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The purpose of this paper is to obtain the reasonable dimensioning for each part and a full-dimension model of assembly dimensions.

The relational path graph of assembly dimension, the shortest-path spanning tree of functional dimension and a revised spanning tree are established in this paper.

The proposed method can obtain reasonable dimensioning of parts and establishment of dimension model in an assembly.

The proposed method can easily realise by computer and be more suitable to automatic dimensioning and establishment of dimension model of parts.

This study examines various artificial intelligence (AI) models for predicting financially distressed firms with poor profitability (“Zombie firms”). In particular, we adopt the Explainable AI (“XAI”) approach to overcome the limitations of the previous AI models, which is well-known as the black-box problem, by utilizing the Local Interpretable Model-agnostic Explanations (LIME) and the Shapley Additive Explanations (SHAP). This XAI approach thus enables us to interpret the prediction results of the AI models. This study focuses on the Korean sample from 2019 to 2023, as it is expected that the COVID-19 pandemic increases the number of zombie firms. We find that the XGBoost model based on a boosting technique has the best predictive performance among several AI models, including the traditional ones (e.g. the logistic regression). In addition, by using the XAI approach, we provide visualized interpretations for the prediction results from the XGBoost model. The analysis further reveals that the return on sales and the selling, general and administrative costs are the most impactful variables for predicting zombie firms. Overall, this study focusing on several AI models not only shows the improvement for the prediction of zombie firms (relative to the traditional models) but also increases the reliability of the prediction results by adopting the XAI approach, providing several implications for market participants, such as financial institutions and investors.

There are limited studies addressing how choosing a maintenance strategy can contribute towards maximising outputs from given inputs, thereby minimising costs and improving a company’s competitiveness. The analytic hierarchy constant sum method (AHCSM) is used to access the appropriateness of maintenance strategies for improving the overall efficiency of a structural steel fabrication construction company.

A semi-structured interview was formulated with the stakeholders of the quality department to understand the company’s maintenance portfolio and its current functional capability. The information from this case study was then dissected to represent the factors that the company deemed appropriate for evaluating their maintenance strategy. The AHCSM approach provided a framework, which ranked the importance of factors that are sensitive to the construction industry and rank the suitability of maintenance strategies.

Factors affecting the selection of maintenance strategies to improve business efficiency are productivity, quality, reliability, cost, safety and work environment, morale, inventory and flexibility. Total productive maintenance strategy produces the most desirable outcome; however, the predictive or condition-based maintenance strategy provides an optimum solution for the case study company while considering the equipment usage, frequency of production and the current economic climate.

The approach presented allows practitioners to consider ways to increase the level of production and improve the efficiency of construction businesses without a high increase in investment. The findings can inform gaps in existing maintenance approaches in achieving business objectives.

Reinforced concrete slabs in fire have been heavily studied over the last three decades. However, most experimental and numerical work focuses on long-duration uniform exposure to standard fire. Considerably less effort has been put into investigating the response to localised fires that result in planarly non-uniform temperature distribution in the exposed elements.

In this paper, the OpenSees for Fire framework for modelling slabs under non-uniform fire exposure is presented, verified against numerical predictions by Abaqus and then validated against experimental tests. The thermal wrapper developed within OpenSees for Fire is then utilised to apply localised fire exposure to the validated slab models using the parameters of an experimentally observed localised fire. The effect of the smoke layer is also considered in this model and shown to significantly contribute to the thermal and thus thermo-mechanical response of slabs. Finally, the effect of localised fire heat release rate (HRR) and boundary conditions are studied.

The analysis showed that boundary conditions are very important for the response of slabs subject to localised fire, and expansive strains may be accommodated as deflections without severely damaging the slab by considering the lateral restraint.

This work demonstrates the capabilities of OpenSees for Fire in modelling structural behaviours subjected to non-uniform fire conditions and investigates the damage pattens of flat slabs exposed to localised fires. It is an advancing step towards understanding structural responses to realistic fires.

The purpose of this paper is to obtain a theoretical model to analyze the effective modulus of cement paste in early age, including the setting and hardening periods, which has a great impact on mechanical properties of concrete structure.

Based on a power law approximation, a generalized mixture rule is used to construct the relationship between the effective modulus and hydration degree. In addition, a new model of the dependence of the Poisson's ratio on the hydration degree and water cement ratio is proposed for cement paste in early age.

The effective Young's modulus, storage shear modulus and Poisson's ratio of cement pastes with different water cement ratios and hydration degrees are studied by the presented model. The model can be applied to simulate the behavior of early-age cement paste at both the setting and the hardening periods. Compared with the experimental results, the correctness of the model is validated.

This work presents a mathematical model that can effectively estimate the effective Young's modulus and Poisson's ratio in the hardening period, and the storage shear modulus in the setting period of cement pastes.

