Potential For Improving Efficiency Research Articles

MEASURING EFFICIENCY USING DATA ENVELOPMENT ANALYSIS: APPLICATION ON 12 POLICE PRECINCTS IN DAVAO CITY, PHILIPPINES

<p>Public security plays a vital role in a developing country. It brings positive externalities. This means that it is the function of government to ensure the protection of citizens, persons in their territory, organization, and institutions against threats. The main purpose of this study is to determine the efficiency of 12 Police Precincts in Davao City, Philippines. The inputs and outputs for police performance measurement were first identified. Data Envelopment Analysis and Multiple Regression Analysis were used to measure efficiency and changes to overall services between 2015-2017. We use window analysis and output-oriented DEA models to sharpen our efficiency estimates with both constant and variable returns to scale. The problem of the presence of non-discretionary input variables is explicitly treated in the models used. Potential improvements in the technical efficiency of police precincts are examined by readjusting the output/input indicators. The analysis indicates that some differences in operating environments, especially socioeconomic factors such as residents and young people's population, significantly influence the efficiency of police precincts.</p><p> </p><p><strong>JEL</strong>: H11; H50; H76</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0559/a.php" alt="Hit counter" /></p>

Energy efficiency improvement potentials through energy benchmarking in pulp and paper industry

This study aims to highlight the energy improvement potentials of Pakistan's paper sector that is one of the most energy intensive industries by benchmarking its specific energy consumption (SEC) to produce a similar grade of paper. To address issues such as the lack of indicators for energy efficiency benchmarking in Pakistan's paper industry. Furthermore, energy saving potential was estimated by comparison with paper industries in the United Kingdom and Canada, where energy benchmarks have already been established and data on energy benchmarking is readily available. This study energy consumption data accounts for 75% of the total energy utilized in Pakistan's paper industry and is compared with the energy consumption of the UK and Canada paper sectors where the most up-to-date energy-saving techniques are used. The calculation shows that when compared to the paper industries in the UK and Canada, Pakistan's paper industry utilizes an additional 1.3 MWh of energy for every tonne of paper produced. With a total yearly paper production of 314,549 metric tonnes, this equates to an additional 408,913 MWh of overall annual energy use. It is concluded that if the proposed energy benchmark in this study is applied within the country's mill comparison, savings of 16.4% of overall energy consumption in the Pakistan paper sector can be achieved. It is also shown that the implementation of the best available techniques used in the UK and Canada in Pakistan's paper sector could result in a potential energy saving of 43% of the total energy consumed by this sector.

OPTIMIZATION OF HEALTHCARE WORKERS AVAILABILITY : INCREASING PRIMARY HEALTH CARE EFFICIENCY IN INDONESIA

Policy has focused on the unequal distribution of health workers, while the potential for improvements in efficiency to address this problem has been neglected. This study aims to measure and compare the level of efficiency in the use of the available health workforce for the delivery of selected primary healthcare services among districts/cities in Indonesia, and to identify factors influencing that efficiency. The Data Envelopment Analysis method with output orientation to measure efficiency and Tobit regression analysis was performed to determine the effect of contextual factors. The average score for the technical efficiency of primary health care service delivery throughout Indonesia was 1.29, indicating the potential to achieve on average 29% higher coverage of the selected primary health services if all were as efficient as the most efficient. The average efficiency score in the Eastern Indonesia region was 1.62 and the average in the Java-Bali region was 1.05, indicating higher potential efficiency gains in the Eastern Indonesia region. Access to health care facilities was a consistently significant factor influencing the efficiency of primary health care in almost all regions. This study has demonstrated the potential for significant gains in coverage of key primary care services through improvements in the efficiency of use of the existing health workforce.

Water Content Variations and Pepper Water-Use Efficiency of Yunnan Laterite Under Root-Zone Micro-Irrigation.

