Large Vendors Research Articles

Особенности утечек информации ограниченного доступа в Российской Федерации

According to official data, over the past year the number of personal data leaks has increased 4 times. The number of published personal data in 2023 exceeds the total population of the Russian Federation by 50 million. The study systematizes the statistics of information leaks in the context of impact factors and the composition of leaked user information in 2022-2023. In the course of analyzing statistical data from the largest vendors in Russia, the main characteristic features of personal data leaks in 2023 were identified and the vulnerabilities of domestic cyberspace were identified. The author identified the imperfections of legislative regulation of the processes of ensuring comprehensive protection of personal data and proposed directions for leveling the identified vulnerabilities.

A data decomposition-based hierarchical classification method for multi-label classification of contractual obligations for the purpose of their governance

Contract governance ensures that the agreed outcomes between customers and vendors are fulfilled. Information Technology (IT) outsourcing organizations enter thousands of contractual relationships each month leading to a high volume of business-critical contractual text that must be reviewed and deciphered for effective governance. The key to effective governance of contracts is a model that facilitates assigning ownership of the obligations to the right departments in an organization and allocating their accountability to the right stakeholders. For this, the contractual obligations need to be identified and classified so that details such as actions to be taken by departments in an organization and their ownership as per a given clause are brought out for the purpose of governance. In this paper, we present our work on automated extraction and classification of obligations present in Software Engineering (SE) contracts for the purpose of contracts governance. We propose a novel data decomposition-based hierarchical classification method for a multi-label classification of contractual obligations. We conducted experiments for a fine-grained automated classification of more than 55,000 statements from 50 large real-life SE contract documents received from a large vendor organization into 152 governance-specific classes. The results indicate that the proposed method can bring about a 7–8% improvement in accuracies when compared to state-of-the-art classification baselines such as BERT, RoBERTa, and generative models such as GPT-2.

BigDaM: Efficient Big Data Management and Interoperability Middleware for Seaports as Critical Infrastructures

Over the last few years, the European Union (EU) has placed significant emphasis on the interoperability of critical infrastructures (CIs). One of the main CI transportation infrastructures are ports. The control systems managing such infrastructures are constantly evolving and handle diverse sets of people, data, and processes. Additionally, interdependencies among different infrastructures can lead to discrepancies in data models that propagate and intensify across interconnected systems. This article introduces “BigDaM”, a Big Data Management framework for critical infrastructures. It is a cutting-edge data model that adheres to the latest technological standards and aims to consolidate APIs and services within highly complex CI infrastructures. Our approach takes a bottom-up perspective, treating each service interconnection as an autonomous entity that must align with the proposed common vocabulary and data model. By injecting strict guidelines into the service/component development’s lifecycle, we explicitly promote interoperability among the services within critical infrastructure ecosystems. This approach facilitates the exchange and reuse of data from a shared repository among developers, small and medium-sized enterprises (SMEs), and large vendors. Business challenges have also been taken into account, in order to link the generated data assets of CIs with the business world. The complete framework has been tested in the main EU ports, part of the transportation sector of CIs. Performance evaluation and the aforementioned testing is also being analyzed, highlighting the capabilities of the proposed approach.

Reflections on the history of interoperability in hospitals.

To discuss the origins of HL7 and its subsequent impact on interoperability in hospitals. Reconstruction of historical events from review of personal notes, interviews with key participants and review of relevant publications. The first versions of HL7 were based on the StatLAN protocol developed at the University of California, San Francisco and later commercialized by Simborg Systems Corporation. With the emergence of specialty clinical and departmental systems in the 1990s, a debate ensued between proponents of "open architecture" vs. "single vendor" systems. Although HL7 became the most widely used data-interchange protocol worldwide in healthcare, open architecture did not prevail in healthcare as it did in other industries. This is due to the unique market characteristics of the healthcare provider industry. The result today is the dominance of the healthcare IT marketplace by a small number of large vendors with relatively few options for in-depth specialty clinical systems.

Four 2023 ACS regional meetings open calls for papers

Organized by local sections of the American Chemical Society, ACS regional meetings provide technical programs and poster sessions, as well as expositions and social events. Abstract submissions are being accepted for four regional meetings taking place in the fall. Joint Midwest–Great Lakes Regional Meeting The Saint Louis Section and East Central Illinois Local Section invite abstract submissions to the 2023 Joint Midwest–Great Lakes Regional Meeting of the American Chemical Society (MWRM–GLRM). The meeting will take place Oct. 18–21 at the Saint Charles Convention Center in Saint Charles, Missouri. The meeting, whose theme is “Scale Up Your STEM,” will feature plenary speakers, technical sessions and special symposia, poster sessions, regional award presentations, social events, and a large vendor exposition. In addition, there will be undergraduate programming, chemistry education workshops for high school teachers, and events sponsored by the local Younger Chemists Committee and the Minority Affairs Committee. Details can be found

A Descriptive Analysis of Redemption Patterns by Vendor Type Among: WIC Participants in Massachusetts.

