Search results for: feed forward network

Authors: Awadhesh Kishore

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One of the most unique characteristics of rabbit feeding behaviour is caecotrophy, which involves the excretion and immediate consumption of specific faeces known as soft faeces. Caecotrophy in rabbits is the instinctual behaviour of eating soft faeces; reduced caecotrophy decreases rabbit growth and lipid synthesis in the liver. Caecotroph ingestion is highest when rabbits are fed a diet high in indigestible fibre. The colon produces two types of waste: hard and soft pellets. The hard pellets are expelled, but the soft pellets are re-ingested by the rabbit directly upon being expelled from the anus by twisting itself around and sucking in those pellets as they emerge from the anus. The type of alfalfa hay in the feed of the rabbits does not affect volatile fatty acid concentration, the pattern of fermentation, or pH in the faeces. The cecal content and the soft faeces contain significant amounts of retinoids and carotenoids, while in the tissues (blood, liver, and kidney), these pigments do not occur in substantial amounts. Preventing caecotrophy reduced growth and altered lipid metabolism, depressing the development of new approaches for rabbit feeding and production. Relative abundance is depressed for genes related to metabolic pathways such as vitamin C and sugar metabolism, vitamin B2 metabolism, and bile secretion. The key microorganisms that regulate the rapid growth performance of rabbits may provide useful references for future research and the development of microecological preparations.

Keywords: caecocolonic microorganisms, caecotrophy, fasting caecotrophy, rabbits, soft pellets

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Authors: Cíntia Martins Sanches

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In the first part of Phoenissae of Seneca, Antigone is a guide to Oedipus, and they leave Thebes: he is blind searching for death (inflicting the punishment himself wished on the killer of Laius, ie exile and death); she is trying to convince him to give up such punishment and bring him back to Thebes. Concerning Oedipus lines, we observed a high frequency of Latin neuter in the treatment the protagonist gave to his daughter Antigone. We considered in this study that such frequency may be related to the sanctification of the daughter, who is seen by him as an enlightened being and without defects, free of the human condition (which takes on the existence of failures by essence). This study, thus, puts forward an analysis of the passages the said feature is present, relating them to the effect of meaning found in each occurrence. As part of a doctorate, this study investigates the stylistic idiom of Seneca in the Oedipus and Phoenissae tragedies, aiming at translating both tragedies expressively. The concept of stylistic idiom concerns the stylistic affinity required for a translation to be equivalent to the source text. In this wise, this study inquires into how the Latin text is organized poetically, pointing out the expressive features frequently appearing in both dramas. The method we used is based on the Semiotics theory — observing how connotation, ie a language use in which prevails the poetic function, naturally polysemous, acts to achieve each expressive effect.

Keywords: antigone, neuter, Oedipus, Phoenissae, Seneca

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Authors: Susana Olmos, Catherine Spencer

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Every year our School in DIT (Dublin Institute of Technology) hosts approximately 80 Erasmus students from partner universities across Europe. Our own students are required to spend a compulsory 3rd year abroad on study and/or work placements. This is an extremely rewarding experience for all of the students, however, it can also be a challenging one. With this in mind, we started a project which aimed to make this transition as easy and productive as possible. The project, which is called MEET: Maximise the Erasmus Experience Together, focuses on the students’ own active engagement in learning and preparation – outside of the classroom –and their own self-directed pursuit of opportunities to develop their confidence and preparedness, which would work as an important foundation for the transformative learning that study abroad implies. We focussed on creating more structured opportunities where Erasmus students from our partner universities (currently studying at DIT) and our second-year students could interact and learn from each other, and in so doing improve both their language and intercultural skills. Our experience so far has been quite positive and we have seen how students taking part in this project have developed as autonomous learners as well as enhanced both their linguistic and intercultural knowledge. As the linguistic element of our project was one of our main priorities, we asked the students to keep a reflective diary on the activities that were organised by the group in the TL. Also, we use questionnaires as well as personal interviews to assess their development. However, there are challenges and proposals we would make to bring this project forward for the near future.

