Analytical Data Management Research Articles

The Effect of Compensation, Effectiveness of Communication and Promotion, on Employee Performance, PT. Artistic Creations Globalindo, Bekasi

This study aims to analyze how strong the influence of Compensation, Communication Effectiveness, and Promotion on Employee Performance partially, this research was conducted at PT. Globalindo Artistic Creations, Bekasi. This study was conducted using primary data obtained from the distribution of questionnaires, a population of 140 employees with a sample of 104 respondents. Management of analytical data using validity and reliability tests as well as regression and correlation tests using SPSS 20. Based on the results of the study, multiple regression equations Y = 1.034 + 0.233 X1 + 0.250 X2 + 0.492 X3 + e The results showed that Compensation (X1) has a positive influence on employee performance (Y), Communication Effectiveness (X2) has a positive influence on employee performance (Y) and Promotion Against (X3) has a positive influence on employee performance (Y). The result of the correlation between Compensation, Communication Effectiveness, and Promotion on employee performance (Y). And the results of the F Test of Compensation, Communication Effectiveness, and Promotion together have a positive and significant effect on Employee Performance

Enhancing IOT based software defect prediction in analytical data management using war strategy optimization and Kernel ELM

Enhancing IOT based software defect prediction in analytical data management using war strategy optimization and Kernel ELM

Glyphosate and Glufosinate Residues in Honey and Other Hive Products

Hive products have numerous beneficial properties; however, the hive's health is affected by the surrounding environment. The widespread use of herbicides in agriculture, such as glyphosate and glufosinate, has raised alarm among consumers, beekeepers, and environmentalists due to their potential to harm bees and humans through the consumption of bee products. This review aims to provide a comprehensive overview of the presence of glyphosate, glufosinate, and their metabolites in hive products, collecting and comparing available data from peer-reviewed research and surveys conducted across several countries. Moreover, it analyzes and discusses the potential impacts of these substances on human and bee health, analytical aspects, and recent regulatory developments. The data has revealed that these substances can be present in the different matrices tested, but the concentrations found are usually lower than the maximum residue limits set. However, the use of different methodologies with non-uniform analytical performances, together with an incomplete search for regulated analytes, leads to heterogeneity and makes comparisons challenging. In addition to the completion of studies on the toxicology of herbicide active ingredients, further monitoring actions are necessary, harmonizing analytical methodologies and data management procedures.

From research cohorts to the patient- a role for "omics" in diagnostics and laboratory medicine?

Human pathologies are complex and might benefit from a more holistic diagnostic approach than currently practiced. Omics is a concept in biological research that aims to comprehensively characterize and quantify large numbers of biological molecules in complex samples, e.g., proteins (proteomics), low molecular weight molecules (metabolomics), glycans (glycomics) or amphiphilic molecules (lipidomics). Over the past decades, respective unbiased discovery approaches have been intensively applied toinvestigate functional physiological and pathophysiological relationships in various research study cohorts. In the context of clinical diagnostics, omics approaches seem to have potential in two main areas: (i)biomarker discovery i.e. identification of individual marker analytes for subsequent translation into diagnostics (as classical target analyses with conventional laboratory techniques), and (ii) the readout ofcomplex, higher-dimensional signatures of diagnostic samples, in particular by means of spectrometric techniques in combination with biomathematical approaches of patternrecognition and artificial intelligence for diagnostic classification. Resulting diagnostic methods could potentially represent a disruptive paradigm shift away from current one-dimensional (i.e.,single analyte marker based) laboratory diagnostics. The underlying hypothesis of omics approaches for diagnostics is that complex, multigenic pathologies can be more accurately diagnosed via the readout of "omics-type signatures" than with the current one-dimensional single marker diagnostic procedures. While this is indeed promising, one must realize that the clinical translation of high-dimensional analytical procedures into routine diagnostics brings completely new challenges with respect to long-term reproducibility and analytical standardization, data management, and quality assurance. In this article, the conceivable opportunities and challenges of omics-based laboratory diagnostics are discussed.

