Search results for: algorithm techniques

Authors: Yuzhi Cai

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This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

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Authors: Supakorn Tantisriyanurak, Hussaya Maneesuwan, Thanyalak Chaisuwan, Sujitra Wongkasemjit

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TUD-1 is a siliceous mesoporous material with a three-dimensional amorphous structure of random, interconnecting pores, large pore size, high surface area (400-1000 m2/g), hydrothermal stability, and tunable porosity. However, the significant disadvantage of the mesoporous silicates is few catalytic active sites. In this work, a series of bimetallic Fe and Ti incorporated into TUD-1 framework is successfully synthesized by sol–gel method. The synthesized Fe,Ti-TUD-1 is characterized by various techniques. To study the catalytic activity of Fe, Ti–TUD-1, phenol hydroxylation was selected as a model reaction. The amounts of residual phenol and oxidation products were determined by high performance liquid chromatography coupled with UV-detector (HPLC-UV).

Keywords: iron, phenol hydroxylation, titanium, TUD-1

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Jian Cao

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This paper describes a novel watermarking technique which we call the random direction embedding (RDE) watermarking. Unlike traditional watermarking techniques, the watermark energy after the RDE embedding does not focus on a fixed direction, leading to the security against the traditional unauthorized watermark removal attack. In addition, the experimental results show that when compared with the existing secure watermarking, namely natural watermarking (NW), the RDE watermarking gains significant improvement in terms of robustness. In fact, the security of the RDE watermarking is not at the cost of low robustness, and it can even achieve more robust than the traditional spread spectrum watermarking, which has been shown to be very insecure.

Keywords: robustness, spread spectrum watermarking, watermarking security, random direction embedding (RDE)

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Authors: Amor Jnifene, Cedric Cocaud

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One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

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Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

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Authors: Ahmed Elaksher, Islam Omar

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For many years, Mars surface has been a mystery for scientists. Lately with the help of geospatial data and photogrammetric procedures researchers were able to capture some insights about this planet. Two of the most imperative data sources to explore Mars are the The High Resolution Imaging Science Experiment (HiRISE) and the Mars Orbiter Laser Altimeter (MOLA). HiRISE is one of six science instruments carried by the Mars Reconnaissance Orbiter, launched August 12, 2005, and managed by NASA. The MOLA sensor is a laser altimeter carried by the Mars Global Surveyor (MGS) and launched on November 7, 1996. In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images for generating a more accurate and trustful surface of Mars. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. In this project, we employed three different 3D to 2D transformation models. These are the parallel projection (3D affine) transformation model; the extended parallel projection transformation model; the Direct Linear Transformation (DLT) model. A set of tie-points was digitized from both datasets. These points were split into two sets: Ground Control Points (GCPs), used to evaluate the transformation parameters using least squares adjustment techniques, and check points (ChkPs) to evaluate the computed transformation parameters. Results were evaluated using the RMSEs between the precise horizontal coordinates of the digitized check points and those estimated through the transformation models using the computed transformation parameters. For each set of GCPs, three different configurations of GCPs and check points were tested, and average RMSEs are reported. It was found that for the 2D transformation models, average RMSEs were in the range of five meters. Increasing the number of GCPs from six to ten points improve the accuracy of the results with about two and half meters. Further increasing the number of GCPs didn’t improve the results significantly. Using the 3D to 2D transformation parameters provided three to two meters accuracy. Best results were reported using the DLT transformation model. However, increasing the number of GCPS didn’t have substantial effect. The results support the use of the DLT model as it provides the required accuracy for ASPRS large scale mapping standards. However, well distributed sets of GCPs is a key to provide such accuracy. The model is simple to apply and doesn’t need substantial computations.

Keywords: mars, photogrammetry, MOLA, HiRISE

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Authors: Kolade Olawande Owoeye, George R. S. Weir

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The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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Authors: Dammak Saida, Mbarek Sonia

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This paper aims to examine the impact of public interest commitment, the attitude towards independence enforcement, and organizational ethical culture on auditors' ethical behavior. It also tests the moderating effect of gender diversity on these relationships. The sample consisted of 100 Tunisian chartered accountants. An online survey was used to collect the data. Data analysis techniques used to test hypotheses The findings of this study provide practical implications for accounting professionals, regulators, and audit firms as they help understand auditors' beliefs and behaviors, which implies more effective mechanisms for improving their ethical values.

