Search results for: threat intelligence

Authors: Driss Kettani

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ICT4D actors are naturally attempted to include AI in the range of enabling technologies and tools that could support and boost the Development process, and to refer to these as AI4D. But, doing so, assumes that AI complies with the very specific features of ICT4D context, including, among others, affordability, relevance, openness, and ownership. Clearly, none of these is fulfilled, and the enthusiastic posture that AI4D is a natural part of ICT4D is not grounded and, to certain extent, does not serve the purpose of Technology for Development at all. In the context of Development, it is important to emphasize and prioritize ICT4D, in the national digital transformation strategies, instead of borrowing "trendy" waves of the IT Industry that are motivated by business considerations, with no specific care/consideration to Development.

Keywords: AI, ICT4D, technology for development, position paper

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Authors: Laura Irimies, Cosmin Irimies

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The public space all over the world is currently confronted with the aggressive assault of fake news that have lately impacted public agenda setting, collective decisions and social attitudes. Top leaders constantly call out most mainstream news as “fake news” and the public opinion get more confused. "Fake news" are generally defined as false, often sensational, information disseminated under the guise of news reporting and has been declared the word of the year 2017 by Collins Dictionary and it also has been one of the most debated socio-political topics of recent years. Websites which, deliberately or not, publish misleading information are often shared on social media where they essentially increase their reach and influence. According to international reports, the exposure to fake news is an undeniable reality all over the world as the exposure to completely invented information goes up to the 31 percent in the US, and it is even bigger in Eastern Europe countries, such as Hungary (42%) and Romania (38%) or in Mediterranean countries, such as Greece (44%) or Turkey (49%), and lower in Northern and Western Europe countries – Germany (9%), Denmark (9%) or Holland (10%). While the study of fake news (mechanism and effects) is still in its infancy, it has become truly relevant as the phenomenon seems to have a growing impact on democratic systems. Studies conducted by the European Commission show that 83% of respondents out of a total of 26,576 interviewees consider the existence of news that misrepresent reality as a threat for democracy. Studies recently conducted at Arizona State University show that people with higher education can more easily spot fake headlines, but over 30 percent of them can still be trapped by fake information. If we were to refer only to some of the most recent situations in Romania, fake news issues and hidden agenda suspicions related to the massive and extremely violent public demonstrations held on August 10th, 2018 with a strong participation of the Romanian diaspora have been massively reflected by the international media and generated serious debates within the European Commission. Considering the above framework, the study raises four main research questions: 1. Is fake news a problem or just a natural consequence of mainstream media decline and the abundance of sources of information? 2. What are the implications for democracy? 3. Can fake news be controlled without restricting fundamental human rights? 4. How could the public be properly educated to detect fake news? The research uses mostly qualitative but also quantitative methods, content analysis of studies, websites and media content, official reports and interviews. The study will prove the real threat fake news represent and also the need for proper media literacy education and will draw basic guidelines for developing a new and essential skill: that of detecting fake in news in a society overwhelmed by sources of information that constantly roll massive amounts of information increasing the risk of misinformation and leading to inadequate public decisions that could affect democratic stability.

Keywords: agenda setting democracy, fake news, journalism, media literacy

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Authors: Mohammad Y. Alfaifi

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Anything that poses a challenge or a threat to our well-being is a stress. Understanding the genetic material and cellular response of rats threatened with Repeated swimming stress provides insights that can influence human health. The aim of the present study was to assess the genetical damage and cytological changes caused by exposure of the test organism (Rattus rattus) to forced swimming stress. For this purpose, animals have been submerged in water path 15 minutes daily for 2 weeks. Following that, we performed a micronuclei (MN) test using MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and cytological parameters using NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells in rat's bone marrow samples. Results showed that there was a slightly but not significant increase in the frequency of micronucleated as well as in cytological parameters in bone marrow cells.

