The front‐line manager is the person responsible for getting the job done. He is the one for whom changes in organisation, systems, and management style will present the greatest…
Abstract
The front‐line manager is the person responsible for getting the job done. He is the one for whom changes in organisation, systems, and management style will present the greatest challenge. Apart from those new skills which changes in social attitudes clearly demand, the impact of new legislation will generate a considerable additional training task among a group whose training in recent years has, by many accounts, suffered varying degrees of neglect.
Argues that the gold standard is the only monetary regime consistent with the philosophy of free enterprise and assesses the contributions of Friedman, Mundell and Hayek to…
Abstract
Argues that the gold standard is the only monetary regime consistent with the philosophy of free enterprise and assesses the contributions of Friedman, Mundell and Hayek to monetary theory as supporters of the free market but opponents of the gold standard. Critically reviews the basic ideas of each and notes that Greenspan, while apparently endorsing the gold standard, has not actually used his position as chairman of the US Federal Reserve System to move towards it. Lists some economists who support both free enterprise and the gold standard as a “vital aspect of political economy”.
Details
Keywords
Karlo Puh and Marina Bagić Babac
Predicting the stock market's prices has always been an interesting topic since its closely related to making money. Recently, the advances in natural language processing (NLP…
Abstract
Purpose
Predicting the stock market's prices has always been an interesting topic since its closely related to making money. Recently, the advances in natural language processing (NLP) have opened new perspectives for solving this task. The purpose of this paper is to show a state-of-the-art natural language approach to using language in predicting the stock market.
Design/methodology/approach
In this paper, the conventional statistical models for time-series prediction are implemented as a benchmark. Then, for methodological comparison, various state-of-the-art natural language models ranging from the baseline convolutional and recurrent neural network models to the most advanced transformer-based models are developed, implemented and tested.
Findings
Experimental results show that there is a correlation between the textual information in the news headlines and stock price prediction. The model based on the GRU (gated recurrent unit) cell with one linear layer, which takes pairs of the historical prices and the sentiment score calculated using transformer-based models, achieved the best result.
Originality/value
This study provides an insight into how to use NLP to improve stock price prediction and shows that there is a correlation between news headlines and stock price prediction.
Details
Keywords
Abdul-Manan Sadick, Argaw Gurmu and Chathuri Gunarathna
Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is…
Abstract
Purpose
Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.
Design/methodology/approach
Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).
Findings
This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.
Research limitations/implications
The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.
Originality/value
This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.
Details
Keywords
The previous article appeared in our September issue and we repeat that Bert and Fred, and their ‘management’ have too many very close relatives in far too many works. As our…
Abstract
The previous article appeared in our September issue and we repeat that Bert and Fred, and their ‘management’ have too many very close relatives in far too many works. As our author states, ‘they’ should be told frankly how a small expenditure on modern equipment for storing and handling oils and greases would save them a lot of money.
George T. Duncan and Allen R. Solem
This simulation consists of a series of exercises in which participants select moves that minimize their penalties in a delivery system (TARTAN) game. It emphasizes multiple‐actor…
Abstract
This simulation consists of a series of exercises in which participants select moves that minimize their penalties in a delivery system (TARTAN) game. It emphasizes multiple‐actor decision making, which shows how negotiation can lead to cooperative solutions with material benefit. It makes use of calculus, and optimization techniques of dynamic programming. In addition, it gives participants practice both with and without a mediator.
S. Marie Moghadasi, Albert J. de Wit and Fabio Chiacchio
The purpose of this paper is to determine thermal behaviour of wing fuel tank wall via heating by external heat sources.
Abstract
Purpose
The purpose of this paper is to determine thermal behaviour of wing fuel tank wall via heating by external heat sources.
Design/methodology/approach
A 3D finite element model of the structure has been created that takes into account convection, conduction and radiation effects. In addition, a 3D finite volume model of the air inside the leading edge is created. Through a computational fluid dynamics approach, the flow of air and thermal behaviour of the air is modelled. The structure and fluid model are coupled via a co-simulation engine to exchange heat flux and temperature. Different ventilation cases of the leading edge and their impact on the thermal behaviour of the tank wall (corresponding to the front spar) are investigated.
