Cost-based Analysis Research Articles

Applications of machine learning & Internet of Things for outdoor air pollution monitoring and prediction: A systematic literature review

According to the World Health Organization (WHO), air pollution kills seven million people every year. Outdoor air pollution is a major environmental health problem affecting low, middle, and high-income countries. In the past few years, the research community has explored IoT-enabled machine learning applications for outdoor air pollution prediction. The general objective of this paper is to systematically review applications of machine learning and Internet of Things (IoT) for outdoor air pollution prediction and the combination of monitoring sensors and input features used. Two research questions were formulated for this review. 1086 publications were collected in the initial PRISMA stage. After the screening and eligibility phases, 37 papers were selected for inclusion. A cost-based analysis was conducted on the findings to highlight high-cost monitoring, low-cost IoT and hybrid enabled prediction. Three methods of prediction were identified: time series, feature-based and spatio-temporal. This review’s findings identify major limitations in applications found in the literature, namely lack of coverage, lack of diversity of data and lack of inclusion of context-specific features. This review proposes directions for future research and underlines practical implications in healthcare, urban planning, global synergy and smart cities.

Understanding enterprise cybersecurity information sharing: a theoretical model and empirical analysis

ABSTRACT This research employs an analytical modelling approach, complemented by empirical analysis, to delve into enterprise cybersecurity information sharing strategies. Utilising a thorough cost-based analysis, we scrutinise the cybersecurity costs and security levels within enterprises, leading to the identification of three core cybersecurity strategies – risk acceptance, risk balance, and risk reduction. Additionally, we delineate four distinct information-sharing strategies: selective, balanced, extensive, and futile sharing. Supported by empirical evidence gathered from a cybersecurity forum, this investigation not only enriches scholarly discussions but also provides valuable insights. Its academic significance is accentuated by offering nuanced guidance for practitioners, facilitating the implementation of effective cybersecurity information-sharing practices.

NOCAP: Near-Optimal Correlation-Aware Partitioning Joins

Storage-based joins are still commonly used today because the memory budget does not always scale with the data size. One of the many join algorithms developed that has been widely deployed and proven to be efficient is the Hybrid Hash Join (HHJ), which is designed to exploit any available memory to maximize the data that is joined directly in memory. However, HHJ cannot fully exploit detailed knowledge of the join attribute correlation distribution. In this paper, we show that given a correlation skew in the join attributes, HHJ partitions data in a suboptimal way. To do that, we derive the optimal partitioning using a new cost-based analysis of partitioning-based joins that is tailored for primary key - foreign key (PK-FK) joins, one of the most common join types. This optimal partitioning strategy has a high memory cost, thus, we further derive an approximate algorithm that has tunable memory cost and leads to near-optimal results. Our algorithm, termed NOCAP (Near-Optimal Correlation-Aware Partitioning) join, outperforms the state of the art for skewed correlations by up to 30%, and the textbook Grace Hash Join by up to 4×. Further, for a limited memory budget, NOCAP outperforms HHJ by up to 10%, even for uniform correlation. Overall, NOCAP dominates state-of-the-art algorithms and mimics the best algorithm for a memory budget varying from below √||relation|| to more than ||relation||.

Improving the Logistics of Institutional Postal Services

Postal services are often considered by the different institutions as a back-up service. Taking into account that in case of large geographical coverage these services can generate significant costs, it is important to optimize the postal service functions within these institutions and to develop the already existing conventional postal services. Within the frame of this article the authors review the logistics processes of the postal services at the University of Miskolc to propose improvements to the processes of postal services focusing on delivery. The main regulatory elements and the logistics processes of the institutional postal services are discussed and some critical remarks are described focusing on three main areas: the facility location optimization of the institutional postal services, the lack of use of modern technologies and the lack of modern administrative facilities. On the basis of these criticisms, the authors define recommendations for improving institutional postal services. Regarding the facility location optimization problem, a mathematical model and an optimization algorithm is described to evaluate the efficiency of the logistics processes of delivery services. The proposed methodology supports a cost-based analysis of different solution variants and a priority-based differentiation between institutions and offices. The suggested approach is tested with a real scenario, where the numerical results validate the efficiency of the evaluation of optimization algorithm. The second improvement direction is the application of a pneumatic tube system. The authors show the most important parts of the proposed pneumatic tube system, which can lead to decreased labor cost and increased service level.

