Situation Map Research Articles

ASSESSMENT OF COMPONENTS OF THE INTERNAL CONTROL SYSTEM FOR THE PURPOSE OF RISK MANAGEMENT OF ORGANIZATIONS

An effective internal control system is closely related to the risk management of the organization, namely, it reduces the risks of failure to achieve the set goals and, according to the COSO concept, provides reasonable assurance of their achievement. The subject of the study is the assessment of the components of the internal control system for the purpose of risk management of organizations. The object of the study is the internal control system of the organization. The article raises the problem of developing a methodology for assessing the formation of all components of the ICS in accordance with the COSO model. The problem lies in the insufficient number of studies on the systematization of control procedures for each component of the ICS in the context of assessing the system, describing standard and non-standard situations that must be responded to promptly and how to assess such situations in the context of internal control and risk management through qualitative indicators that are not measurable. Model. To substantiate the methodology for assessing the formation of all components of the ICS in accordance with the COSO model, the criterion for assessing and measuring non-financial indicators of financial stability of organizations is presented. The study uses the grouping method, which allows studying the interrelations of phenomena, as well as their interdependencies, to identify the influence of certain factors and trends. The article uses the comparative method as the most common method of analysis, as well as the methods of induction and synthesis. Conclusions. The methodology for assessing the formation of ICS components in accordance with the COSO model in organizations is of theoretical significance in terms of developing scientific and theoretical provisions concerning the construction of internal control and improving the effectiveness of ICS, as well as practical significance in the context of applying the developed package of documents. Practical significance. As a result, the methodology for assessing the formation of all ICS components in accordance with the COSO model was substantiated, a number of documents were developed that systematized the indicators for assessing the ICS components, including non-financial indicators. It is proposed to form a map of typical situations: standard and non-standard, as well as situations with increased complexity, allowing you to create new algorithms for action to reduce risk. Originality. The author's contribution is to develop a methodology for assessing the formation of all ICS components in accordance with the COSO model.

Value stream mapping in the preparation of patients for surgery A study of a private hospital in Turkey

BackgroundDue to the equipment used in the health system, drugs, and the need for specialized health personnel, the operating rooms are the most costly, and time is the most valuable resource. From this point of view, the study was aimed to raise awareness about Value Stream Mapping, which is one of the problem-solving practices in nurses, and to practice with a sample VSM study (eliminating non-value-creating activities, creating flow in processes, and avoiding delays due to the preparation of the surgery in the pre-op period with continuous improvement). MethodsObservational action research. The research, Value Stream Mapping, which is one of the lean methods, was carried out in a private hospital between December 2019 and March 2022. A total of 59 patient flows were observed in three stages. First, the current situation map was drawn. Value-added and non-value-added time was determined. The problems experienced in the current situation were determined and suggestions were developed for their solution, kaizen studies were carried out. Onset time and delays in minutes were monitored for all first cases on a daily basis. ResultNon-value-added activities were reduced from 102 min to 52 min on average. In particular, the quality increased from 0 % to 36 %. "If patients were not in the operating room within 10 min of the scheduled start time, this was considered a late start". While the rate of starting the surgery on time at the first observation was 0 %, this rate increased to 70 % at the end of the study. ConclusionsImproving the pre-op preparation process was effective in increasing the percentage of surgery that started on time in the operating room. It is thought that value stream mapping can be a useful method for improving on-time starts in the operating room.

The social processes that emergency nurses use to achieve sustainability: A constructivist grounded theory.

