Search results for: cyber threat intelligence

Authors: Hamza Saeed, Khurram Iqbal Ahmad Khan

Abstract:

Effective information management is crucial for any construction project and its success. Primary areas of information generation are either the construction site or the design office. There are different types of information required at different stages of construction involving various stakeholders creating complexity. There is a need for effective management of information flows to reduce uncertainty creating complexity. Nature provides a unique perspective in terms of dealing with complexity, in particular, information complexity. System dynamics methodology provides tools and techniques to address complexity. It involves modeling and simulation techniques that help address complexity. Nature has been dealing with complex systems since its creation 4.5 billion years ago. It has perfected its system by evolution, resilience towards sudden changes, and extinction of unadaptable and outdated species that are no longer fit for the environment. Nature has been accommodating the changing factors and handling complexity forever. Humans have started to look at their natural counterparts for inspiration and solutions for their problems. This brings forth the possibility of using a biomimetics approach to improve the management practices used in the construction sector. Ants inhabit different habitats. Cataglyphis and Pogonomyrmex live in deserts, Leafcutter ants reside in rainforests, and Pharaoh ants are native to urban developments of tropical areas. Detailed studies have been done on fifty species out of fourteen thousand discovered. They provide the opportunity to study the interactions in diverse environments to generate collective behavior. Animals evolve to better adapt to their environment. The collective behavior of ants emerges from feedback through interactions among individuals, based on a combination of three basic factors: The patchiness of resources in time and space, operating cost, environmental stability, and the threat of rupture. If resources appear in patches through time and space, the response is accelerating and non-linear, and if resources are scattered, the response follows a linear pattern. If the acquisition of energy through food is faster than energy spent to get it, the default is to continue with an activity unless it is halted for some reason. If the energy spent is rather higher than getting it, the default changes to stay put unless activated. Finally, if the environment is stable and the threat of rupture is low, the activation and amplification rate is slow but steady. Otherwise, it is fast and sporadic. To further study the effects and to eliminate the environmental bias, the behavior of four different ant species were studied, namely Red Harvester ants (Pogonomyrmex Barbatus), Argentine ants (Linepithema Humile), Turtle ants (Cephalotes Goniodontus), Leafcutter ants (Genus: Atta). This study aims to improve the information system in the construction sector by providing a guideline inspired by nature with a systems-thinking approach, using system dynamics as a tool. Identified factors and their interdependencies were analyzed in the form of a causal loop diagram (CLD), and construction industry professionals were interviewed based on the developed CLD, which was validated with significance response. These factors and interdependencies in the natural system corresponds with the man-made systems, providing a guideline for effective use and flow of information.

Keywords: biomimetics, complex systems, construction management, information management, system dynamics

Procedia PDF Downloads 136

Authors: Radha Rajamma, Susheela Palanisamy

Abstract:

The use of chemical fertilizers and pesticides has posed a serious threat to the environment, cause disturbance to the soil ecosystem, pollute the water causing serious health problems. The indigenous practices such as herbal spray, phyto-alternatives, etc. offer harmless alternatives in integrated pest management. The use of plant materials has become an integral part of insect pest management because of their cheap and non-toxic nature. Hence an investigation has been made to determine the bio-efficacy of vermiwash and two leaf extracts, Azadirachta indica and Vitex negundo against mealy bug, Paracoccus marginatus. The results on the effect of vermitechnologies on the activity of mealy bug indicated the effectiveness of vermiwash foliar application in suppressing the pest activity. Accumulative mortality of mealy bug increased gradually with the increase of exposure intervals. The combined treatment of vermiwash with Azadirachta indica reported the highest mortality percentage of 96% followed by the individual treatment of leaf extracts. Hence vermiwash was proved to be the most effective in enhancing the potency of mealy bug and decreased LC50 of the target insect.

