Search results for: noise reduction techniques

Authors: Sungwon Jung

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The percentage of 20 years or older apartment houses in South Korea is approximately 20% (1.55 million houses), and the explosive increase of aged houses is expected around the first planned new towns. Accordingly, we should prepare for social issues such as difficulty of housing lease and degradation of housing performance. The improvement of performance of aged houses is essential for achieving the national energy and carbon reduction goals, and we should develop techniques to respond to the changing construction environment. Furthermore, we should develop a performance evaluation system that is appropriate for the demands of residents such as the improvement of remodeling floor plan by performance improvement in line with the residence type of the housing vulnerable groups such as low-income group and elderly people living alone. For this purpose, remodeling techniques and business models optimized for the target complexes must be spread through the development of various business models. In addition, it is necessary to improve the remodeling business by improving the laws and systems related to the improvement of the residential performance and to prepare techniques to respond to the increasing business demands. In other words, performance improvement and evaluation and knowledge systems need to be researched as new issues related to remodeling that has not been addressed in the existing research.

Keywords: remodelling, performance evaluation, web-based system, big data

Procedia PDF Downloads 204

Authors: Vladimir V. Nikulin, Bekmurza H. Aitchanov, Olimzhon A. Baimuratov

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Quantum communication technology takes advantage of the intrinsic properties of laser carriers, such as very high data rates and low power requirements, to offer unprecedented data security. Quantum processes at the physical layer of encryption are used for signal encryption with very competitive performance characteristics. The ultimate range of applications for QC systems spans from fiber-based to free-space links and from secure banking operations to mobile airborne and space-borne networking where they are subjected to channel distortions. Under practical conditions, the channel can alter the optical wave front characteristics, including its phase. In addition, phase noise of the communication source and photo-detection noises alter the signal to bring additional ambiguity into the measurement process. If quantized values of photons are used to encrypt the signal, exploitation of quantum communication links becomes extremely difficult. In this paper, we present the results of analysis and simulation studies of the effects of noise on phase estimation for quantum systems with different number of encryption bases and operating at different power levels.

Keywords: encryption, phase distortion, quantum communication, quantum noise

Procedia PDF Downloads 529

Authors: Man Chul Jeong, Hyoung Jin Lee, Sang Yoon Lee, Ji Hyun Park, Min Wook Chang, In-Seuck Jeung

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This study focus on the drag reduction effect of the base bleed at supersonic flow. Base bleed is the method which bleeds the gas on the tail of the flight vehicle and reduces the base drag, which occupies over 50% of the total drag in any flight speed. Thus base bleed can reduce the total drag significantly, and enhance the total flight range. Drag reduction ratio of the base bleed is strongly related to the mass flow rate of the bleeding gas. Thus selecting appropriate mass flow rate is important. However, since the flight vehicle has various flight speed, same mass flow rate of the base bleed can have different drag reduction effect during the flight. Thus, this study investigates the effect of the drag reduction depending on the flight speed by numerical analysis using STAR-CCM+. The analysis model is 155mm diameter projectile with boat-tailed shape base. Angle of the boat-tail is chosen previously for minimum drag coefficient. Numerical analysis is conducted for Mach 2 and Mach 3, with various mass flow rate, or the injection parameter I, of the bleeding gas and the temperature of the bleeding gas, is fixed to 300K. The results showed that I=0.025 has the minimum drag at Mach 2, and I=0.014 has the minimum drag at Mach 3. Thus as the Mach number is higher, the lower mass flow rate of the base bleed has more effect on drag reduction.

