Search results for: electrochemical performance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13334

Search results for: electrochemical performance

6734 Development of an EEG-Based Real-Time Emotion Recognition System on Edge AI

Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 105
6733 A User Identification Technique to Access Big Data Using Cloud Services

Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

Abstract:

Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

Procedia PDF Downloads 476
6732 UAV’s Enhanced Data Collection for Heterogeneous Wireless Sensor Networks

Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

Abstract:

In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

Procedia PDF Downloads 82
6731 Concentric Circle Detection based on Edge Pre-Classification and Extended RANSAC

Authors: Zhongjie Yu, Hancheng Yu

Abstract:

In this paper, we propose an effective method to detect concentric circles with imperfect edges. First, the gradient of edge pixel is coded and a 2-D lookup table is built to speed up normal generation. Then we take an accumulator to estimate the rough center and collect plausible edges of concentric circles through gradient and distance. Later, we take the contour-based method, which takes the contour and edge intersection, to pre-classify the edges. Finally, we use the extended RANSAC method to find all the candidate circles. The center of concentric circles is determined by the two circles with the highest concentricity. Experimental results demonstrate that the proposed method has both good performance and accuracy for the detection of concentric circles.

Keywords: concentric circle detection, gradient, contour, edge pre-classification, RANSAC

Procedia PDF Downloads 131
6730 Metabolic Predictive Model for PMV Control Based on Deep Learning

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

Abstract:

In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

Procedia PDF Downloads 257
6729 Influence Maximization in Dynamic Social Networks and Graphs

Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

Abstract:

Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

Procedia PDF Downloads 239
6728 Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles

Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane

Abstract:

In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.

Keywords: autonomous vehicles, convoy, non-linear control, non-linear observer, sliding mode

Procedia PDF Downloads 141
6727 Design and Study of a Low Power High Speed 8 Transistor Based Full Adder Using Multiplexer and XOR Gates

Authors: Biswarup Mukherjee, Aniruddha Ghoshal

Abstract:

In this paper, we propose a new technique for implementing a low power high speed full adder using 8 transistors. Full adder circuits are used comprehensively in Application Specific Integrated Circuits (ASICs). Thus it is desirable to have high speed operation for the sub components. The explored method of implementation achieves a high speed low power design for the full adder. Simulated results indicate the superior performance of the proposed technique over conventional 28 transistor CMOS full adder. Detailed comparison of simulated results for the conventional and present method of implementation is presented.

Keywords: high speed low power full adder, 2-T MUX, 3-T XOR, 8-T FA, pass transistor logic, CMOS (complementary metal oxide semiconductor)

Procedia PDF Downloads 348
6726 Improving Health Workers’ Well-Being in Cittadella Hospital (Province of Padua), Italy

Authors: Emanuela Zilli, Suana Tikvina, Davide Bonaldo, Monica Varotto, Scilla Rizzardi, Barbara Ruzzante, Raffaele Napolitano, Stefano Bevilacqua, Antonella Ruffatto

Abstract:

A healthy workplace increases productivity, creativity and decreases absenteeism and turnover. It also contributes to creating a more secure work environment with fewer risks of violence. In the past 3 years, the healthcare system has suffered the psychological, economic and social consequences of the COVID-19 pandemic. On the other hand, the healthcare staff reductions determine high levels of work-related stress that are often unsustainable. The Hospital of Cittadella (in the province of Padua) has 400 beds and serves a territory of 300,000 inhabitants. The hospital itself counts 1.250 healthcare employees (healthcare professionals). This year, the Medical Board of Directors has requested additional staff; however, the economic situation of Italy can not sustain additional hires. At the same time, we have initiated projects that aim to increase well-being, decrease stress and encourage activities that promote self-care. One of the projects that the hospital has organized is the psychomotor practice. It is held by therapists and trainers who operate according to the traditional method. According to the literature, the psychomotor practice is specifically intended for the staff operating in the Intensive Care Unit, Emergency Department and Pneumology Ward. The project consisted of one session of 45 minutes a week for 3 months. This method brings focus to controlled breathing, posture, muscle work and movement that help manage stress and fatigue, creating a more mindful and sustainable lifestyle. In addition, a Qigong course was held every two weeks for 5 months. It is an ancient Chinese practice designed to optimize the energy within the body, reducing stress levels and increasing general well-being. Finally, Tibetan singing crystal bowls sessions, held by a music therapist, consisted of monthly guided meditation sessions using the sounds of the crystal bowls. Sound therapy uses the vibrations created from the crystal bowls to balance the vibrations within the body to promote relaxation. In conclusion, well-being and organizational performance are closely related to each other. It is crucial for any organization to encourage and maintain better physical and mental health of the healthcare staff as it directly affects productivity and, consequently, user satisfaction of the services provided.

