Search results for: negative data

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 163

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 151

Authors: K. W. Nam, B. J. Kim, S. J. Lee

Abstract:

Along with the development of network infrastructures, such as high-speed Internet and mobile environment, the explosion of multimedia data is expanding the range of multimedia services beyond voice and data services. Amid this flow, research is actively being done on the creation, management, and transmission of metadata on digital content to provide different services to users. This paper proposes a system for the insertion, storage, and retrieval of metadata about digital content. The metadata server with Binary XML was implemented for efficient storage space and retrieval speeds, and the transport data size required for metadata retrieval was simplified. With the proposed system, the metadata could be inserted into the moving objects in the video, and the unnecessary overlap could be minimized by improving the storage structure of the metadata. The proposed system can assemble metadata into one relevant topic, even if it is expressed in different media or in different forms. It is expected that the proposed system will handle complex network types of data.

Keywords: video, multimedia, metadata, editing tool, XML

Procedia PDF Downloads 165

Authors: Luís Pina

Abstract:

The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.

Keywords: GSM, marine biology, marine turtles, unstructured supplementary service data (USSD)

Procedia PDF Downloads 202

Authors: Daphne Sobolev, Niklas Voege

Abstract:

During the last three decades, consumer ethics perceptions have attracted the attention of a large number of researchers. Nevertheless, little is known about the effect of the cognitive and situational contexts of the decision on ethics judgments. In this paper, the interrelationship between consumers’ ethics perceptions, legality evaluations and mind-sets are explored. Legality evaluations represent the cognitive context of the ethical judgments, whereas mind-sets represent their situational context. Drawing on moral development theories and priming theories, it is hypothesized that both factors are significantly related to consumer ethics perceptions. To test this hypothesis, 289 participants were allocated to three mind-set experimental conditions and a control group. Participants in the mind-set conditions were primed for aggressiveness, politeness or awareness to the negative legal consequences of breaking the law. Mind-sets were induced using a sentence-unscrambling task, in which target words were included. Ethics and legality judgments were assessed using consumer ethics and internet ethics questionnaires. All participants were asked to rate the ethicality and legality of consumer actions described in the questionnaires. The results showed that consumer ethics and legality perceptions were significantly correlated. Moreover, including legality evaluations as a variable in ethics judgment models increased the predictive power of the models. In addition, inducing aggressiveness in participants reduced their sensitivity to ethical issues; priming awareness to negative legal consequences increased their sensitivity to ethics when uncertainty about the legality of the judged scenario was high. Furthermore, the correlation between ethics and legality judgments was significant overall mind-set conditions. However, the results revealed conflicts between ethics and legality perceptions: consumers considered 10%-14% of the presented behaviors unethical and legal, or ethical and illegal. In 10-23% of the questions, participants indicated that they did not know whether the described action was legal or not. In addition, an asymmetry between the effects of aggressiveness and politeness priming was found. The results show that the legality judgments and mind-sets interact with consumer ethics perceptions. Thus, they portray consumer ethical judgments as dynamical processes which are inseparable from other cognitive processes and situational variables. They highlight that legal and ethical education, as well as adequate situational cues at the service place, could have a positive effect on consumer ethics perceptions. Theoretical contribution is discussed.

Keywords: consumer ethics, legality judgments, mind-set, priming, aggressiveness

Procedia PDF Downloads 292

Authors: Jing Jin

Abstract:

The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

Procedia PDF Downloads 57

Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

Abstract:

Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

Procedia PDF Downloads 582

Authors: Pui Hong Chung, Wing Chi Ho, Jun Li, Cyrus Leung, Ek Yeoh

Abstract:

Background: Cigarette smoking is associated with poor tuberculosis (TB) outcomes in terms of progression of active TB, relapse of TB and TB-related mortality, but the association with latent tuberculosis infection (LTBI) is unclear. The systematic review conducted aimed at studying the association between active smoking and LTBI, and likelihood of dose-response relationship. Methods: Two independent reviewers searched three electronic databases comprising PudMed, Medline by EBSCOHOST, ExcerptaMedica Database (EMBASE), from inception up to 31st Dec 2015 for studies reporting data on current smoking and the LTBI with tuberculin skin test (TST) or interferon-γ release assays (IGRAs) results, comparing the odds ratios (ORs) of outcome measure of TST or IGRAs among current smokers with 95% confidence intervals (CI). Results: Seven studies were identified, including six cross-sectional studies and one longitudinal cohort study. The outcome measures from three studies were in TST, three studies in IGRAs and one for both tests. For TST, OR ranging from 1.39 to 3.40 (95% CI) with all studies shown positive association between cigarette smoking and LTBI. For IGRAs, OR ranging from 0.47 to 1.89 (95% CI) with one study shown the negative association that might be related to impaired interferon-gamma production in immunosuppressive persons. One identified study demonstrated positive dose-response relationship in TST result. Conclusions: Cigarette smoking is likely to be a risk factor of LTBI. There is the important implication for TB and tobacco control program to halt TB by empowering public health policy. Further study is also needed to provide more evidence of the dose-response model/relationship.

Keywords: latent tuberculosis infection, systematic review, active smoking, model

Procedia PDF Downloads 254

Authors: Mohammadreza Ashouri, Majid Bayatian

Abstract:

Analysis of fire data is a way for the implementation of any plan to improve the level of safety in cities. Such an analysis is able to reveal signs of changes in a given period and can be used as a measure of safety. The information of about 66,341 fires (from 2002 to 2012) released by Tehran Safety Services and Fire-Fighting Organization and data on the population and the number of households provided by Tehran Municipality and the Statistical Yearbook of Iran were extracted. Using the data, the fire changes, the rate of injuries, and mortality rate were determined and analyzed. The rate of injuries and mortality rate of fires per one million population of Tehran were 59.58% and 86.12%, respectively. During the study period, the number of fires and fire stations increased by 104.38% and 102.63%, respectively. Most fires (9.21%) happened in the 4th District of Tehran. The results showed that the recorded fire data have not been systematically planned for fire prevention since one of the ways to reduce injuries caused by fires is to develop a systematic plan for necessary actions in emergency situations. To determine a reliable source for fire prevention, the stages, definitions of working processes and the cause and effect chains should be considered. Therefore, a comprehensive statistical system should be developed for reported and recorded fire data.

Keywords: fire statistics, fire analysis, accident prevention, Tehran

Procedia PDF Downloads 177

Authors: Nam Don Kim, Jungho Moon, Tae Yun Chung

Abstract:

This paper proposes an Internet of Things (IoT) based virtualization platform for providing smart tourism services. The virtualization platform provides a consistent access interface to various types of data by naming IoT devices and legacy information systems as pathnames in a virtual file system. In the other words, the IoT virtualization platform functions as a middleware which uses the metadata for underlying collected data. The proposed platform makes it easy to provide customized tourism information by using tourist locations collected by IoT devices and additionally enables to create new interactive smart tourism services focused on the tourist locations. The proposed platform is very efficient so that the provided tourism services are isolated from changes in raw data and the services can be modified or expanded without changing the underlying data structure.

Keywords: internet of things (IoT), IoT platform, serviceplatform, virtual file system (VSF)

Procedia PDF Downloads 498

Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

Abstract:

3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

Procedia PDF Downloads 132

Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

Abstract:

Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

Procedia PDF Downloads 357

Authors: P. Senthil Kumari

Abstract:

Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

Procedia PDF Downloads 500

Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

Abstract:

The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

Procedia PDF Downloads 387

Authors: Ruth Hegarty, Noel Connaughton

Abstract:

Sustainability reporting has become a priority for many global multinational companies. This is associated with ever-increasing expectations from key stakeholders for companies to be transparent about their strategies, activities and management with regard to sustainability issues. The Global Reporting Initiative (GRI) encourages reporters to only provide information on the issues that are really critical in order to achieve the organisation’s goals for sustainability and manage its impact on environment and society. A key challenge for most reporting organisations is how to identify relevant issues for sustainability reporting and prioritise those material issues in accordance with company and stakeholder needs. A recent study indicates that most of the largest companies listed on the world’s stock exchanges are failing to provide data on key sustainability indicators such as employee turnover, energy, greenhouse gas emissions (GHGs), injury rate, pay equity, waste and water. This paper takes an indepth look at the approaches used by a select number of international sustainability leader corporates to identify key sustainability issues. The research methodology involves performing a detailed analysis of the sustainability report content of up to 50 companies listed on the 2014 Dow Jones Sustainability Indices (DJSI). The most recent sustainability report content found on the GRI Sustainability Disclosure Database is then compared with 91 GRI Specific Standard Disclosures and a small number of GRI Standard Disclosures. Preliminary research indicates significant gaps in the information disclosed in corporate sustainability reports versus the indicator content specified in the GRI Content Index. The following outlines some of the key findings to date: Most companies made a partial disclosure with regard to the Economic indicators of climate change risks and infrastructure investments, but did not focus on the associated negative impacts. The top Environmental indicators disclosed were energy consumption and reductions, GHG emissions, water withdrawals, waste and compliance. The lowest rates of indicator disclosure included biodiversity, water discharge, mitigation of environmental impacts of products and services, transport, environmental investments, screening of new suppliers and supply chain impacts. The top Social indicators disclosed were new employee hires, rates of injury, freedom of association in operations, child labour and forced labour. Lesser disclosure rates were reported for employee training, composition of governance bodies and employees, political contributions, corruption and fines for non-compliance. The reporting on most other Social indicators was found to be poor. In addition, most companies give only a brief explanation on how material issues are defined, identified and ranked. Data on the identification of key stakeholders and the degree and nature of engagement for determining issues and their weightings is also lacking. Generally, little to no data is provided on the algorithms used to score an issue. Research indicates that most companies lack a rigorous and thorough methodology to systematically determine the material issues of sustainability reporting in accordance with company and stakeholder needs.

Keywords: identification of key stakeholders, material issues, sustainability reporting, transparency

Procedia PDF Downloads 303

Authors: Masoud Charkhabi

Abstract:

We examine trade theory with this motivation. The full set of World Trade Organization data are organized into country-year pairs, each treated as a different entity. Topological Data Analysis reveals that among the 16 region and 240 region-year pairs there exists in fact a distinguishable group of region-period pairs. The generally accepted periods of shifts from dissimilar-dissimilar to similar-similar trade in goods among regions are examined from this new perspective. The period breaks are treated as cumulative and are flexible. This type of all-subsets analysis is motivated from computer science and is made possible with Lossy Compression and Graph Theory. The results question many patterns in similar-similar to dissimilar-dissimilar trade. They also show indications of economic shifts that only later become evident in other economic metrics.

Keywords: econometrics, globalization, network science, topological data, analysis, trade theory, visualization, world trade

Procedia PDF Downloads 367

Authors: Chia-Ching Sun, Li-Yin Chien, Chun-Ting Hsiao

Abstract:

Background: Appropriate gestation weight gain benefits pregnant women and their children; however, excessive weight gain could raise the risk of adverse health outcomes and chronicle diseases. Nevertheless, there is currently limited evidence on the effect of physical activities on pregnant women’s gestational weight gain. Purpose: This study aimed to explore the correlation between the level of physical activity and gestation weight gain during the second and third trimester of pregnancy. Methods: This longitudinal study enrolled 800 healthy pregnant women aged over 20 from six hospitals in northern Taiwan. Structured questionnaires were used to collect data twice for each participant during 14-27 and 28-40 weeks of gestation. Variables included demographic data, maternal health history, and lifestyle. The International Physical Activity Questionnaire-short form was used to measure the level of physical activity from walking and of moderate-intensity and vigorous-intensity before and during pregnancy. Weight recorded at prenatal checkups were used to calculate average weight gain in each trimester of pregnancy. T-tests, ANOVA, chi-squared tests, and multivariable logistic regression models were applied to determine the predicting factors for weight gain during the second and third trimester. Result: Participants who had achieved recommended physical activity level (150 minutes of moderate physical activity or 75 minutes of vigorous physical activity a week) before pregnancy (aOR=1.85, 95% CI=1.27-2.67) or who achieved recommended walking level (150 minutes a week) during the second trimester of pregnancy (aOR=1.43, 95% CI= 1.00-2.04) gained significantly more weight during the second trimester. Compared with those who did not reach recommended level of moderate-intensity physical activity (150 minutes a week), women who had reached that during the second trimester were more likely to be in the less than recommended weight gain group than in the recommended weight gain group (aOR=2.06, CI=1.06-4.00). However, there was no significant correlation between physical activity level and weight gain in the third trimester. Other predicting factors of excessive weight gain included education level which showed a negative correlation (aOR=0.38, CI=0.17-0.88), whereas overweight and obesity before pregnancy showed a positive correlation (OR=3.97, CI=1.23-12.78). Conclusions/implications for practice: Participants who had achieved recommended physical activity level before pregnancy significantly reduced exercise during pregnancy and gained excessive weight during the second trimester. However, women who engaged in the practice of physical activity as recommended could effectively control weight gain in the third trimester. Healthcare professionals could suggest that pregnant women who exercise maintain their pre-pregnancy level of physical activity, given activities requiring physical contact or causing falls are avoided. For those who do not exercise, health professionals should encourage them to gradually increase the level of physical activity. Health promotion strategies related to weight control and physical activity level achievement should be given to women before pregnancy.

Keywords: pregnant woman, physical activity, gestation weight gain, obesity, overweight

Procedia PDF Downloads 148

Authors: A. Chellil, A. Nour, S. Lecheb, H.Mechakra, A. Bouderba, H. Kebir

Abstract:

In this paper, the numerical study for the instability of a composite rotor is presented, under dynamic loading response in the harmonic analysis condition. The analysis of the stress which operates the rotor is done. Calculations of different energies and the virtual work of the aerodynamic loads from the rotor is developed. The use of the composite material for the rotor, offers a good Stability. Numerical calculations on the model develop of three dimensions prove that the damage effect has a negative effect on the stability of the rotor. The study of the composite rotor in transient system allowed to determine the vibratory responses due to various excitations.

Keywords: rotor, composite, damage, finite element, numerical

Procedia PDF Downloads 483

Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

Abstract:

The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

Procedia PDF Downloads 144

Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

Abstract:

This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

Procedia PDF Downloads 78

Authors: Zainab Atia, Hongwei He, Panagiotis Sarantopoulos

Abstract:

Over the past few years, firms have witnessed a massive increase in sophisticated algorithmic deployment, which has become quite pervasive in today’s modern society. With the wide availability of data for retailers, the ability to track consumers using algorithmic pricing has become an integral option in online platforms. As more companies are transforming their businesses and relying more on massive technological advancement, pricing algorithmic systems have brought attention and given rise to its wide adoption, with many accompanying benefits and challenges to be found within its usage. With the overall aim of increasing profits by organizations, algorithmic pricing is becoming a sound option by enabling suppliers to cut costs, allowing better services, improving efficiency and product availability, and enhancing overall consumer experiences. The adoption of algorithms in retail has been pioneered and widely used in literature across varied fields, including marketing, computer science, engineering, economics, and public policy. However, what is more, alarming today is the comprehensive understanding and focus of this technology and its associated ethical influence on consumers’ perceptions and behaviours. Indeed, due to algorithmic ethical concerns, consumers are found to be reluctant in some instances to share their personal data with retailers, which reduces their retention and leads to negative consumer outcomes in some instances. This, in its turn, raises the question of whether firms can still manifest the acceptance of such technologies by consumers while minimizing the ethical transgressions accompanied by their deployment. As recent modest research within the area of marketing and consumer behavior, the current research advances the literature on algorithmic pricing, pricing ethics, consumers’ perceptions, and price fairness literature. With its empirical focus, this paper aims to contribute to the literature by applying the distinction of the two common types of algorithmic pricing, dynamic and personalized, while measuring their relative effect on consumers’ behavioural outcomes. From a managerial perspective, this research offers significant implications that pertain to providing a better human-machine interactive environment (whether online or offline) to improve both businesses’ overall performance and consumers’ wellbeing. Therefore, by allowing more transparent pricing systems, businesses can harness their generated ethical strategies, which fosters consumers’ loyalty and extend their post-purchase behaviour. Thus, by defining the correct balance of pricing and right measures, whether using dynamic or personalized (or both), managers can hence approach consumers more ethically while taking their expectations and responses at a critical stance.

Keywords: algorithmic pricing, dynamic pricing, personalized pricing, price ethicality

Procedia PDF Downloads 85

Authors: Shekoufeh Behdad, Amirhossein Yadegari, Leila Ghodrati, Saman Yadegari

Abstract:

Context: Preoperative anxiety is a common psychological reaction experienced by all patients undergoing surgery. It can have negative effects on the patient's well-being and even impact surgical outcomes. Therefore, finding effective interventions to reduce preoperative anxiety is important in improving patient care. Research Aim: The aim of this study is to compare the effects of oral administration of zaleplon (5 mg) and alprazolam (0.5 mg) on preoperative anxiety levels in women undergoing gynecological abdominal surgery. Methodology: This study is a double-blind, randomized clinical trial conducted after receiving approval from the university's ethics committee and obtaining written informed consent from the patients. The night before the surgery, patients were randomly assigned to receive either 0.5 mg of alprazolam or 5 mg of zaleplon orally. Anxiety levels, measured using a 10-cm visual analog scale, and hemodynamic variables (blood pressure and heart rate) were assessed before drug administration and on the morning of the operation after the patient entered the pre-operation room. Findings: The study found that there were no significant differences in mean anxiety levels or hemodynamic variables before and after administration of either drug in both groups (P value > 0.05). This suggests that both 0.5 mg of alprazolam and 5 mg of zaleplon effectively reduce preoperative anxiety in women undergoing abdominal surgery without serious side effects. Theoretical Importance: This study contributes to the understanding of the effectiveness of alprazolam and zaleplon in reducing preoperative anxiety. It adds to the existing literature on pharmacological interventions for anxiety management, specifically in the context of gynecological abdominal surgery. Data Collection: Data for this study were collected through the assessment of anxiety levels using a visual analog scale and measuring hemodynamic variables, including systolic, diastolic, and mean arterial blood pressures, as well as heart rate. These measurements were taken before drug administration and on the morning of the surgery. Analysis Procedures: Statistical analysis was performed to compare the mean anxiety levels and hemodynamic variables before and after drug administration in the two groups. The significance of the differences was determined using appropriate statistical tests. Questions Addressed: This study aimed to answer the question of whether there are differences in the effects of alprazolam and zaleplon on preoperative anxiety levels in women undergoing gynecological abdominal surgery. Conclusion: The oral administration of both 0.5 mg of alprazolam and 5 mg of zaleplon the night before surgery effectively reduces preoperative anxiety in women undergoing abdominal surgery. These findings have important implications for the management of preoperative anxiety and can contribute to improving the overall surgical experience for patients.