The retail environment is an important determinant of food package redemption in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). The objectives of this study were to describe where Massachusetts WIC households redeemed their food benefits each month and monthly variations in benefit redemption depending on a household's most frequently used vendor type each month. These were cross-sectional and longitudinal analyses of administrative data provided by Massachusetts WIC. Monthly redemption data for 209,973 households shopping at approximately 1,000 unique vendors between January 2015 and August 2019 were analyzed. Outcomes were mean monthly percentage of households that relied on each vendor type when redeeming benefits and mean monthly percent redemption for each benefit category. For each month, households were classified as using 1 of 8 vendor types. The monthly percentage of households redeeming at each vendor type was calculated, as well as the monthly percent redemption for each benefit category by vendor type. The averages of these monthly percentages were computed for 2015 and 2019. Data from months when households did not redeem any benefits were excluded from primary analyses because it was not possible to determine their vendor type for that month. On average across months in 2019, the majority of Massachusetts WIC households (63%) relied on large vendors only (ie, superstores, supermarkets, and large grocery stores) when redeeming benefits, and 5% relied on small grocery or convenience stores only. Between 2015 and 2019, mean monthly reliance on small grocery and convenience stores decreased by 3.1 and 0.7 percentage points, respectively. Compared with other vendor types, households that redeemed benefits at superstores only had, in an average month, lower redemption levels for most benefit categories. For example, in the 2019 mean across months, percent redemption of breakfast cereal was 53% among households redeeming at superstores only compared with 74% for those redeeming at small grocery stores only. By contrast, households that relied on small grocery stores only had, in an average month, lower redemption levels for yogurt and cash value benefit compared with other vendor types; for example, in the 2019 mean across months, percent redemption of yogurt was 34% among households redeeming at small grocery stores only compared with 62% among those redeeming at supermarkets only. Results suggest that retail-based efforts to increase redemption should consider vendor-type reliance. Strategies to increase redemption may be especially important for WIC shoppers relying on superstores.

Large vendor’s capability and relationship management: An idea of winning contract mechanism in B2B

Large vendor’s capability and relationship management: An idea of winning contract mechanism in B2B

Collaborative Artificial Intelligence in Practice: The Next Steps.

Collaborative Artificial Intelligence in Practice: The Next Steps.

Next Generation Parking System with Computer Vision and Machine Learning

Parking management is a term that describes methods for making better use of parking resources. The first step toward successful parking management is to identify the cause of the problem. Finding suitable parking is among the fastest-growing industries of all, given the ever-increasing number of cars on the road. Traditionally, traffic has been a nightmare. To address these issues, businesses adopted intelligent parking systems from large hardware vendors. These, on the other hand, are unfit for purpose and also have resulted in major parking issues at many businesses. The approach attempts to offer a practical answer to the problem of smart parking. We aim to create a functioning software that will inform requesting customers if there is still a free parking spot near their location using technologies like Machine Learning, CNN, OpenCV, and React.

Shifting Priorities: A Look at a Course Adopted Text (CATs) e-Book Program and How Its Success Realigned One Library’s e-Book Collection Priorities

Like many academic librarians, St. Norbert College collection librarians have been trying to find the right configuration of e-book acquisition strategies to meet our users’ needs. Since 2017, St. Norbert’s strategy had been a combination of a subscription to a large vendor package, multiple evidence-based acquisition (EBA) programs, and one-time orders of e-books purchased as a part of faculty departmental requests. In Fall 2018, St. Norbert Library started a partnership with the campus bookstore, began receiving the list of course adopted texts (CATs), and launched a new and parallel e-book strategy of purchasing unlimited access e-books for CATs. This study provides data on the reach and growth of St. Norbert Library’s CATs e-books program, including the number of courses and types of courses affected by library supplied CATs e-books, and the types and publishers of library supplied CATs. As the CATs program grew so did the costs to support it and St. Norbert determined to investigate the usage of the CATs e-books compared to its concurrently licensed EBA content and evaluate the compatibility and sustainability of its CATs and EBA programs. Discussions detail why St. Norbert came to value CATs e-books over EBA e-books, how, despite the potential for symbiosis, St. Nobert’s determined its EBAs to be incompatible with its CATs program, and why the St. Norbert Library decided not to continue both the EBA and the CATs programs. Conclusions discuss CATs e-book successes and how developing, sustaining, and continuing to evolve the CATs e-book program has been integral to St. Norbert Library’s collection moving in new strategic directions.

