Search results for: recurrent artificial neural network

Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

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The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

Procedia PDF Downloads 136

Authors: Pitak Keawbunsong, Sathaporn Promwong

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This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

Procedia PDF Downloads 340

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

Procedia PDF Downloads 213

Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

Procedia PDF Downloads 141

Authors: Irfan Zafar

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Over the years the Telecom Industry in the country has shown a lot of progress in terms of infrastructure development coupled with the availability of telecom services. This has however led to the cut throat completion among various operators thus leading to reduced tariffs to the customers. The profit margins have seen a reduction thus leading the operators to think of other avenues by adopting new models while keeping the quality of service intact. The outsourcing of the network and the resources is one such model which has shown promising benefits which includes lower costs, less risk, higher levels of customer support and engagement, predictable expenses, access to the emerging technologies, benefiting from a highly skilled workforce, adaptability, focus on the core business while reducing capital costs. A lot of research has been done on outsourcing in terms of reasons of outsourcing and its benefits. However this study is an attempt to analyze the effects of the outsourcing on an organizations performance (Telecommunication Sector) considering the variables (1) Cost Reduction (2) Organizational Performance (3) Flexibility (4) Employee Performance (5) Access to Specialized Skills & Technology and the (6) Outsourcing Risks.

Keywords: outsourcing, ICT, telecommunication, IT, networking

Procedia PDF Downloads 399

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

Procedia PDF Downloads 189

Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

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In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

Procedia PDF Downloads 664

Authors: Leila Karshenas, Hamid Reza Khodaei, Behnaz Mahdavi

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We know that nitric oxide (NO) plays an important role in all sexual activities of animals. It is made in body from NO synthase enzyme and L-arginin molecule. NO can bound with sulfur-iron complexes and because production of steroid sexual hormones is related to enzymes which have this complex, NO can change the activity of these enzymes. NO affects many cells including endothelial cells of veins, macrophages and mast cells. These cells are found in testis leydig cells and therefore are important source of NO in testis tissue. Minimizing damages to sperm at the time of sperm freezing and thawing is really important. The goal of this study was to determine the function of NO before freezing and its effects on quality and viability of sperms after thawing and incubation. 4 Holstein bulls were selected from the age of 4, and artificial insemination was done for 3 weeks (2 times a week). Treatments were 0, 10, 50 and 100 nm of sodium nitroprusside (SNP). Data analysis was performed by SAS98 program. Also, mean comparison was done using Duncan's multiple ranges test (P<0.05). Concentrations used was found to increase motility and viability of spermatozoa at 1, 2 and 3 hours after thawing significantly (P<0.05), but there was no significant difference at zero time. SNP levels reduced the amount of lipid peroxidation in sperm membrane, increased acrosome health and improved sample membranes especially in 50 and 100 nm treatments. According to results, adding SNP to semen diluents increases motility and viability of spermatozoa. Also, it reduces lipid peroxidation in sperm membrane and improves sperm function.

Keywords: sperm motility, nitric oxide, lipid peroxidation, spermatozoa

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Authors: Ahmad Saad, Shuja Abbas, Breanna Marine