REAL-TIME ANALYTICS: BENEFITS, LIMITATIONS, AND TRADEOFFS

Real-time analytics is a relatively new branch of analytics. A common definition of real-time analytics is that it consists in analyzing data as quickly as possible over the most recent data possible. This defines the essence of the fundamental needs of users, but in no way is a specific requirement for the corresponding software systems due to the vagueness of the definition. As a result, different manufacturers of analytical datamanagement systems and researchers classify real-time analytics systems as extremely different systems, which differ in architecture, functionality, and even timing. The purpose of this article is to analyze the different approaches to providing real-time analytics, their advantages and disadvantages, and the tradeoffs that both system designers and their users inevitably have to make.

Implementing Cooperative Integrated Reading and Composition (CIRC) Method to Enhance the Reading Comprehension of Indonesian EFL Learner

The objective of this research is to reveal the application of the Cooperative, Integrated Reading and Composition (CIRC) method to increase the reading comprehension of Indonesian EFL learners at junior schools. The CIRC method is one of the teaching methods that English teachers adjust to encourage their students to learn reading comprehension (Gupta & Ahuja, 2015); Zarei, 2012). One reason the researcher investigates reading is in the late time, the EFL learners are very less to spend their time on their reading habits (Derinalp, 2021). The EFL learners are very less to spend their time on their reading habits (Fan, 2016). Reading comprehension is one of the important skills of a language. Much information from the text form problematic issues (Riazi, 2017). It needs a complex skill to acquire this language skill. Therefore, the language learner who concerns with transforming information must prepare a strategy to work. This research applied a quasi-experimental method with a non-equivalent control group design. This study took the junior high school students in Parepare, Indonesia, as its subjects. Two groups of students were involved in the study, one as an experimental group and one as the control group. The data were collected using a comprehension test of the reading content. Management of analytical data was tested by the t-test and the accumulation of the percentage value. The results showed that CIRC improves the reading comprehension of Indonesian junior high students.

Napa

Google services continuously generate vast amounts of application data. This data provides valuable insights to business users. We need to store and serve these planet-scale data sets under the extremely demanding requirements of scalability, sub-second query response times, availability, and strong consistency; all this while ingesting a massive stream of updates from applications used around the globe. We have developed and deployed in production an analytical data management system, Napa, to meet these requirements. Napa is the backend for numerous clients in Google. These clients have a strong expectation of variance-free, robust query performance. At its core, Napa's principal technologies for robust query performance include the aggressive use of materialized views, which are maintained consistently as new data is ingested across multiple data centers. Our clients also demand flexibility in being able to adjust their query performance, data freshness, and costs to suit their unique needs. Robust query processing and flexible configuration of client databases are the hallmark of Napa design. Most of the related work in this area takes advantage of full flexibility to design the whole system without the need to support a diverse set of preexisting use cases. In comparison, a particular challenge we faced is that Napa needs to deal with hard constraints from existing applications and infrastructure, so we could not do a "green field" system, but rather had to satisfy existing constraints. These constraints led us to make particular design decisions and also devise new techniques to meet the challenges. In this paper, we share our experiences in designing, implementing, deploying, and running Napa in production with some of Google's most demanding applications.

Integration of chatbots into the system of professional training of Masters

The article presents and describes innovative technologies of training in the professional training of Masters. For high-quality training of students of technical specialties, it becomes necessary to rethink the purpose, results of studying and means of teaching professional disciplines in modern educational conditions. The experience of implementing the chatbot tool in teaching the discipline “Mathematical modeling of socio-economic systems” in the educational and professional program 124 System Analysis is described. The characteristics of the generalized structure of the chatbot information system for investment analysis are presented and given: input information, information processing system, output information, which creates a closed cycle (system) of direct and feedback interaction. The information processing system is represented by accounting and analytical data management blocks. The investment analysis chatbot will help masters of the specialty system analysis to manage the investment process efficiently based on making the right decisions, understanding investment analysis in the extensive structure of financial management and optimizing risks in these systems using a working mobile application. Also, the chatbot will allow you to systematically assess the disadvantages and advantages of investment projects or the direction of activity of a system analyst, while increasing interest in performing practical tasks. A set of software for developing a chatbot integrated into training is installed: Kotlin programming, a library for network interaction Retrofit, receiving and transmitting data, linking processes using the HTTP API. Based on the results of the study, it is noted that the impact of integrating a chatbot into the training of Masters ensures the development of their professional activities, which gives them the opportunity to be competent specialists and contributes to the organization of high-quality training.

