Search results for: feed selection

Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

Procedia PDF Downloads 505

Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: M. Fozan Ur Rab, Mahrukh, M. Alam, N. Sheikh

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The purpose of this study is to analyze various high lift low Reynolds number airfoils using two-dimensional Computational Fluid Dynamics (CFD) code in the isolated flow field and select optimum airfoil to suit the motorsports application. The airfoil is selected after comparing the stall behavior, transition location, pressure recovery, pressure distribution and boundary layer characteristics of various airfoils. The prime consideration while selecting airfoil is highest Cl while achieving the sustainable performance over a range of Reynolds numbers encountered on the race track. The increase in Cl is always accompanied by the increase in Cd but this must be compromised since the main goal is to increase an aerodynamic grip. It is always desirable to increase the down-force in Formula One (F1)/Formula Student (FS) to gain reduction in lap time. This paper establishes the criteria for selection of high lift low Reynolds number airfoil while considering various parameters which affect the performance of airfoils.

Keywords: aerodynamics, airfoil, downforce, formula student, lap time

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Authors: Brayan S. Pabón, R. Ricardo Moreno, Edith Gonzalez

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Inside the wide Colombian natural fiber set is the banana stem leaf, known as Calceta de Plátano, which is a material present in several regions of the country and is a fiber extracted from the pseudo stem of the banana plant (Musa paradisiaca) as a regular maintenance process. Colombia had a production of 2.8 million tons in 2007 and 2008 corresponding to 8.2% of the international production, number that is growing. This material was selected to be studied because it is not being used by farmers due to it being perceived as a waste from the banana harvest and a propagation pest agent inside the planting. In addition, the Calceta does not have industrial applications in Colombia since there is not enough concrete knowledge that informs us about the properties of the material and the possible applications it could have. Based on this situation the industrial design is used as a link between the properties of the material and the need to transform it into industrial products for the market. Therefore, the project identifies potential design attributes that the banana stem leaf can have for product development. The methodology was divided into 2 main chapters: Methodology for the material recognition: -Data Collection, inquiring the craftsmen experience and bibliography. -Knowledge in practice, with controlled experiments and validation tests. -Creation of design attributes and material profile according to the knowledge developed. Moreover, the Design methodology: -Application fields selection, exploring the use of the attributes and the relation with product functions. -Evaluating the possible fields and selection of the optimum application. -Design Process with sketching, ideation, and product development. Different protocols were elaborated to qualitatively determine some material properties of the Calceta, and if they could be designated as design attributes. Once defined, performed and analyzed the validation protocols, 25 design attributes were identified and classified into 4 attribute categories (Environmental, Functional, Aesthetics and Technical) forming the material profile. Then, 15 application fields were defined based on the relation between functions of product and the use of the Calceta attributes. Those fields were evaluated to measure how much are being used the functional attributes. After fields evaluation, a final field was defined , influenced by traditional use of the fiber for packing food. As final result, two products were designed for this application field. The first one is the Multiple Container, which works to contain small or large-thin pieces of food, like potatoes chips or small sausages; it allows the consumption of food with sauces or dressings. The second is the Chorizo container, specifically designed for this food due to the long shape and the consumption mode. Natural fiber research allows the generation of a solider and a more complete knowledge about natural fibers. In addition, the research is a way to strengthen the identity through the investigation of the proper and autochthonous, allowing the use of national resources in a sustainable and creative way. Using divergent thinking and the design as a tool, this investigation can achieve advances in the natural fiber handling.

Keywords: banana stem leaf, Calceta de Plátano, design attributes, natural fibers, product design

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Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: Dinmukhamed T., Vassiliy S.

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This article suggests the idea of fitting clothes and accessories based on augmented reality. A logical data model has been developed, taking into account the decision-making module (colors, style, type, material, popularity, etc.) based on personal data (age, gender, weight, height, leg size, hoist length, geolocation, photogrammetry, number of purchases of certain types of clothing, etc.) and statistical data of the purchase history (number of items, price, size, color, style, etc.). Also, in order to provide information to the user, it is planned to develop an augmented reality system using a QR code. This system of selection and fitting of clothing and accessories based on augmented reality will be used in stores to reduce the time for the buyer to make a decision on the choice of clothes.

Keywords: augmented reality, online store, decision-making module, like QR code, clothing store, queue

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Authors: Marianna De Almeida

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Greek secondary education is a highly selective system with regard to the access of students to Greek universities. Since access from elementary to lower secondary education and afterward to upper secondary education is rather liberal and almost free of selective mechanisms, the basic selection process comes after graduating from upper secondary school into play when students go through a highly selective process for university entry. This structure is responsible for the experience of extreme stress on the part of the candidates during a period of at least two years before the entrance examination leading to a radical change in students' everyday life routines. Instead of the school being an important agent for academic and psychological support, it seems that other agents, such as the informal private preparatory school and the student's families, take on the supportive role.

