Hasil untuk "Management information systems"

Prashant K. Aher, Sanjaykumar L. Patil, Uttam M. Chaskar et al.

Battery management systems (BMS) rely heavily on estimating the state of charge (SOC) as the foundation for controlling other functionalities. Significant advancements in the use of non-linear Kalman filters (KFs) aim to address the growing need for model-based state estimation in BMS. The KFs are robust enough to handle the effects of process and sensor noise. However, KFs cannot entirely eradicate the inherent battery model error. Consequently, the precision of SOC estimation heavily relies on the model’s accuracy. Despite this importance, the precise quantitative correlation between the model and SOC estimation accuracy still needs to be discovered. This article outlines and validates three equivalent-circuit battery models, followed by SOC estimation using the extended Kalman filter under real-time operating conditions. The 2RCH battery model outperforms the others, achieving root-mean-square errors (RMSE) that are 1 mV, 9 mV, and 12 mV lower than those of the 2RC model across three different drive profiles. Correlation and regression analyses of the normalized RMSE and standard deviation are performed to compare the model error and SOC estimation error. The Pearson correlation coefficients of 0.9087 and 0.9175 in the first and second cases, respectively, reveal a strong linear relationship between these parameters. This study examines two metrics to determine how model accuracy affects SOC estimation accuracy: overall error level and the dispersion of the error frequency distribution. The analytical expressions established in this work provide significant information for reliability evaluation to implement a robust control plan in BMS. Additionally, it can be conveniently adapted to evaluate and predict the SOC estimation error when KF-based SOC estimation is employed. The novelty of this work is in quantitatively establishing the link between battery model accuracy and SOC estimation accuracy in a Kalman Filter–based framework, which has not been widely reported.

Maryna V. Kovbatiuk, Ivanna I. Strilok, Viktoriya V. Shklyar et al.

Modern realities indicate that improving the efficiency of management processes is impossible without the use of information and software that should be integrated into the management system. Therefore, the article explores the importance of this integration in the context of globalized markets, emphasizing its role in increasing competitiveness, introducing innovations and making operational and strategic decisions. It is noted that the main advantages of integration are: increased management efficiency through automation of routine tasks, increased control over own operations; improved coordination between departments through the use of a single database, simplification of information exchange and promotion of more effective cooperation; informed decision-making through access to real-time data; reduction of costs for personnel, paper and other resources; gaining competitive advantages in such areas as marketing, sales, production and logistics. It is emphasized that the information support of international enterprises has moved to a new level, where information has not only become an information resource, but also performs important functions in management. By using advanced analytics and business intelligence tools, international companies can gain strategic insights for further development, identify market trends, and make informed operational decisions that meet their current and global goals. The existing unified software of the leading ERP-systems vendors that can be used in the management of an enterprise, in particular, an international company, is analyzed. Given that the changing conditions of enterprise functioning require an individual approach and the creation of a custom-made product, a comparative characterization of unified and individual software products is carried out. An example of individual software products that take into account the specifics of certain enterprises is the software developed with the participation of the authors for enterprises in the water transport and insurance industries. With a view to optimizing the process of using information and software in the management of an international enterprise, the authors propose an appropriate mechanism. For its successful implementation, it is necessary to take into account that the integration of information technology is a complex process that requires careful planning and implementation, in particular, the factor of financing and staff training. As modern international businesses continue to evolve and adapt to change, the use of information and software is becoming a critical success factor. High-tech management solutions allow companies to respond effectively to global market challenges and remain competitive in an ever-changing business environment.

Ourania Areta Hiziroglu, Onur Dogan

Organizations face significant challenges in measuring and enhancing sustainability performance across complex operational processes. Current assessment methods frequently lack granularity, real-time capability, and integration with operational data. This study addresses these gaps by developing a conceptual framework that integrates business process mining with Global Reporting Initiative (GRI) metrics. The methodology incorporates environmental, social, and economic sustainability indicators into process mining techniques through systematic metric mapping and event log enrichment. The framework enables the extraction and analysis of sustainability performance data at the process level, creating detailed heat maps that visualize resource utilization, emissions, and waste generation. An application to a Purchase-to-Pay process case study demonstrates how process variants impact sustainability metrics differently. Delays increase emissions by 16.7%, while rework increases waste generation by 41.7%. The results identify specific process bottlenecks with high environmental impact and reveal critical misalignments between economic and environmental sustainability goals. This framework provides organizations with a standardized yet flexible approach to measuring sustainability performance, bridging the gap between high-level sustainability reporting and operational processes. It enables continuous monitoring, targeted interventions, and transparent reporting across diverse industry contexts.

