Total Solution Research Articles

Generalized Entropy and Solution Information for Measuring Puzzle Difficulty

Metrics for problem difficulty are used by many puzzle generation algorithms, as well as by adaptive algorithms that want to provide players with the puzzles at the correct level of difficulty. A recently proposed general metric, puzzle entropy, combines an analysis of game mechanics with a model of player knowledge in the form of inference rules to predict problem difficulty. The entropy of a puzzle is the amount of information required, given a player’s knowledge about the puzzle, to describe a solution to a puzzle. This paper generalizes the concepts of puzzle entropy and solution information, providing a better foundation for the previous work and creating new algorithms, Minimum Solution Information and Total Solution Information. While functionally very similar to past work, the new algorithm allows knowledge about a puzzle to be represented as a policy, something that can be learned more easily. We then evaluate the impact of policies, inference rules, and player knowledge in the 2016 game, The Witness.

Modeling of reflected ultrasonic fields in composed samples

Ultrasonic nondestructive testing involves the study of propagation, reflection and refraction patterns of elastic waves excited by contact or non-contact piezoelectric transducers in the inspected object. The finite element modeling usually requires high computational costs and additional postprocessing to select individual waves from the total solution. When probing joints of homogeneous materials, such as turbine blades made of heat-resistant monocrystalline alloys, the joint boundary is low-contrast, and the reflected signals are relatively weak. This causes additional difficulties for their separation from the total wave field and correct interpretation of the information they bring. To solve this problem, explicit asymptotic representations for reflected and transmitted waves in a two-layer elastic half-space with a surface source are proposed in the present work, which allow fast parametric analysis. They can be used to analyze ultrasonic probing data, for example, to estimate the state of the junction zone or to determine the mutual orientation of the crystals’ principal axes.

Energy and Water Interventions That Contribute to the Climate-Proofing of Buildings on Multiple Scales: A Literature Review

In the framework of planning and designing resilient housing under a changing climate, the present study constitutes a comprehensive literature review exploring climate-proofing solutions for the built environment concerning energy supply and water availability. This study delved into a multitude of sources that included scientific papers and reports and European Union guidelines and tools. The identified solutions covered building, urban, and territorial scales. The hazards of interest included heatwaves, heavy precipitation, droughts, earthquakes, wildfires, and storms. Several types of solutions were found (e.g., nature-based, education/capacity-building, engineering/built environment, etc.) with different times of application and timescales of action (e.g., defensive measures, short-term solutions, long-term adaptive, etc.). The maturity of the identified solutions was assessed based on the Technology Readiness Level (TRL) and Societal Readiness Level (SRL). Moreover, each solution’s contribution to climate mitigation was investigated. The solutions were assessed in terms of self-sustainability and other key criteria, namely, effectiveness, contribution to resilience maturity and climate change mitigation, adaptive nature, financing access, risk reduction, and social cohesion. In total, 85 energy and water solutions were determined from the desk review analysis and 67 (30 for the energy sector and 37 for the water sector) solutions were finally retained and proposed.

Master curves for unidirectional flows of FENE-P fluids in rectilinear and curvilinear geometries

We demonstrate that velocity profiles for steady, unidirectional shear flows of the FENE-P (Finitely-Extensible Nonlinear Elastic, with Peterlin closure) fluid, undergoing canonical rectilinear (pressure-driven flow in a rectangular channel or a circular pipe) or curvilinear (in Taylor–Couette or Dean configurations) flows, obey universal master curves that are a function only of the ratio Wi/L , for a fixed solvent to solution viscosity parameter β. Here, Wi is the Weissenberg number defined as the product of the dumbbell relaxation time and an appropriate shear rate, while L is the ratio of the maximum extension of the polymer to its equilibrium root-mean-square end-to-end distance. The data collapse and the resulting master curves for the velocity profile is a generalization of the recent demonstration of master curves for polymer viscosity and first normal stress coefficient for a FENE-P fluid under steady simple shear flow (Yamani and McKinley, 2023). For pressure-driven channel and pipe flows, we derive simple analytical expressions for the velocity profiles, in the high shear-rate regime of Wi/L≫1, that readily elucidate the role of finite extensibility of the polymer on the velocity profiles. In the Wi/L≫1 regime, for all the flows considered, the limit of zero solvent (β=0) is shown to be singular, owing to the absence of a high-shear plateau in the total solution viscosity, resulting in very different velocity profiles for β=0 and β→0.