Keywords: zaleplon, alprazolam, premedication, abdominal surgery

Procedia PDF Downloads 75

Authors: Olga Smilevska Spasova, Katerina Boshkovska, Gorica Popova, Mirjana Popovska

Abstract:

Introduction: Pneumonia is an infection of the pulmonary parenchyma. HPIV 3 is one of four viruses that is a member of the Paramyxoviridae family designated types 1-4 that have a nonsegmented, single-stranded RNA genome with a lipid-containing envelope. They are spread from the respiratory tract by aerosolized secretions or by direct contact with secretions. Type 3 is endemic and can cause serious illness in immunocompromised patients. Illness caused by parainfluenza occurs shortly after inoculation with the virus. The level of immunoglobulin A antibody in serum is the best predictor of susceptibility to infection. Streptococcus pneumonia or pneumococcus is a Gram-positive, spherical bacteria, usually found in pairs and it is a member of the genus Streptococcus. Streptococcus pneumonia resides asymptomatically in healthy carriers typically colonizing the respiratory tract, sinuses, and nasal cavity. In individuals with weaker immune systems like young infants, pneumococcal bacterium is the most common cause of community-acquired pneumonia in the world. Case Report: The aim is to present a case of lower respiratory tract infection in an infant caused by parainfluenza virus 3, S. pneumonia and undifferentiated gram-negative bacteria that was successfully treated. The infant is with a history of recurrent episodes of wheezing in the past 3mounts.Infant of 10months presents 2weeks before admittance with high fever, runny nose, and cough. The primary pediatrician prescribed oral cefpodoxime for 10days and inhaled salbutamol. Two days before admittance in hospital the infant with high fever, cough, and difficulty breathing. At admittance, infant is pale, anxious with rapid respirations, cough, wheezing and tachycardia. On auscultation: vesicular breathing sounds with high pitched wheezing and on the right coarse crackles. Investigations: Blood analysis: RBC: 4, 7 x1012L, WBC: 8,3x109L: Neut: 42.73% Lym: 41.57%, Hgb: 9.38 g/dl MCV: 62.7fl, MCH: 20.0pg MCHC: 31.8 g/dl RDW: 18.7% Plt-307.9 x109LCRP: 2,5mg/l, serum iron-7.92umol/l, O2sat-97% on blood gas analysis, puls-125/min.X-ray of chest with hyperinflationand right pericardial consolidation. Microbiological analysis of sputum sample is positive for undifferentiated gram-negative bacteria (colonizer)–resistant to cefotaxime, ampicillin, cefoxitin, sulfamet.+trimetoprim and sensitive to amikacin, gentamicin, and ciprofloxacin. Molecular multiplex RT-PCR for 19 viruses and multiplex PCR for 7 bacteria test for respiratory pathogens positive for Parainfluenza virus 3(Ct=22.73), Streptococcus pneumonia (Ct=26.75).IED: IgG-9.31g/l, IgA-0.351g/l, IgM-0.86g/l. Therapy: Treatment was started with inhaled salbutamol, intravenous antibiotic cefotaxime as well as systemic corticosteroids. On day 7 because of slow clinical resolution of chest auscultation findings and an etiologic clue with a positive sputum sample for resistant undifferentiated gram negative bacteria, a second intravenous antibiotic was administered amikacin. The infant is discharged on day 14 with resolution of clinical findings. Conclusion: Mixed co-infections with respiratory viruses and bacteria in immunocompromised infants are likely to lead to a more severe form of community acquired pneumonia that will need hospitalization.

