Search results for: time driven activity based costing

Authors: Noopur Anand, Amit Gupta

Abstract:

Sewage divers are the workers involved in cleaning and maintaining of the sewerage lines by entering through manholes. The working conditions of sewage divers in India are more challenging than in other countries. Though India has legal acts framed to ensure protection of the divers called 'The Prohibition of Employment of Manual Scavengers and their Rehabilitation Act, 2013' by Ministry of Law and Justice but these are usually not implemented. Further, the divers are not even provided with safety gear like mask, eyewear, helmet, safety suit, safety belt, gloves, and shoes because of lack of initiative among the agencies/individuals employing them and low awareness of importance of the protective gear amongst workers themselves. Several reports and studies show that because of the non-availability of safety gear, many sewage workers get infected and many of them retire even before attaining superannuation and about 70% of the manual scavengers die while on job. Though there are neoprene safety suits, costing only a few thousand, available in the market which can suffice but is beyond the buying capacity of the sewage diver and agencies/individuals employing them are reluctant to procure it as they find it expensive. In absence of safety suits, the divers get exposed to the parasites, viruses, and disease-causing germs present in the sewage. The research was undertaken with the objective of developing an affordable safety-suit which would save diver from coming into direct contact with the sewage thus preventing infections and diseases. The low cost of the suit may also motivate their employers to procure them for sewage divers.

Keywords: manhole cleaner, manual scavenger, prototype, low-cost safety-suit

Procedia PDF Downloads 154

Authors: Mohammad Amin Mozaheb, Jalal Farzaneh Dehkordi, Khojasteh Hosseinzadehpilehvar

Abstract:

English Language Teaching (ELT) is widely promoted across the world. ELT textbooks play pivotal roles in the mentioned process. Since biases of authors have been an issue of continuing interest to analysts over the past few years, the present study seeks to analyze an ELT textbook using Critical Discourse Analysis (CDA). To obtain the goal of the study, the listening section of a book called World English 3 (new edition) has been analyzed in terms of the cultures and countries mentioned in the listening section of the book using content-based analysis. The analysis indicates biases towards certain cultures. Moreover, some countries are shown as rich and powerful countries, while some others have been shown as poor ones without considering the history behind them.

Keywords: ELT, textbooks, critical discourse analysis, World English

Procedia PDF Downloads 213

Authors: Hsien-Tsen Wang

Abstract:

Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

Procedia PDF Downloads 77

Authors: Hayet El Kolli, Hocine Laouer

Abstract:

Bunium in the world comprises about 50 to 100 species, mostly distributed in: Algeria, Italy, Pakistan, Iran, and South Africa. Bunium species have several uses like: Bunium persicum which is commonly used as antispasmodic, carminative, anti-obesity and lactogage. This plant have been widely used as an additive in food stuff such as in bread cooking, rice and yoghurt for its carminative, anti-dyspepsia and antispasmodic effect. The B. paucifolium oil has a wide spectrum of action against moulds, yeast and bacteria. The chemical compositions of Bunium incrassatum and Bunium alpinum essential oils were carry out by GC and GC/MS. Therefore, antibacterial activity of two oils was investigated by disk diffusion method against Pseudomonas aeruginosa ATCC 27853, Escherichia coli ATCC 25922, Salmonella typhimurium ATCC 1331, Staphylococcus aureus ATCC 25923, Klebsiella pneumoniae ATCC 700603, Bacillus cereus ATCC 10876, Enterococcus faecalis ATCC 49452, Lysteria monocytogenes ATCC 15313, Citrobacter freundii ATCC 8090, Proteus mirabilis ATCC 35659. A moderate antibacterial activity was found. In conclusion, it is found that essential oils of the two species are rich in sesquiterpens and other oxygenated compounds. These compounds have been reported to show bactericidal activity and the presence of phenolic compounds makes them useful antioxidants so that results confirm some ethnopharmacologique applications of these two oils of Bunium.

