Analysis System Research Articles

Analysis of Game Variables and Influence on Defensive Success in Elite Handball

Background: The analysis of defensive game variables in handball is essential to increase the performance of a team. Objectives: This study aimed to analyse defensive success based on the game variables and situational variables that predict defensive efficiency in elite handball. Methods: The sample was composed of 1925 competition units in the defensive phase. Data from 16 matches of the XXIII Men's Handball World Championship of 2013 were analysed. The dependent variable was the defensive efficiency in each unit, and the independent variables were defensive actions, zones of field, location of the shot, numerical situation, and duration of the defense. Data were obtained from the HandballTAS tool (Handball Tactic Analysis System). The collected data were analysed quantitatively through inferential statistics (independent sample t-test) with the assistance of SPSS 22.0. Results: The defenses analysed in which an offensive foul, a ball recovery or steal, a throw block and a passive play action were recorded, achieved defensive success. In the analysis of field areas, the greatest defensive efficiency was obtained in shots from zone 1, with 60%, and from zone 2, with 54%. The highest percentages of goalkeeper effectiveness correspond to the middle zone, and the central zone. The greatest defensive efficiency was obtained in a warning of passive play situation with 70% and in numerical superiority situation with 67%. Finally, in the analysis of the duration, the greatest defensive efficiency was obtained in the half defenses (26 ≤ 50 seconds) with 60%. Conclusion: This study serves to demonstrate which defensive game variables have the greatest influence on defensive efficiency. This aspect will serve to help the coach make decisions during a handball match and increase the probability of success in each defense.

Integrated Morphometric and Hypsometric Analysis of Niragantipalli Micro Watershed Using Remote Sensing and Geographical Information System Techniques

Employing Remote sensing (RS) and geographic information system (GIS) for the morphometric parameters analysis are discovered to be tremendous usefulness in the prioritization of watersheds for soil, water conservation and natural resource management at micro watershed level. The analysis of morphometric parameters plays a crucial role for understanding and managing watersheds. In current study an, attempt was to determine the morphological parameters of Niragantipalli micro-watershed in Chikkaballapura District of Karnataka, India. For detail study, Google earth pro, GPS visualizer conversion toll and Arc GIS were used for preparation of DEM and delineation of the watershed boundary. GIS was used for evaluation of basic, linear, areal and relief aspects of morphometric parameters. The Niragantipalli micro-watershed occupies an area of 632 ha with third order stream (truck order) and dendritic drainage pattern. The mean bifurcation ratio of the micro-watershed is 2.5 it suggests that the drainage system formed on homogeneous rock when the influences of geologic structures on the network of streams were negligible and generate sharp peak flow. With a drainage density of 1.31 km/km2, the drainage network is extremely coarse. The watershed is elongated, as shown by the form factor of 0.27 and elongation ratio of 0.58. The results from the morphometric analysis of the watershed are very beneficial for developing and designing conservation structures of soil and watershed management measures. The hypsometric curves’ structure as well as estimated hypsometric integral results reflects the Niragantipalli Micro Watershed erosional stages. As a result, the study concludes that morphometric and hypsometric analysis findings may be useful to stakeholders participating in catchment development and management projects.

Predicting customer sentiment: the fusion of deep learning and a fuzzy system for sentiment analysis of Arabic text

Predicting customer sentiment: the fusion of deep learning and a fuzzy system for sentiment analysis of Arabic text

Теоретические основы построения систем управления современными предприятиями

Timely research and analysis of enterprise management systems, their competent decomposition into component parts in order to implement corrective actions to improve the final efficiency of the management process as a whole, are relevant areas of theoretical and practical scientific research. As a result of the study of existing approaches to the concept of a management system, its substantive characteristics as an anthropogenic system and directions for study, analysis and improvement at specific enterprises have been clarified. The importance of such properties of the management system in modern conditions is substantiated as: integrity, manifested in the presence of its own pattern of development and influence on the characteristics of the controlling and controlled subsystems; synergy, providing qualitatively new properties, and dynamic equilibrium, compensating for the effects of the internal and external environment on the functioning of the enterprise. As the main directions of the decomposition of the management system, the following are highlighted: functional areas of management – production subsystem, financial subsystem, personnel subsystem, etc.; management functions – planning, organization, motivation, control, etc.; object and subject of management; dynamic and static subsystems, where the static subsystem (structure, resources, controls) sets the framework for management activities, and the dynamic subsystem (management process carried out using management functions) transfers the system from one stable state to another to compensate for the effects exerted by the external and internal environment.