Assessing hospital electronic health record vendor performance across publicly reported quality measures.

Little is known regarding variation among electronic health record (EHR) vendors in quality performance. This issue is compounded by selection effects in which high-quality hospitals coalesce to a subset of market leading vendors. We measured hospital performance, stratified by EHR vendor, across 4 quality metrics. We used data on 1272 hospitals in 2018 across 4 quality measures: Leapfrog Computerized Provider Order Entry/EHR Evaluation, Centers for Medicare and Medicaid Services Hospital Compare Star Ratings, Hospital-Acquired Condition (HAC) score, and Hospital Readmission Reduction Program (HRRP) ratio. We examined score distributions and used multivariable regression to evaluate the association between vendor and score, recovering partial R2 to assess the proportion of quality variation explained by vendor. We found significant variation across and within EHR vendors. The largest vendor, vendor A, had the highest mean score on the Leapfrog Computerized Provider Order Entry/EHR Evaluation and HRRP ratio, vendor G had the highest Hospital Compare score, and vendor F had the highest HAC score. In adjusted models, no vendor was significantly associated with higher performance on more than 2 measures. EHR vendor explained between 1.2% (HAC) and 7.6 (HRRP) of the variation in quality performance. No EHR vendor was associated with higher quality across all measures, and the 2 largest vendors were not associated with the highest scores. Only a small fraction of quality variation was explained by EHR vendor choice. Top performance on quality measures can be achieved with any EHR vendor; much of quality performance is driven by the hospital and how it uses the EHR.

Value Creation Analysis: Semiconductor Intellectual Property Business Models and Dynamic Capabilities

Semiconductor intellectual property (SIP) represents a crucial component of integrated circuit design activities. However, many small SIP firms fail to create value and adopt a viable business model. This article aims to investigate the value creation mechanism within the SIP business by drawing on the business model and dynamic capabilities views of the firm. First, the authors classify the forms and types of SIP from a technology and market perspective. Analyzing ten leading SIP firms, three SIP business models based on resources, competencies, and strategies are then identified. Dynamic capabilities are then linked to the selection and implementation of classified business models. Findings of the study suggest that existing SIP business models primarily favor large vendors. Keystone business model is proposed as a possible successful business model for small vendors. Consequently, this article provides insights and opportunities for leveraging the SIP ecosystem and business model innovation for small firms in the industry.

Program for organizing the work of hybrid and multi-provider cloud structures of the enterprise

The article discusses the advantages of the cloud model “infrastructure as a service”, a way to solve the problem of integrating an enterprise with a cloud infrastructure if a full transition to cloud computing in public cloud systems is unacceptable for various reasons. As an option to solve the problem, it is proposed to organize a hybrid cloud cluster from the existing equipment of the enterprise and the public cloud of one or more providers. The issue of building multi-provider cloud structures, the limitations of the current way of managing virtual machines, the features of organizing virtual cloud data centers and their structure are considered, a comparison is made of the classic model for deploying server applications with a model managed by a load balancer on virtual machines. As a means of organizing and managing a hybrid and complex cloud, the Nebula Cloud software package is proposed, its capabilities, structure, modules, technology and method of work, results of test implementations are described. The results of comparing the software package being developed with the closest competing analogues of large vendors are given, conclusions are made about the prospects for using the software package and plans for further research with the aim of increasing the speed, efficiency and fault tolerance of virtual machines.

Assessing the suitability of the Greenhouse Gas Protocol for calculation of emissions from public cloud computing workloads

Efficiency improvements over the past decade have meant that data center energy usage has decoupled from the growth in IT workloads. Much of this efficiency improvement has been attributed to innovations made by “hyperscale” public cloud vendors, where a large proportion of new IT workloads are now being deployed. However, the move to the cloud is making it more difficult to assess the environmental impact of workloads deployed there. Although the large cloud vendors are amongst the largest purchasers of renewable electricity, customers do not have access to the data they need to complete emissions assessments under the Greenhouse Gas Protocol. Data such as Power Usage Effectiveness, emissions factors and equipment embodied energy are not available from public cloud vendors. This paper demonstrates how the Greenhouse Gas Protocol method of assessment of IT emissions does not work for public cloud environments and suggests how this can be tackled by the cloud vendors themselves.

