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  1. Article ; Online: Blockchain-Based Approach for Crop Index Insurance in Agricultural Supply Chain

    Ilhaam A. Omar / Raja Jayaraman / Khaled Salah / Haya R. Hasan / Jiju Antony / Mohammed Omar

    IEEE Access, Vol 11, Pp 118660-

    2023  Volume 118675

    Abstract: Crop insurance serves as a crucial risk mitigation strategy for farmers facing uncertainties stemming from unpredictable weather conditions and vulnerabilities within the agricultural production process. Unfortunately, the prevailing traditional methods ... ...

    Abstract Crop insurance serves as a crucial risk mitigation strategy for farmers facing uncertainties stemming from unpredictable weather conditions and vulnerabilities within the agricultural production process. Unfortunately, the prevailing traditional methods of crop insurance are laden with complexities, high costs, and, more critically, a lack of trust, which has deterred farmers from safeguarding their crops. Addressing these challenges, we present an innovative blockchain-based crop index insurance solution aimed at delivering multiple benefits. Our solution leverages blockchain technology to ensure unprecedented transparency throughout the insurance ecosystem. Every transaction and data exchange among farmers, insurers, and weather data providers is recorded on an immutable ledger, fostering trust, accountability, and confidence among all stakeholders. Moreover, blockchain’s inherent immutability and the use of smart contracts mitigate the risk of fraudulent activities in the crop insurance domain. Claims are processed autonomously, significantly reducing the possibility of fraudulent claims and enhancing the integrity of the system. One of the primary concerns of farmers, delayed claim settlements, is addressed by our solution. Smart contracts enable automated and prompt claim processing, ensuring that farmers receive timely payouts. Furthermore, our solution substantially reduces costs by eliminating intermediaries and streamlining administrative processes. This affordability democratizes crop insurance, making it accessible to a broader spectrum of farmers, including those in low-income countries. Our comprehensive approach integrates advanced algorithms for secure information sharing and interaction among stakeholders. We have rigorously tested the smart contract code under diverse scenarios using the Remix IDE, with the code’s availability on GitHub as a reference. Security vulnerabilities have been meticulously assessed and addressed. Thus, our paper presents an effective, low-cost, ...
    Keywords Blockchain ; ethereum ; transparency ; crop index insurance ; agriculture ; smart contracts ; Electrical engineering. Electronics. Nuclear engineering ; TK1-9971
    Subject code 336
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher IEEE
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Severity of vehicle-to-vehicle accidents in the UAE

    Praveen Maghelal / Abdulrahim Haroun Ali / Elie Azar / Raja Jayaraman / Kinda Khalaf

    Heliyon, Vol 9, Iss 10, Pp e20694- (2023)

    An exploratory analysis using machine learning algorithms

    2023  

    Abstract: The World Health Organization (WHO) identifies road traffic injuries as a global health problem. The Eastern-Mediterranean region is particularly suffering from low traffic safety levels, recording the third highest death per capita ratio in the world. ... ...

    Abstract The World Health Organization (WHO) identifies road traffic injuries as a global health problem. The Eastern-Mediterranean region is particularly suffering from low traffic safety levels, recording the third highest death per capita ratio in the world. It is critical to evaluate and understand the causes of crashes and their severity levels as a first step to devising policies that aim to reduce these causes. Previous studies examining the frequency or severity of crashes present important limitations that motivate the need for the current work. While these studies have investigated the relation of contributing factors to severity of crashes, not until recently the importance of these factors are bring investigated. Even then, less research have explored various Machine Learning models and none in the middle-eastern region. This is critical because the WHO report concludes that the chances of dying in a traffic crash in this region are second only to Africa per 100000 population.This is a first study analyzing the severity of vehicle-to-vehicle crashes among drivers in the United Arab Emirates. Traffic Crash Data was obtained from the Abu Dhabi Police, which consisted of 11,400 observations during the period 2014–2017. Machine learning algorithms, including gradient boosting (GB), support vector machines (SVM), and random forest (RF), were trained and tested to predict crash severity and extract (using feature analysis) its determinants. The models were evaluated using two performance metrics: prediction accuracy and F1-scores.The RF model outperformed both GB and SVM, with the confusion matrix of RF reporting a better prediction for all four crash severity classes. The feature importance analysis indicates that the age of car, age of the injured, and the age of the initiator have the highest effect on severity, which is an important finding as the listed factors were rarely considered in previous studies. Vehicle and road characteristics such as vehicle class, crash type, and lighting are slightly associated ...
    Keywords Crashes ; Severity ; Machine learning ; Random forest ; United Arab Emirates ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Subject code 380
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: A Conceptual Model for Integrating Sustainable Supply Chain, Electric Vehicles, and Renewable Energy Sources

    Ankit R. Patel / Dhaval R. Vyas / Anilkumar Markana / Raja Jayaraman

    Sustainability, Vol 14, Iss 14484, p

    2022  Volume 14484

    Abstract: The effects of climate change can be seen immediately in ecosystems. Recent events have resulted in a commitment to the Paris Agreement for the reduction of carbon emissions by a significant amount by the year 2030. Rapid urbanisation is taking place to ... ...

