Search results for: optical techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8056

Search results for: optical techniques

4186 Blockchain’s Feasibility in Military Data Networks

Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

Abstract:

Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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4185 A Study of the Performance Parameter for Recommendation Algorithm Evaluation

Authors: C. Rana, S. K. Jain

Abstract:

The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

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4184 Assesing Spatio-Temporal Growth of Kochi City Using Remote Sensing Data

Authors: Navya Saira George, Patroba Achola Odera

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This study aims to determine spatio-temporal expansion of Kochi City, situated on the west coast of Kerala State in India. Remote sensing and GIS techniques have been used to determine land use/cover and urban expansion of the City. Classification of Landsat images of the years 1973, 1988, 2002 and 2018 have been used to reproduce a visual story of the growth of the City over a period of 45 years. Accuracy range of 0.79 ~ 0.86 is achieved with kappa coefficient range of 0.69 ~ 0.80. Results show that the areas covered by vegetation and water bodies decreased progressively from 53.0 ~ 30.1% and 34.1 ~ 26.2% respectively, while built-up areas increased steadily from 12.5 to 42.2% over the entire study period (1973 ~ 2018). The shift in land use from agriculture to non-agriculture may be attributed to the land reforms since 1980s.

Keywords: Geographical Information Systems, Kochi City, Land use/cover, Remote Sensing, Urban Sprawl

Procedia PDF Downloads 127
4183 Convergence Analysis of Cubic B-Spline Collocation Method for Time Dependent Parabolic Advection-Diffusion Equations

Authors: Bharti Gupta, V. K. Kukreja

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A comprehensive numerical study is presented for the solution of time-dependent advection diffusion problems by using cubic B-spline collocation method. The linear combination of cubic B-spline basis, taken as approximating function, is evaluated using the zeros of shifted Chebyshev polynomials as collocation points in each element to obtain the best approximation. A comparison, on the basis of efficiency and accuracy, with the previous techniques is made which confirms the superiority of the proposed method. An asymptotic convergence analysis of technique is also discussed, and the method is found to be of order two. The theoretical analysis is supported with suitable examples to show second order convergence of technique. Different numerical examples are simulated using MATLAB in which the 3-D graphical presentation has taken at different time steps as well as different domain of interest.

Keywords: cubic B-spline basis, spectral norms, shifted Chebyshev polynomials, collocation points, error estimates

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4182 Analysis of Supply Chain Complexity Sub-Dimensions for Garment Industry

Authors: Niyanta Mehra, Aakriti Khurania, Kshitij Rastogi, S. K. Garg

Abstract:

There is plenty of literature available that accounts for complexity management in a supply chain. A major fraction of this literature considers a large number of parameters in order to devise management techniques. However, multiple such parameters do not directly affect the result, and incorporating these can make the analyses overly complicated. Most of the causes of supply chain inefficiencies are due to the interconnectedness and interdependencies in the structure, processes, and environment of the supply chains. The level of complexity varies across industries in terms of intensity and ease of management. After a review of the literature related to complexities in supply chains, the paper attempts to build a framework to study the relative significance of these complexities. This paper aims to identify critical complexities for the garment industry. Understanding and controlling these complexities open avenues for better supply chain management and also assist decision-makers in the garment industry in formulating risk mitigation strategies.

Keywords: complexity dimensions, garment industry, supply chain complexity, supply chain management

Procedia PDF Downloads 141
4181 Enhancing Financial Security: Real-Time Anomaly Detection in Financial Transactions Using Machine Learning

Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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4180 Composite Kernels for Public Emotion Recognition from Twitter

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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4179 Solving Crimes through DNA Methylation Analysis

Authors: Ajay Kumar Rana

Abstract:

Predicting human behaviour, discerning monozygotic twins or left over remnant tissues/fluids of a single human source remains a big challenge in forensic science. Recent advances in the field of DNA methylations which are broadly chemical hallmarks in response to environmental factors can certainly help to identify and discriminate various single-source DNA samples collected from the crime scenes. In this review, cytosine methylation of DNA has been methodologically discussed with its broad applications in many challenging forensic issues like body fluid identification, race/ethnicity identification, monozygotic twins dilemma, addiction or behavioural prediction, age prediction, or even authenticity of the human DNA. With the advent of next-generation sequencing techniques, blooming of DNA methylation datasets and together with standard molecular protocols, the prospect of investigating and solving the above issues and extracting the exact nature of the truth for reconstructing the crime scene events would be undoubtedly helpful in defending and solving the critical crime cases.

