Search results for: data access

Authors: Aisyiyah Fauziah Rahmah

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Generally, an urban city has a rapid growth, it has frequent a variety of problems, especially of convenience in public space usage. The density of population in urban areas and the high activity is also indicated as a cause of urban resident lifestyle for the worse in social relationships and allow for the stress. Streets and green space (parks) are the only public space in a residential area which is used as a place to build social activity, to meet and interact with the other housing dweller. The high level of activity and social interaction that occurs will affect the spatial arrangement. It can be effected the space structures in housing more complex. Ease in access to public space is the reason many dweller prefer doing social activities there. Hillier in Carmona et al (2003) explains that the pattern and intensity of movement of individuals is influenced by the configuration of space, even the space structure can be regarded as the single most influential determinant of movements in the space. Whyte in Zhang and Lawson (2009) also suggest some factors such as seats, trees, water and legibility of space encourage people to stay in public outdoor space. Furthermore this activities can attract more activities. Villa Bukit Tidar is a housing in Lowokwaru District which highest number of people in Malang City, so social activity is also high there. It has natural and recreational concept and provided with view of Malang City from heights. This potential is able to attract the people who live there to stay in public outdoor space and doing activities there. From this study we can find whether the ease of access to public space and visual satisfaction of Villa Bukit Tidar housing affect the usage of public space. This study was carried out by observing the streets pattern and plot pattern to know the configuration space of Villa Bukit Tidar housing through values of connectivity and integrity by resulting from space sintax analysis. Distributing questionnaires also carried out to determine the level of satisfaction and importance perception of visual condition in the public space in Villa Bukit Tidar housing through Important Performance Analysis (IPA). Results of this research indicated that the public spaces in Villa Bukit Tidar housing who has high connectivity and integrity is considered to be visually satisfied and it has a higher public space usage than has low connectivity and integrity are considered to be visually dissatisfied.

Keywords: configuration space, visual perception, social activities, public space usage

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Authors: Ahmed Fradi

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In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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Authors: R. K. Pateriya, Jyoti Bharti

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This paper presents an approach for data hiding methods which provides a secret communication between sender and receiver. The data is hidden in gray-scale images and the boundary of gray-scale image is used to store the mapping information. In this an approach data is in ASCII format and the mapping is in between ASCII value of hidden message and pixel value of cover image, since pixel value of an image as well as ASCII value is in range of 0 to 255 and this mapping information is occupying only 1 bit per character of hidden message as compared to 8 bit per character thus maintaining good quality of stego image.

Keywords: ASCII value, cover image, PSNR, pixel value, stego image, secret message

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Authors: Olusola Bamisile, Oluwaseun Ayodele, Mustafa Dagbasi

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The main objective of this research is to optimize the power produced by a solar chimney wind turbine. The cut out speed and the maximum possible production are considered while performing the optimization. Solar chimney is one of the solar technologies that can be used in rural areas at cheap cost. With over 50% of rural areas still yet to have access to electricity. The OptimTool in MATLAB is used to maximize power produced by the turbine subject to certain constraints. The results show that an optimized turbine produces about ten times the power of the normal turbine which is 111 W/h. The rest of the research discuss in detail solar chimney power plant and the optimization simulation used in this study.

Keywords: solar chimney, optimization, wind turbine, renewable energy systems

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Authors: Gunasekaran Raja, Kottilingam Kottursamy, Rajakumar Arul, Ramkumar Jayaraman, Krithika Sairam, Lakshmi Ravi

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The synchronization server maintains a dynamically changing cache, which contains the data items which were requested and collected by the mobile node from the server. The order and presence of tuples in the cache changes dynamically according to the frequency of updates performed on the data, by the server and client. To synchronize, the data which has been modified by client and the server at an instant are collected, batched together by the type of modification (insert/ update/ delete), and sorted according to their update frequencies. This ensures that the DCASH (Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y synchronizing Mobile Database Systems) gives priority to the frequently accessed data with high usage. The optimal memory management algorithm is proposed to manage data items according to their frequency, theorems were written to show the current mobile data activity is reverse Y in nature and the experiments were tested with 2g and 3g networks for various mobile devices to show the reduced response time and energy consumption.