A-195 Combination of Lean Mindset, Robotics and Digitalization allowed us to manage a 2.5 times increase in workload in our central reference lab

Abstract Background Our Agilus Diagnostics, Gurugram, India is a Central Reference Laboratory and part of the pan-India network over 400 lab in India. Our Gurugram lab delivers 3,200 tubes in the serum work area in 17 hour operations daily and is ISO 15189 and CAP accredited.In Jan 2023, our lab started to support Govt PHC Program samples and our workload increased to 8000 tubes. This was a clear operational and clinical challenge for us with a 2.5 x jump in workload. To achieve this goal, a lean mindset with process improvement steps were to be applied required across the total testing process. This lean approach was supported by cobas ® Lab Automation systems managed by navify ® Lab Operations informatics automation solution. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency when faced with this challenge. Methods We took 4 major steps We redesigned lab processes using lean process improvement operational dashboards. This poster will show the metric we track which help eliminate waste in the system. We optimized our total lab automation solution with smart load balancing across cobas ® Pro integrated analyzers and staff friendly recursive workflow. Clear and strict use of off peak hours for maintenance and QC procedures and standardized predictable schedule of operation. This poster will share our time table with key milestones across the 24 hours We built on the Informatics solution using 5 layered Auto verification rules based decision framework. IQC, Systems Flags check, Sample Quality checks, Biological Reference check, custom Auto verification Range, Critical ranges Delta check Criteria, Clinical Correlation Rule are all part of the auto verification logic framework. Results We were able to deliver the following results.Lean process design led to 53% simplification. Number of process steps reduced to 29 from 62 steps across the total testing process. Total Lab Automation has helped improve 90 percentile production TAT by 46% from 250 mins to 135 mins Our 90 % TAT CV has significantly reduced making our production predictable. Over 17,500 results / day reported are subject to auto verification with 87 % of all results auto-verified and auto-approved. Not a single additional employee was added in the analytical or post analytical areas of the lab operations Conclusions Lean Mindset complemented by Total Laboratory Automation along with Decision Automation on an Informatics solution has enhanced lab performance in terms of TAT, Efficiency, and Staff Motivation. This poster will also demonstrate using incremental effectiveness analysis comparative data of key performance indicators, such predictability in production, and efficiency of workforce, senior staff time saved, before and after technology deployment. The challenge of increase in sample workload is real in India and this approach allows for a sustainable way to ensure patient impact with minimum burden on our workforce.

Analytical solution of seismic power-based equation of motion

This research proposes an innovative power-based equation of motion (PBEM) for the single degree of freedom (SDOF) system considering seismic excitation. The external or input frequency function, solution of time, relation between external and kinetic powers, and equation of strain-power (SP) are obtained by solving the power balance equation (PBE). The external frequency function is related to both the particular and total solutions of the PBEM. The particular solution of PBEM is applied on the shake table test of the tunnel-soil-pile interaction (TSPI) model, real-scale test of 2-storied reinforced concrete frame structure, and case study of Bolu tunnel for the verification purpose. The differences in verification (PBEM and previous works) results are found to be 21.6 % for the real-scale test and 19.5 % for the case study. These differences may represent a reasonable agreement with verification. Also, the relationship between the kinetic and external powers is verified with the previous shake table test of steel cantilever column, whereas the difference in results is found to be 5 %. Finally, a design chart is proposed for predicting the input frequency function for various frequency ratios and damping.