Keywords: erasmus, intercultural competence, linguistic competence, extra curriculum activities

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Authors: Yu-Chen Luo, Wan-Tzu Yen, I-Ping Liu, Po-Hsuan Yeh, Yuh-Lang Lee

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The use of a Pt electrode leads to high catalytic efficiency in the ethanol electro-oxidation. However, the carbon monoxide (CO) released in the reaction will poison the Pt surfaces, lowering the electrocatalytic activity. In this study, composite electrodes are prepared to overcome the poisoning issue, and the related electro-oxidation behaviors are studied by surface-enhanced infrared absorption spectroscopy (SEIRAS) and cyclic voltammetry (CV). An electroless plating method is utilized to deposit Pt catalytic layers on the Pd film-coated FTO substrates. According to the SEIRAS spectra, the carbon dioxide signal of the Pt/Pd composite electrode is larger than that of the Pt one, whereas the CO signal of the composite electrode is relatively smaller. This result suggests that the studied Pt/Pd electrode has a better ability against CO poisoning. The CV analyses are conducted in alkaline environments, and current densities related to the ethanol oxidation in the forward scan (If) and to the CO poisoning in the backward scan (Ib) are measured. A higher ratio of If to Ib (If/Ib) usually represents a better ability against the poisoning effect. The If/Ib values are 2.53 and 2.07 for the Pt and Pt/Pd electrodes, respectively, which is possibly attributed to the increasing ability of CO adsorption of Pt electrode. Despite the lower If/Ib, the Pt/Pd composite electrode shows a higher ethanol oxidation performance in the alkaline system than the Pt does. Furthermore, its stability is also superior.

Keywords: cyclic voltammogram, electroless deposition, ethanol electro-oxidation, surface-enhanced infrared absorption spectroscopy

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Rafiu Babatunde Ibrahim, Richard Oluseyi Taiwo, Abiodun Toheeb Akintunde

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The relationship between road transport infrastructure and commercial activities in Nigeria has been a topical issue and identified as one of the crucial components for economic development in the country. This study examines road transport infrastructure and commercial activities along selected roads in Ede, Nigeria. The study assesses the characteristics of the selected roads, the condition of road infrastructure, the degree of road network connectivity, maintenance culture for the road infrastructure as well as commercial activities along identified roads in the study area. Stratified Sampling Techniques were used to partition the study area into core, Intermediate and Suburb Township zones. Roads were also classified into Major, Distributor and Access Roads. Field observation and measurement, as well as a questionnaire, were used to obtain primary data from 246 systematically sampled respondents along the roads selected, and they were analyzed using descriptive and inferential statistics. The study revealed that most of the roads were characterized by an incidence of potholes. A total of 448 potholes were observed, where Olowoibida Road accounted for (19.0%), Federal Polytechnic Road (17.4%), and Back to Land Road (16.3%). The majority of the selected roads have no street lights and are of open drainage systems. Also, the condition of road surfaces was observed to be deteriorating. Road network connectivity of the study area was found to be poorly connected with 11% using the alpha index and 40% of Gamma index. It was found that the tailoring business (39) is predominant on major roads and Distributor Roads, while petty trading (35) is dominant on the access road. Results of correlation analysis (r = 0.242) show that there is a low positive correlation between road infrastructure and commercial activities; the significant relationships have indeed explained how important it is in influencing commercial activities across the study area. The study concluded by emphasizing the need for the provision of more roads and proper maintenance of the existing ones. This will no doubt improve the commercial activities along the roads in the study area.

Keywords: road transport, infrastructure, commercial activities, maintenance culture

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Authors: Baharak Mousapour

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Creating public spaces which are tailored for the specific demands of the individuals is one of the challenges for the contemporary interior designers. Improving the general knowledge as well as providing a forum for all walks of life to exploit is one of the objectives of a public library. In this regard, interior design in consistent with the demands of the individuals is of paramount importance. Seemingly, study spaces, in particular, those in close relation to the personalized sector, have proven to be challenging, according to the literature. To address this challenge, attributes of individuals, namely, perception of people from public spaces and their interactions with the so-called spaces, should be analyzed to provide interior designers with something to work on. This paper follows the analytic-descriptive research methodology by outlining case study libraries which have personalized public libraries with the investigation of the type of personalization as its primary objective and (I) recognition of physical schedule and the know-how of the spatial connection in indoor design of a library and (II) analysis of each personalized space in relation to other spaces of the library as its secondary objectives. The significance of the current research lies in the concept of personalization as one of the most recent methods of attracting people to libraries. Previous research exists in this regard, but the lack of data concerning personalization makes this topic worth investigating. Hence, this study aims to put forward approaches through real-case studies for the designers to deal with this concept.

