Search results for: imbalance data

Authors: K. B. Chathyushya, M. Shiva Prakash, R. Hemalatha

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Introduction: Gastrointestinal (GI) tract has a number of microorganisms (microbiota) that influences the host’s health. The imbalance in the gut microbiota, which is also called as gut dysbiosis, affects human health which causes various metabolic, inflammatory, and infectious diseases. Probiotics play an important role in reinstating the gut balance. Probiotics are involved in the maintenance of healthier gut microbiota and have also been identified as effective adjuvants in insulin resistance therapies. Methods: This paper systematically reviews different randomized, controlled, blinded trials of probiotics for the treatment of various diseases along with the therapeutic or prophylactic properties of probiotic bacteria in different metabolic, inflammatory, infectious and anxiety-related disorders. Conclusion: The present review summarises that probiotics have some considerable effect in the management of various diseases, however, the benefits are strain specific, although more clinical trials are need to be carried out with different probiotic and symbiotic combinations as some probiotics have broad spectrum of benefits and few with specific activity

Keywords: life style diseases, cognition, health, gut dysbiosis, probiotics

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Authors: M. Rajasekar, K. Suresh

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Diosmin is a flavonoid, most abundantly found in many citrus fruits. As a flavonoid, it possesses a multitude of biological activities including anti-hyperglycemic, anti-lipid peroxidative, anti-inflammatory, antioxidant, and anti-mutagenic properties. At this point, we established the anti-proliferative and apoptosis-inducing activities of diosmin in Hep-2 and KB cells. Diosmin has cytotoxic effects through inhibiting cellular proliferation of Hep-2 and KB cells, which leads to the induction of apoptosis, as apparent by an increase in the fraction of cells in the sub-G1phase of the cell cycle. Results exposed that inhibition of cell proliferation is associated with regulation of the Interleukins/STAT pathway. In addition, Diosmin treatment with Hep-2 and KB cells actively stimulated reactive oxygen species (ROS) and mitochondrial membrane depolarization. And also an imbalance in the Bax/Bcl-2 ratio triggered the caspase cascade and shifting the balance in favor of apoptosis. These observations conclude that Diosmin induce apoptosis via Interleukins /STAT-mediated pathway.

Keywords: diosmin, apoptosis, antioxidant, STAT pathway

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Authors: Yoonah Lee, Richard Kyung

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With technological advances in the computational biomedical field, the ability to measure neurotransmitters’ chemical imbalances that affect depression and anxiety has been established. By comparing the thermodynamics stability of amino acid supplements, such as glutamine, tyrosine, phe-nylalanine, and methionine, this research analyzes mood-regulating neurotransmitters, amino acid supplements, and antipsychotic substances (ie. Reserpine molecule and CRF complexes) in relation to depression and anxiety and suggests alternative complexes that are low in energy to act as more efficient treatments for mood disorders. To determine a molecule’s thermodynamic stability, this research examines the molecular energy using Avogadro, a software for building virtual molecules and calculating optimized geometry using GAFF (General Amber Force Field) and UFF (Universal Force Field). The molecules, built using Avogadro, is analyzed using their theoretical values and atomic properties.

Keywords: amino acids, anxiety, depression, neurotransmitters

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Authors: Ashvamedh, Chandra Bhushan Singh, Anil Kumar Sarda

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Introduction: Ileal perforation is a common cause for peritonitis in developing countries. Surgery is the ideal treatment as it eliminates soilage of peritoneal cavity in an effort to lessen the toxaemia and enhance the recovery of the patient. However, there is no uniformity of standardized operative procedure that is most effective for management. Material and method: The study was conducted on 66 patients of perforation peritonitis from November 2013 to February 2015 in Lok Nayak Hospital. Data of each patient were recorded on a pre-determined proforma. The methods used for repair were Primary repair, Resection anastomosis (RA) and Ileostomy. Result: Male preponderance was noticed among the patients with majority in their third decade. Of all perforations 40.9% were tubercular and 34.8% were typhoid. Amongst operated cases 27.3% underwent primary repair, RA was performed in 45.5%, Ileostomy in 27.3%patients. The average time taken for RA and ileostomy was more than primary repair. The type of repair bear no significance to size or no of perforation but was significant statistically for distance from I/C valve(P=.005) and edema of bowel wall(p=.002) when analysed for post op complications. Wound infection, dehiscence, intra-abdominal collections were complications observed bearing no significance to type of repair. Ileostomy per se has its own complications peristomal skin excoriation seen in 83.3%, electrolyte imbalance in 33.3%, duration for closure averaged 188 days (median 150 days, range 85-400 days). Conclusion: Primary closure is preferable in patients with single, small perforations. RA is advocated in patients with multiple or large perforation, perforation proximal to stricture. Ileostomy should not be considered as primary definitive procedure and reserved only for moribund patients as a lifesaving procedure. It has more morbidity and requires a second surgery for closure increasing the cost of treatment as well.

