Search results for: low input farming

Authors: G. Kaur, A. P. Kulkarni, S. Giddey

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Production of fuels and chemicals using renewable energy is a promising way for large-scale energy storage and export. Solid oxide electrolysers (SOEs) integrated with renewable source of energy can produce 'Syngas' H₂/CO from H₂O/CO₂ in the desired ratio for further conversion to liquid fuels. As only a waste CO₂ from industrial and power generation processes is utilized in these processes, this approach is CO₂ neutral compared to using fossil fuel feedstock. In addition, the waste heat from industrial processes or heat from solar thermal concentrators can be effectively utilised in SOEs to further reduce the electrical requirements by up to 30% which boosts overall energy efficiency of the process. In this paper, the electrochemical performance of various novel steam/CO₂ reduction electrodes (cathode) would be presented. The efficiency and lifetime degradation data for single cells and a stack would be presented along with the response of cells to variable electrical load input mimicking the intermittent nature of the renewable energy sources. With such optimisation, newly developed electrodes have been tested for 500+ hrs with Faraday efficiency (electricity to fuel conversion efficiency) up to 95%, and thermal efficiency in excess of 70% based upon energy content of the syngas produced.

Keywords: carbon dioxide, steam conversion, electrochemical system, energy storage, fuel production, renewable energy

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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Probabilistic analysis has become one of the most popular methods to quantify and manage geotechnical risks due to the spatial variability of soil input parameters. The correlation length is one of the key factors of quantifying spatial variability of soil parameters which is defined as a distance within which the random variables are correlated strongly. This paper aims to assess the impact of correlation length on the long-term settlement of soft soils improved with preloading. The concept of 'worst-case' spatial correlation length was evaluated by determining the probability of failure of a real case study of Vasby test fill. For this purpose, a finite difference code was developed based on axisymmetric consolidation equations incorporating the non-linear elastic visco-plastic model and the Karhunen-Loeve expansion method. The results show that correlation length has a significant impact on the post-construction settlement of soft soils in a way that by increasing correlation length, probability of failure increases and the approach to asymptote.

Keywords: Karhunen-Loeve expansion, probability of failure, soft soil settlement, 'worst case' spatial correlation length

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO

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Authors: Devon Simpson

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Recycled Manure Solids (RMS), attained via centrifugation from Canadian dairy farms, were synthesized into a non-polluting fertilizer by bonding micronutrients (Fe, Zn, and Mn) to cellulose fibers and then assessed for the effectiveness of nutrient recovery in tomatoes. Manure management technology is critical for improving the sustainability of agroecosystems and has the capacity to offer a truly circular economy. The ability to add value to manure byproducts offers an opportunity for economic benefits while generating tenable solutions to livestock waste. The dairy industry is under increasing pressure from new environmental protections such as government restrictions on manure applications, limitations on herd size as well as increased product demand from a growing population. Current systems use RMS as bedding, so there is a lack of data pertaining to RMS use as a fertilizer. This is because of nutrient distribution, where most nutrients are retained in the liquid effluent of the solid-liquid separation. A literature review on the physical and chemical properties of dairy manure further revealed more data for raw manure than centrifuged solids. This research offers an innovative perspective and a new avenue of exploration in the use of RMS. Manure solids in this study were obtained directly from dairy farms in Salmon Arm and Abbotsford, British Columbia, and underwent physical, chemical, and biological characterizations pre- and post-synthesis processing. Samples were sent to A&L labs Canada for analysis. Once characterized and bonded to micronutrients, the effect of synthesized RMS on nutrient recovery in tomatoes was studied in a greenhouse environment. The agricultural research package ‘agricolae’ for R was used for experimental design and data analysis. The growth trials consisted of a randomized complete block design (RCBD) that allowed for analysis of variance (ANOVA). The primary outcome was to measure nutrient uptake, and this was done using an Inductively Coupled Plasma Mass Spectrometer (IC-PMS) to analyze the micronutrient content of both the tissue and fruit of the tomatoes. It was found that treatments containing bonded dairy manure solids had an increased micronutrient concentration. Treatments with bonded dairy manure solids also saw an increase in yield, and a brix analysis showed higher sugar content than the untreated control and a grower standard.

