Search results for: thermal network

Authors: Peter J. Glinos

Abstract:

The Alternative Education Resource Organization (AERO), one of the largest international hubs for alternative educators led by Jerry Mintz, has had a major impact on the global alternative education movement. The organization’s publications, like the AERO-Gramme Newsletter and its successor, the Education Revolution Magazine, allowed members across the globe to discuss issues, share support, and submit writings on policies and reforms. Stored on AERO's online digital archive, this work uses these publications from 1989 to 2011 to investigate the network's entanglements with America, Canada, Russia, Ukraine, Israel, Palestine, Japan, India, and Guatemala. Inspired by Reinhart Koselleck, this historical analysis will trace AERO’s entanglements within the United States, Japan, and Russia, contextualizing each of these multiple temporalities within the history of each nation’s education system, the developments within AERO, and the global geo-political climate at the time of AERO’s expansion. To help remedy the lack of attention paid by global historians to the role state organizations play supporting global networks, as noted in What is Global History? by Sebastian Conrad, this work will focus on the relationship between AERO and state actors.

Keywords: global history, history of education, neoliberalism, transnational history, alternative education

Procedia PDF Downloads 28

Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

Abstract:

With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

Procedia PDF Downloads 74

Authors: Richard Maguire

Abstract:

This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

Procedia PDF Downloads 124

Authors: Marvin Ricardo Awarab

Abstract:

There has never been a greater need for telecom services. The Internet of Things (IoT), 5G networking, and edge computing are the driving forces behind this increased demand. The fierce demand offers communications service providers significant income opportunities. The telecom sector is centered on automation, and realizing a digital operation that functions as a real-time business will be crucial for the industry as a whole. Automation in telecom refers to the application of technology to create a more effective, quick, and scalable alternative to the conventional method of operating the telecom industry. With the promotion of 5G and the Internet of Things (IoT), telecom companies will continue to invest extensively in telecom automation technology. Automation offers benefits in the telecom industry; developing countries such as Namibia may not fully tap into such benefits because of the lack of funds and infrastructural resources to invest in automation. This paper fully investigates the benefits of automation in the telecom industry. Furthermore, the paper identifies hiccups that developing countries such as Namibia face in their quest to fully introduce automation in the telecom industry. Additionally, the paper proposes possible avenues that Namibia, as a developing country, adopt investing in automation infrastructural resources with the aim of reaping the full benefits of automation in the telecom industry.

Keywords: automation, development, internet, internet of things, network, telecom, telecommunications policy, 5G

Procedia PDF Downloads 63

Authors: Jiaqi Yan, Yani Shi

Abstract:

The blockchain technology is regarded as the most promising technology that has the potential to trigger a technological revolution. However, besides the bitcoin industry, we have not yet seen a large-scale application of blockchain in those domains that are supposed to be impacted, such as supply chain, financial network, and intelligent manufacturing. The reasons not only lie in the difficulties of blockchain implementation, but are also root in the challenges of blockchain-oriented information systems design. As the blockchain members are self-interest actors that belong to organizations with different existing information systems. As they expect different information inputs and outputs of the blockchain application, a common language protocol is needed to facilitate communications between blockchain members. Second, considering the decentralization of blockchain organization, there is not any central authority to organize and coordinate the business processes. Thus, the information systems built on blockchain should support more adaptive business process. This paper aims to address these difficulties by providing a modeling approach for blockchain-oriented information systems design. We will investigate the information structure of distributed-ledger data with conceptual modeling techniques and ontology theories, and build an effective ontology mapping method for the inter-organization information flow and blockchain information records. Further, we will study the distributed-ledger-ontology based business process modeling to support adaptive enterprise on blockchain.

