Analyzing Textual Data for Fatality Classification in Afghanistan's Armed Conflicts: A BERT Approach

Afghanistan has witnessed many armed conflicts throughout history, especially in the past 20 years; these events have had a significant impact on human lives, including military and civilians, with potential fatalities. In this research, we aim to leverage state-of-the-art machine learning techniques to classify the outcomes of Afghanistan armed conflicts to either fatal or non-fatal based on their textual descriptions provided by the Armed Conflict Location & Event Data Project (ACLED) dataset. The dataset contains comprehensive descriptions of armed conflicts in Afghanistan that took place from August 2021 to March 2023. The proposed approach leverages the power of BERT (Bidirectional Encoder Representations from Transformers), a cutting-edge language representation model in natural language processing. The classifier utilizes the raw textual description of an event to estimate the likelihood of the event resulting in a fatality. The model achieved impressive performance on the test set with an accuracy of 98.8%, recall of 98.05%, precision of 99.6%, and an F1 score of 98.82%. These results highlight the model's robustness and indicate its potential impact in various areas such as resource allocation, policymaking, and humanitarian aid efforts in Afghanistan. The model indicates a machine learning-based text classification approach using the ACLED dataset to accurately classify fatality in Afghanistan armed conflicts, achieving robust performance with the BERT model and paving the way for future endeavors in predicting event severity in Afghanistan.Comment: 6 pages, 4 figures, 2 table

Construction waste in India: a structural equation model for identification of causes

Construction industries are bulk generators of waste globally; improper management leads to environmental catastrophes. This paper identifies the significant factors through exploratory factor analysis and presents a novel approach to determining the causal relationships of various factors that lead to waste generation at construction sites by structural equation modelling. The analysis identifies maintaining and managing a site waste-management plan (SMP) as the top factor, with a path coefficient of 0·96. The impacts on waste generation of factors such as the operation stage (0·91), ordering and purchasing stage (0·84), hauling and handling stage (0·76), material handling stage (0·73), documentation (0·60) and culture (0·46) are quantified. Appropriate documentation provides the framework for SMP, on the basis of which other mitigation measures may be enforced, thus reinforcing the analysis results of SMP variables. Standardised documentation procedures for SMP need to be initiated and incentivised within existing green building performance rating frameworks, such as Green Rating for Integrated Habitat Assessment and Leadership in Energy and Environmental Design–India. </jats:p

Implementing site waste-management plans, recycling in India: barriers, benefits, measures

Despite the guidelines framed by the Indian government, there is non-compliance with site waste-management plans (SWMPs) as well as recycling at construction sites. This paper identifies the existing barriers and potential benefits and enforcement measures for implementing SWMP and recycling of construction and demolition (C&amp;D) waste. Data gathered by means of a questionnaire survey, structured interviews and case studies are analysed using the beneficial index value (BIV) and relative mapping approach. From the results, it is concluded that factor B4 (‘no guidelines are available in the company’) has the highest BIV (6.70) and is the major barrier in implementing SWMPs. Factors BF4 (BIV: 7.42) with an efficient SWMP (‘there will be conservation of natural resources) and MI8 (BIV: 7.32) (‘legal requirements on environmental protection’) are the most significant benefit and enforcement measure for SWMP implementation, respectively. Probable behavioural, legal, technical and marketing barriers for enforcement of recycling are identified, and the suggested measures for efficient recycling are as follows: (a) behavioural – enforcement of construction in government projects using recycled materials; (b) technical – development of code provisions for acceptable quantity of recycled construction waste (CW) in various building components; (c) legal – higher landfill charge with strict penalties for illegal dumping; and (d) marketing – increasing sales outlets for recycling material. Also, successful European C&amp;D waste-management practices are compared with Indian initiatives to improve the CW management status. </jats:p