A Cost-Based Analysis of Anti-aging Products Across Four Major United States Retailers.

Background In the field of aesthetic dermatology, there is currently very little data on affordability and cost analysis regarding cosmeceuticals as more demand from patients showing interest in cosmeceutical products to reduce and prevent aging continues to grow.Photoaging, a form of extrinsic aging from sun exposure, can be ameliorated by applying sunscreen and retinol products. Topical ascorbic acid and niacinamide have been shown to target the oxidative stress process that contributes to photoaging.These four products have been identified as the cosmeceutical ingredients with the most evidence-based data on photoaging prevention and treatment. Objective Given the demand for effective skin care,the paucity of data on cost differentiation, and the availability of cosmeceutical products, we analyzed the unit cost offour anti-aging products from major online and physical retailers in the United States. Such a cost comparison may facilitate more economically appropriate recommendations on skin care to consumers. Methods and materials We analyzed sunscreen, topical vitamin C (ascorbic acid), topical vitamin B3 (niacinamide), and topical vitamin A (retinol) products sold by four major United States retailers: Walmart, Ulta, Walgreens, and Amazon. The average cost in dollars per ounce (dollar/oz) was calculated for each product category at each retailer. Statistical analyses were done to determine statistical significance for each product category between retailers as well as between each category of product. Results Between the four retailers, Walmart offered the lowest cost per ounce for every product. In contrast, Amazon offered the highest cost per ounce for every product except for sunscreen. We also found that sunscreen products are less expensive per ounce as compared to retinol, ascorbic acid, and niacinamide products. Conclusion Dermatologists should be knowledgeable of product costs when providing patients with anti-aging product recommendations. Our study provides data on the financial cost by retail location of evidence-based anti-aging cosmeceuticals to better guide physicians in patient consulting and economical resource sharing.

DOMESTIC COMPONENT LEVEL ASSESSMENT FOR A SALT FACTORY AND A SALT PRODUCTION

The TKDN (Domestic Component Level) assessment of goods and services is a method to determine local manufacturers/industrie’s capability to create quality products internationally standardized. This study assessed the salt factory's TKDN to increase the NaCl content, based on cost-based analysis stipulated at the Minister Industry Regulation No.16/M-IND/PER/2/2011. Meanwhile, the TKDN of salt production was assessed based on process-based analysis stipulated in Minister Industry Regulation No.16/2020. According to the cost-based analysis results, the goods and services at the pilot project stage had the TKDN value of 27.4%. However, due to an increase in the number of main domestic components at the commercial stage, this value increased to 70.9%. Meanwhile, according to the processed-based analysis results, the salt production had the same processes at the pilot project stage and commercial stages. The TKDN value of 85.5% was obtained for the two stages. The value is relatively high because the raw material is produced locally with the local labor and used work tools owned by the local industry. The cost-based analysis was found to be highly dependent on the equipment component’s origin, while the process-based analysis depends on the origin of labor, works tool, and material owner.