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Introduction: This study explores the potential applications of autologous pedal fat pad grafting as a minimally invasive therapeutic strategy for addressing pedal fat pad loss. Without adequate shock absorbing tissue, a patient can experience functional deficits, ulcerations, loss of quality of life, and significant limitations with ambulation. This study details a novel technique involving autologous adipose grafting from the abdomen to enhance plantar fat pad thickness in a patient involved in a severe motor vehicle accident which resulted in total fat pad loss of the heel. Autologous adipose grafting (AAG) was used following adipose allografting in an effort to recreate a normal shock absorbing surface to allow return to activities of daily living and painless ambulation. Methods: A 46-year-old male sustained multiple open pedal fractures and necrosis to the heel fat pad after a motorcycle accident, which resulted in complete loss of the calcaneal fat pad. The patient underwent serial debridement’s, utilization of wound vac therapy and split thickness skin grafting to accomplish complete closure, despite complete loss of adipose to area. Patient presented with complaints of pain on ambulation, inability to bear weight on the heel, recurrent ulcerations, admitted had not been ambulating for two years. Clinical exam demonstrated complete loss of the plantar fat pad with a thin layer of epithelial tissue overlying the calcaneal bone, allowing visibility of the osseous contour of the calcaneus. Scar tissue had formed in place of the fat pad, with thickened epithelial tissue extending from the midfoot to the calcaneus. After conservative measures were exhausted, the patient opted for initial management by adipose allograft matrix (AAM) injections. Post operative X-ray imaging revealed noticeable improvement in calcaneal fat pad thickness. At 1 year follow up, the patient was able to ambulate without assistive devices. The fat pad at this point was significantly thicker than it was pre-operatively, but the thickness did not restore to pre-accident thickness. In order to compare the take of allograft versus autografting of adipose tissue, the decision to use adipose autograft through abdominal liposuction harvesting was deemed suitable. A general surgeon completed harvesting of adipose cells from the patient’s abdomen via liposuction, and a podiatric surgeon performed the AAG injection into the heel. Total of 15 cc’s of autologous adipose tissue injected to the calcaneus. Results: There was a visual increase in the calcaneal fat pad thickness both clinically and radiographically. At the 6-week follow up, imaging revealed retention of the calcaneal fat pad thickness. Three months postop, patient returned to activities of daily living and increased quality of life due to their increased ability to ambulate. Discussion: AAG is a novel treatment for pedal fat pad loss. These treatments may be viable and reproducible therapeutic choices for patients suffering from fat pad atrophy, fat pad loss, and/or plantar ulcerations. Both treatments of AAM and AAG exhibited similar therapeutic results by providing pain relief for ambulation and allowing for patients to return to their quality of life.

Keywords: podiatry, wound, adipose, allograft, autograft, wound care, limb reconstruction, injection, limb salvage

Procedia PDF Downloads 82

Authors: Oscar Covarrubias, Diane Ghanem, Christopher Murdock, Babar Shafiq

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Introduction: ChatGPT is an advanced language AI tool designed to understand and generate human-like text. The aim of this study is to assess the ability of ChatGPT-4 to re-write orthopaedic trauma patient education materials at the recommended 6th-grade level. Methods: Two independent reviewers accessed ChatGPT-4 (chat.openai.com) and gave identical instructions to simplify the readability of provided text to a 6th-grade level. All trauma-related articles by the Orthopaedic Trauma Association (OTA) and American Academy of Orthopaedic Surgeons (AAOS) were sequentially provided. The academic grade level was determined using the Flesh-Kincaid Grade Level (FKGL) and Flesch Reading Ease (FRE). Paired t-tests and Wilcox-rank sum tests were used to compare the FKGL and FRE between the ChatGPT-4 revised and original text. Inter-rater correlation coefficient (ICC) was used to assess variability in ChatGPT-4 generated text between the two reviewers. Results: ChatGPT-4 significantly reduced FKGL and increased FRE scores in the OTA (FKGL: 5.7±0.5 compared to the original 8.2±1.1, FRE: 76.4±5.7 compared to the original 65.5±6.6, p < 0.001) and AAOS articles (FKGL: 5.8±0.8 compared to the original 8.9±0.8, FRE: 76±5.5 compared to the original 56.7±5.9, p < 0.001). On average, 14.6% of OTA and 28.6% of AAOS articles required at least two revisions by ChatGPT-4 to achieve a 6th-grade reading level. ICC demonstrated poor reliability for FKGL (OTA 0.24, AAOS 0.45) and moderate reliability for FRE (OTA 0.61, AAOS 0.73). Conclusion: This study provides a novel, simple and efficient method using language AI to optimize the readability of patient education content which may only require the surgeon’s final proofreading. This method would likely be as effective for other medical specialties.