Keywords: Azadirachta indica, Paracoccus marginatus, vermiwash, Vitex negundo

Procedia PDF Downloads 291

Authors: Mariam Arif

Abstract:

The objective of the current study is to find out the electoral violence against women and its implications on their political participation. This paper is a qualitative study to get an in-depth analysis of the phenomenon. This study used questionnaires and interviews for findings. This paper attempts to study electoral violence and women in politics in Pakistan. The study concluded that women are subjected to different categories of violence defined as physical violence that involves sexual and bodily harm to a politically active woman or to people associated with her. Social and psychological violence includes class difference, stress, social limitations, family pressure and character assassination. Economic violence is defined as a systematic restriction of access to economic resources available to women thus hinder women active participation in politics (elections). All these violence against women in elections are threat to the integrity of the electoral process of the country that eventually affects women’s participation as voters, party candidates, election officials and political party leaders. It also undermines the free and fair democratic process. This qualitative paper shows a significant negative relationship between electoral violence and women participation in politics.

Keywords: elections, politics, violence, women

Procedia PDF Downloads 158

Authors: Onur Yuksel

Abstract:

In today’s complex foreign relations between countries, the nuclear enrichment and nuclear weapon have become a threat for all states in the world. There are couple isolated states which have capacity to produce nuclear weapons such as Iran and North Korea. In this article, Iran nuclear negotiation was analyzed in terms of its relations especially with The United States in order to find the important factors that affect the course of the ongoing nuclear negotiation. In this sense, the Force Field Analysis was used by determining and setting forth Driving and Restraining Forces of the nuclear negotiations in order to see the big picture and to develop strategies that may improve the long-term ongoing Iran nuclear negotiations. It is found that Iran nuclear negotiation heavily depends on breaking down the idea of Iran’s supporting terrorist organizations and being more transparent about nuclear and uranium enrichment. Also, it was found that Iran has to rebuild its relations with Western countries, especially with the United States. In addition, the counties— who contribute to Iran nuclear negotiations— will need to work on the dynamics and drivers of the Israel and Iran relations in order to peacefully transform the conflict between the two states.

Keywords: driving force, Iran nuclear negotiation, restraining force, the force field analysis

Procedia PDF Downloads 156

Authors: Nishtha Batra

Abstract:

This study was conducted to identify the effect of perceived stress on emotional regulation, aggression and psychological well-being. Analysis was conducted using correlational and regression models to examine the relationships between perceived stress (independent variable) and psychological factors containing emotional intelligence, psychological well-being and aggression. Subjects N=100, Male students 50 and Female students 50. The data was collected using Cohen's Perceived Stress Scale, Gross’s Emotional Regulation Questionnaire (ERQ), Ryff’s Psychological Well-being scale and Orispina’s aggression scale. Correlation and regression (SPSS version 22) Emotional regulation and psychological well-being had a significant relationship with Perceived stress.

Keywords: perceived stress, psychological well-being, aggression, emotional regulation, students

Procedia PDF Downloads 25

Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

Abstract:

With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

Procedia PDF Downloads 153

Authors: Sourabh Harihar, Henk Jan Verhagen

Abstract:

The nurturing of a mangrove ecosystem requires a protected coastal environment with adequate drainage of the soil substratum. In a conceptual design undertaken for a mangrove rejuvenation project along the eastern coast of Mumbai (India), various engineering alternatives have been thought of as a protective coastal structure and drainage system. One such design uses bamboo-pile walls in creating shielded compartments in the form of various layouts, coupled with bamboo drains. The bamboo-based design is found to be environmentally and economically advantageous over other designs like sand-dikes which are multiple times more expensive. Moreover, employing a natural material such as bamboo helps the structure naturally blend with the developing mangrove habitat, allaying concerns about dismantling the structure post mangrove growth. A cost-minimising and eco-friendly bamboo structure, therefore, promises to pave the way for large rehabilitation projects in future. As mangrove ecosystems in many parts of the world increasingly face the threat of destruction due to urban development and climate change, protective nature-based designs that can be built in a short duration are the need of the hour.