Incorporating potassium-rich waste material in a sustainable way to stabilize dispersive clay: A novel practical approach for the construction industry

The inappropriate use of dispersive clay in constructing roads/highways, embankments, and other structures causes significant challenges to the construction industry. The dispersive clay treatment in this work was carried out for the first time using eco-friendly and sustainable potassium-based material rather than calcium-based, which makes it particularly innovative. This study investigated the impact of potassium-rich wood ash (KRWA) on dispersion, index, unconfined compression strength (UCS), consolidation, physio-chemical, mineralogical and microstructure properties. KRWA amount varied up to 35% and cured for up to 60 days at about 20 to 25 °C. The results revealed that 10% KRWA is the optimum content, decreasing the dispersion and sodium percentage by 82% and 57%, respectively, with 28 days of curing and changing the soil class to non-dispersive. A 56% reduction in plasticity was observed with optimum content, which caused the soil to become more friable, enhancing the treated clay's workability. Moreover, a 575% raise in UCS and a 60% reduction in compressibility were witnessed, which indicates improved load-bearing capacity and the capability of the stabilized clay to bear external loads better. The physio-chemical study revealed that the ion exchange, agglomeration, and flocculation take place immediately with minor/no curing that decreased the repulsion and diffuse double layer thickness, followed by the initiation of the pozzolanic activity, which formed different cementitious gels. X-ray diffraction and scanning electron microscopy experiments confirmed the formation of gels and produced a considerably thicker microstructure. Moreover, cost-based analysis shows that KRWA is more economical than conventional additives for highway/road applications.

Cost-based analysis of the impact of data completeness and representational consistency

Data quality is an important topic for businesses and therefore requires appropriate analysis tools. Although several rule-based systems exist today for quality measurement, their results do not always reflect the real impact of quality issues on practical data usability and are therefore not well-suited to base economic decisions on. This work practically implements and evaluates an alternative, cost-based approach for data quality analysis starting from a ‘fitness for use’-perspective. The practical impact of completeness and representational consistency of data stored in an integrated relational database is investigated in an experiment with 218 volunteers. Two alternative versions of this database are then prepared by manually improving their data quality. Participants are randomly assigned to one of three databases and are given a set of questions to resolve by means of SQL. As questions are resolved, we measure several cost-based indicators such as ability to solve, time to solve and number of attempts. Results indicate that the impact of data quality issues can differ significantly from what would be expected when using rule-based measurement. Effects range from almost no impact to a 65% reduction in time needed to solve tasks. Effect sizes up to 0.43 using one-way ANCOVA tests are observed.

Optimising vitrectomy operation note coding with machine learning.

The accurate encoding of operation notes is essential for activity-based funding and workforce planning. The aim of this project was to evaluate the procedural coding accuracy of vitrectomy and to develop machine learning, natural language processing (NLP) models that may assist with this task. This retrospective cohort study involved vitrectomy operation notes between a 21-month period at the Royal Adelaide Hospital. Coding of procedures were based on the Medicare Benefits Schedule (MBS)-the Australian equivalent to the Current Procedural Terminology (CPT®) codes used in the United States. Manual encoding was conducted for all procedures and reviewed by two vitreoretinal consultants. XGBoost, random forest and logistic regression models were developed for classification experiments. A cost-based analysis was subsequently conducted. There were a total of 1724 procedures with individual codes performed within 617 vitrectomy operation notes totalling $1 528 086.60 after manual review. A total of 1147 (66.5%) codes were missed in the original coding that amounted to $736 539.20 (48.2%). Our XGBoost model had the highest classification accuracy (94.6%) in the multi-label classification for the five most common procedures. The XGBoost model was the most successful model in identifying operation notes with two or more missing codes with an AUC of 0.87 (95% CI 0.80-0.92). Machine learning has been successful in the classification of vitrectomy operation note encoding. We recommend a combined human and machine learning approach to clinical coding as automation may facilitate more accurate reimbursement and enable surgeons to prioritise higher quality clinical care.

Optimal maintenance tasks taking into account cost indicators

The reliability of technical systems plays a key role in ensuring their efficient operation over time. This article discusses the importance of reliability in maintaining preset parameters of the functioning of a system and its dependence on operating conditions. Maintenance is done to maintain the reliability of a system and control its functionality. The authors propose methods for selecting quality indicators and the optimal frequency of preventive maintenance and emphasise the importance of considering cost aspects when making decisions on maintenance. In conclusion, the article offers a brief algorithm for quality control of technical systems while placing an emphasis on system safety and economic efficiency. The study demonstrates the need to develop and apply new cost-based analysis methods to determine optimal maintenance strategies for technical systems. Overall, the article provides recommendations for improving maintenance operations and increasing the reliability of technical systems.