E-Waste Management in Nam Theun 2 Power Company Limited: A Review of Issues, Challenges and Solutions

This paper reviews the e-waste management practices of Nam Theun 2 Power Company (NTPC), one of the leading power generation companies in Laos. The study focuses on the company's use of Total Environmental Solutions – Asset Material Management (TES-AMM), a leading e-waste recycling company, to manage their e-waste. In this paper, a mixed-methods research design has been applied, including a survey of employees and interviews with key stakeholders at NTPC, as well as document analysis to assess the company's compliance with the relevant regulations and standards. The results of the study indicate that NTPC has an effective e-waste management system in place that is compliant with the relevant regulations and standards, but it also highlights opportunities for improvement. The study also provides an overview of TES-AMM's e-waste recycling process, which is found to be in line with international standards. The study contributes to the existing literature by providing insights into the specific challenges and opportunities for improving e-waste management in the power generation industry part in Laos.

E-Library: A Total solution for Library Automation & Management Software for College Libraries in Rajasthan

E-Library: A Total solution for Library Automation & Management Software for College Libraries in Rajasthan

Efficient separation of HEPES and CO2-derived fructose by nanofiltration: Optimizing pH for improved separation and proposing a potential mechanism

Utilization of an in vitro multi-enzyme catalytic system for the synthesis of fructose from carbon dioxide is a promising approach towards achieving carbon neutrality. However, the lack of effective separation methods for the buffer HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) and the product fructose within the system has hindered the industrialization of in vitro multi-enzyme catalytic synthesis systems. This study aimed to separate and recover HEPES and fructose using nanofiltration technology. We investigated the influence of various parameters, including total solution concentration, solute concentration ratio, pH, and temperature, on the nanofiltration separation performance. Experimental results revealed that increasing the pH to 9.0 significantly decreased the fructose retention rate while maintaining a nearly complete HEPES retention rate. The HEPES-fructose mixed solution was further subjected to diafiltration using a spiral-wound membrane, ultimately yielding fructose and HEPES solutions with purities of 90.22 % and 92.93 %, respectively. Combining separation test results with models such as DSPM-DE, and using characterization methods such as ATR-FTIR and pore size distribution analysis, we observed pore swelling during nanofiltration of the HEPES-fructose solution at pH 9.0. A mechanism for this pore swelling, induced by the dissociation of HEPES under the influence of pH, was proposed: Dissociated HEPES in the solution interacts with the membrane surface at the liquid-membrane interface, causing reversible swelling of the membrane pores at the membrane surface, thereby reducing the retention rate of fructose. The nanofiltration process developed in this study effectively separates HEPES and fructose, enabling resource recycling and cost reduction. Furthermore, this study provides theoretical foundations and practical guidance for the design of nanofiltration separation strategies for similar systems using HEPES as a buffer, holding significant scientific and practical value.

Local Modeling by Adapting Source Calibration Models to Analyte Shifted Target Domain Samples Without Reference Values.

Spectral multivariate calibration aims to derive models characterizing mathematical relationships between sample analyte amounts and corresponding spectral responses. These models are effective at predicting target domain sample analyte amounts when target samples are within the analyte and spectral calibration source domain. Models fail when target samples shift (analyte amounts and/or spectra) from the original calibration domain model. A total recalibration solution requires acquisition of new sample reference values and spectra. However, obtaining enough reference values to distinguish the target domain may be challenging or expensive. A simpler approach adapts the original model to the target domain using target sample spectra without analyte reference values (unlabeled). Analytical chemists have developed several machine learning algorithms using unlabeled regression domain adaptation processes. Unfortunately, prediction accuracy declines for these methods depending on how much the target domain analyte distribution has shifted from the calibration distribution, and regression transfer learning methods are instead needed. Regression domain adaptation and transfer learning are often referred to as model updating in analytical chemistry, but regression domain adaptation only applies to spectral shifts. The regression transfer learning method presented in this paper named null augmentation regression constant analyte (NARCA) leverages unlabeled repeat spectra of a single target sample to update an original calibration model to the shifted target domain sample. With sample repeat spectra, the analyte amount can be assumed constant or nearly constant for NARCA and because models are formed for one sample, NARCA operates as a local modeling method. The performance of NARCA as a regression transfer learning method is evaluated using five near-infrared data sets.

