Comprehensive Evaluation Approach Research Articles

A method to enhance Apache Spark performance based on data segmentation and configuration parameters settings

When using modern big data processing tools, there is a problem of increasing the productivity of using modern frameworks in the context of effective setting of various configuration parameters. The object of the research is computational processes of processing big data with the use of technologies of high-performance frameworks. The subject is methods and approaches to the effective setting of configuration parameters of frameworks in the conditions of limitations of virtualization environments and local resources. The purpose of the study is to improve the performance of Apache Spark and Apache Hadoop deployment modes based on a combined approach that includes preprocess segmentation of input data and setting of basic and additional configuration parameters that take into account the limitations of the virtual environment and local resources. Achieving the set goal involves the following tasks: create a synthesized set of WordCount test data for using input data segmentation methods. Determine the composition of general and specific Apache Spark and Apache Hadoop configuration parameters that most affect the performance of frameworks in Spark Standalone and Hadoop Yarn (FIFO) deployment modes. Justify changes in the values of the configuration parameters (accepted by default) by setting the level of parallelism, the number of partitions of the input file according to the number of processor cores, the number of tasks assigned to each core and the system executor. Conduct experimental research to substantiate theoretical results and prove their use in practice. Methods. The research used the following methods: statistical analysis; a method of generating test data based on defined segmentation characteristics with arbitrary volumes of data; a systematic approach for comprehensive evaluation and analysis of performance of frameworks based on selected configuration parameters. The results. On the basis of the developed system of parameters for evaluating the performance of the studied frameworks, experiments were carried out, which include: the application of the method of segmentation of input data based on the division of the input file into paragraphs (lines) for different values of the ranges of the number of words and the number of letters in each word; setting the main parameters and specific ones, in particular, partitioning and parallelism, taking into account the characteristics of the virtual environment and the local resource. According to the obtained results, a detailed analysis of the use of the proposed methods to improve the performance of the studied frameworks with recommendations for choosing the optimal values of data segmentation parameters and configuration parameters was carried out. You are snowmen. The obtained results of the experiments allow us to conclude that the use of the proposed methods of setting the configuration parameters of Spark and Hadoop will increase the processing productivity: for small files (0.5–1 GB) on average up to 25–30%, for large ones (1.5–2.5 GB ) – up to 10–20% on average. At the same time, the average value of the execution time of one task decreased by 10-15% for files of different sizes and with different number of words in a line.

Operative Treatment of Patellofemoral Instability: Osteotomies for Torsional and Coronal Malalignment

Patellofemoral instability (PFI) is a prevalent orthopedic issue that leads to significant morbidity and functional limitation. It has a notable incidence, specifically higher amongst adolescent females, and a recurrence rate ranging from 17% to 33%. Recurrent PFI significantly increases the risk of degenerative changes and early-onset osteoarthritis. Patients with multiple risk factors increase recurrence rates significantly, and thus identifying and managing anatomical risk factors is an effective strategy for patients. These include: trochlear dysplasia, patella alta, increased tibial tubercle-to-trochlear groove (TT-TG) distance, increased femoral anteversion, external tibial torsion and valgus limb alignment.This study outlines a comprehensive evaluation and surgical approach focusing on PFI associated with torsional or coronal malalignments. The evaluation includes a detailed patient history, clinical examination, and diagnostic imaging. Surgical interventions are selected based on an algorithmic approach tailored to the specific pathoanatomy of the instability, focusing on both bony and soft-tissue procedures.Surgical techniques for addressing PFI in the presence of malalignment include proximal and distal bony procedures. Specific techniques detailed in this study include femoral torsional osteotomy over an intramedullary nail, distal femur opening and closing wedge osteotomies, and torsional tibial osteotomies fixed with an intramedullary nail or plate.

Determination of prickle effect detection thresholds in Llama fiber knitted fabrics

The study delves into determining the detection thresholds for the prickle effect in Llama fiber knitted fabrics, crucial for fabric acceptability assessment, by consumers of garments made from natural fibers. Employing standard evaluation methods involving moistened skin and perception scoring, coupled with the identification of objectionable (coarse) fiber content as a pivotal variable, the research using 41-invited panelist elucidates the intricate interplay between fiber characteristics (diameter) and prickle perception. Despite efforts to mitigate hairiness through finishing processes, the study unveils the nuanced impact of fiber protrusion on the prickle effect, necessitating a comprehensive evaluation approach. Through pairwise comparisons and perception scales, the study unveils strong associations between prickle perception and expression degrees, reaffirming panelists' sensitivity in detecting subtle variations. Statistical analyses underscore significant differences in coarse fiber content and diameter between paired samples, further corroborating panelists' discernment. It can be clearly concluded, from this analysis, the prickle effect detection thresholds in llama fiber fabrics range from 2.36 to 2.42% in coarse fiber differences and from 0.11 to 1.63 microns in fiber diameter difference, in the 95% of the tested cases or more probability. In conclusion, the study delineates critical thresholds (2.36%) for prickle detection in Llama fiber fabrics, offering invaluable insights for fabric evaluation and refinement processes, and emphasizing the heightened sensitivity of finished fabric samples in prickle perception.