Keywords: stress, entrance examinations, family support, secondary education

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Authors: M. A. Moghaddas, M. Short, N. Wiley, A. Y. Yi, K. F. Graff

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The application of ultrasonic vibrations to machining processes has a long history, ranging from slurry-based systems able to drill brittle materials, to more recent developments involving low power ultrasonics for high precision machining, with many of these at the research and laboratory stages. The focus of this development is the application of high levels of ultrasonic power (1,000’s of watts) to standard, heavy duty machine tools – drilling being the immediate focus, with developments in milling in progress – with the objective of dramatically increasing system productivity through faster feed rates, this benefit arising from the thrust force reductions obtained by power ultrasonic vibrations. The presentation will describe development of an advanced drilling system based on a special, acoustically designed, rugged drill module capable of functioning under heavy duty production conditions, and making use of standard tool holder means, and able to obtain thrust force reductions while maintaining or improving surface finish and drilling accuracy. The characterization of the system performance will be described, and results obtained in drilling several materials (Aluminum, Stainless steel, Titanium) presented.

Keywords: dimensional accuracy, machine tool, productivity, surface roughness, thrust force, ultrasonic vibrations, ultrasonic-assisted drilling

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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Authors: Ravneet Kaur

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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

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Authors: Hande Ünlü, Yu Morishita

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The total area of forest land in Japan accounts for 67% of the national land; however, despite this wealth and hundred years history of silviculture, today Japanese forestry faces socio-economic stagnation in forestry. While the growing gap in the people-forest relationship causes the depopulation of many forest villages, this paper introduces a methodology aiming to develop a place-specific approach in revitalizing this relationship. The paper focuses on a case study from Taiki town in the Hokkaido region to analyze the place's specific socio-economic requirements through interviews and workshops with the local experts, researchers, and stakeholders. Based on the analyzed facts, a master outline of design requirements is developed to produce locally sourced architectural embodiments that aim to act as a unifying element between the forests and the people of Taiki town. In parallel, the proposed methodology aims to generate a cycle of research feed and a researcher retreat, a definition given by Memu Earth Lab to the researchers' stay at Memu in Taiki town for a defined period to analyze local resources, for the continuous improvement of the introduced methodology to revitalize the interaction between people and forest through architecture.

Keywords: architecture, Japanese forestry, local timber, people-forest relationship, research platform

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Authors: Rafał Kamiński, Joel Rech, Philippe Bertrand, Christophe Desrayaud

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Titanium alloys are among the most important material in the aircraft industry, due to its low density, high strength, and corrosion resistance. However, these alloys are considered as difficult to machine because they have poor thermal properties and high reactivity with cutting tools. The Selective Laser Melting (SLM) process becomes even more popular through industry since it enables the design of new complex components, that cannot be manufactured by standard processes. However, the high temperature reached during the melting phase as well as the several rapid heating and cooling phases, due to the movement of the laser, induce complex microstructures. These microstructures differ from conventional equiaxed ones obtained by casting+forging. Parts obtained by SLM have to be machined in order calibrate the dimensions and the surface roughness of functional surfaces. The ball milling technique is widely applied to finish complex shapes. However, the machinability of titanium is strongly influenced by the microstructure. So the objective of this work is to investigate the influence of the SLM process, i.e. microstructure, on the machinability of titanium, compared to conventional forming processes. The machinability is analyzed by measuring surface roughness, cutting forces, cutting tool wear for a range of cutting conditions (depth of cut ap, feed per tooth fz, spindle speed N) in accordance with industrial practices.

Keywords: ball milling, microstructure, surface roughness, titanium

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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Authors: Selvakuma Kumaresh, Man Young Kim

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Combustion phenomenon will be accomplished effectively by the development of low emission combustor. One of the significant factors influencing the entire Combustion process is the mixing between a swirling angular jet (Primary Air) and the non-swirling inner jet (fuel). To study this fundamental flow, the chamber had to be designed in such a manner that the combustion process to sustain itself in a continuous manner and the temperature of the products is sufficiently below the maximum working temperature in the turbine. This study is used to develop the effective combustion with low unburned combustion products by adopting the concept of high swirl flow and motility of holes in the secondary chamber. The proper selection of a swirler is needed to reduce emission which can be concluded from the emission of Nox and CO2. The capture of CO2 is necessary to mitigate CO2 emissions from natural gas. Thus the suppression of unburned gases is a meaningful objective for the development of high performance combustor without affecting turbine blade temperature.

Keywords: combustion, emission, can-type combustion chamber, CFD, motility of holes, swirl flow

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Authors: Alice Sanwald, Thomas Schober

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We analyze mortality and follow-up costs of heart attack patients using administrative data from Austria (2002-2011). As treatment intensity in a hospital largely depends on whether it has a catheterization laboratory, we focus on the effects of patients' initial admission to these specialized hospitals. To account for the nonrandom selection of patients into hospitals, we exploit individuals' place of residence as a source of exogenous variation in an instrumental variable framework. We find that the initial admission to specialized hospitals increases patients' survival chances substantially. The effect on 3-year mortality is -9.5 percentage points. A separation of the sample into subgroups shows the strongest effects in relative terms for patients below the age of 65. We do not find significant effects on longterm inpatient costs and find only marginal increases in outpatient costs.