To examine the experiences of emergency nurses and develop a substantive theory that describes the processes they use to support or prevent sustainability in their nursing practice. Constructivist grounded theory. Between February 2018 and January 2019, observations and semi-structured interviews were conducted with 29 emergency nurses. Data underwent constant comparison, and coding was performed in three phases: open, focused, and theoretical, employing constructivist grounded theory. Additionally, some situational analysis mapping was undertaken and integrated as a method to explore the broader context affecting nursing practice. The study achieved theoretical saturation and rigour was ensured through evaluations of credibility, transferability, and confirmability. A substantive grounded theory was constructed to describe the basic social process of 'Achieving Personal and Professional Sustainability' with subprocesses that included 'Driving forces', 'Developing and using armouries', 'Balancing work-life', and 'Making emergency work effective'. This theory delineates two phases, 'exploration and establishment' and 'maintenance', and two key properties: 'Constructing and evolving professional identity' and 'Perceiving and reshaping the meaning of effective work and care'. The theory also highlights the dynamic interplay of individual, social, and institutional elements. 'Achieving Personal and Professional Sustainability' is important for emergency nurses to sustain themselves personally and professionally in their work. This research has substantial and global impacts. Emergency nursing can use this information as a guide to better understand strategies for both personal and professional sustainability. Policymakers may use the findings to foster a supportive work environment and enhance nurse well-being. Implementation of recommendations can lead to improved patient care outcomes. The methodological approach offers potential for future research, positively impacting emergency nursing practice and workforce sustainability worldwide. Reporting adheres to EQUATOR's COREQ guidelines for qualitative studies. No patient or public contribution.

Research on the Movement Speed of Situational Map Symbols Based on User Dynamic Preference Perception

When designing situational maps, selecting distinct and visually comfortable movement speeds for dynamic elements is an ongoing challenge for designers. This study addresses this issue by conducting two experiments to measure the human eye’s ability to discern moving speeds on a screen and examines how symbol movement speeds within situational maps affect users’ subjective experiences, task performance, and visual comfort. The first experiment measured participants’ speed discrimination capabilities for Landolt Ring of varying sizes moving at 0–256°/s, yielding speed discrimination thresholds of 7–23% and a sensitive velocity range of 1–64°/s. The second experiment evaluated observers’ visual perceptions of moving elements within a cognitive task across the same range of 1–64°/s, identifying three significant benchmarks—8°/s, 16°/s, and 32°/s. These can be utilized to categorize slow-, moderate-, and fast-moving symbols in situational maps. The findings can aid in designing human–machine interface environments with improved viewer experience and visual comfort for both Air Traffic Control interfaces and situational maps.

On the Smith–Thom deficiency of Hilbert squares

AbstractWe give an expression for the Smith–Thom deficiency of the Hilbert square of a smooth real algebraic variety in terms of the rank of a suitable Mayer– Vietoris mapping in several situations. As a consequence, we establish a necessary and sufficient condition for the maximality of in the case of projective complete intersections, and show that with a few exceptions, no real nonsingular projective complete intersection of even dimension has maximal Hilbert square. We also provide new examples of smooth real algebraic varieties with maximal Hilbert square.

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. We demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

A lightweight improved residual neural network for bearing fault diagnosis

Timely and accurate fault diagnosis is essential for modern industrial system reliability and safety. However, traditional bearing fault diagnosis using the residual neural network (ResNet) is limited by high parameters, computational costs, and low accuracy. To address this, a lightweight improved residual network (LIResNet) is proposed to enhance the ResNet structure. LIResNet introduces a parallel layer (PL) merging the discrete cosine transform convolutional layer (DCTConv) and the standard convolutional layer (Conv). This reduces trainable parameters, aiding feature extraction from input signals, with spectrograms preprocessed by CWT fed into the PL. Furthermore, integrating a self-attention mechanism enhances fault feature comprehension. The residual structure is refined using low-rank decomposition, reducing model complexity. This refinement, combined with a max-pooling layer and single convolutional layer, forms the downsampling residual module (DAM). The proposed batch-free normalization (BFN) and improved hard-swish activation function constitute the normalized activation module (NAM), ensuring model stability and nonlinear mapping in low-batch data situations. Experiments across bearing datasets reveal that the proposed method achieves a diagnostic accuracy of 99.8%, surpassing ResNet18′s 98.7%. Moreover, while ResNet comprises 11.18M parameters and 753.07M Flops, the proposed method uses 0.06M parameters and 49.49M Flops. These findings underscore the improved lightweight performance and diagnostic capability of our approach.