Keywords: mobile databases, synchronization, cache, response time

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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Authors: Maximilian Winkens, Matthias Goerke

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The state-oriented maintenance enables the preventive intervention before the failure of a component and guarantees avoidance of expensive breakdowns. Because the timing of the maintenance is defined by the component’s state, the remaining service life can be exhausted to the limit. The basic requirement for the state-oriented maintenance is the ability to define the component’s state. New potential for this is offered by gentelligent components. They are developed at the Corporative Research Centre 653 of the German Research Foundation (DFG). Because of their sensory ability they enable the registration of stresses during the component’s use. The data is gathered and evaluated. The methodology developed determines the current state of the gentelligent component based on the gathered data. This article presents this methodology as well as current research. The main focus of the current scientific work is to improve the quality of the state determination based on the life-cycle data analysis. The methodology developed until now evaluates the data of the usage phase and based on it predicts the timing of the gentelligent component’s failure. The real failure timing though, deviate from the predicted one because the effects from the production phase aren’t considered. The goal of the current research is to develop a methodology for state determination which considers both production and usage data.

Keywords: state-oriented maintenance, life-cycle data, gentelligent component, preventive intervention

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Authors: Loide Sambo

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Achieving energy security has, in the past few decades, become one of the main goals in the security agenda of every country around the world. For Southern African Countries (SAC) the aim is not different, yet these countries face a particular challenge in the pursuit of their energy security. More than just secure enough energy sources to fuel their industrial and societal needs, SAC have as well to ensure that they trade their rich energy resources to the global market in a way that promotes and safeguards their economic development objectives. Considering the relevance of this issue to the SAC, the present paper explores the possibility of these countries to achieve energy security through regional cooperation, under the Southern Africa Development Community (SADC) platform. It discusses the challenges and opportunities for advancing energy security in this region through cooperation. After analyzing the data through the documentary analysis method, it was found that regional cooperation among SAC to improve energy security is not effective since cooperation in the region is still very susceptible to a plethora of challenges, such as political instability, lack of development of infrastructure and expertise, lack of good governance, lack of sense of cohesiveness, and most important lack of political commitment. It was also found that significant commitment on regional cooperation had been centered on the electricity sub-sector due to the region’s huge electricity deficit. Thus less commitment is dedicated to the development and policy harmonization of the other sub-sectors such as the one of natural gas and oil, for instance. Hence, it is recommended that the leadership of the SAC is fully committed to cooperate and harmonize the policies, the strategic plans, as well as the infrastructure concerning to all the natural energy resources and its respective sub-sectors. This would provide the SAC significant leverage to negotiate for the energy market access, ensuring that the region’s energy commodities are traded, while the countries themselves retain enough energy to sustain their economic growth and development, improving, therefore, their energy security.

Keywords: regional cooperation, energy security, economic development, political commitment

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Authors: Ahmed Abdolkhalig, Rastko Zivanovic

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This paper evaluates the Total Vector Error of an estimated Phasor as define in IEEE C37.118 standard within different medium access in Local Area Networks (LAN). Three different LAN models (CSMA/CD, CSMA/AMP, and Switched Ethernet) are evaluated. The Total Vector Error of the estimated Phasor has been evaluated for the effect of Nodes Number under the standardized network Band-width values defined in IEC 61850-9-2 communication standard (i.e. 0.1, 1, and 10 Gbps).

Keywords: phasor, local area network, total vector error, IEEE C37.118, IEC 61850

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: Sabri Serkan Güllüoğlu

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Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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Authors: Savin Phoeun

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Long time civil war, economic, infrastructure, social, and political structure were destroyed and everything starts from zero. Transport and communication are the key feature of the national economic growth, especially inland transport and other mode take a complementary role which supported by government and international organization both direct and indirect to private sector and small and medium size enterprises. The objectives of this study are to study the general characteristics, capacity and competitive KPIs of Cambodian Inland Transport Operators. Questionnaire and interview were formed from capacity and competitiveness key performance indicators to take apart in survey to Inland Transport Companies in Phnom Penh capital city of Cambodia. And descriptive statistics was applied to identify the data. The result of this study divided into three distinct sectors: 1). Management ability of transport operators – capital management, financial and qualification are in similar level which can compete between local competitors (moderated level). 2). Ability in operation: customer service providing is better but seemed in high cost operation because mostly they are in family size. 3). Local Cambodian Inland Transport Service Providers are able to compete with each other because they are in similar operation level while Thai competitors mostly higher than. The suggestion and recommendation from the result that inland transport companies should access to new technology, improve strategic management, build partnership (join/corporate) to be bigger size of capital and company in order to attract truthfulness from customers and customize the services to satisfy. Inland Service Providers should change characteristic from only cost competitive to cost saving and service enhancement.