Somayeh Tamjid, Fatemeh Nooshinfard, Moluk S. Hoseini Beheshti et al.

Following recent trends in information management systems, conventional word-based information retrieval methods are changing to concept-based approaches by means of the broad application of ontologies. More specifically, the use of ontologies for knowledge management is significant in the medical sciences and human disease domains due to the diversity and necessity of information sharing between numerous data repositories such as medical records, health record systems, and so on. Furthermore, ontologies make natural language processing approaches more feasible by reducing semantic ambiguity and making concepts comprehensible to computer-based deductions. In this research, a semi-automated approach for ontology development is proposed, which assists in identifying structural components of an ontology and determining possible relations between them based on scientific text records. The proposed approach, in a general view, includes the gathering of a large volume of technical data in text format, processing, and extraction of results with a minimal contribution of human-based supervision. The processing stage is coded in Matlab code named TmbOnt_Alfa and applies two main techniques including word frequency and Lexico-Synactic patterns analysis, to identify concepts and relations, respectively. The role of the human supervisor is narrowed to entering target terms, eliminating unnecessary outputs, and finalizing the ontology structure. In order to evaluate the efficiency of the proposed method, a case study for ontological development in the field of glaucoma has been conducted, and results are compared with medical subject headings of MESH descriptors, the Persian medical thesaurus, ontology of diseases, and Bioassay ontology (BAO). According to results, the developed ontology, when compared by Glaucoma entry, covered 80% of the medical titles in Mesh, 100% of the medical terms developed in the Persian Medical Thesaurus, and 100% of the Persian medical descriptors. Moreover, the resultant ontology structure is compatible with more than 90% of the same ontology represented in Bioassay and 57% of the ontology of diseases (DO). It also proposed an average of 30% more terms for existing ontological structures. According to results, the developed ontology, when compared by Glaucoma entry, covered 80% of the medical titles in Mesh, 100% of the medical terms developed in the Persian Medical Thesaurus, and 100% of the Persian medical descriptors. Moreover, the resultant ontology structure is compatible with more than 90% of the same ontology represented in Bioassay and 57% of the ontology of diseases (DO). It also proposed an average of 30% more terms for existing ontological structures.

Anna Camilla Ottesen, Stine Nørgaard Plougmann, Jane Hyldgaard Nielsen et al.

Women with prior gestational diabetes face a highly increased risk of type 2 diabetes and are difficult to recruit for follow-up care, possibly due to a loss of professional support in the care pathway. This study aimed to explore Danish health professionals’ experiences of the challenges in the care pathway for women with prior gestational diabetes, the obstacles to continuity of care, and the possibility of better preventing type 2 diabetes. Qualitative semi-structured interviews with 12 healthcare professionals were conducted. The interviews were analyzed using inductive content analysis. The study adheres to the COREQ checklist. The findings are organized into five main categories. The conclusions indicate that gestational diabetes is easily overlooked due to a lack of information sharing and continuity across health care delivery systems. Creating a management plan and engaging general practice nurses as designated health professionals may improve the care pathway and better prevent type 2 diabetes.

Liudmila I. Khoruzhy, Yuriy N. Katkov, Ekaterina A. Katkova et al.