Keywords: bamboo, environment, mangrove, rehabilitation

Procedia PDF Downloads 281

Authors: Cassi Henderson, Lucia Corsini, Shiv Kapila, Egle Augustaityte, Tsemaye Uwejamomere Zinzan Gurney, Aleyna Yildirim

Abstract:

Plastic pollution is a major threat to human and planetary health. In Low- and Middle-Income Countries, plastic waste poses a major problem for marginalized populations who lack access to formal waste management systems. This study explores the potential for converting waste plastic into construction blocks. It is the first study to analyze the use of polyethylene terephthalate (PET) as a binder in plastic-sand bricks. Unlike previous studies of plastic sand-bricks, this research tests the properties of bricks that were made using a low-cost kiln technology that was co-designed with a rural, coastal community in Kenya.  The mechanical strength, resistance to fire and water absorption properties of the bricks are tested in this study. The findings show that the bricks meet structural standards for mechanical performance, fire resistance and water absorption. It was found that 30:70 PET to sand demonstrated the best overall performance.

Keywords: recycling, PET, plastic, sustainable construction, sustainable development

Procedia PDF Downloads 123

Authors: Ibrahim Alshalan

Abstract:

The Islamic Republic of Iran is one of the greatest and most powerful countries, not only in the Arabian Gulf but in the entire Middle East region. However, the Iranian regime, which came to power as a result of the 1979 revolution that resulted in overthrowing the Shah Mohammad Reza Pahlavi, has been the biggest source of threat to the stability of the Middle East since the revolution until this day. It has ambitions to dominate the neighboring Arab countries, especially Iraq, Syria, Lebanon, Yemen and Bahrain. Iran has bad relationships with countries of the Gulf Cooperation Council (GCC), which includes Saudi Arabia, United Arab Emirates, Kuwait, Qatar, Oman and Bahrain. The main objective of this paper is to shed light on the deteriorating political relations between the Iranian regime on one hand and the GCC on the other, especially Saudi Arabia which is witnessing more challenges as a result of Iran's determination to develop its nuclear program. Another important objective of this paper is to identify the Iranian role in the creation of the hotbeds of conflict in addition to its responsibility for some of the region's problems. It also aims to answer the question; why does Iran insist on developing its controversial nuclear program?

Keywords: Iran, GCC, Gulf, Saudi Arabia

Procedia PDF Downloads 571

Authors: Kristof Lukas Heidemann

Abstract:

The adverse effects of climate change, such as rising sea levels, increased temperatures, and extreme weather events, are already posing a significant threat to the lives of people living in extreme weather zones all around the globe and could displace more than a billion people worldwide in the upcoming decades, causing a wave of climate-induced migration. Notwithstanding the urgency of the situation, this situation has so far not been addressed in a specific international treaty. Therefore, this paper analyses whether solutions might be found through existing legal frameworks. To that end, the investigation scrutinizes the possibilities of overcoming the conceptual challenge of combining climate law, refugee law, and human rights law. The paper concludes that the differences in objective, scope, and enforcement of the three fields are too fundamental to be surmounted by overlapping concepts, e.g., state responsibility or the non-refoulement principle. Consequently, states are urged to tackle the problem with a separate international treaty in which the advantages of the different traditions are incorporated into a new protection mechanism.

Keywords: climate change, climate treaties, forcibly displaced persons, human rights, improving and creating advanced knowledge of concepts, non-refoulement, state responsibility, refugee law, refugee status

Procedia PDF Downloads 3

Authors: Zheng Yuxun

Abstract:

This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

Procedia PDF Downloads 49

Authors: Fathi Elyaagubi

Abstract:

Salinization is a major threat to the productivity of agricultural land. The Gefara Plain located in the northwest of Libya; comprises about 80% of the total agricultural activity. The high water requirements for the populations and agriculture are depleting the groundwater aquifer, resulting in intrusion of seawater in the first few kilometers along the coast. Due to increasing salinity in the groundwater used for irrigation, the soils of the Gefara Plain are becoming increasingly saline. This research paper investigated the sensitivity of these soils to increased salinity using Co2 evolution as an integrating measure of soil function. Soil was collected from four sites located in the Gefara Plain, Almaya, Janzur, Gargaresh and Tajura. Soil collected from Tajura had the highest background salinity, and Janzur had the highest organic matter content. All of the soils had relatively low organic matter content, ranging between 0.49-%1.25. The cumulative rate of 14CO2 of added 14C-labelled Lolium shoots (Lolium perenne L.) to soils was decreased under effects of water containing different concentrations of NaCl at 20, 50, 70, 90, 150, and 200 mM compared to the control at any time of incubation in four sites.