Keywords: DNA methylation, differentially methylated regions, human identification, forensics

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4178 Dynamical Models for Enviromental Effect Depuration for Structural Health Monitoring of Bridges

Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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4177 Bioreactor for Cell-Based Impedance Measuring with Diamond Coated Gold Interdigitated Electrodes

Authors: Roman Matejka, Vaclav Prochazka, Tibor Izak, Jana Stepanovska, Martina Travnickova, Alexander Kromka

Abstract:

Cell-based impedance spectroscopy is suitable method for electrical monitoring of cell activity especially on substrates that cannot be easily inspected by optical microscope (without fluorescent markers) like decellularized tissues, nano-fibrous scaffold etc. Special sensor for this measurement was developed. This sensor consists of corning glass substrate with gold interdigitated electrodes covered with diamond layer. This diamond layer provides biocompatible non-conductive surface for cells. Also, a special PPFC flow cultivation chamber was developed. This chamber is able to fix sensor in place. The spring contacts are connecting sensor pads with external measuring device. Construction allows real-time live cell imaging. Combining with perfusion system allows medium circulation and generating shear stress stimulation. Experimental evaluation consist of several setups, including pure sensor without any coating and also collagen and fibrin coating was done. The Adipose derived stem cells (ASC) and Human umbilical vein endothelial cells (HUVEC) were seeded onto sensor in cultivation chamber. Then the chamber was installed into microscope system for live-cell imaging. The impedance measurement was utilized by vector impedance analyzer. The measured range was from 10 Hz to 40 kHz. These impedance measurements were correlated with live-cell microscopic imaging and immunofluorescent staining. Data analysis of measured signals showed response to cell adhesion of substrates, their proliferation and also change after shear stress stimulation which are important parameters during cultivation. Further experiments plan to use decellularized tissue as scaffold fixed on sensor. This kind of impedance sensor can provide feedback about cell culture conditions on opaque surfaces and scaffolds that can be used in tissue engineering in development artificial prostheses. This work was supported by the Ministry of Health, grants No. 15-29153A and 15-33018A.

Keywords: bio-impedance measuring, bioreactor, cell cultivation, diamond layer, gold interdigitated electrodes, tissue engineering

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4176 Pedagogical Technologies of Teaching Natural Geography

Authors: Mirzahmedov Ismoiljon Karimjon Ugli, Juraeva Shakhnoza Abdumalik Kizi

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The article deals with the current scientific problems of natural geography related to the development of new pedagogical technologies and their implementation in the educational process. The use of recommended interactive methods in independent study is considered very effective and is a very useful method for students, especially for students who work more on themselves. Today's demand is to make young people talented, intelligent, innovative, as well as mature and well-rounded individuals, as a result of the work carried out in the field of education today. This is how creating tables of different contents and filling them out shows the student's talent and desire for innovation. Also, the techniques and methods necessary for today's student are shown, the role of the teacher in conducting lessons meaningfully, the suitability of the method used by the teacher for the lesson, factors affecting the quality of education, and natural issues of the use of methods based on the specific features of geography are highlighted.

Keywords: teaching methods, educational process, educational technologies, education, problem, didactics, natural geography

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4175 The Contribution of Woman Towards Social Development: A Case of Saudi Arabia

Authors: Haga Elimam

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The study has contributed to determine the degree to which the women of Saudi Arabia play an imperative role in the developmental processes. This research provided a twofold objective to motivate Saudi females to take part in the development of society. The quantitative design has been implied for assessing outcomes through descriptive statistics techniques. The data has been analyzed by regression analysis. The outcomes of the study showed that when women were provided with health and educational necessities and adequate opportunities, they were able to contribute effectively in achieving desired developmental objectives for the nation. Saudi women constitute approximately half of the society; thus, they are equally provided health and justice rights. It has been concluded through the results of the study that the nature of Saudi society, customs, traditions, and beliefs affect the role played by women of Saudi Arabia. This study examines the tangible changes that comprised all aspects of life due to international exposure.

Keywords: social development, social service, sustainable development, civil society and educational sector

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4174 Reliability Analysis for the Functioning of Complete and Low Capacity MLDB Systems in Piston Plants

Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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4173 Mechanical Cortical Bone Characterization with the Finite Element Method Based Inverse Method

Authors: Djamel Remache, Marie Semaan, Cécile Baron, Martine Pithioux, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

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Cortical bone is a complex multi-scale structure. Even though several works have contributed significantly to understanding its mechanical behavior, this behavior remains poorly understood. Nanoindentation testing is one of the primary testing techniques for the mechanical characterization of bone at small scales. The purpose of this study was to provide new nanoindentation data of cortical bovine bone in different directions and at different bone microstructures (osteonal, interstitial and laminar bone), and then to identify anisotropic properties of samples with FEM (finite element method) based inverse method. Experimentally and numerical results were compared. Experimental and numerical results were compared. The results compared were in good agreement.