Keywords: submergence stress, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

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Authors: Dongchuan Su, Hai Xie, Naibin Jiang

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Under severe accident cases, the nuclear reactor core may meltdown inside the lower head of the reactor pressure vessel (RPV). Retaining the melt pool inside the RPV is an important strategy of severe accident management. During this process, the inner wall of the lower head will be heated to high temperature of a thousand centigrade, and the outer wall is immersed in a large amount of cooling water. The material of the lower head will have serious creep damage under the high temperature and the temperature difference, and this produces a great threat to the integrity of the RPV. In this paper, the ANSYS program is employed to build the finite element method (FEM) model of the lower head, the creep phenomena is simulated under the severe accident case, the time dependent strain and stress distribution is obtained, the creep damage of the lower head is investigated, the integrity of the RPV is evaluated and the theoretical basis is provided for the optimized design and safety assessment of the RPV.

Keywords: severe accident, lower head of RPV, creep, FEM

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Authors: Dulani Jayasuriya

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This study outlines the developmental steps of a chatbot for administrative purposes of a large undergraduate course. The chatbot is able to handle student queries about administrative details, including assessment deadlines, course documentation, how to navigate the course, group formation, etc. The development window screenshots are that of a free account on the Snatchbot platform such that this can be adopted by the wider public. While only one connection to an answer based on possible keywords is shown here, one needs to develop multiple connections leading to different answers based on different keywords for the actual chatbot to function. The overall flow of the chatbot showing connections between different interactions is depicted at the end.

Keywords: chatbots, education, technology, snatch bot, artificial intelligence

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Authors: Nithya Devi

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Poverty, hunger and water scarcity are threats to human rights and are assaults on human dignity. The very existence of man is questioned when his basic rights are violated. Addressing this social phenomenon should be a key objective of any human rights discourse. The origins of these problems have various root causes. For Asia, colonisation was an essential factor that caused great inequalities in the distribution of wealth. In the post-colonial era, the colonised states were developing nations grappling with these issues. Today, some of the developing states have progressed to developed nations. However, others remain as economically vulnerable countries. Within states, the widening income gap poses further threat to human rights. Hence ASEAN states have prioritised socio-economic rights, particularly basic needs, in the human rights discourse in this region. To date, poverty and development goals are given primary importance. This paper seeks to show how a human rights approach has dealt with poverty and development goals in this region and evaluates its effectiveness in addressing these concerns.

Keywords: ASEAN, development, human rights, poverty

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Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

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Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

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This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Asegid Belay Kebede, Getachew Biru Worku

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The Earth and its inhabitants have faced an existential threat as a result of severe manmade actions. Global warming and climate change have been the most apparent manifestations of this threat throughout the world, with increasingly intense heat waves, temperature rises, flooding, sea-level rise, ice sheet melting, and so on. One of the major contributors to this disaster is the ever-increasing production and consumption of energy, which is still primarily fossil-based and emits billions of tons of hazardous GHG. The transportation industry is recognized as the biggest actor in terms of emissions, accounting for 24% of direct CO2 emissions and being one of the few worldwide sectors where CO2 emissions are still growing. Rail transportation, which includes all from light rail transit to high-speed rail services, is regarded as one of the most efficient modes of transportation, accounting for 9% of total passenger travel and 7% of total freight transit. Nonetheless, there is still room for improvement in the transportation sector, which might be done by incorporating alternative and/or renewable energy sources. As a result of these rapidly changing global energy situations and rapidly dwindling fossil fuel supplies, we were driven to analyze the possibility of renewable energy sources for traction applications. Even a small achievement in energy conservation or harnessing might significantly influence the total railway system and have the potential to transform the railway sector like never before. As a result, the paper begins by assessing the potential for photovoltaic (PV) power generation on train rooftops and existing infrastructure such as railway depots, passenger stations, traction substation rooftops, and accessible land along rail lines. As a result, a method based on a Google Earth system (using Helioscopes software) is developed to assess the PV potential along rail lines and on train station roofs. As an example, the Addis Ababa light rail transit system (AA-LRTS) is utilized. The case study examines the electricity-generating potential and economic performance of photovoltaics installed on AALRTS. As a consequence, the overall capacity of solar systems on all stations, including train rooftops, reaches 72.6 MWh per day, with an annual power output of 10.6 GWh. Throughout a 25-year lifespan, the overall CO2 emission reduction and total profit from PV-AA-LRTS can reach 180,000 tons and 892 million Ethiopian birrs, respectively. The PV-AA-LRTS has a 200% return on investment. All PV stations have a payback time of less than 13 years, and the price of solar-generated power is less than $0.08/kWh, which can compete with the benchmark price of coal-fired electricity. Our findings indicate that PV-AA-LRTS has tremendous potential, with both energy and economic advantages.