PyICLab: An integrated Python-based toolkit for in-silico simulations of ion chromatography

PyICLab is an open-source Python-based package featuring an object-oriented programming (OOP) interface, providing tools for realistic and customized numerical simulations of ion chromatography (IC). In this paper, we showcase PyICLab's use in simulating diverse separation scenarios, including isocratic carbonate elution, gradient hydroxide elution, high-concentration and large-volume injections. The accuracy of the embedded models was validated by demonstrating strong correlations between predicted and experimental results. Additionally, PyICLab's capability to handle complex IC configurations was demonstrated through a simulation of a column-switching system for seawater analysis. PyICLab offers valuable resources for chromatographic optimization, method development, and educational purposes. It is available on PyPI at pypi.org/project/pyIClab. Interested readers can install PyICLab using the pip command in a Python 3.11 or higher environment.

Enhanced facial expression recognition using transfer learning and M-CLAHE

In recent years, Facial Expression Recognition (FER) techniques have gained substantial attention within the realm of biometric technology due to their wide range of applications, including emotion analysis, human-computer interaction, and surveillance systems. This paper presents a robust and efficient FER system composed of three key steps. First, precise face detection is performed using the Viola-Jones algorithm, a well-established method for detecting facial features in real-time. Second, the detected images are enhanced using a Modified Contrast Limited Adaptive Histogram Equalization (M-CLAHE) technique to improve contrast and visibility. Finally, feature extraction and classification are carried out using three powerful Convolutional Neural Network (CNN) architectures: VGG16, ResNet50, and Inception-v3, all benefiting from Transfer Learning to boost performance. Experiments were conducted on two widely-used datasets, JAFEE and CK+, with Inception-v3 achieving remarkable accuracy, reaching 98.43% and 99.93% on the respective databases. These results underline the effectiveness and robustness of our approach, particularly through the use of Transfer Learning, which significantly enhances the overall performance of the model compared to existing methods.

Effects of inter- and intraindividual compensation-sensitive shot styles on performance in Olympic air rifle shooting

Background: Aiming point analysis systems (APAS) are commonly used in sports shooting but face four main challenges: they do not account for intra-session variations, they overlook inter-individual shooter preferences, they ignore compensation mechanisms of technical features, and they do not respect the real shot location at the target. Methods: To address the first three challenges, we developed and validated an automated approach detector algorithm (ADA) for movement phase detection. When compared to three independent expert ratings, the ADA demonstrated a high correlation (r = .811). Building on the ADA and addressing challenge 3 and 4, this study applied cluster-analysis and ANOVA to determine the performance relevance of compensation-sensitive shot styles using datasets from a single athlete and 26 advanced to elite level athletes. Results: Significant performance differences in shot styles for both datasets, with each shot style distinctively differing from the others could be found. Conclusions: Shot styles which allow for compensation and intra-individual movement phase differences exhibit performance variations. Coaches and athletes should emphasize holistic training, focusing on combinations of features that allow for compensation.

Quantitative Assessment of New Frontiers in Dermatochalasis and Periorbital Hyperpigmentation Treatment: The Role of Cross-Linked Porcine Collagen.