Drugs analysis and citizens safety. Workflows for chemical analysis and structural elucidation of new psychoactive substances in the EU

NPS are novel synthesized compounds that are being produced by a slight alteration/modification in the chemical structure of existing illegal substances, already registered in the European Union (EU). A number of products imported from non-EU countries, which have not been necessarily controlled under international law, may be subject to monitoring in agreement with EU legislation.In order to proper establish the chemical identity of seized substances, there is a need to use specific analytical workflows. The latter, many times not available in normal control laboratories, involve the use of powerful instrumentation such as 1H and 13C nuclear magnetic resonance (NMR), high-resolution tandem mass-spectrometry (HR-MS), UV/IR and Raman spectroscopy. The time needed for detailed analysis and interpretation of the results demands considerable commitment. A way to maximize this analysis is to employ modern chemoinformatic platforms, which can promote the management and centralisation of analytical data from multiple techniques and instruments, as well as combining tentative identifications with predicted chemical and structural information.The paper presents and discusses existing workflows for monitoring, communication and management of analytical data regarding the structural elucidation and chemical identification of NPS seized in EU by member states customs services, which are of high importance for the safety and security of citizens. The dissemination of all the received information between control authorities strives to help and protect EU citizens by harmful substances. In addition the paper provides an interesting link between safety and security by indicating ways to extend the proposed methodology.

Cloud computing with AI for banking and e-commerce applications

PurposeIn cloud computing, banking knowledge with business intelligence (BI) will be a better option for the users, and the users do not have an overall picture of the whole thing until the entire job is completed.Design/methodology/approachAlthough the constraints are costly, complex, inflexible and integrated BI infrastructures, it helps to combine the banking and electronic commerce (EC) application data. Furthermore, this paper explores cloud computing infrastructure as a potential remedy for data processing issues.FindingsA modern cloud computing with artificial intelligence, environmental climate to shorten periods for BI delivery, rising the expense of BI programs relatively with traditional BI of EC applications, provide customers with the ability for quicker rollout and better flexibility to incorporate research and to improve the performance, accuracy and efficiency.Originality/valueIn the technological world of today, the new era of BI analytical data management has been established with certain restrictions on the adoption of BI.

Quality and assurance control management of analytical data in the case of biomonitoring

The industrial development of the Arctic is steadily increasing, which leads to the degradation of the ecosystems of the region. In case of ecological biomonitoring of fragile Arctic nature, the quality of the analytical work and the accuracy of the results obtained come to the fore. Accreditation of analytical laboratories provides confidence and recognition of its results. Verification of the qualifications of analytical laboratories through interlaboratory comparison tests conducted under international programs allows an objective assessment of the quality of the analysis results, compare the data with other laboratories, demonstrate technical competence, and provide additional confidence in the quality of research results obtained by the laboratory.

Procedures for systematic capture and management of analytical data in academia

Data management in universities is a challenging endeavor in particular due to the diverse infrastructure of devices and software in combination with limited budget. Nevertheless, in particular the analytical measurements and data sets need to be stored if possible digitally and in a well-organized manner. This manuscript describes how scientists can achieve a data management workflow focusing on data capture and storage by small adaptions to commonly used systems. The presented method includes data transfer options from ubiquitous devices like NMR instruments, GC (MS) or LC (MS), IR and Raman, or mass spectrometers to a central server and the visualization of the available data files in an electronic lab notebook (ELN). The given instruments were chosen according to the needs of synthetic chemists, in particular devices needed in organic, inorganic and polymer chemistry where single data files in the range of several megabytes per data set are produced. Altogether, three different data transfer systems were elaborated to allow a flexible handling of different devices running with different proprietary software: The first procedure allows data capture via the use of a mail server as data exchange point. With the second procedure, data are automatically mirrored from a local file folder to a central storage server where new files are monitored and processed. The third procedure was designed to transfer data with manual support to a central server which is supervised to register new information. All components that are necessary to install and use the herein elaborated functions are available as Open Source and the designed workflows are described step by step to facilitate the adaption of procedures in other universities accordingly if desired.

