Real Tool Research Articles

Acoustics and vibration based milling diagnostics using supervised machine learning approaches

In industrial machining processes, tool failures may result in losses in surface and dimensional accuracy of a finished part, or possible damage to both the work piece and the machine. Consequently, tool condition monitoring has become essential to achieve high-quality machining as well as cost-effective production. Moreover, cutting tool degradation may vary considerably under different operation conditions and materials behaviour. Therefore, real time identification of the tool state during machining is critical. In this study the acoustic and vibration responses of the cutting tool and of the workpiece material are measured with the help of a microphone and a piezoelectric accelerometer. Many milling experiments were conducted for different conditions and tool failures, from which features were calculated in time and frequency domains and then split into two groups: 80% for the machine learning model training, 20% for the test phase. Then several supervised machine learning approaches have been applied and compared. Results of our study are implemented in a real tool wear predictive maintenance framework.

Methodological approaches to analysis of efficiency of functioning of logistics system of the enterprise

Introduction. Analysis of efficiency of functioning of logistics system of the enterprise is a real tool for managing such a system, ensuring its stability and dynamic development. Also such an analysis is a tool for searching adequate directions of providing and increasing the efficiency of functioning of logistics system of the enterprise. The purpose of this paper is to explore and develop the methodological approaches to analysis of efficiency of functioning of logistics system of the enterprise. To achieve the purpose of the paper, the set of methods of theoretical generalization (induction, deduction, analogy, abstraction, comparison, generalization, grouping, analysis, synthesis, causality), abstract-logical and tabular methods are used. Results. The importance of researching methodological provisions to analysis of efficiency of functioning of logistics system of the enterprise are proven. The key criteria of the efficiency of functioning of logistics system of the enterprise are determined. The objects, subjects, main tasks, directions, principles, methods, information base of analysis of efficiency of functioning of logistics system of the enterprise are substantiated. An algorithm for analyzing the efficiency of functioning of logistics system of the enterprise is developed. The directions of the analysis are highlighted and characterized. The main indicators of efficiency of functioning of logistics system of the enterprise are systematized and grouped according to the directions of analysis. Conclusion. Based on the results of analysis the efficiency of functioning of logistics system of the enterprise, strategic prospects for its optimization are developed and the most optimal management solutions for further development are determined. Further research should focus on developing strategic and tactical vectors of increasing the efficiency of functioning of logistics system of the enterprise.

Optimization of Material Utilization by Developing a Reliable Design Criterion for Tool Construction in Cross-Wedge Rolling

The massive forming industry in Germany produces around 1.4 million parts every year, which are mainly used in safety-relevant areas such as the automotive industry. The production of these parts requires a considerable amount of energy, much of which remains unused and causes high CO2 emissions. An efficient approach to reduce these emissions and improve material utilization is cross-wedge rolling, which enables efficient material utilization but is limited by the so-called Mannesmann effect, which leads to unwanted material defects. This paper describes the development and validation of a safe design criterion for cross-wedge rolling tools in order to avoid material damage caused by the Mannesmann effect and thus increase resource efficiency in forging. Based on simulation-supported investigations and experimental tests, process maps are created for various materials. The validation is carried out both in an experimental test facility with real tools and in an industrial production facility, which leads to a significant reduction in excess material and CO2 emissions. The results show that the full resource potential of cross-wedge rolling can be exploited by optimizing process parameters and tool geometries.

A web‐based operational tool for the identification of best practices in European agricultural systems

AbstractUnder the same perspective of the Sustainable Development Goal (SDG) 15.3 aiming to restore degraded land and soil, one of the current priorities of the new Common Agriculture Policy (CAP) is to overcome the serious environmental problems raised by intensive agriculture. Despite the steps forward guaranteed by new technologies and innovations (e.g., IoT, precision agriculture), the availability of real operational tools, which could help the member states fulfil the high requirements and expectations of the new CAP and SDGs, is still lacking. To fill this gap, in the H2020 LandSupport project, the web‐based best practice tool was developed to identify, on‐the‐fly, optimized agronomic solutions to help achieve land‐degradation neutrality. The tool's core is the ARMOSA process‐based model, which dynamically simulates the continuum soil–plant–atmosphere, combining several cropping systems, crops, nitrogen fertilization rates, tillage solutions, and crop residue management for specific regions of interest. It provides a synthetic “Best Practice index” to identify the optimized local solutions, which combines the production, nitrate leaching, and SOC_change, according to the end‐user dynamic requests. The tool was implemented for three case studies: Marchfeld Region in Austria, Zala County in Hungary, and Campania Region in Italy, which are representative of a variety of different pedoclimatic conditions. In the present work, we report three possible cases of use in supporting best practices aiming toward soil and water conservation: (i) crop production optimization; (ii) impact of management practices (i.e., cover crops) over soil carbon; (iii) lowering the impact of nitrate leaching.

