Search results for: imbalance data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24436

Search results for: imbalance data

24346 Government (Big) Data Ecosystem: Definition, Classification of Actors, and Their Roles

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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24345 Government Big Data Ecosystem: A Systematic Literature Review

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

Procedia PDF Downloads 196
24344 A Machine Learning Decision Support Framework for Industrial Engineering Purposes

Authors: Anli Du Preez, James Bekker

Abstract:

Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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24343 A Review: Recycled Materials Used in Construction

Authors: Oghenerukome Akponovo, Lynda I. Onyebuchukwu

Abstract:

Construction waste, along with that of many other industries, contributes significantly to the world's annual solid waste totals. Most of these materials, such as ash from rice hulls, slags, cement kiln dust, tire ash, plastic waste (PW), and silica fumes, end up in landfills or waterways. Some of them might even end up polluting the air from high in the atmosphere. It's sustainable, cheap, and environmentally friendly to recycle these items into new building supplies. When constructing a "Green" structure, the materials employed have the potential to either exacerbate environmental imbalance or maintain a stable ecosystem. The purpose of this research is to take stock of what is already known about recycling's potential in the construction industry and to identify its deficiencies. Therefore, this study systematically reviews the wide range of recycled materials that go into building construction. Recognizing that the construction industry's use of recycled materials has an influence on the environment and that investigating these materials may have a substantial economic impact if they were discovered

Keywords: building, construction, recycled materials, waste management

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24342 Providing Security to Private Cloud Using Advanced Encryption Standard Algorithm

Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

Abstract:

In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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24341 Understanding Water Governance in the Central Rift Valley of Ethiopia: Zooming into Transparency, Accountability, and Participation

Authors: Endalew Jibat, Feyera Senbeta, Tesfaye Zeleke, Fitsum Hagos

Abstract:

Water governance considers multi-sector participation beyond the state; and for sustainable use of water resources, appropriate laws, policies, regulations, and institutions needs to be developed and put in place. Water policy, a critical and integral instrument of water governance, guided water use schemes and ensures equitable water distribution among users. The Ethiopian Central Rift Valley (CRV) is wealthy of water resources, but these water resources are currently under severe strain owing to an imbalance in human-water interactions. The main aim of the study was to examine the state of water resources governance in the CRV of Ethiopia, and the impact of the Ethiopian Water Resources Management Policy on water governance. Key informant interviews (KII), focused group discussions, and document reviews were used to gather data for the study. The NVivo 11 program was used to organize, code, and analyze the data. The results revealed that water resources governance practices such as water allocation and apportionment, comprehensive and integrated water management plans, water resources protection, and conservation activities were rarely implemented. Water resources management policy mechanisms were not fully put in place. Lack of coherence in water policy implementation, absence of clear roles and responsibilities of stakeholders, absence of transparency and accountability in irrigation water service delivery, and lack of meaningful participation of key actors in water governance decision-making were the primary shortcomings observed. Factors such as over-abstraction, deterioration of buffer zone, and chemical erosion from surrounding farming have contributed to the reduction in water volume and quality in the CRV. These challenges have influenced aquatic ecosystem services and threaten the livelihoods of the surrounding communities. Hence, reforms relating to policy coherence and enforcement, stakeholder involvement, water distribution strategies, and the application of water governance principles must be given more emphasis.

Keywords: water resources, irrigation, governance, water allocation, governance principles, stakeholders engagement, central rift valley

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24340 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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24339 Investing the Employees Higher Quitting Intention at the Call Centers of Pakistan: A Reality or a Myth: A Case Study of Pakistan Telecommunication Sector

Authors: Naheed Malik, Marisa Smith

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This study has been undertaken as an attempt to explore the underlying reasons that cause higher employee turnover rates at the call centers of Pakistan. This research also aimed to examine the relationship among the job related variables such as job satisfaction, organizational commitment, supervisor support, self-esteem, organizational stressors (work overload, role ambiguity and work family conflict) and quitting inclination. A total of 340 call centers respondents filled the survey questionnaire. The data was analyzed through SPSS 19.0. Results reveal the significant relationship among the study variables and stress level contributing more towards employee penchant to leave the job. A significant amount of call centers employee have proclivity to quit from their jobs as soon as they would be able to find some other jobs with attractive compensation. The majority of the respondents were found to be unhappy and dissatisfied due to hectic schedule and imbalance between family and work. This research also highlighted the specific areas in which call centre management needs to emphasize deliberately that affect more sharply on employee leaving aptitude. This study also suggests some useful strategies for the well being of employees that can minimize their tendency of quitting and retention in the long run.