Assessment of Masses in the Right Upper Quadrant using Ultrasound Imaging: A Comprehensive Diagnostic Approach for Clinical Evaluation in Bangladesh

Ultrasound serves as a pivotal tool in identifying and assessing masses in the right upper quadrant (RUQ) of the abdomen, crucial for determining precise organ involvement, composition, characteristics, and extension into neighboring structures. This cross-sectional prospective study conducted at various medical facilities in Dhaka enrolled 130 patients, utilizing real-time ultrasound with a 3.5MHz transducer. Among the 100 patients with abnormal sonographic findings, 40% exhibited RUQ masses, predominantly affecting males (75%). Liver masses were most common (75%), including abscesses, hepatocellular carcinomas, secondary lesions, hemangiomas, and simple cysts. Gall bladder masses (10%) mostly consisted of advanced stage carcinomas and polyp-like masses. Right renal masses (15%) comprised simple cysts, severe hydrone-phrosis, renal cell carcinoma, and angiomyolipoma. Ultrasound emerges as the preferred initial imaging modality for RUQ mass detection, offering high diagnostic accuracy, non-invasiveness, affordability, and widespread availability. While supplementary investigations like serological tests, CT scans, and histopathology may be necessary for definitive diagnoses, ultrasound aids in formulating initial patient management guidelines. Despite its limitations, ultrasound remains popular and highly preferred for RUQ imaging, emphasizing its significance in clinical practice.

Evaluation of spatial and temporal changes in illicit drug use in the Taipei metropolitan area via wastewater-based epidemiology

Taiwan, identified as pivotal in the Asian drug trafficking chain, has been experiencing a surge in illicit drug-related issues. Wastewater-based epidemiology (WBE) has emerged as a promising approach for comprehensive evaluation of actual illicit drug usage. This study presents the first WBE investigation of illicit drug consumption in Taiwan based on the analysis of wastewater from four wastewater treatment plants (WWTPs) in the Taipei metropolitan area. Additionally, it demonstrates a high correlation between the amounts of illicit drugs seized and influent concentrations over an extended period of time. The reliability of solid-phase extraction and analysis via high-performance liquid chromatography-tandem mass spectrometry (HPLC–MS/MS) was validated for 16 illicit drugs (methamphetamine, ketamine, cocaine, codeine, methadone, morphine, meperidine, fentanyl, sufentanil, para-methoxyamphetamine (PMA), para-methoxymethamphetamine (PMMA), 3,4-methylenedioxymethamphetamine (MDMA), cathinone, methcathinone, mephedrone (MEPH), and 4-methylethcathinone (4-MEC)). Methamphetamine, ketamine, and 4-MEC were consistently detected in all wastewater samples, underscoring their prevalence in the Taipei metropolitan area. Biochemical oxygen demand (BOD) and ammonia nitrogen (ammonia N) were employed to reduce uncertainty in estimations of population size during back-calculation of illicit drug consumption. The results indicate that methamphetamine was the most consumed drug (175–740 mg day−1 1000 people−1), followed by ketamine (22-280 mg day−1 1000 people−1). In addition, urban-related WWTPs exhibited higher consumption of methamphetamine and ketamine than did the suburban-related WWTP, indicating distinct illicit drug usage patterns between suburban and urban regions. Moreover, an examination of temporal trends in wastewater from the Dihua WWTP revealed a persistent predominance of ketamine and methamphetamine, consistent with statistical data pertaining to seizure quantities and urine test results. The study provides encouraging insight into spatial and temporal variations in illicit drug usage in the Taipei metropolitan area, emphasizing the complementary role of WBE in understanding trends in illicit drug abuse.

