Search results for: trading signals generation

Authors: Usman Aliyu Jalam, Shuaibu Alolo Sumaila, Sa’adiya Iliyasu Muhammed

Abstract:

Modern building industry lays much emphasis on sophisticated materials that have high embodied energy with intrinsic distinctiveness for damaging the environment. But today, advances in solid waste management have resulted in alternative building materials as partial or complete replacement of the conventional materials like cement, aggregate etc particularly for low cost housing. Investigations carried out revealed that an estimated 18.0 million tonnes of agricultural solid wastes are being generated in Nigeria annually. This constitutes a problem not only to the natural environment but also to the built environment more particularly with the way the wastes are being dispose of. The paper has discussed the present status on the generation and utilisation of agricultural solid wastes, their recycling potentials and environmental implications. It further discovered that although considerable quantity of these wastes were found to have the potentials of being recycled as building materials, the availability of the appropriate technology remains a big challenge in the country. Moreover, majority of the wastes type have gained popularity as fuel. As such, the economic and environmental benefits of recycling the wastes and the use of the wastes as fuel need further investigation.

Keywords: agricultural waste, building, environment, materials, Nigeria

Procedia PDF Downloads 400

Authors: Tongpong Sriboon, Prapita Thanarak, Chaitawatch Khunrangabsang

Abstract:

Nowadays, the usage of power generated from photovoltaic system has been promoted significantly in Thailand. The targeted result which is to increase the Solar Power Generation in 2036 to 6000 megawatts (MW) was planned by Alternative Energy Development Plan (AEDP 2015) and Power Development Plan (PDP 2015). The solar rooftop 200 MW was promoted and supported under the Feed-in Tariff scheme (FiT) in two phases; phase I in 2012 and phase II in 2015. However, the number of people interested in supporting the projects reduced due to many reasons which range from the first process to the last that is to sell electricity back to Electricity Authority. This paper will review this situation especially in total electricity generated from solar rooftop system during the day that has been sold back to the grid utility in different capacity FiT rates. With many stakeholders involved, the regulations and criteria were established to maintain the standard of the system. Besides, lots of problems have occurred during the processes including reliability and quality. These problems were shortly followed by other irrevocably issues concerning politics, social, economic etc. In order to effectively develop solar PV power system in Thailand, the problems and solutions were compared to those from six countries including Japan, Australia. America, China, German and Malaysia. This paper particularly focuses on policies and measurement implemented to encourage the rising in solar PV system interest. This review enables one to gain insight into the nature of the changes that have taken place in each and every country mentioned above as well as the underlying reasons behind them. Brief analysis is carried out on identify key challenges and opportunities for solar PV application. This could help create a development path that is suitable with situations to enhance the overall performance of solar PV power generating system in Thailand.

Keywords: solar PV rooftop, PV policy, self-consumption, solar PV power generation

Procedia PDF Downloads 313

Authors: D. Kuvshinov, A. Siswanto, J. Lozano-Parada, W. Zimmerman

Abstract:

Ozone is well known as a powerful fast reaction rate oxidant. The ozone based processes produce no by-product left as a non-reacted ozone returns back to the original oxygen molecule. Therefore an application of ozone is widely accepted as one of the main directions for a sustainable and clean technologies development. There are number of technologies require ozone to be delivered to specific points of a production network or reactors construction. Due to space constrains, high reactivity and short life time of ozone the use of ozone generators even of a bench top scale is practically limited. This requires development of mini/micro scale ozone generator which can be directly incorporated into production units. Our report presents a feasibility study of a new micro scale rector for ozone generation (MROG). Data on MROG calibration and indigo decomposition at different operation conditions are presented. At selected operation conditions with residence time of 0.25 s the process of ozone generation is not limited by reaction rate and the amount of ozone produced is a function of power applied. It was shown that the MROG is capable to produce ozone at voltage level starting from 3.5kV with ozone concentration of 5.28E-6 (mol/L) at 5kV. This is in line with data presented on numerical investigation for a MROG. It was shown that in compare to a conventional ozone generator, MROG has lower power consumption at low voltages and atmospheric pressure. The MROG construction makes it applicable for emerged and dry systems. With a robust compact design MROG can be used as incorporated unit for production lines of high complexity.