Conservation as a Tool for Cultural Rights in the Democratic Republic of the Congo: The We have gaps Project

ABSTRACT This paper outlines the aim, methodology, and initial results of a joint initiative between two universities (Université de Kinshasa in Kinshasa, Democratic Republic of the Congo and Université de Liège in Liège, Belgium), two conservation training courses (Academy of Fine Arts of Kinshasa and École Supérieure des Arts Saint-Luc in Liège), and the Institute of National Museums of Congo. The Nous avons des lacunes (We have gaps) project plays on the notion of loss – both material and of knowledge – to involve communities in the construction of endogenous knowledge on the conservation of objects: a task to be carried out by the Congolese, for the Congolese. For many Congolese, concepts such as ‘museum’ and ‘conservation’ sound foreign, and the idea of cultural rights remains highly abstract and theoretical. The challenge is to transform the manifestation of these rights through conservation into a real tool for empowerment. The exhibition concept is two-fold: conservators explain what loss or material alteration has occurred in a specific object, and how they remedy it, thus arousing interest in a little-known profession. At the same time, they show and explain their own gaps in knowledge, and ask the public for information about the technique, function, use, naming, or names of the mystery object in the four national languages and numerous Congolese idioms. The Nous avons des lacunes project aims to highlight the role and involvement of communities and different social entities as active guardians of their heritage, by humbly admitting the lack of knowledge among professionals.

ECG imaging as a real time tool to guide left bundle branch pacing implant in patients with left bundle branch block and resynchronization therapy indication

Abstract Background Left bundle branch pacing (LBBP) has emerged as a promising alternative technique for cardiac resynchronization therapy (CRT). ECG imaging (ECGI) may provide an accurate assessment of electrical resynchronization using real-time maps during LBBP implant. Purpose To evaluate the usefulness of ECGI to guide LBBP implant, by analyzing the ventricular activation times and the degree of resynchronization at each screwing step during the lead implant. Methods Four patients with CRT indication and left bundle branch block (LBBB) referred for LBBP were prospectively enrolled. ECGI was performed during the implant procedure. Cardiac signals were recorded using ECGI and projected into an artificial intelligence-derived geometric model. Thus, generating imageless and non-invasive activation maps at defined stages during lead screwing: basal rhythm (LBBB), right ventricular (RV) septum, mid-septal, deep-septal, and finally pacing from the left bundle branch (according with guidelines ECG criteria). The following parameters were measured: a) total activation time (TAT); b) left ventricular activation time (LVAT); c) left ventricular dyssynchrony index (LVDI) (as a quantifier of intraventricular dyssynchrony); d) ventricular electrical uncoupling (VEU); and e) histogram overlap between LV and RV distribution (the last 2 markers of interventricular dyssynchrony). Results The study cohort comprised men with a median age of 68 [Q1 59- Q3 79], with a median basal LBBB QRS duration of 175 ms [160-188] and a median LVEF of 32% [28-39]. A shortening of the activation times and a decrease in intra and interventricular dyssynchrony was achieved when the final lead position was reached. See the results in Figure 2. Conclusion Real-time and imageless ECGI system may offer a novel approach for guiding LBBP and it is useful to ensure left ventricular resynchronization.ECGI to guide LBBP implantActivation and dyssynchrony measurements

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries.

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

Reelekcja prezydenta w systemie politycznym Republiki Włoskiej. Od teorii do praktyki

The Constitution of the Italian Republic, in the section devoted to the head of state, does not refer anywhere to the issue of re-election or term limits. From the beginning of the Italian Republic, the debate on this issue was theoretical in nature, until 2013. Then, for the first time in history, a sitting president was elected for another term. The situation took place again in 2022. These events resulted in the transfer of the topic of re-election from a theoretical to a practical one, being perceived as a real tool in the hands of the electors. The aim of this work was to examine the issue of presidential re-election in the Italian political system. Legal and political analysis has shown that the presidential re-election, which for years was perceived in Italy as an undesirable solution, ultimately contributed twice to the stabilization of the Italian political system.

