Search results for: potential intelligence
11135 The Use of Microalgae Cultivation for Improving the Effluent Behavior of Anaerobic Digestion of Food Wastes at Psychrophilic Range
Authors: Pedro M. Velasco, Cecilia C. Alday, Oscar C. Avello, Ximena T. Faundez, Luis M. Velasco
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Anaerobic digestion (AD) plants of food waste (FW) produced by agro-industry, have been widely developed from last decade to nowadays, because of the advantages over aerobic active sludge systems. Despite several bioreactor configurations and operation modes have been successfully improved and implemented at industrial scale in a wide range of applications, effluent behavior, after AD, does not commonly meet requirements for direct disposal into the environment without further treatments. In addition, literature has rarely shown AD of food waste at psychrophilic range. This temperature range may be of interest for making AD plant operation easier and increasing the stability of digestion. In spite of literature shows several methods for post-treatment, such as the use of microalgae, these have not been cultivated on effluents from AD at psychrophilic range. Hence, with the aim of showing the potential use of AD of FW at the psychrophilic range (25ºC) and the viability of microalgae post-treatment, single batch reactors have been used for methane potential tests at laboratory scale. Afterwards, digestates, derived from this AD of FW sludge, were diluted with fresh water at different ratios (1:0, 1:1; 1:4) and used as culture media for photoautotrophic microalgae. Several parameters, such as pH, biogas production, and chemical oxygen demand, were measured periodically over several months. Results show that methane potential is 150 ml g-1 per volatile solid with up to 57.7 % of methane content. Moreover, microalgae has been successfully cultivated on all tested effluents and in case of 1:1 and 1:4 rates, the resulting effluents meet the quality levels required for irrigation water.Keywords: anaerobic digestion, biogas, food waste, microalgae, psychrophilic range
Procedia PDF Downloads 30411134 Interactions on Silent Mode: Parental Smartphone Distractions on Infant Mental Health
Authors: Terry Gomez
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This interpretive phenomenological qualitative study explored potential risks related to infant mental health with parental smartphone use while caring for infants. Data were collected through nine online interviews of first-time parents with infants under one-year-old. All parents reported using their smartphone during child-bonding activities such as playtime, feeding, and sleep-time. Results indicated that smartphone distractions appear to influence the synchrony of parent-child interactions. Infants displayed physical, verbal, or emotional reactions to parents’ smartphone distractions, indicating that smartphone use influences infants’ behaviors. Parents shared information on how smartphones helped them with their transition into parenthood. The findings of this study provide insights helpful to inform infant mental health professionals and parents about potential developmental consequences associated with parental technoference and absent presence.Keywords: absent presence, infant mental health, parental distractions, smartphones, technoference
Procedia PDF Downloads 12911133 Machine Learning Based Digitalization of Validated Traditional Cognitive Tests and Their Integration to Multi-User Digital Support System for Alzheimer’s Patients
Authors: Ramazan Bakir, Gizem Kayar
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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification
Procedia PDF Downloads 13711132 First Principles Study of Structural and Elastic Properties of BaWO4 Scheelite Phase Structure under Pressure
Authors: Abdennour Benmakhlouf, Abdelouahab Bentabet
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In this paper, we investigated the athermal pressure behavior of the structural and elastic properties of scheelite BaWO4 phase up to 7 GPa using the ab initio pseudo-potential method. The calculated lattice parameters pressure relation have been compared with the experimental values and found to be in good agreement with these results. Moreover, we present for the first time the investigation of the elastic properties of this compound using the density functional perturbation theory (DFPT). It is shown that this phase is mechanically stable up to 7 GPa after analyzing the calculated elastic constants. Other relevant quantities such as bulk modulus, pressure derivative of bulk modulus, shear modulus; Young’s modulus, Poisson’s ratio, anisotropy factors, Debye temperature and sound velocity have been calculated. The obtained results, which are reported for the first time to the best of the author’s knowledge, can facilitate assessment of possible applications of the title material.Keywords: pseudo-potential method, pressure, structural and elastic properties, scheelite BaWO4 phase