Keywords: dielectric barrier discharge (DBD), micro reactor, ozone, plasma

Procedia PDF Downloads 338

Authors: Sandeep Kumar, Naveen Gupta

Abstract:

Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

Procedia PDF Downloads 201

Authors: Renuka Mahadevan, Maneka Jayasinghe, Dianne Dredge

Abstract:

Over the last two years, tourism has been subject to unprecedented changes, and experts predict further change, especially with respect to travel and tourism choices. As concerns regarding the environment and climate change grow, many tourism industry stakeholders are particularly keen on taking steps to mitigate the adverse impacts of the travel industry to the broader society and environment. This approach and process is commonly referred to as 'Sustainable Tourism'. An emerging concept that extends beyond 'sustainable tourism' is 'Regenerative Tourism', which aims to impact the local systems, society and environment positively. In particular, it aims to provide transformational experiences to tourists and thereby inspire the travellers while the local cultural heritage and traditions are preserved from generation to generation. This study analyses how tourism stakeholders are shifting their attitude towards travel and tourism, particularly regarding its impact on people, places, businesses and the environment. The analysis will be based on a global survey of 1200 businesses, tourism organisations, employees, and travel consumers. The preliminary analysis of responses reveals a high interest towards transformational experiences during travel.

Keywords: regenerative tourism, transformational, experience, local systems

Procedia PDF Downloads 71

Authors: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

Abstract:

The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, firefly algorithm, PVDG, voltage fluctuation

Procedia PDF Downloads 321

Authors: Maria Tsompanoglou, Dimitris Armenis

Abstract:

Vessel behavior in different operational and weather conditions constitutes the main area of interest for the ship operator. Ship speed and fuel consumption are the most decisive parameters in this respect, as their correlation provides information about the economic and environmental efficiency of the vessel, becoming the basis of decision making in terms of maintenance and trading. In the analysis of vessel operational profile for the evaluation of fuel consumption and the equivalent CO2 emissions footprint, the indications of Speed Through Water are widely used. The seasonal and regional variations in seawater characteristics, which are available nowadays, can provide the basis for accurate estimation of the errors in Speed Through Water indications at any time. Accuracy in the speed value on a route basis can enable operator identify the ship fuel and propulsion efficiency and proceed with improvements. This paper discusses case studies, where the actual vessel speed was corrected by a post-processing algorithm. The effects of the vessel correction to standard Key Performance Indicators, as well as operational findings not identified earlier, are also discussed.

Keywords: data analytics, MATLAB, vessel performance monitoring, speed through water

Procedia PDF Downloads 300

Authors: Rowshan Mamtaz, Shuvo Ahmed, Imran Noor, Sumaiya Rahman, Prithvi Shams, Fahmida Gulshan

Abstract:

Last few decades have witnessed a phenomenal rise in the use of electrical and electronic equipment globally in our everyday life. As these items reach the end of their lifecycle, they turn into e-wastes and contribute to the waste stream. Bangladesh, in conformity with the global trend and due to its ongoing rapid growth, is also using electronics-based appliances and equipment at an increasing rate. This has caused a corresponding increase in the generation of e-wastes. Bangladesh is a developing country; its overall waste management system, is not yet efficient, nor is it environmentally sustainable. Most of its solid wastes are disposed of in a crude way at dumping sites. Addition of e-wastes, which often contain toxic heavy metals, into its waste stream has made the situation more difficult and challenging. Assessment of generation of e-wastes is an important step towards addressing the challenges posed by e-wastes, setting targets, and identifying the best practices for their management. Understanding and proper management of e-wastes is a stated item of the Sustainable Development Goals (SDG) campaign, and Bangladesh is committed to fulfilling it. A better understanding and availability of reliable baseline data on e-wastes will help in preventing illegal dumping, promote recycling, and create jobs in the recycling sectors and thus facilitate sustainable e-waste management. With this objective in mind, the present study has attempted to estimate the amount of e-wastes and its future generation trend in Bangladesh. To achieve this, sales data on eight selected electrical and electronic products (TV, Refrigerator, Fan, Mobile phone, Computer, IT equipment, CFL (Compact Fluorescent Lamp) bulbs, and Air Conditioner) have been collected from different sources. Primary and secondary data on the collection, recycling, and disposal of the e-wastes have also been gathered by questionnaire survey, field visits, interviews, and formal and informal meetings with the stakeholders. Material Flow Analysis (MFA) method has been applied, and mathematical models have been developed in the present study to estimate e-waste amounts and their future trends up to the year 2035 for the eight selected electrical and electronic equipment. End of life (EOL) method is adopted in the estimation. Model inputs are products’ annual sale/import data, past and future sales data, and average life span. From the model outputs, it is estimated that the generation of e-wastes in Bangladesh in 2018 is 0.40 million tons and by 2035 the amount will be 4.62 million tons with an average annual growth rate of 20%. Among the eight selected products, the number of e-wastes generated from seven products are increasing whereas only one product, CFL bulb, showed a decreasing trend of waste generation. The average growth rate of e-waste from TV sets is the highest (28%) while those from Fans and IT equipment are the lowest (11%). Field surveys conducted in the e-waste recycling sector also revealed that every year around 0.0133 million tons of e-wastes enter into the recycling business in Bangladesh which may increase in the near future.

