Labor Cost Savings Research Articles

Utility of large language models for creating clinical assessment items.

To compare student performance, examiner perceptions and cost of GPT-assisted (generative pretrained transformer-assisted) clinical and professional skills assessment (CPSAs) items against items created using standard methods. We conducted a prospective, controlled, double-blinded comparison of CPSA items developed using GPT-assistance with those created through standard methods. Two sets of six practical cases were developed for a formative assessment sat by final year medical students. One clinical case in each set was created with GPT-assistance. Students were assigned to one of the two sets. The results of 239 participants were analysed in the study. There was no statistically significant difference in item difficulty, or discriminative ability between GPT-assisted and standard items. One hundred percent (n=15) of respondents to an examiner feedback questionnaire felt GPT-assisted cases were appropriately difficult and realistic. GPT-assistance resulted in significant labour cost savings, with a mean reduction of 57% (880 GBP) in labour cost per case when compared to standard case drafting methods. GPT-assistance can create CPSA items of comparable quality with significantly less cost when compared to standard methods. Future studies could evaluate GPT's ability to create CPSA material in other areas of clinical practice, aiming to validate the generalisability of these findings.

Extraction of crop canopy features and decision-making for variable spraying based on unmanned aerial vehicle LiDAR data

Implementation of precision agriculture aerial applications using unmanned aerial vehicles (UAVs) represents a pivotal technological aspect in precision agriculture. However, current UAV applications are still far from realizing true precision variable spraying. The use of UAVs to analyze and model crop growth, pest and disease conditions, and other pertinent information to enable targeted precision spraying poses a formidable challenge. Herein, a UAV variable-rate spray system with adaptive flow control based on crop canopy morphology was developed using a UAV equipped with a light detection and ranging (LiDAR) sensor to support precision spraying of cotton. Point cloud data captured by the LiDAR sensor initially undergo processing using the simple morphological filter (SMRF) algorithm and feature extraction function. Subsequently, cotton canopy volumes measured by the alpha shape algorithm, convex hull by slices shape algorithm, and voxel-based method were compared with manual measurements with coefficient of determination R2 values of 0.89, 0.78, and 0.82, respectively. The results of the validation experiments denote that the cotton canopy volume obtained using the alpha shape algorithm is in good agreement with that obtained using manual measurements; thus, this algorithm is employed for volume calculations in this design. Models were constructed to relate UAV flight parameters, cotton canopy volume, and spraying parameters to the duty cycle of variable control signals, which enabled the UAV to adjust the flow rate in real time to match the cotton canopy structure. In addition, a polygonal prescription map decoding algorithm based on the cotton canopy morphology was introduced. This algorithm is used for real-time decoding of prescription maps and extraction of flow, latitude, and longitude information. Finally, field experiments were conducted, and the results indicate that the UAV variable-rate spray system designed in this study exhibits biological efficacy (effective application thresholds provided by the pesticide manufacturer) comparable to that of the constant-rate spray system at a lower application rate. Furthermore, it exhibited superior spray deposition efficiency and coverage compared with the constant-rate spray system. Notably, the use of the variable-rate spray system in cotton crops resulted in a 43.37% reduction in spray volume while maintaining high application quality, providing an opportunity for pesticide and labor cost savings.

Farmers' Perceptions on Implementing Automatic Milking Systems in Large USA Dairies: Decision-Making Process, Management Practices, Labor, and Herd Performance.

Automatic Milking System (AMS) installations are increasing in the USA despite the higher investment cost than conventional systems. Surveys on AMSs conducted outside the USA focused on small-medium herds, specific regions, or aspects of AMS milking. This study described farmers' perceptions about the decision-making process of adopting an AMS in the USA's large dairies (≥7 AMS boxes) regarding changes in technology, housing, management practices, labor, herd performance, and health. After being contacted, 27 of 55 farmers from large AMS herds completed the survey. The main reasons for adopting an AMS were labor costs, cows' welfare, and herd performance. Most farms constructed new barns, used a free-flow traffic system, and changed their feed management. Increases in water and energy use were perceived by 42% and 62% of farmers, respectively. Farmers estimated decreases in labor costs of over 21%, and AMS employees worked 40-60 h/week. Milk production increases were reported by 58%, with 32% observing higher milk fat and protein content. Easier sick cow detection, better mastitis management, and improvements in pregnancy rates were reported. Thus, farmers transitioning to AMSs perceived altered resource utilization, labor cost savings, and improvements in employee quality of life, animal welfare, and farm management. While 54% of respondents would recommend an AMS to other farms, 38% suggested considering additional aspects prior to adoption.