Procedia PDF Downloads 43911131 Predicting Oil Spills in Real-Time: A Machine Learning and AIS Data-Driven Approach
Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas
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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)
Procedia PDF Downloads 7311130 Plans for Villages in the Margin of the Lagoon with an Accentuation on Tourism Advancement, Case Study: Village Rogbeh, Shadegan, Iran
Authors: Seyed Mohammad Mousavi Shalheh, Elham Rostami, Seyed Majid Mousavi, Somayeh Shirin Jani
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The aim of this research was to evaluate the potential of Rogbeh village located in Khanafereh, Shadegan city functions in Khuzestan also is the feasibility to build infrastructure and appropriate spaces to attract tourists as well as creating jobs and transforming the village institute of ecotourism in the region. It seems that the village has the potential for developing rural tourism with careful planning, and with regard to job creation and economic recovery programs, social-cultural and environmental-ecological accompanied will be welcomed by the people. Therefore, we can provide a strategy for developing tourism and achieving sustainable advancement of rural tourism. Based on researches carried out and according to regional climate differences and the position of the Rogbeh Village toward the lagoon, this research can be used by other researchers to develop and manage tourism.Keywords: Shadegan Lagoon, Iranian villages, tourism industry, local architecture, Rogbeh village, landscape design, ecology
Procedia PDF Downloads 17311129 Superiority of Bone Marrow Derived-Osteoblastic Cells (ALLOB®) over Bone Marrow Derived-Mesenchymal Stem Cells
Authors: Sandra Pietri, Helene Dubout, Sabrina Ena, Candice Hoste, Enrico Bastianelli
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Bone Therapeutics is a bone cell therapy company addressing high unmet medical needs in the field of bone fracture repair, more specifically in non-union and delayed-union fractures where the bone repair process is impaired. The company has developed a unique allogeneic osteoblastic cell product (ALLOB®) derived from bone marrow which is currently tested in humans in the indication of delayed-union fractures. The purpose of our study was to directly compare ALLOB® vs. non-differentiated mesenchymal stem cells (MSC) for their in vitro osteogenic characteristics and their in vivo osteogenic potential in order to determine which cellular type would be the most adapted for bone fracture repair. Methods: Healthy volunteers’ bone marrow aspirates (n=6) were expended (i) into BM-MSCs using a complete MSC culture medium or (ii) into ALLOB® cells according to its manufacturing process. Cells were characterized in vitro by morphology, immunophenotype, gene expression and differentiation potential. Additionally, their osteogenic potential was assessed in vivo in the subperiosteal calvaria bone formation model in nude mice. Results: The in vitro side-by-side comparison studies showed that although ALLOB® and BM-MSC shared some common general characteristics such as the 3 minimal MSC criteria, ALLOB® expressed significantly higher levels of chondro/osteoblastic genes such as BMP2 (fold change (FC) > 100), ALPL (FC > 12), CBFA1 (FC > 3) and differentiated significantly earlier than BM-MSC toward the osteogenic lineage. Moreover the bone formation model in nude mice demonstrated that used at the same cellular concentration, ALLOB® was able to induce significantly more (160% vs.107% for control animals) bone formation than BM-MSC (118% vs. 107 % for control animals) two weeks after administration. Conclusion: Our side-by-side comparison studies demonstrated that in vitro and in vivo, ALLOB® displays superior osteogenic capacity to BM-MScs and is therefore a better candidate for the treatment of bone fractures.Keywords: gene expression, histomorphometry, mesenchymal stem cells, osteogenic differentiation potential, preclinical
Procedia PDF Downloads 33011128 Insight-Based Evaluation of a Map-Based Dashboard
Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg
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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage compared to task-based evaluation methods.Keywords: visual analytics, dashboard, insight-based evaluation, geographic visualization
Procedia PDF Downloads 11611127 Application of the Urban Forest Credit Standard as a Tool for Compensating CO2 Emissions in the Metalworking Industry: A Case Study in Brazil