The development of cloud technologies enables companies to actively implement technologies for cost management and risk reduction in their financial and economic activities. The use of cloud-based models of risk management in the financial and economic activities of the enterprise will help small and medium-sized companies in the agro-industrial sector in Russia to make structural and strategic changes, as well as discover new opportunities for business expansion. The purpose of the study is to develop models for cost management and reduction of risks in the financial and economic activities of companies based on the OLAP technology for application in Russian agro-industrial enterprises. The study employs a qualitative approach based on the case study methodology. The paper discloses and substantiates the authors’ conceptual model of a cost management system that allows executives to make decisions proceeding from four types of cost prices. The distinguishing feature of the management system is the use of a digital twin, which makes it possible to manage risks at the early stages of decision-making. The application of OLAP systems improves the quality of analysis and visualization methods as part of the cost management system. In addition, the study provides practical insight into how the applied model will help small and medium-sized agro-industrial enterprises to develop different business vision strategies based on cost reduction, manage the level of risk at the early stages of decision-making, and analyze information from a geographically dispersed logistics chain of divisions (production facilities, warehouses, stores).

Samuel Faloye, Sanjay Ranjeeth, Sonny Ako-Nai

Over the years, technology has become an essential part of our lives, with technological advancement presenting on-going opportunities. However, technology creates negative emotions, anxiety and fear among some people due to an established set of norms and individual behaviour patterns. Such fear, anxiety and apprehension has been described as technophobia, which constrains individuals’ ability to use technology and thus puts them at a disadvantage. The continuous emergence of new technologies has given rise to increased technophobia, which is now believed to affect a third of every population. This article examines age differences in the level of technophobia as well as the personal characteristics that positively influence it. A quantitative methodology was employed, and 384 questionnaires were distributed to participants in Pietermaritzburg, KwaZulu-Natal, South Africa. The findings show that technophobia occurs within all age groups (the young, middle-aged and older). However, young adults with no formal education and employment demonstrated lower levels of technophobia than other age groups. The results also demonstrate a significant relationship between levels of technophobia and the demographic profile of respondents. The article concludes with a discussion on strategies to manage technophobia.

Zaher Ali Al-Sai, Mohd Heikal Husin, Sharifah Mashita Syed-Mohamad et al.

Big Data and analytics have become essential factors in managing the COVID-19 pandemic. As no company can escape the effects of the pandemic, mature Big Data and analytics practices are essential for successful decision-making insights and keeping pace with a changing and unpredictable marketplace. The ability to be successful in Big Data projects is related to the organization’s maturity level. The maturity model is a tool that could be applied to assess the maturity level across specific key dimensions, where the maturity levels indicate an organization’s current capabilities and the desirable state. Big Data maturity models (BDMMs) are a new trend with limited publications published as white papers and web materials by practitioners. While most of the related literature might not have covered all of the existing BDMMs, this systematic literature review (SLR) aims to contribute to the body of knowledge and address the limitations in the existing literature about the existing BDMMs, assessment dimensions, and tools. The SLR strategy in this paper was conducted based on guidelines to perform SLR in software engineering by answering three research questions: (1) What are the existing maturity assessment models for Big Data? (2) What are the assessment dimensions for Big Data maturity models? and (3) What are the assessment tools for Big Data maturity models? This SLR covers the available BDMMs written in English and developed by academics and practitioners (2007–2022). By applying a descriptive qualitative content analysis method for the reviewed publications, this SLR identified 15 BDMMs (10 BDMMs by practitioners and 5 BDMMs by academics). Additionally, this paper presents the limitations of existing BDMMs. The findings of this paper could be used as a grounded reference for assessing the maturity of Big Data. Moreover, this paper will provide managers with critical insights to select the BDMM that fits within their organization to support their data-driven decisions. Future work will investigate the Big Data maturity assessment dimensions towards developing a new Big Data maturity model.

Angela Keniston, Vishruti Patel, Lauren McBeth et al.