Keywords: artificial intelligence, AI, chatGPT, patient education, readability, trauma education

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Rafael Haag, Elton Rossini

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This work aims to validate and make the projections of solar energy for the Brazilian period from 2025 to 2100. As the plants designed by the HadGEM2-AO (Global Hadley Model 2 - Atmosphere) General Circulation Model UK Met Office Hadley Center, belonging to Phase 5 of the Intercomparison of Coupled Models (CMIP5). The simulation results of the model are compared with monthly data from 2006 to 2013, measured by a network of meteorological sections of the National Institute of Meteorology (INMET). The performance of HadGEM2-AO is evaluated by the efficiency coefficient (CEF) and bias. The results are shown in the table of maps and maps. HadGEM2-AO, in the most pessimistic scenario, RCP 8.5 had a very good accuracy, presenting efficiency coefficients between 0.94 and 0.98, the perfect setting being Solar radiation, which indicates a horizontal trend, is a climatic alternative for some regions of the Brazilian scenario, especially in spring.

Keywords: climate change, projections, solar radiation, scenarios climate change

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Authors: Bhargavi G., Arathi R. Shankar

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Transmitter and receiver closer to every other, which creates the twin benefits of better-nice links and more spatial reuse. In a network with nomadic customers, this inevitably includes deploying greater infrastructure, normally in the form of microcells, hot spots, disbursed antennas, or relays. A less pricey alternative is the recent concept of femtocells, additionally known as domestic base stations that are facts get admission to points installed by means of domestic users to get higher indoor voice and records insurance. Femtocells have the potential to offer excessive exceptional community get entry to indoor customers at low cost, even as concurrently reducing the load. gift femtocells that perform in 4G can also be extended for 5G sub-6 GHz band. Designing the femtocell in mmWave band of 5G may have many blessings in terms of bandwidth availability and coverage. Multiband microstrip patch antennas can be considered as a low value and prominent antennas in designing the femtocells because the single antenna helps multiple frequency.

Keywords: 5G, mmWave, antennas, wireless communications, femtocell

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

Procedia PDF Downloads 435

Authors: Sareh Enjavi

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In recent years, the field of visual communication design has seen a significant shift in the way that art is created and consumed, with the advent of new technologies like virtual reality, augmented reality, and artificial intelligence. This paper explores the ways in which technology is changing the landscape of visual communication design, and how designers are incorporating new technological tools into their artistic practices. The primary objective of this research paper is to investigate the ways in which technology is influencing the creative process of designers and artists in the field of visual communication design. The paper also aims to examine the challenges and limitations that arise from the intersection of art and technology in visual communication design, and to identify strategies for overcoming these challenges. Drawing on examples from a range of fields, including advertising, fine art, and digital media, this paper highlights the exciting innovations that are emerging as artists and designers use technology to push the boundaries of traditional artistic expression. The paper argues that embracing technological innovation is essential for the continued evolution of visual communication design. By exploring the intersection of art and technology, designers can create new and exciting visual experiences that engage and inspire audiences in new ways. The research also contributes to the theoretical and methodological understanding of the intersection of art and technology, a topic that has gained significant attention in recent years. Ultimately, this paper emphasizes the importance of embracing innovation and experimentation in the field of visual communication design, and highlights the exciting innovations that are emerging as a result of the intersection of art and technology, and emphasizes the importance of embracing innovation and experimentation in the field of visual communication design.

Keywords: visual communication design, art and technology, virtual reality, interactive art, creative process

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Authors: Chien-Chun Hung, Chun-Fong Wu

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It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: mini UAV, reconnaissance, wireless transmission, ZigBee modulus

Procedia PDF Downloads 196

Authors: Ali Asgary, Haopeng Zhou, Ghassem Tofighi

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Use of virtual (VR), augmented reality (AR), and extended reality technologies for training and education has increased in recent years as more hardware and software tools have become available and accessible to larger groups of users. Similarly, the applications of these technologies in earthquake related training and education are on the rise. Several studies have reported promising results for the use of VR and AR for evacuation behaviour and training under earthquake situations. They simulate the impacts that earthquake has on buildings, buildings’ contents, and how building occupants and users can find safe spots or open paths to outside. Considering that considerable number of earthquake injuries and fatalities are linked to the behaviour, our goal is to use these technologies to reduce the impacts of building contents on people. Building on our artificial intelligence (AI) based indoor earthquake risk assessment application that enables users to use their mobile device to assess the risks associated with building contents during earthquakes, we develop a virtual reality application to demonstrate the behavior of different building contents during earthquakes, their associate moving, spreading, falling, and collapsing risks, and their risk mitigation methods. We integrate realistic seismic models, building contents behavior with and without risk mitigation measures in virtual reality environment. The application can be used for training of architects, interior design experts, and building users to enhance indoor safety of the buildings that can sustain earthquakes. This paper describes and demonstrates the application development background, structure, components, and usage.