Keywords: call centers, stress, job satisfaction, organizational commitment, supervisor’s support, self esteem, employee turnover, employees’ intention to quit, customer service representative (CSRs)

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24338 Business Intelligence for Profiling of Telecommunication Customer

Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

Abstract:

Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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24337 Spino-Pelvic Alignment with SpineCor Brace Use in Adolescent Idiopathic Scoliosis

Authors: Reham H. Diab, Amira A. A. Abdallah, Eman A. Embaby

Abstract:

Background: The effectiveness of bracing on preventing spino-pelvic alignment deterioration in idiopathic scoliosis has been extensively studied especially in the frontal plane. Yet, there is lack of knowledge regarding the effect of soft braces on spino-pelvic alignment in the sagittal plane. Achieving harmonious sagittal plane spino-pelvic balance is critical for the preservation of physiologic posture and spinal health. Purpose: This study examined the kyphotic angle, lordotic angle and pelvic inclination in the sagittal plane and trunk imbalance in the frontal plane before and after a six-month rehabilitation period. Methods: Nineteen patients with idiopathic scoliosis participated in the study. They were divided into two groups; experimental and control. The experimental group (group I) used the SpineCor brace in addition to a rehabilitation exercise program while the control group (group II) had the exercise program only. The mean ±SD age, weight and height were 16.89±2.15 vs. 15.3±2.5 years; 59.78±6.85 vs. 62.5±8.33 Kg and 162.78±5.76 vs. 159±5.72 cm for group I vs. group II. Data were collected using for metric Π system. Results: Mixed design MANOVA showed that there were significant (p < 0.05) decreases in all the tested variables after the six-month period compared with “before” in both groups. Moreover, there was a significant decrease in the kyphotic angle in group I compared with group II after the six-month period. Interpretation and conclusion: SpineCor brace is beneficial in reducing spino-pelvic alignment deterioration in both sagittal and frontal planes.

Keywords: adolescent idiopathic scoliosis, SpineCor, spino-pelvic alignment, biomechanics

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24336 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

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Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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24335 PDDA: Priority-Based, Dynamic Data Aggregation Approach for Sensor-Based Big Data Framework

Authors: Lutful Karim, Mohammed S. Al-kahtani

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Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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24334 Prenatal Lead Exposure and Postpartum Depression: An Exploratory Study of Women in Mexico

Authors: Nia McRae, Robert Wright, Ghalib Bello

Abstract:

Introduction: Postpartum depression is a prevalent mood disorder that is detrimental to the mental and physical health of mothers and their newborns. Lead (Pb) is a toxic metal that is associated with hormonal imbalance and mental impairments. The hormone changes that accompany pregnancy and childbirth may be exacerbated by Pb and increase new mothers’ susceptibility to postpartum depression. To the best of the author’s knowledge, this is the only study that investigates the association between prenatal Pb exposure and postpartum depression. Identifying risk factors can contribute to improved prevention and treatment strategies for postpartum depression. Methods: Data was derived from the Programming Research in Obesity, Growth, Environment and Social Stress (PROGRESS) study which is an ongoing longitudinal birth cohort. Postpartum depression was identified by a score of 13 or above on the 10-Item Edinburg Postnatal Depression Scale (EPDS) 6-months and 12-months postpartum. Pb was measured in the blood (BPb) in the second and third trimester and in the tibia and patella 1-month postpartum. Quantile regression models were used to assess the relationship between BPb and postpartum depression. Results: BPb in the second trimester was negatively associated with the 80th percentile of depression 6-months postpartum (β: -0.26; 95% CI: -0.51, -0.01). No significant association was found between BPb in the third trimester and depression 6-months postpartum. BPb in the third trimester exhibited an inverse relationship with the 60th percentile (β: -0.23; 95% CI: -0.41, -0.06), 70th percentile (β: -0.31; 95% CI: -0.52, -0.10), and 90th percentile of depression 12-months postpartum (β: -0.36; 95% CI: -0.69, -0.03). There was no significant association between BPb in the second trimester and depression 12-months postpartum. Bone Pb concentrations were not significantly associated with postpartum depression. Conclusion: The negative association between BPb and postpartum depression may support research which demonstrates lead is a nontherapeutic stimulant. Further research is needed to verify these results and identify effect modifiers.