Collagen dermal fillers have shown efficacy in addressing age-related changes in facial appearance. However, their potential in rejuvenating the periorbital region remains unexplored. The aim of this study was to evaluate the effectiveness, clinical safety, and patient satisfaction associated with the utilization of collagen dermal fillers in individuals with dermatochalasis and periorbital hyperpigmentation. This study was reviewed and approved by the institutional review board of China Medical University Hospital (IRB No. CMUH107-REC2-157). Adults diagnosed with dermatochalasis or periorbital hyperpigmentation received periorbital injections of a sterile cross-linked highly-purified specific antigen free porcine dermal collagen (FACIALGAIN® Collagen Implant with Lidocaine, Sunmax Biotechnology Co. Ltd., Taipei, Taiwan) and were assessed for hydration, elasticity, pigmentation index, redness index, lightness value, and density with the DermaLab® Combo Multiparameter Skin Analysis System (Cortex Technology, Hadsund, Denmark) and Cutometer® Dual MPA 580 (Courage+Khazaka electronic GmbH, Köln, Germany). Data was collected prior to injection and at 1 week, 4 weeks, and 12 weeks after injection. Patient satisfaction on volume augmentation, decrease in hyperpigmentation, persistence, and overall satisfaction were also recorded. A total of 12 samples each were recruited for dermatochalasis and periorbital hyperpigmentation. For dermatochalasis subjects, hydration of the periorbital tissue significantly increased at week 1 and 4 (p = 0.011 and p = 0.015). Elasticity decreased by week 4 and persisted until week 12 (p = 0.001 and 0.014). For periorbital hyperpigmentation patients, lightness value increased significantly starting week 1 (p = 0.016), tapering off at week 12. Elasticity decreased by week 4 and persisted until week 12 (p = 0.002 and p = 0.002). Median overall patient satisfaction was 4 out of 5 for the dermatochalasis group and 4.5 out of 5 for the periorbital hyperpigmentation group, with a mild but insignificant decrease by week 12. DermaLab® Combo and Cutometer® Dual MPA 580 are considered effective methods for evaluating patients undergoing dermal filler injections. The utilization of cross-linked porcine collagen dermal filler injections can serve as a minimally invasive approach to enhance skin laxity in dermatochalasis and address discoloration in periorbital hyperpigmentation. However, it is important to note that regular treatments may be necessary to sustain the desired outcomes. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/0026 .

An unsupervised machine learning-based profile system of Chinese researchers

The construction of researcher profiles is crucial for modern research management and talent assessment. Given the decentralized nature of researcher information and evaluation challenges, we propose a profile system for Chinese researchers based on unsupervised machine learning and algorithms. This system builds comprehensive profiles based on researchers’ basic and behavior information dimensions. It employs Selenium and Web Crawler for real-time data retrieval from academic platforms, utilizes TF-IDF and BERT for expertise recognition, DTM for academic dynamics, and K-means clustering for profiling. The experimental results demonstrate that these methods are capable of more accurately mining the academic expertise of researchers and performing domain clustering scoring, thereby providing a scientific basis for the selection and academic evaluation of research talents. This interactive analysis system aims to provide an intuitive platform for profile construction and analysis.

Advanced Personal Budget Analytics: Combining Optical Character Recognition and Natural Language Processing for Automated Budget Categorization and Insight Extraction

A budget tracking system is a tool designed to help users monitor their financial resources, categorize expenses and control their financial resources. An Intelligent Personal Budget Analysis System is designed to redefine personal finance management. IntelliFinance is a user- friendly app designed for seamless and efficient daily expense management removing the necessity for conventional paper documentation. This project inculcates the concepts of Computer Vision, Machine Learning and Data Analytics, aims to surpass traditional budget tracking by incorporating innovative features such as receipt scanning and analysis. The project is implemented using Android Studio and Firebase, incorporating advanced features such as Optical Character Recognition (OCR) to capture receipt images, extract text, and process it for further analysis. Firebase ML Kit is utilized for scanning and text recognition, while Natural Language Processing (NLP) is applied for categorizing the extracted text. The system provides a personal budget analysis that enhances the accuracy of financial tracking by offering users a comprehensive overview of their spending habits, complemented by detailed reports and visualizations. Ultimately, this project serves as a financial companion, empowering users to take control of their finances, make informed decisions, and achieve their financial goals.