Measurement of the horizontal control framework closed polygon method as a basis for making maps on the UNS Pabelan Campus

Mapping is a method of determining the location and position of an area on the earth’s surface, which includes measuring distances, angles, vertical directions, and horizontal directions. A situation map is the starting point for a project that aims to determine changes in the state of an area over time. The initial measurement of the scenario map takes the form of determining the points of the basic mapping framework that are evenly dispersed in the area being assessed by measuring the horizontal control frame. ents, was used in the horizontal control framework’s experimental procedure. The closed polygon approach was used to take measurements with 44 control points as a horizontal frame. The angle correction, abscissa correction, and ordinate correction satisfied the practicality to be employed, according to the data obtained from the measurement of the horizontal control frame using the closed polygon method. The implications of utilizing the closed polygon method to measure the horizontal control frame are the foundation for precise mapping of the situation for future measurements.

Diasporic Epistemologies in Cuban Independent Journalism

This article examines how digital diasporic journalism changes epistemic practices in the Cuban context. The last decade has seen a practical transnationalization of digitally native independent news sites in Cuba in light of two phenomena: the emigration/forced exile of many young journalists and the affordances of digital technologies, making it possible for these journalists to continue reporting despite their spatial dispersion abroad. How are digital and diasporic ways of knowing changing Cuban journalists’ epistemic practices? By taking a relational approach, we explore digital diasporas as a site of connectivity co-inhabited by multiple and hybrid traveling imaginaries. The article is based on 44 interviews with Cuban independent journalists, which are analyzed through postfoundational discourse analysis (PDA) and situational mapping. The data reveals three important epistemological cleavages that shape digital diasporic journalists’ access to knowledge. These are (1) place as an epistemic category, (2) the epistemic status they confer on themselves and other social actors, and (3) the autonomy they claim when constructing clear boundaries between journalism, activism, and propaganda.

Variaciones ortográficas en el español de Cuba

Part of the lexical stock of the Cuban macrosystem of speech is still subject to spelling variation. This is because of various historical, etymological, morphological, phonological, or even connotative-affective reasons, which may condition the choice of the graphical output. A map of the current situation of orthographic variation in Cuban Spanish will be presented, taking into consideration the above-mentioned reasons. This work is part of a variational lexicography project of personal authorship that attempts to gather different elements that make up the Cuban diasystem.

An efficient urban flood mapping framework towards disaster response driven by weakly supervised semantic segmentation with decoupled training samples

Despite the proven effectiveness of data-driven deep learning techniques in urban flood mapping, the availability of annotation data remains a critical factor impeding their timeliness in real applications. Recent progress in weakly supervised semantic segmentation (WSSS) presents promising solutions for addressing this limitation. To accomplish prompt and accurate flood mapping in complex urban areas from high-resolution remote sensing images to support disaster management and response, this study makes contributions in three key aspects: weak training data generation, the improvement of WSSS algorithm, and the construction of benchmark datasets. Firstly, we present a novel yet efficient weak training data generation strategy by decoupling the acquisition of positive and negative samples. This strategy enables the rapid generation of block-level weak annotations assisted by pre-flood river data or the segment anything model (SAM) for zero-shot segmentation, thereby alleviating the burden of weak data labeling. Secondly, to enhance the flood detection results in complex urban landscapes based on low-cost weak labels, we design an end-to-end WSSS framework incorporating tree filtering-based structure constraints and a perturbed dual-branch cross self-distillation mechanism. Lastly, to evaluate the performance of the proposed approach, we constructed two large aerial imagery datasets, namely Calgary-Flood and Huston-Flood. These datasets encompass diverse urban land covers and include challenging scenarios with extensive shadows, providing a robust benchmark for evaluating our method against various urban environments. Experimental results demonstrate that our weak data annotation strategy substantially enhances efficiency. Additionally, the proposed WSSS framework exhibits superior performance in comparison to existing state-of-the-art methods, particularly in terms of edge delineation and algorithmic stability. The advancements in weak data annotation strategy, end-to-end model architecture, and benchmark dataset development in this study collectively exploit the potential of the weakly supervised paradigm for rapid flood mapping in urgent situations. The datasets and code will be publicly available at (https://github.com/YJ-He/Flood_Mapping_WSSS).