Keywords: ileal perforation, ileostomy, perforation peritonitis, typhoid perforation management

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Authors: Petr Daniel Edward Kovarik, Malcolm Jackson, Charles Kelly, Rahul Patil, Shahid Iqbal

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Introduction: Recognition of the presence of extra capsular spread (ECS) has been a major change in the TNM 8th edition published by the American Joint Committee on Cancer in 2018. Irrespective of the size or number of lymph nodes, the presence of ECS makes N3b disease a stage IV disease. The objective of this retrospective observational study was to conduct a comparative analysis of survival outcomes in patients with lymph node-positive cutaneous head and neck squamous cell carcinoma (CHNSCC) based on their TNM 7th and TNM 8th editions classification. Materials and Methods: From January 2010 to December 2020, 71 patients with CHNSCC were identified from our centre’s database who were treated with radical surgery and adjuvant radiotherapy. All histopathological reports were reviewed, and comprehensive nodal mapping was performed. The data were collected retrospectively and survival outcomes were compared using TNM 7th and 8th editions. Results: The median age of the whole group of 71 patients was 78 years, range 54 – 94 years, 63 were male and 8 female. In total, 2246 lymph nodes were analysed; 195 were positive for cancer. ECS was present in 130 lymph nodes, which led to a change in TNM staging. The details on N-stage as per TNM 7th edition was as follows; pN1 = 23, pN2a = 14, pN2b = 32, pN2c = 0, pN3 = 2. After incorporating the TNM 8th edition criterion (presence of ECS), the details on N-stage were as follows; pN1 = 6, pN2a = 5, pN2b = 3, pN2c = 0, pN3a = 0, pN3b = 57. This showed an increase in overall stage. According to TNM 7th edition, there were 23 patients were with stage III and remaining 48 patients, stage IV. As per TNM 8th edition, there were only 6 patients with stage III as compared to 65 patients with stage IV. For all patients, 2-year disease specific survival (DSS) and overall survival (OS) were 70% and 46%. 5-year DSS and OS rates were 66% and 20% respectively. Comparing the survival between stage III and stage IV of the two cohorts using both TNM 7th and 8th editions, there is an obvious greater survival difference between the stages if TNM 8th staging is used. However, meaningful statistics were not possible as the majority of patients (n = 65) were with stage IV and only 6 patients were stage III in the TNM 8th cohort. Conclusion: Our study provides a comprehensive analysis on lymph node data mapping in this specific patient population. It shows a better differentiation between stage III and stage IV in the TNM 8th edition as compared to TNM 7th however meaningful statistics were not possible due to the imbalance of patients in the sub-cohorts of the groups.

Keywords: cutaneous head and neck squamous cell carcinoma, extra capsular spread, neck lymphadenopathy, TNM 7th and 8th editions

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Nanhee Cho, Eugene Han, Hanbyul Kim, Hochan Cho

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Pre-diabetes includes impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) and there is a strong probability that pre-diabetes will lead to diabetes mellitus (DM). Serum fibroblast growth factor 21 (FGF-21) is known to be increased as a compensatory response to metabolic imbalance under conditions such as obesity, metabolic syndrome, and DM. This study aims to identify the relationship of serum FGF-21 with pre-diabetes, and with biomarkers of related metabolic diseases. Fifty five Korea adult patients participated in a cohort study from June 2012 to December 2015. The analysis revealed that BMI, FBS levels, and serum FGF-21 levels were significantly higher in the IFG group compared to those in the normal group. A multiple regression analysis was conduted on the correlations of serum FGF-21 levels with BMI, and FBS levels, and the result did not show statistical significance. In conclusion, our results revealed that serum FGF-21 level serve as a marker to predict IFG.