Keywords: Bunium alpinum, Bunium incrassatum, apiaceae, essential oil, sesquiterpens, phenols, antibacterial, antioxidant activities

Procedia PDF Downloads 358

Authors: M. Mehani, N. Salhi, T. Valeria, S. Ladjel

Abstract:

Red River Gum (Eucalyptus camaldulensis) is a tree of the genus Eucalyptus widely distributed in Algeria and in the world. The value of its aromatic secondary metabolites offers new perspectives in the pharmaceutical industry. This strategy can contribute to the sustainable development of our country. Preliminary tests performed on the essential oil of Eucalyptus camendulensis showed that this oil has antibacterial activity vis-à-vis the bacterial strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium graminearum). The culture medium used was nutrient broth Muller Hinton. The interaction between the bacteria and the essential oil is expressed by a zone of inhibition with diameters of MIC indirectly expression of. And we used the PDA medium to determine the fungal activity. The extraction of the aromatic fraction (essentially oil- hydrolat) of the fresh aerian part of the Eucalyptus camendulensis was performed by hydrodistillation. The average essential oil yield is 0.99%. The antimicrobial and fungal study of the essential oil and hydrosol showed a high inhibitory effect on the growth of pathogens.

Keywords: essential oil, Eucalyptus camendulensis, bacteria and fungi, red river gum

Procedia PDF Downloads 217

Authors: Shivankar Agrawal, Indira Sarangthem

Abstract:

Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus (MRSA) remains one of the major causes of healthcare-associated and community-onset infections worldwide. Hence the search for non-toxic natural compounds having antibacterial activity has intensified for future drug development. The exploration of less studied niches of Earth can highly increase the possibility to discover novel bioactive compounds. Therefore, in this study, the cultivable fraction of fungi from the sediments of natural hot springs has been studied to mine potential fungal candidates with antibacterial activity against the human pathogen Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus. We isolated diverse strains of thermophilic fungi from a collection of samples from sediment. Following a standard method, we isolated a promising thermophilic fungus strain IBSD19, identified as Acrophialophora levis, possessing the potential to produce an anti-Staphylococcus aureus agent. The growth conditions were optimized and scaled to fermentation, and its produced extract was subjected to chemical extraction. The ethyl acetate fraction was found to display significant activity against Staphylococcus aureus and MRSA with a minimum inhibitory concentration (MIC) of 0.5 mg/ml and 4 mg/ml, respectively. The cell membrane integrity assay and SEM suggested that the fungal metabolites cause bacteria clustering and further lysis of the cell.

Keywords: antibacterial activity, antioxidant, fungi, Staphylococcus aureus, MRSA, thermophiles

Procedia PDF Downloads 122

Authors: Brenda Thean I. Lim, Safurah Jaafar

Abstract:

Augmented reality (AR) in the healthcare industry has been gaining popularity in recent years, principally in areas of medical education, patient care and digital health solutions. One of the drivers in deciding to invest in AR technology is the potential economic benefits it could bring for patients and healthcare providers, including the pharmaceutical and medical technology sectors. Works of literature have shown that the benefits and impact of AR technologies have left trails of achievements in improving medical education and patient health outcomes. However, little has been published on the economic impact of AR in healthcare, a very resource-intensive industry. This systematic review was performed on studies focused on the benefits and impact of AR in healthcare to appraise if they meet the founded quality criteria so as to identify relevant publications for an in-depth analysis of the economic impact assessment. The literature search was conducted using multiple databases such as PubMed, Cochrane, Science Direct and Nature. Inclusion criteria include research papers on AR implementation in healthcare, from education to diagnosis and treatment. Only papers written in English language were selected. Studies on AR prototypes were excluded. Although there were many articles that have addressed the benefits of AR in the healthcare industry in the area of medical education, treatment and diagnosis and dental medicine, there were very few publications that identified the specific economic impact of technology within the healthcare industry. There were 13 publications included in the analysis based on the inclusion criteria. Out of the 13 studies, none comprised a systematically comprehensive cost impact evaluation. An outline of the cost-effectiveness and cost-benefit framework was made based on an AR article from another industry as a reference. This systematic review found that while the advancements of AR technology is growing rapidly and industries are starting to adopt them into respective sectors, the technology and its advancements in healthcare were still in their early stages. There are still plenty of room for further advancements and integration of AR into different sectors within the healthcare industry. Future studies will require more comprehensive economic analyses and costing evaluations to enable economic decisions for or against implementing AR technology in healthcare. This systematic review concluded that the current literature lacked detailed examination and conduct of economic impact and benefit analyses. Recommendations for future research would be to include details of the initial investment and operational costs for the AR infrastructure in healthcare settings while comparing the intervention to its conventional counterparts or alternatives so as to provide a comprehensive comparison on impact, benefit and cost differences.