Keywords: depression, lead, postpartum, prenatal

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24333 Assessment of Environmental Impacts and Determination of Sustainability Level of BOOG Granite Mine Using a Mathematical Model

Authors: Gholamhassan Kakha, Mohsen Jami, Daniel Alex Merino Natorce

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Sustainable development refers to the creation of a balance between the development and the environment too; it consists of three key principles namely environment, society and economy. These three parameters are related to each other and the imbalance occurs in each will lead to the disparity of the other parts. Mining is one of the most important tools of the economic growth and social welfare in many countries. Meanwhile, assessment of the environmental impacts has directed to the attention of planners toward the natural environment of the areas surrounded by mines and allowing for monitoring and controlling of the current situation by the designers. In this look upon, a semi-quantitative model using a matrix method is presented for assessing the environmental impacts in the BOOG Granite Mine located in Sistan and Balouchestan, one of the provinces of Iran for determining the effective factors and environmental components. For accomplishing this purpose, the initial data are collected by the experts at the next stage; the effect of the factors affects each environmental component is determined by specifying the qualitative viewpoints. Based on the results, factors including air quality, ecology, human health and safety along with the environmental damages resulted from mining activities in that area. Finally, the results gained from the assessment of the environmental impact are used to evaluate the sustainability by using Philips mathematical model. The results show that the sustainability of this area is weak, so environmental preventive measures are recommended to reduce the environmental damages to its components.

Keywords: sustainable development, environmental impacts' assessment, BOOG granite, Philips mathematical model

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24332 Modern Forms and Aesthetics in Design

Authors: Chukwuma Anya, Mekwa Eme

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The term ‘’FORM’’ in design could be referred to as the combination of various shapes of different sizes and assembling them in appropriate positions to achieve a unique figure of high aesthetic value. A deduction from this definition is that forms contribute immensely to the actualization of aesthetics in a building. When these various shapes and figures are properly assembled, it may give rise to a concept in design. However some architects and other designers either misuse or abuse the use of these shapes, hence resulting to a design imbalance, lack of uniformity and expression. This academic work is designed to educate the public on the proper usage of some regular shapes like circles, rectangles, pentagons, hexagons, triangles etc, to achieve a unique form in design. By the end of this work, one should be able to assemble different shapes to express different emotions of the mind, such as peace, love, confusion, war, and unity. Some elements of design, such as balance, stability, functionality and aesthetics, will also be achieved even as the building maintains its unique form.

Keywords: aesthetics, form, balance, stability

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24331 Decision Support Tool for Water Re-used Systems

Authors: Katarzyna Pawęska, Aleksandra Bawiec, Ewa Burszta-Adamiak, Wiesław Fiałkiewicz