Cost-based analysis and optimization of distributed generations and shunt capacitors incorporated into distribution systems with nonlinear demand modeling

This paper optimizes the allocations of Distributed Generators (DG) and Shunt Capacitor (SC) banks to minimize a multi-objective problem consisting of four different indices. These indices include active/reactive power loss reduction, voltage profile improvement, and system stability enhancement. Consequently, the costs of energy loss, allocated devices, and total operation are estimated per year for different installed DG/SC pairs for studied systems. Multi-DG and SC banks are optimally installed in the standard 69-bus and 136-bus radial distribution systems considering six nonlinear load models. The six models are generated from the nonlinear relationship between the system voltage and demand. Furthermore, the load type affects the DG/SC allocation optimization problem and other performance parameters such as the total voltage deviation (TVD), stability index (SI), and the power drawn from the utility. A new metaheuristic optimization called the Jellyfish Search Algorithm (JSA) is adopted and applied to allocate the DG units and the SC banks optimally into the distribution systems. The savings in the annual energy loss reach 65.88%, 95.99%, and 97.91% with industrial load demand for 1DG/1SC, 2DG/2SC, and 3DG/3SC allocations, respectively for the 69-bus RDS. While for the 136-bus RDS, the saving reaches 39.71% with constant-impedance demand, 58.84%, and 73.87% with commercial demand for 1DG/1SC, 3DG/3SC, and 6DG/6SC pairs, respectively. It is found that the JSA is practical and suitable for solving these nonlinear optimization problems, and it gives better results as compared to other algorithms in the literature.

Prediction of Neutropenic Events in Chemotherapy Patients: A Machine Learning Approach.

Severe and febrile neutropenia present serious hazards to patients with cancer undergoing chemotherapy. We seek to develop a machine learning-based neutropenia prediction model that can be used to assess risk at the initiation of a chemotherapy cycle. We leverage rich electronic medical records (EMRs) data from a large health care system and apply machine learning methods to predict severe and febrile neutropenic events. We outline the data curation process and challenges posed by EMRs data. We explore a range of algorithms with an emphasis on model interpretability and ease of use in a clinical setting. Our final proposed model demonstrates an out-of-sample area under the receiver operating characteristic curve of 0.865 (95% CI, 0.830 to 0.891) in the prediction of neutropenic events on the basis of only 20 clinical features. The model validates known risk factors and offers insight into potential novel clinical indicators and treatment characteristics that elevate risk. It relies on factors that are directly extractable from EMRs, provided a tool can be easily integrated into existing workflows. A cost-based analysis provides insight into optimal risk thresholds and offers a framework for tailoring algorithms to individual hospital needs. A better understanding of neutropenic risk on an individual level enables a more informed approach to patient monitoring and treatment decisions.

Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants

• Cost-based modelling of the share of different modes of vehicle use. • We consider: manual and autonomous vehicle (AV) ownership and on-demand AV services. • Heterogeneity in travel and cost pattern considered by using representative data. • Ownership (manual or automated) is the least cost option for most cases. • High income, business use, rurality and primary vehicle are associated with ownership. A major uncertainty in the diffusion of autonomous vehicles is the split between ownership and automated mobility services. We calculate total cost of ownership and use (TCOU) to compare four alternatives: private manually driven vehicles, private automated vehicles, automated on-demand exclusive use mobility services (ridesourcing) and automated on-demand pooled mobility services (ridesplitting), for both conventional and electric propulsions. We also included potential usefulness of travel time in the driverless vehicles in the TCOU calculations, thus including some of the non-financial factors in travel decision making. While nearly all current studies are limited to comparing average representative trips or mileage of existing vehicles, we calculate TCOUs for every vehicle in the UK National Travel Survey dataset, considering heterogeneity in mileage patterns, trip purposes, time spent driving, value of time, vehicle age, depreciation and other factors between different vehicles. The results suggest that a near-total transition to automated ride services is highly unlikely, since ownership of (automated or manually driven) vehicles continues to be the least-cost option in most cases. Even in the most pro-mobility service test case, ownership remains more cost-effective for one third of the current vehicle fleet. Regression analysis shows that higher income of the main driver, business use of the vehicle, rural location of the household or being the main household vehicle leads to a higher likelihood that automated vehicle ownership will be lower cost compared to automated mobility services. Within automated on-demand ride services, exclusive use services are cost effective for more cases compared to pooled, shared-use type options, with uncertain consequences for future travel demand.