Abstract Background Hospital systems have rapidly adapted to manage the influx of patients with COVID-19 and hospitalists, specialists in inpatient care, have been at the forefront of this response, rapidly adapting to serve the ever-changing needs of the community and hospital system. Institutional leaders, including clinical care team members and administrators, deployed many different strategies (i.e. adaptations) to manage the influx of patients. While many different strategies were utilized in hospitals across the United States, it is unclear how frontline care teams experienced these strategies and multifaceted changes. As these surge adaptations likely directly impact clinical care teams, we aimed to understand the perceptions and impact of these clinical care and staffing adaptations on hospitalists and care team members in order to optimize future surge plans. Methods Qualitative, semi-structured interviews and focus groups with hospitalist physicians, advanced practice providers (APPs), and hospital nursing and care management staff at a quaternary academic medical center. Interviews focused on the impact of COVID-19 surge practices on the following areas: (1) the experience of clinical care teams with the adaptations used to manage the surge (2) the perception and experience with the communication strategies utilized (3) the personal experience with the adaptations (i.e. how they impacted the individual) and (4) if participants had recommendations on strategies for future surges. We utilized rapid qualitative analysis methods to explore themes and subthemes. Results We conducted five focus groups and 21 interviews. Three themes emerged from the work including (1) dynamic clinical experience with a lot of uncertainty, (2) the importance of visible leadership with a focus on sense-making, and (3) the significant emotional toll on care team members. Subthemes included sufficient workforce, role delineation and training, information sharing, the unique dichotomy between the need for flexibility and the need for structure, the importance of communication, and the emotional toll not only on the provider but their families. Several recommendations came from this work. Conclusions COVID-19 surge practices have had direct impact on hospitalists and care team members. Several tactics were identified to help mitigate the many negative effects of COVID-19 on frontline hospitalist providers and care teams.

Antonio Aloisi, Nastazja Potocka-Sionek

Workers are increasingly being managed by technologies. Before spreading to larger segments of the labour market, algorithmic management systems were a signature feature of platform work. The exercise of power through digital labour platforms is one cause of the precarious working conditions in this area, an issue that could soon concern a wider group of workers in traditional economic sectors. This article elucidates the provisions regulating algorithmic management in the proposed EU Directive on improving working conditions in platform work, which tackles automated surveillance and automated decision-making practices. The proposed Directive mandates the disclosure of their adoption and sets out information and explanation rights regarding the categories of actions monitored and the parameters considered. Unlike rules concerning the presumption of employment status, the provisions on algorithmic management apply to all platform workers, including genuinely self-employed persons. Before offering a reasoned overview of the legal measures envisaged in the proposed text, this article grapples with the process leading to the proposed Directive in order to reveal the background and alternatives to the current formulation. It addresses the interplay between the text and other instruments regulating the deployment of technologies for managing workers. The steps intended to hold platforms to account are remarkable, but the regulatory technique could result in partially overlapping models, thereby increasing legal uncertainty and arbitrage.

Kirill V. Plaksiy, Lidiia L. Kulagina, Andrey A. Nikiforov et al.

The information security (IS) issues in the currently popular graph database management systems (DBMS), suitable for big data processing and storing information created during the generation of criminal cases on money laundering and financing of terrorism (ML/FT), are examined. This paper continues the previous authors’ research and aims to analyze IS threats and vulnerabilities of graph DBMS. These DBMS differ from the relational ones in the type of stored data and the principle of their storage; therefore the compiling of a list of IS threats is urgent due to its absence on a global scale. The original IS threat list and methods for protecting against them, as well as some recommendations for eliminating vulnerabilities used by IS threats are proposed. The obtained results are based on the analysis of IS threats for conventional DBMS and taking into account the peculiarities of graph DBMS, their structure as well as vulnerabilities of specific graph DBMS.

Mohammad R. Gohardoust, Asher Bar-Tal, Mohaddese Effati et al.

Many arid and semiarid regions of the world face serious water shortages that are projected to have significant adverse impacts on irrigated agriculture and create unprecedented challenges for providing food and water security for the rapidly growing human population in a changing global climate. Consequently, there is a momentous incentive to shift to more resource-efficient soilless greenhouse production systems. Though there is considerable empirical and theoretical research devoted to specific issues related to control and management of soilless culture systems, a comprehensive approach that quantitatively considers relevant physicochemical processes within containerized soilless growth modules is missing. An important first step towards development of advanced soilless culture management strategies is a comprehensive characterization of hydraulic and physicochemical substrate properties. In this study we applied state-of-the-art measurement techniques to characterize six soilless substrates and substrate mixtures [i.e., coconut coir, perlite, volcanic tuff, perlite/coconut coir (50/50 vol.-%), tuff/coconut coir (70/30 vol.-%), and Growstone^®/coconut coir (50/50 vol.-%)] that are used in commercial production in Israel and the United States. The measured substrate properties include water retention characteristics, saturated hydraulic conductivity, packing and particle densities, as well as phosphorus and ammonium adsorption isotherms. In addition, integral water availability and integral energy parameters were calculated to compare investigated substrates and provide valuable information for irrigation and fertigation management.