IRRIGATION PROCEDURE (MODE) OF TOMATO GROWN BY THE LOW PRESSURE DRIP IRRIGATION METHOD

Presently, the Republic of Kazakhstan, particularly the Kyzylorda region, grapples with a significant water scarcity issue. In light of this, the utilization of the drip irrigation method plays a crucial role in the judicious management of water resources. In regions like Kyzylorda, characterized by pronounced drought conditions, the efficacy of employing a low-pressure drip irrigation system is notably high. This approach results in an augmented land utilization coefficient, savings in material and labor costs, and an enhanced efficiency in the utilization of irrigation water. The implementation of a drip irrigation system contributes to the improvement of soil nutrition, air circulation, and water-physical properties. It mitigates soil erosion risks, ensures optimal water utilization by supplying irrigation water directly to the roots of each plant, and thereby maximizes the plants' water utilization efficiency. The likelihood of achieving abundant, excellent, and consistent harvests from agricultural crops rises. This method offers several advantages compared to alternative irrigation techniques, including reduced labor costs, preservation of the soil's fundamental structure, prevention of surface soil folds, the ability to concurrently apply fertilizers to the root system area, a potential 30-100% increase in crop productivity, a 50-60% decrease in irrigation water usage, and suitability for use in areas with high slopes.

Extended Sanitation Intervals for Cage Components and Automated Watering Valves: Validation and Cost Analysis.

Although the Guide suggests changing rodent cage components every 2 wk, it states that "decreased sanitation frequency may be justified if the microenvironment in the cages, under the condition of use ..., is not compromised." The purpose of this study was to evaluate extended sanitation intervals of cage components (automated watering valve, wire bar lid, and filter top) of mouse individually ventilated caging (IVCs) at our institution. We hypothesized that there would be no significant difference in relative light units measured by ATP luminometry of these cage components at the control time point of 14 d as compared with each extended time interval: 28, 56, and 84 d. In addition, for automated watering valves, the study was extended to 168 d. We also hypothesized that time-and-motion studies performed by moving to a sanitation interval of 84 d for all components would result in substantial time and cost savings. The components of a total of 24 cages containing 4 or 5 mice each were swabbed, and an ATP luminometer was used to detect organic matter. We found no significant differences in organic matter load between 14 d and all other time points for all cage components. Our time- and cost-savings analysis found that extending the sanitation interval of cage components from every 2 wk (14 d) to every 3 mo (84 d) for every 10,000 cages would save about 3,000 technician hours annually, for a total annual labor cost savings of about $100,000. This study is the first to validate the extended sanitation interval of automated watering valves and confirms the findings of previous studies that validated the extended sanitation frequency of wire bar lids and filter tops of rodent IVCs. Overall, extending the sanitation frequency of cage components reduces workload of animal care staff without compromising the cage microenvironment.

Nonregular Employment and Payout Policy: Evidence from the Massachusetts Independent Contractor Law

Compared with regular employees, independent contractors (ICs) offer labor flexibility and cost savings to their employers. Using a difference-in-differences design around the 2004 Massachusetts law that discourages IC usage, we find that this exogenous decrease in IC usage makes treated firms’ earnings more sensitive to changes in sales, increases labor-related expenses, and reduces profitability. Firms subsequently reduce share repurchases. The decrease is more pronounced for firms with high operating leverage and financial constraints. Our results are robust to entropy balancing. We conclude that IC usage affects firms’ operating leverage and profitability, which in turn, influence payout policy. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.00103 .

ChatGPT Isn't Magic

ChatGPT Isn't Magic

P‐TS‐51 | Labor Cost Savings with Updated Standing Order Strategy

P‐TS‐51 | Labor Cost Savings with Updated Standing Order Strategy

A cooperative model to lower cost and increase the efficiency of methane leak inspections at oil and gas sites