Keywords: acute myocardial infarction, mortality, costs, instrumental variables, heart attack

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Authors: Narong Anurak

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This study aimed to find out the hair-care purchasing behavior at hypermarkets and to investigate two factors, package design and advertising channels, that influenced hair-care purchasing behavior. The subjects of the study consisted of 100 housewives aged between 20-60 who usually shopped at Big C Tiwanon. They were selected by accidental sampling, and were asked to complete a questionnaire. The main findings of the survey were that the majority of respondents regarding their brand selection of hair-care products, they gave priority to the product quality followed by a reasonable price, and fragrance, respectively. Besides, more than half of the respondents had brand loyalty while the rest were attracted by an attractive package design and advertising promotion campaigns. The respondents who were attracted by the package design said that the information on the labels influenced their purchasing decision the most, and television was a medium that best reached them as well.

Keywords: advertising channels, consumer purchasing decisions, hair-care market, package design

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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: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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Authors: Anuradha Banerjee

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Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

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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: Mohammed A. A. Sarhan, Issam A. Al-Khatib

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Complying with the technical specifications of compost production is of high importance not only for environmental protection but also for increasing the productivity and promotion of compost use by farmers in agriculture. This study focuses on the compost quality of the Palestinian market and farmers’ attitudes toward agricultural use of compost. The quality is assessed through selection of 20 compost samples of different suppliers and producers and lab testing for quality parameters, while the farmers’ attitudes to compost use for agriculture are evaluated through survey questionnaire of 321 farmers in the Hebron area. The results showed that the compost in the Palestinian markets is of medium quality due to partial or non-compliance with the quality standards and guidelines. The Palestinian farmers showed a positive attitude since 91.2% of them have the desire to use compost in agriculture. The results also showed that knowledge of difference between compost and chemical fertilizers, perception of compost benefits and previously experiencing problems in compost use, are significant factors affecting the farmers’ attitude toward the use of compost as an organic fertilizer.

Keywords: attitude, compost, compost quality, organic fertilizer, manure

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Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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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: Doo Ki Lee, Kumaresh Selvakumar, Man Young Kim, In Jae Song

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The widespread utilization of mixer in selective catalytic reduction (SCR) system marks a remarkable advantage in diesel engines. In the automotive selective catalytic reduction (SCR) system, the de-NOX efficiency can be improved by highly uniform flow with effective turbulent mixing. In this paper, the exhaust pipe is complemented with the swirling mixers of three different vane angles installed at the upstream of the SCR reactor. The attributes of the mixer are established by the variation in flow behavior followed by the drawback owing to the absence of mixer. In particular, the information pertaining to the selection of proper static mixer is provided based on the correlation between the uniformity index (UI) and the pressure drop. The uniform distribution of the flow at the entrance of the SCR reactor aids to determine the configuration which gives high mixing performance and comprehend the function of the mixer.

Keywords: pressure drop, selective catalytic reduction, static mixer, turbulent mixing, uniformity index

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

Abstract:

Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

NFV-based network implements a variety of network functions with software on general-purpose servers, and this allows the network operator to select any capabilities and locations of network functions without any physical constraints. In this paper, we evaluate the influence of the maximum tolerable network delay on the virtual routing function deployment guidelines which the authors proposed previously. Our evaluation results have revealed the following: (1) the more the maximum tolerable network delay condition becomes severe, the more the number of areas where the route selection function is installed increases and the total network cost increases, (2) the higher the routing function cost relative to the circuit bandwidth cost, the increase ratio of total network cost becomes larger according to the maximum tolerable network delay condition.

Keywords: NFV (Network Functions Virtualization), resource allocation, virtual routing function, minimum total network cost

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Authors: Fakhreddin El Wali Elalaoui, Maatouk Mustapha

Abstract:

The problem of global climate change isbecoming more and more serious. Therefore, there is a growing interest in renewable energy sources to minimize the impact of this phenomenon. Environmental policies are changing in different countries, including Morocco, with a greater focus on the integration and development of renewable energy projects. The purpose of this paper is to evaluate the potential of solar power plants in Morocco based on two technologies: concentrated solar power (CSP) and photovoltaics (PV). In order to perform an accurate search, we must follow a certain method to select the correct criteria. Four selection criteria were retained: climate, topography, location, and water resources. AnalyticHierarchy Process (AHP) was used to calculate the weight/importance of each criterion. Once obtained, weights are applied to the map for each criterion to produce a final ranking that ranks regions according to their potential. The results show that Morocco has strong potential for both technologies, especially in the southern region. Finally, this work is the first in the field to include the whole of Morocco in the study area.

Keywords: PV, Csp, solar energy, GIS

Procedia PDF Downloads 83