Keywords: public interest, independence, organizational culture, professional behavior, Tunisian auditors

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Authors: Edgar Teixeira, Eurico Carrapatoso

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As 3D displays become increasingly affordable, while production techniques and computational resources to create stereoscopic content being ever more accessible, a new dimension is literally introduced along with new expressive and immersive potentialities in support of designing for the screen. Prospective design visionaries have already at the reach of their hands an innovative and powerful visualization technology, which enables them to actively envision future trends and vanguardist directions. This paper explores the aesthetic and informational potentialities of stereoscopic motion graphics, providing insight on the application of 3D displays in design practice, proposing strategies to investigate stereoscopic communication, discussing potential repercussions to extant theory and impacts on audience.

Keywords: design, visual communication, technology, stereoscopy, 3D media

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Authors: Manuel Valencia Alejaandro Paz, Luz Nidia Quintero Jairo Palacios

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In present paper a set of technical approaches to improve the energy efficiency in processes controlled by electric motor drive systems EMDS are listed and analyzed. Energy saving becomes fundamental to improve the sustainability and competitiveness of organizations all around the world; increasing costs of electricity had impulse the use of different strategies to reduce the electric power condition. A summary of these techniques is presented and evaluated in the potential for energy saving policies.

Keywords: energy saving, EMDS, induction motor, energy efficiency, sustainability

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Goran Begović

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In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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Authors: Aishwarya Pothula

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Euthanasia in India is a politically dormant policy issue in the sense that discussions around it are sporadic in nature (usually with developments in specific cases) and it stays as a dominant issue in the public domain for a fleeting period. In other words, it is a non-political issue that has been unable to successfully get on the policy agenda. This paper studies how the Supreme Court of India (SC) plays a role in euthanasia’s policy making. In 2011, the SC independently put a law in place that legalized passive euthanasia through its judgement in the Aruna Shanbaug v. Union of India case. According to this, it is no longer illegal to withhold/withdraw a patient’s medical treatment in certain cases. This judgement, therefore, is the empirical focus of this paper. The paper essentially employs two techniques of discourse analysis to study the SC’s system of argumentation. The two methods, Text Analysis using Gasper’s Analysis Table and Frame Analysis – are complemented by two discourse techniques called metaphor analysis and lexical analysis. The framework within which the analysis is conducted lies in 1) the judicial process of India, i.e. the SC procedures and the Constitutional rules and provisions, and 2) John W. Kingdon’s theory of policy windows and policy entrepreneurs. The results of this paper are three-fold: first, the SC dismiss the petitioner’s request for passive euthanasia on inadequate and weak grounds, thereby setting no precedent for the historic law they put in place. In other words, they leave the decision open for the Parliament to act upon. Hence the judgement, as opposed to arguments by many, is by no means an instance of judicial activism/overreach. Second, they define euthanasia in a way that resonates with existing broader societal themes. They combine this with a remarkable use of authoritative and protective tones/stances to settle at an intermediate position that balances the possible opposition to their role in the process and what they (perhaps) perceive to be an optimal solution. Third, they soften up the policy community (including the public) to the idea of passive euthanasia leading it towards a Parliamentarian legislation. They achieve this by shaping prevalent principles, provisions and worldviews through an astute use of the legal instruments at their disposal. This paper refers to this unconventional role of the SC as ‘judicial entrepreneurship’ which is also the first scholarly contribution towards research on euthanasia as a policy issue in India.

Keywords: argumentation analysis, Aruna Ramachandra Shanbaug, discourse analysis, euthanasia, judicial entrepreneurship, policy-making process, supreme court of India

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Authors: Sakshi Piplani, Ajit Kumar