Keywords: soil salinity, gefara plain, organic matter, 14C-labelled lolium shoots

Procedia PDF Downloads 220

Authors: André Python

Abstract:

To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

Procedia PDF Downloads 349

Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

Abstract:

There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: social network sites, online social network, privacy, trust, security and authentication

Procedia PDF Downloads 380

Authors: Dipak Sonawane, Sudarshan Daga, Somesh Gupta

Abstract:

Quantitative risk assessment (QRA) is a very precise and consistent approach to defining the likelihood, consequence and severity of a major incident/accident. A variety of hazardous cargoes in bulk, such as hydrocarbons and flammable/toxic chemicals, are handled at various ports. It is well known that most of the operations are hazardous, having the potential of damaging property, causing injury/loss of life and, in some cases, the threat of environmental damage. In order to ensure adequate safety towards life, environment and property, the application of scientific methods such as QRA is inevitable. By means of these methods, comprehensive hazard identification, risk assessment and appropriate implementation of Risk Control measures can be carried out. In this paper, the authors, based on their extensive experience in Risk Analysis for ports and harbors, have exhibited how QRA can be used in practice to minimize and contain risk to tolerable levels. A specific case involving the operation for unloading of hydrocarbon at a port is presented. The exercise provides confidence that the method of QRA, as proposed by the authors, can be used appropriately for the identification of hazards and risk assessment of Ports and Terminals.

Keywords: quantitative risk assessment, hazard assessment, consequence analysis, individual risk, societal risk

Procedia PDF Downloads 79

Authors: Mayar Almasri, Rosa Helmi, Rayana Enany

Abstract:

This report describes the features of AutoCAD software released by Adobe. It explains how the program makes it easier for engineers and designers and reduces their time and effort spent using AutoCAD. Moreover, it highlights how AutoCAD works, how some of the commands used in it, such as Shortcut, make it easy to use, and features that make it accurate in measurements. The results of the report show that most users of this program are designers and engineers, but few people know about it and find it easy to use. They prefer to use it because it is easy to use, and the shortcut commands shorten a lot of time for them. The feature got a high rate and some suggestions for improving AutoCAD in Aperture, but it was a small percentage, and the highest percentage was that they didn't need to improve the program, and it was good.

Keywords: artificial intelligence, design, planning, commands, autodesk, dimensions

Procedia PDF Downloads 128

Authors: Loren Clarke, Katie Reed

Abstract:

The integration of artificial intelligence (AI) in high school education assessment offers transformative potential, providing more personalized, timely, and accurate evaluations of student performance. However, the successful adoption of AI-driven assessment systems requires robust change management strategies to navigate the complexities and resistance that often accompany such technological shifts. This presentation explores effective methods for implementing AI in high school assessment, emphasizing the need for strategic planning and stakeholder engagement. Focusing on a case study of a Victorian high school, it will examine the practical steps taken to integrate AI into teaching and learning. This school has developed innovative processes to support academic integrity and foster authentic cogeneration with AI, ensuring that the technology is used ethically and effectively. By creating comprehensive professional development programs for teachers and maintaining transparent communication with students and parents, the school has successfully aligned AI technologies with their existing curricula and assessment frameworks. The session will highlight how AI has enhanced both formative and summative assessments, providing real-time feedback that supports differentiated instruction and fosters a more personalized learning experience. Participants will learn about best practices for managing the integration of AI in high school settings while maintaining a focus on equity and student-centered learning. This presentation aims to equip high school educators with the insights and tools needed to effectively manage the integration of AI in assessment, ultimately improving educational outcomes and preparing students for future success. Methodologies: The research is a case study of a Victorian high school to examine AI integration in assessments, focusing on practical implementation steps, ethical practices, and change management strategies to enhance personalized learning and assessment. Outcomes: This research explores AI integration in high school assessments, focusing on personalized evaluations, ethical use, and change management. A Victorian school case study highlights best practices to enhance assessments and improve student outcomes. Main Contributions: This research contributes by outlining effective AI integration in assessments, showcasing a Victorian school's implementation, and providing best practices for ethical use, change management, and enhancing personalized learning outcomes.