Keywords: health promotion, healthcare workers management, Weel being and organizational performance, Psychomotor practice

Procedia PDF Downloads 68
6725 Single Machine Scheduling Problem to Minimize the Number of Tardy Jobs

Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

Abstract:

Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.

Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds

Procedia PDF Downloads 555
6724 Modern Pedagogy Techniques for DC Motor Speed Control

Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

Abstract:

Based on a survey conducted for second and third year students of the electrical engineering department at Maharishi Markandeshwar University, India, it was found that around 92% of students felt that it would be better to introduce a virtual environment for laboratory experiments. Hence, a need was felt to perform modern pedagogy techniques for students which consist of a virtual environment using MATLAB/Simulink. In this paper, a virtual environment for the speed control of a DC motor is performed using MATLAB/Simulink. The various speed control methods for the DC motor include the field resistance control method and armature voltage control method. The performance analysis of the DC motor is hence analyzed.

Keywords: DC Motor, field control, pedagogy techniques, speed control, virtual environment, voltage control

Procedia PDF Downloads 442
6723 Numerical Study of the Dynamic Behavior of an Air Conditioning with a Muti Confined Swirling Jet

Authors: Mohamed Roudane

Abstract:

The objective of this study is to know the dynamic behavior of a multi swirling jet used for air conditioning inside a room. To conduct this study, we designed a facility to ensure proper conditions of confinement in which we placed five air blowing devices with adjustable vanes, providing multiple swirling turbulent jets. The jets were issued in the same direction and the same spacing defined between them. This study concerned the numerical simulation of the dynamic mixing of confined swirling multi-jets, and examined the influence of important parameters of a swirl diffuser system on the dynamic performance characteristics. The CFD investigations are carried out by a hybrid mesh to discretize the computational domain. In this work, the simulations have been performed using the finite volume method and FLUENT solver, in which the standard k-ε RNG turbulence model was used for turbulence computations.

Keywords: simulation, dynamic behavior, swirl, turbulent jet

Procedia PDF Downloads 399
6722 Content-Based Color Image Retrieval Based on the 2-D Histogram and Statistical Moments

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

Procedia PDF Downloads 457
6721 Flexible Design Solutions for Complex Free form Geometries Aimed to Optimize Performances and Resources Consumption

Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

Abstract:

By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

Procedia PDF Downloads 377
6720 Application of Liquid Emulsion Membrane Technique for the Removal of Cadmium(II) from Aqueous Solutions Using Aliquat 336 as a Carrier

Authors: B. Medjahed, M. A. Didi, B. Guezzen

Abstract:

In the present work, emulsion liquid membrane (ELM) technique was applied for the extraction of cadmium(II) present in aqueous samples. Aliquat 336 (Chloride tri-N-octylmethylammonium) was used as carrier to extract cadmium(II). The main objective of this work is to investigate the influence of various parameters affected the ELM formation and its stability and testing the performance of the prepared ELM on removal of cadmium by using synthetic solution with different concentrations. Experiments were conducted to optimize pH of the feed solution and it was found that cadmium(II) can be extracted at pH 6.5. The influence of the carrier concentration and treat ratio on the extraction process was investigated. The obtained results showed that the optimal values are respectively 3% (Aliquat 336) and a ratio (feed: emulsion) equal to 1:1.

Keywords: cadmium, carrier, emulsion liquid membrane, surfactant

Procedia PDF Downloads 406
6719 The Effects of Self-Graphing on the Reading Fluency of an Elementary Student with Learning Disabilities

Authors: Matthias Grünke

Abstract:

In this single-case study, we evaluated the effects of a self-graphing intervention to help students improve their reading fluency. Our participant was a 10-year-old girl with a suspected learning disability in reading. We applied an ABAB reversal design to test the efficacy of our approach. The dependent measure was the number of correctly read words from a children’s book within five minutes. Our participant recorded her daily performance using a simple line diagram. Results indicate that her reading rate improved simultaneously with the intervention and dropped as soon as the treatment was suspended. The findings give reasons for optimism that our simple strategy can be a very effective tool in supporting students with learning disabilities to boost their reading fluency.