Keywords: assessment, competitiveness, inland transport, operator

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Authors: Okanlawon Simon Ayorinde, Odunjo Oluronke Omolola, Fadamiro Joseph Akinlabi, Adedibu Afolabi Adebgite

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A road is a path established over land, especially prepared way between places for the use of pedestrian, riders, and vehicles: a hard surface built for vehicles to travel on. The social, economic and health importance of roads in any community and nation cannot be underestimated. Roads provide access to properties and they also provide mobility which is ability to transport goods and services from one place to another. In the residential zones of many indigenous cities in Nigeria, roads are usually blocked for social ceremonies. Road blocked for ceremonies as used in this study are a temporary barrier across a road, used to stop or hinder traffic from passing through to the other side. Social ceremonies that could warrant road blockage include marriage, child naming, funeral, celebration of life’s achievement, birthday anniversary etc. These activities are likely to generate environmental hazards and their attendant risks. The assessment of these hazards and risks in residential zones of indigenous cities in Nigeria becomes imperative. The study is focused on Ogbomoso, Oyo State, Nigeria. The town has two local government councils namely Ogbomoso North and Ogbomoso South. Urban tracts that are easy to identify are political wards in the absence of land use segregation, houses numbering and street naming. The wards that had residential having a minimum of 60% of their land use components were surveyed and fifteen out of twenty wards identified in the town were surveyed. The study utilized primary data collected through questionnaire administration The three major road categories (Trunk A-Federal; Trunk B- State; Trunk C-Local) were identified and trunk C-Local roads were purposively selected being the concern of this study because they are the ones often blocked for social activities. The major stakeholders interviewed and the respective sampling methods are residents (random and systematic), social ceremony organizers (purposive), government officials (purposive) and road users namely commercial motorists and commercial motor cyclists (random and incidental). Data analysis was mainly descriptive. Two indices to measure respondents’ perception were developed. These are ‘Hazard Severity Index’ (HSI) and ‘Relative Awareness Index’ (RAI).Thereafter, policy implications and recommendations were provided.

Keywords: road, residential zones, indigenous cities, blocked, social ceremonies

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Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Eszter Siposne Nandori

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The paper describes how the subjective interpretation of poverty changed during the COVID-19 pandemic. The results of data collection at the end of 2020 are compared to the results of a similar survey from 2019. The methods of systematic data collection are used to collect data about the beliefs of the population about poverty. The analysis is carried out in Borsod-Abaúj-Zemplén County, one of the most backward areas in Hungary. The paper concludes that poverty is mainly linked to material values, and it did not change from 2019 to 2020. Some slight changes, however, highlight the effect of the pandemic: poverty is increasingly seen as a generational problem in 2020, and another important change is that isolation became more closely related to poverty.

Keywords: Hungary, interpretation of poverty, pandemic, systematic data collection, subjective poverty

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Authors: Nicodemus M. J. Mbwambo, Yu-Shan Sun, Murali Sitaraman, Joan Krone

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This paper presents a generic data abstraction that captures a navigable tree position. The mathematical modeling of the abstraction encapsulates the current tree position, which can be used to navigate and modify the tree. The encapsulation of the tree position in the data abstraction specification avoids the use of explicit references and aliasing, thereby simplifying verification of (imperative) client code that uses the data abstraction. To ease the tasks of such specification and verification, a general tree theory, rich with mathematical notations and results, has been developed. The paper contains an example to illustrate automated verification ramifications. With sufficient tree theory development, automated proving seems plausible even in the absence of a special-purpose tree solver.