The necessity of automated manufacture for cell-based immunotherapies: a cost-based analysis

The necessity of automated manufacture for cell-based immunotherapies: a cost-based analysis

Cost-based analysis of operative maxillofacial fracture managements

Aims: There is no current study presenting a descriptive cost-based analysis of operative maxillofacial fracture managements in Turkey. Therefore, this study attempted to investigate the overall treatment costs of maxillofacial traumas. Materials and Methods: Maxillofacial trauma patients treated between January 2012 and December 2016 with at least 12 months of follow-up were included in this study. Parameters including age, gender, etiology of injury, site of trauma, additional traumas, comorbidities, length of hospitalization, treatment technique and material used in surgery, duration of surgery, complication rates, and hospital costs for treatments were analyzed retrospectively. The costs were converted into USD ($) according to the currency exchange rate. Results: The most cost-effective (351$) was the teenage group (10–17 years) and the most expensive (793$) was the group over 61 years of age with significant differences. Etiologically, assaults were statistically significantly (P = 0.047) cheaper than motorbike accidents. The most expensive treatments were tetrad site fractures, and the most cost-effective treatments were maxillary fractures. The total costs of tetrad site fractures (1088$) was statistically significantly expensive than that of maxillary fractures (245$) (P = 0.006). Additional injuries caused statistically significantly higher costs to maxillofacial trauma treatments (P = 0.002). Closed techniques or plate fixations with six holes or less were statistically significantly cheaper than plate fixations with more than six holes (P

Economic aspects of ensuring the capacity adequacy of electric power systems

The present report deals with economic issues of selecting means ensuring the capacity adequacy of electric power systems. Cost analysis of various engineering measures ensuring the capacity adequacy has been performed, namely: construction of backup generating facilities, erection of new power transmission lines, or increase of transmission capacity of existing power lines. The cost-based analysis has been conducted based on investment programs and regulatory acts in place. Recommendations on developing computational models of power systems have been given based on the results obtained in order to assess the capacity adequacy parameters, with account made for the cost of various engineering measures to be taken for their improvement.In prevailing practice of calculation of capacity adequacy parameters, the structure of electric power systems transmission network is presented as a transport model which makes an aggregate of reliability zones and tie-lines between them of a given transmission capacity. The main objective of calculation of capacity adequacy parameters is to determine the required generating capacity redundancy level, i.e. the values of the capacity margin and its location within electric power systems to ensure a required level of capacity adequacy. With that in mind, when evaluating and accordingly when forming transport models, it should be useful to take into account the transmission constraints only for those power grid segments, whose cost of transmission capacity increase is comparable with that of construction of new generating facilities.On the basis of calculation data, one may state that for overhead electric lines of short or average length the cost of 1 kW of its transmission capacity will be considerably lower than that of installed capacity of a new generating facility, with the above costs comparable only with the length of the line close to its critical value. When forming transport models of electric power systems, it is useful to take into account not only the distance between electric power system nodes, but also their potential need of margin capacity. As far as remote nodes are concerned, if these are of low need in margin capacity, it should be reasonable to separate them as specifi c reliability areas.