Keywords: interior design, library, library design, personalization

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Authors: Ciaran Smiddy, Fergus Nugent, Karen Fitzmaurice

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A measure of prescribing and administration of Antimicrobial Prophylaxis before and during Covid-19(2019 vs. 2021) was desired to assess how these were affected by Covid-19. Antimicrobial Prophylaxis was assessed for 60 patients, under 3 Orthopaedic Consultants, against local guidelines. The study found that compliance with guidelines improved significantly, from 60% to 83%, but Appropriate use of Vancomycin reduced from 37% to 29%.

Keywords: antimicrobial stewardship, prescribing, spinal surgery, vancomycin

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Pankaj Chandna, Dinesh Kumar

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The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology

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Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

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Authors: N. P. Eswara Reddy, S. Thahir Basha

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Here, we report the success stories of potential leaf, seed and root endophytes against soil borne as well as foliar plant pathogens which are nutritionally adequate and safe for consumption. Endophytes are the microorganisms that reside asymptomatically in the tissues of higher plants are a robust source of potential biocontrol agents and it is presumed that the survival ability of endophytes may be better when compared to phylloplane microflora. Of all the 68 putative leaf endophytes, the endophytes viz., EB9 (100%), and EB35 (100%) which were superior in controlling Colletotrichum gloeosporioides causing mango anthracnose were identified as Brevundimonas bullata (EB09) and Bacillus thuringiensis (EB35) and further delayed in ripening of mango fruits up to 21 days. As a part, the seed endophyte GSE-4 was identified as Archoromobacter spp. against Sclerotium rolfsii causing stem rot of groundnut and the root endophyte REB-8 against Rhizoctonia bataticola causing dry root rot of chickpea was identified as Bacillus subtilis. Both recorded least percent disease incidence (PDI) and increased plant growth promotion, respectively. Further, the novel Bacillus subtilis (SEB-2) against Macrophomina pahseolina causing charcoal rot of sunflower provides an ample scope for exploring the endophytes at large scale. The talc-based formulations of these endophytes developed can be commercialized after toxicological studies. At the bottom line these unexplored endophytes are the need of the hour against aggressive plant pathogens and to maintain the quality and abundance of food and feed and also to fetch marginal economy to the farmers will be discussed.

Keywords: endophytes, plant pathogens, commercialization, abundance of food

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Authors: Jun-ya Nagase

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Recently, the need of colonoscopy is increasing because of the rise of colonic disorder including cancer of the colon. However, current colonoscopy depends on doctor's skill strongly. Therefore, a large intestine endoscope that does not depend on the techniques of a doctor with high safety is required. In this research, we aim at development a novel large intestine endoscope that can realize safe insertion without specific techniques. A wheel movement type robot, a snake-like robot and an earthworm-like robot are all described in the relevant literature as endoscope robots that are currently studied. Among them, the tracked crawler robot can travel by traversing uneven ground flexibly with a crawler belt attached firmly to the ground surface. Although conventional crawler robots have high efficiency and/or high ground-covering ability, they require a comparatively large space to move. In this study, a small cylindrical crawler robot inspired by amoeba locomotion, which does not need large space to move and which has high ground-covering ability, is proposed. In addition, we developed a prototype of the large intestine endoscope using the proposed crawler mechanism. Experiments have demonstrated smooth operation and a forward movement of the robot by application of voltage to the motor. This paper reports the structure, drive mechanism, prototype, and experimental evaluation.

Keywords: tracked-crawler, endoscopic robot, narrow path, amoeba locomotion.