Keywords: blockchain, ontology, information systems modeling, business process

Procedia PDF Downloads 449

Authors: Mardiana Ahamad Zabidi, Akmalluddin Md. Yunus

Abstract:

Soursop (Anona muricata) is one of the underutilized tropical fruits containing nutrients, particularly dietary fibre and antioxidant properties that are beneficial to human health. This objective of this study is to investigate the feasibility of matured soursop pulp flour (SPF) to be substituted with high-protein wheat flour in bread. Bread formulation was substituted with different levels of SPF (0%, 5%, 10% and 15%). The effect on physicochemical properties and sensory attributes were evaluated. Higher substitution level of SPF resulted in significantly higher (p<0.05) fibre, protein and ash content, while fat and carbohydrate content reduced significantly (p<0.05). FESEM showed that the bread crumb surface of control and 5% SPF appeared to distribute evenly and coalesced by thin gluten film. However, higher SPF substitution level in bread formulation exhibited a deleterious effect by formation of discontinuous gluten network. For texture profile analysis, 5% SPF bread resulted in the lowest value of hardness. The score of sensory evaluation showed that 5% SPF bread received good acceptability and is comparable with control bread.

Keywords: soursop pulp flour, bread, physicochemical properties, sensory attributes, scanning electron microscopy (SEM)

Procedia PDF Downloads 322

Authors: Adriana Stefan, Cristina-Elisabeta Pelin, George Pelin, Maria Daniela Stelescu, Elena Manaila

Abstract:

Elastomeric composites have been known for a long time, but, to our knowledge, space and the aeronautic community has been directing a special attention to them only in the last decade. The required properties of advanced elastomeric materials used in space applications (such as O-rings) are sealing, abrasion, low-temperature flexibility, the long-term compression set properties, impact resistance and low-temperature thermal stability in different environments, such as ionized radiations. Basically, the elastomeric nanocomposites are composed of a rubber matrix and a wide and varied range of nanofillers, added with the aim of improving the physico-mechanical and elasticity modulus properties of the materials as well as their stability in different environments. The paper presents a partial synthesis of the research regarding the use of silicon carbide in nanometric form and/or organophylized montmorillonite as fillers in butyl rubber matrix. The need of composite materials arose from the fact that stand-alone polymers are ineffective in providing all the superior properties required by different applications. These drawbacks can be diminished or even eliminated by incorporating a new range of additives into the organic matrix, fillers that have important roles in modifying properties of various polymers. A composite material can provide superior and unique mechanical and physical properties because it combines the most desirable properties of its constituents while suppressing their least desirable properties. The commercial importance of polymers and the continuous increase of their use results in the continuous demand for improvement in their properties to meet the necessary conditions. To study the performance of the elastomeric nanocomposites were mechanically tested, it will be tested the qualities of tensile at low temperatures and RT and the behavior at the compression at cryogenic to room temperatures and under different environments. The morphology of specimens will be investigated by optical and scanning electronic microscopy.

Keywords: elastomeric nanocomposites, O-rings, space applications, mechanical properties

Procedia PDF Downloads 288

Authors: Stuti Modi, Aditi Kambli

Abstract:

This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

Procedia PDF Downloads 186

Authors: Abdul Salam Turkmani

Abstract:

Clay of the northern Palmyra region is one of the most important raw materials used in the Syrian ceramics industry. This study is focused on the evaluation of various laboratory analyses such as chemical analysis (XRF), mineral X-ray diffraction analysis (XRD), differential thermal analysis (DTA), and semi-industrial tests carried out on samples collected on two representative locations of the upper Oligocene in AlMkamen valley (MK) and lower Miocene in AlZukara valley (ZR) of the northern part of Palmyra, Syria. Chemical results classify the (MK) and (ZR) clays as semi-plastic red clay slightly carbonate and (eliminate probable) illite-chlorite clays with a very fine particle size distribution. Content of SiO₂ between 46.28-57.66%, Al2O3 13.81-25.2%, Fe₂O₃ 3.47-11.58%, CaO 1.15-7.19%, Na₂O+K₂O varied between 3.34-3.71%. Based on clay chemical composition and iron and carbonate content, these deposits can be considered as red firing clays. Their mineralogical composition is mainly represented by illite, kaolinite and quartz, and accessories minerals such as calcite, feldspar, phillipsite, and goethite. The results of the DTA test confirm the presence of gypsum and quartz phases in (MK) clay. Ceramic testing shows good green and dry bending strength values, which varied between 9-14 kg/cm², at 1160°C to 1180°C. Water absorption moves from 14.6 % at 1120°C to 2.2% at 1180°C to 1.6% at 1200°C. Breaking load after firing changes from 400 to 590 kg/cm². At 1200°C (MK), clay reaches perfect vitrification. After firing, the color of the clay changes from orange-hazel to red-brown at 1180°C. Technological results confirmed the suitability of the studied clays to produce floor and wall ceramic tiles. Using one of the two types of clay into the ceramic body or both types together gave satisfactory industrial results.

Keywords: ceramic, clay, industry , Palmyra

Procedia PDF Downloads 196

Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

Abstract:

Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

Procedia PDF Downloads 97

Authors: Jin Hwa Yang, Hwang Bae, Sung Uk Ryu, Byong Guk Jeon, Sung Jae Yi, Hyun Sik Park

Abstract:

Experimental studies using a large-scale thermal-hydraulic integral test facility, System–integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL), have been carried out to validate the performance of the prototype, SMART. After Fukushima accident, the passive safety systems have been dealt as important designs for retaining of nuclear safety. One of the concerned scenarios for evaluating the passive safety system is a Complete Loss of Coolant Flow (CLOF). The flowrate of coolant in the primary system is maintained by Reactor Coolant Pump (RCP). When the supply of electric power of RCP is shut off, the flowrate of coolant decreases sharply, and the temperature of the coolant increases rapidly. Therefore, the reactor trip signal is activated to prevent the over-heating of the core. In this situation, Passive Residual Heat Removal System (PRHRS) plays a significant role to assure the soundness of the SMART. The PRHRS using a two-phase natural circulation is a passive safety system in the SMART to eliminate the heat of steam generator in the secondary system with heat exchanger submarined in the Emergency Cooling Tank (ECT). As the RCPs continue to coast down, inherent natural circulation in the primary system transfers heat to the secondary system. The transferred heat is removed by PRHRS in the secondary system. In this paper, the progress of the CLOF accident is described with experimental data of transient condition performed by SMART-ITL. Finally, the capability of passive safety system and inherent natural circulation will be evaluated.

Keywords: CLOF, natural circulation, PRHRS, SMART-ITL

Procedia PDF Downloads 438

Authors: Changyeop Lee, Sewon Kim, Jongho Lee

Abstract:

Reburning technology has been developed to adopt various commercial combustion systems. Fuel lean reburning is an advanced reburning method to reduce NOx economically without using burnout air, however it is not easy to get high NOx reduction efficiency. In the fuel lean reburning system, the localized fuel rich eddies are used to establish partial fuel rich regions so that the NOx can react with hydrocarbon radical restrictively. In this paper, a new advanced reburning method which supplies reburn fuel with oscillatory motion is introduced to increase NOx reduction rate effectively. To clarify whether forced oscillating injection of reburn fuel can effectively reduce NOx emission, experimental tests were conducted in vertical combustion furnace. Experiments were performed in flames stabilized by a gas burner, which was mounted at the bottom of the furnace. The natural gas is used as both main and reburn fuel and total thermal input is about 40kW. The forced oscillating injection of reburn fuel is realized by electronic solenoid valve, so that fuel rich region and fuel lean region is established alternately. In the fuel rich region, NOx is converted to N2 by reburning reaction, however unburned hydrocarbon and CO is oxidized in fuel lean zone and mixing zone at downstream where slightly fuel lean region is formed by mixing of two regions. This paper reports data on flue gas emissions and temperature distribution in the furnace for a wide range of experimental conditions. All experimental data has been measured at steady state. The NOx reduction rate increases up to 41% by forced oscillating reburn motion. The CO emissions were shown to be kept at very low level. And this paper makes clear that in order to decrease NOx concentration in the exhaust when oscillating reburn fuel injection system is adopted, the control of factors such as frequency and duty ratio is very important.