    Abstract The effects of climate change can be seen immediately in ecosystems. Recent events have resulted in a commitment to the Paris Agreement for the reduction of carbon emissions by a significant amount by the year 2030. Rapid urbanisation is taking place to provide room for an increasing number of people’s residences. Increasing the size of a city and the number of people living there creates a daily need for consumable resources. In the areas of transportation, supply chains, and the utilisation of renewable energy sources, deliver on pledges that promote the accomplishment of the Sustainable Development Goals established by the United Nations. As a result, the supply chain needs to be handled effectively to meet the requirements of growing cities. Management of the supply chain should be in harmony with the environment; nevertheless, the question of how to manage a sustainable supply chain without having an impact on the environment is still mostly understood. The purpose of this study is to present a conceptual model that may be used to maintain a sustainable supply chain with electric vehicles in such a way that caters to both environmental concerns and human requirements. As part of the continual process of achieving sustainability, interrelationships between the various aspects that are being investigated, comprehended, and applied are provided by the model that was developed. It is self-evident that governmental and international organisations that are concerned with supply-demand side information will benefit from such a model, and these organisations will locate viable solutions in accordance with the model’s recommendations. Beneficiaries consist of individuals who are active in the supply chain and are concerned with supply-demand side information. These individuals also need to understand how to effectively manage this information.
    Keywords COVID-19 ; electric vehicles (EVs) ; renewable energy sources (RESs) ; supply chain management (SCM) ; sustainable supply chain (SSC) ; sustainable development goals (SDGs) ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 620
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Prioritizing Indicators for Sustainability Assessment in Manufacturing Process

    Vikas Swarnakar / Amit Raj Singh / Jiju Antony / Raja Jayaraman / Anil Kr Tiwari / Rajeev Rathi / Elizabeth Cudney

    Sustainability, Vol 14, Iss 3264, p

    An Integrated Approach

    2022  Volume 3264

    Abstract: Sustainable manufacturing has renewed attention among researchers to address various sustainability challenges in manufacturing industries. Sustainability assessments of manufacturing organizations help minimize the negative environmental impact and ... ...

    Abstract Sustainable manufacturing has renewed attention among researchers to address various sustainability challenges in manufacturing industries. Sustainability assessments of manufacturing organizations help minimize the negative environmental impact and enhance reputation among public and regulatory agencies. To assess the sustainability of the manufacturing process; it is indispensable to investigate the structured set of triple bottom line (3BL) indicators. Moreover, there is no comprehensive and structured set of 3BL indicators that can effectively assess the sustainability of any organization’s manufacturing process. This research aims to identify and prioritize experts’ consensus structured set of 3BL indicators. The 3BL indicators were identified through an open-ended questionnaire. The prioritization was performed through the Best-Worst Scaling (BWS) approach. Further, Multi-Criteria Decision Analysis (MCDA) method was utilized to draw the consensus ranking of sustainability indicators in manufacturing. The findings indicated that the release of greenhouse/harmful gas is the best indicator in the perspective of environmental criteria followed by the rate of contribution to society and operational cost are the most important critical indicator in the case of social and economic sustainability criteria. The outcome of the present study will facilitate researchers and practitioners in developing suitable readiness and operational plans for the sustainability assessment of the manufacturing process.
    Keywords sustainable manufacturing ; sustainability indicators ; triple bottom line indicator selection ; Delphi study ; best-worst scaling ; multi-criteria decision analysis ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 320
    Language English
    Publishing date 2022-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Ensuring protocol compliance and data transparency in clinical trials using Blockchain smart contracts

    Ilhaam A. Omar / Raja Jayaraman / Khaled Salah / Mecit Can Emre Simsekler / Ibrar Yaqoob / Samer Ellahham

    BMC Medical Research Methodology, Vol 20, Iss 1, Pp 1-

    2020  Volume 17

    Abstract: Abstract Background Clinical Trials (CTs) help in testing and validating the safety and efficacy of newly discovered drugs on specific patient population cohorts. However, these trials usually experience many challenges, such as extensive time frames, ... ...

    Abstract Abstract Background Clinical Trials (CTs) help in testing and validating the safety and efficacy of newly discovered drugs on specific patient population cohorts. However, these trials usually experience many challenges, such as extensive time frames, high financial cost, regulatory and administrative barriers, and insufficient workforce. In addition, CTs face several data management challenges pertaining to protocol compliance, patient enrollment, transparency, traceability, data integrity, and selective reporting. Blockchain can potentially address such challenges because of its intrinsic features and properties. Although existing literature broadly discusses the applicability of blockchain-based solutions for CTs, only a few studies present their working proof-of-concept. Methods We propose a blockchain-based framework for CT data management, using Ethereum smart contracts, which employs IPFS as the file storage system to automate processes and information exchange among CT stakeholders. CT documents stored in the IPFS are difficult to tamper with as they are given unique cryptographic hashes. We present algorithms that capture various stages of CT data management. We develop the Ethereum smart contract using Remix IDE that is validated under different scenarios. Results The proposed framework results are advantageous to all stakeholders ensuring transparency, data integrity, and protocol compliance. Although the proposed solution is tested on the Ethereum blockchain platform, it can be deployed in private blockchain networks using their native smart contract technologies. We make our smart contract code publicly available on Github. Conclusions We conclude that the proposed framework can be highly effective in ensuring that the trial abides by the protocol and the functions are executed only by the stakeholders who are given permission. It also assures data integrity and promotes transparency and traceability of information among stakeholders.
    Keywords Blockchain ; Clinical trials ; Healthcare ; Ethereum ; Smart contracts ; IPFS ; Medicine (General) ; R5-920
    Subject code 005
    Language English
    Publishing date 2020-09-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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