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Authors: Manel Hammami, Gabriele Grandi

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In recent years, multilevel inverters have become more attractive for single-phase photovoltaic (PV) systems, due to their known advantages over conventional H-bridge pulse width-modulated (PWM) inverters. They offer improved output waveforms, smaller filter size, lower total harmonic distortion (THD), higher output voltages and others. The most common multilevel converter topologies, presented in literature, are the neutral-point-clamped (NPC), flying capacitor (FC) and Cascaded H-Bridge (CHB) converters. In both NPC and FC configurations, the number of components drastically increases with the number of levels what leads to complexity of the control strategy, high volume, and cost. Whereas, increasing the number of levels in case of the cascaded H-bridge configuration is a flexible solution. However, it needs isolated power sources for each stage, and it can be applied to PV systems only in case of PV sub-fields. In order to improve the ratio between the number of output voltage levels and the number of components, several hybrids and asymmetric topologies of multilevel inverters have been proposed in the literature such as the FC asymmetric H-bridge (FCAH) and the NPC asymmetric H-bridge (NPCAH) topologies. Another asymmetric multilevel inverter configuration that could have interesting applications is the cascaded asymmetric H-bridge (CAH), which is based on a modular half-bridge (two switches and one capacitor, also called level doubling network, LDN) cascaded to a full H-bridge in order to double the output voltage level. This solution has the same number of switches as the above mentioned AH configurations (i.e., six), and just one capacitor (as the FCAH). CAH is becoming popular, due to its simple, modular and reliable structure, and it can be considered as a retrofit which can be added in series to an existing H-Bridge configuration in order to double the output voltage levels. In this paper, an original and effective method for the analysis of the DC-link voltage ripple is given for single-phase asymmetric H-bridge multilevel inverters based on level doubling network (LDN). Different possible configurations of the asymmetric H-Bridge multilevel inverters have been considered and the analysis of input voltage and current are analytically determined and numerically verified by Matlab/Simulink for the case of cascaded asymmetric H-bridge multilevel inverters. A comparison between FCAH and the CAH configurations is done on the basis of the analysis of the DC and voltage ripple for the DC source (i.e., the PV system). The peak-to-peak DC and voltage ripple amplitudes are analytically calculated over the fundamental period as a function of the modulation index. On the basis of the maximum peak-to-peak values of low frequency and switching ripple voltage components, the DC capacitors can be designed. Reference is made to unity output power factor, as in case of most of the grid-connected PV generation systems. Simulation results will be presented in the full paper in order to prove the effectiveness of the proposed developments in all the operating conditions.

Keywords: asymmetric inverters, dc-link voltage, level doubling network, single-phase multilevel inverter

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: Hasan Bulent Kantarci

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This paper examine how Zakat provide a fair income redistribution and struggle with poverty. To provide a fair income redistribution and struggle with poverty take place among the fundamental tasks of all countries. Each country seeks a solution for this problem according to their political, economical and administrative styles through applying various economic and financial policies. The same situation gets handled via zakat association in the Islam. Nowadays, we observe different versions of zakat in developed countries. The applications such as negative income tax denote merely a difference from the zakat being applied almost the same way under changed names. But the minimum values to donate the zakat (e.g. 85 gr. gold and 40 animals) get altered and various amounts are put into practice. It might be named as negative income tax instead of zakat, nonetheless, these applications are based on the Holy Koran and the hadith released 1400 years ago. Besides, considering the savage and slavery in the world at those times, we might easily recognize the true value of the zakat applied the first time then in Islamic system. Through zakat is enabled an income transfer by the government so that the poor could reach the minimum level of life standard. To whom the zakat would be donated was not left to people’s heart and encouraged to determine according to objective criteria. Since the zakat is obligatory, the transfer do not get forward by hand but via the government and get distributed, which requires a vast government organization. Through applying the zakat as it must be would achieve to reduce the poverty mostly and ensuring the fair income redistribution.