Keywords: sustainable development, global warming, energy crisis, photovoltaic energy conversion, techno-economic analysis, transportation system, light rail transit

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Authors: David Nchinda Keming

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The present study is focused on both the national and international collective fight against Boko Haram terrorism on Cameroon and the rule played by the Lake Chad Basin Countries (LCBCs) and the global community to suffocate the sect’s activities in the region. Although countries of the Lake Chad Basin include: Cameroon, Chad, Nigeria and Niger others like Benin also joined the course. The justification for the internationalisation of the fight against Boko Haram could be explained by the ecological and international climatic importance of the Lake Chad and the danger posed by the sect not only to the Lake Chad member countries but to global armed, civil servants and the international political economy. The study, therefore, kick start with Cameroon’s reaction to Boko Haram’s terrorist attacks on its territory. It further expounds on Cameroon’s request on bilateral diplomacy from members of the UN Security Council for an international collective support to staple the winds of the challenging sect. The study relies on the hypothesis that Boko Haram advanced terrorism on Cameroon was more challenging to the domestic military intelligence thus forcing the government to seek for bilateral and multilateral international collective support to secure its territory from the powerful sect. This premise is tested internationally via (multilateral cooperation, bilateral response, regional cooperation) and domestically through (solidarity parade, religious discourse, political manifestations, war efforts, the vigilantes and the way forward). To accomplish our study, we made used of the mixed research methodologies to interpret the primary, secondary and tertiary sources consulted. Our results reveal that the collective response was effectively positive justified by the drastic drop in the sect’s operations in Cameroon and the whole LCBCs. Although the sect was incapacitated, terrorism remains an international malaise and Cameroon hosts a fertile ground for terrorists’ activism. Boko Haram was just weakened and not completely defeated and could reappear someday even under a different appellation. Therefore, to absolutely eradicate terrorism in general and Boko Haram in particular, LCBCs must improve their military intelligence on terrorism and continue to collaborate with advanced experienced countries in fighting terrorism.

Keywords: Boko Haram, terrorism, domestic, international, response

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Authors: Nasir Baba Ahmed, Nicolas Daclin, Marc Olivaux, Gilles Dusserre

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The Mobile field hospital is critical in terms of managing emergencies in crisis. It is a sub-section of the main hospitals and the health sector, tasked with delivering responsive, immediate, and efficient medical services during a crisis. With the aim to prevent further crisis, the assessment of the cyber assets follows different methods, to distinguish its strengths and weaknesses, and in turn achieve cyber resiliency. The work focuses on assessments of cyber resilience in field hospitals with trends growing in both the field hospital and the health sector in general. This creates opportunities for the adverse attackers and the response improvement objectives for attaining cyber resilience, as the assessments allow users and stakeholders to know the level of risks with regards to its cyber assets. Thus, the purpose is to show the possible threat vectors which open up opportunities, with contrast to current trends in the assessment of the mobile field hospitals’ cyber assets.

Keywords: assessment framework, cyber resilience, cyber security, mobile field hospital

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Authors: Dursun Kalebaşi

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When we examine the history of mankind (from the past up to the present), we see that millions of people died because of the wars. Especially, since the beginning of 19th century, the increase of the human death rate is caused mostly by the regional conflicts and natural disasters rather than the wars. From that point of view, the biggest threat humanity face today is temperature increase and climate change that started to emerge in recent years. When we take into account the natural disasters on one hand and refuges that flee from regional conflicts on the other, it stands out as a dramatic situation because of the huge human losses. In this context, most of the countries started to give more importance to Search and Rescue (SAR) operations to stop the loss of lives or decrease the death rate. This article will tell about the SAR activities in Turkey since 2000 and discuss the Turkey’s contributions to Rescue Missions after the natural disasters in different parts of the world. Moreover, there will be some new highlights to a more habitable and more peaceful world through the SAR missions.