Impact of real property tax tools of Sulu Provincial Assessor’s Office: employees’ perspectives

The effect that real property tax instruments at the Sulu Provincial Assessor's office have on Sulu local government entities is the subject of this study. One hundred respondents were included in the study; most were middle-aged (26–39), with over half of them being employed full-time. Employees were highly in agreement about these technologies' efficacy, according to the survey, with tax mapping activities and computerization through electronic methods obtaining "Strongly Agree" ratings. For the Schedule of Market Value category, on the other hand, the rating was "Agree," indicating a somewhat lower but still favorable opinion of the fairness and accuracy of property assessments. When the tools were categorized based on gender, age, or work position, the study also did not find any discernible variations in the degree of impact of the tools. When the data was sorted by duration of employment, there were notable distinctions, indicating that employees with varying tenures had differing perceptions. The study found that respondents, independent of demographic variables, had a higher degree of agreement about the perceived impact and effectiveness of different real property tax instruments. The study's conclusion emphasizes how crucial it is to take into account the various backgrounds and experiences of staff members when assessing how well the Sulu Provincial Assessor's office's real property tax tools work.

A novel ESIPT fluorescent probe for early detection and assessment of ferroptosis-mediated acute kidney injury via peroxynitrite fluctuation

BackgroundAcute kidney injury (AKI) poses a severe risk to public health, mostly manifested by damage and death of renal tubular epithelial cells. However, routine blood examination, a conventional approach for clinical detection of AKI, is not available for identifying early-stage AKI. Plenty of reported methods were lack of early biomarkers and real time evaluation tools, which resulted in a vital challenge for early diagnosis of AKI. Therefore, developing novel probes for early detection and assessment of AKI is exceedingly crucial. ResultsBased on ESIPT mechanism, a new fluorescent probe (MEO-NO) with 2-(2′-hydroxyphenyl) benzothiazole (HBT) derivatives as fluorophore has been synthesized for dynamic imaging peroxynitrite (ONOO−) levels in ferroptosis-mediated AKI. Upon the addition of ONOO−, MEO-NO exhibited obvious fluorescence changes, a significant Stokes shift (130 nm) and rapid response (approximately 45 s), and featured exceptional sensitivity (LOD = 7.28 nM) as well as high selectivity from the competitive species at physiological pH. In addition, MEO-NO was conducive to the biological depth imaging ONOO− in cells, zebrafish, and mice. Importantly, MEO-NO could monitor ONOO− levels during sorafenib-induced ferroptosis and CP-induced AKI. With the assistance of MEO-NO, we successfully visualized and tracked ONOO− variations for early detection and assessment of ferroptosis-mediated AKI in cells, zebrafish and mice models. Significance and noveltyBenefiting from the superior performance of MEO-NO, experimental results further demonstrated that the levels of ONOO− was overexpressed during ferroptosis-mediated AKI in cells, zebrafish, and mice models. The developed novel probe MEO-NO provided a strong visualization tool for imagining ONOO−, which might be a potential method for the prevention, diagnosis, and treatment of ferroptosis-mediated AKI.

Tools Identification By On-Board Adaptation of Vision-and-Language Models

A robotic workshop assistant has been a long-standing grand challenge for robotics, speech, computer vision, and artificial intelligence (AI) research. We revisit the goal of visual identification of tools from human queries in the current era of Large Vision-and-Language models (like GPT-4). We find that current off-the-shelf models (that are trained on internet images) are unable to overcome the domain shift and unable to identify small, obscure tools in cluttered environments. Furthermore, these models are unable to match tools to their intended purpose or affordances. We present a novel system for online domain adaptation that can be run directly on a small on-board processor. The system uses Hyperdimensional Computing (HD), a fast and efficient neuromorphic method. We adapted CLIP to work with explicit ("I need the hammer") and implicit purpose-driven queries ("Drive these nails"), and even with depth images as input. This demo allows the user to try out various real tools and interact via free-form audio.

