena Mishra

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Nano-composite of polypyrrole/multiwalled carbon nanotubes:mangenese oxide (PPy/MWCNT:MnO2) was electrochemically deposited on the surface of carbon cloth (CC). The nano-composite was structurally characterized by FTIR, SEM, TEM and UV-Vis studies. Nano-composite was also characterized by cyclic voltammetry (CV), current voltage measurements (I-V) and the optical band gaps of film were evaluated from UV-Vis absorption studies. The PPy/MWCNT:MnO2 nano-composite was used as anode in microbial fuel cell (MFC) for sewage waste water treatment, power and coulombic efficiency measurement. The prepared electrode showed good electrical conductivity (0.1185 S m-1). This was also supported by band gap measurements (direct 0.8 eV, indirect 1.3 eV). The obtained maximum power density was 1125.4 mW m-2, highest chemical oxygen demand (COD) removal efficiency was 93% and the maximum coulombic efficiency was 59%. For the first time PPy/MWCNT:MnO2 nano-composite for MFC prepared from nano-composite electrode having the potential for the use in MFC with good stability and better adhesion of microbes is being reported. The SEM images confirm the growth and development of microbe’s colony.

Keywords: carbon cloth, electro-polymerization, functionalization, microbial fuel cells, multi walled carbon nanotubes, polypyrrole

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Odewumi Olatunde, Adegun Sunday

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Linguistic diversity is seen to complicate attempts to build a stable and cohesive political community. Hence, the challenge of integration is enormous in a multi-ethno-lingual country like Nigeria. In the same vein, justification for minority language rights claims in relation to broader political theories of justice, freedom and democracy cannot be ignored. It is in the light of the fore-going that this paper explores Nigeria’s experiments at language policy and planning(LPP) and the long drawn agitations for self-determination and linguistic freedom by the minority ethnic groups in the polity which has been exacerbated by the National Policy on Education language provisions. The paper succinctly reviews Nigeria’s LPP efforts and its attendant theater of conflicts; explores international attempts at evolving normative principles of freedom and equality for language policy and finally evaluates the position of the Nigerian LPP in the light of evolving international conventions. On this premise, it is concluded that giving a conscientious and honest implementation of the Nigerian language provisions as assessed from their face validity, the nation’s efforts could be exonerated from running afoul of any known civilized values and best practices. It is, therefore, recommended that an effectual and consistent commitment to implementation driven by a renewed political will is what is required for the nation to succeed in this direction.

Keywords: integration, rights, challenge, conventions, policy

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Mohammad Javad Behzadnia, Hamidreza Javadzadeh

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Background: Pain management is essential to surmounting multi-injured people in an overcrowded emergency setting. Its role would be more apparent when the physician encounters a mass casualty in a war zone or even a military prehospital. Having sedative and analgesic properties, rapid onset and offset effects, and maintaining the cardiovascular and respiratory contain are the main reason for selecting Ketamine as a good choice in the war zone. Methods: In a prospective interventional study in a war zone, we have selected and followed two groups of casualties for pain management. All were men with an average age of 26.6±8 y/o and 27.5 ±7 y/o in A and B groups, respectively. Group A received only Ketamine and Group B received Ketamine and diazepam. Results: This study showed that all of the injured patients who received Ketamine had experienced some agitation, and they may finally need benzodiazepines for sedation, but in group B that received benzodiazepine before or simultaneous with Ketamine, the agitation was significantly reduced. (P Value ≤0.05) Conclusion: Various factors may affect pain score and perception; patients' culture, mental health, previous drug usage, and addiction could alter the pain score in similar situations. It seems that the significant agitation is due to catecholamine release in stressful Moments of the battlefield. Accordingly, this situation could be exacerbated due to ketamine properties. Nonetheless, as a good choice in the war zone, Ketamine is now recommended to combine with benzodiazepines for procedural sedation and analgesia (PSA).