ANÁLISE DO FLUXO DO ATENDIMENTO DE PACIENTES EM HEMODINÂMICA SUSTENTADO NO PENSAMENTO LEAN

ABSTRACT Objective: to analyze the patient care flow in a Hemodynamics service grounded on Lean Thinking based on Value Stream Mapping. Method: an exploratory-descriptive case study carried out in the Hemodynamics service of a public university hospital from southern Brazil. Data collection was conducted through participant observation with twelve members of the multiprofessional team and interviews with five participants from May 2021 to February 2022. The analysis was based on the Lean framework and on the stages foreseen in Value Stream Mapping. Results: the Value Stream Map of the current situation of the service was prepared, identifying suppliers and customers of the process and their requirements. A total of 61 problems related to unmet requirements were listed, of which 12 were prioritized in order to promote improvement planning. Conclusion: with Value Stream Mapping it was possible to establish improvement priorities that exert impacts on operational performance of the service. It was identified that improvements related to standardization of the activities minimize waste from failures and waiting times, which were the most prevalent in the service, among others observed.

Evaluation of Drainage Network System (Case Study of Pangkajene Kepulauan State Agricultural Polytechnic Campus Area)

The purpose of this research is to identify the condition of highway drainage channels and evaluate the existing highway drainage network system in accommodating runoff discharge, channel dimensions and flow direction in channels that occur inundation in the Pangkajene Islands State Agricultural Polytechnic Campus area which is expected to help solve flooding problems in the area. The research method used is descriptive quantitative, which is a method of calculation and description of the results of field data processing. Secondary data collection includes; rainfall data for the last 10 years, obtained from the Department of Resources; topographic maps, drainage network maps and situation maps, obtained from the Politani Pangkep Campus planning section. Primary data collection is obtained from direct measurements in the field using a Waterpass measuring instrument to measure elevation and channel length. The results of this study found that the drainage capacity < 2-year and 5-year return period Plan Flood Discharge, so planning is needed to increase drainage capacity

Transformative climate change education and the school caretaker: a more-than-human analysis with young people

Schools are central to climate change education and climate-friendly transformations both as places which actually produce CO2 emissions and, above all, as educational institutions. Following a new materialist, transdisciplinary approach, we research here some of the entanglements that constitute schools as whole institutions. As part of the research-education-cooperation k.i.d.Z.21_aCtiOn2 (Austrian Climate Research Program), our innovative approach meant that the situational analyses were conducted both by young people and collaborating researchers. The experiences and accounts were captured in situational maps that illustrate the entangled agencies of people, discussions, places and matter relevant to CO2 reductions and transformation attempts. The analysis of those maps led to new perspectives on the intra-actions between the material and the discursive in schools. In particular, the caretakers’ entanglements with areas relevant to climate-friendly transformations are revealed as critical to transformative climate change education. We conclude with an outlook on schools becoming transformative, climate-friendly places by building on these kinds of entanglements and explicitly incorporating non-pedagogical aspects as part of a whole-school approach.

The trend of change in the role of pre-hospital emergency medical services in Iran’s healthcare system: a situational analysis

