Time Cost Research Articles

Imbalance-Robust Multi-Label Self-Adjusting kNN

In the task of multi-label classification in data streams, instances arriving in real time need to be associated with multiple labels simultaneously. Various methods based on the k Nearest Neighbors algorithm have been proposed to address this task. However, these methods face limitations when dealing with imbalanced data streams, a problem that has received limited attention in existing works. To approach this gap, this paper introduces the Imbalance-Robust Multi-Label Self-Adjusting kNN (IRMLSAkNN), designed to tackle multi-label imbalanced data streams. IRMLSAkNN’s strength relies on maintaining relevant instances with imbalance labels by using a discarding mechanism that considers the imbalance ratio per label. On the other hand, it evaluates subwindows with an imbalance-aware measure to discard older instances that are lacking performance. We conducted statistical experiments on 32 benchmark data streams, evaluating IRMLSAkNN against eight multi-label classification algorithms using common accuracy-aware and imbalance-aware measures. The obtained results demonstrate that IRMLSAkNN consistently outperforms these algorithms in terms of predictive capacity and time cost across various levels of imbalance.

The topical azithromycin meibomian gland dysfunction survey: The effect of topical azithromycin on signs and symptoms of meibomian gland dysfunction.

The aim of this study was to assess the long-term effects of topical azithromycin on signs, symptoms and self-management of meibomian gland dysfunction (MGD). Forty participants were assessed for MGD and its effect on the fluorescein tear break-up time (FTBUT). Participants were treated with topical azithromycin twice daily for 2 weeks and then once daily for a further 2 weeks. One year after treatment, 31 participants completed a survey assessing pre- and post-treatment effect on symptoms, lifestyle and self-treatment methods. Following treatment, there was a significant reduction in MGD grading from a median of grade 2 to grade 0 (z = 4.40, p < 0.0001) and an increase in FTBUT from a median of 3-8 s (z = 4.75, p < 0.0001). One year afterwards, the survey showed a significant improvement in symptoms (sensitivity to light, grittiness, burning, blurred vision, all p < 0.03) and reduction in required self-treatments (lid wipes, tear substitutes, both p < 0.03). There was also a reduced impact on lifestyle (reading, night driving, computer use and watching television, all p < 0.0001) and in all environmental conditions (all p < 0.0001). This study confirms the positive effect of topical azithromycin on MGD and shows it has a long-term impact on symptoms, self-treatment methods and lifestyle. This has implications for both chair time and healthcare costs when managing patients with MGD. Pending further clinical trials in a larger population with different demographics, topical azithromycin should be considered by all eyecare practitioners as a viable pharmacological treatment when managing MGD.

Design and application of small-diameter closed thoracic drainage tube fixation following lung wedge resection: A randomised prospective study.

The use of indwelling closed thoracic drainage tubes in the wedge resection of the lungs is of great significance to postoperative recovery. However, there are potential risks. To explore the design feasibility and application effect of triple-buffer-system-fixed small-diameter (18 F) thoracic closed drainage tubes following lung wedge resection. A total of 136 patients with indwelling thoracic drainage tubes following pulmonary wedge resection were recruited, with 70 patients allocated to the control group and 66 to the experimental group. The drainage tube in the experimental group was fixed with the triple-buffer system, while that in the control group was fixed using the conventional lifting platform method. The incidence of unplanned extubation, the indwelling time of the drainage tube and the time and material costs, as well as information regarding any subcutaneous emphysema and skin tension blisters, were recorded following the operation. The pain and degree of comfort were assessed using a chi-square test and a rank sum t-test to compare the differences between the two groups. There were no statistically significant differences in terms of age, gender and sweating between the two groups. Compared with the control group, the unplanned extubation rate of the experimental group was lower (χ2= 8.513; P= 0.004), the indwelling time of the drainage tube was shorter (t= 2.108; P= 0.037), the cumulative material cost was lower (t= 3.778; P< 0.001), the time cost was also lower (Z= 2.717; P= 0.008), the degree of comfort was higher (Z= 2.752; P= 0.006), and the degree of pain was lower (Z= 4.019; P< 0.001). The incidence of subcutaneous emphysema was significantly lower in the experimental group than in the control group (χ2= 8.513; P= 0.004). The use of the triple-buffer system to fix small-diameter (18 F) thoracic closed drainage tubes can reduce the unplanned extubation rate, indwelling time of the drainage tube and the incidence of adverse reactions.