Keywords: battlefield, ketamine, benzodiazepine, pain control

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Authors: Amina Sultan, Mohamed Ghonim, Eman Oweida, Aya Abdelaziz

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Objective: To assess the diagnostic reliability of multi-detector CT in pre and post-operative evaluation of cochlear implant candidates. Material and Methods: The study includes 40 patients (18 males and 22 females); mean age 5.6 years. They were classified into two groups: Group A (20 patients): cochlear implant device was Nucleus-22 and Group B (20 patients): the device was MED-EL. Cochlear length (CL) and cochlear height (CH) were measured pre-operatively by 128-multidetector CT. Electrode length (EL) and insertion depth angle (α) were measured post-operatively by MDCT. Results: For Group A mean CL was 9.1 mm ± 0.4 SD; mean CH was 4.1 ± 0.3 SD; mean EL was 18 ± 2.7 SD; mean α angle was 299.05 ± 37 SD. Significant statistical correlation (P < 0.05) was found between preoperative CL and post-operative EL (r²=0.6); as well as EL and α angle (r²=0.7). Group B's mean CL was 9.1 mm ± 0.3 SD; mean CH was 4.1 ± 0.4 SD; mean EL was 27 ± 2.1 SD; mean α angle was 287.6 ± 41.7 SD. Significant statistical correlation was found between CL and EL (r²= 0.6) and α angle (r²=0.5). Also, a strong correlation was found between EL and α angle (r²=0.8). Significant statistical difference was detected between the two devices as regards to the electrode length. Conclusion: Multidetector CT is a reliable tool for preoperative planning and post-operative evaluation of the outcomes of cochlear implant operations. Cochlear length is a valuable prognostic parameter for prediction of the depth of electrode array insertion which can influence criteria of device selection.

Keywords: angle of insertion (α angle), cochlear implant (CI), cochlear length (CL), Multidetector Computed Tomography (MDCT)

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Authors: Monika Lipska

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Drinking water is water with a very high quality, and as such represents only 2.5% of the total quantity of all water in the world. For many years we have observed continuous increase in its consumption as a result of many factors such as: Growing world population (7 billion in 2011r.), increase of human lives comfort and – above all – the economic growth. Due to the rocketing consumption and growing costs of production of water with such high-quality parameters, we experience accelerating interest in alternative sources of obtaining potable water. One of the ways of saving this valuable material is using rainwater in the Urban Building. With an exponentially growing demand, the acquisition of additional sources of water is necessary to maintain the proper balance of all ecosystems. The first part of the paper describes what rainwater is and what are its potential sources and means of use, while the main part of the article focuses on the description of the methods of obtaining water from rain on the example of new urban building in Poland. It describes the method and installations of rainwater in the new urban building (“MBJ2030”). The paper addresses also the issue of monitoring of the whole recycling systems as well as the particular quality indicators important because of identification of the potential risks to human health. The third part describes the legal arrangements concerning the recycling of rainwater existing in different European Union countries with particular reference to Poland on example the new urban building in Warsaw.

Keywords: rainwater, potable water, non-potable water, Poland

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Authors: Giacomo Ciani

Abstract:

This paper reviews the impact of quantum noise on modern gravitational wave interferometers and explains how squeezed vacuum states are used to push the noise below the standard quantum limit. With the first detection of gravitational waves from a pair of colliding black holes in September 2015 and subsequent detections including that of gravitational waves from a pair of colliding neutron stars, the ground-based interferometric gravitational wave observatories LIGO and VIRGO have opened the era of gravitational-wave and multi-messenger astronomy. Improving the sensitivity of the detectors is of paramount importance to increase the number and quality of the detections, fully exploiting this new information channel about the universe. Although still in the commissioning phase and not at nominal sensitivity, these interferometers are designed to be ultimately limited by a combination of shot noise and quantum radiation pressure noise, which define an envelope known as the standard quantum limit. Despite the name, this limit can be beaten with the use of advanced quantum measurement techniques, with the use of squeezed vacuum states being currently the most mature and promising. Different strategies for implementation of the technology in the large-scale detectors, in both their frequency-independent and frequency-dependent variations, are presented, together with an analysis of the main technological issues and expected sensitivity gain.