IntroductionFollowing the significant changes in healthcare systems over the last century, the role of pre-hospital emergency medical services (EMS) has been drawn against numerous challenges. In view of this, the present study aims to reflect on the trend of change in the role of pre-hospital EMS to meet new situations and needs, thereby providing a clear picture of this process.MethodsRespecting the intricate concept of development and the major changes in Iran’s healthcare system, this study was fulfilled using situational analysis (SA), developed by Clarke (2018), in Iran within 2022–2023. For this purpose, the data were collected through semi-structured, in-depth individual interviews with four faculty members, two managers involved in EMS, and six highly skilled EMS personnel in various positions. Moreover, the relevant articles published from 1950 to 2023 were reviewed. The data analysis was then performed via SA in the form of open coding as well as simultaneous analysis through three types of maps, viz., situational, social worlds/arenas, and positional maps, along with constant comparative analysis.ResultsPre-hospital EMS in Iran has thus far had two turning points from 1970 to 2023, wherein academic components, need for equipment and resources, in conjunction with basic needs in the modern society, have been the main propellers. As well, the complexity of care for non-communicable diseases (NCDs), demand for managed care, and technological advancement has gradually resulted in further development in EMS. This trend describes the EMS situation in Iran from 1973 to 2023, as well as the EMS emergence stages, quantitative growth and infrastructure, and clinical education development in 2002–2023, indicating the lack of funding and inadequate scientific infrastructure in proportion to the population receiving such services.ConclusionConsidering the trend of change in the approaches adopted by healthcare systems across the world, and given the breakthroughs in nursing and medicine, along the education of professionals during the last thirty years, the descriptions of duties and performance in EMS have moved from primary care and patient transfer to specialized services and outpatient care. In addition, the cultural context specific to Iran, the challenges of women working in EMS centers, the disconnection of service providers, namely, the Iranian Red Crescent Society (IRCS) Relief and Rescue Organization (R&RO), Iran’s National Police Force (INPF), and Iran’s National Medical Emergency Organization (INMEO), as well as lack of resources and equipment, and the geographical distribution of human resources (HRs) based on population dispersion, are thus among the significant issues facing pre-hospital EMS in this country.

PENINGKATAN DETEKSI-AKSI BERBASIS DATA, INFORMASI, DAN KEJADIAN AKTUAL UNTUK PEMETAAN SITUASI KAMTIBMAS MELALUI PEMOLISIAN PREDIKTIF DALAM RANGKA PEMELIHARAAN KAMTIBMAS

This study aims to determine the increase in the base of action-detection based on data, information and actual incidents for mapping the Kamtibmas situation and to determine the maintenance of security and public order using predictive policing. This study uses a qualitative approach with a mix method that uses the level of understanding, attitude and orientation of police officers towards increased detection based on data, information and actual incidents which can be identified through surveys. These problems are then analyzed using the concept of predictive policing, the dimensions of predictive policing, and the basis for mapping the Kamtibmas situation with a predictive policing approach. The results of this study obtained that the data presented in this section are data obtained through interviews and tabulation results on the attitudes of research respondents. Respondents' attitudes towards the main issues studied in this study, which are related to increased detection of data and information-based actions as well as actual incidents which form the basis for compiling the Kamtibmas situation map. There has been an increase in requests for Harkamtibmas activity reports in the form of data and information from each function in the regional unit. Request this report in both digital and manual format. Data and information needed in addition to filling out centralized digital and manual report formats. Since the existence of the Presisi program, especially the emphasis on predictive policing, there has been an increasing push to increase action-detection activities and to expand information and data sources. As a consequence, improving personnel capabilities and improving operational activities also need adjustments. Therefore, this research needs to be socialized more periodically in order to increase the motivation, understanding and ability of personnel at the Satwil and Bag, Sat, sie levels in supporting increased action detection based on data, information and actual events and it is necessary to develop a mechanism for integrating and collaborating data and information from each part and function through a data center that can and is easily accessed.

高中历史教材的中国边疆史地内容及教学应用研究

National unity and ethnic unity are the fundamental issues of national development, but border issues in the new era are still emerging endlessly, hindering the great rejuvenation of the Chinese nation. Strengthening the teaching of China’s frontier history and geography in high school history education is not only the need of the new era, but also the requirement of the core literacy of the history discipline and the trend of the college entrance examination proposition. The textbook “Outline of Chinese and Foreign History (Part 1)” presents the map of the border situation in various stages of Chinese history, the border governance of successive dynasties, and the political, economic, cultural characteristics and ethnic integration of border minorities, etc. In the specific process of high school history teaching practice, attention should be paid to the selection of timing and historical materials, the design of teaching mode and class type in the teaching application of the contents of the historical geography of the China’s borderland, in order to cultivate students’ feelings for home and country, and enhance their awareness of safeguarding of national unity and ethnic unity.