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The water shortage becomes a serious problem not only in African and Middle Eastern countries, but also recently in the European Union. Scarcity of water means that not all agricultural, industrial and municipal needs will be met. When the annual availability of renewable freshwater per capita is less than 1,700 cubic meters, countries begin to experience periodic or regular water shortages. The phenomenon of water stress is the result of an imbalance between the constantly growing demand for water and its availability. The constant development of industry, population growth, and climate changes make the situation even worse. The search for alternative water sources and independent supplies is becoming a priority for many countries. Data enabling the assessment of country’s condition regarding water resources, water consumption, water price, wastewater volume, forecasted climate changes e.g. temperature, precipitation, are scattered and their interpretation by common entrepreneurs may be difficult. For this purpose, a digital tool has been developed to support decisions related to the implementation of water and wastewater re-use systems, as a result of an international research project “Framework for organizational decision-making process in water reuse for smart cities” (SMART-WaterDomain) funded under the EIG-CONCERT Japan call on Smart Water Management for Sustainable Society. The developed geo-visualization tool graphically presents, among others, data about the capacity of wastewater treatment plants and the volume of water demand in the private and public sectors for Poland, Germany, and the Czech Republic. It is expected that such a platform, extended with economical water management data and climate forecasts (temperature, precipitation), will allow in the future independent investigation and assessment of water use rate and wastewater production on the local and regional scale. The tool is a great opportunity for small business owners, entrepreneurs, farmers, local authorities, and common users to analyze the impact of climate change on the availability of water in the regions of their business activities. Acknowledgments: The authors acknowledge the support of the Project Organisational Decision Making in Water Reuse for Smart Cities (SMART- WaterDomain), funded by The National Centre for Research and Development and supported by the EIG-Concert Japan.

Keywords: circular economy, digital tool, geo-visualization, wastewater re-use

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24330 Acupuncture and Topiramat in Treatment of Migraine

Authors: Lazgeen Mohammed

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The greatest advantage of acupuncture over western medicine is that it is safe . Unlike synthetic drugs, acupuncture has virtually no side effects, and the procedures for treating headaches are much less invasive. Migraine headaches are usually one-sided, pulsating or throbbing, and moderate or severe in intensity.. Some patients also experience auras, a neurological symptom that develops gradually over 5-20 minutes. The patient may see brief flashes or waves of light, or changes in their vision. Other common features of auras include vertigo, imbalance, confusion and numbness.Acupuncture had been used to treat 50 patients suffering from migraine ,topiramat (topamax) given to prevent the attacks, duration of treatment is 10 weeks , the patients were fallowed up for one year .Topiramat is called an anticonvulsant.Topiramat is also used to prevent migraine headaches in adults and teenagers who are at least 12 years old. This medicine will only prevent migraine headaches or reduce the number of attacks. It will not treat a headache that has already begun.

Keywords: acpuncture, migraine, topiramat, headache

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24329 Interferometric Demodulation Scheme Using a Mode-Locker Fiber Laser

Authors: Liang Zhang, Yuanfu Lu, Yuming Dong, Guohua Jiao, Wei Chen, Jiancheng Lv

Abstract:

We demonstrated an interferometric demodulation scheme using a mode-locked fiber laser. The mode-locked fiber laser is launched into a two-beam interferometer. When the ratio between the fiber path imbalance of interferometer and the laser cavity length is close to an integer, an interferometric fringe emerges as a result of vernier effect, and then the phase shift of the interferometer can be demodulated. The mode-locked fiber laser provides a large bandwidth and reduces the cost for wavelength division multiplexion (WDM). The proposed interferometric demodulation scheme can be further applied in multi-point sensing system such as fiber optics hydrophone array, seismic wave detection network with high sensitivity and low cost.

Keywords: fiber sensing, interferometric demodulation, mode-locked fiber laser, vernier effect

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24328 Indo-US Strategic Collaboration in Space Capabilities and its Effect on the Stability of South Asian Region

Authors: Shahab Khan, Damiya Saghir

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With the advent of space technology, a new era began where space, considered the new ‘High ground,’ is used for a variety of commercial (communications, weather and navigational information, Earth resources monitoring and imagery) and military applications (surveillance, tracking, reconnaissance and espionage of adversaries). With the ever-evolving geo-political environment, where now the US foreseeing India as a counterbalance to China’s economic and military rise, significant growth in strategic collaboration between US and India has been witnessed, particularly in the space domain. This is creating a strategic imbalance in South Asia with implications for all regional countries. This research explores the present and future of Indo-US strategic collaboration in the space domain with envisaged effects and challenges for countries in the South Asian region.