Keywords: augmented reality, benefit, economic impact, healthcare, patient care

Procedia PDF Downloads 184

Authors: Yan Zhang

Abstract:

Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 371

Authors: Duy M. P. Vo, Cornelia Sennewald, Gerald Hoffmann, Chokri Cherif

Abstract:

The development of solutions to improve the resistance of buildings to short-term dynamic loads, particularly impact load, is driven by the urgent demand worldwide on securing human life and critical infrastructures. The research training group GRK 2250/1 aims to develop mineral-bonded composites that allow the fabrication of thin-layered strengthening layers providing available concrete members with enhanced impact resistance. This paper presents the development of 3D woven wire cellular structures that can be used as innovative reinforcement for targeted composites. 3D woven wire cellular structures are truss-like architectures that can be fabricated in an automatized process with a great customization possibility. The specific architecture allows this kind of structures to have good load bearing capability and forming behavior, which is of great potential to give strength against impact loading. An appropriate combination of topology and material enables an optimal use of thin-layered reinforcement in concrete constructions.

Keywords: 3D woven cellular structures, ductile behavior, energy absorption, fiber-based reinforced concrete, impact resistant

Procedia PDF Downloads 284

Authors: Robert Lenzie

Abstract:

Transcranial electrical stimulation (tES) is significant in the research literature. However, the effects of tES on brain activity are still poorly understood at the surface level, the Brodmann Area level, and the impact on neural networks. Using a method like electroencephalography (EEG) in conjunction with tES might make it possible to comprehend the brain response and mechanisms behind published observed alterations in more depth. Using a method to directly see the effect of tES on EEG may offer high temporal resolution data on the brain activity changes/modulations brought on by tES that correlate to various processing stages within the brain. This paper provides unpublished information on a cutting-edge methodology that may reveal details about the dynamics of how the human brain works beyond what is now achievable with existing methods.

Keywords: tACS, frequency, EEG, optimal

Procedia PDF Downloads 63

Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

Abstract:

New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: information visualization, visual analytics, text mining, visual text analytics tools, big data visualization

Procedia PDF Downloads 386

Authors: Asif Zaman, Moinul Islam Zaber, Amin Ahsan Ali

Abstract:

In recent years of industrialization, the South Asian countries are being affected by air pollution due to a severe increase in fine particulate matter 2.5 (PM₂.₅). Among them, Bangladesh is one of the most polluting countries. In this paper, statistical analyses were conducted on the time series of PM₂.₅ from various districts in Bangladesh, mostly around Dhaka city. Research has been conducted on the dynamic interactions and relationships between PM₂.₅ concentrations in different zones. The study is conducted toward understanding the characteristics of PM₂.₅, such as spatial-temporal characterization, correlation of other contributors behind air pollution such as human activities, driving factors and environmental casualties. Clustering on the data gave an insight on the districts groups based on their AQI frequency as representative districts. Seasonality analysis on hourly and monthly frequency found higher concentration of fine particles in nighttime and winter season, respectively. Cross correlation analysis discovered a phenomenon of correlations among cities based on time-lagged series of air particle readings and visualization framework is developed for observing interaction in PM₂.₅ concentrations between cities. Significant time-lagged correlations were discovered between the PM₂.₅ time series in different city groups throughout the country by cross correlation analysis. Additionally, seasonal heatmaps depict that the pooled series correlations are less significant in warmer months, and among cities of greater geographic distance as well as time lag magnitude and direction of the best shifted correlated particulate matter time series among districts change seasonally. The geographic map visualization demonstrates spatial behaviour of air pollution among districts around Dhaka city and the significant effect of wind direction as the vital actor on correlated shifted time series. The visualization framework has multipurpose usage from gathering insight of general and seasonal air quality of Bangladesh to determining the pathway of regional transportation of air pollution.

Keywords: air quality, particles, cross correlation, seasonality

Procedia PDF Downloads 98

Authors: Arleta Rifati Nixha, Mustafa Arslan, Adem Ergün, Nahit Gencer

Abstract:

Polyphenol oxidase (PPO), sometimes referred to as phenol oxidase, catecholase, phenolase, catechol oxidase, or even tyrosinase, is considered to be an o-dipenol. PPO (EC 1.14.18.1), a multifunctional copper containing enzyme, is widely distributed in nature. It catalyzes two distinct reactions of melanin synthesis: a hydroxylation of monophenols to o-diphenols (monophenolase activity) and an oxidation of o-diphenols to o-quinones (diphenolase activity), both using molecular oxygen. Additionaly, investigation demonstrated that various dermatological disorders, such as age spots and freckle, were caused by the accumulation of an excessive level of epidermal pigmentation. Tyrosinase has also been linked to Parkinson’s and other neurodegenerative diseases. Nitrogen heterocycles have received a great deal of attention in the literature because of biological properties. Especially, among these heterocyclic systems, pyridine containing compounds have been the subject of expanding research efforts in heteroaromatic and biological chemistry. The pyrido [2,3-d] pyrimidine heterocycles, which are those annelated to a pyrimidine ring, are important because of their wide range of biological and pharmaceutical applications (i.e., bronchodilators, vasodilators) and their anti-allergic, cardiotonic, antihypertensive, and hepatoprotective activities. In this study series of 12 new carbazole substituted pyridopyrimidine urea(thiourea) derivatives were synthesized and evaluated effect on PPO. Additionally, we presented structure-activity relationship analyses and theoretical calculations of the compounds.

Keywords: carbazole, pyridopyrimidine, urea, thiourea, tyrosinase inhibitors

Procedia PDF Downloads 418

Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

Abstract:

Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

Procedia PDF Downloads 54

Authors: Hyunjoo Choi, Jeonghun Nam, Chae Seung Lim

Abstract:

Acoustomicrofluidics has gained much attention due to the advantages, such as noninvasiveness and easy integration with other miniaturized systems, for clinical and biological applications. However, a limitation of acoustomicrofluidics is the complicated and costly fabrication process of electrodes. In this study, we propose a low-cost and lithography-free device using Lamb wave for blood analysis. Using a Lamb wave, calcium ion-removed blood plasma and coagulation reagents can be rapidly mixed for blood coagulation test. Due to the coagulation process, the viscosity of the sample increases and the viscosity change can be monitored by internal acoustic streaming of microparticles suspended in the sample droplet. When the acoustic streaming of particles stops by the viscosity increase is defined as the coagulation time. With the addition of calcium ion at 0-25 mM, the coagulation time was measured and compared with the conventional index for blood coagulation analysis, prothrombin time, which showed highly correlated with the correlation coefficient as 0.94. Therefore, our simple and cost-effective Lamb wave-based blood analysis device has the powerful potential to be utilized in clinical settings.

Keywords: acoustomicrofluidics, blood analysis, coagulation, lamb wave

Procedia PDF Downloads 326

Authors: Qiang Zhang, Xiaojian Hu

Abstract:

In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 150

Authors: Eva Čáslavová, Andrej Višněvský

Abstract:

This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.

Keywords: dimensions, brand personality, ice hockey, international sports event, marketing

Procedia PDF Downloads 222

Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

Abstract:

This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

Procedia PDF Downloads 88

Authors: Sengul Uysal, Gokhan Zengin, Abdurrahman Aktumsek, Sukru Karatas

Abstract:

In this research, we determined the total sugar content, fatty acid compositions and α-amylase and α-glucosidase inhibitory activity of methanolic and water extracts of nine different fruit tree leaves. α-amylase and α-glycosidase inhibitory activity were determined by using Caraway-Somogyi–iodine/potassium iodide (IKI) and 4-nitrophenyl-α-D-glucopyranoside (PNPG) as substrate, respectively. Total sugar content of the nine different fruit tree leaves varies from 281.02 mg GE/g (glucose equivalents) to 643.96 mg GE/g. Methanolic extract from avocado leaves had the strongest in α-amylase and α-glucosidase inhibitory activity, 69.21% and 96.26 %, respectively. Fatty acid composition of nine fruit tree leaves was characterized by GC (gas chromatography) and twenty-four components were identified. Among the tested fruit tree leaves, the main component was linolenic acid (49.09%). The level of essential fatty acids are over 50% in mulberry, grape and loquat leaves. PUFAs (polyunsaturated fatty acids) were major group of fatty acids present in oils of mulberry, fig, pomegranate, grape, and loquat leaves. Therefore, these oils can be considered as a good source of polyunsaturated fatty acids. Furthermore, avocado can be regarded as a new source for diabetic therapies.

