ChatGPT: Vision and Challenges

Artificial intelligence (AI) and machine learning have changed the nature of scientific inquiry in recent years. Of these, the development of virtual assistants has accelerated greatly in the past few years, with ChatGPT becoming a prominent AI language model. In this study, we examine the foundations, vision, research challenges of ChatGPT. This article investigates into the background and development of the technology behind it, as well as its popular applications. Moreover, we discuss the advantages of bringing everything together through ChatGPT and Internet of Things (IoT). Further, we speculate on the future of ChatGPT by considering various possibilities for study and development, such as energy-efficiency, cybersecurity, enhancing its applicability to additional technologies (Robotics and Computer Vision), strengthening human-AI communications, and bridging the technological gap. Finally, we discuss the important ethics and current trends of ChatGPT

Multifactor optimization for development of hybrid aluminium matrix composites

481-489The present study aims to multi factor optimization for preparation of aluminum matrix composites (AMC) by reinforcement of SiC/ Al2O3/ Al2O3+ SiC particles having dual particle size (DPS) and triplicate particle size (TPS) based upon signal to noise (S/N) ratio analysis. In this work the amalgamation of fused deposition modelling (FDM) and vacuum moulding (V-process) assisted stir casting (SC) has been employed for the development of AMC. The process parameters under investigation are: particle size (DPS/ TPS); reinforcement type (Al2O3/ SiC/ Al2O3+ SiC); vacuum pressure (VP) (300-400 mm of Hg); moulding sand grit size (American foundry society (AFS) No. 50-70); vibration time (VT) (4-6 sec) and reinforcement proportion/composition (5/7.5/10 by wt.%). The S/N ratio based upon the wear performance (pin-on disc tester), micro hardness (HV) and dimensional accuracy/deviation (Δt) has been evaluated by using Minitab-17 software which further acts as input for multifactor optimization. The best parametric setting proposed for multi objective/factor optimization is: DPS of Al2O3+ SiC reinforcement at 350 mm of Hg VP with 50 AFS No. sand grain size, 4sec VT and 10% composition/proportion. The results of analysis of variance (ANOVA) highlight that particle size (with 18.49% contribution) and reinforcement type (with 42.13% contribution) have significant influence on multi factor optimization for the development of AMC. Confirmatory experiments have been performed which shows that the proposed amalgamation of FDM and V-process assisted SC can be successfully applied for enhancing the performance of AMC. Finally the X-chart and R-chart have been plotted at the proposed settings, which highlights that amalgamation process is controlled and useful for mass/ batch production

Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported hallucinations within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial.Comment: Preprint submitted to IoTCPS Elsevier (2023

Endoscopic spray cryotherapy for esophageal cancer: safety and efficacy

Few options exist for patients with localized esophageal cancer ineligible for conventional therapies. Endoscopic spray cryotherapy with low-pressure liquid nitrogen has demonstrated efficacy in this setting in early studies

Transformative effects of ChatGPT on modern education: emerging era of AI chatbots

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported “hallucinations” within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial

Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe

Intrusion detection techniques in wireless local area networks

This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation

Experiences in Passively Detecting Session Hijacking Attacks in IEEE 802.11 Networks

Current IEEE 802.11 wireless networks are vulnerable to session hijacking attacks as the existing standards fail to address the lack of authentication of management frames and network card addresses, and rely on loosely coupled state machines. Even the new WLAN security standard - IEEE 802.11i does not address these issues. In our previous work, we proposed two new techniques for improving detection of session hijacking attacks that are passive, computationally inexpensive, reliable, and have minimal impact on network performance. These techniques utilise unspoofable characteristics from the MAC protocol and the physical layer to enhance confidence in the intrusion detection process. This paper extends our earlier work and explores usability, robustness and accuracy of these intrusion detection techniques by applying them to eight distinct test scenarios. A correlation engine has also been introduced to maintain the false positives and false negatives at a manageable level. We also explore the process of selecting optimum thresholds for both detection techniques. For the purposes of our experiments, Snort-Wireless open source wireless intrusion detection system was extended to implement these new techniques and the correlation engine. Absence of any false negatives and low number of false positives in all eight test scenarios successfully demonstrated the effectiveness of the correlation engine and the accuracy of the detection techniques

On Securing Wireless LAN Access to Government Information Systems

The success of the IEEE 802.11 series of standards has led to a proliferation of affordable and interoperable wireless networking devices. Wireless functionality is an integrated feature of many laptops, personal digital assistants, and even mobile phones. With the ratification of the security enhancement to IEEE 802.11, referred to as IEEE 802.11i, in 2004 and the subsequent availability of implementations of the standard in current hardware, many of the security concerns surrounding the original wireless standards would seem to have been addressed. Are the security enhanced features of IEEE 802.11i, however, suitable for securing access to Australian Government information systems? In this paper, we review the capability of the security features of IEEE 802.11i to address the requirements for securing access to Government information systems as expressed in the Australian Government information technology security manual (ACSI33). Our review identifies the requirements of ACSI33 and reveals that a number of these can be met by specific security configurations of IEEE 802.11i. Meeting these requirements, however, is highly dependent not only on the correct configuration of the wireless networking components, but also the supporting authentication infrastructure. Additionally, remaining vulnerabilities in the IEEE 802.11i standard are identified as are vulnerabilities introduced by the use of mobile and wireless devices

Passive Techniques for Detecting Session Hijacking Attacks in IEEE 802.11 Wireless Networks

Wireless networking technologies based on IEEE 802.11 series of standards are evolving to address many of the security issues that plagued earlier wireless standards. Unfortunately the current standards fail to authenticate management frames and network card addresses, and rely on loosely coupled state machines. This results in serious vulnerabilities that may lead to denial of service, session hijacking, and address masquerading attacks. Until the standards are updated to redress these problems, wireless network deployments must be supported by wireless intrusion detection systems–a challenging and under researched area. This paper presents techniques for improving detection of session hijacking attacks that are passive, computationally inexpensive, reliable, and have minimal impact on network performance. Experimental results are presented to give confidence in the utility of the techniques