Keywords: space, satellites, Indo-US strategic agreements in space domain, balance of power in South Asian region

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24327 Control the Flow of Big Data

Authors: Shizra Waris, Saleem Akhtar

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Big data is a research area receiving attention from academia and IT communities. In the digital world, the amounts of data produced and stored have within a short period of time. Consequently this fast increasing rate of data has created many challenges. In this paper, we use functionalism and structuralism paradigms to analyze the genesis of big data applications and its current trends. This paper presents a complete discussion on state-of-the-art big data technologies based on group and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also covers big data analytics techniques, processing methods, some reported case studies from different vendor, several open research challenges and the chances brought about by big data. The similarities and differences of these techniques and technologies based on important limitations are also investigated. Emerging technologies are suggested as a solution for big data problems.

Keywords: computer, it community, industry, big data

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24326 Effect of Eight Weeks Aerobic Training with Purslane Seeds on Peroxidant and Antioxidants Indicators in Women with Type2 Diabetes

Authors: Shima Dehghan

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Aim: imbalance between antioxidant defensive system and increasing production of free radicals caused oxidative stress that can be rolled in cellular damage and occurring some of diseases such as diabetes. The aim of current study was to investigate the effect of eight weeks aerobic training on peroxidant and antioxidants indicators in women with type2 diabetes. Methodology: thirty two inactive women with type 2 diabetes were randomly assigned into four groups: 1. control, 2. Aerobic training, 3. Purslane seed and 4. Aerobic training + Purslane seed groups. Subjects were asked to accomplish eight weeks aerobic training (50 min aerobic exercise, 3 days/week, for to achieve 65-75% maximum of heart rate). Also, subjects in certain groups received purslane seeds for eight weeks. Blood samples were obtained in two sets (one session and after 8 weeks). Data was analyzed using one way ANOVA. A significant difference was accepted at p < 0/05 level. Results: After eight weeks of aerobic training with purslane seeds supplementation, malon dyaldehyde (MDA) concentration in training group were significantly decreased (p < 0/000), but A difference significant was not found in control group. Superoxide dismutase (SOD) and catalase (CAT) concentrations in training group were significantly increased (p < 0/000), while difference significant wasnot found in control group. Conclusion: The finding of the current study indicates that disciplined aerobic training with purslane seeds supplementation can be caused improvement in peroxidant/antioxidant balance in women with type2 diabetes.

Keywords: aerobic training, purslane seed, peroxidant/antioxidant balance, diabetes2

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24325 Operative Technique of Glenoid Anteversion Osteotomy and Soft Tissue Rebalancing for Brachial Plexus Birth Palsy

Authors: Michael Zaidman, Naum Simanovsky

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The most of brachial birth palsies are transient. Children with incomplete recovery almost always develop an internal rotation and adduction contracture. The muscle imbalance around the shoulder results in glenohumeral joint deformity and functional limitations. Natural history of glenohumeral deformity is it’s progression with worsening of function. Anteversion glenoid osteotomy with latissimus dorsi and teres major tendon transfers could be an alternative procedure of proximal humeral external rotation osteotomy for patients with severe glenohumeral dysplasia secondary to brachial plexus birth palsy. We will discuss pre-operative planning and stepped operative technique of the procedure on clinical example.

Keywords: obstetric brachial plexus palsy, glenoid anteversion osteotomy, tendon transfer, operative technique

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24324 High Performance Computing and Big Data Analytics

Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

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24323 Selection of Soil Quality Indicators of Rice Cropping Systems Using Minimum Data Set Influenced by Imbalanced Fertilization

Authors: Theresa K., Shanmugasundaram R., Kennedy J. S.