Keywords: base bleed, supersonic, drag reduction, recirculation

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: Luqman Ali Shah, Murtaza Sayed, Mohammad Siddiq

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Three-dimensional cross-linked polymer microgels with temperature responsive N-isopropyl acrylamide (NIPAM) and pH-sensitive methacrylic acid (MAA) were successfully synthesized by free radical emulsion polymerization with different amount of MAA. Silver and gold nanoparticles with size of 6.5 and 3.5 nm (±0.5 nm) respectively were homogeneously reduced inside these materials by chemical reduction method at pH 2.78 and 8.36 for the preparation of hybrid materials. The samples were characterized by FTIR, DLS and TEM techniques. The catalytic activity of the hybrid materials was investigated for the reduction of 4-nitrophenol (4- NP) using NaBH4 as reducing agent by UV-visible spectroscopy. The hybrid polymer network synthesized at pH 8.36 shows enhanced catalytic efficiency compared to catalysts synthesized at pH 2.78. In this study, it has been explored that catalyst activity strongly depends on amount of MAA, synthesis pH and type of metal nanoparticles entrapped.

Keywords: cross-linked polymer microgels, free radical polymerization, metal nanoparticles, catalytic activity, comparative study

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Authors: Hsu-Hui Cheng, Peng-Chian Chen, Shu-Yuan Chang, Jie-Ying Zhang

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Activities in the music practice rooms range from playing, listening, rehearsing to music performing. The good room acoustics in a music practice room enables a music teacher to teach more effectively subtle concepts such as intonation, articulation, balance, dynamics and tone production. A poor acoustical environment would deeply affect the development of basic musical skills of music students. Practicing in the music practice room is an essential daily activity for music students; consequently, music practice rooms are very important facilities in a music school or department. The purpose of this survey is to measure and analyze the acoustic condition of piano practice rooms at the department of music in Zhaoqing University and accordingly apply a more effective teaching method to music students. The volume of the music practice room is approximately 25 m³, and it has existing curtains and some wood hole sound-absorbing panels. When all small music practice rooms are in constant use for teaching, it was found that the values of the background noise at 45, 46, 42, 46, 45 dB(A) in the small music practice room ( the doors and windows were close), respectively. The noise levels in the small music practice room to higher than standard levels (35dB(A)).

Keywords: acoustical performance, music practice room, noise level, piano room

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Authors: Majid Pourahmadi

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The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

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Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

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Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

Procedia PDF Downloads 248

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Muhammad Afzal, Junaid Uzair Satti

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The noise emanating from the ducting of heating, ventilation, and air-conditioning (HVAC) system is often attenuated by using the dissipative silencers. Such devices work well for the high-frequency noise but are less operative in the low-frequency noise range. The present study analyzes a reactive silencer comprising expansion chamber of the elastic membranes partitioned symmetrically by a rigid plate. The Mode-Matching scheme has been developed to solve the governing boundary value problem. The orthogonal and non-orthogonal duct modes of acoustic pressures and normal velocities are matched at interfaces. It enables to recast the differential system into the infinite system of linear algebraic of equations, which is, then truncated and inverted for the solution. The truncated solution is validated through the conservation of energy and reconstruction of matching conditions. The results for scattering energy flux and transmission loss are shown against frequency and the dimensions of the chamber. It is seen that the stop-band of the silencer can be shifted to the broadband by changing the dimensions of the chamber and the properties of the elastic membranes. The modeled reactive silencer is more efficient in low frequency regime where the passive devices are least effective.

Keywords: acoustic scattering, elastic membranes mode-matching, reactive silencer

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Authors: Sunny Arora, Meghal A. Desai

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An impetus towards green consumerism and implementation of sustainable techniques, consumption of natural products and utilization of environment friendly techniques have gained accelerated acceptance. Butein, a natural colorant, has many medicinal properties apart from its use in dyeing industries. Extraction of butein from the flowers of flame of forest was carried out using ultrasonication bath. Solid loading (2-6 g), extraction time (30-50 min), volume of solvent (30-50 mL) and types of solvent (methanol, ethanol and water) have been studied to maximize the yield of butein using the Taguchi method. The highest yield of butein 4.67% (w/w) was obtained using 4 g of plant material, 40 min of extraction time and 30 mL volume of methanol as a solvent. The present method provided a greater reduction in extraction time compared to the conventional method of extraction. Hence, the outcome of the present investigation could further be utilized to develop the method at a higher scale.