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Valproic acid (VPA) is the first synthetic therapeutic agent used to treat epileptic disorders, which account for affecting nearly 1% world population. Teratogenicity caused by VPA has prompted the search for next generation drug with better efficacy and lower side effects. Recent studies have posed HDAC8 as direct target of VPA that causes the teratogenic effect in foetus. We have employed molecular dynamics (MD) and docking simulations to understand the binding mode of VPA and their analogues onto HDAC8. A total of twenty 3D-structures of human HDAC8 isoforms were selected using BLAST-P search against PDB. Multiple sequence alignment was carried out using ClustalW and PDB-3F07 having least missing and mutated regions was selected for study. The missing residues of loop region were constructed using MODELLER and energy was minimized. A set of 216 structural analogues (>90% identity) of VPA were obtained from Pubchem and ZINC database and their energy was optimized with Chemsketch software using 3-D CHARMM-type force field. Four major neurotransmitters (GABAt, SSADH, α-KGDH, GAD) involved in anticonvulsant activity were docked with VPA and its analogues. Out of 216 analogues, 75 were selected on the basis of lower binding energy and inhibition constant as compared to VPA, thus predicted to have anti-convulsant activity. Selected hHDAC8 structure was then subjected to MD Simulation using licenced version YASARA with AMBER99SB force field. The structure was solvated in rectangular box of TIP3P. The simulation was carried out with periodic boundary conditions and electrostatic interactions and treated with Particle mesh Ewald algorithm. pH of system was set to 7.4, temperature 323K and pressure 1atm respectively. Simulation snapshots were stored every 25ps. The MD simulation was carried out for 20ns and pdb file of HDAC8 structure was saved every 2ns. The structures were analysed using castP and UCSF Chimera and most stabilized structure (20ns) was used for docking study. Molecular docking of 75 selected VPA-analogues with PDB-3F07 was performed using AUTODOCK4.2.6. Lamarckian Genetic Algorithm was used to generate conformations of docked ligand and structure. The docking study revealed that VPA and its analogues have more affinity towards ‘hydrophobic active site channel’, due to its hydrophobic properties and allows VPA and their analogues to take part in van der Waal interactions with TYR24, HIS42, VAL41, TYR20, SER138, TRP137 while TRP137 and SER138 showed hydrogen bonding interaction with VPA-analogues. 14 analogues showed better binding affinity than VPA. ADMET SAR server was used to predict the ADMET properties of selected VPA analogues for predicting their druggability. On the basis of ADMET screening, 09 molecules were selected and are being used for in-vivo evaluation using Danio rerio model.

Keywords: HDAC8, docking, molecular dynamics simulation, valproic acid

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Authors: N. H. Alias, S. A. Aziz, Y. Abdullah, H. M. Kamari, S. Sani, M. P. Ismail, N. U. Saidin, N. A. A. Salim, N. E. E. Abdullah

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Gamma (γ) irradiation study has been investigated on the 6 rectangular shape of the standard X-Ray lead glass with 5/16” thick, providing 2.00 mm lead shielding value; at selected Sievert doses (C1; 0, C2; 0.07, C3; 0.035, C4; 0.07, C5; 0.105 and C6; 0.14) by using (XRD) X-ray Diffraction techniques, ultrasonic and (UV-VIS) Ultraviolet-Visible Spectroscopy. Concentration of lead in 0.5 N acid nitric (HNO3) environments is then studied by means of Atomic Absorption Spectroscopy (AAS) as to observe the glass corrosion behavior after irradiation at room temperature. This type of commercial glass is commonly used as radiation shielding glass in medical application.

Keywords: gamma irradiation, lead glass, leaching, structural

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Authors: Uma Shanker, Vidhisha Jassal

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A novel green route was used to synthesize few metal hexacyanoferrates (FeHCF, NiHCF, CoHCF and CuHCF) nanoparticles using Sapindus mukorossias a natural surfactant and water as a solvent. The synthesized nanoparticles were characterized by Powder X-ray diffraction (PXRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Fourier Transform Infrared Spectroscopy (FTIR) and Thermo gravimetric techniques. Trasmission electron microscopic images showed that synthesized MHCF nanoparticles exhibited cubic and spherical shapes with exceptionally small sizes ranging from 3nm - 186 nm.

Keywords: metal hexacyanoferrates, natural surfactant, Sapindus mukorossias, nanoparticles

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Authors: Fatih Sogut

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Developments in information technologies have caused significant changes in terms of radio and television broadcasting. With these changes in terms of production format, transmission techniques and service delivery, the distinction between traditional media and New Media has emerged. The viewer/listener, who was in a passive position before, is now in an active position and has a say in many matters, including content production. Visual and auditory data transfer has diversified and become easier thanks to the convergence phenomenon. These transformations and developments also affected one of the oldest electronic communication tools, radio. In this study, in order to adapt to the new era that emerged with the digital age, the change in radio broadcasting and the factors that led to this change were tried to be explained.

Keywords: Internet, radio broadcasting, digital transformation, Internet broadcasting

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Authors: Anubhav Shrivastava, Lakshya Bhat, Shivarudraswamy

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Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic.