Authors: Marie Madeleine Sarzi Inacio, Ligiane Carolina Leite Dauzacker, Rodrigo Henriques Lopes Da Silva
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The climate changes resulting from human activity have increased interest in more sustainable production practices to reduce and offset pollutant emissions. Brazil, with its vast areas capable of carbon absorption, holds a significant advantage in this context. However, to optimize the country's sustainable potential, it is important to establish a robust carbon market with clear rules for the eligibility and validation of projects aimed at reducing and offsetting Greenhouse Gas (GHG) emissions. In this study, our objective is to conduct a feasibility analysis through a case study to evaluate the implementation of an urban forest credits standard in Brazil, using the Urban Forest Credits (UFC) model implemented in the United States as a reference. Thus, the city of Ribeirão Preto, located in Brazil, was selected to assess the availability of green areas. With the CO2 emissions value from the metalworking industry, it was possible to analyze information in the case study, considering the activity. The QGIS software was used to map potential urban forest areas, which can connect to various types of geospatial databases. Although the chosen municipality has little vegetative coverage, the mapping identified at least eight areas that fit the standard definitions within the delimited urban perimeter. The outlook was positive, and the implementation of projects like Urban Forest Credits (UFC) adapted to the Brazilian reality has great potential to benefit the country in the carbon market and contribute to achieving its Greenhouse Gas (GHG) emission reduction goals.Keywords: carbon neutrality, metalworking industry, carbon credits, urban forestry credits
Procedia PDF Downloads 7611126 Anti-Inflammatory Activity of Topical Anthocyanins by Complexation and Niosomal Encapsulation
Authors: Aroonsri Priprem, Sucharat Limsitthichaikoon, Suttasinee Thappasarapong
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Anthocyanins are natural pigments with effective UV protection but their topical use could be limited due to their physicochemical characteristics. An attempt to overcome such limitations by complexation of 2 major anthocyanin-rich sources, C. ternatea, and Z. mays, for investigation on potential use as topical anti-inflammatory. Cell studies indicate no cytotoxicity of the anthocyanin complex (AC) up to 1 mg/ml tested in HaCaT and human forehead fibroblasts by MTT. Croton oil-induced ear edema in Wistar rats suggests an effective dose of 5 mg/cm2 of AC as a topical anti-inflammatory in comparison to 0.5 mg/cm2 of fluocinolone acetonide. Niosomal encapsulation of the AC significantly prolonged the anti-inflammatory activity particularly at 8 h after topical application (p = 0.0001). The AC was not cytotoxic and its anti-inflammatory and activity was dose-dependent and prolonged by niosomal encapsulation. It has also shown to promote collagen type 1 production in cell culture. Thus, AC could be a potential candidate for topical anti-inflammatory agent from natural resources.Keywords: anthocyanin complex, ear edema, inflammation, niosomes, skin
Procedia PDF Downloads 32811125 Co-Synthesis of Exopolysaccharides and Polyhydroxyalkanoates Using Waste Streams: Solid-State Fermentation as an Alternative Approach
Authors: Laura Mejias, Sandra Monteagudo, Oscar Martinez-Avila, Sergio Ponsa
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Bioplastics are gaining attention as potential substitutes of conventional fossil-derived plastics and new components of specialized applications in different industries. Besides, these constitute a sustainable alternative since they are biodegradable and can be obtained starting from renewable sources. Thus, agro-industrial wastes appear as potential substrates for bioplastics production using microorganisms, considering they are a suitable source for nutrients, low-cost, and available worldwide. Therefore, this approach contributes to the biorefinery and circular economy paradigm. The present study assesses the solid-state fermentation (SSF) technology for the co-synthesis of exopolysaccharides (EPS) and polyhydroxyalkanoates (PHA), two attractive biodegradable bioplastics, using the leftover of the brewery industry brewer's spent grain (BSG). After an initial screening of diverse PHA-producer bacteria, it was found that Burkholderia cepacia presented the highest EPS and PHA production potential via SSF of BSG. Thus, B. cepacia served to identify the most relevant aspects affecting the EPS+PHA co-synthesis at a lab-scale (100g). Since these are growth-dependent processes, they were monitored online through