Keywords: aoecosystems, dairy manure, micronutrient fertilizer, manure management, nutrient recovery, nutrient recycling, recycled manure solids, regenerative agricugrlture, sustainable farming

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Moiz S. Vohra, Nagalingam Arun Prasanth, Wei L. Tan, S. H. Yeo

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The understanding of generation and collapse of acoustic cavitation bubbles are prerequisites for application of cavitation erosion. Microbubbles generated due to rapid fluctuation of pressure induced by propagation of ultrasonic wave lead to formation of high velocity microjets and or shock waves upon collapse. Due to vast application of ultrasonic, it is important to characterize and understand cavitation collapse pressure under the radiating surface at different conditions. A comparative investigation is carried out to determine impact load and dynamic pressure distribution exerted upon bubble collapse using thin film pressure sensors. Measurements were recorded at different input conditions such as amplitude, stand-off distance, insertion depth of the horn inside the liquid and pulse on-off time of acoustic vibrations. Impact force of 2.97 N is recorded at amplitude of 108 μm and stand-off distance of 1 mm from the sensor film, whereas impulsive force as low as 0.4 N is recorded at amplitude of 12 μm and stand-off distance of 5 mm from the sensor film. The results drawn from the investigation indicated that variety of impact loads can be achieved by controlling generation and collapse of bubbles, making it suitable to use for numerous application.

Keywords: ultrasonic cavitation, bubble collapse, pressure mapping sensor, impact load

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Mehmet Nefes, Selman Demirel, Hasan H. Ertok, Cenk Sen

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A typical reliability engineering problem regarding communication satellites has been considered to determine redundancy allocation scheme of power amplifiers within payload transponder module, whose dominant function is to amplify power levels of the received signals from the Earth, through maximizing reliability against mass, power, and other technical limitations. Adding each redundant power amplifier component increases not only reliability but also hardware, testing, and launch cost of a satellite. This study investigates a multi-objective approach used in order to solve Redundancy Allocation Problem (RAP) for a communication satellite payload transponder, focusing on design cost due to redundancy and reliability factors. The main purpose is to find the optimum power amplifier redundancy configuration satisfying reliability and capacity thresholds simultaneously instead of analyzing respectively or independently. A mathematical model and calculation approach are instituted including objective function definitions, and then, the problem is solved analytically with different input parameters in MATLAB environment. Example results showed that payload capacity and failure rate of power amplifiers have remarkable effects on the solution and also processing time.

Keywords: communication satellite payload, multi-objective optimization, redundancy allocation problem, reliability, transponder

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Authors: Madjid Karimirad

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Floating solar was not very well-known in the renewable energy field a decade ago; however, there has been tremendous growth internationally with a Compound Annual Growth Rate (CAGR) of nearly 30% in recent years. To reach the goal of global net-zero emission by 2050, all renewable energy sources including solar should be used. Considering that 40% of the world’s population lives within 100 kilometres of the coasts, floating solar in coastal waters is an obvious energy solution. However, this requires more robust floating solar solutions. This paper tries to enlighten the fundamental requirements in the design of floating solar for offshore installations from the hydrodynamic and offshore engineering points of view. In this regard, a closer look at dynamic characteristics, stochastic behaviour and nonlinear phenomena appearing in this kind of structure is a major focus of the current article. Floating solar structures are alternative and very attractive green energy installations with (a) Less strain on land usage for densely populated areas; (b) Natural cooling effect with efficiency gain; and (c) Increased irradiance from the reflectivity of water. Also, floating solar in conjunction with the hydroelectric plants can optimise energy efficiency and improve system reliability. The co-locating of floating solar units with other types such as offshore wind, wave energy, tidal turbines as well as aquaculture (fish farming) can result in better ocean space usage and increase the synergies. Floating solar technology has seen considerable developments in installed capacities in the past decade. Development of design standards and codes of practice for floating solar technologies deployed on both inland water-bodies and offshore is required to ensure robust and reliable systems that do not have detrimental impacts on the hosting water body. Floating solar will account for 17% of all PV energy produced worldwide by 2030. To enhance the development, further research in this area is needed. This paper aims to discuss the main critical design aspects in light of the load and load effects that the floating solar platforms are subjected to. The key considerations in hydrodynamics, aerodynamics and simultaneous effects from the wind and wave load actions will be discussed. The link of dynamic nonlinear loading, limit states and design space considering the environmental conditions is set to enable a better understanding of the design requirements of fast-evolving floating solar technology.

