Optimizing multi-tenant database architecture for efficient software as a service delivery

A multi-tenant database (MTDB) is the backbone for any cloud app that employs a software as a service (SaaS) delivery paradigm. Every cloud-based SaaS delivery strategy relies heavily on the architecture of multitenant databases. The hardware and performance costs for quicker query execution and space savings provided by the architecture of MTDBs are implementation costs. All tenants’ data may be kept in a single table with a common schema and database format, making it the most cost-effective MTDB configuration. The arrangement becomes congested if tenants have varying storage needs. In this research, we present a space-saving architecture that improves transactional query execution while avoiding the waste of space due to different attribute needs. Extensible markup language (XML) and JavaScript object notation (JSON) compare the proposed system against the state of the art. The suggested multitenant database architecture reduces unnecessary space and improves query performance. The experimental findings show that the suggested system outperforms the state-ofthe-art extension table method

Diagnostic System of the APT Hydraulic Press

Diplomová práce se zabývá zkoumáním aktuálního stavu hydraulického lisu APT v oblasti diagnostiky. K zjištění technického stavu bylo využito metod technické bezdemontážní diagnostiky, a to tribodiagnostiky, vibrodiagnostiky a termodiagnostiky. Na základě naměřených hodnot odebraného vzorku oleje, vibračního signálu a fotek z IR termokamery bylo stanovené vyhodnocení aktuálního technického stavu hydraulického lisu APT. Na závěr bylo provedeno doporučení pro další provoz, aby byla zaručena vysoká provozní spolehlivost a životnost zařízení.The master thesis deals with the examination of the current state of the APT hydraulic press in the field of diagnostics. To determine the technical condition, the methods of technical non-disassembly diagnostics were used, namely tribodiagnostics, vibrodiagnostics and thermodiagnostics. Based on the measured values of the oil sample, the vibration signal and the photos from the IR thermal camera, the evaluation of the current technical state of the APT hydraulic press was determined. In last part, recommendations were made for further operation to ensure high operational reliability and service life.340 - Katedra výrobních strojů a konstruovánívýborn

Research of Lubrication Problems on Production Line

Import 23/07/2015Bakalářská práce se zabývá zkoumáním stavu mazáním výrobní linky. K zjištění technického stavu bylo využito metody bezdemontážní technické diagnostiky, a to tribodiagnostiky. Na základě naměřených hodnot odebraných vzorků bylo stanovené vyhodnocení stavu maziv. Na závěr byly provedeny návrhy na další řešení mazání výrobní linky.This bachelor thesis deals with the state of lubrication of the production line. The method of technical diagnostics and tribodiagnostics was used to determine the technical state. The evaluation of the lubricants´ condition was based on the measured values of the samples. At the end of my bachelory thesis, proposals for further lubricating solutions of the production line were made.340 - Katedra výrobních strojů a konstruovánívýborn

Customer segmentation in e-commerce: K-means vs hierarchical clustering

Customer segmentation is important for e-commerce companies to understand and target different customers. The primary focus of this work is the application and comparison of K-means clustering and hierarchical clustering, unsupervised machine learning techniques, in customer segmentation for e-commerce platforms. Clustering leverages customer search behavior, reflecting brand preferences, and identifying distinct customer segments. The proposed work explores the K-means algorithm and hierarchical clustering. It uses them to classify customers in a standard e-commerce customer dataset, mainly focused on frequently searched brands. Both techniques are compared based on silhouette scores and cluster visualizations. K-means clustering yielded well-separated segments compared to hierarchical clustering. Then, using the K-means algorithm, customers are classified into different segments based on brand search patterns. Further, targeted marketing strategies are discussed for each segment. Results show three customer segments: high searchers-low buyers, loyal customers, and moderate engagers. The proposed work provides valuable insights into customers that could be used for developing targeted marketing campaigns, product recommendations, and customer engagement strategies to enhance the conversion rate, customer satisfaction, and, in turn, the growth of an e-commerce platform

Assessment of periodontal status in adults with diabetes mellitus

Background: Diabetes mellitus is a group of chronic metabolic disorders known to exhibit a myriad of complications over a period of time. Periodontal disease is the sixth most common complication in diabetic patients. The aim of the study was to assess the periodontal status of adult diabetic patients.Methods: 100 diabetic patients in the age group of 25-80 years fulfilling the inclusion criteria were examined by a calibrated WHO CPI probe to assess their periodontal status as per the scoring criteria of the community periodontal index. Student t test, Chi square test and ANOVA F were applied for statistical analysis. p>0.05 was considered not significant and p<0.01 was considered highly significant.Results: A prevalence of 73% periodontitis was found in diabetic study population with statistically high significance (p=0.001) found according to age. A total of 52% Shallow pockets and 15% Deep pockets were reported respectively in middle (41-56 years) and older (57-80 years) age groups. Further, 47% male population was found to have statistically significant (p=0.027) more periodontitis (shallow and deep periodontal pockets) compared to female (26%) population.Conclusions: Within limitations of the study it may be safely concluded that assessment of periodontal status of DM patients revealed chronic periodontal destruction particularly in age groups beyond 40 years in majority of study population depicting that age is significantly associated with the increased prevalence and severity of periodontal disease in patients with diabetes