Keywords: virtual reality, earthquake damage, building content, indoor risks, earthquake risk mitigation, interior design, unity game engine, oculus

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Authors: Ruphi Naz, Altaf Ahmad, Mohammad Anis

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Sialic acid (5-Acetylneuraminic acid, Neu5Ac) is a common sugar found as a terminal residue on glycoconjugates in many animals. Humans brain and the central nervous system contain the highest concentration of sialic acid (as N-acetylneuraminic acid) where these acids play an important role in neural transmission and ganglioside structure in synaptogenesis. Due to its important biological function, sialic acid is attracting increasing attention. To understand metabolic networks, fluxes and regulation, it is essential to be able to determine the cellular and subcellular levels of metabolites. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. Taking this, we developed a genetically encoded FRET (fluorescence resonance energy transfer) based nanosensor to analyse the sialic acid level in living cells. Sialic acid periplasmic binding protein (sia P) from Haemophilus influenzae was taken and ligated between the FRET pair, the cyan fluorescent protein (eCFP) and Venus. The chimeric sensor protein was expressed in E. coli BL21 (DE3) and purified by affinity chromatography. Conformational changes in the binding protein clearly confirmed the changes in FRET efficiency. So any change in the concentration of sialic acid is associated with the change in FRET ratio. This sensor is very specific to sialic acid and found stable with the different range of pH. This nanosensor successfully reported the intracellular level of sialic acid in bacterial cell. The data suggest that the nanosensors may be a versatile tool for studying the in vivo dynamics of sialic acid level non-invasively in living cells

Keywords: nanosensor, FRET, Haemophilus influenzae, metabolic networks

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.

Keywords: IoT, network formation, sensor nodes, SSAIL technology

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: S. Potgieter-Vermaak, N. Bain, A. Brown, K. Shaw

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It is well-known from public news media that air pollution is a health hazard and is responsible for early deaths. The quantification of the relationship between air quality and health is a probing question not easily answered. It is known that airborne particulate matter (APM) <2.5µm deposits in the tracheal and alveoli zones and our research probes the possibility of quantifying pulmonary injury by linking reactive oxygen species (ROS) in these particles to DNA damage. Currently, APM mass concentration is linked to early deaths and limited studies probe the influence of other properties on human health. To predict the full extent and type of impact, particles need to be characterised for chemical composition and structure. APMs are routinely analysed for their bulk composition, but of late analysis on a micro level probing single particle character, using micro-analytical techniques, are considered. The latter, single particle analysis (SPA), permits one to obtain detailed information on chemical character from nano- to micron-sized particles. This paper aims to provide a snapshot of studies using data obtained from chemical characterisation and its link with in-vitro studies to inform on personal health risks. For this purpose, two studies will be compared, namely, the bioaccessibility of the inhalable fraction of urban road dust versus total suspended solids (TSP) collected in the same urban environment. The significant influence of metals such as Cu and Fe in TSP on DNA damage is illustrated. The speciation of Hg (determined by SPA) in different urban environments proved to dictate its bioaccessibility in artificial lung fluids rather than its concentration.