Keywords: Islamic finance, zakat, income redistribution, circle of poverty, negatif income tax

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Norbert Magyar, Jozsef Kovacs, Peter Tanos, Balazs Trasy, Tamas Garamhegyi, Istvan Gabor Hatvani

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Water is one of the most important common resources, and as a result of urbanization, agriculture, and industry it is becoming more and more exposed to potential pollutants. The prevention of the deterioration of water quality is a crucial role for environmental scientist. To achieve this aim, the operation of monitoring networks is necessary. In general, these networks have to meet many important requirements, such as representativeness and cost efficiency. However, existing monitoring networks often include sampling sites which are unnecessary. With the elimination of these sites the monitoring network can be optimized, and it can operate more economically. The aim of this study is to illustrate the applicability of the CCDA (Combined Cluster and Discriminant Analysis) to the field of water quality monitoring and optimize the monitoring networks of a river (the Danube), a wetland-lake system (Kis-Balaton & Lake Balaton), and two surface-subsurface water systems on the watershed of Lake Neusiedl/Lake Fertő and on the Szigetköz area over a period of approximately two decades. CCDA combines two multivariate data analysis methods: hierarchical cluster analysis and linear discriminant analysis. Its goal is to determine homogeneous groups of observations, in our case sampling sites, by comparing the goodness of preconceived classifications obtained from hierarchical cluster analysis with random classifications. The main idea behind CCDA is that if the ratio of correctly classified cases for a grouping is higher than at least 95% of the ratios for the random classifications, then at the level of significance (α=0.05) the given sampling sites don’t form a homogeneous group. Due to the fact that the sampling on the Lake Neusiedl/Lake Fertő was conducted at the same time at all sampling sites, it was possible to visualize the differences between the sampling sites belonging to the same or different groups on scatterplots. Based on the results, the monitoring network of the Danube yields redundant information over certain sections, so that of 12 sampling sites, 3 could be eliminated without loss of information. In the case of the wetland (Kis-Balaton) one pair of sampling sites out of 12, and in the case of Lake Balaton, 5 out of 10 could be discarded. For the groundwater system of the catchment area of Lake Neusiedl/Lake Fertő all 50 monitoring wells are necessary, there is no redundant information in the system. The number of the sampling sites on the Lake Neusiedl/Lake Fertő can decrease to approximately the half of the original number of the sites. Furthermore, neighbouring sampling sites were compared pairwise using CCDA and the results were plotted on diagrams or isoline maps showing the location of the greatest differences. These results can help researchers decide where to place new sampling sites. The application of CCDA proved to be a useful tool in the optimization of the monitoring networks regarding different types of water bodies. Based on the results obtained, the monitoring networks can be operated more economically.

Keywords: combined cluster and discriminant analysis, cost efficiency, monitoring network optimization, water quality

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Authors: Rahul Malhotra

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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Authors: Diogo Ribeiro, Teresa Neto, Ricardo Santos, Maria Portela, Alexandra Trincão

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This article describes a set of innovating student recruitment strategies in a 1st cycle course of Civil Engineering, in particular the Civil Engineering Degree from the School of Engineering - Polytechnic of Porto (ISEP-PP). The strategies described were two-fold, targeting, for one, the increment on the number of admissions for the degree’s first year and two, promoting the re-entry of students who, for whatever reason, interrupted their studies. For the first objective, teacher-student binomials were set, whilst for the second, personalized contacts and assistance were provided. The main initiatives were promoted by the team of degree directors and were upheld with the participation and in consonance with the School’s external relations office. These initiatives were put forward as an attempt to minimize the impact of a national and international crisis on the AEC industry when the sustainability of the course was at risk. The implementation of these strategies was assessed on basis of a statistical analysis of the data collected from official sources and by surveys promoted. The results showed that the re-entry boost of former students, attending classes scattered on the three curricular years, secured registrations on some Curricular Units (UC’s) which more than doubled their numbers. Accompanied by a still incipient but regained interest on Civil Engineering it was possible in the short span of three years to reset the number of new students from less than 10 to the currently maximum allowed of 75, and so invert the tendency of an abrupt decline on the total number of students enrolled on the degree.