Keywords: floating solar, offshore renewable energy, wind and wave loading, design space

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Authors: Haiping Ding, Rongchu Zhu, Zhenxia Song

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Local irregular topography has a great impact on earthquake ground motion. For scarp topography, using numerical simulation method, the influence extent and scope of the scarp terrain on scarp's upside and downside ground motion are discussed in case of different vertical incident SV waves. The results show that: (1) The amplification factor of scarp's upside region is greater than that of the free surface, while the amplification factor of scarp's downside part is less than that of the free surface; (2) When the slope angle increases, for x component, amplification factors of the scarp upside also increase, while the downside part decrease with it. For z component, both of the upside and downside amplification factors will increase; (3) When the slope angle changes, the influence scope of scarp's downside part is almost unchanged, but for the upside part, it slightly becomes greater with the increase of slope angle; (4) Due to the existence of the scarp, the z component ground motion appears at the surface. Its amplification factor increases for larger slope angle, and the peaks of the surface responses are related with incident waves. However, the input wave has little effects on the x component amplification factors.

Keywords: scarp topography, ground motion, amplification factor, vertical incident wave

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Authors: Michal Gregor, Jiri Polcar, Petr Horejsi, Michal Simon

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Machine visualization is an area of interest with fast and progressive development. We present a method of machine visualization which will be applicable in real industrial conditions according to current needs and demands. Real factory data were obtained in a newly built research plant. Methods described in this paper were validated on a case study. Input data were processed and the virtual environment was created. The environment contains information about dimensions, structure, disposition, and function. Hardware was enhanced by modular machines, prototypes, and accessories. We added new functionalities and machines into the virtual environment. The user is able to interact with objects such as testing and cutting machines, he/she can operate and move them. Proposed design consists of an environment with two degrees of freedom of movement. Users are in touch with items in the virtual world which are embedded into the real surroundings. This paper describes the development of the virtual environment. We compared and tested various options of factory layout virtualization and visualization. We analyzed possibilities of using a 3D scanner in the layout obtaining process and we also analyzed various virtual reality hardware visualization methods such as Stereoscopic (CAVE) projection, Head Mounted Display (HMD), and augmented reality (AR) projection provided by see-through glasses.

Keywords: augmented reality, spatial scanner, virtual environment, virtual reality

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Authors: Amitesh Goswami, Vishal Gulati, Annu Yadav

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In this paper, WEDM has been used to investigate the machining characteristics of Inconel-625 alloy. The machining characteristics namely material removal rate (MRR) and surface roughness (SR) have been investigated along with surface microstructure analysis using SEM and EDS of the machined surface. Taguchi’s L27 Orthogonal array design has been used by considering six varying input parameters viz. Pulse-on time (Ton), Pulse-off time (Toff), Spark Gap Set Voltage (SV), Peak Current (IP), Wire Feed (WF) and Wire Tension (WT) for the responses of interest. It has been found out that Pulse-on time (Ton) and Spark Gap Set Voltage (SV) are the most significant parameters affecting material removal rate (MRR) and surface roughness (SR) are. Microstructure analysis of workpiece was also done using Scanning Electron Microscope (SEM). It was observed that, variations in pulse-on time and pulse-off time causes varying discharge energy and as a result of which deep craters / micro cracks and large/ small number of debris were formed. These results were helpful in studying the effects of pulse-on time and pulse-off time on MRR and SR. Energy Dispersive Spectrometry (EDS) was also done to check the compositional analysis of the material and it was observed that Copper and Zinc which were initially not present in the Inconel 625, later migrated on the material surface from the brass wire electrode during machining