Keywords: automation, data abstraction, maps, specification, tree, verification

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Authors: Z. Ezzouine, A. Nakheli

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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

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Authors: Gilang Maulana, Dhika Rahma Qomariah, Yasin Fadil

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Purpose: This research meant to measure the magnitude of the influence of the quality of the presentation to the targeted audience perception in catching information presentation. Design/Methodology/Approach: This research uses a quantitative research method. The kind of data that uses in this research is the primary data. The population in this research are students the economics faculty of Semarang State University. The sampling techniques uses in this research is purposive sampling. The retrieving data uses questionnaire on 30 respondents. The data analysis uses descriptive analysis. Result: The quality of presentation influential positive against perception of the audience. This proved that the more qualified presentation will increase the perception of the audience. Limitation: Respondents were limited to only 30 people.

Keywords: quality of presentation, presentation, audience, perception, semarang state university

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

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Authors: Zegeye Abebe

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Background: Unhealthy diet is a major risk factor for CRC. This study assessed diet-related CRC burden from 1990 to 2021 in Organization for Economic Co-operation and Development (OECD) nations and estimated the burden until 2050 Methods: Data for OECD countries on diet-related CRC disability-adjusted life years (DALYs) and deaths were obtained from the Global Burden of Disease (GBD), 2021. The estimated annual percent change (EAPC) was calculated to analyse the CRC burden attributable to dietary factors. A generalised additive model with negative binomial distribution was used to predict the future burden of CRC attributable to dietary factors from 2021 to 2050. Results: In 2021, the age-standardised percentage of diet-related CRC DALYs and deaths were 39.1% (95% uncertainty interval (UI): 9.3, 61.3) and 39.0% (95% UI: 9.7, 60.9), respectively, in the OECD countries. Between 1990 and 2021, the age-standardised DALYs decreased from 185 to 129 per 100,000, and deaths decreased from 8 to 6 per 100,000 population for OECD countries. Similarly, the EAPC of rates showed a downward trend (EAPCdeaths = -1.26, and EAPCDALYs = -1.20). The estimated diet-related CRC DALYs and deaths are projected to increase to 4.1 million DALYs and 0.2 million deaths by 2050. There has been a downward trend in CRC deaths (EAPC = 1.33 for both sexes) and in DALYs (-0.90 for males and -1.0 for females) from 1990 to 2050. Conclusion: Diet-related CRC burden remains significant. Implementation of nutrition intervention programmes is necessary to promote access to affordable and nutritious foods and to raise awareness about the importance of a healthy diet in reducing CRC risk.

Keywords: colorectal cancer, dietary factor, age-standardized DALYs rate, age-standardized death rate, global burden of diseases

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Authors: Yuqing Chen, Ying Xu, Renfa Li

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The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

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Authors: Dagem Alemayehu, Samson Gebersilassie, Jan Frank

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Climate change is impacting nutrition through reducing food quantity and access, limiting dietary diversity, and decreased nutritional food content as well as strongly affecting seasonal rainfall in Ethiopia. Nevertheless, only a few data is available on the impacts of seasonality in Infant, and Young Child Feeding (IYCF) practices undernutrition among 6-23 months old children in different agro-ecological zones of poor resource settings of Ethiopia. Methods: Socio-demographic, anthropometry, and IYCF indicators were assessed in the harvest and lean seasons among children aged 6–23 months of age randomly selected from rural villages of lowland and midland agro-ecological zones. Results: Child stunting and underweight increased from prevalence of 32.8 % and 23.9 % (lowland &midland respectively) in the lean season to 36.1% and 33.8 % harvest seasons, respectively. The biggest increase in the prevalence of stunting and underweight between harvest and lean seasons was noted in the lowland zone. Wasting decreased from 11.6% lean to 8.5% harvest, with the biggest decline recorded in the midland zone. Minimum meal frequency, minimum acceptable diet, and poor dietary diversity increased considerably in harvest compared to a lean season in the lowland zone. Feeding practices and maternal age were predictors of wasting, while women's dietary diversity and children's age was a predictor of child dietary diversity in both seasons. Conclusion: There is seasonal variation in undernutrition and IYCF practices among children 6-23 months of age with more pronounced effect lowland agro-ecological zone.