Understanding the water content variations in Yunnan laterite (red loam soil, SR) in small-scale environments and exploring the potential for crop water-use efficiency (WUE) improvement are crucial for improving water-saving irrigation technologies used in greenhouse agriculture in Yunnan, China. In this study, a closed-loop model for calculating soil water in greenhouse potted cultivation was established based on water conservation. A Yunnan SR, yellow sand soil (SY), and a 1:1 SR–SY mixture (SM) subjected to root-zone micro-irrigation or surface-drip irrigation were experimentally examined to compare their water content variations and pepper WUEs. The results showed that the soil type and soil type–irrigation mode interaction had significant effects on both soil evaporation and pepper WUE, and that the variations in soil evaporation with respect to time can be expressed using a cubic polynomial function. In small-scale greenhouse cultivation, IG has good water-saving potential and is suitable for the SR (which has a better water-retention capacity), whereas IM is more suitable for the SY (which has a better water-penetration capacity). Mixing certain proportions of the SY into the SR will effectively impact the water content variations and crop WUE and provide opportunities for further improving the water-saving efficiency.

Energy efficiency improvement and emission reduction potential of domestic gas burners through re-orientating the angle and position of burner holes: Experimental and numerical study

The trend towards enhancing the thermal performance of domestic cooking burners necessitates developing a new design for such devices. With this picture in mind, this paper numerically and experimentally investigates the effect of burner head design configurations on the energy efficiency and CO emission of domestic gas burners. The results of a three-dimensional steady-state computational fluid dynamics (CFD) model is validated with the experimental data according to Volunteers in Technical Assistance (VITA) standard in cold start, hot start, and Simmer condition for two types of burners. Having the model validated, a step-by-step approach has been undertaken to improve the design of these reference cases, resulted in a total number of nine burner configurations analysed in this research. This is followed by determining the influence of introduced geometries on the thermal efficiency of burners. Based on the insights from the numerical model, the most efficient burner exhibits 3.3–22.2% higher thermal efficiency and 20.2–32.6% lower CO emission—depending on the gas flow rate—relative to the conventional burners. The optimised design can be implemented into existing burners with relatively little need for reconstruction. • Experimental and numerical study of natural gas combustion in domestic gas burners. • Experimental setup is designed to measure the thermal efficiency of typical burners. • A three-dimensional steady-state turbulent model is developed for numerical study. • Intense mixing induced by secondary effect improved the efficiency by 3.3–22.2%. • Optimum burner configuration lowered the carbon monoxide emission by 20.2–32.6%.

Artificial Intelligence Curriculum Needs Assessment for a Pediatric Radiology Fellowship Program: What, How, and Why?

Artificial intelligence (AI) holds enormous potential for improvements in patient care, efficiency, and innovation in pediatric radiology practice. Although there is a pressing need for a radiology-specific training curriculum and formalized AI teaching, few resources are available. The purpose of our study was to perform a needs assessment for the development of an AI curriculum during pediatric radiology training and continuing education. A focus group study using a semistructured moderator-guided interview was conducted with radiology trainees' and attending radiologists' perceptions of AI, perceived competence in interpretation of AI literature, and perceived expectations from radiology AI educational programs. The focus group was audio-recorded, transcribed, and thematic analysis was performed. The focus group was held virtually with seven participants. The following themes we identified: (1) AI knowledge, (2) previous training, (3) learning preferences, (4) AI expectations, and (5) AI concerns. The participants had no previous formal training in AI and variability in perceived needs and interests. Most preferred a case-based approach to teaching AI. They expressed incomplete understanding of AI hindered its clinical applicability and reiterated a need for improved training in the interpretation and application of AI literature in their practice. We found heterogeneity in perspectives about AI; thus, a curriculum must account for the wide range of these interests and needs. Teaching the interpretation of AI research methods, literature critique, and quality control through implementation of specific scenarios could engage a variety of trainees from different backgrounds and interest levels while ensuring a baseline level of competency in AI.