Keywords: MRR, SEM, SR, taguchi, Wire Electric Discharge Machining

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Authors: Ayodele A. Otaiku

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Purpose: Nigeria has become the largest importer of rice in Africa and second in the world, 2015. Investigate interactions of organic rice farming on soil quality and health from bio-waste converted to biofertilizer and its environmental impact on rice crop. Methodology: Bio-wastes, poultry waste, organic agriculture wastes, wood ash mixed with microbial inoculant organisms called OBD-Plus microbes (broad spectrum) composted in anaerobic digester to OBD-biofertilizer (2010 - 2012) uses microbes to build humus and other stable carbons. Two field experiments were carried out at Badeggi, Niger state in 2011 and 2012 to evaluate the response of lowland rice production using biofertilizer. The experimental field was laid out in a strip-plot design with five treatments and three replications and at twenty-one day old seedlings of FARO 44 and FARO 52 rice varieties were transplanted. Plots without fertiliser application served as control. Findings: The highest rice grain yield increase of 4.4 t/ha over the control in 2012 against the Nigeria average of lowland rice grain yields of 1.5 t/ha. The utilization of OBD-Biofertilizer can decrease the use of chemical nitrogen fertilizer, prevent the depletion of soil organic matter and reduce environmental pollution. Increasing the floodwater productivity and optimizing the recycling of nutrients cum grazer populations and disease by biocontrols microbes present in the OBD-Biofertilizer. Organic matter in the soil improves by 58% and C/N 15 (2011) and 13.35 (2012). Implications: OBD- Biofertilizer produce plant growth hormones such as indole acetic acid (IAA), glomalin related soil protein and extracellular enzymes as phosphatases that promote soil health and quality. Conclusion: Microorganisms can enhance nutrients use efficiency by increasing root surface area e.g., mycorrhizal, fungi, promoting other beneficial symbioses of the host plant and microbial interactions resulting to increase in soil organic matter. By 2030, climate change is projected to depress cereal production in Africa by 2 to 3 percent. Improved seeds and increased fertilizer use should more than compensate, but this factor will still weigh heavily on efforts to make progress.

Keywords: OBD-plus microbial consortia, OBD-biofertilizer, rice production, soil quality, sustainable agriculture

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: Georgii Emelianov, Mikhail Polikarpov, Fabian Hübner, Jochen Deuse, Jochen Schiemann

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Recycling refrigerating appliances plays a major role in protecting the Earth's atmosphere from ozone depletion and emissions of greenhouse gases. The performance of refrigerator recycling plants in terms of material retention is the subject of strict environmental certifications and is reviewed periodically through specialized audits. The continuous collection of Refrigerator data required for the input-output analysis is still mostly manual, error-prone, and not digitalized. In this paper, we propose an automated data collection system for recycling plants in order to deduce expected material contents in individual end-of-life refrigerating appliances. The system utilizes laser scanner measurements and optical data to extract attributes of individual refrigerators by applying transfer learning with pre-trained vision models and optical character recognition. Based on Recognized features, the system automatically provides material categories and target values of contained material masses, especially foaming and cooling agents. The presented data collection system paves the way for continuous performance monitoring and efficient control of refrigerator recycling plants.

Keywords: automation, data collection, performance monitoring, recycling, refrigerators

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Authors: Abhigna Bhatt, Arnab Banerjee

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A periodic system with only a single coupling degree of freedom is called a monocoupled system. Monocoupled systems with mechanisms like mass in the mass system generates effective negative mass, mass connected with rigid links generates inertial amplification, and spring-mass connected with a rigid link generateseffective negative stiffness. In this paper, the representative unit cell is introduced, considering all three mechanisms combined. Further, the dynamic stiffness matrix of the unit cell is constructed, and the dispersion relation is obtained by applying the Bloch theorem. The frequency response function is also calculated for the finite length of periodic unit cells. Moreover, the input displacement signal is given to the finite length of periodic structure and using inverse Fourier transform to visualize the wave propagation in the time domain. This visualization explains the sudden attenuation in metamaterial due to energy dissipation by an embedded resonator at the resonance frequency. The visualization created for wave propagation is found necessary to understand the insights of physics behind the attenuation characteristics of the system.

Keywords: mono coupled system, negative effective mass, negative effective stiffness, inertial amplifier, fourier transform

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Authors: Ilir Rexhepi, Naim Ismajli

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Quality and quality management are key factors of success nowadays. Public sector and quality management in this sector contains many challenges and difficulties, most notably in a new country like Kosovo. This study analyses the process of implementation of quality management system in public administration institutions in this country. The main objective is to show how to set up a quality management system and how does the quality management system setup affect the overall public administration services in Kosovo. This study shows how the efficiency and effectiveness of public institution services/performance is rapidly improving through the establishment and functionalization of Quality Management System. The specific impact of established QMC within the organization has resulted with the identification of mission related processes within the entire system including input identification, the person in charge and the way of conversion to the output of each activity though the interference with other service processes within the system. By giving detailed analyses of all steps of implementation of the Quality Management System, its effect and consequences towards the overall public institution service performance, we try to go one step further, by showing it as a very good example or tool of other public institutions for improving their service performance. Interviews with employees, middle and high level managers including the quality manager and general secretaries are also part of analyses in this paper.