Rusinaru Denisa, Popirlan Claudiu, Stoian Gabriel et al.

The actual operation of the power distribution systems asks for high power quality (PQ). This fully justifies the investments in improving the metrics of power grid performances. But maintaining a PQ data infrastructure in a numerous locations is time-consuming and prohibitive. Moreover, each PQ monitor releases its own data format. These considerations justified using of a central PQ management system able to manipulate elliptical and time discontinuous information. The paper presents the characteristics of a webbased application designed to collect the data measured with different technologies of monitors and translate them into a common PQ data interchange format allowing comprehensive and long-duration grid operation assessment. The unitary formatted data generated by this customized software tool can be further processed by a proprietary software platform for PQ management owned by the network operator. The present version of this conversion tool is applicable only for one product family operating in the local power distribution grid. Further development is planned for integrating other two monitor vendors/families.

Andrizal Andrizal, Anton Hidayat, Tuti Angraini et al.

Metoda mengamati warna urin sudah dilakukan sejak lama untuk melengkapi diagnosa penyakit yang diderita seorang pasien. Pengamatan dengan panca indra vision manusia dilakukan untuk meneliti dan menganalisa warna urin seseorang dan menghubungkannya dengan penyakit yang diderita pasien tersebut. Fungsi vision manusia dapat digantikan dengan sistem komputer yang dilengkapi dengan alat yang mampu mendeteksi warna seperti kamera maupun jenis sensor warna lainnya. Warna objek dapat dibedakan dengan menguraikan komponen warna objek tersebut berupa komponen warna dalam domain frekuensi maupun dalam domain spasial. Hal ini dimungkinkan karena setiap warna memiliki nilai panjang gelombang tertentu dan dituangkan dalam nilai frekuensi. Sensor warna TCS 3200 menghasilkan sinyal output dengan frekuensi yang berbeda berdasarkan warna yang discan oleh foto dioda pada sensor tersebut. pengenalan suatu objek ditandai dengan bentuk, warna dan variable lainnya dari objek tersebut. Ekstrak ciri dari suatu objek dapat dituangkan dalam bentuk pola data maupun histogram yang mencirikan warna objek tersebut. Penelitian ini bertujuan untuk membuat histogram dan pola data warna urin berdasarkan indikasi kondisi yang diderita seorang pasien. Sebagai acuan warna yang digunakan adalah warna dasar urinalisis hasil penelitian di Cleveland Clinic, di Ohio tahun 2013. Dari hasil penelitian telah didapatkan pola data dan histogram warna yang berbeda berdasarkan warna urin yang dideteksi. Diharapkan hasil penelitian ini dapat digunakan pada proses identifikasi penyakit melalui warna urin secara online.

Porczek Mariusz, Rucińska Dorota, Lewiński Stanisław

The severe flood of 1997, which seriously affected Polish, Czech and German territories, gave impetus to research into the management of flood-prone areas. The material losses caused by the “Flood of the Millennium” totalled billions of Polish zloty. The extent of the disaster and of infrastructure repair costs changed the attitude of many branches of the economy, and of science. This is the direct result of consideration of the introduction of changes into spatial management and crisis management. At the same time, it focused the interest of many who were trained in analysing the vulnerability of land-use features to natural disasters such as floods. Research into the spatial distribution of geographic environmental features susceptible to flood in the Odra valley was conducted at the Faculty of Geography and Regional Studies of the University of Warsaw using Geographic Information Systems (GIS). This study seeks to examine the possibility of adapting vector and raster data and using them for land-use classification in the context of risk of flood and inundation damage. The analysed area of the city and surrounding area of Raciborz, on the upper Odra River, is a case study for identifying objects and lands susceptible to natural hazards based on publicly available satellite databases of the highest resolution, which is a very important factor in the quality of further risk analyses for applied use. The objective of the research was to create a 10×10-m-pixel raster network using raster data made available by ESA (Copernicus Land Monitoring Service) and vector data from Open Street Map.

