Search results for: thermal network

Authors: Haibo Sheng, Yuan Hu

Abstract:

Spinel structure Zinc stannate (Zn2SnO4, ZS)/Graphene was successfully synthesized by a simple in situ hydrothermal route. Morphological study and structure analysis confirmed the homogenously loading of ZS on the graphene sheets. Then, the resulted ZS/graphene hybrids were incorporated into epoxy resin to form EP/ZS/graphene composites by a solvent dispersion method. Improved thermal stability was investigated by Thermogravimetric Analysis (TGA). Cone calorimeter result showed low peak heat release rate (PHRR). Toxical gases release during combustion was evaluated by a facile device organized in our lab. The results showed that the release of NOx, HCN decrease of about 55%. Also, TG-IR technology was used to investigate the gas release during the EP decomposition process. The CO release had decreased about 80%.The EP/G/ZS showed lowest hazards during combustion (including flame retardancy, thermal stability, lower toxical gases release and so on) than pure EP.

Keywords: fire hazards, zinc stannate, epoxy resin, toxical gas hazards

Procedia PDF Downloads 182

Authors: Francisco J. García-de-Quirós, Gianmarco Radice

Abstract:

When considering small robots working in a cooperative community for Moon surface exploration, navigation and inter-nodes communication aspects become a critical issue for the mission success. For this approach to succeed, it is necessary however to deploy the required infrastructure for the robotic community to achieve efficient self-localization as well as relative positioning and communications between nodes. In this paper, an exploration mission concept in which two cooperative robotic systems co-exist is presented. This paradigm hinges on a community of reference agents that provide support in terms of communication and navigation to a second agent community tasked with exploration goals. The work focuses on the role of the agent community in charge of the overall support and, more specifically, will focus on the positioning and navigation methods implemented in RF microwave bands, which are combined with the communication services. An analysis of the different methods for range and position calculation are presented, as well as the main limiting factors for precision and resolution, such as phase and frequency noise in RF reference carriers and drift mechanisms such as thermal drift and random walk. The effects of carrier frequency instability due to phase noise are categorized in different contributing bands, and the impact of these spectrum regions are considered both in terms of the absolute position and the relative speed. A mission scenario is finally proposed, and key metrics in terms of mass and power consumption for the required payload hardware are also assessed. For this purpose, an application case involving an RF communication network in UHF Band is described, in coexistence with a communications network used for the single agents to communicate within the both the exploring agents as well as the community and with the mission support agents. The proposed approach implements a substantial improvement in planetary navigation since it provides self-localization capabilities for robotic agents characterized by very low mass, volume and power budgets, thus enabling precise navigation capabilities to agents of reduced dimensions. Furthermore, a common and shared localization radiofrequency infrastructure enables new interaction mechanisms such as spatial arrangement of agents over the area of interest for distributed sensing.

Keywords: cooperative robotics, localization, robot navigation, surface exploration

Procedia PDF Downloads 294

Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

Abstract:

The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

Procedia PDF Downloads 80

Authors: P. Senthil Kumari

Abstract:

Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

Procedia PDF Downloads 508

Authors: Leila Keshavarz Afshar, Hedieh Sajedi

Abstract:

Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

Procedia PDF Downloads 148

Authors: A. Sri Janani, K. Immanuel Arokia James

Abstract:

Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.

Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique

Procedia PDF Downloads 359

Authors: Lucero Luciano, Cesar Celis, Jose Ramos

Abstract:

Polygeneration improves energy efficiency and reduce both energy consumption and pollutant emissions compared to conventional generation technologies. A polygeneration system is a variation of a cogeneration one, in which more than two outputs, i.e., heat, power, cooling, water, energy or fuels, are accounted for. In particular, polygeneration systems integrating solar energy and water desalination represent promising technologies for energy production and water supply. They are therefore interesting options for coastal regions with a high solar potential, such as those located in southern Peru and northern Chile. Notice that most of the Peruvian and Chilean mining industry operations intensive in electricity and water consumption are located in these particular regions. Accordingly, this work focus on the design and integration of a polygeneration system producing industrial heating, cooling, electrical power and water for an industrial plant. The design procedure followed in this work involves integer linear programming modeling (MILP), operational planning and dynamic operating conditions. The technical and economic feasibility of integrating renewable energy technologies (photovoltaic and solar thermal, PV+CPS), thermal energy store, power and thermal exchange, absorption chillers, cogeneration heat engines and desalination technologies is particularly assessed. The polygeneration system integration carried out seek to minimize the system total annual cost subject to CO2 emissions restrictions. Particular economic aspects accounted for include investment, maintenance and operating costs.