Keywords: quality, quality management system, efficiency, public administration institutions

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Authors: Joanna Rybicka-Łada, Magda Kosmal, Anna Kuśnierz

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One of the main problems of the glass industry is the still high consumption of energy needed to produce glass mass, as well as the increase in prices, fuels, and raw materials. Therefore, comprehensive actions are taken to improve the entire production process. The key element of these activities, starting from filling the set to receiving the finished product, is the melting process, whose task is, among others, dissolving the components of the set, removing bubbles from the resulting melt, and obtaining a chemically homogeneous glass melt. This solution avoids dust formation during filling and is available on the market. This process consumes over 90% of the total energy needed in the production process. The processes occurring in the set during its conversion have a significant impact on the further stages and speed of the melting process and, thus, on its overall effectiveness. The speed of the reactions occurring and their course depend on the chemical nature of the raw materials, the degree of their fragmentation, thermal treatment as well as the form of the introduced set. An opportunity to minimize segregation and accelerate the conversion of glass sets may be the development of new technologies for preparing and dosing sets. The previously preferred traditional method of melting the set, based on mixing all glass raw materials together in loose form, can be replaced with a set in a thickened form. The aim of the project was to develop a glass set in a selectively or completely densified form and to examine the influence of set processing on the melting process and the properties of the glass.

Keywords: glass, melting process, glass set, raw materials

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Authors: Houda Khaled, Fredj Chaabani, Frederic Boulvain

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The Aptian series in north-central Tunisia was studied in detail regarding to lithology, microfacies, and magnetic susceptibility to provide new insights into the paleoenvironmental evolution and sea level changes in the carbonate platform. The study series is about 350 meters thick, and it consists of fives sequences of limestones, separated by four levels of marlstones and marly limestones. Petrographic study leads to the definition of 11 microfacies which are successively recorded along the Serdj section into the outer ramp, mid-ramp, inner ramp and coastal facies associations. The magnetic susceptibility of all samples was measured and compared with the facies and microfacies. There is a clear link between facies and magnetic susceptibility; the distal facies show high values while the proximal areas show lower values. The magnetic susceptibility profile reflects stratigraphic variations in response to relative changes in sea level and input of detrital materials. During the Aptian, kaolinite/illite intensity ratios show high values possibly indicating a warming trend followed then by decreasing values that may indicate a cooling trend. During the Albian, this cooling trend is reverted into humid/warming.

Keywords: Aptian, mineralogy, petrology, Serdj massif

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Authors: T. Nakkeran, C. Dhamodharan, Win Myint Soe , Ramasamy Deverajan, M. Ganesh Babu

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This manuscript presents the results of an experimental investigation performed to study the material and mechanical properties of two weld joints fabricated within close proximity. The experiment was designed using welded S355 D Z35 with distances between two parallel adjacent weld toes at 8 mm. These distances were less than the distance that has normally been recommended in standards, codes, and specifications. The main idea of the analysis is to determine any significant effects when welding the joints with the close proximity of 8mm using the SAW welding process of the one joint with high heat put and one joint welded with the FCAW welding process and evaluating the destructing and nondestructive testing between the welded joints. Further, we have evaluated the joints with Mechanical Testing for evaluating by performing Tensile test, bend testing, Macrostructure, Microstructure, Hardness test, and Impact testing. After evaluating the final outcome of the result, no significant changes were observed for welding the close proximity of weld of 8mm distance between the joints as compared to the specification minimum distance between the weldments of any design should be 50mm.