Keywords: distributed generation, fuzzy logic, matlab, newton raphson, IEEE 14 bus, voltage regulation, radial network

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Authors: Tejinder Singh Sidhu

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Hot corrosion has been recognized as a severe problem in steam-powered electricity generation plants and industrial waste incinerators as it consumes the material at an unpredictably rapid rate. Consequently, the load-carrying ability of the components reduces quickly, eventually leading to catastrophic failure. The inability to either totally prevent hot corrosion or at least detect it at an early stage has resulted in several accidents, leading to loss of life and/or destruction of infrastructures. A number of countermeasures are currently in use or under investigation to combat hot corrosion, such as using inhibitors, controlling the process parameters, designing a suitable industrial alloy, and depositing protective coatings. However, the protection system to be selected for a particular application must be practical, reliable, and economically viable. Due to the continuously rising cost of the materials as well as increased material requirements, the coating techniques have been given much more importance in recent times. Coatings can add value to products up to 10 times the cost of the coating. Among the different coating techniques, thermal spraying has grown into a well-accepted industrial technology for applying overlay coatings onto the surfaces of engineering components to allow them to function under extreme conditions of wear, erosion-corrosion, high-temperature oxidation, and hot corrosion. In this study, the hot corrosion performances of Ni-20Cr and Cr₃C₂-NiCr coatings developed by High Velocity Oxy-Fuel (HVOF) process have been studied. The coatings were developed on a Fe-based superalloy, and experiments were performed in an actual industrial environment of a coal-fired boiler. The cyclic study was carried out around the platen superheater zone where the temperature was around 1000°C. The study was conducted for 10 cycles, and one cycle was consisting of 100 hours of heating followed by 1 hour of cooling at ambient temperature. Both the coatings deposited on Fe-based superalloy imparted better hot corrosion resistance than the uncoated one. The Ni-20Cr coated superalloy performed better than the Cr₃C₂-NiCr coated in the actual working conditions of the coal fired boiler. It is found that the formation of chromium oxide at the boundaries of Ni-rich splats of the coating blocks the inward permeation of oxygen and other corrosive species to the substrate.

Keywords: hot corrosion, coating, HVOF, oxidation

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Authors: Parastou Kharazmi

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Failure and leakage of metallic components because of corrosion in infrastructure structures is a considerably problematic and expensive issue and the traditional solution of replacing the component is costly and time-consuming. Rehabilitation techniques by using advanced polymeric materials are an alternative solution towards this problem. This paper provides a summary of analyses on relined rehabilitated metallic samples after exposure in practice and real condition to study the composite material performance when it is exposed to water, heat and chemicals in real condition. The study was carried out by using different test methods such as microscopy, thermal and chemical as well as mechanical analyses.

Keywords: composite, material, rehabilitation, structure

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Authors: Ruby Priya, O. P. Pandey

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Herein, we report the structural and luminescent properties of undoped and Eu doped SrY₂O₄ phosphors. The phosphors are synthesized via the combustion synthesis route using glycine as a fuel. The structural, morphological, and optical characterizations are done via X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescent (PL) techniques. The pure phase SrY₂O₄ is obtained at 1100℃, below which impure phases such as Y₂O₃ and SrO were dominant. All the phosphors are excited under UV excitation and exhibited intense emission around 611 nm, which is the typical transition of Eu ions. The phase formation of the synthesized phosphors is studied via analyzing XRD patterns. The as-synthesized phosphors find tremendous applications in optoelectronic devices, light-emitting diodes, and sensors.

Keywords: combustion, europium, glycine, luminescence

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Authors: Saadat Ali, Rashid Abdulla Ahmed Alshehhi

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Cable faults are always probable and common during or after commissioning, causing significant delays and disrupting power distribution or transmission network, which is intolerable for the utilities&service providers being their reliability and business continuity measures. Therefore, the adoption of rapid localization & rectification methodology is the main concern for them. This paper explores the present techniques available for high voltage cable localization & rectification and which is preferable with regards to easier, faster, and also less harmful to cables. It also provides insight experience of high resistance fault locating by utilization of the Very Low Frequency (VLF) method.

Keywords: faults, VLF, real cases, cables

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Authors: Rajbir Cheema

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In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in different research information systems, which can have a wide range of negative effects on data quality, the subject of data quality should be treated with better results. This paper examines the data quality problems in research information systems and presents the new techniques that enable organizations to improve their quality of research information.