Keywords: civil engineering, monitoring, performance indicators, strategies, student recruitment

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Authors: Satyananda Patra, Venugopal Rayasam

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The quality of pellets produced is affected by quality and type of green pellets, amount of addition of binders and fluxing agents along with the provided firing conditions. The green pellet quality depends upon chemistry, mineralogy and granulometry of fines used for pellet making, the feed size, its moisture content and porosity. During firing of green pellets, ingredients present within reacts to form different phases and microstructure. So in turn, physical and metallurgical properties of pellets are influenced by amount and type of binder and flux addition, induration time and temperature. During iron making process, the metallurgical properties of fired pellets are decided by the type and amount of these phases and their chemistry. Green pelletizing and induration studies have been already carried out with magnetite and hematite ore fines but for Indian iron ores of high alumina content showing different pelletizing characters, these studies cannot be directly interpreted. The main objective of proposed research work is to understand the green pelletizing process and determine the water bentonite interaction at different levels. Swelling behavior of bentonite and microstructure of the green pellet are investigated. Conversion of iron ore fines into pellets, the key raw material and process variables that influence the pellet quality needs to be identified and a correlation should be established between them.

Keywords: iron ore, pelletization, binders, green pellets, microstructure

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Authors: Varsha Kheradiya, Ganga Prasad Pandey

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The use of wearable antennas is rising because wireless devices become small. The wearable antenna is part of clothes used in communication applications, including energy harvesting, medical application, navigation, and tracking. In current years, Antennas embroidered on clothes, conducting antennas based on fabric, polymer embedded antennas, and inkjet-printed antennas are all attractive ways. Also shows the analysis required for wearable antennas, such as wearable antennae interacting with the human body. The primary requirements for the antenna are small size, low profile minimizing radiation absorption by the human body, high efficiency, structural integrity to survive worst situations, and good gain. Therefore, research in energy harvesting, biomedicine, and military application design is increasingly favoring flexible wearable antennas. Textile materials that are effectively used for designing and developing wearable antennas for body area networks. The wireless body area network is primarily concerned with creating effective antenna systems. The antenna should reduce their size, be lightweight, and be adaptable when integrated into clothes. When antennas integrate into clothes, it provides a convenient alternative to those fabricated using rigid substrates. This paper presents a study of U slot loaded wearable textile antenna. U slot patch antenna design is illustrated for wideband from 1GHz to 6 GHz using textile material jeans as substrate and pure copper polyester taffeta fabric as conducting material. This antenna design exhibits dual band results for WLAN at 2.4 GHz and 3.6 GHz frequencies. Also, study U slot position horizontal and vertical shifting. Shifting the horizontal positive X-axis position of the U slot produces the third band at 5.8 GHz.

Keywords: microstrip patch antenna, textile material, U slot wearable antenna, wireless body area network

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Authors: Azizza Mala, Babo Fadlalla, Elnour Mohamed, Siran Wang, Junfeng Li, Tao Shao

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Sweet sorghum is considered one of the best plants for silage production and is now a more important feed crop in many countries worldwide. It is simple to ensile because of its high water-soluble carbohydrates (WSC) concentration and low buffer capacity. This study investigated the effect of adding Pediococcus acidilactici AZZ5 and Lactobacillus plantarum AZZ4 isolated from elephant grass on the fermentation quality of sweet sorghum silage. One commercial bacteria Lactobacillus Plantarum, Ecosyl MTD/1(C.B.)), and two strains were used as additives Pediococcus acidilactici (AZZ5), Lactobacillus plantarum subsp. Plantarum (AZZ4) at 6 log colony forming units (cfu)/g of fresh sweet sorghum grass in laboratory silos (1000g). After 15, 30, and 60 days, the silos for each treatment were opened. All of the isolated strains enhanced the silage quality of sweet sorghum silage compared to the control, as evidenced by significantly (P < 0.05) lower ammonia nitrogen (NH3-N) content and undesirable microbial counts, as well as greater lactic acid (L.A.) contents and lactic acid/acetic acid (LA/AA) ratios. In addition, AZZ4 performed better than all other inoculants during ensiling, as evidenced by a significant (P < 0.05) reduction in pH and ammonia-N contents and a significant increase in lactic acid contents.