Keywords: S355 carbon steel, weld proximity, SAW process, FCAW process, heat input, bend test, tensile test, hardness test, impact test, macro and microscopic examinations

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Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks

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Authors: Maha Rashid Al-Azib, Almuzn Qasem Alqathradi, Amal Munir Alshahrani, Bilqis Mohammed Assiri, Ali Almuflih

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The Occupational Safety and Health Management System in one of the largest Saudi companies has been experiencing in the last 10 years extensive direct and indirect expenses due to lack of proactive leading indicators and safety leadership effective procedures. And since there are no studies that are associated with this department of safety in the company, this research has been conducted. In this study we used a mixed method approach containing a literature review and experts input, then a qualitative questionnaire provided by Institute for Work and Health related to determining the company’s occupational safety and health management system level out from three levels (Compliance - Improvement - Continuous Learning) and the output regarding the company’s level was in Continuous Learning. After that Deming cycle was employed to create a set of proactive leading indicators and analyzed using the SMART method to make sure of its effectiveness and suitability to the company. The objective of this research is to provide a set of proactive indicators to contribute in making an efficient occupational safety and health management system that has less accidents which results in less expenses. Therefore, we provided the company with a prototype of an APP, designed and empowered with our final results to contribute in supporting decisions making processes.

Keywords: proactive leading indicators, OSH MS, safety leadership, accidents reduction

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Boukrida Rafiq

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Democracy is based on the notion that all citizens have the right to participate in the managing of political affairs and that every citizens input is of equal importance. This basic assumption clearly places emphasis on public participation in maintaining a stable democracy. The level of public participation, however is highly contested with many theorists arguing that too much public participation would overwhelm and ultimately cripple democratic systems. On the other hand, others who favor high levels of participation argue that more citizen involvement leads to greater representation. Regardless of these disagreements over the utopian level of participation, there is widespread agreement amongst scholars that, at the very least, some participation is necessary to maintain democratic systems. The ways in which citizens participate vary greatly and depending on the method used, influence political decision making at varying levels. The method of political participation is a key in controlling public influence over political affairs and therefore is also an integral part of maintaining democracy, whether it be "thin" (low levels of participation) or "Robust" (high levels of participation). High levels of participation or "robust" democracy are argued by some theorists to enhance democracy through providing the opportunity for more issues to be represented during decision making. The notion of widespread participation was first advanced by classical theorists.

Keywords: assumption clearly places emphasis, ultimately cripple, influence political decision making at varying, classical theorists

Procedia PDF Downloads 460

Authors: Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

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The filleting yield and the chemical composition of farmed sea bass (Dicentrarchus labrax); rainbow trout (Oncorynchus mykiss) and meagre (Argyrosomus regius) was investigated in farmed fish in NW Greece. The results provide an estimate of the quantity of fish required to produce one kilogram of fillet weight, an estimation which is required for the operational management of fish processing companies. Furthermore in this work, the ratio of feed input required to produce one kilogram of fish fillet (FFCR) is presented for the first time as a useful indicator of the ecological footprint of consuming farmed fish. The lowest lipid content appeared in meagre (1,7%) and the highest in trout (4,91%). The lowest fillet yield and fillet yield feed conversion ratio (FYFCR) was in meagre (FY=42,17%, FFCR=2,48), the best fillet yield (FY=53,8%) and FYFCR (2,10) was exhibited in farmed rainbow trout. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: farmed fish, flesh quality, filleting yield, lipid

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Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner

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Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Keywords: calculation of risk factor, fuzzy logic, fuzzy programming for ship, safety navigation of ships

Procedia PDF Downloads 189

Authors: Aye Pa Pa Myo

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Writing in English is accounted as a complex process for English as a foreign language learners. Besides, committing errors in writing can be found as an inevitable part of language learners’ writing. Generally, academic writing is quite difficult for most of the students to manage for getting better scores. Students can commit common errors in their writings when they try to write academic writing. Error analysis deals with identifying and detecting the errors and also explains the reason for the occurrence of these errors. In this paper, the researcher has an attempt to examine the common errors of undergraduate students in their academic writings at Pathein University. The purpose of doing this research is to investigate the errors which students usually commit in academic writing and to find out the better ways for correcting these errors in EFL classrooms. In this research, fifty-third-year non-English specialization students attending Pathein University were selected as participants. This research took one month. It was conducted with a mixed methodology method. Two mini-tests were used as research tools. Data were collected with a quantitative research method. Findings from this research pointed that most of the students noticed their common errors after getting the necessary input, and they became more decreased committing these errors after taking mini-test; hence, all findings will be supportive for further researches related to error analysis in academic writing.

Keywords: academic writing, error analysis, EFL learners, mini-tests, mixed methodology

Procedia PDF Downloads 132