Keywords: HPIV- 3, infant, pneumonia, S. pneumonia, x-ray chest

Procedia PDF Downloads 74

Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

Abstract:

Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

Procedia PDF Downloads 282

Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

Abstract:

The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

Procedia PDF Downloads 154

Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

Abstract:

Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

Procedia PDF Downloads 246

Authors: S. Ahmad, M. Rizwan, B. Ayub, S. Mehmood, P. Akhtar

Abstract:

This experiment was conducted to investigate the effect of supplementation of pure herbal blend on growth performance of boilers. One hundred and twenty birds were randomly distributed into 4 experimental units of 3 replicates (10 birds/replicate) as: negative control (basal diet), positive control (Lincomycin at the rate of 5g/bag), pure herbal blend at the rate of 150g/bag and pure herbal blend at the rate of 300g/bag. The data regarding weekly feed intake, body weight gain and feed conversion ratio were recorded, and fecal samples were collected at the end of starter and finisher phase for nutrient digestibility trial. The results of feed intake showed significant (P < 0.05) results in 1st (305g), 2nd (696.88g), 3rd (1046.9g) and 4th (1173.2g) week and feed conversion ratio indicated significant (P < 0.05) variations in 1st (2.54) and 4th (2.28) week of age. Also, both starter and finisher phase indicated significant (P < 0.05) differences among all treatment groups in feed intake (2023.4g) and (2302.6g) respectively. The statistical analysis indicated significant (P < 0.05) results in crop filling percentage (86.6%) after 2 hours of first feed supplementation. In case of nutrient digestibility trial, results showed significant (P < 0.05) values of crude protein and crude fat in starter phase as 69.65% and 56.62% respectively, and 69.57% and 48.55% respectively, in finisher phase. Based on overall results, it was concluded that the dietary inclusion of pure herbal blend containing neem tree leaves powder, garlic powder, ginger powder and turmeric powder increase the production performance of broilers.

Keywords: neem tree leave, garlic, ginger, herbal blend, broiler

Procedia PDF Downloads 201

Authors: Martin Kendra, Tomas Skrucany, Jaroslav Masek

Abstract:

The noise is one of the negative elements influencing the human health. This article is due to the measurement of noise emitted by road vehicle and its parts during the operation. Measurement was done in the interior of common passenger cars with a digital sound meter. The results compare the noise value in different cars with different body shape, which influences the driver’s health. Transport has considerable ecological effects, many of them detrimental to environmental sustainability. Roads and traffic exert a variety of direct and mostly detrimental effects on nature.

Keywords: driver, noise measurement, passenger road vehicle, road transport

Procedia PDF Downloads 443

Authors: Bensaid A., Mostephaoui T., Nedjai R.

Abstract:

A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 104

Authors: Nasir Ullah

Abstract:

Marketing strategies are important factors in the success of a company. Local pharmaceutical companies in Pakistan face several issues, such as low-level budgets, lack of skilled human resources, and challenges to competing with multinational competitors that have negative impacts on their success. However, still there exist local companies with great levels of success in the pharmaceutical sector. This study aims to evaluate the marketing strategies of successful local companies in the pharmaceutical sector of Khyber Pakhtunkhwa, Pakistan. The study employed a constructivist approach to know about successful strategies of the marketing managers that worked well. For this purpose, in-depth interviews were conducted with marketing managers of four pharmaceutical companies which were deemed as successful on the basis of their annual target achievements. Thematic analysis was conducted using Nvivo to devise major themes from the collected data. Four major themes or successful strategies were identified. These are i) share in the profit to marketing and sales staff, ii) invitation to the doctors for participation in free medical camps and health awareness seminars, iv) incentives for the Doctors and retailers, v) utilization of traditional capital (local social relationships) by the marketing officers. The study concludes that profit share to the employees, valuing doctors through their involvement and utilization of traditional capital are the successful marketing strategies of the successful pharmaceutical companies in the Pakhtun society of Pakistan. The study suggests hiring local staff that can utilize their traditional capital to influence doctors' decisions regarding the prescription of their medicine to the patients. The study also suggests profit share or increased bonuses to the marketing and sales staff as a measure of success.

Keywords: successful marketing strategies, pharmaceutical industry, traditional social capital, local companies

Procedia PDF Downloads 33