Reference Architectures to Measure Data Completeness Across Integrated Databases

Completeness is an important aspect of data quality and to determine data acceptability one needs to measure the completeness of the data set of concerned. One type of data completeness measure is population-based completeness (PBC). Nevertheless, the notion of PBC will be of little use until we can determine the eorts required (in terms of architectural design) to implement PBC. In this paper, we present the types of PBC system reference architecture and motivate the selection of each

Data Accessibility Model Using QR Code for Lifetime Healthcare Records

One factor that determines the quality of healthcareservices is the accessibility of patient records. Fast and seamless access to patient records is necessary in order to support sharing of complete lifetime patient records among healthcare providers while promoting the greater use of it. Nevertheless, studies on how complete lifetime patient record can be acquired by improving the way these records are accessed are limited. In this paper, the conceptual model of data accessibility in healthcare domain will be presented. QR code technology will be adopted in the model as a tool that enables multi-platforms data access points. Incremental data updates will be used as a mean to share complete, up-to-date lifetime patient records. Software prototype architecture and the interface design of the model will be also presented in this paper. The contribution of the work is on improving lifetime patient records accessibility that consequently promotes sharing of complete patient records among healthcare providers

Beginning Database: A Practical Approach for Non-relational Database

Developing any applications that involve storage of data in a database requires application developer to carefully and precisely build design plans in order to produce high quality and useful product. There are many approaches that can be adopted in order to explain database design. Furthermore, database technology is rapidly developed and changing. As the result, the way to describe database design should be updated in order to reflect the current and latest database technology. The primary objective of this book is to equip the students with basic knowledge on how to design database for other types of data model like object-oriented and object-relational data model

Database Performance Tuning Methods for Manufacturing Execution System

In manufacturing industry where data are produced and shared every day, data volumes could be large enough for the database performance to become an issue. Manufacturing Execution System (MES) is such a system that cannot tolerate with poor database performance as the system relies heavily on real-time reporting that requires instance query responses. Manufacturing products’ quality and production targets can be affected as the result of delayed queries. Therefore, the need to maintain the acceptable level of database performance in this domain is crucial. One task in maintaining database performance is identification and diagnosis of the root causes that may cause delayed queries. Poor query design has been identified as one major cause of delayed queries that affect real-time reporting. Nevertheless, as various methods available to deal with poor query design, it is important for a database administrator to decide the method or combination of methods that work best. In this paper, we present a case study on the methods used by a real manufacturing industry company called as Silterra and the methods proposed in the literature that deal with poor query design. For each method, we elicit its strength and weaknesses and analyse the practical implementation of it

Query Rewriting using Multitier Materialized Views for Cyber Manufacturing Reporting

Within cyber manufacturing context, Internet of Data (IoD) technology has enabled manufacturing sector to store and transfer mass data rapidly for processing.  Data growth which is driven by advancement in the way data are produced and interconnected has caused volume of data a crucial issue to address. As such, in monitoring delicate wafer processing in semiconductor manufacturing, reporting delay problem caused by databases of high data volumes is intolerable. This is because, various reports (that require access to large databases) need to be frequently generated in the shortest time possible. Reporting delay is usually handled through SQL query rewriting. In this paper, the results of experimenting SQL query rewriting by utilizing multitier materialized views structure is presented. In particular, we define sub-materialized views (SMVs) concept, and implement it using real data sets from SilTerra (a semiconductor industry). The outcome of the experiment supports the hypothesis that SQL query rewriting using SMV outperforms the classic rewriting. The results reveal that the performance of SMV is far better (than without SMV) for complex queries against large data sets. The benefits of SMV are not limited to cyber manufacturing domain as the use of SMV can contribute other industries with similar problem

The influence of graphitization catalyst electrode in electrical discharge machining of polycrystalline diamond-finishing condition

Electrical Discharge Machining (EDM) is a non-contact machining process that becomes famous in machining of Polycrystalline Diamond (PCD). The material is typically used as the cutting tools for aerospace and automotive industries. However, low electrical conductivity and high melting temperature of PCD has caused slower EDM process. This investigation purposely designed to investigate the influence of different types of electrode which are Copper (ordinary electrode) and Copper-Nickel (newly proposed graphitization catalyst electrode) on EDM performance of MRR and Ra. Interestingly the newly proposed electrode gave positive impact to the investigated performance indication. Cu-Ni electrode recorded 35% better in MRR than the Cu electrode, though with higher short-circuiting rate. Cu-Ni also provided the lowest Ra value with 10% better than the best Ra produced by Cu electrode. This phenomenon occurred as due to the high interaction between the catalyst materials of nickel and diamond which supported by the qualification data provided in this investigation