Keywords: cytokine, fibroblast growth factor 21, impaired fasting glucose, prediabetes

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: aerial image, landcover, LiDAR, soil fertility degradation

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Authors: Youssef I. Hafez

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Since ancient history rivers have been the fostering and favorite place for people and civilizations to live and exist along river banks. However, due to floods and droughts, especially sever conditions due to global warming and climate change, river channels are completely evolving and moving in the lateral direction changing their plan form either through straightening of curved reaches (meander cut-off) or increasing meandering curvature. The lateral shift or shrink of a river channel affects severely the river banks and the flood plain with tremendous impact on the surrounding environment. Therefore, understanding the formation and the continual processes of river channel meandering is of paramount importance. So far, in spite of the huge number of publications about river-meandering, there has not been a satisfactory theory or approach that provides a clear explanation of the formation of river meanders and the mechanics of their associated geometries. In particular two parameters are often needed to describe meander geometry. The first one is a scale parameter such as the meander arc length. The second is a shape parameter such as the maximum angle a meander path makes with the channel mean down path direction. These two parameters, if known, can determine the meander path and geometry as for example when they are incorporated in the well known sine-generated curve. In this study, a uniform excess energy theory is used to illustrate the origin and mechanics of formation of river meandering. This theory advocates that the longitudinal imbalance between the valley and channel slopes (with the former is greater than the second) leads to formation of curved meander channel in order to reduce the excess energy through its expenditure as transverse energy loss. Two relations are developed based on this theory; one for the determination of river channel radius of curvature at the bend apex (shape parameter) and the other for the determination of river channel sinuosity. The sinuosity equation tested very well when applied to existing available field data. In addition, existing model data were used to develop a relation between the meander arc length and the Darcy-Weisback friction factor. Then, the meander wave length was determined from the equations of the arc length and the sinuosity. The developed equation compared well with available field data. Effects of the transverse bed slope and grain size on river channel sinuosity are addressed. In addition, the concept of maximum channel sinuosity is introduced in order to explain the changes of river channel plan form due to changes in flow discharges and sediment loads induced by global warming and climate changes.

Keywords: river channel meandering, sinuosity, radius of curvature, meander arc length, uniform excess energy theory, transverse energy loss, transverse bed slope, flow discharges, sediment loads, grain size, climate change, global warming

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Muhammad Umair, Syed Qasim Gilani

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A technique using Independent Component Analysis (ICA) for blind receiver signal processing is investigated. The problem of the receiver signal processing is viewed as of signal equalization and implementation imperfections compensation. Based on this, a model similar to a general ICA problem is developed for the received signal. Then, the use of ICA technique for blind signal equalization in the time domain is presented. The equalization is regarded as a signal separation problem, since the desired signal is separated from interference terms. This problem is addressed in the paper by over-sampling of the received signal. By using ICA for equalization, besides channel equalization, other transmission imperfections such as Direct current (DC) bias offset, carrier phase and In phase Quadrature phase imbalance will also be corrected. Simulation results for a system using 16-Quadraure Amplitude Modulation(QAM) are presented to show the performance of the proposed scheme.

Keywords: blind equalization, blind signal separation, equalization, independent component analysis, transmission impairments, QAM receiver

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Rashmi Tyagi, Savita Vermani

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Violence against women is the result of long-standing power imbalance between men and women and thus seriously compromises the well-being, productivity and contribution of one half the population. The costs incurred to the family especially children and society at large in terms of physical, psychological, social and financial losses are huge. The communities’ native to the state of Haryana in India is primarily patriarchal, burdened with age old regressive mindset under the socio-cultural and religious structures which discriminates against women. Therefore it was important to bring to light the issues affecting women in this region. Therefore this study focused on studying the consequences of crime on victim women and their families. Two hundred women were randomly selected and out of those one hundred twenty, who were affected with some kind of violence were interviewed. Data was collected and statistically analyzed for physical, psychological, inter-family and societal consequences of violence on these women. Women reported physical injuries, gynecological problems, unwanted pregnancies, frigidity, phobia and sexual dysfunction. 58.9% women felt decreased work efficiency. Psychological problems encountered were anxiety, isolation, depression, suicidal tendencies. 66.7% respondents suffered from anxiety followed by 65.0% faced depression symptoms. At family levels, 40.0% respondents felt the atmosphere was unsuitable for children while 39.2% reported lack of interaction. The societal consequences reported were breakdown of interaction with friends and family (44.2%) and resulting humiliation and demeaning remarks from others (38.3%). The impact of violence on women had an adverse effect on children. 36.7% children felt responsible for abuse and powerless to stop it, 29.2% reported living with fear. Concerted efforts are required to curb violence against women in Haryana.

Keywords: impact of violence against women on children, patriarchal society, physical psychological and societal consequences, violence against women

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Jair Servín-Aguilar, Yu Tang

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We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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