Keywords: search and rescue, natural disasters, migration and world peace, Turkish army forces

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Authors: Tina Abrefa-Gyan

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Background: In Ghana and the rest of sub-Saharan Africa, HIV/AIDS is a public health threat and also causes medical crises for many who are infected with the virus. Objective: This study tested a social care intervention developed to help improve the quality of life of those living with HIV/AIDS in Ghana. Method: Adult respondents (N = 248) were assigned to receive the intervention or usual care for six weeks. Results: Results of the study revealed significant differences between the treatment and control groups in their reports of quality of life. Respondents reported better quality of life upon receiving the intervention. Implication: This study sheds light on the positive relationship between the intervention and quality of life among those living with HIV/AIDS in Ghana. Conclusion: The intervention is innovative and novel in the setting. It will, therefore, help to reduce the risks such as depression, low cognitive functioning, and low physical functioning associated with low quality of life among people living with HIV/AIDS in Ghana in specific, and in sub-Saharan Africa in general.

Keywords: social care intervention, HIV/AIDS, Ghana, quality of life

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk, L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: decision making support systems, emergency risk assessment, natural and anthropogenic safety, on-line control, territory

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Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: J. Cwiklak, M. Grzegorzewski, M. Adamski

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The paper presents results of the project conducted in Poland devoted to study on bird strikes at military airfields. The main aim of this project was to develop methods of aircraft protection against threats from birds. The studies were carried out using two methods. One by transect and the other one by selected sector scanning. During the research, it was recorded, that 104 species of birds in the number about of 36000 were observed. The most frequent ones were starling Sturnus vulgaris (31.0%), jackdaw Corvus monedula (18.3%), rook Corvus frugilegus (15.9 %), lapwing Vanellus vanellus (6.2%). Moreover, it was found, that starlings constituted the most serious threat. It resulted from their relatively high attendance at the runway (about 300 individuals). Possible repellent techniques concerning of the Deblin military airfield were discussed. The analysis of the birds’ concentration depending on the altitude, part of the day, year, part of the airfield constituted a base to work out critical flight phase and appropriate procedures to prevent bird strikes.

Keywords: airport, bird strikes, flight safety, preventive methods

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Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

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Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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Authors: Grace Titilayo, Kolawole-Amao

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Influence and authority of law within society should be respected by all and sundry regardless of individual status. Rule of law implies that every citizen is subject to the law. In a society governed by the rule of law, government and its officials and agents are also held subject to and accountable under the law. Law should not be employed to suit individual tenets. Where the rule of law operates, the government is the government of law and not of men. Corruption is a factor that kills the growth of the rule of law. Where corruption flourishes, the rule of law fails, simply put, corruption is a threat to the rule of law. It bastardized and undermines the rule of law and good governance principles - where men rule at their discretion rather than the use of the rule of law which makes governance processes ineffective. Corruption is prevalent all over the world, and has extremely far reaching effects. Many of the world’s greatest challenges have been amplified by corruption, for example poverty, unequal distribution of wealth and resources, and world hunger and it weakens the application and the entrenchment of the rule of law. It saps citizens' trust in their governments and undercuts government credibility. This paper will discuss the rule of law in the present democratic system in Nigeria, the impact of corruption on the rule of law in Nigeria and how corruption undermines and subverts the entrenchment of the rule of law in the present day Nigeria.

Keywords: rule of law, corruption, Nigeria, influence, authority

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Authors: Sinead Impey, Gaye Stephens, Declan O’Sullivan