Keywords: fermentation, lactobacillus plantarum, lactic acid bacteria, pediococcus acidilactic, sweet sorghum

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Layan Kateb, Jawaher Ragban, Rawia Alamri, Rewaa Alhazmi

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This paper evaluates user satisfaction with the AI functionality of Coconote, an innovative app designed to transform raw input -documents, voice recordings, and video recordings- into structured study materials such as flashcards, study guides, and transcripts. Leveraging AI-driven natural language processing and summarization algorithms, Coconote aims to streamline the study process by providing personalized, accessible, and accurate learning tools. To measure user satisfaction, we conducted a survey among 20 participants, including students, educators, and professionals, who tested the app’s core features over a two-week period. The survey assessed criteria such as ease of use, accuracy of generated materials, and perceived value in enhancing productivity. Results indicate high satisfaction levels with the app’s ability to produce coherent and concise outputs, with 83% of respondents reporting improved study efficiency. However, feedback highlighted areas for improvement, including occasional inaccuracies in transcription and customization limitations in flashcard formatting. This study demonstrates the potential of AI to transform learning methods and identifies key areas for refinement in user-centric design. Coconote represents a step forward in leveraging AI to enhance educational technology

Keywords: tools for students, artificial intelligence in education, AI study tool, ethical AI tools

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Authors: Nurunnahar Akter, Elena Kulinskaya, Nicholas Steel, Ilyas Bakbergenuly

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Although Hormone Replacement Therapy (HRT) is an effective treatment in ameliorating menopausal symptoms, it has mixed effects on different health outcomes, increasing, for instance, the risk of breast cancer. Because of this, many symptomatic women are left untreated. Untreated menopausal symptoms may result in other health issues, which eventually put an extra burden and costs to the health care system. All-cause mortality analysis may explain the net benefits and risks of the HRT therapy. However, it received far less attention in HRT studies. This study investigated the impact of HRT on all-cause mortality using electronically recorded primary care data from The Health Improvement Network (THIN) that broadly represents the female population in the United Kingdom (UK). The study entry date for this study was the record of the first HRT prescription from 1984, and patients were followed up until death or transfer to another GP practice or study end date, which was January 2017. 112,354 HRT users (cases) were matched with 245,320 non-users by age at HRT initiation and general practice (GP). The hazards of all-cause mortality associated with HRT were estimated by a parametric Weibull-Cox model adjusting for a wide range of important medical, lifestyle, and socio-demographic factors. The multilevel multiple imputation techniques were used to deal with missing data. This study found that during 32 years of follow-up, combined HRT reduced the hazard ratio (HR) of all-cause mortality by 9% (HR: 0.91; 95% Confidence Interval, 0.88-0.94) in women of age between 46 to 65 at first treatment compared to the non-users of the same age. Age-specific mortality analyses found that combined HRT decreased mortality by 13% (HR: 0.87; 95% CI, 0.82-0.92), 12% (HR: 0.88; 95% CI, 0.82-0.93), and 8% (HR: 0.92; 95% CI, 0.85-0.98), in 51 to 55, 56 to 60, and 61 to 65 age group at first treatment, respectively. There was no association between estrogen-only HRT and women’s all-cause mortality. The findings from this study may help to inform the choices of women at menopause and to further educate the clinicians and resource planners.

Keywords: hormone replacement therapy, multiple imputations, primary care data, the health improvement network (THIN)

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Authors: Robin C. Ladwig

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The future of work becomes less predictable, which requires increasing the adaptability of organizations to social and work changes. Society is transforming regarding gender identity in the sense that more people come forward to identify as trans and gender diverse (TGD). Organizations are ill-equipped to provide a safe and encouraging work environment by lacking inclusive organizational structures. The qualitative multi-method research about TGD inclusivity in the workplace explores the enablers and barriers for TGD individuals to satisfactory engage in the work environment and organizational culture. Furthermore, these TGD insights are analyzed about their organizational implications and awareness from a leadership and management perspective. The semi-structured online interviews with TGD individuals and the photo-elicit open-ended questionnaire addressed to leadership and management in diversity, career development, and human resources have been analyzed with a critical grounded theory approach. Findings demonstrated the significance of TGD voices, the support of leadership and management, as well as the synergy between voices and leadership. Hence, it indicates practical implications such as the revision of exclusive language used in policies, data collection, or communication and reconsideration of organizational decision-making by leaders to include TGD voices.