Does the Addition of Low-Dose Antibiotics Compromise the Mechanical Properties of Polymethylmethacrylate (PMMA)?

The increasing numbers of total joint replacements and related implant-associated infections demand solutions, which can provide a high-dose local delivery of antibiotics. Antibiotic-loaded bone cement (ALBC) is an accepted treatment method for infected joint arthroplasties. The mechanical properties of low-dose gentamicin-loaded bone cement (BC) in medium- and high-viscosity versions were compared to unloaded BC using a vacuum mixing system. As an additional control group, manual mixed unloaded BC was used. In a uniaxial compression test, ultimate compressive strength, compressive yield strength, and compression modulus of elasticity, as well as ultimate and yield strain, were determined according to ISO 5833-2022 guidelines. All groups exceeded the minimum compressive strength (70 MPa) specified in the ISO 5833 guidelines. Both ALBC groups showed a similar ultimate compressive and yield strength to the unloaded BC. The results showed that vacuum mixing increased the compression strength of BC. ALBC showed similar compressive strength to their non-antibiotic counterparts when vacuum mixing was performed. Added low-dose gentamicin acted as a plasticizer on bone cement. From a biomechanical point of view, the usage of gentamicin-based ALBC formulations is viable.

High-order total differential solution of multivariate function based on Yang Hui triangle

High-order total differential solution of multivariate function based on Yang Hui triangle

Investigation of the Complexation Activity of 2,4-Dithiouracil with Au(III) and Cu(II) and Biological Activity of the Newly Formed Complexes

The goal of this study is to synthesize, determine the structure, and examine the antimicrobial properties of novel Cu(II) and Au(III) complexes of 2,4-dithiouracil and its derivatives. These complexes were obtained by mixing aqueous solutions of the corresponding metal salts with the ligand dissolved in DMSO and aqueous NaOH, using a metal-to-ligand ratio of 1:4:2. The structures of the new compounds were analyzed by melting point determination, microwave plasma atomic emission spectrometry (MP-AES) for Cu and Au, inductively coupled plasma optical emission spectrometry (ICP-OES) for S, attenuated total reflection (ATR), solution and solid-state NMR, and Raman spectroscopy. The data for 2,4-dithiouracil obtained from the 1H NMR, 13C NMR, distortionless enhancement by polarization transfer spectrum (DEPT-135), proton–proton homonuclear correlation spectrum (1H-1H COSY), long-range 1H-13C heteronuclear multiple bond correlation experiment (HMBC), and heteronuclear single quantum coherence spectra (HSQC) aided the interpretation of the NMR data for the gold and copper complexes. Furthermore, the antimicrobial effect of the free ligands and their complexes was assessed against Gram-positive and Gram-negative bacteria, as well as yeasts.

Monitoring the lactation-related behaviors of sows and their piglets in farrowing crates using deep learning