Keywords: butein, flowers of Flame of the Forest, Taguchi method, ultrasonic bath

Procedia PDF Downloads 445

Authors: Sihyun Park, Hyunwoo Kim, Wooyoung Jung, Dongwoo You

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Regular maintenance works are very important on the axial forces of the cable-band bolts in suspension bridges. The band bolts show stress reduction for several reasons, including cable wire creep, the bolt relaxation, load fluctuation and cable rearrangements, etc., with time. In this study, with respect to the stress reduction that occurs over time, we carried out the theoretical review of the main cause based on the field measurements. As a result, the main cause of reduction in the cable-band bolt axial force was confirmed by the plastic deformation of the zinc plating layer used in the main cable wire, and thus, the theoretical process was established for the practical use in the field.

Keywords: cable-band Bolts, field test, maintenance, stress reduction

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: Alexander J. Severinsky, Allen L. Sessoms

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Atmospheric carbon dioxide (CO₂) has dominated the discussion about the causes of climate change. This is a reflection of the time horizon that has become the norm adopted by the IPCC as the planning horizon. Recently, it has become clear that a 100-year time horizon is much too long, and yet almost all mitigation efforts, including those in the near-term horizon of 30 years, are geared toward it. In this paper, we show that, for a 30-year time horizon, methane (CH₄) is the greenhouse gas whose radiative forcing exceeds that of CO₂. In our analysis, we used radiative forcing of greenhouse gases in the atmosphere since they directly affect the temperature rise on Earth. In 2019, the radiative forcing of methane was ~2.5 W/m² and that of carbon dioxide ~2.1 W/m². Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m² and ~3.1 W/m², respectively. There is a substantial spread in the data for anthropogenic and natural methane emissions as well as CH₄ leakages from production to consumption. We estimated the minimum and maximum effects of the reduction of these leakages. Such action may reduce the annual radiative forcing of all CH₄ emissions by between ~15% and ~30%. This translates into a reduction of the RF by 2050 from ~2.8 W/m² to ~2.5 W/m² in the case of the minimum effect and to ~2.15 W/m² in the case of the maximum. Under the BAU, we found that the RF of CO₂ would increase from ~2.1 W/m² nowadays to ~3.1 W/m² by 2050. We assumed a reduction of 50% of anthropogenic emission linearly over the next 30 years. That would reduce radiative forcing from ~3.1 W/m² to ~2.9 W/m². In the case of ‘net zero,’ the other 50% of reduction of only anthropogenic emissions would be limited to either from sources of emissions or directly from the atmosphere. The total reduction would be from ~3.1 to ~2.7, or ~0.4 W/m². To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m², then an additional reduction of radiative forcing of CO₂ would be approximately 2.7 -2.15=0.55 W/m². This is a much larger value than in expectations from ‘net zero’. In total, one needs to remove from the atmosphere ~660 GT to match the maximum reduction of current methane leakages and ~270 GT to achieve ‘net zero.’ This amounts to over 900 GT in total.

Keywords: methane leakages, methane radiative forcing, methane mitigation, methane net zero

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Authors: I. Muslih, A. Alkhalailah, A. Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: dust effect, MENA, solar energy, PV system

Procedia PDF Downloads 189

Authors: Ilario Gabriele Gerloni, Vincenza Carchiolo, Alessandro Longheu, Ugo Becciani, Eva Sciacca, Fabio Vitello

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ICT tools and platforms endorse more and more educational process. Many models and techniques for people to be educated and trained about specific topics and skills do exist, as classroom lectures with textbooks, computers, handheld devices and others. The choice to what extent ICT is applied within learning contexts is related to personal access to technologies as well as to the infrastructure surrounding environment. Among recent techniques, the adoption of Virtual Reality (VR) and Augmented Reality (AR) provides significant impulse in fully engaging users senses. In this paper, an application of AR/VR within Geographic Information Systems (GIS) context is presented. It aims to provide immersive environment experiences for educational and training purposes (e.g. for civil protection personnel), useful especially for situations where real scenarios are not easily accessible by humans. First acknowledgments are promising for building an effective tool that helps civil protection personnel training with risk reduction.