Fortified Settlements of the 9th and 10th Centuries ad in Central Europe: structure, function and symbolism

Open access article. © Society for Medieval Archaeology 2012.The structure, function(s)and symbolism of early medieval (9th-10th centuries ad) fortified settlements from central Europe, in particular today's Austria, Hungary, Czech Republic and Slovakia, are examined in this paper. It offers an overview of the current state of research together with new insights based on analysis of the site of Gars-Thunau in Lower Austria. Special emphasis is given to the position of the fortified sites in the landscape, to the elements of the built environment and their spatial organisation, as well as to graves within the fortified area. The region under study was situated on the SE border of the Carolingian (and later the Ottonian) Empire, with some of the discussed sites lying in the territory of the 'Great Moravian Empire' in the 9th and 10th centuries. These sites can therefore provide important comparative data for researchers working in other parts of the Carolingian Empire and neighbouring regions.Alexander von Humboldt FoundationAustrian Science Fun

A machine learning model for predicting innovation effort of firms

Classification and regression tree (CART) data mining models have been used in several scientific fields for building efficient and accurate predictive models. Some of the application areas are prediction of disease, targeted marketing, and fraud detection. In this paper we use CART which widely used machine learning technique for predicting research and development (R&amp;D) intensity or innovation effort of firms using several relevant variables like technical opportunity, knowledge spillover and absorptive capacity. We found that accuracy of CART models is superior to the often-used linear parametric models. The results of this study are considered necessary for both financial analysts and practitioners. In the case of financial analysts, it establishes the power of data-driven prototypes to understand the innovation thinking of employees, whereas in the case of policymakers or business entrepreneurs, who can take advantage of evidence-based tools in the decision-making process

Real time Indian sign language recognition using transfer learning with VGG16

Normal people’s interaction and communication are easier than those with disabilities such as hearing and speech, which are very complicated; hence, the use of sign language plays a crucial role in bridging this gap in communication. While previous attempts have been made to solve this problem using deep learning techniques, including convolutional neural networks (CNNs), support vector machine (SVM), and K-nearest neighbours (KNN), these have low accuracy or may not be employed in real time. This work addresses both issues: improving upon prior limitations and extending the challenge of classifying characters in Indian sign language (ISL). Our system, which can recognize 23 hand gestures of ISL through a purely camera-based approach, eliminates expensive hardware like hand gloves, thus making it economical. The system yields an accuracy of 97.5% on the training dataset, utilizing a pre-trained VGG16 CNN optimized by the Adam optimizer and cross-entropy loss function. These results clearly show how effective transfer learning is in classifying ISL and its possible real-world applications

Allosteric Modulators of Steroid Hormone Receptors : Structural Dynamics and Gene Regulation

Peer reviewedPublisher PD

Characterization of a distinct population of circulating human non-adherent endothelial forming cells and their recruitment via intercellular adhesion molecule-3

Circulating vascular progenitor cells contribute to the pathological vasculogenesis of cancer whilst on the other hand offer much promise in therapeutic revascularization in post-occlusion intervention in cardiovascular disease. However, their characterization has been hampered by the many variables to produce them as well as their described phenotypic and functional heterogeneity. Herein we have isolated, enriched for and then characterized a human umbilical cord blood derived CD133+ population of non-adherent endothelial forming cells (naEFCs) which expressed the hematopoietic progenitor cell markers (CD133, CD34, CD117, CD90 and CD38) together with mature endothelial cell markers (VEGFR2, CD144 and CD31). These cells also expressed low levels of CD45 but did not express the lymphoid markers (CD3, CD4, CD8)or myeloid markers (CD11b and CD14) which distinguishes them from ‘early’ endothelial progenitor cells (EPCs). Functional studies demonstrated that these naEFCs (i) bound Ulex europaeus lectin, (ii)demonstrated acetylated-low density lipoprotein uptake, (iii) increased vascular cell adhesion molecule (VCAM-1) surface expression in response to tumor necrosis factor and (iv) in co-culture with mature endothelial cells increased the number of tubes, tubule branching and loops in a 3- dimensional in vitro matrix. More importantly, naEFCs placed in vivo generated new lumen containing vasculature lined by CD144 expressing human endothelial cells (ECs). Extensive genomic and proteomic analyses of the naEFCs showed that intercellular adhesion molecule (ICAM)-3 is expressed on their cell surface but not on mature endothelial cells. Furthermore, functional analysis demonstrated that ICAM-3 mediated the rolling and adhesive events of the naEFCs under shear stress. We suggest that the distinct population of naEFCs identified and characterized here represents a new valuable therapeutic target to control aberrant vasculogenesis.Sarah L. Appleby, Michaelia P. Cockshell, Jyotsna B. Pippal, Emma J. Thompson, Jeffrey M. Barrett, Katie Tooley, Shaundeep Sen, Wai Yan Sun, Randall Grose, Ian Nicholson, Vitalina Levina, Ira Cooke, Gert Talbo, Angel F. Lopez and Claudine S. Bonde