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

This paper provides a summary of the issues in the passive fire protection of steel structures. Types of passive fire protection and the material properties of protection members and steel members are described. The paper deals with the possibility of partial fire protection for secondary steel beams, in cases where, due to possible membrane action, it is not necessary to apply passive protection to the entire beams.

Studies of partially fire-protected steel structures are compared, and results from studies with different input data are summarized. A fire experiment was conducted to investigate the effect of partial passive protection in a small-scale furnace. Based on the findings of the experiment, numerical models were prepared using Ansys Mechanical.

The results are summarized, and a partial fire protection length of 500 mm is recommended. Various partial fire protection lengths were compared, and the temperature development of the steel contactors was compared using a protection length of 500 mm. At the end of the paper, options for partial passive protection of steel beams are presented.

Extended paper from ASFE2021 based on selection.

International trade transactions, extracted from customs declarations, include several fields, among which the product description and the product category are the most important. The product category, also referred to as the Harmonised System Code (HS code), serves as a pivotal component for determining tax rates and administrative purposes. A predictive tool designed for product categories or HS codes becomes an important resource aiding traders in their decision to choose a suitable code. This tool is instrumental in preventing misclassification arising from the ambiguities present in product nomenclature, thus mitigating the challenges associated with code interpretation. Moreover, deploying this tool would streamline the validation process for government officers dealing with extensive transactions, optimising their workload and enhancing tax revenue collection within this domain.

This study introduces a methodology focused on the generation of sentence embeddings for trade transactions, employing Sentence BERT (SBERT) framework in conjunction with the Multiple Negative Ranking (MNR) Loss function following a contrastive learning paradigm. The procedure involves the construction of pairwise samples, including anchors and positive transactions. The proposed method is evaluated using two publicly available real-world datasets, specifically the India Import 2016 and United States Import 2018 datasets, to fine-tune the SBERT model. Several configurations involving pooling strategies, loss functions, and training parameters are explored within the experimental setup. The acquired representations serve as inputs for traditional machine learning algorithms employed in predicting the product categories within trade transactions.

Encoding trade transactions utilising SBERT with MNR loss facilitates the creation of enhanced embeddings that exhibit improved representational capacity. These fixed-length embeddings serve as adaptable inputs for training machine learning models, including support vector machine (SVM) and random forest, intended for downstream tasks of HS code classification. Empirical evidence supports the superior performance of our proposed approach compared to fine-tuning transformer-based models in the domain of trade transaction classification.

Our approach generates more representative sentence embeddings by creating the network architectures from scratch with the SBERT framework. Instead of exploiting a data augmentation method generally used in contrastive learning for measuring the similarity between the samples, we arranged positive samples following a supervised paradigm and determined loss through distance learning metrics. This process involves continuous updating of the Siamese or bi-encoder network to produce embeddings derived from commodity transactions. This strategy aims to ensure that similar concepts of transactions within the same class converge closer within the feature embedding space, thereby improving the performance of downstream tasks.

The institution of food and cookery exhibitions and the dissemination of practical knowledge with respect to cookery by means of lectures and demonstrations are excellent things in their way. But while it is important that better and more scientific attention should be generally given to the preparation of food for the table, it must be admitted to be at least equally important to insure that the food before it comes into the hands of the expert cook shall be free from adulteration, and as far as possible from impurity,—that it should be, in fact, of the quality expected. Protection up to a certain point and in certain directions is afforded to the consumer by penal enactments, and hitherto the general public have been disposed to believe that those enactments are in their nature and in their application such as to guarantee a fairly general supply of articles of tolerable quality. The adulteration laws, however, while absolutely necessary for the purpose of holding many forms of fraud in check, and particularly for keeping them within certain bounds, cannot afford any guarantees of superior, or even of good, quality. Except in rare instances, even those who control the supply of articles of food to large public and private establishments fail to take steps to assure themselves that the nature and quality of the goods supplied to them are what they are represented to be. The sophisticator and adulterator are always with us. The temptations to undersell and to misrepresent seem to be so strong that firms and individuals from whom far better things might reasonably be expected fall away from the right path with deplorable facility, and seek to save themselves, should they by chance be brought to book, by forms of quibbling and wriggling which are in themselves sufficient to show the moral rottenness which can be brought about by an insatiable lust for gain. There is, unfortunately, cheating to be met with at every turn, and it behoves at least those who control the purchase and the cooking of food on the large scale to do what they can to insure the supply to them of articles which have not been tampered with, and which are in all respects of proper quality, both by insisting on being furnished with sufficiently authoritative guarantees by the vendors, and by themselves causing the application of reasonably frequent scientific checks upon the quality of the goods.

Alec Snobel samples service with its roots in ancient history