Keywords: education, virtual reality, augmented reality, GIS, civil protection

Procedia PDF Downloads 152

Authors: Jahangir Ahmad Rather, Emad A. Khudaish, Ahsanulhaq Qurashi, Palanisamy Kannan

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Chemical modification and assembling of fullerenes are fundamentally important for the application of fullerenes as functional molecules and in molecular devices and organic electronic devices. We have synthesized fullerene nanorods C60NRs conjugate via liquid-liquid interface and the synthesized C60NRs was characterized by FTIR spectroscopy, field emission electron microscopy (FESEM) and X-ray diffraction techniques. The C60NRs were immobilized on glassy carbon electrode via surface bound diazonium salts as an impact strategy. This method involves electrografting of p–nitrophenyl to give GCE–Ph–NO2 and then the terminal nitro-group was chemically reduced to GCE–Ph–NH2 in a presence of sodium borohydride/gold–polyaniline nanocomposite (NaBH4/Au–PANI). The Au–PANI composite was synthesized and characterized by FTIR, UV-vis, SEM and EDX techniques. The C60NRs were immobilized on GCE–Ph–NH2 via amination reaction which involves N-H addition across a π-bond on [60] fullerene. The immobilized C60NRs/GCE was subjected to electrochemical reduction in 1.0 M KOH to yield ERC60NRs/GCE sensor. The developed sensor shows high electrocatalytic activity for the detection of ethylparaben (EP) over a concentration range from 0.01 to 0.52 µM with a detection limit (LOD) 3.8 nM. The amount of EP present in the nourishing repair cream (OlAY®) was determined by standard addition method at the developed ERC60NRs/GCE sensor. The total concentration of EP was found to be 0.011 µM (0.1%) and is within the permissible limit of 0.19 % EP in cosmetics according to the European scientific committee (SCCS) on consumer safety on 22 March 2011 (SCCS/1348/11).

Keywords: diazonium salt reduction, ethylparaben (EP), endocrine disruptor, fullerene nanorods (C60NRs), gold–polyaniline nanocomposite (Au–PANI)

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Authors: Muhammad Faiz Liew Abdullah, Bhagwan Das, Nor Shahida, Abdul Fattah Chandio

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This study presents the designed features of Graphical User Interface (GUI) for chromatic dispersion (CD) reduction using digital signal processing (DSP) techniques. GUI is specially designed for windows platform. The obtained simulation results from matlab are presented via this GUI. After importing results from matlab in GUI, It will present your work on any windows7 and onwards versions platforms without matlab software. First part of the GUI contains the research methodology block diagram and in the second part, output for each stage is shown in separate reserved area for the result display. Each stage of methodology has the captions to display the results. This GUI will be very helpful during presentations instead of making slides this GUI will present all your work easily in the absence of other software’s such as Matlab, Labview, MS PowerPoint. GUI is designed using C programming in MS Visio Studio.

Keywords: Matlab simulation results, C programming, MS VISIO studio, chromatic dispersion

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Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Sport performance analysis is a technique that is becoming every year more important for athletes of every level. Many techniques have been developed to measure and analyse efficiently the performance of athletes in some sports, but in combat sports these techniques found in many times their limits, due to the high interaction between the two opponents during the competition. In this paper the problem will be framed. Moreover the physical performance measurement problem will be analysed and three different techniques to manage it will be presented. All the techniques have been used to analyse the performance of 22 high level Judo athletes.

