Search results for: improved sparrow search algorithm

Authors: Ethan James

Abstract:

Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 181

Authors: Maryam Kiani

Abstract:

The aim of this study was to investigate the influence of carbon black additive on the properties of fly ash-based geopolymer. The geopolymer samples were prepared using fly ash as the primary source material, along with an alkali activator solution and different concentrations of carbon black additive. The effects of carbon black on the geopolymer binder were evaluated by analyzing the compressive strength, flexural strength, water absorption, and microstructural properties of the cured samples. The results revealed that the inclusion of carbon black additive significantly enhanced the mechanical properties of the geopolymer binder. The compressive and flexural strengths were found to increase with the addition of carbon black, showing improvements of up to 25% and 15%, respectively. Moreover, the water absorption of the geopolymer samples reduced due to the presence of carbon black, indicating improved resistance against water permeability. Microstructural analysis using scanning electron microscopy (SEM) revealed a more compact and homogenous structure in the geopolymer samples with carbon black. The dispersion of carbon black particles within the geopolymer matrix was observed, suggesting improved interparticle bonding and increased densification. Overall, this study demonstrates the positive impact of carbon black additive on the qualities of fly ash-based geopolymer, emphasizing its potential as an effective enhancer for geopolymer binder applications.

Keywords: fly-ash, carbon black, nanotechnology, geopolymer

Procedia PDF Downloads 113

Authors: Jingya Liu, Yue Wu, Jiabin Luo

Abstract:

This work investigates an intermodal transportation system for delivering goods from a Regional Distribution Centre to supermarkets on the Isle of Wight (IOW) via the port of Southampton or Portsmouth in the UK. We consider this integrated logistics chain as a 3-echelon transportation system. In such a system, there are two types of transport methods used to deliver goods across the Solent Channel: one is accompanied transport, which is used by most supermarkets on the IOW, such as Spar, Lidl and Co-operative food; the other is unaccompanied transport, which is used by Aldi. Five transport scenarios are studied based on different transport modes and ferry routes. The aim is to determine an optimal delivery plan for supermarkets of different business scales on IOW, in order to minimise the total running cost, fuel consumptions and carbon emissions. The problem is modelled as a vehicle routing problem with time windows and solved by genetic algorithm. The computing results suggested that accompanied transport is more cost efficient for small and medium business-scale supermarket chains on IOW, while unaccompanied transport has the potential to improve the efficiency and effectiveness of large business scale supermarket chains.

Keywords: genetic algorithm, intermodal transport system, Isle of Wight, optimization, supermarket

Procedia PDF Downloads 369

Authors: Kofi Nkonkonya Mpuangnan, Samantha Govender, Hlengiwe Romualda Mhlongo

Abstract:

Educational leaders are skilled architects crafting a vibrant environment where growth, creativity, and adaptability can flourish within schools. Their journey is one of transformation, urging them to explore administrative strategies that align seamlessly with evolving educational models and cater to the specific needs of students, educators, and stakeholders. Through this committed effort to innovate, they seek to enhance the effectiveness and influence of educational systems, paving the way for a more inclusive and forward-thinking educational environment. In this context, the authors explored the concept of transforming educational leadership with administrative strategies in alignment with the following research objectives. To find the strategies that can be adopted by transformation leaders to promote effective administrative practices in an educational setting and to explore the roles of educational leaders in promoting collaboration in education. To find answers to these questions, a systematic literature review underpinned by the transformational leadership model was adopted. Therefore, concepts integrated from a variety of outlets, including academic journals, conference proceedings, and reports found within SCOPUS, WoS, and IBSS databases. A search was aided using specific themes like innovative administrative practices, the roles of educational leaders, and interdisciplinary approaches to administrative practices. The process of conducting the search adhered to the five-step framework, which was subjected to inclusion and exclusion of studies. It was found that transformational leadership, agile methodologies, employee wellbeing, seminars and workshops could foster a culture of innovation and creativity among teachers and staff to transform administrative practices in education settings. It was recommended that professional development programs be organized periodically for educational leaders in educational institutions to help them revitalize their knowledge and skills in educational administration.