oxygen consumption using a dynamic respirometric system, but also quantifying the biomass production (gravimetric) and the obtained products (EtOH precipitation for EPS and solid-liquid extraction coupled with GC-FID for PHA). Results showed that B. cepacia has grown up to 81 mg per gram of dry BSG (gDM) at 30°C after 96 h, representing up to 618 times higher than the other tested strains' findings. Hence, the crude EPS production was 53 mg g-1DM (2% carbohydrates), but purity reached 98% after a dialysis purification step. Simultaneously, B. cepacia accumulated up to 36% (dry basis) of the produced biomass as PHA, mainly composed of polyhydroxybutyrate (P3HB). The maximum PHA production was reached after 48 h with 12.1 mg g⁻¹DM, representing threefold the levels previously reported using SSF. Moisture content and aeration strategy resulted in the most significant variables affecting the simultaneous production. Results show the potential of co-synthesis via SSF as an attractive alternative to enhance bioprocess feasibility for obtaining these bioplastics in residue-based systems.Keywords: bioplastics, brewer’s spent grain, circular economy, solid-state fermentation, waste to product
Procedia PDF Downloads 14411124 Renewable Energy from Local Waste for Producing of Processed Agricultural Products
Authors: Ruedee Niyomrath, Somboon Sarasit, Chaisri Tharaswatpipat
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This research aims to study the potential of local waste material in quantity and quality. The potential for such local forms of waste material used as renewable energy for the production of processed agricultural products. The results of this study are useful to producers of agricultural products to use fuel that in local, reduce production costs, and conservation. The results showed that Samut Songkhram is a small province located in the central Thailand, sea area, and subdivided into 3 districts. This province has a population of 80 percent of farmers and agriculture with 50 percent of the area planted to coconut growing. Productivity of coconut help create value for the primacy of the province. Waste materials from coconut have quantity and quality potentials for processing biomass into charcoal as the renewable energy for the production of processed agricultural products.Keywords: waste, renewable energy, producing of product, processed agricultural products
Procedia PDF Downloads 44011123 Perspectives of Renewable Energy in 21st Century in India: Statistics and Estimation
Authors: Manoj Kumar, Rajesh Kumar
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With the favourable geographical conditions at Indian-subcontinent, it is suitable for flourishing renewable energy. Increasing amount of dependence on coal and other conventional sources is driving the world into pollution and depletion of resources. This paper presents the statistics of energy consumption and energy generation in Indian Sub-continent, which notifies us with the increasing energy demands surpassing energy generation. With the aggrandizement in demand for energy, usage of coal has increased, since the major portion of energy production in India is from thermal power plants. The increase in usage of thermal power plants causes pollution and depletion of reserves; hence, a paradigm shift to renewable sources is inevitable. In this work, the capacity and potential of renewable sources in India are analyzed. Based on the analysis of this work, future potential of these sources is estimated.Keywords: depletion of reserves, energy consumption and generation, emmissions, global warming, renewable sources
Procedia PDF Downloads 43211122 Carbon Storage in Natural Mangrove Biomass: Its Destruction and Potential Impact on Climate Change in the UAE
Authors: Hedaya Ali Al Ameri, Alya A. Arabi
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Measuring the level of carbon storage in mangroves’ biomass has a potential impact in the climate change of UAE. Carbon dioxide is one of greenhouse gases. It is considered to be a main reason for global warming. Deforestation is a key source of the increase in carbon dioxide whereas forests such as mangroves assist in removing carbon dioxide from atmosphere by storing them in its biomass and soil. By using Kauffman and Donato methodology, above- and below-ground biomass and carbon stored in UAE’s natural mangroves were quantified. Carbon dioxide equivalent (CO2eq) released to the atmosphere was then estimated in case of mangroves deforestation in the UAE. The results show that the mean total biomass of mangroves in the UAE ranged from 15.75 Mg/ha to 3098.69 Mg/ha. The estimated CO2eq released upon deforestation in the UAE was found to have a minimal effect on the temperature increase and thus global warming.Keywords: carbon stored in biomass, mangrove deforestation, temperature change, United Arab Emirate