The Sustained Improvements in E-commerce Business through Big Data and Data Analytics of Wal-Mart Company

Today e-commerce is the latest worldwide way of doing business trading. Growing innovations like the internet, network and satellite technology allow companies to move to online businesses. Today e-commerce has an infinite influence on the culture that changes the way people around the world do their lives. This has huge consequences for manufacturers, distributors, dealers, wholesalers, and customers. There are plenty of businesses coming forward and beginning e-commerce business from the last 6 decades so that eighty percent of companies have achieved enormous market success. Nowadays, the progress of e-commerce is largely continuing, as it is now compulsory for the company to carry out data analytics to withstand the market. A lot of data will be generated in various aspects such as advertisement, information exchange, order and payment, delivery, customer support, and customer reviews when trading through the internet. The company's main challenge is how to use the data to further improve the product. These companies are now creating a research department that performs data analysis using different technologies and makes a good contribution to the profit of companies and helps the company to make good decisions. Wal-Mart is the largest vendor in the United States and has also expanded its market in twenty-eight countries around the world. Now it was struggling to keep in top position because of the enormous competition from other firms. It was, therefore, premeditated to use excessive amounts of the present dataset from the past several years to analyze it using special research teams. This paper examined the various elements of the e-commerce industry, the list of possible data produced in e-commerce, the need for data analysis in e-commerce, the challenges of performing data analysis in e-commerce, the technologies needed to achieve data analysis in e-commerce, how companies use the dataset to survive on the market and how Wal-Mart company performs data analytics to understand business scenario.

Which Came First, it or Productivity? Virtuous Cycle of Investment and Use in Enterprise Systems

While it is now well established that IT intensive firms are more productive, a critical question remains: Does IT cause productivity or are productive firms simply willing to spend more on IT? We address this question by examining the productivity and performance effects of enterprise systems investments in a uniquely detailed and comprehensive data set of 623 large, public U.S firms. The data represent all U.S. customers of a large vendor during 1998-2005 and include the vendor's three main enterprise system suites: Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM). A particular benefit of our data is that they distinguish the purchase of enterprise systems from their installation and use. Since enterprise systems often take years to implement, firm performance at the time of purchase often differs markedly from performance after the systems go live. Specifically, in our ERP data, we find that purchase events are uncorrelated with performance while go-live events are positively correlated. This indicates that the use of ERP systems actually causes performance gains rather than strong performance driving the purchase of ERP. In contrast, for SCM and CRM, we find that performance is correlated with both purchase and go-live events. Because SCM and CRM are installed after ERP, these results imply that firms that experience performance gains from ERP go on to purchase SCM and CRM. Our results are robust against several alternative explanations and specifications and suggest that a causal relationship between ERP and performance triggers additional IT adoption in firms that derive value from their initial investment. These results provide an explanation of simultaneity in IT value research that fits with rational economic decision-making: Firms that successfully implement IT, react by investing in more IT. Our work suggests replacing either-or views of causality with a positive feedback loop conceptualization in which successful IT investments initiate a virtuous cycle of investment and gain. Our work also reveals other important estimation issues that can help researchers identify relationships between IT and business value.

The Sustained Improvements in E-commerce Business through Big Data and Data Analytics of Wal-Mart Company

Today e-commerce is the latest worldwide way of doing business trading. Growing innovations like the internet, network and satellite technology allow companies to move to online businesses. Today e-commerce has an infinite influence on the culture that changes the way people around the world do their lives. This has huge consequences for manufacturers, distributors, dealers, wholesalers, and customers. There are plenty of businesses coming forward and beginning e-commerce business from the last 6 decades so that eighty percent of companies have achieved enormous market success. Nowadays, the progress of e-commerce is largely continuing, as it is now compulsory for the company to carry out data analytics to withstand the market. A lot of data will be generated in various aspects such as advertisement, information exchange, order and payment, delivery, customer support, and customer reviews when trading through the internet. The company's main challenge is how to use the data to further improve the product. These companies are now creating a research department that performs data analysis using different technologies and makes a good contribution to the profit of companies and helps the company to make good decisions. Wal-Mart is the largest vendor in the United States and has also expanded its market in twenty-eight countries around the world. Now it was struggling to keep in top position because of the enormous competition from other firms. It was, therefore, premeditated to use excessive amounts of the present dataset from the past several years to analyze it using special research teams. This paper examined the various elements of the e-commerce industry, the list of possible data produced in e-commerce, the need for data analysis in e-commerce, the challenges of performing data analysis in e-commerce, the technologies needed to achieve data analysis in e-commerce, how companies use the dataset to survive on the market and how Wal-Mart company performs data analytics to understand business scenario.