An examination of labor time-use on spring-calving dairy farms in Ireland

The seasonal workload associated with pasture-based dairy farms, combined with increasing herd sizes, has led to a renewed focus on labor time-use and efficiency on dairy farms. The objective of this study was to examine labor time-use on pasture-based dairy farms in the spring and summer seasons. A total of 82 spring-calving Irish dairy farms completed the study from February 1 to June 30, 2019 (150 d). Each farmer recorded their labor input on one alternating day each week using a smartphone app. Any labor input by farm workers not using the app was recorded through a weekly online survey. Farms with data for each month (n = 76) were classified into 1 of 4 herd size categories (HSC) for analysis: farms with 50 to 90 cows (HSC 1); 91 to 139 cows (HSC 2); 140 to 239 cows (HSC 3); and ≥240 cows (HSC 4). Total hours of labor input was similar on HSC 1 (1,821 h) and HSC 2 (2,042 h) farms, but predictably as HSC increased further, total hours of labor input increased (HSC 3: 2,462 h, HSC 4: 3,040 h). On a monthly basis, labor input peaked in February (15.4 h/d) and March (15.7 h/d). The farmer worked on average 60.0 h/wk over the duration of the study period. Hired labor and contractors completed a greater amount of work as HSC increased. Labor efficiency, as measured by hours/cow, improved as HSC increased (HSC 1: 26.3 h/cow, HSC 2: 17.7 h/cow, HSC 3: 14.3 h/cow, HSC 4: 10.9 h/cow), though there were large variations in labor efficiency within HSC. Milking was the most time-consuming task, representing 31% of farm labor input making it an important focus for potential improvements in efficiency. The next 5 most time-consuming tasks were calf care (14%), grassland management (13%), cow care (10%), repairs and maintenance (10%), and administration/business (8%). This study contributes to the understanding of labor use during the busiest (most labor demanding) time of the year on pasture-based dairy farms and points to areas where labor efficiency improvements can be made on farms. The considerable variation in farm labor efficiency observed within HSCs emphasizes the necessity for a greater focus on knowledge transfer of methods to achieve improved labor efficiency and a better work-life balance on many dairy farms. As the 2 busiest months on most dairy farms, February and March require the most focus for identification of potential labor savings.

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. To demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

Exergy Analysis of the Prevailing Residential Heating System and Derivation of Future CO2-Reduction Potential

The residential heating sector accounts for a large share of the worldwide annual primary energy consumption. In order to reduce CO2-emissions, it is therefore particularly important to analyse this sector for potential efficiency improvements. In Europe, natural gas boilers are the most widely used heating technology since they are cost-effective and can be installed in any type of building. The energy efficiency of these boilers is already high. However, in their internal process, heat is generated at a high temperature level which is only used for space heating and therefore a high amount of exergy remains unused. This research aims to develop the potential of using the exergy to further improve the efficiency of the systems. A novel combination of methods is applied to analyse the thermodynamic behaviour of gas-fired boilers in detail and over the cycle of a year. The analysis is performed in two steps: In the first step a system is examined in stationary operating points. This is carried out through an experimental setup and a three-dimensional numerical simulation. In the second step, the obtained data is applied to a transient annual building simulation. The results show the temporal distribution and total amount of the annual exergy loss for a common residential building. The exergy loss accumulates to 16,271 kWh per year, which shows the high potential to partially convert the exergy to electrical energy and significantly reduce the external electricity demand and CO2-emissions of the building. Based on this, new technologies such as Thermoelectric Generators can be developed, which can enable this potential.

Development of self-powered multifunctional piezomagnetic nanoparticles for non-invasive post-surgical osteosarcoma theranogeneration