Keywords: Research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization

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Authors: Raida Zouari, Iness Ahriz, Rafik Zayani, Ali Dziri, Ridha Bouallegue

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This paper proposes a room level indoor localization algorithm based on the use Multi-Layer Neural Network (MLNN) classifiers and one versus one strategy. Seven parameters of the Channel Impulse Response (CIR) were used and Gram-Shmidt Orthogonalization was performed to study the relevance of the extracted parameters. Simulation results show that when relevant CIR parameters are used as position fingerprint and when optimal MLNN architecture is selected good room level localization score can be achieved. The current study showed also that some of the CIR parameters are not correlated to the location and can decrease the localization performance of the system.

Keywords: mobile indoor localization, multi-layer neural network (MLNN), channel impulse response (CIR), Gram-Shmidt orthogonalization

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Authors: Nidia Thalia Alva Rangel, Ferran Padros Blazquez, Ma. Ines Gomez Del Campo Del Paso

Abstract:

Happiness has been since antiquity a concept of interest around the world. Positive psychology is the science that begins to study happiness in a more precise and controlled way, obtaining wide amount of research which can be applied. One of the central constructs of Positive Psychology is Carol Ryff’s psychological well-being model as eudaimonic happiness, which comprehends six dimensions: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance. Humanistic psychology is a clear precedent of Positive Psychology, which has studied human development topics and it features a great variety of intervention techniques nevertheless has little evidence with controlled research. Therefore, the present research had the aim to evaluate the efficacy of a humanistic intervention program to increase psychological well-being in healthy adults through a mixed methods study. Before and after the intervention, it was applied Carol Ryff’s psychological well-being scale (PWBS) and the Symptom Check List 90 as pretest and posttest. In addition, a questionnaire of five open questions was applied after each session. The intervention program was designed in experiential workshop format, based on the foundational attitudes defined by Carl Rogers: congruence, unconditional positive regard and empathy, integrating humanistic intervention strategies from gestalt, psychodrama, logotherapy and psychological body therapy, with the aim to strengthen skills in the six dimensions of psychological well-being model. The workshop was applied to six volunteer adults in 12 sessions of 2 hours each. Finally, quantitative data were analyzed with Wilcoxon statistic test through the SPSS program, obtaining as results differences statistically significant in pathology symptoms between prettest and postest, also levels of dimensions of psychological well-being were increased, on the other hand for qualitative strand, by open questionnaires it showed how the participants were experiencing the techniques and changing through the sessions. Thus, the humanistic psychology program was effective to increase psychological well-being. Working to promote well-being prompts to be an effective way to reduce pathological symptoms as a secondary gain. Experiential workshops are a useful tool for small groups. There exists the need for research to count with more evidence of humanistic psychology interventions in different contexts and impulse the application of Positive Psychology knowledge.

Keywords: happiness, humanistic psychology, positive psychology, psychological well-being, workshop

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Authors: Nadia Akkari

Abstract:

This paper presents the analysis and simulation of the control of double star induction motor, using direct torque control (DTC) based on RST regulator. The DTC is an excellent solution for general- purpose induction drives in very wide range the short sampling time required by the TC schemes makes them suited to a very fast torque and flux controlled drives as well the simplicity of the control algorithm. DTC is inherently a motion sensorless control method. The RST regulator can improve the double star induction motor performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. Simulation results indicate that the proposed regulator has better performance responses. The implementation of the DTC applied to a double star induction motor based on RST regulator is validated with simulated results.

Keywords: Direct Torque Control (DTC), Double Star Induction Motor (DSIM), RST Regulator

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

Abstract:

Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

Procedia PDF Downloads 177

Authors: Vijay Kr. Yadav, Nilam Rathi

Abstract:

Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

Procedia PDF Downloads 239

Authors: Rajan Deglurkar

Abstract:

The research carried out in this piece of work is on 'Framework of Sustainable Manufacturing for Small and Medium Enterprises'. It consists of elucidation of concepts about sustainable manufacturing and sustainable product development with critical review performed on seven techniques of sustainable manufacturing. The work also covers the survey about critical review of awareness in the market with respect to the manufacturers and the consumers. The factors and challenges for sustainable manufacturing implementation are reviewed and simple framework is constructed for the small and medium enterprise for successful implementation of sustainable manufacturing and sustainable product.

Keywords: sustainable development, sustainable manufacturing, resource efficiency, framework for sustainable manufacturing

Procedia PDF Downloads 495