Methane is a potent greenhouse gas that tends to leak from equipment at oil and gas (O&G) sites. Conventional leak detection and repair methods for fugitive methane emissions are labor-intensive and costly because they involve time-consuming close-range, component-level inspections at each site. This has prompted duty holders to examine new methods and strategies that could be more cost-effective. We examined a cooperative model in which multiple duty holders of upstream O&G sites in a region use shared services to inspect on-site equipment using optical gas imaging camera or Method 21. This approach was hypothesized to be more efficient and cost-effective than independent inspection programs by each duty holder in the region. To test this hypothesis, we developed a geospatial simulation model using empirical data from 11 O&G-producing regions in Canada and the United States. We used the model to compare labor cost, transit time, mileage, vehicle emissions, and driving risk between independent and co-op leak inspection programs. The results indicate that co-op leak inspection programs can generate relative savings in labor costs (1.8%–34.2%), transit time (0.6%–38.6%), mileage (0.2%–43.1%), vehicle emissions (0.01–4.0 tCO2), and driving risk (1.9%–31.9%). The largest relative savings and efficiency gains resulting from co-op leak inspection programs were in regions with a high diversity of duty holders, which was confirmed with simulations of fictitious O&G sites and road networks spanning diverse conditions. We also found reducing leak inspection time by 75% with streamlined methods can additionally reduce labor cost by 8.8%–41.1%, transit time by 5.6%–20.2%, and mileage by 2.60%–34.3% in co-op leak inspection programs. Overall, this study demonstrates that co-op leak inspection programs can be more efficient and cost-effective, particularly in regions with a large diversity of O&G duty holders, and that methods to reduce leak inspection time can create additional savings.

RESEARCH MS ACCESS SOFTWARE FOR APPLICATION IN SMART GARMENT FACTORY MACHINE MANAGEMENT

This study was conducted to support the process of Vietnamese garment companies in building smart factories with production activities that can be controlled automatically. It is a model for managing the system of machines in the factory using MS Access, which allows for updating machines information, searching for machines, reporting, and statistics. It allows for managing the information changes in the system, including machine information, warranty time, maintenance schedule, repair history, disposed of machines, and purchasing new machines. The system replaced a batch of manual operations and paperwork procedures with queries, macros, and reports. The results are labor cost savings, reduced costs, and increased machine utilization efficiency.

A new approach to predicting compositional regions of facilitated glass formation in the Gd-Ni-Al system

Efficient search for new compositions of amorphous alloys and significant savings in labor and material costs for the ones production require the development of reliable theoretical methods for predicting the glass-forming ability of multicomponent metal alloys. We introduce a new model for predicting the compositions of bulk amorphous metallic glasses (BMGs) and ribbons with its test application to the Gd-Ni-Al system. The proposed model parameters Θx−y(x),Θx−y(y) make it possible to forecast the location of glass-forming compositions by finding the minimum result of multiplying the PHSS parameter by the geometric coefficient Γ1,2,3(x), Γ1,2,3(y). The compositions of Gd-Ni-Al system with the best glass-forming ability (GFA), namely Gd49Ni29Al22 (BMG) and Gd40Ni51Al9 (ribbon), have been successfully determined using these parameters. The correlation between the geometric factors Γ1,2,3(x), Γ1,2,3(y) and effective packing density is shown. Amorphous alloys can be formed only at certain content of the Gd-Ni-Al system components, under which the geometric factors Γ1,2,3(x), Γ1,2,3(y) are close to the radius ratios central atom 1/central atom 2 and central atom 2/central atom 1, respectively. The results of this work open up prospects for developing reliable theoretical methods of new metal glasses prediction.

Chinese Intelligence Prescription System improves prescription accuracy while decreasing labor and drug costs

Background and AimThe traditional method of taking Chinese Medicine involves creating a decoction by cooking medicinal Chinese herbs. However, this method has become less popular, being replaced by the more convenient method of consuming concentrated Chinese herbal extracts, which creates challenges related to the complexity of stacking multiple formulas.MethodsWe developed the Chinese Intelligence Prescription System (CIPS) to simplify the prescription process. In this study, we used data from our institutions pharmacy to calculate the number of reductions, average dispensing time, and resulting cost savings.ResultsThe mean number of prescriptions was reduced from 8.19 ± 3.65 to 7.37 ± 3.34 (p=2.46;times10^{-8}). The reduction in the number of prescriptions directly resulted in decreased dispensing time, reducing it from 1.79 ± 0.25 to 1.63 ± 0.66 min (p=1.88;times10^{-14}). The reduced dispensing time totaled 3.75 h per month per pharmacist, equivalent to an annual labor cost savings of $15,488 NTD per pharmacist. In addition, drug loss was reduced during the prescription process, with a mean savings of $4,517 NTD per year. The combined savings adds up to a not insignificant $20,005 NTD per year per pharmacist. When taking all TCM clinics/hospitals in Taiwan into account, the total annual savings would be $77 million NTD.ConclusionCIPS assists clinicians and pharmacists to formulate precise prescriptions in a clinical setting to simplify the dispensing process while reducing medical resource waste and labor costs.