Keywords: Bangladesh, end of life, e-waste, material flow analysis

Procedia PDF Downloads 198

Authors: P. Y. Chiang, Y. H. Chen, Y. J. Lin, C. C. Chang, W. C. Hsu

Abstract:

The number of the elderly in the world population and the rate of falls in this increasing numbers of older people are increasing. Decreasing muscle strength and an increasing risk of falling are associated with the ageing process. Because the effects of seated stepping training on the walking performance in the elderly remain unclear, the main purpose of the proposed study is to perform electromyography analysis during walking and seated stepping in the elderly. Four surface EMG electrodes were sticked on the surface of lower limbs muscles, including vastus lateralis (VL), and gastrocnemius (GT) of both sides. Before test, maximal voluntary contraction (MVC) of the respective muscle was obtained using manual muscle testing. The analog raw data of EMG signals were digitized with a sampling frequency of 2000 Hz. The signals were fully rectified and the linear envelope were calculated. Stepping motion cycle was separated into two phases by stepping timing (ST) and pedal return timing (PRT). ST refer to the time when the pedal marker reached the highest height, representing the contra-lateral leg was going to release the pedal. PRT refer to the time when the pedal marker reached the lowest height, representing the contra-lateral leg was going to step the pedal. We assumed that ST acted the same role in initial contact during walking, and PRT for toe-off. The period from ST to next PRT was called pushing phase (PP), during which the leg would start to step with resistance, and we compare this phase with the stance phase in level walking. The period from PRT to next ST was called returning phase (RP), during which leg would not have any resistance in this phase, and we compare this phase with the swing phase in level walking. VL and Gastro muscular activation had similar patterns in both side. The ability may transfer to those needed during loading response, mid-stance and terminal swing phase. User needed to make more effort in stepping compared with walking with similar timing; thus the strengthening of the VL and Gastro may be helpful to improve the walking endurance and efficiency for the elderly.

Keywords: elderly, electromyography, seated stepping, walking

Procedia PDF Downloads 221

Authors: May Maricel De Gracia

Abstract:

Different generations respond differently to instruction because of their diverse characteristics, learning styles and study habits. Teaching strategies that were effective many years ago may not be effective now especially to the current generation which is Gen Z. Using quantitative research design, the main goal of this paper is to determine the impact of the implementation of educational technology integration in a private high school in the math performance of its Junior High School (JHS) students on SY 2014-2018 based on their periodical exam performance and on their final math grades. In support, survey on the use of technology was administered to determine the characteristics of both students and teachers of SY 2017-2018. Another survey regarding study habits was also administered to the students to determine their readiness with regards to note-taking skills, time management, test taking/preparation skills, reading, and writing and math skills. Teaching strategies were recommended based on the need of the current Gen Z JHS students. A total of 712 JHS students and 12 math teachers participated in answering the different surveys. Periodic exam means and final math grades between the school years without technology (SY 2004-2008) and with technology (SY 2014-2018) were analyzed through correlation and regression analyses. Result shows that the periodic exam mean has a 35.29% impact to the final grade of the students. In addition, z-test result where p > 0.05 shows that the periodical exam results do not differ significantly between the school years without integration of technology and with the integration of technology. However, with p < 0.01, a significant positive difference was observed in the final math grades of students between the school years without technology integration and with technology integration.