Keywords: agroecology, seasonality, stunting, wasting

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Authors: Amir AlAmeeri, Mohamed Ibrahim

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Various data points are constantly being measured in the production system, and due to the nature of the wells, these data points, such as pressure, temperature, water cut, etc.., fluctuations are constant, which requires high frequency monitoring and collection. It is a very difficult task to analyze these parameters manually using spreadsheets and email. An automated system greatly enhances efficiency, reduce errors, the need for constant emails which take up disk space, and frees up time for the operator to perform other critical tasks. Various production data is being recorded in an oil field, and this huge volume of data can be seen as irrelevant to some, especially when viewed on its own with no context. In order to fully utilize all this information, it needs to be properly collected, verified and stored in one common place and analyzed for surveillance and monitoring purposes. This paper describes how data is recorded by different parties and departments in the field, and verified numerous times as it is being loaded into a repository. Once it is loaded, a final check is done before being entered into a production monitoring system. Once all this is collected, various calculations are performed to report allocated production. Calculated production data is used to report field production automatically. It is also used to monitor well and surface facility performance. Engineers can use this for their studies and analyses to ensure field is performing as it should be, predict and forecast production, and monitor any changes in wells that could affect field performance.

Keywords: automation, oil production, Cheleken, exploration and production (E&P), Caspian Sea, allocation, forecast

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Xiaogang Li, Jieqiong Miao

Abstract:

As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

Procedia PDF Downloads 462

Authors: Terungwa Simon Yange, Agana Moses A.

Abstract:

This paper studied steganography and designed a simplistic approach to a steganographic tool for hiding information in image files with the view of addressing the security challenges with data by hiding data from unauthorized users to improve its security. The Structured Systems Analysis and Design Method (SSADM) was used in this work. The system was developed using Java Development Kit (JDK) 1.7.0_10 and MySQL Server as its backend. The system was tested with some hypothetical health records which proved the possibility of protecting data from unauthorized users by making it secret so that its existence cannot be easily recognized by fraudulent users. It further strengthens the confidentiality of patient records kept by medical practitioners in the health setting. In conclusion, this work was able to produce a user friendly steganography software that is very fast to install and easy to operate to ensure privacy and secrecy of sensitive data. It also produced an exact copy of the original image and the one carrying the secret message when compared with each.

Keywords: steganography, cryptography, encryption, decryption, secrecy

Procedia PDF Downloads 267

Authors: Nushrat Khan, Mike Thelwall, Kayvan Kousha

Abstract:

Making research data openly accessible has been mandated by most funders over the last 5 years as it promotes reproducibility in science and reduces duplication of effort to collect the same data. There are evidence that articles that publicly share research data have higher citation rates in biological and social sciences. However, how and whether shared data is being reused is not always intuitive as such information is not easily accessible from the majority of research data repositories. This study aims to understand the practice of data citation and how data is being reused over the years focusing on biodiversity since research data is frequently reused in this field. Metadata of 38,878 datasets including citation counts were collected through the Global Biodiversity Information Facility (GBIF) API for this purpose. GBIF was used as a data source since it provides citation count for datasets, not a commonly available feature for most repositories. Analysis of dataset types, citation counts, creation and update time of datasets suggests that citation rate varies for different types of datasets, where occurrence datasets that have more granular information have higher citation rates than checklist and metadata-only datasets. Another finding is that biodiversity datasets on GBIF are frequently updated, which is unique to this field. Majority of the datasets from the earliest year of 2007 were updated after 11 years, with no dataset that was not updated since creation. For each year between 2007 and 2017, we compared the correlations between update time and citation rate of four different types of datasets. While recent datasets do not show any correlations, 3 to 4 years old datasets show weak correlation where datasets that were updated more recently received high citations. The results are suggestive that it takes several years to cumulate citations for research datasets. However, this investigation found that when searched on Google Scholar or Scopus databases for the same datasets, the number of citations is often not the same as GBIF. Hence future aim is to further explore the citation count system adopted by GBIF to evaluate its reliability and whether it can be applicable to other fields of studies as well.

Keywords: data citation, data reuse, research data sharing, webometrics

Procedia PDF Downloads 178