A Comprehensive Evaluation and Mitigation Approaches for Traffic-Related Noise in the Sungai Long Region, Malaysia

A Comprehensive Evaluation and Mitigation Approaches for Traffic-Related Noise in the Sungai Long Region, Malaysia

The Implementation of Authentic Assessment in Speaking Class based on MBKM Curriculum at the UMKABA University

The research investigates the implementation of authentic assessment in speaking learning within the independent curriculum framework at UMKABA. It highlights the appropriateness and coordination of applying authentic assessment, emphasizing its alignment with the cognitive, affective, and psychomotor domains of learning. The study underscores authentic assessment as a paradigm shift in learning evaluation, focusing on holistic skill and character development in line with the MBKM curriculum's goals. Key components of effective authentic assessment preparation, such as rubric creation and alignment with learning outcomes, are discussed. Challenges faced by lecturers in preparing clear and objective assessment criteria are acknowledged, yet the benefits of authentic assessment in fostering 21st-century skills are emphasized. The study concludes that authentic assessment under the Merdeka Curriculum offers a more comprehensive evaluation approach, encompassing not only knowledge but also skills and attitudes, thus providing students with diverse opportunities to showcase their abilities. Keywords: authentic assessment, speaking, MBKM Curriculum

Comparison and assessment of nutritional composition in shoots of six bamboo species in Southeast China

The introduction of bamboo species is one of the strategies used to enrich edible fresh bamboo shoots resources across diverse regions. However, there is a lack of investigation on the adaptability of bamboo species and the nutritional profiles of their shoots post-introduction. In this study, the nutritional components of bamboo shoots from six bamboo species that have been successfully introduced were compared and evaluated. These six bamboo species possess shoots rich in soluble sugar, soluble protein, and crude fibre. Furthermore, the shoots exhibit significant concentrations of potassium and iron, along with an abundance of amino acids. Notably, the amino acid content is highest in the apical region of the bamboo shoot, followed by the middle section, with the base having the lowest levels. When evaluated through several assessment systems, the shoots exhibited varying scores and rankings. A comprehensive evaluation approach was then utilized to assign final scores and rankings to all six species. Recommendations are provided for the selection of high-quality nutrient-dense bamboo shoots grown in the same field following successful introduction.

An integrated model for road freight transport firm selection in third-party logistics using T-spherical Fuzzy sets

The efficient selection of road freight transport (RFT) firms plays a critical role in constructing well-operating logistics systems for large-scale third-party logistics (3PL) providers. However, the decision-making process for such selection is often complex and uncertain due to various influential criteria and dynamic industry nature. To address this challenge, a novel decision-making model that integrates Delphi, CRiteria Importance Through Intercriteria Correlation (CRITIC) and Combined compromise ranking solution (CoCoSo) methods based on T-Spherical Fuzzy sets has been proposed in this paper. The model integrates expert opinions with an extensive literature review to identify the influential criteria and their corresponding weights. Subsequently, it employs a comprehensive evaluation approach to rank the RFT firms based on their performance. The model accommodates uncertainties and subjectivity by utilizing T-Spherical Fuzzy Numbers, offering robustness and transparency in decision-making. A case study involving 15 evaluation criteria and 12 RFT firms were selected to demonstrate the applicability and aptness of the proposed model. Flexibility and Integrability to different transport modes emerged as the two most essential criteria, whereas RFT firm A2 emerged as the best alternative with the highest performance score of 3.0861, followed by RFT firm A7 with a score value of 3.0499.

Advancements in automated testing tools for Android set-top boxes: a comprehensive evaluation and integration approach

Advancements in automated testing tools for Android set-top boxes: a comprehensive evaluation and integration approach

Multi-indicator analytical study of 18 trace elements and fat in 5 beans based on entropy analysis (EA) and gray pattern recognition (GPR)

ABSTRACT Five varieties of beans from Laibin, Guangxi, China, including mung beans, soybeans, black beans, red beans, and adzuki beans, were chosen as study subjects for multi-index determination and full assessment. Data on the fat, ash, crude fiber, trace element, thermogravimetric analysis and combustion heat of five different types of beans were gathered. The results showed that the order of combustion heat of the 5 kinds of beans was black beans>soybeans>mung beans>adzuki beans>red beans, the order of combustion stability was soybeans>mung beans>black beans>red beans>adzuki beans, the order of fat content was soybeans>red beans>adzuki beans>black beans>mung beans, the order of ash content was black beans>soybeans>adzuki beans>mung beans>red beans, the order of crude fiber content was red beans>soybeans>adzuki beans, and the order of multi-index stoichiometric analysis was soybeans>red beans>black beans>mung beans>adzuki beans. The quality of the food was assessed and classified using the stoichiometric approach, while the food nutrition was assessed from the perspectives of fat, ash, crude fiber, trace elements, thermogravimetric analysis and combustion heat. This work provides a solid scientific foundation for the assessment and investigation of the thermo gravimetric analysis of food combustion stability. This study’s multi-index comprehensive evaluation approach offers a novel concept for food nutrition.