Procedia PDF Downloads 39611121 Development and Modeling of a Geographic Information System Solar Flux in Adrar, Algeria
Authors: D. Benatiallah, A. Benatiallah, K. Bouchouicha, A. Harouz
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The development and operation of renewable energy known an important development in the world with significant growth potential. Estimate the solar radiation on terrestrial geographic locality is of extreme importance, firstly to choose the appropriate site where to place solar systems (solar power plants for electricity generation, for example) and also for the design and performance analysis of any system using solar energy. In addition, solar radiation measurements are limited to a few areas only in Algeria. Thus, we use theoretical approaches to assess the solar radiation on a given location. The Adrar region is one of the most favorable sites for solar energy use with a medium flow that exceeds 7 kWh / m2 / d and saddle of over 3500 hours per year. Our goal in this work focuses on the creation of a data bank for the given data in the energy field of the Adrar region for the period of the year and the month then the integration of these data into a geographic Information System (GIS) to estimate the solar flux on a location on the map.Keywords: Adrar, flow, GIS, deposit potential
Procedia PDF Downloads 37411120 Adapting Cyber Physical Production Systems to Small and Mid-Size Manufacturing Companies
Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour
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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop
Procedia PDF Downloads 14011119 Development and Characterization of Mesoporous Silica Nanoparticles of Quercetin in Skin Cancer
Authors: Khusboo Agrawal, S. Saraf
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Quercetin, a flavonol provides a cellular protection against UV induced oxidative damages due to its excellent free radical scavenging activity and direct pro-apoptopic effect on tumor cells. However, its topical use is limited due to its unfavorable physicochemical properties. The present study was aimed to evaluate the potential of mesoporous silica nanoparticles as topical carrier system for quercetin delivery. Complexes of quercetin with mesoporous silica was prepared with different weight ratios and characterized by thermo gravimetric analysis, X-ray diffraction, high resolution TEM, FT-IR spectroscopy, zeta potential measurements and differential scanning calorimetry The protective effect of this vehicle on UV-induced degradation of the quercetin was investigated revealing a certain positive influence of the inclusion on the photostability over time. Epidermal accumulation and transdermal permeation of this molecule were ex vivo evaluated by using Franz diffusion cells. The immobilization of Quercetin in mesoporous silica nanoparticles (MSNs) increased the stability without undermining the antioxidant efficacy.Keywords: cancer, MSNs, quercetin, topical delivery
Procedia PDF Downloads 30811118 AI-Enabled Smart Contracts for Reliable Traceability in the Industry 4.0
Authors: Harris Niavis, Dimitra Politaki
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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.Keywords: blockchain, data quality, industry4.0, product quality
Procedia PDF Downloads 18911117 Highly Conductive Polycrystalline Metallic Ring in a Magnetic Field
Authors: Isao Tomita
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Electrical conduction in a quasi-one-dimensional polycrystalline metallic ring with a long electron phase coherence length realized at low temperature is investigated. In this situation, the wave nature of electrons is important in the ring, where the electrical current I can be induced by a vector potential that arises from a static magnetic field applied perpendicularly to the ring’s area. It is shown that if the average grain size of the polycrystalline ring becomes large (or comparable to the Fermi wavelength), the electrical current I increases to ~I0, where I0 is a current in a disorder-free ring. The cause of this increasing effect is examined, and this takes place if the electron localization length in the polycrystalline potential increases with increasing grain size, which gives rise to coherent connection of tails of a localized electron wave function in the ring and thus provides highly coherent electrical conduction.Keywords: electrical conduction, electron phase coherence, polycrystalline metal, magnetic field
Procedia PDF Downloads 38811116 Exploring the Potential of Phase Change Materials in Construction Environments
Authors: A. Ait Ahsene F., B. Boughrara S.