Keywords: mechanical behavior of bone, nanoindentation, finite element analysis, inverse optimization approach

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4172 Effect of Non-Fat Solid Ratio on Bloom Formation in Untempered Chocolate

Authors: Huanhuan Zhao, Bryony J. James

Abstract:

The relationship between the non-fat solid ratio and bloom formation in untempered chocolate was investigated using two types of chocolate: model chocolate made of varying cocoa powder ratios (46, 49.5 and 53%) and cocoa butter, and commercial Lindt chocolate with varying cocoa content (70, 85 and 90%). X-ray diffraction and colour measurement techniques were used to examine the polymorphism of cocoa butter and the surface whiteness index (WI), respectively. The polymorphic transformation of cocoa butter was highly correlated with the changes of WI during 30 days of storage since it led to the redistribution of fat within the chocolate matrix and resulted in a bloomed surface. The change in WI indicated a similar bloom rate in the chocolates, but the model chocolates with a higher cocoa powder ratio had more pronounced total bloom. This is due to a higher ratio of non-fat solid particles on the surface resulting in microscopic changes in morphology. The ratio of non-fat solids is an important factor in determining the extent of bloom but not the bloom rate.

Keywords: untempered chocolate, microstructure of bloom, polymorphic transformation, surface whiteness

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4171 Toluene Methylation with Methanol Using Synthesized HZSM-5 Catalysts Modified by Silylation and Dealumination

Authors: Weerachit Pulsawas, Thirasak Rirksomboon

Abstract:

Due to its abundance from catalytic reforming and thermal cracking of naphtha, toluene could become more value-added compound if it is converted into xylenes, particularly p-xylene, via toluene methylation. Attractively, toluene methylation with methanol is an alternative route to produce xylenes in the absence of other hydrocarbon by-products for which appropriate catalyst would be utilized. In this study, HZSM-5 catalysts with Si/Al molar ratio of 100 were synthesized via hydrothermal treatment and modified by either chemical liquid deposition using tetraethyl-orthosilicate or dealumination with steam. The modified catalysts were characterized by several techniques and tested for their catalytic activity in a continuous down-flow fixed bed reactor. Various operating conditions including WHSV’s of 5 to 20 h-1, reaction temperatures of 400 to 500 °C, and toluene-to-methanol molar ratios (T/M) of 1 to 4 were investigated for attaining possible highest p-xylene selectivity. As a result, the catalytic activity of parent HZSM-5 with temperature of 400 °C, T/M of 4 and WHSV of 24 h-1 showed 65.36% in p-xylene selectivity and 11.90% in toluene conversion as demonstrated for 4 h on stream.

Keywords: toluene methylaion, HZSM-5, silylation, dealumination

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4170 Hierarchically Modeling Cognition and Behavioral Problems of an Under-Represented Group

Authors: Zhidong Zhang, Zhi-Chao Zhang

Abstract:

This study examines adolescent psychological and behavioral problems. The Achenbach systems of empirically based assessment (ASEBA) were used as the instrument. The problem framework consists of internal, external and social behavioral problems which are theoretically developed based on about 113 items plus relevant background variables. In this study, the sample consist of 1,975 sixth and seventh grade students in Northeast China. Stratified random sampling method was used to collect the data, meaning that samples were from different school districts, schools, and classes. The researchers looked at both macro and micro effect. Therefore, multilevel analysis techniques were used in the data analysis. The parts of the research results indicated that the background variables such as extracurricular activities were directly related to students’ internal problems.