The Size of a Company and the Intensity of Use of Accrual-Based Earnings Management and Real Earnings Management Tools

Abstract Subject and purpose of work: The aim of the study is to analyse the relationship between the degree of use of accrual-based earnings management and real earnings management instruments and the size of public companies. Materials and methods: The empirical analyses are based on the results of a survey of finance and accounting professionals representing 124 non-financial companies listed on the Warsaw Stock Exchange. The Kruskal-Wallis test (along with tests of intergroup comparisons) was considered the primary method for assessing the relationships occurring between the variables considered. Results: The research showed that the intensity of using accrual-based earnings management and real earnings management tools is statistically dependent on both the value of generated net revenues from the sale of products, goods and materials and the value of total assets of a given company. However, a greater diversification of the values of variables describing the degree of use of earnings management instruments was recorded in individual sub-populations separated on the basis of the value of realised sales. Conclusions: The research appears to be relevant from the perspective of a further search for the determinants of financial performance manipulation in the Polish capital market.

A novel image-guided laparoscopic liver resection with integrated fluorescent imaging and artificial intelligence: A preliminary study.

568 Background: Technology innovations improve surgical techniques. ICG fluorescence imaging is beneficial for real time navigation tool during surgery and enables accurate surgery. Recently, the prediction of anatomical structures by artificial intelligence (AI) is expected to support surgeons as navigation tool. We developed a visual-support AI system to perform the laparoscopic liver resection (LLR) using ICG fluorescence imaging and AI technology. Methods: Procedure: ICG fluorescence imaging was used for liver mapping and securing surgical margin. AI model development and evaluation: Over 430 images extracted from 13 videos of LLR for hepatocellular carcinoma and colorectal liver metastasis was used to develop and evaluate the AI algorithm at Anaut Inc. The annotation was performed on video frames capturing a LLR performed by 2 surgeons for hepatic vein and Glisson sheath. The performance of AI on unlearned LH videos was evaluated quantitatively using Intersection-Over-Union (IOU) and Dice coefficients, and qualitatively on a five-point scale (from 1 to 5) by 10 hepato-biliary-pancreatic surgeons using 35 randomly extracted still images from the analyzed videos. Results: ICG fluorescence imaging could visualize the demarcation line and clarified the boundaries of the liver transected surface. The hepatic veins and Glisson sheath were appeared in the parenchymal transection plane during segmentectomy and securing surgical margin, and this AI system enabled to recognize and display these vascular structures through color-coding under bleeding and ICG fluorescent imaging without visual discrepancies. The AI model accurately recognized vascular structures of any size (IoU=0.33, Dice=0.44) in real-time (<0.12 s) In the qualitative evaluation by surgeons, the mean sensitivity score was 4.10 ± 0.92 (range 3.61–4.76). Additionally, this AI system also recognized vascular structures during robot-assisted liver resection. Conclusions: This is the first study demonstrating that AI can precisely identify vascular structures during LLR. Novel image-guided LLR using ICG fluorescent imaging and artificial intelligence is expected to provide safer and more accurate LLR, thereby contributing to reduce complications and improve survival rates.

Lorsque le bruit fait silence… Retour réflexif sur une ethnographie de cours de salsa

The practice of salsa induces conditions of exchange between social actors that are almost exclusively based on the gaze. Beyond the explanation of the conditions of the collection of materials, this article offers a more general methodological reflection on the ethnography of fields in which speech as an instrument of interaction is limited. It allows us to formulate some conclusions on the heuristic value of body language and its conditions of possibility, and on the benefits of considering the “discomforts” of the field as real tools of knowledge.

My co-worker is a real tool: Perceptions of Human-AI teamwork

This paper explores the evolving dynamics of Human-AI teams (HATs). The paper does this by examining the shift of AI from a mere tool to an active team contributor. Additionally, the paper surveys the concepts of mental models, schemas, and social norms in HAT interaction to understand human perceptions and expectations in these hybrid collaborations. Finally, the paper advocates for interdisciplinary research to enhance the efficacy of HATs, underscoring the need to navigate the intricate relationship between humans and AI in various contexts.