Top ten errors of statistical analysis in observational studies for cancer research.

Observational studies using registry data make it possible to compile quality information and can surpass clinical trials in some contexts. However, data heterogeneity, analytical complexity, and the diversity of aspects to be taken into account when interpreting results makes it easy for mistakes to be made and calls for mastery of statistical methodology. Some questionable research practices that include poor analytical data management are responsible for the low reproducibility of some results; yet, there is a paucity of information in the literature regarding specific statistical pitfalls of cancer studies. In addition to proposing how to avoid or solve them, this article seeks to expose ten common problematic situations in the analysis of cancer registries: convenience, dichotomization, stratification, regression to the mean, impact of sample size, competing risks, immortal time and survivor bias, management of missing values, and data dredging.

HadoopDB

The production environment for analytical data management applications is rapidly changing. Many enterprises are shifting away from deploying their analytical databases on high-end proprietary machines, and moving towards cheaper, lower-end, commodity hardware, typically arranged in a shared-nothing MPP architecture, often in a virtualized environment inside public or private "clouds". At the same time, the amount of data that needs to be analyzed is exploding, requiring hundreds to thousands of machines to work in parallel to perform the analysis. There tend to be two schools of thought regarding what technology to use for data analysis in such an environment. Proponents of parallel databases argue that the strong emphasis on performance and efficiency of parallel databases makes them well-suited to perform such analysis. On the other hand, others argue that MapReduce-based systems are better suited due to their superior scalability, fault tolerance, and flexibility to handle unstructured data. In this paper, we explore the feasibility of building a hybrid system that takes the best features from both technologies; the prototype we built approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce-based systems.

Application of Six Sigma Methods for Improving the Analytical Data Management Process in the Environmental Industry

AbstractHoneywell applied the rigorous and well‐documented Six Sigma quality‐improvement approach to the complex, highly heterogeneous, and mission‐critical process of remedial site environmental data management to achieve a sea change in terms of data quality, environmental risk reduction, and overall process cost reduction. The primary focus was to apply both qualitative and quantitative Six Sigma methods to improve electronic management of analytical laboratory data generated for environmental remediation and long‐term monitoring programs. The process includes electronic data delivery, data QA/QC checking, data verification, data validation, database administration, regulatory agency reporting and linkage to spatial information, and real‐time geographical information systems. Results of the analysis identified that automated, centralized web‐based software tools delivered through Software as a Service (SaaS) model are optimal to improve the process resulting in cost reductions, while simultaneously improving data quality and long‐term data usability and perseverance. A pilot project was completed that quantified cycle time and cost improvements of 50% and 65%, respectively.

Analytical Data Management System without Delays ACD/SpecManager

Analytical Data Management System without Delays ACD/SpecManager

Project Management in Construction: Software Use and Research Directions

This paper focuses on future research and the use of project management software in the construction industry. Data are drawn from an empirical study of project management professionals that yielded 240 replies (35% response rate), 42 of which were from the construction industry. Data were collected on: demographics and work environment, project management software usage patterns, analytical technique usage, data management, and suggestions for future research. The results indicate that construction professionals have different characteristics, needs and preferences, as compared to the overall sample. The study shows that construction professionals are more experienced and educated than the respondents in the overall study, they tend to work on fewer projects with larger numbers of activities, and they are more likely to use Primavera (Primavera, Inc., Bala Cynwyd, Pa.) than Microsoft Project (Microsoft Corp., Redmond, Wash.). Construction respondents are heavy users of critical path analysis for planning and control, resource scheduling for planning, and earned value analysis for control. The number of activities in a typical project and the use of software for all active projects were the key determinants of the usage of specific analytical techniques. These factors are also significant determinants of the types of information entered and updated, although the effect is weaker. Although construction professionals are generally satisfied with the quality of schedules produced by the software, they still expressed a clear interest in future research on resource scheduling/leveling in general and a net present value option in particular. To maximize the impact on practice, development of new planning and control methods should include their integration into project management software.