Insights into the Promising Prospect of G Protein and GPCR-Mediated Signaling in Neuropathophysiology and Its Therapeutic Regulation

G protein-coupled receptors (GPCRs) are intricately involved in the conversion of extracellular feedback to intracellular responses. These specialized receptors possess a crucial role in neurological and psychiatric disorders. Most nonsensory GPCRs are active in almost 90% of complex brain functions. At the time of receptor phosphorylation, a GPCR pathway is essentially activated through a G protein signaling mechanism via a G protein-coupled receptor kinase (GRK). Dopamine, an important neurotransmitter, is primarily involved in the pathophysiology of several CNS disorders; for instance, bipolar disorder, schizophrenia, Parkinson’s disease, and ADHD. Since dopamine, acetylcholine, and glutamate are potent neuropharmacological targets, dopamine itself has potential therapeutic effects in several CNS disorders. GPCRs essentially regulate brain functions by modulating downstream signaling pathways. GPR6, GPR52, and GPR8 are termed orphan GPCRs because they colocalize with dopamine D1 and D2 receptors in neurons of the basal ganglia, either alone or with both receptors. Among the orphan GPCRs, the GPR52 is recognized for being an effective psychiatric receptor. Various antipsychotics like aripiprazole and quetiapine mainly target GPCRs to exert their actions. One of the most important parts of signal transduction is the regulation of G protein signaling (RGS). These substances inhibit the activation of the G protein that initiates GPCR signaling. Developing a combination of RGS inhibitors with GPCR agonists may prove to have promising therapeutic potential. Indeed, several recent studies have suggested that GPCRs represent potentially valuable therapeutic targets for various psychiatric disorders. Molecular biology and genetically modified animal model studies recommend that these enriched GPCRs may also act as potential therapeutic psychoreceptors. Neurotransmitter and neuropeptide GPCR malfunction in the frontal cortex and limbic-related regions, including the hippocampus, hypothalamus, and brainstem, is likely responsible for the complex clinical picture that includes cognitive, perceptual, emotional, and motor symptoms. G protein and GPCR-mediated signaling play a critical role in developing new treatment options for mental health issues, and this study is aimed at offering a thorough picture of that involvement. For patients who are resistant to current therapies, the development of new drugs that target GPCR signaling cascades remains an interesting possibility. These discoveries might serve as a fresh foundation for the creation of creative methods for pharmacologically useful modulation of GPCR function.</jats:p

Financial and Mental Health Concerns of Impoverished Urban-dwelling Bangladeshi People During COVID-19

Background: The COVID-19 pandemic has impacted the physical, mental and financial health of many individuals. Individuals living in impoverished crowded settings may be particularly vulnerable to COVID-19-related stressors. How substantially marginalized groups like impoverished urban-dwelling individuals have been impacted during this pandemic is poorly understood. The present study aimed to investigate the associated factors of financial concerns and symptoms of depression and posttraumatic stress disorder (PTSD) during the COVID-19 pandemic among impoverished urban-dwelling individuals residing in Dhaka, Bangladesh. Methods: A cross-sectional survey was conducted between August and September 2020 using face-to-face interviews in six disadvantaged neighborhoods (“slums”) in Dhaka. Individuals were interviewed using a semi-structured questionnaire consisting of questions assessing socio-demographics, lifestyle, financial well-being relating to the COVID-19 pandemic, depression, and PTSD. Results: Four-hundred-and-thirty-five individuals (male = 54.7%; mean age = 45.0 ± 12.0 years; age range = 18–85 years) participated. Most (96.3%) reported that their household income decreased due to the COVID-19 pandemic. Factors associated with decreased household incomes included female gender, primary education, joblessness, food scarcity and depression. Depression symptoms were linked to female gender, joblessness, divorce, living in a joint family, excessive sleep and smoking. Low incomes, excessive sleep, joblessness and food scarcity were positively associated with PTSD symptoms. In contrast, less sleep appeared protective against PTSD. Conclusions: Public health initiatives, in particular mental health services that target stress and biocentric approaches that consider how humans interact with multiple facets of nature, should be introduced to mitigate against potential financial and psychological effects of the pandemic on impoverished urban-dwelling individuals in Bangladesh