A new family of fourth-order Ostrowski-type iterative methods for solving nonlinear systems

<abstract><p>Ostrowski's iterative method is a classical method for solving systems of nonlinear equations. However, it is not stable enough. In order to obtain a more stable Ostrowski-type method, this paper presented a new family of fourth-order single-parameter Ostrowski-type methods for solving nonlinear systems. As a generalization of the Ostrowski's methods, the Ostrowski's methods are a special case of the new family. It was proved that the order of convergence of the new iterative family was always fourth-order when the parameters take any real number. Finally, the dynamical behavior of the family was briefly analyzed using real dynamical tools. The new iterative method can be applied to solve a wide range of nonlinear equations, and it was used in numerical experiments to solve the Hammerstein equation, boundary value problem, and nonlinear system. These numerical results supported the theoretical results.</p></abstract>

РОЛЬ УНИВЕРСИТЕТСКИХ КОМПЛЕКСОВ В СОЦИАЛЬНО-ЭКОНОМИЧЕСКОМ РАЗВИТИИ РЕГИОНОВ СТРАНЫ

Education plays an important role in the development of the socio-economic system. It not only generates qualified specialists, but also has a strong influence on the economic, political and social development of the regions. In modern conditions, education is becoming a real tool for the qualitative development of the country and increasing its economic potential. For a more accurate understanding of the role of university complexes in socio-economic development, the task of a comprehensive assessment of the main aspects of their contribution to the development of the regions of our country is urgent. The article examines how university complexes contribute to scientific research, the development of innovations and the creation of new technologies. The article analyzes exactly how university complexes act as incubators for startups and young entrepreneurs. Attention is also paid to attracting investments, specialists and talented youth. The cultural role of university complexes is also not ignored. The authors consider the impact on socio-economic development of key trends in education, namely digitalization and mobility. The evolution of the roles played by university complexes is noted. They go beyond traditional knowledge transfer and become active participants in socio-economic and regional governance. Thanks to their multifaceted activities, universities play a key role in creating a favorable economic environment and ensure the sustainable development of both individual regions and our country as a whole. The article focuses on the fact that education is not just a process of acquiring knowledge and skills, but rather a unifying force capable of transforming the socio–economic sphere of the regions of our country.

Development of a convolutional neural network model to predict the size and location of corrosion defects on pipelines based on magnetic flux leakage signals

This study employs the convolutional neural network (CNN) to predict the dimensions and locations of corrosion defects on steel pipelines based on magnetic flux leakage (MFL) signals. Extensive three-dimensional parametric finite element analyses are carried out to generate MFL signals corresponding to semi-ellipsoidal-shaped corrosion defects with different sizes and locations on a pipe model. The white noises characterized by different signal-to-noise ratios are considered in the analysis to represent the measurement errors in the real MFL inspection tool. The numerically generated MFL signals are used to train and validate the CNN model to predict the dimensions and locations of the corrosion defects. The results indicate that the developed CNN model achieves a high predictive accuracy. The study demonstrates the application of CNN model to improve the pipeline integrity management practice.

A real time condition based sustainable maintenance method for milling process

The manufacturing industry must reduce energy consumption during the machining process to comply with energy demand and usage restrictions. Previous research has employed various methods to take a optimization plan in machining process. However, these studies mostly rely on static machining conditions, without paying much attention for the condition variation, which may lead to a coarse energy efficiency optimization in machining process. Hence, this study introduces a real time condition based sustainable maintenance method for machining process. Firstly, a real-time data acquisition system is employed to collect and send data to the developed tool condition prediction model using deep learning. Then, the physical energy prediction model is employed to reflect the real time energy consumption behaviors based on the real time tool condition. Subsequently, a similarity analysis is employed to decide whether a new optimization is required. And, once it is required, an optimization using NSGA-II and TOPSIS is conducted. Experiments were conducted on a milling machine and compared with traditional methods, and verified using triple bottom line. Results indicated that the proposed method can reduce the energy consumption by 2.51% and 7.01%, and it can maintain a qualified product during the machining process.

On density measurement using various radiation sources: Cs-137, X-ray and pulsed neutron

The use of controllable sources for density measurement is gaining more attention as a safer alternative to chemical sources, since chemical sources pose risks to both humans and the environment. Nuclear density tools using electronically controlled sources, such as X-ray tubes and pulsed neutron generators, are being researched as a replacement for radiological gamma sources such as Cs-137. This study, based on the real gamma density tool structure, optimizes the design of the X-ray and pulsed neutron-gamma density tools, providing a reference for the optimization of source-less density tools. Firstly, the study gives a comparison of density measurement using three sources through a combination of theory and simulation results. And the performance of the tools is evaluated using indicators such as detection efficiency, formation density sensitivity, and depth of investigation. Finally, based on the characteristics of different sources, the aforementioned indicators are balanced to obtain the optimal value of the source-to-detector distance, thus the structure of the X-ray density tool and pulsed neutron-gamma density tool are optimized.