Keywords: educational leadership, innovative strategies, administrative practices, professional development, stakeholder engaement, student outcome

Procedia PDF Downloads 93

Authors: J. W. Mbogani, B. A. Bunyasi

Abstract:

The special skills for five students in the vocational class in Kakamega program for Hearing impaired were identified within one term period of the Kenyan education system. Three students were identified as having a liking for tailoring. The remaining two students did not show any interest in any vocational subject. The three students were attached to two professionals in practicing general tailors within the school vicinity for scaffolding purposes. The students were allowed to attend general classes under the normal curriculum and were withdrawn after eleven in the morning for tailoring classes. The students were then monitored with the guideline of a checklist. The purpose of monitoring was to establish whether the behavior of the students reflected a motivated student. It was established that two of them improved in their school attendance in terms of regularity, punctuality and responsibility accomplishment. The third student ended up attending only tailoring classes. The socialization aspect of the two students improved a lot. They also tended to identify more with the teachers than their fellow students. We recommend that learners with special needs in education should be subjected to the normal curriculum. They may benefit more and attain a skill that could help them economically. Further study should also be done to in several institutions involving learners in other classes.

Keywords: general tailoring, scaffolding, term, vocational class

Procedia PDF Downloads 139

Authors: Vural Erdogan

Abstract:

We created two-dimensional hexagonal cellular automata to obtain complexity by using simple rules same as Conway’s game of life. Considering the game of life rules, Wolfram's works about life-like structures and John von Neumann's self-replication, self-maintenance, self-reproduction problems, we developed 2-states and 3-states hexagonal growing algorithms that reach large populations through random initial states. Unlike the game of life, we used six neighbourhoods cellular automata instead of eight or four neighbourhoods. First simulations explained that whether we are able to obtain sort of oscillators, blinkers, and gliders. Inspired by Wolfram's 1D cellular automata complexity and life-like structures, we simulated 2D synchronous, discrete, deterministic cellular automata to reach life-like forms with 2-states cells. The life-like formations and the oscillators have been explained how they contribute to initiating self-maintenance together with self-reproduction and self-replication. After comparing simulation results, we decided to develop the algorithm for another step. Appending a new state to the same algorithm, which we used for reaching life-like structures, led us to experiment new branching and fractal forms. All these studies tried to demonstrate that complex life forms might come from uncomplicated rules.

Keywords: hexagonal cellular automata, self-replication, self-reproduction, self- maintenance

Procedia PDF Downloads 152

Authors: Saugata Bose, Ritambhra Korpal

Abstract:

The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

Procedia PDF Downloads 357

Authors: David Broussard

Abstract:

This review article delves into the realm of marine conservation finance, addressing the inadequacies in current financial streams from the private sector and the underutilization of existing financing mechanisms. The study emphasizes the emerging field of “blue finance”, which contributes to economic growth, improved livelihoods, and marine ecosystem health. The financial burden of marine conservation projects typically falls on philanthropists and governments, contrary to the polluter-pays principle. However, the private sector’s increasing commitment to NetZero and growing environmental and social responsibility goals prompts the need for alternative funding sources for marine conservation initiatives like marine protected areas. The article explores the potential of utilizing several financing mechanisms like carbon credits and other forms of payment for ecosystem services in the marine context, providing a solution to the lack of private funding for marine conservation. The methodology employed involves a systematic and quantitative approach, combining traditional review methods and elements of meta-analysis. A comprehensive search of the years 2000 - 2023, using relevant keywords on the Scopus platform, resulted in a review of 252 articles. The temporal evolution of blue finance studies reveals a significant increase in annual articles from 2010 to 2022, with notable peaks in 2011 and 2022. Marine Policy, Ecosystem Services, and Frontiers in Marine Science are prominent journals in this field. While the majority of articles focus on payment for ecosystem services, there is a growing awareness of the need for holistic approaches in conservation finance. Utilizing bibliometric techniques, the article showcases the dominant share of payment for ecosystem services in the literature with a focus on blue carbon. The classification of articles based on various criteria, including financing mechanisms and conservation types, aids in categorizing and understanding the diversity of research objectives and perspectives in this complex field of marine conservation finance.

Keywords: biodiversity offsets, carbon credits, ecosystem services, impact investment, payment for ecosystem services

Procedia PDF Downloads 84

Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

Abstract:

In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

Procedia PDF Downloads 446

Authors: M. L. Mangena, N. Mokoena, K. Rashamuse, M. G. Tlou

Abstract:

Tertiary alcohol ester (TAE) hydrolases are a group of esterases (EC 3.1.1.-) that catalyze the kinetic resolution of TAEs and as a result, they are sought-after for the production of optically pure tertiary alcohols (TAs) which are useful as building blocks for number biologically active compounds. What sets these enzymes apart is, the presence of a GGG(A)X-motif in the active site which appears to be the main reason behind their activity towards the sterically demanding TAEs. The genome of Pseudomonas syringae pv. maculicola (Psm) comprises a multitude of genes that encode esterases. We therefore, hypothesize that some of these genes encode TAE hydrolases. In this study, Psm was screened for TAE hydrolase activity using the linalyl acetate (LA) plate assay and a positive reaction was observed. As a result, the genome of Psm was screened for esterases with a GGG(A)X-motif using the motif search tool and two potential TAE hydrolase genes (PsmEST1 and 2, 1100 and 1000bp, respectively) were identified, PsmEST1 was amplified by PCR and the gene sequenced for confirmation. Analysis of the sequence data with the SingnalP 4.1 server revealed that the protein comprises a signal peptide (22 amino acid residues) on the N-terminus. Primers specific for the gene encoding the mature protein (without the signal peptide) were designed such that they contain NdeI and XhoI restriction sites for directional cloning of the PCR products into pET28a. The gene was expressed in E. coli JM109 (DE3) and the clones screened for TAE hydrolase activity using the LA plate assay. A positive clone was selected, overexpressed and the protein purified using nickel affinity chromatography. The activity of the esterase towards LA was confirmed using thin layer chromatography.

Keywords: hydrolases, tertiary alcohol esters, tertiary alcohols, screening, Pseudomonas syringae pv., maculicola genome, esterase activity, linalyl acetate

Procedia PDF Downloads 355

Authors: Tae Gwan Kim, Hyun Kyu Cho, Young Hoon Lee, Young Chul Park

Abstract:

Foam monitors are devices that are installed on cargo tank decks to suppress cargo area fires in oil tankers or hazardous chemical ship cargo ships. In general, the main design parameter of the foam monitor is the distance of the projection through the foam monitor. In this study, the relationship between flow characteristics and projection distance, depending on the shape was examined. Numerical techniques for fluid analysis of foam monitors have been developed for prediction. The flow pattern of the fluid varies depending on the shape of the flow path of the foam monitor, as the flow losses affecting projection distance were calculated through numerical analysis. The basic shape of the foam monitor was an L shape designed by N Company. The modified model increased the length of the flow path and used the S shape model. The calculation result shows that the L shape, which is the basic shape, has a problem that the force is directed to one side and the vibration and noise are generated there. In order to solve the problem, S-shaped model, which is a change model, was used. As a result, the problem is solved, and the projection distance from the nozzle is improved.

Keywords: CFD, foam monitor, projection distance, moment

Procedia PDF Downloads 343

Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

Abstract:

Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

Procedia PDF Downloads 197

Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

Abstract:

The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

Procedia PDF Downloads 73

Authors: Ramita Vongrat, Pornsri Sapsrithong, Manit Nithitanakul

Abstract:

In this work, blends of polyamide 6 (PA6) and polybutylene terephthalate (PBT) were successfully prepared. The effect of epoxidized natural rubber (ENR-25) and n butyl acrylate glycidyl methacrylate ethylene (EBa-GMA) as a compatibilizer on properties of PA6/PBT blends was also investigated by varying amount of ENR-50 and EBa-GMA, i.e., 0, 0.1, 0.5, 5 and 10 phr. All blends were prepared and shaped by using twin-screw extruder at 230 °C and injection molding machine, respectively. All test specimens were characterized by phase morphology, impact strength, tensile, flexural properties, and hardness. The results exhibited that phase morphology of PA6/PBT blend without compatibilizer was incompatible. This could be attributed to poor interfacial adhesion between the two polymers. SEM micrographs showed that the addition of ENR-25 and EBa-GMA improved the compatibility of PA6/PBT blends. With the addition of ENR-50 as a compatibilizer, the uniformity and the maximum reduction of dispersed phase size were observed. Additionally, the results indicate that, as the amount of ENR-25 increased, and EBa-GMA increased, the mechanical properties, including stress at the peak, tensile modulus, and izod impact strength, were also improved.

Keywords: EBa-GMA, epoxidized natural rubber-25, polyamide 6, polybutylene terephthalate

Procedia PDF Downloads 169

Authors: Mahadev Bhise, Nabanita Majumder

Abstract:

Recent studies have found association between air pollutants and mortality, particularly how concentration of air pollutant explains under-five mortality across the countries. Thus, the present study evaluates the relationship between Carbon dioxide (CO2) emission and under-five mortality, while controlling other well-being determinant of Under-five mortality in 100 countries using panel unbalanced cross sectional data. We have used PCSE and GMM model for the period 1990-2011 to meet our objectives. Our findings suggest that, the positive relationship between lagged periods of carbon dioxide and under-five mortality; the percentage of rural population with access of improved water is negatively associated with under-five mortality, while in case of urban population with access of improved water, is positively related to under-five mortality. Access of sanitation facility, food production index, GDP per capita, and concentration of urban population have significant negative impact on under-five mortality. Further, total fertility rate is significantly associated (positive) with under-five mortality which indicates relative change in fertility is related to relative change in under-five mortality.