Keywords: future of work, occupational identity, organisational decision-making, trans and gender diverse identity

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Authors: Saikat Majumdar, D. C. Kalita

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The Agriculture sector plays an important role in the rural economy of India. It is the backbone of our Indian economy and is the dominant sector in terms of employment and livelihood. Agriculture still contributes significantly to export earnings and is an important source of raw materials as well as of demand for many industrial products particularly fertilizers, pesticides, agricultural implements and a variety of consumer goods, etc. The performance of the agricultural sector influences the growth of Indian economy. According to the 2011 Agricultural Census of India, an estimated 61.5 percentage of rural populations are dependent on agriculture. Proper Agricultural infrastructure has the potential to transform the existing traditional agriculture into a most modern, commercial and dynamic farming system in India through its diffusion of technology. The rate of adoption of modern technology reflects the progress of development in agricultural sector. The adoption of any improved agricultural technology is also dependent on the development of road infrastructure or road network. The present study was consisting of 300 sample farmers out which 150 samples was taken from the developed area and rest 150 samples was taken from underdeveloped area. The samples farmers under develop and underdeveloped areas were collected by using Multistage Random Sampling procedure. In the first stage, North 24 Parganas District have been selected purposively. Then from the district, one developed and one underdeveloped block was selected randomly. In the third phase, 10 villages have been selected randomly from each block. Finally, from each village 15 sample farmers was selected randomly. The extents of adoption of technology in different areas were calculated through various parameters. These are percentage area under High Yielding Variety Cereals, percentage area under High Yielding Variety pulses, area under hybrids vegetables, irrigated area, mechanically operated area, amount spent on fertilizer and pesticides, etc. in both developed and underdeveloped areas of North 24 Parganas District, West Bengal. The percentage area under High Yielding Variety Cereals in the developed and underdeveloped areas was 34.86 and 22.59. 42.07 percentages and 31.46 percentages for High Yielding Variety pulses respectively. In the case the area under irrigation it was 57.66 and 35.71 percent while for the mechanically operated area it was 10.60 and 3.13 percent respectively in developed and underdeveloped areas of North 24 Parganas district, West Bengal. It clearly showed that the extent of adoption of technology was significantly higher in the developed area over underdeveloped area. Better road network system helps the farmers in increasing his farm income, farm assets, cropping intensity, marketed surplus and the rate of adoption of new technology. With this background, an attempt is made in this paper to study the impact of Agricultural Infrastructure on the adoption of modern technology in agriculture in North 24 Parganas District, West Bengal.

Keywords: agricultural infrastructure, adoption of technology, farm income, road network

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: I. S. R. Butswat, D. Zahraddeen

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This study identified and described some skill-based and necessity-driven entrepreneurship in animal agriculture (AA). AA is an integral segment of the world food industry, and provides a good and rapid source of income. The contribution of AA to the Sub-Saharan economy is quite significant, and there are still large opportunities that remain untapped in the sector. However, it is imperative to understand, simplify and package the various components of AA in order to pave way for rapid wealth creation, poverty eradication and women empowerment programmes in sub-Saharan Africa and other developing countries. The entrepreneurial areas of AA highlighted were animal breeding, livestock fattening, dairy production, poultry farming, meat production (beef, mutton, chevon, etc.), rabbit farming, wool/leather production, animal traction, animal feed industry, commercial pasture management, fish farming, sport animals, micro livestock production, private ownership of abattoirs, slaughter slabs, animal parks and zoos, among others. This study concludes that reproductive biotechnology such as oestrous synchronization, super-/multiple ovulation, artificial insemination and embryo transfer can be employed as a tool for improvement of genetic make-up of low-yielding animals in terms of milk, meat, egg, wool, leather production and other economic traits that will necessitate sustainable job and wealth creations.

Keywords: animal, agriculture, entreprenurship, wealth

Procedia PDF Downloads 250