Pig farming is a major sector of livestock production. The preweaning stage is a critical period in the pig farming process, where lactation-related behaviors between sows and their piglets directly influence the preweaning survivability of the piglets. Lactation-related behaviors are mutual interactions that require the combined monitoring of both the sow and her piglets. Conventional naked-eye observation is discontinuous and labor-intensive and may result in undetected abnormal behavior and economic losses. Thus, this study proposed to monitor the lactation-related behaviors of sows and their piglets simultaneously and continuously using computer vision. Videos were recorded from farrowing crates using embedded systems equipped with regular RGB cameras. The sow posture recognition model (SPRM), comprising a convolutional neural network (CNN) of the architecture EfficientNet and a long short-term memory network, was trained to identify seven postures of sows. The piglet localization and tracking model (PLTM), comprising a CNN of the architecture YOLOv7 and a simple online and realtime tracking algorithm, was trained to localize and track piglets in the farrowing crate. The sow posture information was then combined with the piglet activity to detect unfed piglets. The trained SPRM and PLTM reached an accuracy of 91.36% and a multiple object tracking accuracy of 94.6%. The performance of the proposed unfed piglet detection achieved a precision of 98.4% and a recall of 90.7%. A long-term experiment was conducted to monitor lactation-related behaviors of sows and their piglets from the birth of the piglets to day 15. The overall mean daily percentages ± standard deviations (SDs) of sow postures were 6.8% ± 2.9% for feeding, 8.8% ± 6.6% for standing, 11.8% ± 4.5% for sitting, 20.6% ± 16.3% for recumbency, 14.1% ± 6.5% for lying, and 38.1% ± 7.5% for lactating. The overall mean daily percentages ± SDs of piglet activities were 38.1% ± 7.5% for suckling, 22.2% ± 5.4% for active, and 39.7% ± 10.5% for rest. The proposed approach provides a total solution for the automatic monitoring of sows and their piglets in the farrowing house. This automatic detection of abnormal lactation-related behaviors can help in preventing piglet preweaning mortality and therefore aid pig farming efficiency.

Strong consistency of an estimator by the truncated singular value decomposition for an errors-in-variables regression model with collinearity

In this paper, we prove strong consistency of an estimator by the truncated singular value decomposition for a multivariate errors-in-variables linear regression model with collinearity. This result is an extension of Gleser's proof of the strong consistency of total least squares solutions to the case with modern rank constraints. While the usual discussion of consistency in the absence of solution uniqueness deals with the minimal norm solution, the contribution of this study is to develop a theory that shows the strong consistency of a set of solutions. The proof is based on properties of orthogonal projections, specifically properties of the Rayleigh-Ritz procedure for computing eigenvalues. This makes it suitable for targeting problems where some row vectors of the matrices do not contain noise. Therefore, this paper gives a proof for the regression model with the above condition on the row vectors, resulting in a natural generalization of the strong consistency for the standard TLS estimator.

An explicit primitive conservative solver for the Euler equations with arbitrary equation of state

This work presents a procedure to solve the Euler equations by explicitly updating, in a conservative manner, a generic thermodynamic variable such as temperature, pressure or entropy instead of the total energy. The presented procedure is valid for any equation of state and spatial discretization. When using complex equations of state such as Span–Wagner, choosing the temperature as the generic thermodynamic variable yields great reductions in the computational costs associated to thermodynamic evaluations. Results computed with a state of the art thermodynamic model are presented, and computational times are analyzed. Particular attention is dedicated to the conservation of total energy, the propagation speed of shock waves and jump conditions. The procedure is thoroughly tested using the Span–Wagner equation of state through the CoolProp thermodynamic library and the Van der Waals equation of state, both in the ideal and non-ideal compressible fluid-dynamics regimes, by comparing it to the standard total energy update and analytical solutions where available.

P‐105: Micro LED Total Repair Solutions for Display Application: EHD Printing, 1‐by‐1 Transfer, and Functional Nano‐ink material

In recent years, micro‐LED technology has become crucial for high‐definition AR/VR displays and large TVs. ENJET addresses production challenges with a specialized bonder machine, employing EHD Printing, 1‐by‐1 transfer for precise, defect‐free micro‐LED production.This work demonstrated dispensing up to 7 µm conductive bond dots via EHD inkjet printing, achieving a placement precision of 1.5 µm in both x and y directions.