Keywords: classroom instruction, technology, generation z, math performance

Procedia PDF Downloads 147

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

Abstract:

This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 113

Authors: Fayssal Amrane, Azeddine Chaiba

Abstract:

In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: doubly fed induction generator (DFIG), direct power control (DPC), neuro-fuzzy control (NFC), maximum power point tracking (MPPT), space vector modulation (SVM), type 2 fuzzy logic control (T2FLC)

Procedia PDF Downloads 419

Authors: Adi A. Maaita, Hamza A. A. Al Sewadi

Abstract:

One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: cryptosystems, information security agreement, key distribution, random numbers

Procedia PDF Downloads 268

Authors: Djelloul Benatiallah

Abstract:

Due to the current high consumption and recent industry growth, the depletion of fossil and natural energy supplies like oil, gas, and uranium is declining. Due to pollution and climate change, there needs to be a swift switch to renewable energy sources. Research on renewable energy is being done to meet energy needs. Solar energy is one of the renewable resources that can currently meet all of the world's energy needs. In most parts of the world, solar energy is a free and unlimited resource that can be used in a variety of ways, including photovoltaic systems for the generation of electricity and thermal systems for the generation of heatfor the residential sector's production of hot water. In this article, we'll conduct a comparison. The first step entails identifying the two empirical models that will enable us to estimate the daily irradiations on a horizontal plane. On the other hand, we compare it using the data obtained from measurements made at the Adrar site over the four distinct seasons. The model 2 provides a better estimate of the global solar components, with an absolute mean error of less than 7% and a correlation coefficient of more than 0.95, as well as a relative coefficient of the bias error that is less than 6% in absolute value and a relative RMSE that is less than 10%, according to a comparison of the results obtained by simulating the two models.

Keywords: solar radiation, renewable energy, fossil, photovoltaic systems

Procedia PDF Downloads 79

Authors: Fazil Hasan, M. Shafiq Ansari, Mohammad Muslim

Abstract:

Zygogramma bicolorata Pallister (Coleoptera: Chrysomelidae) is an exotic insect and effective biocontrol agent of Parthenium hysterophorus L. (Asteraceae). Our study aimed to determine the induction and termination of diapause, in response to abiotic (temperature and moisture) and biotic factors (age and reproductive status) and the effect of diapause on adult longevity and female fecundity. The adults burrowed into the soil about 1–6 cm below the surface for diapause at any time from July to December with a peak of 70% in the 2nd week of December at Aligarh region, India. The termination of diapause took place in May and June with the commencement of monsoon rains. Non-diapausing adults were also capable of breeding during winter under laboratory conditions. There was a significantly increased in the percentage of diapaused adults in subsequent generation i.e. 4% in F1 generation and 90% in F7 generation. The percentage of diapause was also significantly increased with age of adults. It has a positive effect on female fecundity as compared to the fecundity in pre-diapaused duration. Experiments proved that soil moisture played an important role in providing the conditions for initiation and termination of diapause. The adults which undergone diapause in January and February were continuously exposed to 35º, 40º and 45º C for one week and a daily dose of 10 and 8 hours for 6 and 5 days, respectively resulting in termination of diapause. This method may be used to initiate mass multiplication for carrying out releases early in the season. Exposure of adults to extremely low temperatures i.e. 5º and 10º C induced 94.3% and 92.5% diapause, respectively with no adult mortality. Therefore, low temperatures can also be used as a medium for the storage of mass reared beetles for a long time without having negative effect on their longevity and fecundity. Thus, our findings are of great utility in the biological suppression of P. hysterophorus as it will enhance the effectiveness of this beetle through manipulation of diapause.