Keywords: desalination, design and integration, polygeneration systems, renewable energy

Procedia PDF Downloads 125

Authors: Abbas Hadj Abbas, Hacini Massaoud, Aiad Lahcen

Abstract:

In Hassi-Messoud’s oil industry, the systems which are water based (WBM) are generally used for drilling in the first phase. For the rest of the well, the oil mud systems are employed (OBM). In the field of oil exploration, panoply of chemical products is employed in the drilling fluids formulation. These components of different natures and whose toxicity and biodegradability are of ill-defined parameters are; however, thrown into nature. In addition to the hydrocarbon (HC, such as diesel) which is a major constituent of oil based mud, we also can notice spills as well as a variety of other products and additives on the drilling sites. These wastes are usually stored in places called (crud wastes). These may cause major problems to the ecosystem. To treat these wastes, we have considered two methods which are: solidification/ stabilization (chemical) and thermal. So that we can evaluate the techniques of treatment, a series of analyses are performed on dozens of specimens of wastes before treatment. After that, and on the basis of our analyses of wastes, we opted for diagnostic treatments of pollution before and after solidification and stabilization. Finally, we have done some analyses before and after the thermal treatment to check the efficiency of the methods followed in the study.

Keywords: wastes treatment, the oil pollution, the norms, wastes drilling

Procedia PDF Downloads 294

Authors: T. Bettaieb, S. Soufi, S. Arbaoui

Abstract:

Stevia rebaudiana Bert. is a natural sweet plant. The leaves contain diterpene glycosides stevioside, rebaudiosides A-F, steviolbioside and dulcoside, which are responsible for its sweet taste and have commercial value all over the world as sugar substitute in foods and medicines. Stevia rebaudiana Bert. is sensitive temperature lower than 9°C. The possibility of its outdoor culture in Tunisian conditions demand genotypes tolerant to low temperatures. In order to evaluate the low temperature tolerance of eight genotypes of Stevia rebaudiana, the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalases (CAT) were measured. Before carrying out the analyses, three genotypes of Stevia were exposed for 1 month at a temperature regime of 18°C during the day and 7°C at night similar to winter conditions in Tunisia. In response to the stress generated by low temperature, antioxidant enzymes activity revealed on native gel and quantified by spectrophotometry showed variable levels according to their degree of tolerance to low temperatures.

Keywords: chilling tolerance, enzymatic activity, stevia rebaudiana bert, low thermal stress

Procedia PDF Downloads 442

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

Procedia PDF Downloads 262

Authors: Mohsen Maraoui

Abstract:

In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

Procedia PDF Downloads 141

Authors: Elisabete Alberdi, Irantzu Álvarez, Laura Girón

Abstract:

The objective of this work is to propose a cycle path or network of paths to the UPV/EHU Campus in Leioa. The proposal will be presented from the point of view of sustainability. In order to achieve this, the roads that are already built will be used, and the road or network will be proposed to be built with the least amount of money possible. To select the most suitable route for the bike lane, various sources of information have been used. Through this data, we analyse the transport infrastructure and the mobility around the UPV/EHU Campus in Leioa. This work aims to satisfy the mobility needs of users on the University Campus to contribute to the sustainability of the campus.