Keywords: artificial intelligence, assessment, curriculum design, teaching and learning, ai in education

Procedia PDF Downloads 19

Authors: Muhammad Nauman Ahmad, Patrick Büker, Sofia Khalid, Leon Van Den Berg, Hamid Ullah Shah, Abdul Wahid, Lisa Emberson, Sally A. Power, Mike Ashmore

Abstract:

Although ozone is well-documented to affect crop yields in the densely populated Indo-Gangetic Plain, there is little knowledge of its effects around cities in more remote areas of South Asia. We surveyed crops around the city of Peshawar, Pakistan for visible injury, linking this to passive measurements of ozone concentrations. Foliar injury was found in the field on potato, onion and cotton when the mean monthly ozone concentration reached 35-55ppb. The symptoms on onion were reproduced in ozone fumigation experiments, which also showed that daytime ozone concentrations of 60ppb and above significantly reduce the growth of Pakistani varieties of both spinach (Beta vulgaris) and onion. Aphid infestation on spinach was also reduced at these elevated ozone concentrations. The ozone concentrations in Peshawar are comparable to those through many parts of northern south Asia, where ozone may therefore be a significant threat to sensitive vegetable crops in peri-urban regions.

Keywords: ozone, air pollution, vegetable crops, peshawar, south asia

Procedia PDF Downloads 740

Authors: Hassan Gana Abdullahi, Michael A. Fullen, David Oloke

Abstract:

Drought poses an enormous global threat to sustainable development and is expected to increase with global climate change. Drought and desertification are major problems in Yobe State (north-east Nigeria). This investigation aims to develop a workable framework and management tool for drought mitigation in Yobe State. Mixed methods were employed during the study and additional qualitative information was gathered through Focus Group Discussions (FGD). Data on socio-economic impacts of drought were thus collected via both questionnaire surveys and FGD. In all, 1,040 questionnaires were distributed to farmers in the State and 721 were completed, representing a return rate of 69.3%. Data analysis showed that 97.9% of respondents considered themselves to be drought victims, whilst 69.3% of the respondents were unemployed and had no other means of income, except through rain-fed farming. Developing a viable and holistic approach to drought mitigation is crucial, to arrest and hopefully reverse environment degradation. Analysed data will be used to develop an integrated framework for drought mitigation and management in Yobe State. This paper introduces the socio-economic and environmental effects of drought in Yobe State.

Keywords: drought, climate change, mitigation, management, Yobe State

Procedia PDF Downloads 370

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 65

Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

Abstract:

Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

Procedia PDF Downloads 41

Authors: Dija Sulekha

Abstract:

Nowadays, a good percentage of reported cybercrimes involve the usage of the Internet, directly or indirectly for committing the crime. Usually, Web Browsers leave traces of browsing activities on the host computer’s hard disk, which can be used by investigators to identify internet-based activities of the suspect. But criminals, who involve in some organized crimes, disable browser file generation feature to hide the evidence while doing illegal activities through the Internet. In such cases, even though browser files were not generated in the storage media of the system, traces of recent and ongoing activities were generated in the Physical Memory of the system. As a result, the analysis of Physical Memory Dump collected from the suspect's machine retrieves lots of forensically crucial information related to the browsing history of the Suspect. This information enables the cyber forensic investigators to concentrate on a few highly relevant selected artefacts while doing the Offline Forensics analysis of storage media. This paper addresses the reconstruction of web browsing activities by conducting live forensics to identify searched terms, downloaded files, visited sites, email headers, email ids, etc. from the physical memory dump collected from Windows 10 Systems. Well-known entry points are available for retrieving all the above artefacts except searched terms. The paper describes a novel methodology to retrieve the searched terms from Windows 10 Physical Memory. The searched terms retrieved in this way can be used for doing advanced file and keyword search in the storage media files reconstructed from the file system recovery in offline forensics.