Keywords: Zygogramma bicolorata, environmental factors, age, sex, diapause, Parthenium hysterophorus, biocontrol

Procedia PDF Downloads 306

Authors: Bin Feng, Zhulin Zong

Abstract:

Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

Procedia PDF Downloads 90

Authors: Vicente Espinola, Luis Torres, Christhian Gonzalez

Abstract:

Entrepreneurship is a topic of current interest in Mexico and the World, which has been fostered through public policies with great impact on its generation. The strategies used in Mexico have not been successful, being motivational strategies aimed at the masses with the intention that someone in the process generates a venture. The strategies used for its development have been "picking of winners" favoring those who have already overcome the initial stages of undertaking without effective support. This situation shows a disarticulation that appears even more in social entrepreneurship; due to this, it is relevant to research on those elements that could develop them and thus integrate a model of entrepreneurship and social innovation for Mexico. Social entrepreneurship should be generating social innovation, which is translated into business models in order to make the benefits reach the population. These models are proposed putting the social impact before the economic impact, without forgetting its sustainability in the medium and long term. In this work, we present a simple model of innovation and social entrepreneurship for Guanajuato, Mexico. This algorithm was based on how social innovation could be generated in a systemic way for Mexico through different institutions that promote innovation. In this case, the technological parks of the state of Guanajuato were studied because these are considered one of the areas of Mexico where its main objectives are to make technology transfer to companies but overlooking the social sector and entrepreneurs. An experimental design of n = 60 was carried out with potential entrepreneurs to identify their perception of the social approach that the enterprises should have, the skills they consider required to create a venture, as well as their interest in generating ventures that solve social problems. This experiment had a 2K design, the value of k = 3 and the computational simulation was performed in R statistical language. A simple model of interconnected variables is proposed, which allows us to identify where it is necessary to increase efforts for the generation of social enterprises. The 96.67% of potential entrepreneurs expressed interest in ventures that solve social problems. In the analysis of the variables interaction, it was identified that the isolated development of entrepreneurial skills would only replicate the generation of traditional ventures. The variable of social approach presented positive interactions, which may influence the generation of social entrepreneurship if this variable was strengthened and permeated in the processes of training and development of entrepreneurs. In the future, it will be necessary to analyze the institutional actors that are present in the social entrepreneurship ecosystem, in order to analyze the interaction necessary to strengt the innovation and social entrepreneurship ecosystem.

Keywords: social innovation, model, entrepreneurship, technological parks

Procedia PDF Downloads 273

Authors: Aishik Deb, Rituparna Sinha

Abstract:

We have developed an algorithm to detect the abnormal segment/"structural variation in the genome across a number of samples. We have worked on simulated as well as real data from the BAM Files and have designed a segmentation algorithm where abnormal segments are detected. This algorithm aims to improve the accuracy and performance of the existing CNV-CH algorithm. The next-generation sequencing (NGS) approach is very fast and can generate large sequences in a reasonable time. So the huge volume of sequence information gives rise to the need for Big Data and parallel approaches of segmentation. Therefore, we have designed a map-reduce approach for the existing CNV-CH algorithm where a large amount of sequence data can be segmented and structural variations in the human genome can be detected. We have compared the efficiency of the traditional and map-reduce algorithms with respect to precision, sensitivity, and F-Score. The advantages of using our algorithm are that it is fast and has better accuracy. This algorithm can be applied to detect structural variations within a genome, which in turn can be used to detect various genetic disorders such as cancer, etc. The defects may be caused by new mutations or changes to the DNA and generally result in abnormally high or low base coverage and quantification values.

Keywords: cancer detection, convex hull segmentation, map reduce, next generation sequencing

Procedia PDF Downloads 136

Authors: Yasith Mindula Saipath Wickramasinghe

Abstract:

Augmented reality applications require a high processing power to load, render and live stream high-definition AR models and virtual scenes; it also requires device sensors to work excessively to coordinate with internal hardware, OS and give the expected outcome in advance features like object detection, real time tracking, as well as voice and text recognition. Excessive thermal generation due to these advanced functionalities has become a major research problem as it is unbearable for smaller mobile devices to manage such heat increment and battery drainage as it causes physical harm to the devices in the long term. Therefore, effective thermal management is one of the major requirements in Augmented Reality application development. As this paper discusses major causes for this issue, it also provides possible solutions in the means of operating system adaptations as well as further research on best coding practises to optimize the application performance that reduces thermal excessive thermal generation.