An On-Treatment Analysis of the MARQUIS Study: Interventions to Improve Inpatient Medication Reconciliation.

It is unclear which medication reconciliation interventions are most effective at reducing inpatient medication discrepancies. Five United States hospitals' interdisciplinary quality improvement (QI) teams were virtually mentored by QI-trained physicians. Sites implemented one to seven evidence-based interventions in 791 patients during the 25-month implementation period. Three interventions were associated with significant decreases in potentially harmful discrepancy rates: (1) defining clinical roles and responsibilities, (2) training, and (3) hiring staff to perform discharge medication reconciliation. Two interventions were associated with significant increases in potentially harmful discrepancy rates: training staff to take medication histories and implementing a new electronic health record (EHR). Hospitals should focus first on hiring and training pharmacy staff to assist with medication reconciliation at discharge and delineating roles and responsibilities of clinical staff. We caution hospitals implementing a large vendor EHR, as medication discrepancies may increase. Finally, the effect of medication history training on discrepancies needs further study.

Vendor of choice and the effectiveness of policies to promote health information exchange

BackgroundAs more hospitals adopt Electronic Health Records (EHR), focus has shifted to how these records can be used to improve patient care. One barrier to this improvement is limited information exchange between providers. In this work we examine the role of EHR vendors, hypothesizing that vendors strategically control the exchange of clinical care summaries. Their strategy may involve the creation of networks that easily exchange information between providers with the same vendor but frustrate exchange between providers with different vendors, even as both Federal and State policies attempt to incentivize exchange through a common format.MethodsUsing data from the 2013 American Hospital Association’s Information Technology Supplement, we examine the relationship between a hospital’s decision to share clinical care summaries outside of their network and EHR vendor market share, measured by the percentage of hospitals that have the same vendor in a Hospital Referral Region.ResultsOur findings show that the likelihood of a hospital exchanging clinical summaries with hospitals outside its health system increases as the percentage of hospitals with the same EHR vendor in the region increases. The estimated odds of a hospital sharing clinical care summaries outside their system is 5.4 (95% CI, 3.29–8.80) times greater if all hospitals in the Hospital Referral Region use the same EHR Vendor than the corresponding odds for a hospital in an area with no hospitals using the same EHR Vendor. When reviewing the relationship of vendor market concentration at the state level we find a positive significant relationship with the percentage of hospitals that share clinical care summaries within a state. We find no significant impact from state policies designed to incentivize information exchange through the State Health Information Exchange Cooperative Program.ConclusionThere are benefits to exchanging using proprietary methods that are strengthened when the vendors are more concentrated. In order to avoid closed networks that foreclose some hospitals, it is important that future regulation attempt to be more inclusive of hospitals that do not use large vendors and are therefore unable to use proprietary methods for exchange.

Dissertation to Book? A Snapshot of Dissertations Published As Books in 2014 and 2015, Available in Open Access Institutional Repositories

INTRODUCTION Graduate students sometimes express consternation about whether the presence of their dissertation in an open access institutional repository (IR) will harm their chances of being able to publish the manuscript as a book. Several studies have addressed the question from different perspectives, but the avenue of examining what had actually been published had not been explored. METHODS This study examines books published in 2014 and 2015 that were listed as dissertations in one large book vendor database. A list of books was downloaded and searched in both ProQuest’s Dissertations & Theses Global database and Google to identify a matching dissertation. RESULTS Only a small percentage of books published as dissertations were found in ProQuest and then subsequently in IRs. The number of libraries holding book titles with corresponding dissertations in IRs dropped between 2014 and 2015. The lists of publishers who published dissertations as books was very similar between 2014 and 2015 data and included large, commercial publishers. DISCUSSION Students should be aware that only a small percentage of the total number of dissertations produced in a year are subsequently published as books, that the time between dissertation and book publication is substantial, and that some subject areas are more likely to be published than others. CONCLUSION These findings provide nuance to the discussions of dissertations in open access repositories and a starting point to monitor trends in this area. They should also provide librarians who are providing supplementary guidance to graduate students with information about the publishing landscape.