OUTCOMES OF SINGLE VERSUS COMBINATION FIXATION IN DISTAL FEMUR FRACTURES: A CHRISTCHURCH EXPERIENCE

IntroductionDistal femur fractures have traditionally been stabilized with either lateral locking plate or retrograde intramedullary nail. Dual-plates and nail-plate combination fixation have the theoretical biomechanical advantage, faster union and allows patients to weight bear immediately.The aim of this study is to compare single vs combination fixation, and evaluate outcomes and complications.MethodWe retrospectively reviewed all patients over 60, admitted to Christchurch Hospital, between 1st Jan 2016 and 31st Dec 2022, with an AO 33A/33B/33C distal femur fracture. Patient demographics, fracture characteristics, operation details, and follow up data were recorded.Primary outcomes are union rate, ambulatory status at discharge, and surgical complications. Secondary outcomes include quality of reduction, operation time and rate of blood transfusions.Results114 patients were included. (92 single fixation, 22 combination fixation).Baseline demographic data and fracture characteristics did not differ between the cohorts.There was no difference in the rate of union or time to union between the two cohorts. Combination fixation patients were allowed to weight-bear as tolerated significantly more than single fixation patients (50% vs 18.9%, p=0.003). There was no difference in length of hospital stay, transfusion, complication and mortality rates.Medial translation of the distal articular block was significantly lower in the combination fixation cohort (1.2% vs 3.4%, p=0.021). Operation time was significantly longer in the combination fixation cohort (183mins vs 134mins, p&lt;0.001).DiscussionThe results show no difference in achieving union or time to union, despite better quality of fracture reduction with dual fixation. This differs to previously published literature. The clear benefit of combination fixation is immediate weight-bearing. As expected, operation times were longer with combination fixation, however this did not translate to more complications.ConclusionCombination fixation allows earlier weight bearing, at the cost of longer operation times.

Robotic versus laparoscopic anterior resection for the treatment of stage II and III sigmoid colon cancer: a propensity score-matched analysis.

Robot-assisted laparoscopic anterior resection is a novel technique. However, evidence in the literature regarding the advantages of robot-assisted laparoscopic surgery (RLS) is insufficient. The aim of this study was to compare the outcomes of RLS versus conventional laparoscopic surgery (CLS) for the treatment of sigmoid colon cancer. We performed a retrospective study at the Northern Jiangsu People's Hospital. Patients diagnosed with sigmoid colon cancer and underwent anterior resection between January 2019 to September 2023 were included in the study. We compared the basic characteristics of the patients and the short-term and long-term outcomes of patients in the two groups. A total of 452 patients were included. Based on propensity score matching, 212 patients (RLS, n = 106; CLS, n = 106) were included. The baseline data in RLS group was comparable to that in CLS group. Compared with CLS group, RLS group exhibited less estimated blood loss (P = 0.015), more harvested lymph nodes (P = 0.005), longer operation time (P < 0.001) and higher total hospitalization costs (P < 0.001). Meanwhile, there were no significant differences in other perioperative or pathologic outcomes between the two groups. For 3-year prognosis, overall survival rates were 92.5% in the RLS group and 90.6% in the CLS group (HR 0.700, 95% CI 0.276-1.774, P = 0.452); disease-free survival rates were 91.5% in the RLS group and 87.7% in the CLS group (HR 0.613, 95% CI 0.262-1.435, P = 0.259). Compared with CLS, RLS for sigmoid colon cancer was found to be associated with a higher number of lymph nodes harvested, similar perioperative outcomes and long-term survival outcomes. High total hospitalization costs of RLS did not translate into better long-term oncology outcomes.