Preprocessing of Crack Recognition: Automatic Crack-Location Method Based on Deep Learning

With advancements in artificial intelligence and computer vision, machine learning has become widely employed in location and detection of road pavement distresses. Recently, recognition methods based on convolutional neural networks (CNNs) have been implemented to segment pavement cracks at pixel level in order to evaluate the pavement condition. However, this method usually consists of some common processes, including manually predetermining the approximate location of cracks followed by selecting the image containing the cracks and then performing pixel-level segmentation, which is why it is worth automating the preprocessing to replace the manual selection step. Moreover, the issues of a low proportion of positive samples, complex crack topologies, different inset conditions, and complex pavement background make the task of automatic pavement location more challenging. Therefore, this paper proposes a novel method for preprocessing crack recognition, which automatically locates cracks and yields great savings in labor costs. Specifically, a real-world road pavement crack data set obtained from a common digital camera mounted on a vehicle is built to test the proposed crack location method, called Double-Head. It improves the accuracy of crack object localization by using an independent fully connected head (fc-head) and a convolution head (conv-head). The results show that our method improves average precision (AP) 6.5% over Faster R-CNN using only a fc-head, and outperforms many advanced object detection methods.

BOSF-SVM: A thermal image-based fault diagnosis method of circuit boards

In recent years, the lack of thermal images and the difficulty of thermal feature extraction have led to low accuracy and efficiency in the fault diagnosis of circuit boards using thermal images. To address the problem, this paper presents a simple and efficient intelligent fault diagnosis method combined with computer vision, namely the bag-of-SURF-features support vector machine (BOSF-SVM). Firstly, an improved BOF feature extraction based on SURF is proposed. The preliminary fault features of the abnormally hot components are extracted by the speeded-up robust features algorithm (SURF). In order to extract the ultimate fault features, the preliminary fault features are clustered into K clusters by K-means and substituted into the bag-of-features model (BOF) to generate a bag-of-SURF-feature vector (BOSF) for each image. Then, all of the BOSF vectors are fed into SVM to train the fault classification model. Finally, extensive experiments are conducted on two homemade thermal image datasets of circuit board faults. Experimental results show that the proposed method is effective in extracting the thermal fault features of components and reducing misdiagnosis and underdiagnosis. Also, it is economical and fast, facilitating savings in labour costs and computing resources in industrial production.

Factors and Labor Cost Savings Associated with Successful Pediatric Imaging without Anesthesia: a Single-Institution Study

In pediatric imaging, sedation is often necessary to obtain diagnostic quality imaging. We aim to quantify patient and imaging-specific factors associated with successful pediatric scans without anesthesia and to evaluate labor cost savings associated with our institutional Scan Without Anesthesia Program (SWAP). Patients who participated in SWAP between 2019-2022 were identified. Chart review was conducted to obtain sociodemographic and clinical information. Radiology database was used to obtain scan duration, modality/body part of examination, and administration of contrast. Mann-Whitney U and Chi-Square tests were used for univariate analysis of factors associated with success. Multivariate logistic regression was used to evaluate independent contributions to success. Associated hospital labor cost savings were estimated using salary information obtained through publicly available resources. Of 731 patients, 698 had successful and 33 had unsuccessful scans (95% success rate). In univariate analysis, older age, female sex, absence of developmental delay, and administration of contrast were significantly associated with successful scans. Multivariate analyses revealed that older age, female sex, and absence of developmental delay were significant independent factors lending toward success. Imaging-related factors were not associated with outcome in multivariate analysis. Estimated labor cost savings were $139,367.80 per year for the medical center. SWAP had an overall success rate of 95%. Older age, absence of developmental delay, and female sex were independently significantly associated with successful outcome. Cost analysis reveals substantial labor cost savings to the institution compared with imaging under anesthesia.

Robot Chef Adoption: The New Industry Strategy To Combat Labor

Through interviews, the authors investigated how robot chefs can be implemented in order to strengthen the business flow of a restaurant and what value the adoption would bring to the market. Results showed that the ability of the robot chef lacking human error, maintaining food quality, being reliable labor, and generating costs savings make it a desired asset to have in any restaurant. Despite its adoption initially being feared by consumers, once the labor cost savings are transferred over to menu prices and quality maintenance is observed, consumer acceptance of the adoption is predicted to surge. The findings suggest that social media advertising of the robot chef and its services are likely to further entice higher levels of business volume from the growing Generation Z and Generation Alpha consumers in the market. Restaurant companies should understand the values that robot chefs can offer to help strengthen their market and service quality.