Relationship between the Significant Solutions of Static Traffic Assignment Problems for Mixed Traffic Flow of Connected and Automated Vehicles and Human-Driven Vehicles

Connected and automated vehicles can reduce the traffic congestion level of the entire network through platoon-driving technologies compared to human-driven vehicles. One promising approach to enhancing platoon-driving technology’s efficiency is deploying dedicated lanes or roads for connected and automated vehicles. Since asymmetric interactions between different vehicle types increase road congestion, it is necessary to distinguish routes for efficient traffic management. However, the traditional traffic assignment problem, which uses only user equilibrium as a constraint with no difference in travel time between users, could not be proposed as a globally optimal solution because it generates an infinite number of locally optimal solutions. Recent studies have attempted to overcome the limitations by considering the sum of system-wide travel times as an additional constraint. Their research sought to help propose optimal deployment strategies through the lowest total travel time solution (best-case) or design robust transport planning strategies through the highest total travel time solution (worst-case). However, past studies have not focused on the possibility of the best/worst case appearing in reality. This study focused on the relationship between the two solutions pointed out in past studies and traffic patterns likely to appear in reality. This study interprets the Karush–Kun–Tucker condition of the static traffic assignment problem, considering the asymmetric interaction, and proposes a solution algorithm using discrete dynamics. The proposed algorithm extends the most widely used method in transportation planning research, which can overcome the limitations of asymmetric interaction problems through simple variations. The proposed algorithm can reliably derive two solutions, and entropy theory shows that both solutions are unlikely to appear in reality without additional policies such as dedicated lanes or roads.

خوارزمية فصيلة ميركات المعدلة لتعدين القواعد الرابطة

تشكل قواعد جمعيات التعدين (ARM) إحدى تقنيات التنقيب عن البيانات المهمة. أصبحت الأساليب الكلاسيكية التي عمل عليها الباحثون سابقًا غير فعالة للتعامل مع النمو المطرد لقواعد البيانات ، مما دفعنا إلى استخدام عملية التعدين لقواعد الارتباط القائمة على ميتاهيورستك، وفي عملنا سنستخرج جميع القواعد الصحيحة ، و التعدين لا يقتصر على القواعد عالية الجودة. ذكاء السرب يعتبر إحدى هذه الأساليب المعتمدة. في هذه الورقة، تم اقتراح تعديل فصيلة ميركات لتعدين قواعد الجمعية (MCC-ARM). تعتمد الخوارزمية المقترحة بشكل أساسي على خوارزمية فصيلة ميركات (MCA). أكبر فائدة هي تنوع الحلول المرشحة في MCA. سنقوم في عملنا بتمثيل القاعدة باستخدام طريقتين مستعارتين من الخوارزمية الجينية، في المجموعة الأولى، تشير كل مجموعة من القواعد إلى كائن في المجتمع و التي تدعى طريقة بيتسبرغ، بينما تشير القاعدة الثانية إلى كائن في المجتمع و التي تدعى طريقة ميشيغان. تهدف الخوارزمية المقترحة إلى فحص أكبر عدد ممكن من قواعد الارتباط الصحيحة. ما يسمى بخوارزمية تتبع نهج تحديد منطقة البحث الفعالة، والتي تعتمد على آلية عشوائية رئيسية لقيادة الخوارزمية في استخراج القواعد البديلة وتجنب الحلول الكلية من الاسترشاد بنفس القاعدة، وهذا أدى إلى قدر كبير من التنوع. بالإضافة إلى ذلك، يستخدم MCC-ARM طريقة التكثيف في عملية البحث المتجاورة لمنع الخوارزمية من الوقوع في الوضع المحلي. لإثبات كفاءتها، سنطبقها في أربع مجموعات بيانات موثوقة (مثل حديقة الحيوان، والائتمان الألماني، والورم الأساسي والشطرنج). لقد حصل التحسين الذي أحدثته الخوارزمية المقترحة على عاملين حاسمين ، وهما عدد القواعد الصحيحة وقيمة لياقة الجودة.

Produkt-Service-Systeme im Maschinen- und Anlagenbau

Abstract Mechanical and plant engineering companies that have been focused primarily on product manufacturing in the past are recognizing the potential of a service-oriented business approach as they transform from technology providers to total solution providers. The increasing demand for holistic solutions is driving the development of product-service systems. This article closes a knowledge gap by developing a process model that enables the standardization and transferability of machine-specific product-service systems to entire machine portfolios.