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Mitigating organisational knowledge loss presents challenges for knowledge managers. Expert knowledge is embodied in people and captured in ‘routines, processes, practices and norms’ as well as in the paper system. These knowledge stores have limitations in so far as they make knowledge diffusion beyond geography or over time difficult. However, technology could present a potential solution by facilitating the capture and management of expert knowledge in a codified and sharable format. Before it can be digitised, however, the knowledge of healthcare experts must be captured. Methods: As a first step in a larger project on this topic, a scoping review was conducted to identify how expert healthcare knowledge is captured digitally. The aim of the review was to identify current healthcare knowledge capture practices, identify gaps in the literature, and justify future research. The review followed a scoping review framework. From an initial 3,430 papers retrieved, 22 were deemed relevant and included in the review. Findings: Two broad approaches –direct and indirect- with themes and subthemes emerged. ‘Direct’ describes a process whereby knowledge is taken directly from subject experts. The themes identified were: ‘Researcher mediated capture’ and ‘Digital mediated capture’. The latter was further distilled into two sub-themes: ‘Captured in specified purpose platforms (SPP)’ and ‘Captured in a virtual community of practice (vCoP)’. ‘Indirect’ processes rely on extracting new knowledge using artificial intelligence techniques from previously captured data. Using this approach, the theme ‘Generated using artificial intelligence methods’ was identified. Although presented as distinct themes, some papers retrieved discuss combining more than one approach to capture knowledge. While no approach emerged as superior, two points arose from the literature. Firstly, human input was evident across themes, even with indirect approaches. Secondly, a range of challenges common among approaches was highlighted. These were (i) ‘Capturing an expert’s knowledge’- Difficulties surrounding capturing an expert’s knowledge related to identifying the ‘expert’ say from the very experienced and how to capture their tacit or difficult to articulate knowledge. (ii) ‘Confirming quality of knowledge’- Once captured, challenges noted surrounded how to validate knowledge captured and, therefore, quality. (iii) ‘Continual knowledge capture’- Once knowledge is captured, validated, and used in a system; however, the process is not complete. Healthcare is a knowledge-rich environment with new evidence emerging frequently. As such, knowledge needs to be reviewed, updated, or removed (redundancy) as appropriate. Although some methods were proposed to address this, such as plausible reasoning or case-based reasoning, conclusions could not be drawn from the papers retrieved. It was, therefore, highlighted as an area for future research. Conclusion: The results described two broad approaches – direct and indirect. Three themes were identified: ‘Researcher mediated capture (Direct)’; ‘Digital mediated capture (Direct)’ and ‘Generated using artificial intelligence methods (Indirect)’. While no single approach was deemed superior, common challenges noted among approaches were: ‘capturing an expert’s knowledge’, ‘confirming quality of knowledge’, and ‘continual knowledge capture’. However, continual knowledge capture was not fully explored in the papers retrieved and was highlighted as an important area for future research. Acknowledgments: This research is partially funded by the ADAPT Centre under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.

Keywords: expert knowledge, healthcare, knowledge capture and knowledge management

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: R. S. Remya, U. S. Sethulekshmi

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Detecting the authenticity of a video is an important issue in digital forensics as Video is used as a silent evidence in court such as in child pornography, movie piracy cases, insurance claims, cases involving scientific fraud, traffic monitoring etc. The biggest threat to video data is the availability of modern open video editing tools which enable easy editing of videos without leaving any trace of tampering. In this paper, we propose an efficient passive method for inter-frame video tampering detection, its type and location by estimating the optical flow of wavelet features of adjacent frames and thresholding the variation in the estimated feature. The performance of the algorithm is compared with the z-score thresholding and achieved an efficiency above 95% on all the tested databases. The proposed method works well for videos with dynamic (forensics) as well as static (surveillance) background.

Keywords: discrete wavelet transform, optical flow, optical flow variation, video tampering

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Authors: Isa Muhammad Zumo

Abstract:

Malaria is one of the worst illnesses that may affect humans. It is typically transmitted by the bite of a female Anopheles mosquito and is caused by parasitic protozoans from the Plasmodium parasite. Government and non-governmental organizations made numerous initiatives to combat the threat of malaria in communities. Nevertheless, the necessary attention was not paid to accurate and current information regarding the size and location of these favourable locations for mosquito development. Because mosquitoes can only reproduce in specific habitats with surface water, this study will locate and map those favourable sites that act as mosquito breeding grounds. Spatial and attribute data relating to favourable mosquito breeding places will be collected and analysed using Geographic Information Systems (GIS). The major findings will be in five classes, showing the vulnerable and risky areas for malaria cases. These risk categories are very high, high, moderate, low, and extremely low vulnerable areas. The maps produced by this study will be of great use to the health department in combating the malaria pandemic.