Keywords: single-case study, learning disabilities, elementary education, reading problems, reading fluency

Procedia PDF Downloads 111
6718 Bending and Shear Characteristics of Hollowcore Slab with Polystyrene Forms

Authors: Kang Kun Lee

Abstract:

New I-slab system with polystyrene forms and precast concrete deck is proposed to reduce the construction period and the self-weight of the slab. This paper presents experimental works on the bending and shear of the I-slabs. Five specimens were tested. The main parameters of experiments are diameters of the holes made by polystyrene form and the thickness of slab. Structural performance of I-slab is evaluated on the basis of failure mode, load-displacement curve, and ultimate strengths. Based on the test results, it is found that the critical punching shear sections are changed as the test variables are different, hence resulting in the varied punching shear strengths. Test results indicate that the developed I-slab is very effective to increase the strength due to self-weight reduction.

Keywords: hollowcore slab, section force-deformation response, precast concrete deck

Procedia PDF Downloads 390
6717 Preliminary Study of Human Reliability of Control in Case of Fire Based on the Decision Processes and Stress Model of Human in a Fire

Authors: Seung-Un Chae, Heung-Yul Kim, Sa-Kil Kim

Abstract:

This paper presents the findings of preliminary study on human control performance in case of fire. The relationship between human control and human decision is studied in decision processes and stress model of human in a fire. Human behavior aspects involved in the decision process during a fire incident. The decision processes appear that six of individual perceptual processes: recognition, validation, definition, evaluation, commitment, and reassessment. Then, human may be stressed in order to get an optimal decision for their activity. This paper explores problems in human control processes and stresses in a catastrophic situation. Thus, the future approach will be concerned to reduce stresses and ambiguous irrelevant information.

Keywords: human reliability, decision processes, stress model, fire

Procedia PDF Downloads 986
6716 Data Quality as a Pillar of Data-Driven Organizations: Exploring the Benefits of Data Mesh

Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

Abstract:

Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

Procedia PDF Downloads 135
6715 Image Steganography Using Least Significant Bit Technique

Authors: Preeti Kumari, Ridhi Kapoor

Abstract:

 In any communication, security is the most important issue in today’s world. In this paper, steganography is the process of hiding the important data into other data, such as text, audio, video, and image. The interest in this topic is to provide availability, confidentiality, integrity, and authenticity of data. The steganographic technique that embeds hides content with unremarkable cover media so as not to provoke eavesdropper’s suspicion or third party and hackers. In which many applications of compression, encryption, decryption, and embedding methods are used for digital image steganography. Due to compression, the nose produces in the image. To sustain noise in the image, the LSB insertion technique is used. The performance of the proposed embedding system with respect to providing security to secret message and robustness is discussed. We also demonstrate the maximum steganography capacity and visual distortion.

Keywords: steganography, LSB, encoding, information hiding, color image

Procedia PDF Downloads 474
6714 Characteristic on Compressive Strength of Blast Slag and Fly Ash Hybrid Geopolymer Mortar

Authors: G. S. Ryu, K. T. Koh, H. Y. Kim, G. H. An, D. W. Seo

Abstract:

Geopolymer mortar is produced by alkaline activation of pozzolanic materials such as fly ground granulated blast-furnace slag (GGBFS) and fly ash (FA). Its unique reaction pathway facilitates rapid strength development in comparison with hydration of ordinary Portland cement (OPC). Geopolymer can be fabricated using various types and dosages of alkali-activator, which effectively gives a wider control over the performance of the final product. The present study investigates the effect of types of precursors and curing conditions on the fresh state and strength development characteristics of geopolymers, thereby comparatively exploring the effect of precursors from various sources of origin. The obtained result showed that the setting time and strength development of the specimens with the identical mix proportion but different precursors displayed significant variations.