Jacek Woźniak

Recenzja książki autorstwa Jarosława Żelińskiego pt. Analiza biznesowa. Praktyczne modelowanie organizacji, wydanej nakładem Wydawnictwa HELION, Gliwice 2017, ISBN: 978-83-246-4880-1, s. 120.

Jakub CIERPKA, Zdzisław WOJCIECHOWSKI

The article presents procedures for implementation of the Occupational Health and Safety Management System (OHSMS) based on the PN-N-18001:2004 norm, illustrated with an example of the administration department in the service company. Performed analysis of the current company situation in the OHS area allowed for identification of a number of dysfunctions, which formed the basis for drafting necessary documents and description of procedures.

Ridoh Adonis, Bethuel Sibongiseni Ngcamu

The study has been triggered by the increase in information breaches in financial organizations worldwide. Such organizations may have policies and procedures, strategies and systems in place in order to mitigate the risk of information breaches, but data breaches are still on the rise. The objectives of this study are to explore the shortfalls of information security on a South African financial institution and further investigate whether business processes are responsive to organization’s needs. This study employed both quantitative and qualitative research methods. Questionnaires were sent to staff level employees, and semi-structured in-depth interviews were conducted with senior management at the organization. The study revealed that employees require training on information management and that there are major training deficiencies for training officers to conduct beneficial information management training at the organization. Information security program that include business risk analysis were not implemented, which results in inadequate information management planning and decisions. A standardized or uniform house rule policy was not consistently implemented across the organization, which resulted in certain areas not protecting information. The qualitative findings revealed that the external cleaning company could obtain access to customer information, if customer data are left lying around. Furthermore, there is major misalignment between policy setters and employees in this organization. The findings allow senior managers to construct projects and program with their teams to improve the state of information management in the organization which spans across the people aspect, technology systems and general information management processes. Furthermore, external companies should start signing Non-Disclosure Agreements - which is not being done currently as this opens the door for data fraud. The organization has information management and security policies in place, but the study concluded that employees do not understand these policies and should receive specialized training to ensure understanding and, ultimately, have employees following these information security policies. Keywords: data breach, information management, business processes, information legislation. JEL Classification: G2

EFSA Panel on Animal Health and Animal Welfare (AHAW)

Abstract This opinion reviews information on small‐scale dairy cow farming systems in Europe, including the impact of production diseases on welfare of cows, and proposes a methodology for welfare assessment in those systems. To address specific expectations of consumers that food be produced locally or regionally or maintaining acceptable animal welfare conditions, in addition to herd size, criteria to define farms as “non‐conventional” were proposed. Several sources were investigated for identifying criteria for the description and categorisation of small‐scale farms, including dairy umbrella organisations and literature. In addition to herd size (up to 75 cows), proposed criteria related to small‐scale farming comprise the workforce source, input level, indigenous breed use and production type certification. To cover the large diversity of farming systems across Europe, it was proposed that farms meeting at least two of these criteria be considered non‐conventional. To adapt the welfare assessment to small‐scale farms, the same risk factors and welfare consequences, as measured by corresponding animal‐based measures identified in previous opinions for intensive farming systems were considered to be also relevant for small‐scale systems. In addition, factors related to resources provided on pasture (e.g. shelter), management of pasture (e.g. mixing herds) and management of the cows (e.g. use of local breeds) were considered more likely to be present in small‐scale systems. An on‐farm survey was run to collect data for welfare assessment from 124 European farms. The distribution of risk factors and animal‐based measures varied across the full range in study farms and showed similar patterns in farms with different grazing systems (from no time to full year on pasture). The animal‐based measures identified for intensive farming are well suited for application in small‐scale dairy farms. Production disease impact on the individual animal's welfare state does not depend on herd size or farming system.

William B. Rouse, Andrew P. Sage