Keywords: air pollution, human health, in-vitro studies, particulate matter

Procedia PDF Downloads 227

Authors: Eun-Ji Lee, Hye-Sung Park, Chan-Jung Lee, Won-Sik Kong

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We analyzed the DNA sequence of the ITS (Internal Transcribed Spacer) region of the 18S ribosomal gene and compared it with the gene sequence of T. fuciformis and Hypoxylon sp. in the BLAST database. The sequences of collected T. fuciformis and Hypoxylon sp. have over 99% homology in the T. fuciformis and Hypoxylon sp. sequence BLAST database. In order to select the optimal medium for T. fuciformis, five kinds of a medium such as Potato Dextrose Agar (PDA), Mushroom Complete Medium (MCM), Malt Extract Agar (MEA), Yeast extract (YM), and Compost Extract Dextrose Agar (CDA) were used. T. fuciformis showed the best growth on PDA medium, and Hypoxylon sp. showed the best growth on MCM. So as to investigate the optimum pH and temperature, the pH range was set to pH4 to pH8 and the temperature range was set to 15℃ to 35℃ (5℃ degree intervals). Optimum culture conditions for the T. fuciformis growth were pH5 at 25℃. Hypoxylon sp. were pH6 at 25°C. In order to confirm the most suitable carbon source, we used fructose, galactose, saccharose, soluble starch, inositol, glycerol, xylose, dextrose, lactose, dextrin, Na-CMC, adonitol. Mannitol, mannose, maltose, raffinose, cellobiose, ethanol, salicine, glucose, arabinose. In the optimum carbon source, T. fuciformis is xylose and Hypoxylon sp. is arabinose. Using the column test, we confirmed sawdust a suitable for T. fuciformis, since the composition of sawdust affects the growth of fruiting bodies of T. fuciformis. The sawdust we used is oak tree, pine tree, poplar, birch, cottonseed meal, cottonseed hull. In artificial cultivation of T. fuciformis with sawdust medium, T. fuciformis and Hypoxylon sp. showed fast mycelial growth on mixture of oak tree sawdust, cottonseed hull, and wheat bran.

Keywords: cultivation, optimal condition, tremella fuciformis, nutritional source

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Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Dobdin, Anatoly Skripal, Andrey Usanov, Dmitry Usanov

Abstract:

One of the most important unsolved problems in modern medicine is the increase of chronic diseases that lead to organ dysfunction or even complete loss of function. Current methods of treatment do not result in decreased mortality and disability statistics. Currently, the best treatment for many patients is still transplantation of organs and/or tissues. Therefore, finding a way of correct artificial matrix biofabrication in case of limited number of natural organs for transplantation is a critical task. One important problem that needs to be solved is development of a nondestructive and noninvasive method to analyze dynamic changes of mechanical characteristics of a matrix with minimal side effects on the growing cells. This research was focused on investigating the properties of matrix as a marker of graft condition. In this study, the collagen gel with human primary dermal fibroblasts in suspension (60, 120, 240*103 cells/mL) and collagen gel with cell spheroids were used as model objects. The stiffness and elasticity characteristics were evaluated by a semiconductor laser autodyne. The time and cell concentration dependency of the stiffness and elasticity were investigated. It was shown that these properties changed in a non-linear manner with respect to cell concentration. The maximum matrix stiffness was observed in the collagen gel with the cell concentration of 120*103 cells/mL. This study proved the opportunity to use the mechanical properties of matrix as a marker of graft condition, which can be measured by noninvasive semiconductor laser autodyne technique.

Keywords: graft, matrix, noninvasive method, regenerative medicine, semiconductor laser autodyne

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Authors: Humaira Saeed Malik, Salma Saad

Abstract:

Introduction: Fowler's syndrome, first described by Clare Fowler in 1985, is a rare urological condition characterized by difficulty in urination due to the abnormal function of the urethral sphincter. It predominantly affects young women and leads to chronic urinary retention. The main concern in managing this condition is ensuring regular bladder emptying. Clam cystoplasty is a bladder augmentation surgery in which the bladder is clam-shelled open, and a segment of the intestine is used to increase the bladder's capacity and reduce bladder pressure. The Mitrofanoff procedure, a surgical creation of a continent urinary diversion, is often performed in patients with Fowler's syndrome who require long-term catheterization. This procedure involves creating a conduit (from the appendix or a segment of the small intestine) between the bladder and the skin, allowing for intermittent self-catheterization to manage urinary retention. Study: This case study examines a 39-year-old gravida 3, para 0+2 woman with a BMI of 40, Fowler's syndrome, type I diabetes, and post-traumatic stress disorder (PTSD), presenting at Dumfries and Galloway Royal Infirmary at 8 weeks of gestation. Diagnosed with Fowler's syndrome at 23, . A sacral nerve stimulator (SNS) device was initially placed but was subsequently removed after one year due to malfunction caused by trauma, subsequently she had undergone clam cystoplasty and the Mitrofanoff procedure for bladder management. Her pregnancy was complicated by vaginal bleeding at 10 weeks, treated with progesterone pessaries, and a urinary tract infection at 14 weeks, managed with antibiotics. Despite these challenges, she continued self-catheterization through the Mitrofanoff stoma and was placed on prophylactic antibiotics. Her diabetes was well-controlled on insulin, and a 20-week fetal anomaly scan was normal. The multidisciplinary team, including an obstetrician and a urologist, planned for serial growth scans and the initiation of low molecular weight heparin (LMWH) from 28 weeks due to the intermediate risk of venous thromboembolism (VTE) and to continue six weeks after delivery. A planned cesarean delivery at 37 weeks was arranged, with an MRI scan scheduled later in the pregnancy to assist in surgical planning, ensuring the preservation of the Mitrofanoff stoma's function. The surgery will occur in an elective setting and include a consultant urologist. Conclusion: Pregnancy in women with Fowler's syndrome who have undergone Clam cystoplasty and the Mitrofanoff procedure is rare, and management requires careful planning and a multidisciplinary approach. This case highlights the importance of individualized care plans and close monitoring of both mother and fetus. The patient's risk of recurrent UTIs, coupled with her diabetes and high BMI, necessitated coordinated care across specialties to ensure the best possible outcomes. The Mitrofanoff procedure proved effective in managing her urinary retention, allowing her to maintain self-catheterization during pregnancy. The multidisciplinary team approach was crucial in addressing her complex medical needs, involving obstetrics, urology, and endocrinology. This case adds valuable information to the limited literature on pregnancy management in patients with Fowler's syndrome who have undergone the Mitrofanoff procedure, highlighting the need for comprehensive, individualized care and the involvement of a multidisciplinary team to achieve the best results.

Keywords: fowler's syndrome, clam cystoplasty, mitrofanoff procedure, pregnancy

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Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

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Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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Authors: Gianmarco Taveri, Ivo Dlouhy

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Geopolymers are well-suited materials to abate CO2 emission coming from the Portland cement production, and then replace them, in the near future, in building and other applications. The cost of production of geopolymers may be seen the only weakness, but the use of wastes as raw materials could provide a valid solution to this problem, as demonstrated by the successful incorporation of fly-ash, a by-product of thermal power plants, and waste glasses. Recycled glass in waste-derived geopolymers was lately employed as a further silica source. In this work we present, for the first time, the introduction of recycled borosilicate glass (BSG). BSG is actually a waste glass, since it derives from dismantled pharmaceutical vials and cannot be reused in the manufacturing of the original articles. Owing to the specific chemical composition (BSG is an ‘alumino-boro-silicate’), it was conceived to provide the key components of zeolitic networks, such as amorphous silica and alumina, as well as boria (B2O3), which may replace Al2O3 and contribute to the polycondensation process. The solid–state MAS NMR spectroscopy was used to assess the extent of boron oxide incorporation in the structure of geopolymers, and to define the degree of networking. FTIR spectroscopy was utilized to define the degree of polymerization and to detect boron bond vibration into the structure. Mechanical performance was tested by means of 3 point bending (flexural strength), chevron notch test (fracture toughness), compression test (compressive strength), micro-indentation test (Vicker’s hardness). Spectroscopy (SEM and Confocal spectroscopy) was performed on the specimens conducted to failure. FTIR showed a characteristic absorption band attributed to the stretching modes of tetrahedral boron ions, whose tetrahedral configuration is compatible to the reaction product of geopolymerization. 27Al NMR and 29Si NMR spectra were instrumental in understanding the extent of the reaction. 11B NMR spectroscopies evidenced a change of the trigonal boron (BO3) inside the BSG in favor of a quasi-total tetrahedral boron configuration (BO4). Thanks to these results, it was inferred that boron is part of the geopolymeric structure, replacing the Si in the network, similarly to the aluminum, and therefore improving the quality of the microstructure, in favor of a more cross-linked network. As expected, the material gained as much as 25% in compressive strength (45 MPa) compared to the literature, whereas no improvements were detected in flexural strength (~ 5 MPa) and superficial hardness (~ 78 HV). The material also exhibited a low fracture toughness (0.35 MPa*m1/2), with a tangible brittleness. SEM micrographies corroborated this behavior, showing a ragged surface, along with several cracks, due to the high presence of porosity and impurities, acting as preferential points for crack initiation. The 3D pattern of the surface fracture, following the confocal spectroscopy, evidenced an irregular crack propagation, whose proclivity was mainly, but not always, to follow the porosity. Hence, the crack initiation and propagation are largely unpredictable.