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The buildings sector accounts for a significant portion of global energy consumption, with much of this energy used to heat and cool indoor spaces. In this context, the integration of innovative technologies such as phase change materials (PCM) holds promising potential to improve the energy efficiency and thermal comfort of buildings. This research topic explores the benefits and challenges associated with the use of PCMs in buildings, focusing on their ability to store and release thermal energy to regulate indoor temperature. We investigated the different types of PCM available, their thermal properties, and their potential applications in various climate zones and building types. To evaluate and compare the performance of PCMs, our methodology includes a series of laboratory and field experiments. In the laboratory, we measure the thermal storage capacity, melting and solidification temperatures, latent heat, and thermal conductivity of various PCMs. These measurements make it possible to quantify the capacity of each PCM to store and release thermal energy, as well as its capacity to transfer this energy through the construction materials. Additionally, field studies are conducted to evaluate the performance of PCMs in real-world environments. We install PCM systems in real buildings and monitor their operation over time, measuring energy savings, occupant thermal comfort, and material durability. These empirical data allow us to compare the effectiveness of different types of PCMs under real-world use conditions. By combining the results of laboratory and field experiments, we provide a comprehensive analysis of the advantages and limitations of PCMs in buildings, as well as recommendations for their effective application in practice.Keywords: energy saving, phase change materials, material sustainability, buildings sector
Procedia PDF Downloads 4111115 Improved K-Means Clustering Algorithm Using RHadoop with Combiner
Authors: Ji Eun Shin, Dong Hoon Lim
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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.Keywords: big data, combiner, K-means clustering, RHadoop
Procedia PDF Downloads 43911114 Predicting Mass-School-Shootings: Relevance of the FBI’s ‘Threat Assessment Perspective’ Two Decades Later
Authors: Frazer G. Thompson
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The 1990s in America ended with a mass-school-shooting (at least four killed by gunfire excluding the perpetrator(s)) at Columbine High School in Littleton, Colorado. Post-event, many demanded that government and civilian experts develop a ‘profile’ of the potential school shooter in order to identify and preempt likely future acts of violence. This grounded theory research study seeks to explore the validity of the original hypotheses proposed by the Federal Bureau of Investigation (FBI) in 2000, as it relates to the commonality of disclosure by perpetrators of mass-school-shootings, by evaluating fourteen mass-school-shooting events between 2000 and 2019 at locations around the United States. Methods: The strategy of inquiry seeks to investigate case files, public records, witness accounts, and available psychological profiles of the shooter. The research methodology is inclusive of one-on-one interviews with members of the FBI’s Critical Incident Response Group seeking perspective on commonalities between individuals; specifically, disclosure of intent pre-event. Results: The research determined that school shooters do not ‘unfailingly’ notify others of their plans. However, in nine of the fourteen mass-school-shooting events analyzed, the perpetrator did inform the third party of their intent pre-event in some form of written, oral, or electronic communication. In the remaining five instances, the so-called ‘red-flag’ indicators of the potential for an event to occur were profound, and unto themselves, might be interpreted as notification to others of an imminent deadly threat. Conclusion: Data indicates that conclusions drawn in the FBI’s threat assessment perspective published in 2000 are relevant and current. There is evidence that despite potential ‘red-flag’ indicators which may or may not include a variety of other characteristics, perpetrators of mass-school-shooting events are likely to share their intentions with others through some form of direct or indirect communication. More significantly, implications of this research might suggest that society is often informed of potential danger pre-event but lacks any equitable means by which to disseminate, prevent, intervene, or otherwise act in a meaningful way considering said revelation.Keywords: columbine, FBI profiling, guns, mass shooting, mental health, school violence
Procedia PDF Downloads 11811113 The Impact of Artificial Intelligence on Marketing Principles and Targets
Authors: Felib Ayman Shawky Salem
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Experiential marketing means an unforgettable experience that remains deeply anchored in the customer's memory. Furthermore, customer satisfaction is defined as the emotional response to the experiences provided that relate to specific products or services purchased. Therefore, experiential marketing activities can influence the level of customer satisfaction and loyalty. In this context, the study aims to examine the relationship between experiential marketing, customer satisfaction and loyalty of beauty products in Konya. The results of this study showed that experiential marketing is an important indicator of customer satisfaction and loyalty and that experiential marketing has a significant positive impact on customer satisfaction and loyalty.Keywords: sponsorship, marketing communication theories, marketing communication tools internet, marketing, tourism, tourism management corporate responsibility, employee organizational performance, internal marketing, internal customer experiential marketing, customer satisfaction, customer loyalty, social sciences.