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Nutrient supplements are indispensable for raising crops and to reap determining productivity. The nutrient imbalance between replenishment and crop uptake is attempted through the input of inorganic fertilizers. Excessive dumping of inorganic nutrients in soil cause stagnant and decline in yield. Imbalanced N-P-K ratio in the soil exacerbates and agitates the soil ecosystems. The study evaluated the fertilization practices of conventional (CFs), organic and Integrated Nutrient Management system (INM) on soil quality using key indicators and soil quality indices. Twelve rice farming fields of which, ten fields were having conventional cultivation practices, one field each was organic farming based and INM based cultivated under monocropping sequence in the Thondamuthur block of Coimbatore district were fixed and properties viz., physical, chemical and biological were studied for four cropping seasons to determine soil quality index (SQI). SQI was computed for conventional, organic and INM fields. Comparing conventional farming (CF) with organic and INM, CF was recorded with a lower soil quality index. While in organic and INM fields, the higher SQI value of 0.99 and 0.88 respectively were registered. CF₄ received with a super-optimal dose of N (250%) showed a lesser SQI value (0.573) as well as the yield (3.20 t ha⁻¹) and the CF6 which received 125 % N recorded the highest SQI (0.715) and yield (6.20 t ha⁻¹). Likewise, most of the CFs received higher N beyond the level of 125 % except CF₃ and CF₉, which recorded lower yields. CFs which received super-optimal P in the order of CF₆&CF₇>CF₁&CF₁₀ recorded lesser yields except for CF₆. Super-optimal K application also recorded lesser yield in CF₄, CF₇ and CF₉.

Keywords: rice cropping system, soil quality indicators, imbalanced fertilization, yield

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24322 A Landscape of Research Data Repositories in Re3data.org Registry: A Case Study of Indian Repositories

Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

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24321 Antiasthmatic Effect of Kankasava in OVA-Induced Asthma Mouse Model

Authors: Bharti Ahirwar

Abstract:

The main object of this study was to evaluate the effect of kankasava on OVA-induced asthma in mouse model. Present study has demonstrated that kankasava exhibited an antiasthmatic effect by attenuated AHR and reducing level of IgE, IL-5, and IL-13, in both serum and BALF in OVA induced asthmatic mice. Effect of kankasav on airway responsiveness was obtained by monitoring the enhanced pen value . Kankasava significantly reduced AHR can be explained, in part, by reduction in both IgE overexoression and cytokine levels. Kankasava significantly decreased IL-4, IL-5, and IL-13 in BALF indicate that it may suppress the excess activity of T-cells and Th2 cytokines, which are implicated in the pathogenesis of allergic asthma, and consequently restore the Th1/Th2 imbalance of the immune system. In summary, we hypothesize that kankasava effectively suppressed elevations in IgE and cytokines levels, AHR, and mucus overproduction in mice with OVA-induced asthma suggested kankasava could be effective in immunological and pharmacological modulation of allergic asthma.

Keywords: asthma, ayurveda, kankasava, cytokine

Procedia PDF Downloads 294
24320 A Study of Cloud Computing Solution for Transportation Big Data Processing

Authors: Ilgin Gökaşar, Saman Ghaffarian

Abstract:

The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

Procedia PDF Downloads 430
24319 Harmonic Data Preparation for Clustering and Classification

Authors: Ali Asheibi

Abstract:

The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 223
24318 Isolation and Identification of the Dominant Flora of the Intestinal Microbiota of Rattus norvegicus an Algerian Firm West

Authors: Karima Ould Yerou, B. Meddah, A. Tir Touil

Abstract:

The intestinal flora also called the intestinal microbiota, consists of different bacteria and other microorganisms which occur naturally in the gastrointestinal tract organs components. These intestinal bacteria are present in their millions and help the functioning of the body in particular allowing aid to degradation of certain molecules into absorbable substrates. They also protect against invasion of the gut by other pathogenic bacteria, that is to say which may be responsible for disease. Factors like stress, antibiotics and diet can affect the balance of intestinal flora and in case of imbalance, digestive disorders type bloating, diarrhea or vomiting may occur. Rattus norvegicus of bad weight of 100 kg, an Algerian firm West are scarified and isolation of their ileum and colon respectively two Bactrian strains Escherichia coli and Lactobacillus are then purified and identified.

Keywords: intestinal flora, Rattus norvegicus, Escherichia coli, lactobacillus, West Algerian farm

Procedia PDF Downloads 315
24317 Linguistic Summarization of Structured Patent Data

Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

Abstract:

Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

Procedia PDF Downloads 249