Non-invasive treatment approaches are gaining increased attention in recent times due to the potential improvement in treatment efficiency. Here we report a brand-new ultrasound (US), magnetic field (MF), and light responsive nanoparticle system based on piezoelectric barium titanate and superparamagnetic iron oxide nanoparticles termed as PiezoMagnetic nanoparticles (PMNPs) for the multimodal anticancer treatment, complimentary imaging, and non-invasive cell stimulation. Systematic electrical studies reveal that PMNPs exhibit superior ferroelectric and conducting properties and produce electrical signals analogous to native tissues when mechanically stimulated and using Food and Drug Administration (FDA) approved Low intensity Pulsed Ultrasound (LIPUS) non-invasively for cell stimulation. The green energy generation from PMNPs are further proved by the real-time demonstration of commercial LED lit-up. Thus, as a proof of concept, we have demonstrated a stepwise treatment efficacy of PMNPs for the post-surgical osteosarcoma therapy, diagnosis, and regeneration (termed as Theranogeneration). The PMNPs exhibited excellent anticancer properties to eradicate the residual osteosarcoma cells by magnetic hyperthermia, photothermal and photodynamic therapy along with complimentary imaging capabilities as X-ray computed tomography contrast agent and label free fluorescent probe. The conjugation of risedronate R (RIS)- a new generation bisphosphonates to PMNPs imparted bone seeking property to PMNPs. Therefore, as a result of noninvasive cell stimulation properties of PMNPs under LIPUS and LIPUS mediated RIS release from PMNPs resulted in enhanced bone regeneration and bone turnover which helps to repair the large bone defects occurs in osteosarcoma resection. Thus, the study corroborates the development of a potential bioactive piezoelectric nanoplatform that can be used to control the cell behaviour and fate in order to develop new types of therapies for multiple diseases including various types of cancers in remotely controlled approaches.

Holistic energy flow analysis of a solar driven thermo-chemical reactor set-up for sustainable hydrogen production

In this contribution, a holistic energy flow analysis of a solar driven pilot plant for green hydrogen production using two-step thermochemical cerium-based redox cycles is carried out. The plant consists of a heliostat field, a large-scale inert gas reactor, an efficient fluid heat recovery system and an electrical vaporizer for steam generation. The system behaviour is physically described, and energy flows are quantified using a complex simulation model considering material and geometric properties of the complete system design. The system energy flow and corresponding impact on plant efficiency is thoroughly analysed with emphasis on plant design, operational strategy, and influence of the crucial control parameters. Influences of a heat recovery system and the size of various types of heat losses are investigated, potential efficiency improvements are revealed and useful possibilities for plant design and material modifications are discussed. The transient system behaviour is investigated by varying temperatures and mass flow rates in a broad practicable range to gain more insight in efficient reactor design and plant control. Two temperature swing strategies are investigated in more detail, which are by far more efficient than any near-isothermal or isothermal strategy for this application.

The potential in efficiency improvement of in-cylinder thermochemical fuel reforming in natural gas engines

With decarbonization becoming the primary focus of the automotive industry, high-efficiency and low-emission engine technologies have garnered increasing attention. Among the advanced technologies, fuel reforming is a promising way to reduce emissions and increase efficiency with hydrogen generated onboard. This paper focuses on the potential of improving efficiency using in-cylinder thermochemical fuel reforming combustion in natural gas engines. The experimental results revealed that combustion in the reforming cylinder inevitably deteriorates, and hydrogen generated by fuel reforming could not counteract the slower combustion due to fuel enrichment. However, the presence of hydrogen in the nonreforming cylinder significantly increased the flame propagation speed, hence improving combustion efficiency. After a series of variable-parameter tests, it was found that the appropriate reforming equivalence ratio was 1.15 at low load and ∼1.2–1.3 at medium to high loads, with efficiency increased up to 4–5% and 8–12%, respectively. Dual-fuel reforming combustion experiments were conducted using a rapid compression machine and a single-cylinder engine to further explore the fuel reforming combustion. The results suggested that, at medium load, the combustion instability in the reforming cylinder can be solved by adopting two-stage combustion at an equivalence ratio of 1.3, and the indicated thermal efficiency could reach 43%. Based on the research results, a remarkable potential improvement in efficiency can be achieved if reforming combustion is successfully implemented. Dual-fuel reforming has the most potential to achieve an even higher engine efficiency, and its practical issues such as transient engine control and soot formation deserve further investigation.