Keywords: arbon dioxide (CO2), under-five mortality (0q5), gross domestic product (GDP), urban population, food production, panel corrected standard errors (PCSE), generalized method of moments (GMM)

Procedia PDF Downloads 309

Authors: Muhammad Yousaf, Shoaib Usman

Abstract:

Numerical studies were conducted using Lattice Boltzmann Method (LBM) to study the natural convection in a square cavity in the presence of roughness. An algorithm basedon a single relaxation time Bhatnagar-Gross-Krook (BGK) model of Lattice Boltzmann Method (LBM) was developed. Roughness was introduced on both the hot and cold walls in the form of sinusoidal roughness elements. The study was conducted for a Newtonian fluid of Prandtl number (Pr) 1.0. The range of Ra number was explored from 103 to 106 in a laminar region. Thermal and hydrodynamic behavior of fluid was analyzed using a differentially heated square cavity with roughness elements present on both the hot and cold wall. Neumann boundary conditions were introduced on horizontal walls with vertical walls as isothermal. The roughness elements were at the same boundary condition as corresponding walls. Computational algorithm was validated against previous benchmark studies performed with different numerical methods, and a good agreement was found to exist. Results indicate that the maximum reduction in the average heat transfer was16.66 percent at Ra number 105.

Keywords: Lattice Boltzmann method, natural convection, nusselt number, rayleigh number, roughness

Procedia PDF Downloads 527

Authors: Gloria Patricia Manurung

Abstract:

Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

Procedia PDF Downloads 229

Authors: John Onyima, Ikechukwu Ezepue

Abstract:

Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

Procedia PDF Downloads 307

Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

Abstract:

Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

Procedia PDF Downloads 397

Authors: Ramandeep Kaur, Kamaljit Kaur, Preeti Ahluwalia, Poonam A. Sachdev

Abstract:

Bread is an ideal vehicle to impart bioactive compounds to the consumers in a convenient manner. This study evaluated bread enriched with red sweet pepper powder (RSP) at 2, 4, 6, 8, 10% and compared to control bread (without RSP). The bread crumbs were assayed for bioactive, physical, nutritional, textural, color, and sensory properties. Bread supplemented with RSP improved its color, nutritional, and bioactive properties. The low moisture content and increased hardness were observed at higher levels of RSP. Color intensity (expressed as L*, a*, b* values) of bread with 2 and 4% RSP were lower than those of high levels, and the same trend was observed for protein, fibre and ash content of bread. Significant (p < 0.05) increases were recorded for bioactive compounds such as total phenols (0.145 to 235 mg GAE/g), antioxidant activity (56% to 78%) and flavonoids (0.112 to 0.379 mg/g) as the level of powder increased. Bread enriched with 8% RSP showed improved sensory profile as compared to control, whereas a further increase in RSP decreased the sensory and textural properties. Thus, RSP act as a natural colorant and functional food that enhanced the functional and nutritional properties of bread and can be used to customize bread for specific health needs.

Keywords: breads, bioactive compounds, red sweet pepper powder, sensory scores

Procedia PDF Downloads 158

Authors: Deepak Nathiya1, Ramesh Roop Rai, Pratima Singh1, Preeti Raj1, Supriya Suman, Balvir Singh Tomar

Abstract:

Background: Sarcopenia is a catabolic state in liver cirrhosis (LC), accelerated with a breakdown of skeletal muscle to release amino acids which adversely affects survival, health-related quality of life, and response to any underlying disease. The primary objective of the study was to investigate the long-term effect of branched-chain amino acids (BCAA) supplementations on parameters associated with improved prognosis in sarcopenic patients with LC, as well as to evaluate its impact on cirrhotic-related events. Methods: We carried out a 24 week, single-center, randomized, open-label, controlled, two cohort parallel-group intervention trial comparing the efficacy of BCAA against lactoalbumin (L-ALB) on 106 sarcopenic liver cirrhotics. The BCAA (intervention) group was treated with 7.2 g BCAA per whereas, the lactoalbumin group was also given 6.3 g of L-Albumin. The primary outcome was to assess the impact of BCAA on parameters of sarcopenia: muscle mass, muscle strength, and physical performance. The secondary outcomes were to study combined survival and maintenance of liver function changes in laboratory and clinical markers in the duration of six months. Results: Treatment with BCAA leads to significant improvement in sarcopenic parameters: muscle strength, muscle function, and muscle mass. The total cirrhotic-related complications and cumulative event-free survival occurred fewer in the BCAA group than in the L-ALB group. Prognostic markers also improved significantly in the study. Conclusion: The current clinical trial demonstrated that long-term BCAAs supplementation improved sarcopenia and prognostic markers in patients with advanced liver cirrhosis.