Implementation of language models within an infrastructure designed for Natural Language Processing

This paper explores cost-effective alternatives for resource-constrained environments in the context of language models by investigating methods such as quantization and CPUbased model implementations. The study addresses the computational efficiency of language models during inference and the development of infrastructure for text document processing. The paper discusses related technologies, the CLARIN-PL infrastructure architecture, and implementations of small and large language models. The emphasis is on model formats, data precision, and runtime environments (GPU and CPU). It identifies optimal solutions through extensive experimentation. In addition, the paper advocates for a more comprehensive performance evaluation approach. Instead of reporting only average token throughput, it suggests considering the curve’s shape, which can vary from constant to monotonically increasing or decreasing functions. Evaluating token throughput at various curve points, especially for different output token counts, provides a more informative perspective.

Fire safety assessment for alternative cruise ship design based on BWM and DEMATEL by linguistic Z‐number

AbstractThis paper proposes a risk assessment method based on the best‐worst method (BWM) and decision‐making trial and evaluation laboratory (DEMATEL) to evaluate the fire safety level of alternative design schemes for cruise ships relative to the standard‐based options. Firstly, the analytic hierarchy model of fire safety assessment is constructed by analyzing the passive fire protection system, active fire protection system, and evacuation and escape capability of cruise ship large cabins. Then, the linguistic scale functions and Z‐numbers are used to deal with the fuzzy evaluation of fire safety factors by experts, and the maximizing consensus technique is adopted to determine the weight of each expert to enhance group consistency. Considering the influence degree of each factor on fire safety and the correlation between factors, the BWM is combined with DEMATEL to establish the risk source weight calculation model. The fire safety level of alternative cruise ship designs is further determined by the fuzzy comprehensive evaluation approach. Finally, to validate the effectiveness of the proposed method, a fire safety assessment is conducted on the alternative design scheme of a luxury cruise passenger restaurant. The results confirm that the proposed method can effectively evaluate the fire safety of alternative design compared to the standard‐based scheme.

Quantifying the bitter masking effect of drug-cyclodextrin complexation: NMR-ROESY mixing time approach

Taste, especially unpleasant taste, can be key for patient compliance. In the formulation development process, drug-cyclodextrin (CD) inclusion complexes are often used to improve the solubility of a drug and/or mask its bitterness. This study aimed to evaluate the bitter masking effect of CDs on different drugs using NMR-ROESY analysis, human sensory tests, and e-tongue measurements. The strength of inclusion complex formation between drugs and CDs was investigated by NMR-ROSEY, and these results were compared to human sensory test results. In the sensory test, participants identified which drug-CD inclusion complexes were not bitter. NMR-ROSEY results aligned with the sensory tests; short magnetization transfer times corresponded to masked bitterness. The electrical tongue was not able to detect the taste of any of the drug-CD inclusion complexes. Additionally, we used NMR-ROSEY to determine which drug-CD inclusion complex formed in a system with multiple drug substances present. This research offers valuable insights into the bitter masking effect of CDs on different drugs and presents a comprehensive evaluation approach using various methods. This knowledge has significant implications for the pharmaceutical industry, clinical practice, and patient care, contributing to improved patient compliance and satisfaction with bitter medications.

Comprehensive evaluation of dam seepage safety combining deep learning with Dempster-Shafer evidence theory

Seepage state is one of the most important factors affecting the safety and durability of dams, which calls for accurate observation and evaluation. Traditional dam seepage evaluation mainly focusses on single monitoring points, and ignores the uncertainty and subjectivity with multi-sensor fusion. This paper presents an evaluation method of dam seepage based on Dempster-Shafer (D-S) evidence theory and deep neural network (DNN). In view of the nonlinearity of the monitoring data and the difference of seepage influencing factors, attention mechanism (AM) and long short-term memory (LSTM) model are combined to evaluate dam seepage safety of single monitoring points, which provides the basis for the comprehensive evaluation. The case study demonstrates that the average RMSE, MAE and MAPE values of AM-LSTM are of minimal losses and higher fitting accuracy. The forecast results of the proposed comprehensive evaluation approach are consistent with the actual dam seepage state, demonstrating its reasonability and reliability.