Keywords: NOx, CO, reburning, pollutant

Procedia PDF Downloads 288

Authors: Thomas Wimmer, Bernhard Weigand

Abstract:

The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

Procedia PDF Downloads 352

Authors: Rahul Agarwal, Ashutosh Singh

Abstract:

Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

Procedia PDF Downloads 234

Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

Abstract:

It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

Procedia PDF Downloads 101

Authors: J. H. Park, R. H. Hwang, K. B. Yi

Abstract:

Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

Procedia PDF Downloads 209

Authors: Arámbula-Villa Gerónimo, García-Lara Kenia Y., Figueroa-Cárdenas J. D., Pérez-Robles J. F., Jiménez-Sandoval S., Salazar-López R., Herrera-Corredor J. A.

Abstract:

The nixtamalization process (thermal-alkaline method) improves the nutritional part of the corn grain. In this process, the using of Ca(OH)₂ is basic, although the chemical mechanisms between this alkali and the carbohydrates (starch), proteins, lipids, and fiber have not been fully identified. In this study, the native corn starch was taken as a model, and it was subjected to cooking with different concentrations of lime (nixtamalization process) and specific studies of FTIR and XRD were carried out to identify the formation of chemical compounds, and the physical, physicochemical, rheological (paste) and structural properties of material obtained were determined. The FTIR spectra showed the formation of calcium-starch complexes. The treatments with Ca(OH)₂ showed a band shift towards 1675 cm⁻¹ and a band in 1436 cm⁻¹ (COO⁻), indicating the oxidation of starch. Three bands were identified (1575, 1550, and 1540 cm⁻¹) characteristics of carboxylic acid salts for three types of coordinated structures: monodentate, pseudo-bridged, and bidentate. The XRD spectra of starch treated with Ca(OH)₂ showed a peak corresponding to CaCO₃ (29.40°). The oxidation of starch was favored with low concentrations of Ca(OH)₂, producing carboxyl and carbonyl groups and increasing the residual CaCO₃. The increased concentration of Ca(OH)₂ showed the formation of calcium carboxylates, with a decrease in relative crystallinity and residual CaCO₃. Samples with low concentrations of Ca(OH)₂ slowed the onset of gelatinization and increased the swelling of the granules and the peak viscosity. The higher concentrations of Ca(OH)₂ difficulted the water absorption and decreased the viscosity rate and peak viscosity. These results can be used to improve the quality characteristics of the dough and tortillas and to get better acceptance by consumers.

Keywords: maize starch, nixtamalization, gelatinization, calcium carboxylates

Procedia PDF Downloads 96

Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

Abstract:

In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

Procedia PDF Downloads 129

Authors: Mahmoud Abdulhamid, Rifan Hardian, Prashant Bhatt, Shuvo Datta, Adrian Ramirez, Jorge Gascon, Mohamed Eddaoudi, Gyorgy Szekely

Abstract:

Polybenzimidazole (PBI) is a high-performance polymer that exhibits high thermal and chemical stability. However, it suffers from low porosity and low fractional free volume, which hinder its application as separation material. Herein, we demonstrate the molecular engineering of gas separation materials by manipulating a PBI backbone possessing kinked moieties. PBI was selected as it contains NH groups which increase the affinity towards CO₂, increase sorption capacity, and favors CO₂ over other gasses. We have designed and synthesized an intrinsically microporous polybenzimidazole (iPBI) featuring a spirobisindane structure. Introducing a kinked moiety in conjunction with crosslinking enhanced the polymer properties, markedly increasing the gas separation performance. In particular, the BET surface area of PBI increased 30-fold by replacing a flat benzene ring with a kinked structure. iPBI displayed a good CO₂ uptake of 1.4 mmol g⁻¹ at 1 bar and 3.6 mmol g⁻¹ at 10 bar. Gas sorption uptake and breakthrough experiments were conducted using mixtures of CO₂/CH₄ (50%/50%) and CO₂/N₂ (50%/50%), which revealed the high selectivity of CO₂ over both CH₄ and N₂. The obtained CO₂/N₂ selectivity is attractive for power plant flue gas application requiring CO₂ capturing materials. Energy and process simulations of biogas CO₂ removal demonstrated that up to 70% of the capture energy could be saved when iPBI was used rather than the current amine technology (methyl diethanolamine [MDEA]). Similarly, the combination of iPBI and MDEA in a hybrid system exhibited the highest CO₂ capture yield (99%), resulting in nearly 50% energy saving. The concept of enhancing the porosity of PBI using kinked moieties provides new scope for designing highly porous polybenzimidazoles for various separation processes.

Keywords: polybenzimidazole (PBI), intrinsically microporous polybenzimidazole (iPBI), gas separation, pnergy and process simulations

Procedia PDF Downloads 92

Authors: Liqiang Duan, Ma Jingkai, Lv Zhipeng, Haifan Cai

Abstract:

The integrated solar combined cycle (ISCC) system has a series of advantages such as increasing the system power generation, reducing the cost of solar power generation, less pollutant and CO₂ emission. In this paper, the parabolic trough collectors with direct steam generation (DSG) technology are considered to replace the heat load of heating surfaces in heat regenerator steam generation (HRSG) of a conventional natural gas combined cycle (NGCC) system containing a PG9351FA gas turbine and a triple pressure HRSG with reheat. The detailed model of the NGCC system is built in ASPEN PLUS software and the parabolic trough collectors with DSG technology is modeled in EBSILON software. ISCC-DSG systems with the replacement of single, two, three and four heating surfaces are studied in this paper. Results show that: (1) the ISCC-DSG systems with the replacement heat load of HPB, HPB+LPE, HPE2+HPB+HPS, HPE1+HPE2+ HPB+HPS are the best integration schemes when single, two, three and four stages of heating surfaces are partly replaced by the parabolic trough solar energy collectors with DSG technology. (2) Both the changes of feed water flow and the heat load of the heating surfaces in ISCC-DSG systems with the replacement of multi-stage heating surfaces are smaller than those in ISCC-DSG systems with the replacement of single heating surface. (3) ISCC-DSG systems with the replacement of HPB+LPE heating surfaces can increase the solar power output significantly. (4) The ISCC-DSG systems with the replacement of HPB heating surfaces has the highest solar-thermal-to-electricity efficiency (47.45%) and the solar radiation energy-to-electricity efficiency (30.37%), as well as the highest exergy efficiency of solar field (33.61%).

Keywords: HRSG, integration scheme, parabolic trough collectors with DSG technology, solar power generation

Procedia PDF Downloads 253

Authors: Shriya Shukla, Lachin Fernando

Abstract:

Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

Procedia PDF Downloads 126

Authors: Sufia Khowaja, Nishat Fatima

Abstract:

Social networking sites are significant for visually impaired to overcome the unique challenges they face and access the resources they need to succeed in their education and beyond which might be difficult to obtain through traditional means. It provides them an opportunity to build relationships, stay connected with their support network as well as to develop social skills which give them emotional support to fell less isolated. In this connection the study is conducted with the aim to determine the use of social networking sites, purpose of using and activities performed by visually impaired at Delhi University, Delhi, Jawaharlal Nehru University, Delhi and Jamia Milia Islamia, Delhi. The study followed survey technique in which structured interview is followed to collect data from 137 visually impaired students and analysed using ‘SPSS ver23’. The findings of the study revealed that mostly used social networking sites are whatsapp by 89.23% students of DU, 95.12% of JNU, 87.09% of JMI, followed by e-mail by 78.46% of DU, 78.04% of JNU, 64.51%; youtube by 73.84% DU, 90.24% JNU, 80.64% JMI. Purpose for using these sites is for academics mentioned by 96.92% DU, 100% JNU, 93.54% JMI. Activities performed on sites are sending and receiving messaging 96.92% DU, 92.68% JNU, 93.55% JMI, communicating with friends and family as well as getting academic information. Findings of the study will be helpful for libraries to disseminate their services and resources as well as latest updates to their visually impaired users with the help of most used tools.

Keywords: social networking sites, visually impaired, Delhi University, Jawaharlal Nehru University, Jamia Milia Islamia

Procedia PDF Downloads 90

Authors: Jay L. Fu

Abstract:

Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 143

Authors: Felix Boehnisch, Alexander Lutz

Abstract:

Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

Procedia PDF Downloads 182

Authors: Morteza Taherinezhad, Ahmad Reza Rabbani, Morteza Asemani, Rudy Swennen

Abstract:

Oil-oil correlation is one of the most important issues in geochemical studies that enables to classify oils genetically. Oil-oil correlation is generally estimated based on non-polar fractions of crude oil (e.g., saturate and aromatic compounds). Despite several advantages, the drawback of using these compounds is their susceptibility of being affected by secondary processes. The polar fraction of crude oil (e.g., asphaltenes) has similar characteristics to kerogen, and this structural similarity is preserved during migration, thermal maturation, biodegradation, and water washing. Therefore, these structural characteristics can be considered as a useful correlation parameter, and it can be concluded that asphaltenes from different reservoirs with the same genetic signatures have a similar origin. Hence in this contribution, an integrated study by using both non-polar and polar fractions of oil was performed to use the merits of both fractions. Therefore, five oil samples from oil fields in the Persian Gulf were studied. Structural characteristics of extracted asphaltenes were investigated by Fourier transform infrared (FTIR) spectroscopy. Graphs based on aliphatic and aromatic compounds (predominant compounds in asphaltenes structure) and sulphoxide and carbonyl functional groups (which are representatives of sulphur and oxygen abundance in asphaltenes) were used for comparison of asphaltenes structures in different samples. Non-polar fractions were analyzed by GC-MS. The study of asphaltenes showed the studied oil samples comprise two oil families with distinct genetic characteristics. The first oil family consists of Salman and Reshadat oil samples, and the second oil family consists of Resalat, Siri E, and Siri D oil samples. To validate our results, biomarker parameters were employed, and this approach completely confirmed previous results. Based on biomarker analyses, both oil families have a marine source rock, whereby marl and carbonate source rocks are the source rock for the first and the second oil family, respectively.

Keywords: biomarker, non-polar fraction, oil-oil correlation, petroleum geochemistry, polar fraction

Procedia PDF Downloads 135

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

Abstract:

Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

Procedia PDF Downloads 316

Authors: Rebecca J. Hafner, Daniel Read, David Elmes

Abstract:

The current research applies decision making theory in order to address the problem of increasing uptake of energy-efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. Specifically, in two studies we apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. As researchers in the Interdisciplinary centre for Storage, Transformation and Upgrading of Thermal Energy (i-STUTE) are currently developing energy efficient heating systems for homes and businesses, we focus on the context of home heating choice, and compare preference for a standard condensing boiler versus an energy efficient heat pump, according to experimental manipulations in the structure of prior information. In Study 1, we find that people prefer stronger alignable features when options are similar; an effect which is mediated by an increased tendency to infer missing information is the same. Yet, in contrast to previous research, we find no effects of alignability on option preference when options differ. The advanced methodological approach used here, which is the first study of its kind to randomly allocate features as either alignable or non-alignable, highlights potential design effects in previous work. Study 2 is designed to explore the interaction between alignability and construal level as an explanation for the shift in attentional focus when options differ. Theoretical and applied implications for promoting energy efficient technologies are discussed.