Analysis of the mechanical characteristics of progressive one-handed underhand shooting in basketball play through kinematics

Background: Progressive one-handed underhand shooting is not only a key movement in basketball but also a primary method of scoring. Objective: This paper aims to compare the mechanical characteristics of players at different levels while performing the progressive one-handed underhand shooting movement to guide training. Methods: Ten athletes were divided into an excellent group and an ordinary group. The shooting was conducted using two SONY cameras, and the kinematics data were acquired through re-analysis in the Simi 3D Motion system for comparative analysis. Results: The average number of successful shots per person in the excellent group was 8.12 ± 0.81, which was significantly different from the ordinary group. During ball holding, the first step length of the excellent group was 1.91 ± 0.03 m, showing a significant difference compared to the ordinary group. At the beginning of ball holding, the right elbow joint angle for the excellent group was 121.26° ± 0.58° and the right hip joint angle was 135.64° ± 0.78°, both significantly different from those in the ordinary group. At the end of holding the ball, the excellent group had a right shoulder joint angle of 51.26° ± 2.36° and a right elbow joint angle of 70.34° ± 1.68°, which was significantly different from the ordinary group. At the end of jump, the excellent group had a right shoulder joint angle of 80.16° ± 2.21° and a right elbow joint angle of 87.45° ± 1.68°, which was significantly different from the ordinary group. During the shooting phase, the excellent group had a shooting angle of 60.12° ± 2.36°, a shooting height of 2.92 ± 0.03 m, and a shooting speed of 4.12 ± 0.46 m/s, all showing significant differences compared to the ordinary group. Conclusion: The excellent group with more sufficient stride, push, and extension and better shooting parameters performed better in performing the movement of progressive one-handed underhand shooting.

Efetividade e segurança do uso do ar ambiente em comparação ao oxigênio a 100% em prematuros em parada cardiorrespiratória: protocolo de revisão sistemática

Introduction: Cardiorespiratory arrest is a clinical situation characterized by the interruption of blood circulation. It is estimated that 11.1% of all live births in the world are premature, generating short and long-term repercussions. One of the main challenges during cardiacarrest in premature infants is providing sufficient, but not excessive, oxygen during assisted ventilation. Objective: To compare the effectiveness and safety of using room air in relation to 100% oxygen in the resuscitation of premature infants in cardiorespiratory arrest. Methods: To this end, we will carry out a systematic review of randomized clinical trials (RCTs). The study protocol was registered on the Prospero Platform (CRD42024519724). We will include preterm infants with gestational age <37 weeks with CA. The searches were carried out in the following databases: Medical Literature Analysis and Retrieval System Online (MEDLINE) via Pubmed, Excerpta Médica dataBASE (Embase) via Elsevier, Cochrane Central Register of Controlled Trials (CENTRAL) via Cochrane Library, Latin American Literature and the Caribbean Doctor in Health Sciences (LILACS) through the Virtual Health Library Portal, without restrictions on language or year of publication. The selection of studies, transmission of data, assessment of the bias of included studies and assessment of the certainty of the evidence will be carried out by two independent investigators. Expected results: Clarify the transit and safety of using room air compared to 100% oxygen, provide useful information for clinical decision-making, and support future high-quality randomized clinical trials on the topic. Conclusion: This study aims to compile existing research to analyze the effectiveness and safety of application of 100% oxygen in the resuscitation of premature infants. Keywords: Heart arrest; infant premature; systematic review.

The Design of PE Course Key Score Information Analysis and Tutoring System Based on Intelligent CAD

The Design of PE Course Key Score Information Analysis and Tutoring System Based on Intelligent CAD

Analysis of poor work postures during morning care operations of intensive care unit nurses: a field research