Keywords: Malaria, vulnerability, mapping, space, Damaturu

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Authors: Muzammil Dar

Abstract:

The confluence of trans-national interests and divergent approaches followed by multiple actors has surrounded the Indo-Pacific region with myriad of strategic complexes- Geo-Political, Geo-economic, and security. This paper has thus made a humble attempt to understand the Indo-Pacific strategic predicament from Asia-Pacific perspective. The portmanteau of Indo-Pacific strategic gamble has multiple actors from global powers to regional actors. On the indo-pacific waters, not only flow trade relations, but the tides of conflicts and controversies are striking these actors against each other. The alliance formation and infrastructure building has built-in threat perceptions from rivals vice-versa. The assertiveness of China as a reality and India’s ideological doctrine of peace and friendship, as well as American rebalancing against China, could be seen as clear and bright on the Indo-Pacific strategic portmanteau. ASEAN and Japan, too, have oscillating posturing in the strategic dilemma. The aim and objective of the paper are to sketch out the prospectus and prejudices of Indo-pacific strategic complex.

Keywords: Indo Pacific, Asia Pacific, security and growth for all in the region, SAGAR, ASEAN China

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Authors: R. Rama Kishore, Sunesh

Abstract:

Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

Procedia PDF Downloads 350

Authors: Nibedita Pani, Vishnu Tejani, T. S. Anantha Singh

Abstract:

Water pollution resulting from discharge of partial/not treated textile wastewater containing high carbon and nitrogen pollutants pose a huge threat to the environment, ecosystem, and human health. It is essential to remove carbon- and nitrogen-based organic pollutants more effectively from industrial wastewater before discharging. The present study focuses on removal of carbon-based pollutant in particular COD (chemical oxygen demand) and nitrogen-based pollutants, in particular, ammoniacal nitrogen by Fenton oxidation process using Fe²⁺ and H₂O₂ as reagents. The study was carried out with high strength wastewater containing initial COD 5632 mg/L and NH⁴⁺-N 1372 mg/L. The major operating condition like pH was varied between 1.0 to 4.0. The maximum degradation was obtained at pH 3.0 taking the molar ratio of Fe²⁺/H₂O₂ as 1:1. At this pH, the removal efficiencies of COD and ammoniacal nitrogen were found to be 77.27% and 74.9%, respectively. The Fenton process can be the best alternative for the simultaneous removal of COD and NH4+-N from industrial wastewater.

Keywords: ammoniacal nitrogen, COD, Fenton oxidation, industrial wastewater

Procedia PDF Downloads 183

Authors: Stephanie M. De Oliveira

Abstract:

For a long time, migrations are characterized as a difficult problem to solve. Various phenomena throughout human history caused personnel migrations, whether by the free will of migrants or not. Nowadays, governments that seek to give these people protection and dignity, either to asylum or to build a new life in a different country, make refugee protection. At present, a large amount of people, have been crossing their country's borders by land, air or sea, becoming refugees and seeking a new life away from fear, threat or violence they suffered in their country of origin. It is known that some countries have already instituted rights and rules for refugees who wish to become citizens in the country to which they immigrated, even though this is not what happens in most cases. The article will be based on research made with UN Refugee Agency (UNHCR) material as well as will analyze the interaction of the Turkish government with the European Union. Since Turkey is not part of the Union, it will be understood how the interaction was made, as well as the search for consensus, and not only humanitarian but also financial aid. The treatment of refugees and the defense of human rights within the country will also be considered.

Keywords: refugees, Turkey, asylum seekers, United Nations

Procedia PDF Downloads 350

Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

Abstract:

Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

Procedia PDF Downloads 145

Authors: Paul Anyaogu, E. U. M. Igbo

Abstract:

This study examines the public view on child street hawking in Aba Urban, Abia State, Nigeria, its causes and effect on the child participant and society at large. The study tends to investigate the influence of socioeconomic status on child street hawking. The current situation reflects a chronic urban poverty, which disposed of parents/guardians to send their children and wards of school age to income yielding activities. A social survey research design was employed to select the respondents. A total of 1,108 questionnaires were administered to the respondents of 18 years and above and 1,038 were retrieved. Also, 24 in-depth interviews were conducted in the study area. The findings revealed that child street hawking is on the increase and a serious threat to social cohesion and national security. The study also revealed that poverty is a major cause of child street hawking. The study recommends that government should create job opportunities for urban dwellers, as well as provide social amenities and also put up poverty alleviation/eradication programmes for the people.

Keywords: Aba Urban, child street hawking, dangers, disposition, poverty

Procedia PDF Downloads 267