Customs services and ways to improve their quality in the context of digitalisation

This article is devoted to problems of the process of rendering services in the field of customs during digitalisation of the economy. The observed mechanism of rendering state customs services, as well as improving their quality, naturally affect the entire service sector and the development of the country’s economy as a whole. The main purposes of the article are to analyse the mechanism of rendering services in the field of customs and to search for effective methods of assessing their quality. The relevance of the article is determined by the need to improve the operations performed to be able to manage the quality of provided customs services. The main objective of this article is to propose possible ways to reduce time costs without losing the quality of customs control in the process of providing the services. The article used both theoretical (analysis of the current legislation) and empirical research methods (giving practical examples of improving the efficiency of customs operations and the quality of customs services). The results of the study are the following: development of sequential operations performed by customs authorities in the process of rendering services in the field of customs; proposal of possible criteria for assessing their quality; formulation of options for managing this quality.

A new framework for project time–cost–environmental trade-off problem with hybrid Fermatean fuzzy–grey information

A new framework for project time–cost–environmental trade-off problem with hybrid Fermatean fuzzy–grey information

Random Regret Minimization Approach to Commuting Mode Choice in São Paulo, Brazil

The random regret minimization (RRM) approach has been widely used in transport literature, but its application in the Global South is still marginal. In this paper we discuss individual commuting mode choice in the city of São Paulo (Brazil) from the perspective of the RRM modeling approach and its variants found in the literature. We estimated several multinomial logit models (random utility maximization [RUM], classical RRM, [Formula: see text]RRM, and hybrid formulations of RUM-RRM models) and explored regret scale and decision rule heterogeneities using latent class models with specific [Formula: see text] parameters. The results showed that the RRM approach outperformed its RUM counterpart in relation to model fit and suggested that it better captured the mode choice behavior of individuals in the analyzed context. We also found that accounting for heterogeneity in scale and decision rules improved the results of the models, and the specific [Formula: see text] parameters indicated that individuals displayed different regret behavior for travel time and travel cost attributes.

An Assessment of the Role of the Timex Sampling Strategy on the Precision of Shoreline Detection Analysis

Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and considerable hardware costs. As such, there is a need for an autonomous low-cost system (~EUR 500), such as Timex cameras, that can be rapidly deployed in the field, while still producing the outcomes required for coastal monitoring. This research presents an assessment of the effect of the sampling strategy (time-lapse intervals) on the precision of shoreline detection for two low-cost cameras located in a remote coastal area in western Ireland, overlooking a dissipative beach–dune system. The analysis shows that RMSD in the detected shoreline is similar to other studies for sampling intervals ranging between 1 s and 30 s (i.e., RMSDmean for Camera 1 = 1.4 m and Camera 2 = 0.9 m), and an increase in the sampling interval from 1 s to 30 s had no significant adverse effect on the precision of shoreline detection. The research shows that depending on the intended use of the detected shorelines, the current standard of 1 s image sampling interval when using Timex cameras can be increased up to 30 s without any significant loss of accuracy. This positively impacts battery life and memory storage, making the systems more autonomous; for example, the battery life increased from ~10 days to ~100 days when the sampling interval was increased from 1 to 5 s.

Comparing Deep Learning and MCWST Approaches for Individual Tree Crown Segmentation

Abstract. Accurate segmentation of individual tree crowns (ITC) segmentation is essential for investigating tree-level based growth trends and assessing tree vitality. ITC segmentation using remote sensing data faces challenges due to crown heterogeneity, overlapping crowns and data quality. Currently, both classical and deep learning methods have been employed for crown detection and segmentation. However, the effectiveness of deep learning based approaches is limited by the need for high-quality annotated datasets. Benefiting from the BaKIM project, a high-quality annotated dataset can be provided and tested with a Mask Region-based Convolutional Neural Network (Mask R-CNN). In addition, we have used the deep learning based approach to detect the tree locations thus refining the previous Marker controlled Watershed Transformation (MCWST) segmentation approach. The experimental results show that the Mask R-CNN model exhibits better model performance and less time cost compared to the MCWST algorithm for ITC segmentation. In summary, the proposed framework can achieve robust and fast ITC segmentation, which has the potential to support various forest applications such as tree vitality estimation.

Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Automatic Identification System (AIS) offers a wealth of vessel navigation data, which underpins research in maritime data mining, situational awareness, and knowledge discovery within the realm of intelligent transportation systems. The flourishing marine industry has prompted AIS satellites and base stations to generate massive amounts of vessel trajectory data, escalating both data storage and calculation costs. The conventional Douglas-Peucker (DP) algorithm used for trajectory compression sets a uniform threshold, which hampers effective compression. Additionally, compressing and accelerating the computation of large datasets poses a significant challenge in real-world applications. To address these limitations, this paper aims to develop a new Graphics Processing Unit (GPU) parallel computing and compression framework that enables the acceleration of the optimal threshold calculation for each trajectory automatically in maritime big data mining. It achieves this by incorporating a new Adaptive DP with Speed and Course (ADPSC) algorithm, which utilizes the dynamic navigation characteristics of different vessels. It can effectively solve the associated computational time cost concern when using the ADPSC algorithm to compress vast trajectory datasets in the real world. Additionally, this paper proposes a novel evaluation metric for assessing compression efficacy based on the Dynamic Time Warping (DTW) method. Comprehensive experiments encompass vessel trajectory datasets from three representative research areas: Tianjin Port, Chengshan Jiao Promontory, and Caofeidian Port. The experimental results demonstrate that 1) the newly developed ADPSC method outperforms in terms of compression, and 2) the designed GPU parallel computing framework can significantly shorten the compression time for extensive datasets. The GPU-accelerated compression methodology not only minimizes storage and transmission costs for data from both manned and unmanned vessels but also enhances data processing speed, supporting real-time decision-making. From a theoretical perspective, it provides the key to the puzzle of realizing the real-time anti-collision of manned and unmanned ships, particularly in complex waters. It hence makes significant contributions to maritime safety in the autonomous shipping era.

Fast Aerodynamic Prediction of Airfoil with Trailing Edge Flap Based on Multi-Task Deep Learning

Conventional methods for solving Navier–Stokes (NS) equations to analyze flow fields and aerodynamic forces of airfoils with trailing edge flaps (TEFs) are known for their significant time cost. This study presents a Multi-Task Swin Transformer (MT-Swin-T) deep learning framework tailored for swift prediction of velocity fields and aerodynamic coefficients of TEF-equipped airfoils. The proposed model combines a Swin Transformer (Swin-T) for flow field prediction with a multi-layer perceptron (MLP) dedicated to lift coefficient prediction. Both networks undergo gradient updates through the shared encoder component of the Swin Transformer. Such a trained network model for computational fluid dynamics simulations is both effective and robust, significantly improving the efficiency of complex aerodynamic shape design optimization and flow control. The study further investigates the impact of integrating multi-task learning loss functions, skip connections, and the network’s structural design on prediction accuracy. Additionally, the effectiveness of deep learning in improving the aerodynamic simulation efficiency of airfoils with TEF is examined. Results demonstrate that the multi-task deep learning approach provides accurate predictions for TEF airfoil flow fields and lift coefficients. The strategic combination of these tasks during network training, along with the optimal selection of loss functions, significantly enhances prediction accuracy compared with the single-task network. In a specific case study, the MT-Swin-T model demonstrated a prediction time that was 1/7214 of the time necessitated by CFD simulation.

Temporal action segmentation for video encryption

Videos contain temporal information, enabling them to capture the dynamic changes of actions and provide richer visual effects. Traditional video encryption methods involve decomposing videos into frames and encrypting them frame by frame, which results in significant resource consumption. This paper proposes a video encryption method based on temporal action segmentation. This methodology involves the identification and extraction of pivotal frames from a video dataset, followed by the encryption of these significant key frames. This approach serves to enhance the efficacy of the video encryption algorithm. The method consists of three modules. The first module uses temporal action segmentation to classify video frames and extract important frames for the second module’s input. The second module encrypts the extracted key frames using a chaos-based encryption algorithm, thereby reducing the time cost of video encryption. The third module outputs the encrypted video. During the encryption process, a large amount of key stream is required. To address this, the paper introduces a new pseudo-random sequence generation method called two-dimensional Gramacy&Lee map (2D-GLM). Comprehensive comparative analysis clearly demonstrates that compared to other systems, 2D-GLM exhibits superior performance and can generate a large number of high-performance pseudo-random sequences. The proposed algorithm is tested on GTEA, and the simulation results demonstrate that it can accomplish video encryption tasks with high security.