BackgroundPoor working postures in morning care operations contribute significantly to work-related muscle fatigue and low back pain among ICU (Intensive Care Unit, ICU) nurses. However,there are few field studies on the relationship between Poor working postures and work-related muscle fatigue, low back pain among ICU nurses.ObjectiveThis study aims to assess the frequency and degree of posture hazards associated with poor working postures during morning care operations of ICU nurses.MethodsTwo ICUs in a Grade-A tertiary hospital in Hunan Province were randomly selected for the field study in May–June 2021 research. The image data of the participating nurses’ morning care work postures were collected by observation method and image recording method, and the postural hazard level was assessed by the two-person interpretation method of the work posture analysis system. The mean and standard deviation, frequency and percentage were used for the basic statistical description, and the general linear model multivariate Hotelling’s T2 test was used to calculate the Hotelling’s T2 and F statistics to explore the pattern of change in the postural hazard score curves.ResultsA total of 45 nurses were observed during morning care operations, resulting in 47.8 h of video data and 34,428 effective static operation posture pictures. Among these pictures, 21,166 (61.5%) depicted poor working postures. Nurses spent up to 7 min and 30 s maintaining a challenging posture during oral care, with the highest postural hazard score (M = 2.2, SD = 0.3) observed during defecation care. Each patient requires a total of 25–30 min of oral care per day.The Hotelling’s T2 test indicated that the change curve of the postural hazard score in each step revealed the largest second-order F value, F = 52.931, P < 0.001.DiscussionICU nurses frequently adopt poor working postures during morning care operations. Further research should focus on optimizing safe working postures to prevent or minimise detrimental occupational hazards resulting from poor working postures.Research on occupational low back pain among ICU nurses can help them work more efficiently, and thereby improving their nursing level.

Are Beaches Losing Their Capacity to Receive Holidaymakers? The Case of Ofir, Portugal

Coastlines are suffering from the effects of erosive processes, the decrease in sediment supply, the rise in mean sea level, and the construction of coastal infrastructure and drainage works, which are further exacerbated by global climate change. The area of the Parque Natural do Litoral Norte (North Coast Natural Park) reveals worsening erosion rates and the transformations directly affect the natural resources that support tourism activities, particularly beach and nature tourism. As part of the CLICTOUR project, we have selected the coastline from Restinga de Ofir to Bonança Beach as a case study. The ESRI ArcGIS software and the Digital Shoreline Analysis System (DSAS) were used to quantify coastline migration and identify the impacts on beach morphology between 2010 and 2023. Based on this information, we calculated changes in carrying capacity and scenarios for visitor usage availability to ensure the protection of fauna and flora, as well as the safety of beachgoers. The results of the linear regression rate confirm the coastline has retreated during the period analyzed (2010–2023). The outcome of these dynamics is noticeable in the beach area, promoting its reduction in area and leisure quality. Considering climate change, this study shows the importance of developing resilience strategies for coastal territories that serve as traditional summer destinations.

Ureteroscopy and lasertripsy for lower pole stones

To investigate the outcomes of ureteroscopy and lasertripsy in lower pole renal stones <2 cm when treated in situ compared to displacement to the upper pole. Using the Medical Literature Analysis and Retrieval System Online (MEDLINE)/PubMed, the Excerpta Medica dataBASE (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Library, and Clinicaltrials.gov we identified adult population, English language, studies published until March 2023 comparing surgical outcomes and stone-free rates (SFRs) in relation to lower pole stones <2 cm managed in situ vs those displaced (International Prospective Register of Systematic Reviews [PROSPERO] identifier: CRD42023432750). Analysis was performed using R with the 'meta' package. Bias analysis was performed using the Cochrane Risk of Bias 2 tool for randomised trials and the Newcastle-Ottawa scale for observational studies. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach was used to ascertain the certainty of evidence. A total of five studies were included, comprising two retrospective cohort studies, three randomised trials, with a total of 408 patients. Meta-analysis demonstrated SFRs are significantly higher in those patients undergoing displacement vs those managed in situ (risk ratio 1.21, 95% confidence interval [CI] 1.10-1.34, P < 0.001). There was no significant difference in complication rates. Operative time was significantly longer in the displacement group (mean difference 5.62 min, 95% CI 0.40-10.83 min; P = 0.03). Overall risk of bias was moderate. Certainty of evidence was moderate for stone-free status, and very low for all other outcomes. This systematic review and meta-analysis demonstrates that for lower pole stones <2 cm displacement strategies have significantly higher SFRs than treatment in situ, with no significant difference in complications. There is significantly increased operative time in the displaced group, but an additional 6 min is unlikely to be clinically significant.