Findings
Results of 3D analysis illustrate good insight into the thermal behaviour of the tank wall. Furthermore, if regions exist in the leading edge that differs significantly from the overall thermal picture of the leading edge, these are visible in a 3D analysis. Finally, the models can be used to support a flammability analysis assessment.
Practical implications
Provided that the bleed pipe is located far enough from the spar and covered with sufficient thermal heat isolation, the composite leading edge structure will not reach extremely high temperatures.
Originality/value
These detailed simulations provide accurate results which can be used as reliable input for the fuel tank flammability analysis.
Details
Keywords
Patrick Arthur and Samuel Koomson
There is evidence of country-level contextual variations regarding the benefits of practical experience acquired by students during higher education. This paper, therefore…
Abstract
Purpose
There is evidence of country-level contextual variations regarding the benefits of practical experience acquired by students during higher education. This paper, therefore, analyses the benefits of student internships in the Ghanaian context.
Design/methodology/approach
In Study 1, two structured but distinct surveys were distributed to senior members and students of six specialised technical education institutions (TIs). Study 2 involved in-depth interviews with the heads of organisations in the tertiary education sector, including trade groups, industries and government agencies.
Findings
Internship provides soft skills, confidence, career development, sense of responsibility, employability, income, knowledge sharing and networking for students/interns. For TIs, it contributes to the professional development of faculty supervisors and helps them to update the content they teach. For employers, it unveils talented and promising students who can be employed immediately after graduation at a relatively cheaper cost.
Research limitations/implications
There is still the need for additional research in different contexts: both developed and developing economies to clear doubts on the controversies surrounding the relevance of internship in the 21st century.
Practical implications
TIs should continue to champion student internship programmes. This study highlights the need for employers to place internship students in areas that relate to their fields of study. It also underscores the need for students to embrace internship since it is the cornerstone to their employability in the labour market.
Social implications
Undeniably, student internships provide a critical platform for career beginners.
Originality/value
This paper contributes to knowledge by offering contextual literature in Ghana on the benefits of student internship programme for interns/students, TIs and employers, all together.
Details
Keywords
Na Xu, Yanxiang Liang, Chaoran Guo, Bo Meng, Xueqing Zhou, Yuting Hu and Bo Zhang
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a…
Abstract
Purpose
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.
Design/methodology/approach
Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.
Findings
Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.
Originality/value
This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.
Details
Keywords
Jun-Hui Chai, Jun-Ping Zhong, Bo Xu, Zi-Jian Zhang, Zhengxiang Shen, Xiao-Long Zhang and Jian-Min Shen
The high-pressure accumulator has been widely used in the hydraulic system. Failure pressure prediction is crucial for the safe design and integrity assessment of the…
Abstract
Purpose
The high-pressure accumulator has been widely used in the hydraulic system. Failure pressure prediction is crucial for the safe design and integrity assessment of the accumulators. The purpose of this study is to accurately predict the burst pressure and location for the accumulator shells due to internal pressure.
Design/methodology/approach
This study concentrates the non-linear finite element simulation procedure, which allows determination of the burst pressure and crack location using extensive plastic straining criterion. Meanwhile, the full-scale hydraulic burst test and the analytical solution are conducted for comparative analysis.
Findings
A good agreement between predicted and measured the burst pressure that was obtained, and the predicted failure point coincided very well with the fracture location of the actual shell very well. Meanwhile, the burst pressure of the shells increases with wall thickness, independent of the length. It can be said that the non-linear finite element method can be employed to predict the failure behavior of a cylindrical shell with sufficient accuracy.
Originality/value
This paper can provide a designer with additional insight into how the pressurized hollow cylinder might fail, and the failure pressure has been predicted accurately with a minimum error below 1%, comparing the numerical results with experimental data.