Keywords: alkali-activated material, blast furnace slag, fly ash, flowability, strength development

Procedia PDF Downloads 248
6713 Influence of the Nature of Plants on Drainage, Purification Performance and Quality of Biosolids on Faecal Sludge Planted Drying Beds in Sub-Saharan Climate Conditions

Authors: El Hadji Mamadou Sonko, Mbaye Mbéguéré, Cheikh Diop, Linda Strande

Abstract:

In new approaches that are being developed for the treatment of sludge, the valorization of by-product is increasingly encouraged. In this perspective, Echinochloa pyramidalis has been successfully tested in Cameroon. Echinochloa pyramidalis is an efficient forage plant in the treatment of faecal sludge. It provides high removal rates and biosolids of high agronomic value. Thus in order to advise the use of this plant in planted drying beds in Senegal its comparison with the plants long been used in the field deserves to be carried out. That is the aim of this study showing the influence of the nature of the plants on the drainage, the purifying performances and the quality of the biosolids. Echinochloa pyramidalis, Typha australis, and Phragmites australis are the three macrophytes used in this study. The drainage properties of the beds were monitored through the frequency of clogging, the percentage of recovered leachate and the dryness of the accumulated sludge. The development of plants was followed through the measurement of the density. The purification performances were evaluated from the incoming raw sludge flows and the outflows of leachate for parameters such as Total Solids (TS), Total Suspended Solids (TSS), Total Volatile Solids (TVS), Chemical Oxygen Demand (COD), Total Kjeldahl Nitrogen (TKN), Ammonia (NH₄⁺), Nitrate (NO₃⁻), Total Phosphorus (TP), Orthophosphorus (PO₄³⁻) and Ascaris eggs. The quality of the biosolids accumulated on the beds was measured after 3 months of maturation for parameters such as dryness, C/N ratio NH₄⁺/NO₃⁻ ratio, ammonia, Ascaris eggs. The results have shown that the recovered leachate volume is about 40.4%; 45.6% and 47.3%; the dryness about 41.7%; 38.7% and 28.7%, and clogging frequencies about 6.7%; 8.2% and 14.2% on average for the beds planted with Echinochloa pyramidalis, Typha australis and Phragmites australis respectively. The plants of Echinochloa pyramidalis (198.6 plants/m²) and Phragmites australis (138 plants/m²) have higher densities than Typha australis (90.3 plants/m²). The nature of the plants has no influence on the purification performance with reduction percentages around 80% or more for all the parameters followed whatever the nature of the plants. However, the concentrations of these various leachate pollutants are above the limit values of the Senegalese standard NS 05-061 for the release into the environment. The biosolids harvested after 3 months of maturation are all mature with C/N ratios around 10 for all the macrophytes. The NH₄⁺/NO₃⁻ ratio is lower than 1 except for the biosolids originating from the Echinochloa pyramidalis beds. The ammonia is also less than 0.4 g/kg except for biosolids from Typha australis beds. Biosolids are also rich in mineral elements. Their concentrations of Ascaris eggs are higher than the WHO recommendations despite a percentage of inactivation around 80%. These biosolids must be stored for an additional time or composted. From these results, the use of Echinochloa pyramidalis as the main macrophyte can be recommended in the various drying beds planted in sub-Saharan climate conditions.

Keywords: faecal sludge, nature of plants, quality of biosolids, treatment performances

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6712 A Compact Quasi-Zero Stiffness Vibration Isolator Using Flexure-Based Spring Mechanisms Capable of Tunable Stiffness

Authors: Thanh-Phong Dao, Shyh-Chour Huang

Abstract:

This study presents a quasi-zero stiffness (QZS) vibration isolator using flexure-based spring mechanisms which afford both negative and positive stiffness elements, which enable self-adjustment. The QZS property of the isolator is achieved at the equilibrium position. A nonlinear mathematical model is then developed, based on the pre-compression of the flexure-based spring mechanisms. The dynamics are further analyzed using the Harmonic Balance method. The vibration attention efficiency is illustrated using displacement transmissibility, which is then compared with the corresponding linear isolator. The effects of parameters on performance are also investigated by numerical solutions. The flexure-based spring mechanisms are subsequently designed using the concept of compliant mechanisms, with evaluation by ANSYS software, and simulations of the QZS isolator.