Non-Isothermal Thermogravimetric Analysis of Carbonation Reaction for Enhanced CO2 Capture

An in-depth investigation into CaO-based carbonation reaction kinetics for CO2 sorption is being conducted using simultaneous thermal analysis (STA), with the application of advanced thermogravimetric and differential scanning calorimetry techniques. Utilizing advanced thermal analysis system for real-time monitoring of simultaneous measurements of mass changes and thermal effects are conducted, ensuring precision and versatility in data acquisition. The study explores the intricacies of the non-isothermal carbonation process across a wide range of temperatures, shedding light on the temperature-dependent trends in reaction rates. Innovative statistical methods, combining regression techniques and Arrhenius equation, are employed to determine energy and reaction kinetics. The sensitivity of carbonation process to varying pressure conditions is meticulously examined in the study, providing pivotal discernment for optimization of reaction parameters across diverse applications. The integration of STA with statistical modeling alongside systematic analysis of temperature-dependent trends and pressure-order relationships not only enhances the understanding of CO2 capture efficiency but also improves the robustness and accuracy of the findings. Furthermore, meticulous cross-validation with existing studies provides a critical evaluation of the experimental approach’s precision and limitations. This study enhances understanding of CaO carbonation kinetics, providing practical implications for carbon capture processes and contributing to sustainable industrial processes.

RANCANG BANGUN PENDETEKSI DEHIDRASI MANUSIA BERDASARKAN WARNA URINE BERBASIS INTERNET OF THINGS (IOT)

In the current technological era, the Internet of Things (IoT) provides creative fixes for numerous health problems. The purpose of this research is to design and construct a urine color analysis system that uses the Internet of Things to identify human dehydration. Urine color is precisely measured and analyzed by the system using color and pH sensors. Data is then sent over an internet connection to a cloud-based platform.The urine color analysis results will be compared to accepted medical standards as part of the processing of the gathered data to ascertain the user's bodily hydration level. This system has a Blynk app-based user interface that offers proper hydration recommendations and real-time information about the user's level of hydration. It is anticipated that by putting this system in place, users will be able to efficiently check their level of hydration and take precautions to avoid being dehydrated. This research offers a more approachable and cost-effective method of managing one's own health in addition to aiding in the development of Internet of Things-based health technology.

X-Tracker: Automated Analysis of Xenopus Tadpole Visual Avoidance Behavior.

Xenopus laevis tadpoles exhibit an avoidance behavior when they encounter a moving visual stimulus. A visual avoidance event occurs when a moving object approaches the eye of a free-swimming animal at an approximately 90-degree angle and the animal turns in response to the encounter. Analysis of this behavior requires tracking both the free-swimming animal and the moving visual stimulus both prior to and after the encounter. Previous automated tracking software does not discriminate the moving animal from the moving stimulus, requiring time-consuming manual analysis. Here we present X-Tracker, an automated behavior tracking code that can detect and discriminate moving visual stimuli and free-swimming animals and score encounters and avoidance events. X-Tracker is as accurate as human analysis without the human time commitment. We also present software improvements to our previous visual stimulus presentation and image capture that optimize videos for automated analysis, and hardware improvements that increase the number of animal-stimulus encounters. X-Tracker is a high throughput, unbiased, and significant time-saving analysis system that will greatly facilitate visual avoidance behavior analysis of Xenopus laevis tadpoles, and potentially other free-swimming organisms. The tool is available at https://github.com/ClineLab/Tadpole-Behavior-Automation.

ECG signal analysis and detection system based on deep learning

In view of the problems of large workload and easy error in traditional manual recognition of ECG signals, and the existing ECG monitoring equipment still has few ECG signal recognition types, low diagnostic accuracy, and excessive reliance on network services, in order to improve the performance of ECG monitoring equipment, an ECG (Electrocardiogram Signals) analysis and detection system is designed based on deep learning technology. The SENet-LSTM (Squeeze-and-Excitation Networks Long Short Term Memory) network model is built to realize automatic diagnosis of 7 categories of ECG signals. The model is built on an intelligent hardware platform that uses ADS1292R as ECG acquisition module, STM32F103 as data processing module, and Raspberry Pi as central processing module. The system uses the integrated high- performance microcomputer Raspberry Pi for calculation and analysis, providing users with offline artificial intelligence (AI: Artificial Intelligence) services. At the same time, the accuracy and precision of the model are and respectively 98.44%, 90.00%thereby realizing real-time detection and accurate classification of ECG, providing patients with accurate disease diagnosis.