Keywords: gravitational waves, interferometers, squeezed vacuum, standard quantum limit

Procedia PDF Downloads 151

Authors: Fatima Zohra Rahou, A.Guen Bouazza, B. Bouazza

Abstract:

SOI TRI GATE FinFET transistors have emerged as novel devices due to its simple architecture and better performance: better control over short channel effects (SCEs) and reduced power dissipation due to reduced gate leakage currents. As the oxide thickness scales below 2 nm, leakage currents due to tunneling increase drastically, leading to high power consumption and reduced device reliability. Replacing the SiO2 gate oxide with a high-κ material allows increased gate capacitance without the associated leakage effects. In this paper, SOI TRI-GATE FinFET structure with use of high K dielectric materials (HfO2) and SiO2 dielectric are simulated using the 3-D device simulator Devedit and Atlas of TCAD Silvaco. The simulated results exhibits significant improvements in the performances of SOI TRI GATE FinFET with gate oxide HfO2 compared with conventional gate oxide SiO2 for the same structure. SOI TRI-GATE FinFET structure with the use of high K materials (HfO2) in gate oxide results into the increase in saturation current, threshold voltage, on-state current and Ion/Ioff ratio while off-state current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, SOI-TRI Gate FinFET, high-K dielectric, Silvaco software

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Authors: Zeynep Ozkan, Cigdem Serra Uzunpinar

Abstract:

Citizenship is a legal bond that binds a person to a certain state. How constitutions define ‘the citizen’ and how they regulate the elements of citizenship have great importance in terms of individuals’ duties before the state as well as the rights they own. Especially in multi-segmented societies that contain foreign elements, it becomes necessary to examinate the institution of naturalization in terms of individuals’ duty of constitutional citizenship. The meaning of citizenship in Turkey has transformed due to the changes in practices of naturalization, in parallel to receiving huge amount of immagrants with the recent Syrian Crisis, the change in the governmental system and facing economic crisis. This transformation took place in the way of a diversion from the states’ initial motive of building the bond of citizenship with the aim of founding/sustaining political unity. Hence, rising of the economic and political motives in naturalization practices are in question, instead of objective and subjective criterias, that are traditionally used on defining the notion of nation. In this study, firstly the regime of citizenship and the legal regime of aliens in Turkish legislation will be given place. Then, the transformation, that the notion of constitutional citizenship underwent, will be studied, especially on the basis of governmental practices of naturalization. The assessment will be made in the context of legal institutions brought with the new governmental system as a result of recent constitutional amendment.

Keywords: constitutional citizenship, naturalization, naturalization practices in Turkish legal system, transformation of the notion of constitutional citizenship

Procedia PDF Downloads 118

Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

Abstract:

Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

Procedia PDF Downloads 328

Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

Abstract:

Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

Procedia PDF Downloads 133

Authors: Hossein Nikandam Kermanshah, Babak Samavatian, Akbar Hemmati Sabet, Mohammad Ahmadpanah

Abstract:

This is a quasi-experimental study that has been conducted in order to compare the effectiveness of social skills training and stress management training on self-esteem and aggression in first grade high school students. Forty-five people were selected from research community and were put randomly in there groups of social skills training, stress management training and control ones. Collecting data tools in this study was devise, self-esteem and AGQ aggression questionnaire. Self-esteem and aggression questionnaires has been conducted as the pre-test and post-test. Social skills training and stress management groups participated in eight 1.5 hour session in a week. But control group did not receive any therapy. For descriptive analysis of data, statistical indicators like mean, standard deviation were used, and in inferential statistics level multi variable covariance analysis have been used. The finding result show that group training social skills and stress management is significantly effective on the self-esteem and aggression, there is a meaningful difference between training social skills and stress management on self-esteem that the preference is with group social skills training, in the difference between group social skills training and stress management on aggression, the preference is with group stress management.

Keywords: social skill training, stress management training, self-esteem aggression, psychological sciences

Procedia PDF Downloads 469