Energy Efficiency Optimization for Machining of Wood Plastic Composite

Enhancing energy efficiency is the key to realizing green manufacturing. One major area of interest in this regard is the improvement of energy efficiency of machine tools during the production of building materials. This project focuses on energy efficiency during the spiral milling of wood plastic composites. To this end, a response surface method was adopted to develop a model and establish the relationship between energy efficiency and milling conditions. Analysis of variance based on individual factors as well as two-factor interactions was performed to gauge their effects on energy efficiency. It was found that milling depth was positively correlated to power efficiency, while spiral angle and feed per tooth displayed non-monotonic behavior. An attempt was made to predict milling conditions that will yield the greatest material removal rate and power efficiency. For wood plastic composites subjected to up-milling, it was determined that a feed per tooth of 0.1 mm, milling depth of 1.5 mm, and spiral angle of 70° were ideal. Considering the potential improvements in energy efficiency and surface quality that these process parameters will bring, it is strongly recommended for use in the industrial machining of wood plastic composites.

An overview of machine learning applications for smart buildings

The efficiency, flexibility, and resilience of building-integrated energy systems are challenged by unpredicted changes in operational environments due to climate change and its consequences. On the other hand, the rapid evolution of artificial intelligence (AI) and machine learning (ML) has equipped buildings with an ability to learn. A lot of research has been dedicated to specific machine learning applications for specific phases of a building's life-cycle. The reviews commonly take a specific, technological perspective without a vision for the integration of smart technologies at the level of the whole system. Especially, there is a lack of discussion on the roles of autonomous AI agents and training environments for boosting the learning process in complex and abruptly changing operational environments. This review article discusses the learning ability of buildings with a system-level perspective and presents an overview of autonomous machine learning applications that make independent decisions for building energy management. We conclude that the buildings’ adaptability to unpredicted changes can be enhanced at the system level through AI-initiated learning processes and by using digital twins as training environments. The greatest potential for energy efficiency improvement is achieved by integrating adaptability solutions at the timescales of HVAC control and electricity market participation.

Solution-Processed, Inverted AgBiS2 Nanocrystal Solar Cells.

AgBiS2 nanocrystals are a promising nontoxic alternative to PbS, CsPbI3, and CdS quantum dots for solution-fabricated nanocrystal photovoltaics. In this work, we fabricated the first inverted (p-i-n) structure AgBiS2 nanocrystal solar cells. We selected spray-coated NiO as the hole-transporting material and used PCBM/BCP as the electron-transporting material. Combining transient photocurrent and photovoltage measurements with femtosecond transient absorption spectroscopy, we investigated the charge collection process on metal oxide/AgBiS2 interfaces and demonstrated that the NiO/AgBiS2 NC junction in the p-i-n configuration is more efficient for charge carrier collection. The fabricated p-i-n solar cells exhibited a 4.3% power conversion efficiency (PCE), which was higher than that of conventional n-i-p solar cells fabricated using the same sample. Additionally, inverted devices showed an ultrahigh short-circuit current (JSC) over 20.7 mA cm-2 and 0.38 V open-circuit voltage (VOC), suggesting their potential for further improvements in efficiency and, eventually, for large-scale production.

Application of solid lubricant for enhanced frictional efficiency of deep drawing process

Manufacturing processes are usually energy intensive, contributing to the global carbon dioxide emissions. Deep Drawing is one of the most common types of sheet metal forming processes with great potential for energy efficiency improvement. In this paper, the optimised combination of molybdenum disulphide (MoS2) and graphite is proposed as a solid lubricant to reduce the punching force and energy consumption of deep drawing process. Different mixtures of MoS2 and graphite are prepared and their tribological performance are measured using experimental tests on tribometer. In order to investigate the friction reduction rate in deep drawing process, finite element simulation of the drawing process is performed. Results show that friction reduction using proposed combination of lubricants has significant effect on punching force and would provide greater process efficiency.