Keywords: augmented reality, device thermal management, GPU, operating systems, device I/O, overheating

Procedia PDF Downloads 118

Authors: Manish Kumar, Krupa Shah

Abstract:

The usage of renewable energy sources is increased day by day to overcome the dependency on fossil fuels. The wind energy is considered as a prominent source of renewable energy. This paper presents an approach for utilizing wind energy obtained from moving the vehicle for cell-phone charging. The selection of wind turbine, blades, generator, etc. is done to have the most efficient system. The calculation procedure for power generated and drag force is shown to know the effectiveness of the proposal. The location of the turbine is selected such that the system remains symmetric, stable and has the maximum induced wind. The calculation of the generated power at different velocity is presented. The charging is achieved for the speed 30 km/h and the system works well till 60 km/h. The model proposed seems very useful for the people traveling long distances in the absence of mobile electricity. The model is very economical and easy to fabricate. It has very less weight and area that makes it portable and comfortable to carry along. The practical results are shown by implementing the portable wind turbine system on two-wheeler.

Keywords: cell-phone charging, on-board power generation, wind energy, vehicle

Procedia PDF Downloads 295

Authors: P. Ghosh, S. B. Sharma

Abstract:

The growing problem of food waste is causing unacceptable economic, environmental and social impacts across the globe. In Australia, food waste is estimated at about AU$8 billion per year; however, information on the extent of wastage at different stages of the food value chain from farm to fork is very limited. This study aims to identify causes for and extent of food waste at wholesaler stage of the food value chain in the state of Western Australia. It also explores approaches applied to reduce and utilize food waste by the wholesalers. The study was carried out at Perth city market in Caning Vale, the main wholesale distribution centre for fruits and vegetables in Western Australia. A survey questionnaire was prepared and shared with 51 wholesalers and their responses to 10 targeted questions on quantity of produce (fruits and vegetables) delivery received and further supplied, reasons for waste generation and innovations applied or being considered to reduce and utilize food waste. Data were computed using the Statistical Package for the Social Sciences (SPSS version 21). Among the wholesalers 52% were primary wholesalers (buy produce directly from growers) and 48% were secondary wholesalers (buy produce in bulk from major wholesalers and supply to the local retail market, caterers, and customers with specific requirements). Average fruit and vegetable waste was 180 Kilogram per week per primary wholesaler and 30 Kilogram per secondary wholesaler. Based on this survey, the fruit and vegetable waste at wholesaler stage was estimated at about 286 tonnes per year. The secondary wholesalers distributed pre-ordered commodities, which minimized the potential to cause waste. Non-parametric test (Mann Whitney test) was carried out to assess contributions of wholesalers to waste generation. Over 56% of secondary wholesalers generally had nothing to bin as waste. Pearson’s correlation coefficient analysis showed positive correlation (r = 0.425; P=0.01) between the quantity of produce received and waste generated. Low market demand was the predominant reason identified by the wholesalers for waste generation. About a third of the wholesalers suggested that high cosmetic standards for fruits and vegetables - appearance, shape, and size - should be relaxed to reduce waste. Donation of unutilized fruits and vegetables to charity was overwhelmingly (95%) considered as one of the best options for utilization of discarded produce. The extent of waste at other stages of fruit and vegetable supply chain is currently being studied.

Keywords: food waste, fruits and vegetables, supply chain, waste generation

Procedia PDF Downloads 312

Authors: Marcin Baranski

Abstract:

This article presents a vibration diagnostic method designed for permanent magnets (PM) traction motors. Those machines are commonly used in traction drives of electrical vehicles. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. This work presents: field-circuit model, results of static tests, results of calculations and simulations.

Keywords: electrical vehicle, permanent magnet, traction drive, vibrations, electrical machine, eccentricity

Procedia PDF Downloads 628

Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

Abstract:

Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

Procedia PDF Downloads 128

Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

Abstract:

Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: combat effectiveness, emerging technologies, human factors, systems safety analysis

Procedia PDF Downloads 142

Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

Abstract:

In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

Procedia PDF Downloads 232

Authors: Dawit Abay Tesfamariam

Abstract:

Ethiopia’s Climate- Resilient Green Economy (ECRGE) strategy focuses mainly on generating and proper utilization of renewable energy (RE). Nonetheless, the current electricity generation of the country is dominated by hydropower. The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources from solar and wind energy were only 8 %. On the other hand, the EEP electricity generation plan in 2030 indicates that 36.1 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the EnergyPLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EnergyPLAN (EP) analysis for two predictive scenarios. The EP simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EP simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was in the three rainy months of the year (June, July, and August). The outcome of the model also showed that in the dry seasons of the year, there would be excess power production in the country. Consequently, based on the validated outcomes of EP indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that if the excess power is utilized with a storage system, it can stabilize the grid system and be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming storage system to synchronize with potentials that can be generated from renewable energy.