Procedia PDF Downloads 6811112 Simulation of Government Management Model to Increase Financial Productivity System Using Govpilot
Authors: Arezou Javadi
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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.Keywords: machine learning, financial income, statistical potential, govpilot
Procedia PDF Downloads 8911111 Simulation of Government Management Model to Increase Financial Productivity System Using Govpilot
Authors: Arezou Javadi
Abstract:
The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.Keywords: machine learning, financial income, statistical potential, govpilot
Procedia PDF Downloads 7011110 Inflammatory Markers in the Blood and Chronic Periodontitis
Authors: Saimir Heta, Ilma Robo, Nevila Alliu, Tea Meta
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Background: Plasma levels of inflammatory markers are the expression of the infectious wastes of existing periodontitis, as well as of existing inflammation everywhere in the body. Materials and Methods: The study consists of the clinical part of the measurement of inflammatory markers of 23 patients diagnosed with chronic periodontitis and the recording of parental periodontal parameters of patient periodontal status: hemorrhage index and probe values, before and 7-10 days after non-surgical periodontal treatment. Results: The level of fibrinogen drops according to the categorization of disease progression, active and passive, with the biggest % (18%-30%) at the fluctuation 10-20 mg/d. Fluctuations in fibrinogen level according to the age of patients in the range 0-10 mg/dL under 40 years and over 40 years was 13%-26%, in the range 10-20 mg/dL was 26%-22%, in the 20-40 mg/dL was 9%-4%. Conclusions: Non-surgical periodontal treatment significantly reduces the level of non-inflammatory markers in the blood. Oral health significantly reduces the potential source for periodontal bacteria, with the potential of promoting thromboembolism, through interaction between thrombocytes.Keywords: chronic periodontitis, atherosclerosis, risk factor, inflammatory markers
Procedia PDF Downloads 12611109 Autonomic Recovery Plan with Server Virtualization
Authors: S. Hameed, S. Anwer, M. Saad, M. Saady
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For autonomic recovery with server virtualization, a cogent plan that includes recovery techniques and backups with virtualized servers can be developed instead of assigning an idle server to backup operations. In addition to hardware cost reduction and data center trail, the disaster recovery plan can ensure system uptime and to meet objectives of high availability, recovery time, recovery point, server provisioning, and quality of services. This autonomic solution would also support disaster management, testing, and development of the recovery site. In this research, a workflow plan is proposed for supporting disaster recovery with virtualization providing virtual monitoring, requirements engineering, solution decision making, quality testing, and disaster management. This recovery model would make disaster recovery a lot easier, faster, and less error prone.Keywords: autonomous intelligence, disaster recovery, cloud computing, server virtualization
Procedia PDF Downloads 16211108 Postbuckling Analysis of End Supported Rods under Self-Weight Using Intrinsic Coordinate Finite Elements
Authors: C. Juntarasaid, T. Pulngern, S. Chucheepsakul
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A formulation of postbuckling analysis of end supported rods under self-weight has been presented by the variational method. The variational formulation involving the strain energy due to bending and the potential energy of the self-weight, are expressed in terms of the intrinsic coordinates. The variational formulation is accomplished by introducing the Lagrange multiplier technique to impose the boundary conditions. The finite element method is used to derive a system of nonlinear equations resulting from the stationary of the total potential energy and then Newton-Raphson iterative procedure is applied to solve this system of equations. The numerical results demonstrate the postbluckled configurations of end supported rods under self-weight. This finite element method based on variational formulation expressed in term of intrinsic coordinate is highly recommended for postbuckling analysis of end-supported rods under self-weight.Keywords: postbuckling, finite element method, variational method, intrinsic coordinate
Procedia PDF Downloads 15811107 Soil Matric Potential Based Irrigation in Rice: A Solution to Water Scarcity
Authors: S. N. C. M. Dias, Niels Schuetze, Franz Lennartz