Design and Implementation of Transformer-Based Multilevel Inverter Topology With Reduced Components

This paper presents a nine-level transformer-based inverter requiring only eight switches. The envisaged structure consists of two standard H-bridges fed from a single dc source. Besides, a single-phase transformer is employed to aid the process of intermediate voltage level generation. An ad-hoc pulsewidth modulation scheme based on boolean logic form equations is developed to derive the gating pulses. An effortless extension of the proposed inverter to a higher number of voltage levels is also achieved by generalizing the switching functions. Furthermore, the superior performance of the proposed topology is demonstrated through a comprehensive cost-based analysis. Finally, the validation of the proposed topology is accomplished through experiments on a down-scale prototype, and the measurement results are included.

Cooling towers performance in a changing climate: Techno-economic modeling and design optimization

This paper presents a model of a natural draft wet type cooling tower, which is based on the conservation laws of thermodynamics. The model assesses the cooling abilities of a tower, the evaporation rate, and the amount of required make-up water, all represented as a function of the atmospheric conditions. The purpose of the model is to estimate the effects of extreme weather conditions on the thermodynamic efficiency of a natural draft wet type cooling tower. World climate is changing and average temperatures are anticipated to rise in the near future, thus affecting the electrical energy generation. To that aim, we study the climate change effects on the ability of natural draft wet type cooling towers to reject heat and hence on the electricity generation of thermal power plants. Additionally, we perform cost-based analyses of a cooling tower considering the long-term projections for air temperature increase, and exemplify our model with reference to a location in France. The results show a remarkable drop in the cooling tower efficiency, and, hence, significant electricity generation losses even when a small increase of atmospheric temperature above the cooling tower design temperature occurs. Furthermore, the results of the cost-based analysis show that large electricity losses are expected. However, the performed cost-based analyses, considering climate change projections, show that even with the highest temperature increase, there is no need for additional tower height. In other words, the concrete costs outweigh the generated revenues from the curtailed power as result of insufficient cooling.

Implications of Robotic Surgery

The interest that I have in robotic surgery stems from the discrepancies between literature at the time that my current hospital purchased their system and the aggressive marketing campaign from the parent company. In urology, the robot is marketed as “nerve-sparing” during prostatectomies and in cardiac it allowed more dexterity or finer motor control. The bulk of the concerns center around issues such as system resetting; electrosurgical arch; increased surgical time; prolonged carbon dioxide insufflation; unnecessarily extended amounts of time under anesthesia; and extremely high costs to purchase and maintain the system on site. A cost-based analysis and a surgical time consideration of robotic versus laparoscopic and open procedures disprove the regularly cited benefits of using a robotic console over the trained surgeon hands for not only surgical risk but financial benefits to both the facility and patient. I gathered records of robotic, laparoscopic and open procedures, the time each takes, the financials for instrumentation and the legal issues or complication associated for each. The robotic technique is a greater cost than any procedure comparable and at an increase of surgical and/or anesthetic time. The greater the anesthetic time, the more potential harm to patients. The greater the surgical time, the higher the risk from increased pneumoperitoneum CO2 insufflation on the cardiovascular and respiratory systems. The higher the cost ratio, the less benefit for the practicing facility. Legalities are a new issue to consider when the robot or the parent company is found at fault considering the health insurance agencies have taken a stand on compensation for only the diagnosis and not the techniques or technology utilized for that treatment.

Economic aspects of ensuring the capacity adequacy of electric power systems

The present report deals with economic issues of selecting means ensuring the capacity adequacy of electric power systems. Cost analysis of various engineering measures ensuring the capacity adequacy has been performed, they are as follows: construction of margin generating capacities, erection of new power transmission lines or increase of transmission capacity of existing power lines. The cost-based analysis has been conducted following investment programs and regulatory acts in place. Recommendations on developing computational models of power systems have been given based on the results obtained in order to assess the capacity adequacy indices with account made for the cost of various engineering measures to be taken for their improvement.