Keywords: renewable energy, power, storage, wind, energy plan

Procedia PDF Downloads 77

Authors: Prarthana Gowda, Tushar Sakorikar, Siva K. Reddy, Darim B. Ferry, Abha Misra

Abstract:

Graphene, a two-dimensional carbon allotrope has demonstrated excellent electrical, mechanical and optical properties. A tunable band gap of grapheme demonstrated broad band absorption of light with a response time of picoseconds, however it suffers a fast recombination of the photo generated carriers. Many reports have explored to overcome this problem; in this presentation, we discuss defect induced enhanced photoresponse in a few layer graphene (FLG) due to exposure of infrared (IR) radiation. The two and four-fold enhancement in the photocurrent is achieved by addition of multiwalled carbon nano tubes (MWCNT) to an FLG surface and also creating the wrinkles in the FLG (WG) respectively. In our study, it is also inferred that the photo current generation is highly dependent on the morphological defects on the graphene. It is observed that the FLG (without defects) generates the photo current instantaneously, and after a prolonged exposure to the IR radiation decays the generation rate. Importantly, the presence of MWCNT on FLG enhances the stability and WG presented both stable as well as enhanced photo response.

Keywords: graphene, multiwalled carbon nano tubes, wrinkled graphene, photo detector, photo current

Procedia PDF Downloads 414

Authors: Parveen Kumar

Abstract:

This article discusses institute information resources. Information, in its most restricted technical sense, is a sequence of symbols that can be interpreted as message information can be recorded as signs, or transmitted as signals. Information is any kind of event that affects the state of a dynamic system. Conceptually, information is the message being conveyed. This concept has numerous other meanings in different contexts. Moreover, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, representation, and especially entropy.

Keywords: institutions, information institutions, information services for mission-oriented institute, pattern

Procedia PDF Downloads 376

Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

Abstract:

Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: natural language inference, explanation generation, variational auto-encoder, generative model

Procedia PDF Downloads 151

Authors: Zeina Merabi, Arij Dao

Abstract:

The temporal order of information processing in the brain is an important code in many acoustic signals, including speech, music, and animal vocalizations. Despite its significance, surprisingly little is known about its underlying cellular mechanisms and network manifestations. In the songbird telencephalic nucleus HVC, a subset of neurons shows temporal combination sensitivity (TCS). These neurons show a high temporal specificity, responding differently to distinct patterns of spectral elements and their combinations. HVC neuron types include basal-ganglia-projecting HVCX, forebrain-projecting HVCRA, and interneurons (HVC¬INT), each exhibiting distinct cellular, electrophysiological and functional properties. In this work, we develop conductance-based neural network models connecting the different classes of HVC neurons via different wiring scenarios, aiming to explore possible neural mechanisms that orchestrate the combination sensitivity property exhibited by HVCX, as well as replicating in vivo firing patterns observed when TCS neurons are presented with various auditory stimuli. The ionic and synaptic currents for each class of neurons that are presented in our networks and are based on pharmacological studies, rendering our networks biologically plausible. We present for the first time several realistic scenarios in which the different types of HVC neurons can interact to produce this behavior. The different networks highlight neural mechanisms that could potentially help to explain some aspects of combination sensitivity, including 1) interplay between inhibitory interneurons’ activity and the post inhibitory firing of the HVCX neurons enabled by T-type Ca2+ and H currents, 2) temporal summation of synaptic inputs at the TCS site of opposing signals that are time-and frequency- dependent, and 3) reciprocal inhibitory and excitatory loops as a potent mechanism to encode information over many milliseconds. The result is a plausible network model characterizing auditory processing in HVC. Our next step is to test the predictions of the model.

Keywords: combination sensitivity, songbirds, neural networks, spatiotemporal integration

Procedia PDF Downloads 65