Keywords: sarcopenia, liver cirrhosis, BCAA, quality of life

Procedia PDF Downloads 136

Authors: Fu Lin

Abstract:

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

Procedia PDF Downloads 140

Authors: Anis A. Ansari, M. Kamil

Abstract:

The development of 3D printing technology has allowed the manufacturing industry to create parts with a high degree of automation, increased design freedom, and improved mechanical performance. Fused deposition modelling (FDM) is a 3D printing technique in which successive layers of thermoplastic polymer are deposited and controlled to create a three-dimensional product. In this study, process parameters such as nozzle temperature and printing speed were chosen to investigate their effects on hardness properties. 3D printed specimens were fabricated by an FDM 3D printer from Polylactic acid (PLA) polymer. After analysis, it was observed that the hardness property is much influenced by print speed and nozzle temperature parameters. Maximum hardness was achieved at higher print speed which indicates that the Shore D hardness is directly proportional to the print speed. Moreover, at higher print speed, it has no significant dependence on the nozzle temperature. Hardness is also influenced by nozzle temperature, though to a lesser extent. The hardness slightly lowers when the nozzle temperature is raised from 190 to 210 oC, but due to improved bonding between each raster, a further rise in temperature increases the hardness property.

Keywords: 3D printing, fused deposition modeling (FDM), polylactic acid (PLA), print speed, nozzle temperature, hardness property

Procedia PDF Downloads 96

Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

Abstract:

The complexes of transition metals with various organic ligands have been extensively studied as models of some important pharmaceutical molecules. It was found that biological properties of different substituted organic molecules are improved when they are complexed by different metals. Therefore, it is of great importance for the development of coordination chemistry to explore the assembly of functional organic ligands with metal ion and to investigate the relationship between the structure and property. In the present work, we have bioassayed the antibacterial potency of benzimidazoles and their metal salts (Cu or Zn) against yeast Sarcina lutea. In order to validate our in vitro study, we performed in silico studies using molecular docking software. The investigated compounds and their metal complexes (Cu, Zn) showed good to moderate inhibitory activity against Sarcina lutea. In silico docking studies of the synthesized compounds suggested that complexed benzimidazoles have a greater binding affinity and improved antibacterial activity in comparison with non-complexed ligands. These results are part of the CMST COST Action No. 1105 "Functional metal complexes that bind to biomolecules".

Keywords: organometallic complexes, benzimidazoles, chemometric design, Sarcina lutea

Procedia PDF Downloads 343

Authors: Kouzi Katia

Abstract:

This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

Procedia PDF Downloads 345

Authors: Ajay R, Rammohan B, Sridhar K S S, Gurusharan N

Abstract:

The objective of the work is to develop a numerical method to solve the inverse mode shape problem by determining the cross-sectional area of a structure for the desired mode shape via the vibration response study of the humerus bone, which is in the form of a cantilever beam with anisotropic material properties. The humerus bone is the long bone in the arm that connects the shoulder to the elbow. The mode shape is assumed to be a higher-order polynomial satisfying a prescribed set of boundary conditions to converge the numerical algorithm. The natural frequency and the mode shapes are calculated for different boundary conditions to find the cross-sectional area of humerus bone from Eigenmode shape with the aid of the inverse mode shape algorithm. The cross-sectional area of humerus bone validates the mode shapes of specific boundary conditions. The numerical method to solve the inverse mode shape problem is validated in the biomedical application by finding the cross-sectional area of a humerus bone in the human arm.

Keywords: Cross-sectional area, Humerus bone, Inverse mode shape problem, Mode shape

Procedia PDF Downloads 128

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

Procedia PDF Downloads 201

Authors: Cyril Kaplan

Abstract:

26 participants played 4 EEG neurofeedback (NF) games encouraged to find their strategies to control the specific NF parameter. Mixed method analysis of performance in the games and post-session interviews led to the identification of states of consciousness that correlated with success in the game. We found that increase in left frontal beta activity was facilitated by evoking interest in observed surroundings, by wondering what is happening behind the window or what lies in a drawer in front.

Keywords: EEG neurofeedback, states of consciousness, frontal beta activity, mixed methods

Procedia PDF Downloads 141

Authors: Ahmed S. Afifi, Ahmed Magdy

Abstract:

Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

Procedia PDF Downloads 106

Authors: Maher Ali Rusho, Sudipta Halder

Abstract:

The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency.

Keywords: algorithm optimisation, memory management, load balancing, performance profiling, asynchronous programming.

Procedia PDF Downloads 12