Keywords: fatty acid compositions, total sugar contents, α-amylase, α-glucosidase, fruit tree leaves, Turkey

Procedia PDF Downloads 469

Authors: Michael Russelle S. Alvarez, Noel S. Quiming, Francisco M. Heralde

Abstract:

This study aims to: a) obtain ethanolic (95% EtOH) and aqueous extracts of Selaginella elmeri, Christella dentata, Elatostema sinnatum, Curculigo capitulata, Euphorbia hirta, Murraya koenigii, Alpinia speciosa, Cymbopogon citratus, Eucalyptus globulus, Jatropha curcas, Psidium guajava, Gliricidia sepium, Ixora coccinea and Capsicum frutescens and screen them for larvicidal activities against Aedes aegypti (Linn.) and Aedes albopictus (Skuse) larvae; b) to fractionate the most active extract and determine the most active fraction; c) to determine the larvicidal properties of the most active extract and fraction against by computing their percentage mortality, LC50, and LC90 after 24 and 48 hours of exposure; and d) to determine the nature of the components of the active extracts and fractions using phytochemical screening. Ethanolic (95% EtOH) and aqueous extracts of the selected plants will be screened for potential larvicidal activity against Ae. aegypti and Ae. albopictus using standard procedures and 1% malathion and a Piper nigrum based ovicide-larvicide by the Department of Science and Technology as positive controls. The results were analyzed using One-Way ANOVA with Tukey’s and Dunnett’s test. The most active extract will be subjected to partial fractionation using normal-phase column chromatography, and the fractions subsequently screened to determine the most active fraction. The most active extract and fraction were subjected to dose-response assay and probit analysis to determine the LC50 and LC90 after 24 and 48 hours of exposure. The active extracts and fractions will be screened for phytochemical content. The ethanolic extracts of C. citratus, E. hirta, I. coccinea, G. sepium, M. koenigii, E globulus, J. curcas and C. frutescens exhibited significant larvicidal activity, with C. frutescens being the most active. After fractionation, the ethyl acetate fraction was found to be the most active. Phytochemical screening of the extracts revealed the presence of alkaloids, tannins, indoles and steroids. A formulation using talcum powder–300 mg fraction per 1 g talcum powder–was made and again tested for larvicidal activity. At 2 g/L, the formulation proved effective in killing all of the test larvae after 24 hours.

Keywords: larvicidal activity screening, partial purification, dose-response assay, capsicum frutescens

Procedia PDF Downloads 316

Authors: M. D. Stelescu, E. Manaila, G. Pelin, M. Georgescu, M. Sonmez

Abstract:

This paper presents studies on the development and characterization of nanocomposites based on ethylene-propylene terpolymer rubber (EPDM), chlorobutyl rubber (IIR-Cl) and organically modified montmorillonite (OMMT). Mixtures were made containing 0, 3 and 6 phr (parts per 100 parts rubber) OMMT, respectively. They were obtained by melt intercalation in an internal mixer - Plasti-Corder Brabender, in suitable blending parameters, at high temperature for 11 minutes. Curing agents were embedded on a laboratory roller at 70-100 ºC, friction 1:1.1, processing time 5 minutes. Rubber specimens were obtained by compression, using a hydraulic press at 165 ºC and a pressing force of 300 kN. Curing time, determined using the Monsanto rheometer, decreases with the increased amount of OMMT in the mixtures. At the same time, it was noticed that mixtures containing OMMT show improvement in physical-mechanical properties. These types of nanocomposites may be used to obtain rubber seals for the space application or for other areas of application.

Keywords: chlorobutyl rubber, ethylene-propylene-diene terpolymers, montmorillonite, rubber seals, space application

Procedia PDF Downloads 156

Authors: Nadia A. Mohamed, Magdy W. Sabaa, Ahmed H. H. El-Ghandour, Marwa M. Abdel-Aziz, Omayma F. Abdel-Gawad

Abstract:

Eighteen carboxymethyl chitosan (CMCh) schiff bases and their reduced derivatives have been synthesized. They were characterized by spectral analyses (FT-IR and H1-NMR) and scanning electron microscopy observation. Their antibacterial activities against Streptococcus pneumoniae (RCMB 010010), Bacillis subtilis (RCMB 010067), as Gram positive bacteria and Escherichia coli (RCMB 010052) as Gram negative bacteria and the antifungal activity against Aspergillus fumigatus (RCMB 02568), Geotricum candidum (RCMB 05097), and Candida albicans (RCMB 05031) were examined using agar disk diffusion method. The results demonstrate how the antibacterial and the antifungal activity are clearly affected by both the nature and position of the substituent groups in the aryl ring of the prepared derivatives. CMCh-4-nitroBenz Schiff base and its reduced form show higher antimicrobial activity comparing with other para substituted derivatives. CMCh-4-nitroBenz Schiff base: 18.3, 17, and 15.6 mm against Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 16.2, 17.3, and 16.4 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively. CMCh-4-nitroBenz reduced form: 19.5, 18.7, and 16.2 mm against Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 17.5, 19.5, and 17.4 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively. Also CMCh-3-bromoBenz show good results; CMCh-3-bromoBenz schiff base: 19.2, 16.9, and 14.6 mm Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 18.4, 17.6, and 15.9 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively.