Keywords: behavioral problems, anxious/depressed problems, internalizing problems, mental health, under-represented groups, empirically-based assessment, hierarchical modeling, ASEBA, multilevel analysis

Procedia PDF Downloads 596
4169 Valorization of Sawdust for the Treatment of Purified Water for Irrigation

Authors: Dalila Oulhaci, Mohammed Zahaf

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The watering technique is essential to maintain a moist perimeter around the roots of the crop. This is the case with topical watering, where the soil around the root system can be kept permanently moist between the two extremes of water content. Moreover, one of the oldest methods used since Roman times throughout North Africa and the Near East was based on the repeated pouring of water into porous earthen vessels buried in the ground. In this context, these two techniques have been combined by replacing the earthen vase with plastic bottles filled with sand which release water through their perforated walls into the surrounding soil. The objective of this work is to first determine the purifying power of the activated sludge treatment plant of Toggourt and then that of the bottled Sawdust filter. For the station, the BOD purification rate was (96.5%), the COD purification rate was (87%) and suspended solids (90%). For the bottle, the BOD removal rate was (35%), and COD removal rate was (12.58%). This work falls within the framework of water saving, sustainable development and environmental protection, and also within the framework of agriculture.

Keywords: wasterwater, sawdust, purification, irrigation, touggourt (Algeria)

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4168 Inverter IGBT Open–Circuit Fault Detection Using Park's Vectors Enhanced by Polar Coordinates

Authors: Bendiabdellah Azzeddine, Cherif Bilal Djamal Eddine

Abstract:

The three-phase power converter voltage structure is widely used in many power applications but its failure can lead to partial or total loss of control of the phase currents and can cause serious system malfunctions or even a complete system shutdown. To ensure continuity of service in all circumstances, effective and rapid techniques of detection and location of inverter fault is to be implemented. The present paper is dedicated to open-circuit fault detection in a three-phase two-level inverter fed induction motor. For detection purpose, the proposed contribution addresses the Park’s current vectors associated to a polar coordinates calculation tool to compute the exact value of the fault angle corresponding directly to the faulty IGBT switch. The merit of the proposed contribution is illustrated by experimental results.

Keywords: diagnosis, detection, Park’s vectors, polar coordinates, open-circuit fault, inverter, IGBT switch

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4167 Hybrid GA-PSO Based Pitch Controller Design for Aircraft Control System

Authors: Vaibhav Singh Rajput, Ravi Kumar Jatoth, Nagu Bhookya, Bhasker Boda

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In this paper proportional, integral, derivative (PID) controller is used to control the pitch angle of the aircraft when the elevation angle is changed or modified. The pitch angle is dependent on elevation angle; a change in one corresponds to a change in the other. The PID controller helps in restricted change of pitch rate in response to the elevation angle. The PID controller is dependent on different parameters like Kp, Ki, Kd which change the pitch rate as they change. Various methodologies are used for changing those parameters for getting a perfect time response pitch angle, as desired or wished by a concerned person. While reckoning the values of those parameters, trial and guessing may prove to be futile in order to provide comfort to passengers. So, using some metaheuristic techniques can be useful in handling these errors. Hybrid GA-PSO is one such powerful algorithm which can improve transient and steady state response and can give us more reliable results for PID gain scheduling problem.

Keywords: pitch rate, elevation angle, PID controller, genetic algorithm, particle swarm optimization, phugoid

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4166 Application of UAS in Forest Firefighting for Detecting Ignitions and 3D Fuel Volume Estimation

Authors: Artur Krukowski, Emmanouela Vogiatzaki

Abstract:

The article presents results from the AF3 project “Advanced Forest Fire Fighting” focused on Unmanned Aircraft Systems (UAS)-based 3D surveillance and 3D area mapping using high-resolution photogrammetric methods from multispectral imaging, also taking advantage of the 3D scanning techniques from the SCAN4RECO project. We also present a proprietary embedded sensor system used for the detection of fire ignitions in the forest using near-infrared based scanner with weight and form factors allowing it to be easily deployed on standard commercial micro-UAVs, such as DJI Inspire or Mavic. Results from real-life pilot trials in Greece, Spain, and Israel demonstrated added-value in the use of UAS for precise and reliable detection of forest fires, as well as high-resolution 3D aerial modeling for accurate quantification of human resources and equipment required for firefighting.

Keywords: forest wildfires, surveillance, fuel volume estimation, firefighting, ignition detectors, 3D modelling, UAV

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4165 Covariance of the Queue Process Fed by Isonormal Gaussian Input Process

Authors: Samaneh Rahimirshnani, Hossein Jafari

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In this paper, we consider fluid queueing processes fed by an isonormal Gaussian process. We study the correlation structure of the queueing process and the rate of convergence of the running supremum in the queueing process. The Malliavin calculus techniques are applied to obtain relations that show the workload process inherits the dependence properties of the input process. As examples, we consider two isonormal Gaussian processes, the sub-fractional Brownian motion (SFBM) and the fractional Brownian motion (FBM). For these examples, we obtain upper bounds for the covariance function of the queueing process and its rate of convergence to zero. We also discover that the rate of convergence of the queueing process is related to the structure of the covariance function of the input process.