Keywords: energy-efficient technologies, decision-making, alignability effects, construal level theory, CO2 reduction

Procedia PDF Downloads 330

Authors: Soney C. George, Thomasukutty Jose, Sabu Thomas

Abstract:

Membrane based separation is the most important energy –efficient separation processes. There are wide ranges of membrane based separation process such as Micro-filtration, ultra filtration, reverse osmosis, electro-dialysis etc. Among these pervaporation is one of the most promising techniques. The promising technique is in the sense that it needs an ease of process design, low energy consumption, environmentally clean, economically cost effective and easily separate azeotropic composition without losing any components, unlike distillation in a short period of time. In the present work, we developed a new bentonite clay reinforced cross-linked PVA nano-composite membranes by solution casting method. The membranes were used for the pervaporation separation of azeotropic composition of isopropanol and water mixtures. The azeotropic composition of water and isopropanol is difficult to separate and we can’t get a better separation by normal separation processes. But the better separation was achieved here using cross-linked PVA/Clay nano-composite membranes. The 2wt% bentonite clay reinforced 5vol% GA cross-linked nano-composite membranes showed better separation efficiency. The selectivity of the cross-linked membranes increases 65% upon filler loading. The water permeance is showed tremendous enhancement upon filler loading. The permeance value changes from 4100 to 8200, due to the incorporation hydrophilic bentonite clay to the cross-linked PVA membranes. The clay reinforced membranes shows better thermal stability upon filler loading was confirmed from TGA and DSC analysis. The dispersion of nanoclay in the polymeric matrix was clearly evident from the TEM analysis. The better dispersed membranes showed better separation performance. Thus the developed cross-linked PVA/Clay membranes can be effectively used for the separation of azeotropic composition of water and isopropanol.

Keywords: poly(vinyl alcohol), membrane, gluraldehyde, permeance

Procedia PDF Downloads 306

Authors: Bandar Alahmadi, Lethia Jackson

Abstract:

Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

Procedia PDF Downloads 339

Authors: Bernice Lottering, Yi-Wen Lin

Abstract:

Chronic pain and depression have an estimated 80% rate of comorbidity with unsatisfactory treatment interventions signifying the importance of developing effective therapeutic interventions for a serious chronic condition affecting a large majority of the global population. Chronic pain is defined as persistent pain presenting for over 3 months. This disease state increases the risk of developing depression in comparison to healthy individuals. In the current study, complete Freund’s adjuvant (CFA) was used to induce cell-mediated chronic inflammatory pain in a murine model. Significant mechanical and thermal hyperalgesia was induced, alongside observable depression-like behaviors. These conditions were attenuated through the use of electroacupuncture (EA). Similarly, these effects were also investigated with respect to the transient receptor potential vanilloid 1 (TRPV1), by analyzing the effects of TRPV1 gene deletion on the comorbidity of chronic pain and depression. The expression of the TRPV1 inflammatory response, and related downstream molecules, including protein kinases (PKs), mitogen-activated protein kinase (MAPKs), and transcriptional factors, were significantly reduced in the thalamus, prefrontal cortex (PFC), hippocampus, and periaqueductal gray (PAG) of CFA-treated mice. In addition, phosphorylated N-methyl-D-aspartate (NMDA) receptor 1 was also found to be reduced in the aforementioned areas, suggesting potential application and validity in a clinical setting. Our study determined the prospective therapeutic effects of EA in the treatment of chronic inflammatory pain and depression comorbidity and provides a novel and detailed mechanism underlying EA-mediated analgesia. These findings may be relevant in the utilization of clinical intervention approaches related to chronic pain and depression comorbidity.

Keywords: chronic pain, depression, NMDA, prefrontal cortex, TRPV1

Procedia PDF Downloads 133