Keywords: sport performance, physical performance, judo, performance coefficients

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Authors: Othman Maklouf, Abdunnaser Tresh

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GPS and inertial navigation system (INS) have complementary qualities that make them ideal use for sensor fusion. The limitations of GPS include occasional high noise content, outages when satellite signals are blocked, interference and low bandwidth. The strengths of GPS include its long-term stability and its capacity to function as a stand-alone navigation system. In contrast, INS is not subject to interference or outages, have high bandwidth and good short-term noise characteristics, but have long-term drift errors and require external information for initialization. A combined system of GPS and INS subsystems can exhibit the robustness, higher bandwidth and better noise characteristics of the inertial system with the long-term stability of GPS. The most common estimation algorithm used in integrated INS/GPS is the Kalman Filter (KF). KF is able to take advantages of these characteristics to provide a common integrated navigation implementation with performance superior to that of either subsystem (GPS or INS). This paper presents a simplified KF algorithm for land vehicle navigation application. In this integration scheme, the GPS derived positions and velocities are used as the update measurements for the INS derived PVA. The KF error state vector in this case includes the navigation parameters as well as the accelerometer and gyroscope error states.

Keywords: GPS, INS, Kalman filter, inertial navigation system

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Authors: A. Benhadji, R. Maachi

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Environmental protection has become a major economic development issues. Indeed, the environment has become both market growth factor and element of competition. It is now an integral part of all industrial strategies. Ecosystem protection is based on the reduction of the pollution load in the treatment of liquid waste. The physicochemical techniques are commonly used which a transfer of pollution is generally found. Alternative to physicochemical methods is the use of microorganisms for cleaning up the waste waters. The objective of this research is the evaluation of the effects of exogenous added Pseudomonas strains on pollutants biodegradation. The influence of the critical parameters such as inoculums concentration and duration treatment are studied. The results show that Pseudomonas putida is found to give a maximum reduction in chemical organic demand (COD) in 4 days of incubation. However, toward to protect biological pollution of environment, the treatment is achieved by electro coagulation process using aluminium electrodes. The results indicate that this process allows disinfecting the water and improving the electro coagulated sludge quality.

Keywords: tannery, pseudomonas, biological treatment, electrocoagulation process, sludge quality

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

Procedia PDF Downloads 79

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

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Authors: Sonali Panigrahy, Manjunatha K., Sudip Barman

Abstract:

Electrocatalytic reduction methods hold significant promise in addressing the urgent need to mitigate excessive greenhouse gas emissions, particularly carbon dioxide (CO₂). A highly effective catalyst is essential for achieving the conversion of CO₂ into valuable products due to the complex, multi-electron, and multi-product nature of the CO₂ reduction process. The electrochemical reduction of CO₂, driven by renewable energy sources, presents a valuable opportunity for simultaneously reducing CO₂ emissions while generating valuable chemicals and fuels, with syngas being a noteworthy product. Silver-based electrodes have been the focus of extensive research due to their low overpotential and remarkable selectivity in promoting the generation of carbon monoxide (CO) in the electrocatalytic carbon dioxide reduction reaction (CO₂RR). In this study, we delve into the synthesis of carbon-supported silver nanoparticles (Ag/C), which serve as efficient electrocatalysts for the reduction of CO₂. The as-prepared catalyst, Ag/C, is not only cost-effective but also highly proficient in facilitating the conversion of CO₂ and H₂O into syngas, which is a customizable mixture of hydrogen (H₂) and carbon monoxide (CO). The highest faradic efficiency for the production of CO on Ag/C was calculated to be 56.4% at -1.4 V vs Ag/AgCl. The maximum partial current density for the generation of CO was determined to be -9.4 mA cm-2 at a potential of -1.6 V vs Ag/AgCl. This research demonstrates the potential of Ag/C as an electrocatalyst to enable the sustainable production of syngas, contributing to the reduction of CO₂ emissions and the synthesis of valuable chemical precursors and fuels.

Keywords: CO₂, carbon monooxide, electrochemical, silver

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Authors: Pushpendra S. Bharti, S. Maheshwari

Abstract:

Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: electric discharge machining, material removal rate, surface roughness, too wear rate, multi-response signal-to-noise ratio, multi response signal-to-noise ratio, optimization

Procedia PDF Downloads 328

Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

Abstract:

High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

Procedia PDF Downloads 104