Keywords: queue length process, Malliavin calculus, covariance function, fractional Brownian motion, sub-fractional Brownian motion

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4164 The Strategy of Traditional Religious Culture Tourism: Taking Taiwan Minhsiung Infernal Lord Festival for Example

Authors: Ching-Yi Wang

Abstract:

The purpose of this study is to explore strategies for integrate Minhsiung environments and cultural resources for Infernal Lord Festival. Minhsiung Infernal Lord Festival is one of the famous religious event in Chia-Yi County, Taiwan. This religious event and the life of local residents are inseparable. Minhsiung Infernal Lord Festival has a rich cultural ceremonies meaning and sentiment of local concern. This study apply field study, document analysis and interviews to analyze Minhsiung Township’s featured attractions and folklore events. The research results reveal the difficulties and strategies while incorporating culture elements into culture tourism. This study hopes to provide innovative techniques for the purpose of prolonging the feasibility of future development of the tradition folk culture.

Keywords: Taiwan folk culture, Minhsiung Infernal Lord Festival, religious tourism, folklore, cultural tourism

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4163 Reduction of Energy Consumption of Distillation Process by Recovering the Heat from Exit Streams

Authors: Apichit Svang-Ariyaskul, Thanapat Chaireongsirikul, Pawit Tangviroon

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Distillation consumes enormous quantity of energy. This work proposed a process to recover the energy from exit streams during the distillation process of three consecutive columns. There are several novel techniques to recover the heat with the distillation system; however, a complex control system is required. This work proposed a simpler technique by exchanging the heat between streams without interrupting the internal distillation process that might cause a serious control problem. The proposed process is executed by using heat exchanger network with pinch analysis to maximize the process heat recovery. The test model is the distillation of butane, pentane, hexane, and heptanes, which is a common mixture in the petroleum refinery. This proposed process saved the energy consumption for hot and cold utilities of 29 and 27%, which is considered significant. Therefore, the recovery of heat from exit streams from distillation process is proved to be effective for energy saving.

Keywords: distillation, heat exchanger, network pinch analysis, chemical engineering

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4162 Interdigitated Flexible Li-Ion Battery by Aerosol Jet Printing

Authors: Yohann R. J. Thomas, Sébastien Solan

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Conventional battery technology includes the assembly of electrode/separator/electrode by standard techniques such as stacking or winding, depending on the format size. In that type of batteries, coating or pasting techniques are only used for the electrode process. The processes are suited for large scale production of batteries and perfectly adapted to plenty of application requirements. Nevertheless, as the demand for both easier and cost-efficient production modes, flexible, custom-shaped and efficient small sized batteries is rising. Thin-film, printable batteries are one of the key areas for printed electronics. In the frame of European BASMATI project, we are investigating the feasibility of a new design of lithium-ion battery: interdigitated planar core design. Polymer substrate is used to produce bendable and flexible rechargeable accumulators. Direct fully printed batteries lead to interconnect the accumulator with other electronic functions for example organic solar cells (harvesting function), printed sensors (autonomous sensors) or RFID (communication function) on a common substrate to produce fully integrated, thin and flexible new devices. To fulfill those specifications, a high resolution printing process have been selected: Aerosol jet printing. In order to fit with this process parameters, we worked on nanomaterials formulation for current collectors and electrodes. In addition, an advanced printed polymer-electrolyte is developed to be implemented directly in the printing process in order to avoid the liquid electrolyte filling step and to improve safety and flexibility. Results: Three different current collectors has been studied and printed successfully. An ink of commercial copper nanoparticles has been formulated and printed, then a flash sintering was applied to the interdigitated design. A gold ink was also printed, the resulting material was partially self-sintered and did not require any high temperature post treatment. Finally, carbon nanotubes were also printed with a high resolution and well defined patterns. Different electrode materials were formulated and printed according to the interdigitated design. For cathodes, NMC and LFP were efficaciously printed. For anodes, LTO and graphite have shown to be good candidates for the fully printed battery. The electrochemical performances of those materials have been evaluated in a standard coin cell with lithium-metal counter electrode and the results are similar with those of a traditional ink formulation and process. A jellified plastic crystal solid state electrolyte has been developed and showed comparable performances to classical liquid carbonate electrolytes with two different materials. In our future developments, focus will be put on several tasks. In a first place, we will synthesize and formulate new specific nano-materials based on metal-oxyde. Then a fully printed device will be produced and its electrochemical performance will be evaluated.