Performance Evaluation of Sand Screening Machine: Effect of Sieve Size and Moisture Content

In construction industry, sand is a major raw material besides water, cement, gravel and steel. The quality of sand is vital in development of firm structures in construction. Thus, for construction industry to remain competitive, it is critical to develop efficient sand screening technologies that produce high quality sand while reducing labour cost. Therefore, the main objective of this research paper was to assess sand sieving technologies used in construction industry in Kenya and to design and evaluate performance operation of the sand screening machine that would help improve the efficiency and quality of sand while lowering the overall construction cost. The specific objectives were to design sand screening machine and to investigate the effect of moisture and sieve sizes on screening time. Experiments were conducted on semi-automatic machine driven by motor to determine fine sand produced at different moisture levels and time consumed. The machine designed consist a motor, sieve, shaft, steel hollow tubes, flat steel bars, sheet metal plates, hinges, eccentric sheaves, and angle bars. The study found that screening raw sand of 10 kg using a designed semi-automatic machine with a sieve of 3mm x 3mm and densities 1442 kg/m3, 1602 kg/m3, 1682 kg/m3, 1922 kg/m3 and 2082 kg/m3 were found to produce 8.1kg, 6.8kg, 6.1kg, 4.1kg and 2.8kg respectively with sieving time of 24s, 26s, 27s, 30s and 32s respectively. Designed semi-automatic sand sieving machine displayed a labour reduction cost of 66% leading to savings of Ksh. 39,600 per month. In addition, the output of the machine screening dry sand (1442 kg/m3) 8 hours per day was found to be 9,720 kg. In conclusion, low density sand and optimal sieve size results to high efficiency and significant labour cost savings. The study recommends the use of sand with low density (dry) and adoption of semi-automatic screening machine technologies in construction industry in order to attain Kenya’s affordable housing programme

Architecture design of cucurbit crops for enhanced productivity by a natural allele.

Increasing production efficiency is a top priority in agriculture. Optimal plant architecture is the biological basis of dense planting, high crop yield and labour cost savings, and is thus critical for improving agricultural productivity. In cucurbit crops, most species have elongated internodes, but the path to architecture improvement is still not clear. Here we identified a pumpkin accession with a dominant bushy trait, and found that the associated Bush locus harbours a cucurbit-conserved cis-regulatory element in the 5' untranslated region of a transcription factor gene YABBY1. In cucurbit crops, various B-region deletions enhance the translation of YABBY1, with consequent proportional suppression of stem length in a dose-dependent manner. Depending on different cultivation patterns, the precise deployment of these alleles has significant effects on yield improvement or labour cost saving. Our findings demonstrate that the engineering of the YABBY1 B-region is an efficient strategy to customize plant architecture in cucurbit crops.

Use of Movable Bus Stop Loading Pads: Feasibility and Design Alternatives

The Americans with Disabilities Act (ADA) of 1990 requires bus stops to be accessible for individuals with disabilities. At a minimum, bus stops must have firm, stable, slip-resistant loading pads with connected sidewalks and curb ramps. Consequently, the typical approach of transit agencies has been to install permanent concrete loading pads at bus stops. This study explored alternatives to conventional concrete pads with movable pads that could be installed quickly, resulting in savings in construction and labor costs and minimizing both disruptions to traffic and impacts to abutting businesses. Potential design alternatives in terms of materials and structural support for these pads were evaluated. The review focused on existing and alternative design materials, especially in applications other than for transit purposes. Six materials were evaluated based on their structural performance, long-term durability, adaptability, life cycle cost, aesthetics, and safety and accessibility of transit riders with mobility devices. Of the six materials, plastic lumber and metal were found to have the highest potential to replace conventional designs. Two design alternatives that rely on the concept of bridge construction were introduced, both of which consist of four major components: foundation, slab, beam, and connections. These new design alternatives are anticipated to minimize maintenance of traffic and the need for heavy machinery to excavate, fill, and/or compact the soil.

The principles of improving the technology of grain crop cultivation

The article describes issues of improving technologies for the cultivation of major agricultural crops, technical re-equipment of agricultural production particular processes, proposes new technologies, high-production technical means, methods of completing energy-rich units and ways to increase the competitiveness of crop production. The article proposes the program for the material and technical re-equipment of winter wheat production in the Krasnodar Krai. The problems of harvesting grain crops with combine harvesters are considered and the new threshing scheme by the “unwinnowed grain” method with harvesters, made in Canada, is proposed. The issues of using different varieties of wheat in terms of maturation are considered in order to increase the sowing time and further harvesting periods and, hence, reduce the number of sowing and harvesting equipment. The technology has been developed for the cultivation of winter wheat using new harvesting equipment and new methods of sowing wheat of different ripening periods. The transition to the proposed technology of winter wheat cultivation and harvesting locally in one of the Krasnodar Krai regions will lead to significant annual savings in labor costs. With the strict implementation of the technology, in particular, the optimal sowing and harvesting timing, using the new technology, the fields will be completely free of weeds over several years.