Keywords: chitosan, schiff base, minimum inhibition concentration, antimicrobial activity

Procedia PDF Downloads 436

Authors: Mulugeta Shegaze, Mekitie Wondafrash, Alemayehu A. Alemayehu, Shikur Mohammed, Zewdu Shewangezaw, Mukerem Abdo, Gebresilasea Gendisha

Abstract:

Background: The 2004 World Health Assembly called for specific actions to halt the overweight and obesity epidemic that is currently penetrating urban populations in the developing world. Adolescents require particular attention due to their vulnerability to develop obesity and the fact that adolescent weight tracks strongly into adulthood. However, there is scarcity of information on the modifiable risk factors to be targeted for primary intervention among urban adolescents in Ethiopia. This study was aimed at determining the magnitude and risk factors of overweight and obesity among high school adolescents in Addis Ababa. Methods: An institution-based cross-sectional study was conducted in February and March 2014 on 456 randomly selected adolescents from 20 high schools in Addis Ababa city.  Demographic data and other risk factors of overweight and obesity were collected using self-administered structured questionnaire, whereas anthropometric measurements of weight and height were taken using calibrated equipment and standardized techniques. The WHO STEPS instrument for chronic disease risk was applied to assess dietary habit and physical activity. Overweight and obesity status was determined based on BMI-for-age percentiles of WHO 2007 reference population. Results: The prevalence rates of overweight, obesity, and overall overweight/ obesity among high school adolescents in Addis Ababa were 9.7% (95%CI = 6.9-12.4%), 4.2% (95%CI = 2.3-6.0%), and 13.9% (95%CI = 10.6-17.1%), respectively. Overweight/obesity prevalence was highest among female adolescents, in private schools, and in the higher wealth category. In multivariable regression model, being female [AOR(95%CI) = 5.4(2.5,12.1)], being from private school [AOR(95%CI) = 3.0(1.4,6.2)], having >3 regular meals [AOR(95%CI) = 4.0(1.3,13.0)], consumption of sweet foods [AOR(95%CI) = 5.0(2.4,10.3)] and spending >3 hours/day sitting [AOR(95%CI) = 3.5(1.7,7.2)] were found to increase overweight/ obesity risk, whereas high Total Physical Activity level [AOR(95%CI) = 0.21(0.08,0.57)] and better nutrition knowledge [AOR(95%CI) = 0.160.07,0.37)] were found protective. Conclusions: More than one in ten of the high school adolescents were affected by overweight/obesity with dietary habit and physical activity are important modifiable risk factors. Well-tailored nutrition education program targeting lifestyle change should be initiated with more emphasis to female adolescents and students in private schools.

Keywords: adolescents, NCDs, overweight, obesity

Procedia PDF Downloads 291

Authors: Sherif M. Hafez, Remon F. Aziz, May S. A. Elalim

Abstract:

Project managers today rely on scheduling tools based on the Critical Path Method (CPM) to determine the overall project duration and the activities’ float times which lead to greater efficiency in planning and control of projects. CPM was useful for scheduling construction projects, but researchers had highlighted a number of serious drawbacks that limit its use as a decision support tool and lacks the ability to clearly record and represent detailed information. This paper discusses the drawbacks of CPM as a scheduling technique and presents a modified critical path method (CPM) model which is called critical path segments (CPS). The CPS scheduling mechanism addresses the problems of CPM in three ways: decomposing the activity duration of separated but connected time segments; all relationships among activities are converted into finish–to–start relationship; and analysis and calculations are made with forward path. Sample cases are included to illustrate the shortages in CPM, CPS full analysis and calculations are explained in details, and how schedules can be handled better with the CPS technique.