Keywords: high resolution digital printing, lithium-ion battery, nanomaterials, solid-state electrolytes

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4161 Understanding Magnetic Properties of Cd1-xSnxCr2Se4 Using Local Structure Probes

Authors: P. Suchismita Behera, V. G. Sathe, A. K. Nigam, P. A. Bhobe

Abstract:

Co-existence of long-range ferromagnetism and semi-conductivity with correlated behavior of structural, magnetic, optical and electrical properties in various sites doping at CdCr2Se4 makes it a most promising candidate for spin-based electronic applications and magnetic devices. It orders ferromagnetically below TC = 130 K with a direct band gap of ~ 1.5 eV. The magnetic ordering is believed to result from strong competition between the direct antiferromagnetic Cr-Cr spin couplings and the ferromagnetic Cr-Se-Cr exchange interactions. With an aim of understanding the influence of crystal structure on its magnetic properties without disturbing the magnetic site, we investigated four compositions with 3%, 5%, 7% and 10% of Sn-substitution at Cd-site. Partial substitution of Cd2+ (0.78Å) by small sized nonmagnetic ion, Sn4+ (0.55Å), is expected to bring about local lattice distortion as well as a change in electronic charge distribution. The structural disorder would affect the Cd/Sn – Se bonds thus affecting the Cr-Cr and Cr-Se-Cr bonds. Whereas, the charge imbalance created due to Sn4+ substitution at Cd2+ leads to the possibility of Cr mixed valence state. Our investigation of the local crystal structure using the EXAFS, Raman spectroscopy and magnetic properties using SQUID magnetometry of the Cd1-xSnxCr2Se4 series reflects this premise. All compositions maintain the Fd3m cubic symmetry with tetrahedral distribution of Sn at Cd-site, as confirmed by XRD analysis. Lattice parameters were determined from the Rietveld refinement technique of the XRD data and further confirmed from the EXAFS spectra recorded at Cr K-edge. Presence of five Raman-active phonon vibrational modes viz. (T2g (1), T2g (2), T2g (3), Eg, A1g) in the Raman spectra further confirms the crystal symmetry. Temperature dependence of the Raman data provides interesting insight to the spin– phonon coupling, known to dominate the magneto-capacitive properties in the parent compound. Below the magnetic ordering temperature, the longitudinal damping of Eg mode associated with Se-Cd/Sn-Se bending and T2g (2) mode associated to Cr-Se-Cr interaction, show interesting deviations with respect to increase in Sn substitution. Besides providing the estimate of TC, the magnetic measurements recorded as a function of field provide the values of total magnetic moment for all the studied compositions indicative of formation of multiple Cr valences.

Keywords: exchange interactions, EXAFS, ferromagnetism, Raman spectroscopy, spinel chalcogenides

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4160 On Block Vandermonde Matrix Constructed from Matrix Polynomial Solvents

Authors: Malika Yaici, Kamel Hariche

Abstract:

In control engineering, systems described by matrix fractions are studied through properties of block roots, also called solvents. These solvents are usually dealt with in a block Vandermonde matrix form. Inverses and determinants of Vandermonde matrices and block Vandermonde matrices are used in solving problems of numerical analysis in many domains but require costly computations. Even though Vandermonde matrices are well known and method to compute inverse and determinants are many and, generally, based on interpolation techniques, methods to compute the inverse and determinant of a block Vandermonde matrix have not been well studied. In this paper, some properties of these matrices and iterative algorithms to compute the determinant and the inverse of a block Vandermonde matrix are given. These methods are deducted from the partitioned matrix inversion and determinant computing methods. Due to their great size, parallelization may be a solution to reduce the computations cost, so a parallelization of these algorithms is proposed and validated by a comparison using algorithmic complexity.

Keywords: block vandermonde matrix, solvents, matrix polynomial, matrix inverse, matrix determinant, parallelization

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4159 Sleep Apnea Hypopnea Syndrom Diagnosis Using Advanced ANN Techniques

Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

Abstract:

Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

Procedia PDF Downloads 115
4158 Applications of AI, Machine Learning, and Deep Learning in Cyber Security

Authors: Hailyie Tekleselase

Abstract:

Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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4157 Performance and Emission Prediction in a Biodiesel Engine Fuelled with Honge Methyl Ester Using RBF Neural Networks

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

Abstract:

In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 550