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The current focus in irrigated agriculture will move from maximizing crop production per unit area towards maximizing the crop production per unit amount of water (water productivity) used. At the same time, inadequate water supply or deficit irrigation will be the only solution to cope with water scarcity in the near future. Soil matric potential based irrigation plays an important role in such deficit irrigated agriculture to grow any crop including rice. Rice as the staple food for more than half of the world population, grows mainly under flooded conditions. It requires more water compared to other upland cereals. A major amount of this water is used in the land preparation and is lost at field level due to evaporation, deep percolation, and seepage. A field experimental study was conducted in the experimental premises of rice research and development institute of Sri Lanka in Kurunegala district to estimate the water productivity of rice under deficit irrigation. This paper presents the feasibility of improving current irrigation management in rice cultivation under water scarce conditions. The experiment was laid out in a randomized complete block design with four different irrigation treatments with three replicates. Irrigation treatments were based on soil matric potential threshold values. Treatment W0 was maintained between 60-80mbars. W1 was maintained between 80-100mbars. Other two dry treatments W2 and W3 were maintained at 100-120 mbar and 120 -140 mbar respectively. The sprinkler system was used to irrigate each plot individually upon reaching the maximum threshold value in respective treatment. Treatments were imposed two weeks after seed establishment and continued until two weeks before physiological maturity. Fertilizer applications, weed management, and other management practices were carried out per the local recommendations. Weekly plant growth measurements, daily climate parameters, soil parameters, soil tension values, and water content were measured throughout the growing period. Highest plant growth and grain yield (5.61t/ha) were observed in treatment W2 followed by W0, W1, and W3 in comparison to the reference yield (5.23t/ha) of flooded rice grown in the study area. Water productivity was highest in W3. Concerning the irrigation water savings, grain yield, and water productivity together, W2 showed the better performance. Rice grown under unsaturated conditions (W2) shows better performance compared to the continuously saturated conditions(W0). In conclusion, soil matric potential based irrigation is a promising practice in irrigation management in rice. Higher irrigation water savings can be achieved in this method. This strategy can be applied to a wide range of locations under different climates and soils. In future studies, higher soil matric potential values can be applied to evaluate the maximum possible values for rice to get higher water savings at minimum yield losses.Keywords: irrigation, matric potential, rice, water scarcity
Procedia PDF Downloads 19811106 Development and Evaluation of a Nutraceutical Herbal Summer Drink
Authors: Munish Garg, Vinni Ahuja
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In the past few years, the high consumption of soft drinks has attracted negative attention world-wide due to its possible adverse effects, leading the health conscious people to find alternative nutraceutical or herbal health drinks. In the present study, a nutraceutical soft drink was developed utilizing some easily available and well known traditional herbs having nutritional potential. The key ingredients were selected as bael, amla, lemon juice, ashwagandha and poppy seeds based on their household routine use in the summer with proven refreshing, cooling and energetic feeling since ages. After several trials made, the final composition of nutraceutical summer soft drink was selected as most suitable combination based on the taste, physicochemical, microbial and organoleptic point of view. The physicochemical analysis of the prepared drink found to contain optimum level of titratable acidity, total soluble solids and pH which were in accordance of the commercial recommendations. There were no bacterial colonies found in the product therefore found within limits. During the nine point’s hedonic scale sensory evaluation, the drink was strongly liked for colour, taste, flavour and texture. The formulation was found to contain flavonoids (80mg/100ml), phenolics (103mg/100ml), vitamin C (250mg/100ml) and has antioxidant potential (75.52%) apart from providing several other essential vitamins, minerals and healthy components. The developed nutraceutical drink provides an economical and feasible option for the consumers with very good taste combined with potential health benefits. The present drink is potentially capable to replace the synthetic soft drinks available in the market.Keywords: herbal drink, summer drink, nutraceuticals, soft drink
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