Keywords: vibration isolator, quasi-zero stiffness, flexure-based spring mechanisms, compliant mechanism

Procedia PDF Downloads 463
6711 Proactive Pure Handoff Model with SAW-TOPSIS Selection and Time Series Predict

Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

Abstract:

This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

Procedia PDF Downloads 488
6710 Thermal Performance of Hybrid PVT Collector with Natural Circulation

Authors: K. Touafek, A. Khelifa, I. Tabet, H. Haloui, H. Bencheikh El Houcine, M. Adouane

Abstract:

Hybrid photovoltaic thermal (PVT) collectors allow simultaneous production of electrical energy thus heat energy. There are several configurations of hybrid collectors (to produce water or air). For hybrids water collectors, there are several configurations that differ by the nature of the absorber (serpentine, tubes...). In this paper, an absorber tank is studied. The circulation of the coolant is natural (we do not use the pump). We present the obtained results in our experimental study and we analyzed the data, and then we compare the results with the theory practices. The electrical performances of the hybrid collector are compared with those of conventional photovoltaic module mounted on the same structure and measured under the same conditions. We conducted experiments with natural circulation of the coolant (Thermosyphon), for a flow rate of 0.025kg/m².

Keywords: experimental, photovoltaic, solar, temperature, tank

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6709 Comparison of Chemical Coagulation and Electrocoagulation for Boron Removal from Synthetic Wastewater Using Aluminium

Authors: Kartikaningsih Danis, Yao-Hui Huang

Abstract:

Various techniques including conventional and advanced have been employed for the boron treatment from water and wastewater. The electrocoagulation involves an electrolytic reactor for coagulation/flotation with aluminium as anode and cathode. There is aluminium as coagulant to be used for removal which may induce secondary pollution in chemical coagulation. The purpose of this study is to investigate and compare the performance between electrocoagulation and chemical coagulation on boron removal from synthetic wastewater. The effect of different parameters, such as pH reaction, coagulant dosage, and initial boron concentration were examined. The results show that the boron removal using chemical coagulation was lower. At the optimum condition (e.g. pH 8 and 0.8 mol coagulant dosage), boron removal efficiencies for chemical coagulation and electrocoagulation were 61% and 91%, respectively. In addition, the electrocoagulation needs no chemical reagents and makes the boron treatment easy for application.

Keywords: boron removal, chemical coagulation, aluminum, electro-coagulation

Procedia PDF Downloads 404
6708 Hardware Co-Simulation Based Based Direct Torque Control for Induction Motor Drive

Authors: Hanan Mikhael Dawood, Haider Salim, Jafar Al-Wash

Abstract:

This paper presents Proportional-Integral (PI) controller to improve the system performance which gives better torque and flux response. In addition, it reduces the undesirable torque ripple. The conventional DTC controller approach for induction machines, based on an improved torque and stator flux estimator, is implemented using Xilinx System Generator (XSG) for MATLAB/Simulink environment through Xilinx blocksets. The design was achieved in VHDL which is based on a MATLAB/Simulink simulation model. The hardware in the loop results are obtained considering the implementation of the proposed model on the Xilinx NEXYS2 Spartan 3E1200 FG320 Kit.

Keywords: induction motor, Direct Torque Control (DTC), Xilinx FPGA, motor drive

Procedia PDF Downloads 622
6707 Iterative Panel RC Extraction for Capacitive Touchscreen

Authors: Chae Hoon Park, Jong Kang Park, Jong Tae Kim

Abstract:

Electrical characteristics of capacitive touchscreen need to be accurately analyzed to result in better performance for multi-channel capacitance sensing. In this paper, we extracted the panel resistances and capacitances of the touchscreen by comparing measurement data and model data. By employing a lumped RC model for driver-to-receiver paths in touchscreen, we estimated resistance and capacitance values according to the physical lengths of channel paths which are proportional to the RC model. As a result, we obtained the model having 95.54% accuracy of the measurement data.

Keywords: electrical characteristics of capacitive touchscreen, iterative extraction, lumped RC model, physical lengths of channel paths

Procedia PDF Downloads 334
6706 Combining Shallow and Deep Unsupervised Machine Learning Techniques to Detect Bad Actors in Complex Datasets

Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

Abstract:

Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

Procedia PDF Downloads 95
6705 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

Procedia PDF Downloads 405