Design and Fabrication of Cost-Effective Composting for Easy Decomposing of Home Wastes

The primary objective is to develop a Household waste Decomposer that not only composting thee kitchen waste but also ensures quick decomposition while minimizing odors. Our design integrates innovative features, such as a compact and user-friendly composting unit, utilizing a controlled aeration system to accelerate the composting process. This aeration system promotes optimal conditions for microbial activity, enhancing the breakdown of organic matter Another one method added to using decomposer sand. Decomposition sand is a biological process that includes the physical breakdown and biochemical transformation of complex organic molecules of dead material into simpler organic and inorganic molecules. There are two effective system used in Household waste Decomposer. This composting process create a bad smell , so that we are using high suction power exhaust fan. In this suction fans is pull a Odorant particles throw out to the atmospheric air Food waste and decomposer sand ismixed well before pouring in top of the hopper. Food waste and decomposer mixer breakdown the particles like (leaf and tomato and other kitchen veg, waste food) using grinding method Traditional composting methods are slow decomposing and high level of odor form. Now odor free decomposer and quick decomposer at a same time cost effective home decomposing.Household waste Decomposer suitable for trace garden

Scheduling of Container Transportation Vehicles in Surface Coal Mines Based on the GA–GWO Hybrid Algorithm

The coal loading operation of the coal preparation plant of an open pit coal mine causes chaos in coal mine vehicle scheduling due to the unreasonable arrival times of outgoing and container transportation vehicles. To further reduce the length of time that vehicle transportation equipment waits for each other and to reduce the total cost of container transportation, the optimisation model of container transportation vehicle scheduling in an open pit coal mine is constructed to minimise the minimum sum of the shortest time of container reversal and the lowest cost of container transportation. To accurately measure the total cost of container backward transportation, waiting time and unit waiting time cost parameters are introduced, and the total cost of container transportation is measured using the transportation cost and the waiting time cost transformation method. An improved grey wolf algorithm is proposed to speed up the convergence of the algorithm and improve the quality of the solution. When employing the genetic algorithm (GA) and grey wolf optimisation algorithm (GWO) for optimising the scheduling of container transport vehicles in coal mines, it is noted that while the GA can achieve the global optimum, its convergence speed is relatively slow. Conversely, the GWO converges more quickly, but it tends to be trapped in local optima. To accelerate the convergence speed of the algorithm and improve the solution quality, a hybrid GA−GWO algorithm is proposed, which introduces three genetic operations of selection, crossover, and mutation of GA into the GWO algorithm to prevent the algorithm from falling into the local optimum due to the fall; at the same time, it introduces hunting and attacking operations into the elite retention strategy of GA, which improves the stability of the algorithm’s global convergence. Analysis indicates that, compared to SA, GWO, and GA, the hybrid algorithm enhances optimisation speed by 43.1%, 46.2%, and 43.7%, increases optimisation accuracy by 4.12%, 6.1%, and 3.2%, respectively, and reduces the total container reversal time by 35.46, 22, and 31 h. The total cost of container transportation is reduced by 2437 RMB, 3512 RMB, and 1334 RMB, respectively.

Low-temperature preparation and characteristics of top-gate thin-film transistors with La-ZTO active layers and polymethylmethacrylate dielectric layers

A top-gate coplanar-structure thin-film transistor (TFT) combining the advantages of both a co-sputtered amorphous La-doped ZnSnO (a-La-ZTO) active layer and solution-based polymethylmethacrylate (PMMA) gate dielectric layer has been prepared under low temperature (100 °C) with low cost for the first time. The results indicate that the PMMA thin film demonstrates anti-reflection properties when it combines with a-La-ZTO layer to form a double-layer film, displaying high transparency to visible light of ∼90.3%. Moreover, it was found that the La target power during the deposition of a-La-ZTO film plays an important role in suppressing the formation of oxygen vacancies and adjusting the carrier concentration of a-La-ZTO active layer, thus impacting a-La-ZTO TFT performance. Overall, the optimum a-La-ZTO TFT with a La target power of 13.9 W, working in an n-channel enhancement mode, possesses a large saturated mobility (>10 cm2 (Vs)−1) and an on/off drain current ratio over 105.