Connecting the Dots: A Comprehensive Modeling and Evaluation Approach to Assess the Performance and Robustness of Charging Networks for Battery Electric Trucks and Its Application to Germany

The successful introduction of battery electric trucks heavily depends on public charging infrastructure. But even as the first trucks capable of long-haul transportation are being built, no coherent fast-charging networks are yet available. This paper presents a methodology for assessing fast charging networks for electric trucks in Germany from the literature. It aims to establish a quantitative understanding of the networks’ performance and robustness to deviations from idealized system parameters and identify crucial charging sites from a transportation planning perspective. Additionally, the study explores the quantification of adaptation effects displayed by agents in response to charging site outages. To achieve these objectives, a comprehensive methodology incorporating infrastructure, vehicle and operational strategy modeling, simulation, and subsequent evaluation is presented. Factors such as charging station locations, C-rates, mandatory rest periods, and vehicle parameters are taken into account, along with the distribution of traffic according to publicly available data. The study aims to offer a comprehensive understanding of charging networks’ performance and resilience. This will be applied in a case study on two proposed networks and newly created derivatives. The proposed network offers over 99% coverage for long-haul transport but leads to a time loss of approximately 7% under reference conditions. This study advances the understanding of the performance and resilience of proposed charging networks, providing a solid foundation for the design and implementation of robust and efficient charging infrastructure for electric trucks.

Notice of Retraction: A hybrid fuzzy multiple criteria decision-making approach for comprehensive performance research and evaluation of RE-CCHP system

Retracted.

Soil Invertebrates As Sentinels Of Soil Health: A Zoological Approach To Soil Quality Assessment.

Soil invertebrates, a diverse and often inconspicuous component of terrestrial ecosystems, play a pivotal role in evaluating soil health and quality. As living organisms residing within the soil matrix, they are sensitive indicators of the environmental conditions and overall ecosystem dynamics, making them invaluable sentinels in the assessment of soil quality. This scientific endeavor seeks to expound upon the critical importance of employing a zoological approach for comprehensive soil quality evaluation. The utilization of soil invertebrates as bioindicators facilitates the assessment of both abiotic and biotic factors shaping soil quality. Their mobility allows them to respond to changing environmental conditions, while their small size renders them particularly sensitive to local variations. As agents of decomposition, nutrient cycling, and ecosystem stability, soil invertebrates play a major role in the sustainable development of agriculture and forestry practices. The application of a zoological perspective to soil quality assessment not only elucidates the complex web of interactions within soil ecosystems but also contributes to the advancement of sustainable agricultural and environmental practices

Advancing insights in contemporary endodontics: Proposing a multimethod approach for comprehensive evaluation of NiTi instruments.

Advancing insights in contemporary endodontics: Proposing a multimethod approach for comprehensive evaluation of NiTi instruments.

Opening the envelope: Efficient envelope-based PPG denoising algorithm

Photoplethysmography (PPG) signals obtained from the skin’s surface offer valuable insights into blood volume fluctuations. With the rising interest in continuous non-invasive physiological monitoring, PPG has garnered significant attention. However, PPG signals are often affected by various forms of noise, impeding reliable feature extraction. Robust data pre-processing approaches are vital for both retrospective and real-time analysis. Existing denoising methods, including recent machine learning techniques, often suffer from implementation challenges, computational inefficiency, and limited interpretability. Addressing this challenge, we propose a novel PPG denoising algorithm. The algorithm was evaluated using a dataset representing approximately 81,015.99 min or 1360.27 h of PPG data collected from 31 patients. The evaluation involved the calculation and analysis of five key metrics: Signal-to-Noise Ratio (SNR), Variance, Total Variation (TV), Shannon entropy, and Instances-per-second (IPS). Our results demonstrate a notable increase in SNR after denoising, indicating effective noise reduction while preserving signal content. Variance and TV values showed a reduction post-denoising, suggesting smoother and less variable signals, validating the noise suppression efficacy. Additionally, Shannon entropy exhibited a decrease after denoising, indicating successful noise reduction and enhanced signal regularity. The nonparametric Wilcoxon signed-rank test (a = 0.05) was employed to assess the statistical significance of the observed differences of these metrics before and after denoising. Furthermore, the computational speed analysis revealed the EPDA’s potential for efficient processing of large datasets and real-time applications. This comprehensive evaluation approach allows for a thorough understanding of the EPDA’s effectiveness in denoising PPG data, fostering advancements in non-invasive physiological monitoring and promoting the broader adoption of PPG-based healthcare technologies.