Keywords: borosilicate glass, characterization, fly-ash, geopolymerization

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Authors: Samuel Nderitu Muchiri, Tracy Wangechi Maina

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Truck drivers face a myriad of challenges in their profession. Enhancements in logistics effectiveness can be pivotal in propelling economic developments. The specific objective of the study was to assess the influence of driver distraction on crash risk. The study is significant as it elucidates best practices that truck drivers can embrace in an effort to enhance road safety. These include amalgamating behaviors that enable drivers to fruitfully execute multifaceted functions such as finding and following routes, evading collisions, monitoring speed, adhering to road regulations, and evaluating vehicle systems’ conditions. The analysis involved an empirical review of ten previous studies related to the research topic. The articles revealed that driver distraction plays a substantial role in road accidents and other crucial road security incidents across the globe. Africa depends immensely on the freight transport sector to facilitate supply chain operations. Several studies indicate that drivers who operate primarily on rural roads, such as those found in Sub-Saharan Africa, have an increased propensity to engage in distracted activities such as cell phone usage while driving. The findings also identified the need for digitalization in truck driving operations, including carrier management techniques such as fatigue management, artificial intelligence, and automating functions like cell phone usage controls. The recommendations can aid policymakers and commercial truck carriers in deepening their understanding of driver distraction and enforcing mitigations to foster road safety.

Keywords: truck drivers, distraction, digitalization, crash risk, road safety

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Authors: Nattachote Rugthaicharoencheep

Abstract:

This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

Procedia PDF Downloads 178

Authors: MyungGu Yeo, JongHan Ha, Gi-Hoon Yang, JaeYoon Lee, SeungHyun Ahn, Hyeongjin Lee, HoJun Jeon, YongBok Kim, Minseong Kim, GeunHyung Kim

Abstract:

Tissue engineering is a rapidly growing interdisciplinary research area that may provide options for treating damaged tissues and organs. As a promising technique for regenerating various tissues, this technology requires biomedical scaffolds, which serve as an artificial extracellular matrix (ECM) to support neotissue growth. Electrospun micro/nanofibers have been used widely in tissue engineering because of their high surface-area-to-volume ratio and structural similarity to extracellular matrix. However, low mechanical sustainability, low 3D shape-ability, and low cell infiltration have been major limitations to their use. In this work, we propose new hybrid scaffolds interlayered with cell-laden electrospun micro/nano fibers and poly(caprolactone) microstructures. Also, we applied various concentrations of alginate and electric field strengths to determine optimal conditions for the cell-electrospinning process. The combination of cell-laden bioink (2 ⅹ 10^5 osteoblast-like MG63 cells/mL, 2 wt% alginate, 2 wt% poly(ethylene oxide), and 0.7 wt% lecithin) and a 0.16 kV/mm electric field showed the highest cell viability and fiber formation in this process. Using these conditions and PCL microstructures, we achieved mechanically stable hybrid scaffolds. In addition, the cells embedded in the fibrous structure were viable and proliferated. We suggest that the cell-embedded hybrid scaffolds fabricated using the cell-electrospinning process may be useful for various soft- and hard-tissue regeneration applications.

Keywords: bioink, cell-laden scaffold, micro/nanofibers, poly(caprolactone)

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

Procedia PDF Downloads 137