Keywords: browser forensics, digital forensics, live Forensics, physical memory forensics

Procedia PDF Downloads 115

Authors: Ghanem Al-Ghamdi

Abstract:

African Horse Sickness causes significant challenges to horse practitioners and owners in Africa and possibly in certain locations in the Arab Pensila. The aim of this work was to observe a hot spot of epidemic in Al-Baha, Southwestern of Saudi Arabia that could be AHS. A five year-old horse farm that had eight horses with no history of clinical problems was visited in late October 2014. In August 2014, horses showed clinical signs of severe pain, congestion of mucus membranes, foam oozing of the nose, recumbency, difficult breath and ultimately death. The course of the disease averaged 2 days. The farm had no previous history of this episode. Other animals including camel, sheep reside the same farm sharing feeding and water sources however no obvious similar clinical problems were noticed among the two species. Five horses showed the clinical disease and all horses were lost. Veterinary help was not available for diagnosis or treatment. A follow up visit to the farm after one year indicated that the three remaining horses were healthy but were relocated to a different facility out the Al-Baha Region. The most likely cause of such clinical problem is African Horse Sickness, however clinical exam and sampling of other horses in the region is absolute must as well as examining arthropods.

Keywords: African horse sickness, horses, Al-Baha, Saudi Arabia

Procedia PDF Downloads 347

Authors: Ashutosh Mishra, Nikhil Goyal

Abstract:

A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

Procedia PDF Downloads 229

Authors: Paul Awolade, Parvesh Singh

Abstract:

The global threat of pathogenic resistance to available therapeutic agents has become a menace to clinical practice, public health and man’s existence inconsequential. This has therefore led to an exigency in the development of new molecular scaffolds with profound activity profiles. In this vein, a versatile synthetic tool for accessing new molecules by incorporating two or more pharmacophores into a single entity with the unique ability to be recognized by multiple receptors hence leading to an improved bioactivity, known as molecular hybridization, has been explored with tremendous success. Accordingly, aware of the similarity in pharmacological activity spectrum of quinoline and 1,2,3-triazole pharmacophores such as; anti-Alzheimer, anticancer, anti-HIV, antimalarial and antimicrobial to mention but a few, the present study sets out to synthesize hybrids of quinoline and 1,2,3-triazole. The hybrids were accessed via click chemistry using copper catalysed azide-alkyne 1,3-dipolar cycloaddition reaction. All synthesized compounds were evaluated for their pharmaco-potential in an antimicrobial assay out of which the 3-OH derivative emerged as the most active with MIC value of 4 μg/mL against Cryptococcus neoformans; a value superior to standard Fluconazole and comparable to Amphotericin B. Structures of synthesized hybrids were elucidated using appropriate spectroscopic techniques (1H, 13C and 2D NMR, FT-IR and HRMS).

Keywords: bioisostere, click chemistry, molecular hybridization, quinoline, 1, 2, 3-triazole

Procedia PDF Downloads 128

Authors: Toyin Cotties Adetiba

Abstract:

Notably, China is a major global economy, thus increasing debate parlance of foreign policy that sees China as a superpower. China’s investment in Africa is visibly seen in African markets with substantial involvement of its multinationals in key commercial sectors such as infrastructure, telecoms, and agriculture. Not minding its positive economic impact on Africa, the debate around the China-African relationship has continued to be filled with some sort of inconsistency and ambiguity. This work engaged a qualitative research method while answering the question of whether the socioeconomic marriage of convenience between African states and China, is a means and the end to the Chinese control of African economy? Can China-Africa’s relationship engender Africa’s economic development or is it a threat to Africa’s development? The paper argued that through the secret dealings of the Chinese companies with African leaders, couched as palace diplomacy, the Chinese have cornered African economy. Concluding that there is need for the reform of the approaches to curtailing socio-economic and political corruption in Africa in the form of applications of ideas molded and refined to transparency in dealing with the Chinese, while economic institutions in African is empowered to effectively fight corruption.

Keywords: Africans, corruption, diplomacy, companies, development

Procedia PDF Downloads 157

Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

Abstract:

Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

Procedia PDF Downloads 131

Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

Abstract:

This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

Procedia PDF Downloads 215

Authors: Julio Vega

Abstract:

Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 127

Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

Abstract:

Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

Procedia PDF Downloads 547