Enhanced biodegradation of phenol under Cr(VI) stress by microbial collaboration and potential application of machine learning for phenol biodegradation

ABSTRACT Cr(VI) and phenol commonly coexist in wastewater, posing a great threat to the environment and human health. However, it is still a challenge for microorganisms to degrade phenol under high Cr(VI) stress. In this study, the phenol-degrading strain Bacillus cereus ZWB3 was co-cultured with the Cr(VI)-reducing strain Bacillus licheniformis MZ-1 to enhance phenol biodegradation under Cr(Ⅵ) stress. Compared with phenol-degrading strain ZWB3, which has weak tolerance to Cr(Ⅵ), and Cr(Ⅵ)-reducing strain MZ-1, which has no phenol-degrading ability, the co-culture of two strains could significantly increase the degraded rate and capacity of phenol. In addition, the co-cultured strains exhibited phenol degradation ability over a wide pH range (7–10). The reduced content of intracellular proteins and polysaccharides produced by the co-cultured strains contributed to the enhancement of phenol degradation and Cr(Ⅵ) tolerance. The determination coefficients R2, RMSE, and MAPE showed that the BP-ANN model could predict the degradation of phenol under various conditions, which saved time and economic cost. The metabolic pathway of microbial degradation of phenol was deduced by metabolic analysis. This study provides a valuable strategy for wastewater treatment containing Cr(Ⅵ) and phenol.

Short message encryption technology of Beidou communication based on SM9

AbstractTo reduce the security authentication time cost, forwarding delay, and enhance message security of Beidou communication short messages, this paper proposes a Beidou communication short message encryption technology based on SM9 (Mobile Code Secure Communication). This technology uses split hierarchical clustering algorithm to cluster the short message data of Beidou Communication, in order to unify the processing of similar short message data and improve the encryption efficiency of subsequent short messages. Based on the data clustering results, this paper constructs a short message forwarding verification model using the SM9 identification password algorithm, and provides the message content of the communication application protocol and the communication receiving information protocol to achieve low‐cost and efficient forwarding verification. In addition, this article improves the initial value selection of Logistic chaotic mapping by coupling the tent map with coupled mapping lattice (CML) in the spatiotemporal chaos model to generate a chaotic initial value sequence, thereby expanding the key space, enhancing the ability to resist exhaustive attacks, enhancing the randomness of the generated key parameters, and optimizing the encryption effect of short messages. The experimental results show that the short message security authentication time of the technology proposed in this article is basically controlled within 25 ms, and the minimum forwarding delay is only 23.9 ms, which can effectively resist attacks and improve the security of Beidou communication.

Development of time–cost trade-off optimization model for construction projects with MOPSO technique

Development of time–cost trade-off optimization model for construction projects with MOPSO technique

TLS fingerprint for encrypted malicious traffic detection with attributed graph kernel

Recently, more and more applications have adopted security protocols like Transport Layer Security (TLS) for data encryption. However, these privacy-enhancing approaches have also been abused by the attackers to deliver malicious payloads. Many existing encrypted network classification methods suffer from the imbalanced volume of normal and malicious traffic, which leads to bad model robustness. In this paper, we propose a novel TLS fingerprinting approach to capture the characteristics of encrypted network traffic. The fingerprints are attributed graphs obtained from TLS sessions, which can simultaneously take into consideration the sequential and statistical features of these sessions. As the communication patterns of different applications differ considerably, the graphs representing TLS connections could be used to characterize the network with the help of the graph kernel method, which results in a model with high accuracy in malicious TLS session detection and application discrimination. Moreover, we adopt Locality-Sensitive Hashing (LSH) and filtering techniques to reduce the time cost of our model. Model evaluation on real-world datasets shows that our model is more robust than existing methods presented in this work when the malicious traffic takes up an extremely small portion of the whole traffic.