Value stream mapping: an application lean in the process of accountability in a philanthropic hospital

Objective: This study aimed to map the value flow of medical records of a philanthropic hospital, identifying opportunities for improvements in the process. Design/methodology/approach: A qualitative research of descriptive and exploratory bias was developed, in which the sources of evidence emerged from participant observation and documentary analysis. Therefore, data collection took place for three months in 2021, which took place in the administrative sectors of a large philanthropic hospital, and the process chosen to be mapped and analyzed was the surgical record. Result: The analysis of the process took place from the patient's discharge to the delivery of the accounts to the typing/billing sector, where the routine of the post desks was observed and the current flows were mapped through the Value Stream Mapping tool (VSM), with several wastes being detected. The time spent in the process was approximately 56 days, after the suggested improvements and drawing up the map of the future situation, this time was reduced to 28 days. With the application of the tool, waste was identified and eliminated in the mapped process, generating a possibility of cost reduction. Originality/value: The study stands out as it seeks to link the context of value stream mapping in a hospital space, opening space for new research and contributing to practical results.

Automating the external placement of symbols for point features in situation maps for emergency response

ABSTRACT In this article, we address the time-critical work of emergency services in the field of disaster and emergency response. Aiming at saving valuable human and time resources during emergency operations, we present one exact and one heuristic approach for the automatic placement of tactical symbols in situation maps. Such maps are used to establish situational awareness and to convey mission-relevant information to emergency personnel. Usually, the information is communicated through the visualization of descriptive symbols which are predominantly placed in a manual process. We automate this process based on an established map layout used by emergency services in Germany that distributes the symbols to the map boundaries. Following general principles and observations from existing literature, we formalize the symbol placement as an optimization problem. We take into account the relevance of tactical symbols as well as short and crossing-free leaders and allow the grouped representation of symbols of similar semantics and spatially close map locations. In experiments with real-world data, we determine a balance between the optimization criteria and show that our heuristic generates high-quality results in less than a second. In an assessment by an expert, we get confirmation that our maps are suitable for use in emergency scenarios.

Image-Like Situational Difference Mapping (ILSDM)-Based Method for Detecting Anomalies in Electromagnetic Environment

Electromagnetic environment anomaly radiation source detection (EMEARD) can provide a basis for electromagnetic (EM) equipment behavior cognition and battlefield threat assessment. Existing methods mainly focus on generating EM space situations but ignore the research on anomaly signal detection. In this paper, the connections between information geometry and performance of sensor networks for anomaly detection are explored. Nonlinear estimation methods based on information geometry can be directly used for anomaly detection. However, Riemann distance as a metric function faces the disadvantages of extensive computation and high complexity. To tackle this issue here, we propose a method based on image-like situation difference mapping, namely ILSDM. which takes the data-driven strategy to obtain the analytic expression of situation difference mapping distance function (DMDF), and anomaly detection is equivalent to the mapping reconstruction of information geometry. Firstly, the EM space situation is acquired through the distributed sensor network. In addition, to solve the perceptual blind area problem, the sensors’ data is estimated by spatial autocovariance optimal interpolation algorithm (Kriging). Secondly, we apply the Gaussian mixture model (GMM) to fit the statistical features of each sensing node into probability density function (PDF), and adjacent sensors with similar PDF are fused by the neighbor average fusion method (NAF). Then, based on the information geometry, the fused PDFs are mapped to the Riemannian manifold space as a series of coordinates, and we further propose to use image-like situation (ILS) to represented the EM space situation. Finally, DMDF measures the information distance between different ILSs to achieve anomaly detection. Numerical simulations and real experiments were conducted to prove the superiority and feasibility of our method for anomaly detection in EM space.