Optimization of oxy-fuel circulating fluidized bed combustion system with high oxygen concentration

High oxygen concentration oxy-fuel circulating fluidized bed (CFB) combustion technology is a high efficiency and low cost oxy-fuel combustion technology, which also has high potential of optimization and efficiency improvement. In this research, energy efficiency is analysed to acquire the effects of flue gas recirculation mode, preheating temperature and oxygen purity on the net efficiency and energy consumption of the 50% oxy-fuel combustion system, so as to obtain the further optimization strategy. The following results are obtained by simulation. The optimal extraction position of recycled flue gas (RFG) is gas preheater outlet, and the net power generation efficiency increases by 0.23% to 25.08%. As the preheating temperature increases from 230 to 400 °C, the net efficiency increases by 1.19% to 26.04%. The net efficiency increases first then decreases as the oxygen purity at ASU outlet increase from 89% to 97.4%, and the optimal value is the 94%. Finally, the optimal system is obtained when RFG is extracted from gas preheater outlet, the preheating temperature is 400 °C and the oxygen purity at ASU outlet is 94%. The net efficiency of the optimization system reaches 27.4%, increasing by 2.55%.

Efficiency Improvement in Sugar Mills through Bagasse Gasification

Biomass energy is useful in mitigating greenhouse gases as biomass growth captures CO2 from the atmosphere. This captured CO2 is eventually released upon the use of these biomass feedstocks, leading to a short duration carbon cycle. One prominent biomass feedstock is the sugarcane bagasse that is a by-product of sugar mills. Conventionally, the bagasse produced after crushing sugarcane is utilized in mills by directly burning it in the boilers. However, an efficient way of utilizing this biomass fuel would be through gasification. The biomass gasification process produces syngas which can be used as fuel for meeting the heat and power demands of the sugar mill, as well as surplus electricity, which can be supplied to the grid. The present study aims to highlight the efficiency improvement potential of bagasse gasification. The entire sugar mill as well as the bagasse gasification process, have been modeled in the ASPEN Plus® software. Heat integration has been performed to optimize the process flowsheets. The electrical energy generated by combusting bagasse is estimated to be 0.57 kWh/kg of bagasse combusted. In contrast, the gasification process can increase this energy generation up to 1.16 kWh/kg of bagasse at 10 % moisture content (by wt.). This study aims to provide awareness about the cleaner and efficient utilization of the energy that lies dormant in these industrial residues.

Exergy Analysis of Coal-Based Series Polygeneration Systems for Methanol and Electricity Co-Production.

This paper quantifies the exergy losses of coal-based series polygeneration systems and evaluates the potential efficiency improvements that can be realized by applying advanced technologies for gasification, methanol synthesis, and combined cycle power generation. Exergy analysis identified exergy losses and their associated causes from chemical and physical processes. A new indicator was defined to evaluate the potential gain from minimizing exergy losses caused by physical processes—the degree of perfection of the system’s thermodynamic performance. The influences of a variety of advanced technical solutions on exergy improvement were analyzed and compared. It was found that the overall exergy loss of a series polygeneration system can be reduced significantly, from 57.4% to 48.9%, by applying all the advanced technologies selected. For gasification, four advanced technologies were evaluated, and the largest reduction in exergy loss (about 2.5 percentage points) was contributed by hot gas cleaning, followed by ion transport membrane technology (1.5 percentage points), slurry pre-heating (0.91 percentage points), and syngas heat recovery (0.6 percentage points). For methanol synthesis, partial shift technology reduced the overall exergy loss by about 1.4 percentage points. For power generation, using a G-class gas turbine decreased the overall exergy loss by about 1.6 percentage points.

Guest Editorial: Special Issue on Magnetically Levitated Motor Systems

Magnetically levitated motor systems based around bearingless motors and generators and magnetic bearings offer a potential step change improvement in motor system lifetime and efficiency, solve critical challenges related to oil-lubricated contact bearings, and feature prognostic capabilities for condition-based maintenance. Acceptance of this technology has been historically limited by challenges related to cost, design and control complexity, manufacturing issues, and low force density. However, recent advances in supporting technologies enable new approaches to address these challenges.