Computer science based solution for a water quality control laboratory management

The National Office of Potable Water (ONEP) is a public body in charge of the production, control and distribution of potable water throughout the Kingdom of Morocco. The ONEP Central Laboratory and a network of 46 decentralised laboratories are in charge of monitoring the quality of produced and distributed water, as well as pollution control of resources intended for drinking water production. In order to perform this activity, ONEP laboratories follow a variety of sampling points and type of samples (treated water, raw water, waste water, sludge from sewage works, treatment reagents, etc.) depending on the objective of control. The variety of biological and physicochemical analyses as well as the significant number of data generated by ONEP laboratories has speedily imposed the need for a data computer management. The ONEP Central Laboratory has developed a computer-based application for laboratory management (GDAL). This application was devised and adopted to satisfy the present and future needs of the Central Laboratory. The pro-software was developed under Power Builder within windows environment (NT and 95). It manages more than 3500 sampling sites throughout Morocco, that is more than 30,000 samples or 1 million items of analytical data, and enables the editing of more than 20 types of analytical reports. This system is intended for 21 users simultaneously and allows the management of analytical data of the central and decentralised laboratories. The system is developed into modules covering all sample life cycle which comprise (1) analysis campaign planning, (2) management of sample-taking missions, (3) samples reception, (4) analysis, (5) invoicing, (6) consultation and printing, (7) processing analytical data provided by the system. GDAL also comprises the laboratory administrative and stock management, and accounting. This application aims to: (a) enable each user to have access to the information about samples analysis in real time; (b) automate everyday tasks of the laboratory; (c) ensure the follow-up of all the information concerning the analysis from planning the sampling to editing the analytical report; (d) improve the accuracy of the results by automating the quality control procedures.

Évaluation du mercury 16 (nova biomedical) : application aux profils d'urgence et de routine sur sang total et urine en néphrologie

The aim of this work was to assess the performances of Mercury 16 (sodium, potassium, chloride, total CO 2, glucose, urea, creatinine and hematocrit on whole blood, plasma, serum, urine, dialysate and cerebrospinal fluid) in following critical situations: use without formation, use with minimal maintenance and short laboratory responses time (less than 5 min.) on whole blood and urine and on icteric samples. The results obtained on whole blood and plasma were quite similar and the correlations between Mercury 16 - whole blood, CX7 Delta (Beckman) and STKS (Coulter) before and after dialysis (30 patients) were highly significant. Considering the well known potential bilirubin interference on glucose, creatinine and blood urea nitrogen determinations, our study showed the insensitivity of Mercury 16 to bilirubin (concentrations up 200 μmol/L to 700 μmol/L as total bilirubin). The correlations between Mercury 16 and CX7 Delta in 42 urine were highly significant. Finally, considering the analytical specifications, the short and easy maintenance, the management of analytical and patient data and reagents, the turnaround time (less than 2 min. for all mesured tests), the possibility of a link (direct or via a specific station) to central laboratory system, Mercury 16 is well adapted to any critical care situations and so, to point care of testing, in agreement with GBEA and Société française de biologie clinique recommendations.

Application of a new AMIQAS computer program for integrated quality control, method evaluation and proficiency testing

The computer program AMI - Quality Assessment Scheme (AMIQAS) was designed to give easy statistical management of analytical data in relation to method evaluation, internal quality control and proficiency testing. The program is designed in accordance with the recommendation of the ISO 5725 guideline and other official recommendations. The program consists of a database, test for outliers, statistics and graphs for evaluation of an analytical method for chemical, biological and environmental analysis, different control charts to be used in day-to-day internal quality control (Shewhart charts and z-charts). Finally the program has facilities to perform proficiency testing (also called external quality control) and produce the relevant evaluation reports for the documentation of method performance and quality control of results of measurements. The present paper demonstrates the applicability of the AMIQAS program for integrated method evaluation, internal quality control and proficiency testing using the determination of the concentration of lead in human whole blood as the numerical example.