Keywords: construction management, scheduling, critical path method, critical path segments, forward pass, float, project control

Procedia PDF Downloads 341

Authors: Golnaz Moghimi, Alireza Afsharghotli, Alireza Rezaei

Abstract:

Construction waste has been gradually increased as a result of upsizing construction projects which are occurred within the lifecycle of buildings. Since waste management is a major priority and has profound impacts on the volume of waste generated in construction stage, the majority of efforts have been attempted to reuse, recycle and reduce waste. However, there is still room to study on lack of sufficient knowledge about waste management in construction industry. This paper intends to provide an insight into the effect of project management knowledge areas on waste management solely on construction stage. To this end, a survey among Iranian building construction industry contractors was conducted to identify the effectiveness of project management knowledge areas on three jobsite key factors including ‘Site activity’, ‘Training’, and ‘Awareness’. As a result, four management disciplines were identified as most influential ones on amount of construction waste. These disciplines were Project Cost Management, Quality Management, Human Resource Management, and Integration Management. Based on the research findings, a new model was presented to develop effective construction waste strategies.

Keywords: awareness, PMBOK, site activity, training, waste management

Procedia PDF Downloads 326

Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

Abstract:

Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors, thus refining marketing strategies and enhancing overall customer experiences. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. The analysis of customer data through BI unveils patterns and trends, informing product development, marketing campaigns, and customer service initiatives aimed at enriching experiences and knowledge. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence, business intelligence, and innovation in product and service offerings. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster innovation. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. The chosen method was justified for its efficacy in handling large sample sizes. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational innovation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Organizations equipped with cutting-edge BI tools are better positioned to devise strategies informed by precise insights into customer needs and behaviors. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. Companies leveraging BI demonstrate adeptness in identifying market opportunities guiding the development of novel products and services. The substantial impact of CEK-DI on PSI highlights the crucial role of customer experiences in driving organizational innovation. Firms actively integrating customer insights into their innovation processes are more likely to create offerings aligned with customer expectations, fostering higher levels of product and service innovation. Additionally, the positive and significant effect of MI on CEK-DI underscores the critical role of market insights in shaping innovative strategies. While the relationship between MI and PSI is positive, a slightly weaker significance level indicates a nuanced association, suggesting that while MI contributes to innovation, other factors may also influence the innovation landscape, warranting further exploration. In conclusion, the study underscores the essential role of intelligence capabilities, particularly artificial intelligence, in driving innovation, emphasizing the necessity for organizations to leverage market and customer intelligence for effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of innovation, influencing experiential customer knowledge and shaping organizational strategies and practices, ultimately enhancing overall customer experiences and organizational performance.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

Procedia PDF Downloads 48

Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

Abstract:

Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

Procedia PDF Downloads 142

Authors: Lorena G. Calvo, Marta Lores, Trinidad de Miguel

Abstract:

Natural extracts containing high polyphenolic concentration possess antibacterial and antifungal activity. The present research characterizes a hydro-organic extract with a high polyphenolic content as an antimicrobial candidate. As a result of this composition, the extract showed pronounced bioactivities with potential uses in agricultural, veterinary, pharmaceutical, and cosmetic industries. Polyphenol compounds were extracted by using hydro-organic solvent mixtures from the shrub Cytisus scoparius. The in vitro antimicrobial activity of this extract was evaluated on Gram-positive and Gram-negative bacteria and the fungus Candida albicans. Microbial species investigated, Bacillus cereus, Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa, are causing agents of several human and animal diseases. The extract showed activity against all tested species. So, it could be used for the development of biocides to control a wide range of pathogenic agents and contribute to the creation of economic and eco-friendly alternatives to antibiotics.

Keywords: antimicrobial properties, antioxidant properties, Cytisus scoparius, polyphenolic extract

Procedia PDF Downloads 129

Authors: Vanessa Matias Leite, Jandira Guenka Palma, Flávio Henrique de Oliveira

Abstract:

This paper presents a model-oriented development approach to software development in the Model-View-Controller (MVC) architectural standard. This approach aims to expose a process of extractions of information from the models, in which through rules and syntax defined in this work, assists in the design of the initial model and its future conversions. The proposed paper presents a syntax based on the natural language, according to the rules agreed in the classic grammar of the Portuguese language, added to the rules of conversions generating models that follow the norms of the Object Management Group (OMG) and the Meta-Object Facility MOF.

Keywords: BNF Syntax, model driven architecture, model-view-controller, transformation, UML

Procedia PDF Downloads 378

Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

Abstract:

Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

Procedia PDF Downloads 13