Real Tool Research Articles

Algorithm-Driven Hedonic Real Estate Pricing – An Explainable AI Approach

AbstractData-driven machine learning algorithms triggered a fundamental change in hedonic real estate pricing. However, their adaptive nonparametric structure makes inference and out-ofsample prediction challenging. This study introduces an explainable approach to interpreting machine learning predictions, which has not been done before in the local market context. Specifically, Random Forest and Extreme Gradient Boosting models are developed for residential real estate price prediction in Warsaw in 2021 on 10,827 property transactions. Model-agnostic Explainable Artificial Intelligence (XAI) methods are then used to investigate the black box decision making. The results show the practicability of applying XAI frameworks in the real estate market context to decode the rationale behind data-driven algorithms. Information about the relationships between input variables is extracted in greater detail. Accurate, reliable and transparent real estate valuation support tools can offer substantial advantages to participants in the real estate market, including banks, insurers, pension and sovereign wealth funds, as well public authorities and private individuals.

Enhancing Clinical Education Training with Immersive Reality (XR)

A core element of clinical education is the observed structured clinical examination (OSCE) that simulates real-life clinical practice. These OSCEs can be enhanced through combining the best elements of emerging technologies in the design of enhanced simulation environments to prepare healthcare graduates for changing clinical practice as it integrates new and emerging technologies. New and emerging immersive reality (XR) headsets that allow digital enhancement of practice with real tools and procedures can be combined with haptic feedback such as a high-fidelity manikin within an interactive immersive room that can replicate a wide variety of real-world scenarios at the touch of a button. In this way XR can enhance authentic learning in clinical and first responder practice by enabling exposure to critical elements of clinical simulation in a safe, contextual learning environment that is cost effective and scalable compared to the expense of simulations involving actors and physical real-life sets. In response this concise paper introduces the development of a framework for enhanced simulation practice using the Blended Learning Simulation Suite (BLISS).

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.

Use of Fruit Waste as Natural Dyes in pH-Sensitive Colorimetric Sensors for Tilapia Fillets Quality Decline

Graphical Abstract Highlight Research 1. The use of dragon fruit peel, mangosteen peel and onion peel waste as natural dyes in colorimetric sensors was analyzed in this study. 2. Natural dyes are added to bioplastics with kappa carrageenan polymer, a mixture of corn starch and kappa carrageenan, and corn starch to determine the characteristics of the best bioplastic to be used as a colorimetry sensor. 3. The quality of the fish fillet compared to the color changes in colorimetry sensor was analysed in this study. 4. Mixture of kappa carrageenan and corn starch as bioplastic with casting method was analyzed in this study. Abstract Tilapia fillet aimed to prolonging shelf life, may still experience quality deterioration posing food safety risks. Colorimetric pH indicators offer a simple and affordable solution to the food industry to evaluating fish spoilage. Natural dyes reduce potential health risks associated with synthetic dyes. Anthocyanin sources haven’t been explored like dragon fruit rind, mangosteen rind, and red onion skin serve as real time quality and safety assessment tools for consumers. This study explores the potential of anthocyanin extracted from dragon fruit rind, mangosteen rind, and red onion skin as colorimetric sensors for evaluating the quality and safety of tilapia fillets. The anthocyanin-based sensors developed using kappa carrageenan and corn starch polymers to achieve sustainability fisheries program and were characterized according to the Japanese Industrial Standard for bioplastics. The results show that anthocyanin from dragon fruit skin exhibited the best color change in response to pH changes in the tilapia fillet, indicating its potential as a reliable indicator of spoilage. This research highlights the feasibility of using natural dyes as colorimetric sensors, reducing the risk of health hazards associated with synthetic dyes. This study also shows that different polymers give different characteristic of bioplastic. Carrageenan bioplastic shows best thickness values of 0,118 mm; Carrageenan and corn starch bioplastics shows best tensile strength values of 20,62 MPa; Carrageenan bioplastic shows best elongation values of 254%; and All polymers shows the same biodegradation rate values of 14,29%. Further studies are needed to explore other natural dyes and optimize the polymers for optimal bioplastic characteristics.

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.

PROSPECTS OF ECONOMIC INTEGRATION OF UKRAINE WITHIN THE FRAMEWORK OF THE ASSOCIATION AGREEMENT WITH THE EU

The article examines the prospects of economic integration within the framework of the association agreement with the EU. It is noted that modern studies on the integration of Ukraine into the EU most often consider the problems of the Ukrainian dimension of European and Euro-Atlantic integration, Ukraine's acquisition of the status of a candidate for EU membership in the conditions of the war in Ukraine , the state European integration policy of Ukraine: theory, methodology, mechanisms, reengineering in international business. The main prospects for further economic integration of Ukraine into the EU are offered: strengthen responsibility for corruption schemes in the economy and in the field of intellectual property rights; implement the Tax Policy Strategy, which should take into account all sectoral aspects of the Association Agreement with the EU; strengthen control over public procurement; apply real tools to stimulate energy efficiency and innovative development (tax credit or tax discount), environmentally safe production (emission limits, correction factors, etc.), establish a tax-free minimum income of citizens and apply real control over persons receiving tax benefits. It is justified that the level of innovative activity should be stimulated primarily by tax benefits. It is shown that in foreign countries, the emphasis is primarily on the financing of innovative research by private companies, which allows them to obtain an innovative product, which can then be sold both inside the country and outside its borders. In Ukraine, for the most part, the state is not interested in such processes and does not create certain preferences for persons developing innovative products. It is proposed to introduce an innovative tax credit, which will allow subjects of innovative activity to reduce the tax burden from corporate income tax or postpone its payment. Thanks to this approach, Ukraine can obtain innovative products that will be in demand on the world market.

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>