Keywords: cycle lane, sustainability, accessibility, transport, agenda 2030

Procedia PDF Downloads 228

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

Abstract:

Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

Procedia PDF Downloads 235

Authors: Aynur Aker, Hasan Kaya

Abstract:

In recent years, the use of the aluminum based alloys in the industry and technology are increasing. Alloying elements in aluminum have further been improving the strength and stiffness properties that provide superior compared to other metals. In this study, investigation of physical properties (microstructure, microhardness, tensile strength, electrical conductivity and thermal properties) in the Al-12.6wt.%Si-%2wt.Ni ternary alloy were investigated. Al-Si-Ni alloy was prepared in a graphite crucible under vacuum atmosphere. The samples were directionally solidified upwards with different growth rate (V) at constant temperature gradient G (7.73 K/mm). The microstructures (flake spacings, λ), microhardness (HV), ultimate tensile strength, electrical resistivity and thermal properties enthalpy of fusion and specific heat and melting temperature) of the samples were measured. Influence of the growth rate and flake spacings on microhardness, ultimate tensile strength and electrical resistivity were investigated and relationships between them were experimentally obtained by using regression analysis. According to results, λ values decrease with increasing V, but microhardness, ultimate tensile strength, electrical resistivity values increase with increasing V. Variations of electrical resistivity for cast samples with the temperature in the range of 300-1200 K were also measured by using a standard dc four-point probe technique. The enthalpy of fusion and specific heat for the same alloy was also determined by means of differential scanning calorimeter (DSC) from heating trace during the transformation from liquid to solid. The results obtained in this work were compared with the previous similar experimental results obtained for binary and ternary alloys.

Keywords: electrical resistivity, enthalpy, microhardness, solidification, tensile stress

Procedia PDF Downloads 376

Authors: Talal Al-Bazali

Abstract:

Air drilling has recently received increasing acceptance by the oil and gas industry due to its unique advantages. The main advantages of air drilling include the higher rate of penetration, less formation damage, lower risk of loss of circulation. However, these advantages cannot be fully realized if thermal effects in air drilling are not well understood and minimized. Due to its high frictional coefficient, low heat conductivity, and high compressibility, air can impact the temperature distribution of bit and thus affect its bit performances. Based on energy and mass balances, a transient thermal model that predicts bit temperature is presented along with numerical solutions in this paper. In addition, several important parameters that influence bit temperature distribution are analyzed. Simulation results show that the bit temperature increases with increasing weight on bit and rotary speed but decreases as the standpipe pressure and flow rate increase. These results can be used to optimize drilling operations and flow parameters for an improved bit performance as shown in this paper.

Keywords: air drilling, rate of penetration, temperature, rotary speed

Procedia PDF Downloads 285

Authors: Hamed Djalal

Abstract:

The thermal analysis of the mechanical draft wet cooling tower is performed in this study by the heat and mass transfer modelization in the packing zone. After combining the heat and mass transfer laws, the mass and energy balances and by involving the Merkel assumptions; firstly, an ordinary differential equations system is derived and solved numerically by the Runge-Kutta method to determine the water and air temperatures, the humidity, and also other properties variation along the packing zone. Secondly, by making some linear assumptions for the air saturation curve, an analytical solution is formed, which is developed for the air washer calculation, but in this study, it is applied for the cooling tower to express also the previous parameters mathematically as a function of the packing height. Finally, a good agreement with experimental data is achieved by both solutions, but the numerical one seems to be the more accurate for modeling the heat and mass transfer process in the wet cooling tower.

Keywords: evaporative cooling, cooling tower, air washer, humidification, moist air, heat, and mass transfer

Procedia PDF Downloads 101

Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

Abstract:

A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

Procedia PDF Downloads 198

Authors: Catherine Joke Adeseko

Abstract:

Enzymatic browning is an economically important disorder that degrades organoleptic properties and prevent the consumer from purchasing fresh fruit and vegetables. Prevention and control of enzymatic browning in fruit and its product is imperative. Therefore, this study sought to investigate the catalytic effect of polyphenol oxidase (PPO) in the adverse browning of African bush mango (Irvingia gabonensis) fruit peel and pulp. PPO was isolated and purified, and its physicochemical properties, such as the effect of pH with SDS, temperature, and thermodynamic studies, which invariably led to thermal inactivation of purified PPO at 80 °C, were evaluated. The pH and temperature optima of PPO were found at 7.0 and 50, respectively. There was a gradual increase in the activity of PPO as the pH increases. However, the enzyme exhibited a higher activity at neutral pH 7.0, while enzymatic inhibition was observed at acidic region, pH 2.0. The presence of SDS at pH 5.0 downward was found to inhibit the activity of PPO from the peel and pulp of I. gabonensis. The average value of enthalpy (ΔH), entropy (ΔS), and Gibbs free energy (ΔG) obtained at 20 min of incubation and temperature 30 – 80 °C were respectively 39.93 kJ.mol-1, 431.57 J.mol-1 .K-1 and -107.99 kJ.mol-1 for peel PPO, and 37.92 kJ.mol-1, -442.51J.mol-1.K-1, and -107.22 kJ.mol-1 for pulp PPO. Thermal inactivation of PPO from I. gabonensis exhibited a reduction in catalytic activity as the temperature and duration of heat inactivation increases using catechol, reflected by an increment in k value. The half-life of PPO (t1/2) decreases as the incubation temperature increases due to the instability of the enzyme at high temperatures and was higher in pulp than peel. Both D and Z values decrease with increase in temperature. The information from this study suggests processing parameters for controlling PPO in the potential industrial application of I. gabonensis fruit in order to prolong the shelf-life of this fruit for maximum utilization.

Keywords: enzymatic, browning, characterization, activity

Procedia PDF Downloads 90

Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

Abstract:

Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO₂ emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization

Procedia PDF Downloads 161

Authors: R. M. Kalayappan, N. Kathiravan

Abstract:

In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

Procedia PDF Downloads 398

Authors: Samar Aoujia, Théo Guérineaub, Rayan Zaitera, Evelyne Fargina, Younès Messaddeqb, Thierry Cardinala

Abstract:

Two barium gallo-germanate glass series were elaborated to investigate the effect of the yttrium introduction on the glass physicochemical properties and crystallization behavior. One to twenty mol% of YO3/2 were either added into the glass matrix or substituted for gallium oxide. The glass structure was studied by Raman spectroscopy, and the thermal, optical, thermo-mechanical and physical properties are examined. The introduction of yttrium ions in both glass series increases the glass transition temperature, crystallization temperature, softening temperature, coefficient of linear thermal expansion and density. Through differential scanning calorimetry and X-ray diffraction analyses, it was found that competition occurs between the gallo-germanate zeolite-type phase and the yttrium-containing phase. From 13 mol% of YO3/2, the yttrium introduction impedes the formation of surface crystallization in these glasses.

Keywords: photonic, heavy-metal oxide, glass, crystallization

Procedia PDF Downloads 145

Authors: Usman Ahmed Khan

Abstract:

Urbanization directly affects the existing infrastructure, landscape modification, environmental contamination, and traffic pollution, especially if there is a lack of urban planning. Recently, the rapid urban sprawl has resulted in less developed green areas and has devastating environmental consequences. This study was aimed to study the past urban expansion rates and measure LST from satellite data. The land use land cover (LULC) maps of years 1996, 2010, 2013, and 2017 were generated using landsat satellite images. Four main classes, i.e., water, urban, bare land, and vegetation, were identified using unsupervised classification with iterative self-organizing data analysis (isodata) technique. The LST from satellite thermal data can be derived from different procedures: atmospheric, radiometric calibrations and surface emissivity corrections, classification of spatial changeability in land-cover. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, From 1996-2017, urban areas increased to about a considerable increase of about 48%. Few areas of the city also shown in a reduction in LST from the year 1996-2017 that actually began their transitional phase from rural to urban LULC. The mean temperature of the city increased averagely about 1ºC each year in the month of October. The green and vegetative areas witnessed a decrease in the area while a higher number of pixels increased in urban class.

Keywords: LST, LULC, isodata, urbanization

Procedia PDF Downloads 100

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

Abstract:

The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 144

Authors: Sarayu Vanga, Jorge Galeano-Cabral, Kaya Wei

Abstract:

Cerebral hypoxia refers to a condition in which there is a decrease in oxygen supply to the brain. Patients suffering from this condition experience a decrease in their body temperature. While there isn't any cure to treat cerebral hypoxia as of date, certain procedures are utilized to help aid in the treatment of the condition. Regulating the body temperature is an example of one of those procedures. Hypoxia is well known to reduce the body temperature of mammals, although the neural origins of this response remain uncertain. In order to speed recovery from this condition, it is necessary to maintain a stable body temperature. In this study, we present an approach to regulating body temperature for patients who suffer from cerebral hypoxia or other similar conditions. After a thorough literature study, we propose the use of thermoelectric blankets, which are temperature-controlled thermal blankets based on thermoelectric devices. These blankets are capable of heating up and cooling down the patient to stabilize body temperature. This feature is possible through the reversible effect that thermoelectric devices offer while behaving as a thermal sensor, and it is an effective way to stabilize temperature. Thermoelectricity is the direct conversion of thermal to electrical energy and vice versa. This effect is now known as the Seebeck effect, and it is characterized by the Seebeck coefficient. In such a configuration, the device has cooling and heating sides with temperatures that can be interchanged by simply switching the direction of the current input in the system. This design integrates various aspects, including a humidifier, ventilation machine, IV-administered medication, air conditioning, circulation device, and a body temperature regulation system. The proposed design includes thermocouples that will trigger the blanket to increase or decrease a set temperature through a medical temperature sensor. Additionally, the proposed design allows an efficient way to control fluctuations in body temperature while being cost-friendly, with an expected cost of 150 dollars. We are currently working on developing a prototype of the design to collect thermal and electrical data under different conditions and also intend to perform an optimization analysis to improve the design even further. While this proposal was developed for treating cerebral hypoxia, it can also aid in the treatment of other related conditions, as fluctuations in body temperature appear to be a common symptom that patients have for many illnesses.

Keywords: body temperature regulation, cerebral hypoxia, thermoelectric, blanket design

Procedia PDF Downloads 160

Authors: Asmau Mukhtar Ahmed, Olga Duran

Abstract:

Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

Procedia PDF Downloads 114

Authors: Maha BenHamad, Ali Snoussi, Ammar Ben Brahim

Abstract:

A steady-state analysis of triple-effect thermal vapor compressor desalination unit was performed. A mathematical model based on mass, salinity and energy balances is developed. The purpose of this paper is to develop a connection between process simulator and process optimizer in order to study the influence of several operating variables on the performance and the produced water cost of the unit. A MATLAB program is used to solve the model equations, and Aspen HYSYS is used to model the plant. The model validity is examined against a commercial plant and showed a good agreement between industrial data and simulations results. Results show that the pressures of the last effect and the compressed vapor have an important influence on the produced cost, and the increase of the difference temperature in the condenser decreases the specific heat area about 22%.

Keywords: steady-state, triple effect, thermal vapor compressor, Matlab, Aspen Hysys

Procedia PDF Downloads 172

Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

Abstract:

In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

Procedia PDF Downloads 120

Authors: Pratibha Biswal, Suyash Morchhale, Anshuman Singh Yadav, Shubham Sanjay Chobe

Abstract:

Energy demands are increasing whereas energy sources, especially non-renewable sources are limited. Due to the intermittent nature of renewable energy sources, it has become the need of the hour to find new ways to store energy. Out of various energy storage methods, latent heat thermal storage devices are becoming popular due to their high energy density per unit mass and volume at nearly constant temperature. This work presents a computational fluid dynamics (CFD) model using ANSYS FLUENT 19.0 for energy storage characteristics of a phase change material (PCM) filled in a vertical triplex tube thermal energy storage system. A vertical triplex tube heat exchanger, just like its name consists of three concentric tubes (pipe sections) for parting the device into three fluid domains. The PCM is filled in the middle domain with heat transfer fluids flowing in the outer and innermost domains. To enhance the heat transfer inside the PCM, eight fins have been incorporated between the internal and external tubes. These fins run radially outwards from the outer-wall of innermost tube to the inner-wall of the middle tube dividing the middle domain (between innermost and middle tube) into eight sections. These eight sections are then filled with a PCM. The validation is carried with earlier work and a grid independence test is also presented. Further studies on freezing and melting process were carried out. The results are presented in terms of pictorial representation of isotherms and liquid fraction

Keywords: heat exchanger, thermal energy storage, phase change material, CFD, latent heat

Procedia PDF Downloads 153

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

Abstract:

Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 380

Authors: Lorenzo Petrucci

Abstract:

This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

Procedia PDF Downloads 176