Towards Auto Contract Generation and Ensemble-based Smart Contract Vulnerability Detection

Smart contracts (SC) are computer programs that are major components of Blockchain. The "intelligent contract" is made up of the rules accepted by the parties concerned. When the transactions started by the parties obey these established rules, then only their transactions will be completed without the involvement of a third party. Because of the simplicity and succinct nature of the solidity language, most smart contracts are written in this language. Smart contracts have two limitations, which are vulnerabilities in SC and that smart contracts can\u27t be understood by all stakeholders, especially non-technical people who are involved in the business, since they are written in a programming language. Hence, the proposed paper used the XGBoost model and BPMN (Business Process Modeling Notation) tool to solve the first and second limitations of the SC respectively. Attackers are drawn to attention because of the popularity and fragility of the Solidity language. Once smart contracts have been launched, they can’t be changed. If that smart contract is vulnerable, attackers may then cash it. BPMN is used to represent business rules or contracts in graphical notation, so everyone involved in the business can understand the business rules. This BPMN diagram can be converted into a smart contract template through the BPMN-SOL tool. A few publications and existing tools exist on smart contract vulnerability detection, but they require more time to forecast and interpretation of vulnerability causes is also difficult. Thus, the proposed model experimented with several deep learning approaches and improved F1 score results by an average of 2% using the XGBoost model based on the ensemble technique to detect vulnerabilities of SCs, which are: Denial of Service (DOS), Unchecked external call, Re-entrancy, and Origin of Transaction. This paper also combined two important features to construct a data set, which are code snippets and n-grams

Effect of soaking time and concentration of NaOH solution on mechanical properties of coir-polyester composites

The green husk coir fibres were treated with different levels of soaking time and concentration of alkali solution. As a result of alkali treatment, the surface modifications were done on the fibre surface and were studied using scanning electron micrographs. The coir–polyester composites were fabricated using hand lay up process and the mechanical properties (tensile, flexural and impact strength) were evaluated as per ASTM standards. The effect of soaking time and concentration of NaOH solution were studied based on evaluated values of mechanical properties to find out optimum fibre treatment parameters

Variability of neonatal premedication practices for endotracheal intubation and LISA in the UK (NeoPRINT survey)

Objective The NeoPRINT Survey was designed to assess premedication practices throughout UK NHS Trusts for both neonatal endotracheal intubation and less invasive surfactant administration (LISA). Design An online survey consisting of multiple choice and open answer questions covering preferences of premedication for endotracheal intubation and LISA was distributed over a 67-day period. Responses were then analysed using STATA IC 16.0. Setting Online survey distributed to all UK Neonatal Units (NNUs). Participants The survey evaluated premedication practices for endotracheal intubation and LISA in neonates requiring these procedures. Main outcome measures The use of different premedication categories as well as individual medications within each category was analysed to create a picture of typical clinical practice across the UK. Results The response rate for the survey was 40.8 % (78/191). Premedication was used in all hospitals for endotracheal intubation but overall, 50 % (39/78) of the units that have responded, use premedications for LISA. Individual clinician preference had an impact on premedication practices within each NNU. Conclusion The wide variability on first-line premedication for endotracheal intubation noted in this survey could be overcome using best available evidence through consensus guidance driven by organisations such as British Association of Perinatal |Medicine (BAPM). Secondly, the divisive view around LISA premedication practices noted in this survey requires an answer through a randomised controlled trial

Information Access Patterns of Faculty in Arts and Sciences Colleges in Chidambaram

The term “user study” focuses on information use patterns, information needs, and information-seeking behaviour. Information- seeking behaviour and information access patterns are areas of active interest among librarians and information scientists. This article reports on a study of the information requirements, usefulness of library resources and services, and problems encountered by faculty members of two arts and science colleges, Government Arts & Science College and Sri Raghavendra Arts & Science College, Chidambaram

Studies on Cu-tolerant bacteria in the Vellar estuary, southeast coast of India

229-231Sediment samples harboured more Cu-tolerant bacteria than seawater samples. Morphological and biochemical characteristics of the selected isolates from each sample were studied. The production of amylase, lipase and protease was also attempted. The genera such as Vibrio, Micrococcus, Corynebacterium and Pseudomonas were commonly encountered. Cu-tolerant forms may be used as a tool to control the Cu pollution in the environment

Advancing post-harvest fruit handling through AI-based thermal imaging: applications, challenges, and future trends

Abstract Recent advancements in imaging, electronics, and computer science have engendered significant progress in non-destructive testing and quality monitoring within the agro-food industry. This progress is particularly evident in integrating infrared thermal imaging (TI) and artificial intelligence (AI) techniques. As a non-contact method, AI-based TI holds promise in detecting various quality attributes and has found extensive applications in agriculture, food processing, and post-harvest fruit handling. This paper delves into recent applications of AI-based thermal imaging, specifically in post-harvest fruit handling. The introduction provides a comprehensive overview of the challenges faced in the post-harvest fruit handling industry while emphasizing the advantages of AI-driven thermal imaging technology. The detailed thermal imaging system encompasses both passive and active thermography techniques. This paper provides an in-depth exploration of artificial intelligence, focusing on machine learning and deep learning. It highlights the significance of convolutional neural networks (CNNs) and their architectural phases. Subsequently, critical applications of AI-based thermal imaging in post-harvest fruit quality assessment are discussed. These applications encompass bruise detection, maturity identification, condition monitoring, grading and sorting, pest and disease detection, and considerations for packaging and supply chain management. Furthermore, this paper addresses the challenges and limitations of AI-based thermal imaging in post-harvest fruit handling. In conclusion, this paper discusses future trends in AI-based thermal imaging, emphasizing the potential for increased automation and integration with emerging technologies in the post-harvest fruit handling sector. The insights provided contribute to the ongoing dialog surrounding optimizing quality assessment processes in the agro-food industry

Pilot ignition development and full scale AB testing

An experimental investigation on the development of a pilot ignition system, using a novel flame ball method, has been successfully carried out for GTRE's Kaveri engine afterburner. The flame ball concept was proved in the specially set-up elemental test facility, which had high altitude simulation capability. Detailed ignition tests incorporating the newly developed pilot ignition system was carried out, under simulated conditions, in the elemental test facility and in the specially set-up full-scale Kaveri engine afterburner facility. Recommendations were made on teh dimensions, location and the type of fuel injector to be used in the pilot ignition system. The pilot ignition system has been successfully developed and tested under full-scale conditions at Bangalore