Search results for: vulnerability intelligence

Authors: Martin Popescu D. Dana Maria

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The aims of this research are to broaden the study on the relationship between emotional intelligence and counterproductive work behavior (CWB). The study sample consisted in 441 Romanian employees from companies all over the country. Data has been collected through web surveys and processed with SPSS. The results indicated an average correlation between the two constructs and their sub variables, employees with a high level of emotional intelligence tend to be less aggressive. In addition, labeling was considered an individual difference which has the power to influence the level of employee aggression. A regression model was used to underline the importance of emotional intelligence together with labeling as predictors of CWB. Results have shown that this regression model enforces the assumption that labeling and emotional intelligence, taken together, predict CWB. Employees, who label themselves as victims and have a low degree of emotional intelligence, have a higher level of CWB.

Keywords: aggression, CWB, emotional intelligence, labeling

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Authors: Suresh Kumar Bandooni, Mirana Laishram

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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.

Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya

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Authors: Azucena Yearby

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This study examined if cultural intelligence can be developed through the study of a foreign language. Specifically, the study sought to determine if strategies such as the Arts/History, Vocabulary and Real or Simulated Experiences have an effect on the development of cultural intelligence in the foreign language classroom. Students enrolled in Spanish 1114 or level 1 Spanish courses at the University of Central Oklahoma (UCO) completed Linn Van Dyne’s 20-item questionnaire that measures Cultural Intelligence (CQ). Results from the study indicated a slight cultural intelligence increase in those students who received an intervention. Therefore, the study recommended that foreign language educators implement the considered strategies in the classroom in order to increase their students’ cultural intelligence.

Keywords: cultural competency, cultural intelligence, foreign language, language

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Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente

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The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.

Keywords: Damage scenarios, masonry buildings, old city center, seismic vulnerability, vulnerability index

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Authors: Nadir A. Carreon, Christa Sonderer, Aakarsh Rao, Roman Lysecky

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With the advent of complex software and increased connectivity, the security of life-critical medical devices is becoming an increasing concern, particularly with their direct impact on human safety. Security is essential, but it is impossible to develop completely secure and impenetrable systems at design time. Therefore, it is important to assess the potential impact on the security and safety of exploiting a vulnerability in such critical medical systems. The common vulnerability scoring system (CVSS) calculates the severity of exploitable vulnerabilities. However, for medical devices it does not consider the unique challenges of impacts to human health and privacy. Thus, the scoring of a medical device on which human life depends (e.g., pacemakers, insulin pumps) can score very low, while a system on which human life does not depend (e.g., hospital archiving systems) might score very high. In this paper, we propose a medical vulnerability scoring system (MVSS) that extends CVSS to address the health and privacy concerns of medical devices. We propose incorporating two new parameters, namely health impact, and sensitivity impact. Sensitivity refers to the type of information that can be stolen from the device, and health represents the impact on the safety of the patient if the vulnerability is exploited (e.g., potential harm, life-threatening). We evaluate fifteen different known vulnerabilities in medical devices and compare MVSS against two state-of-the-art medical device-oriented vulnerability scoring systems and the foundational CVSS.

Keywords: common vulnerability system, medical devices, medical device security, vulnerabilities

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Authors: Enze Zhang

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Large numbers of inter-basin water transfer (IBWT) projects are constructed or proposed all around the world as solutions to water distribution and supply problems. Nowadays, as climate change warms the atmosphere, alters the hydrologic cycle, and perturbs water availability, large scale IBWTs which are sensitive to these water-related changes may carry significant risk. Given this reality, IBWTs have elicited great controversy and assessments of vulnerability to climate change are urgently needed worldwide. In this paper, we consider the South-to-North Water Transfer Project (SNWTP) in China as a case study, and introduce a bottom-up vulnerability assessment framework. Key hazards and risks related to climate change that threaten future water availability for the SNWTP are firstly identified. Then a performance indicator is presented to quantify the vulnerability of IBWT by taking three main elements (i.e., sensitivity, adaptive capacity, and exposure degree) into account. A probabilistic Budyko model is adapted to estimate water availability responses to a wide range of possibilities for future climate conditions in each region of the study area. After bottom-up quantifying the vulnerability based on the estimated water availability, our findings confirm that SNWTP would greatly alleviate geographical imbalances in water availability under some moderate climate change scenarios but raises questions about whether it is a long-term solution because the donor basin has a high level of vulnerability due to extreme climate change.

Keywords: vulnerability, climate change, inter-basin water transfer, bottom-up

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Authors: Umesh Kumar Singh, Chanchala Joshi

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With increasing dependency on IT infrastructure, the main objective of a system administrator is to maintain a stable and secure network, with ensuring that the network is robust enough against malicious network users like attackers and intruders. Security risk management provides a way to manage the growing threats to infrastructures or system. This paper proposes a framework for risk level estimation which uses vulnerability database National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) and the Common Vulnerability Scoring System (CVSS). The proposed framework measures the frequency of vulnerability exploitation; converges this measured frequency with standard CVSS score and estimates the security risk level which helps in automated and reasonable security management. In this paper equation for the Temporal score calculation with respect to availability of remediation plan is derived and further, frequency of exploitation is calculated with determined temporal score. The frequency of exploitation along with CVSS score is used to calculate the security risk level of the system. The proposed framework uses the CVSS vectors for risk level estimation and measures the security level of specific network environment, which assists system administrator for assessment of security risks and making decision related to mitigation of security risks.

Keywords: CVSS score, risk level, security measurement, vulnerability category

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Authors: Mehrnoosh Abouzari

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Artificial intelligence has covered all areas of human life and has helped or replaced many jobs. One of the areas of application of artificial intelligence in the police is to detect crime, identify the accused or victim and prove the crime. It will play an effective role in implementing preventive justice and creating security in the community, and improving judicial decisions. This will help improve the performance of the police, increase the accuracy of criminal investigations, and play an effective role in preventing crime and high-risk behaviors in society. This article presents and analyzes the capabilities and capacities of artificial intelligence in police and similar examples used worldwide to prove the necessity of using artificial intelligence in the police. The main topics discussed include the performance of artificial intelligence in crime detection and prediction, the risk capacity of criminals and the ability to apply arbitray institutions, and the introduction of artificial intelligence programs implemented worldwide in the field of criminal investigation for police.

Keywords: police, artificial intelligence, forecasting, prevention, software

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Authors: Fathul Mubin, Budi E. Nurcahya

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In 2006, a large earthquake ever occurred in the province of Yogyakarta, which caused considerable damage. This is the basis need to investigate the seismic vulnerability index in around of the earthquake zone. This research is called microzonation of earthquake hazard. This research has been conducted at the site and surrounding of Prambanan Temple, includes homes and civil buildings. The reason this research needs to be done because in the event of an earthquake in 2006, there was damage to the temples at Prambanan temple complex and its surroundings. In this research, data collection carried out for 60 minutes using three component seismograph measurements at 165 points with spacing of 1000 meters. The data recorded in time function were analyzed using the spectral ratio method, known as the Horizontal to Vertical Spectral Ratio (HVSR). Results from this analysis are dominant frequency (Fg) and maximum amplification factor (Ag) are used to obtain seismic vulnerability index. The results of research showed the dominant frequency range from 0.5 to 30 Hz and the amplification is in interval from 0.5 to 9. Interval value for seismic vulnerability index is 0.1 to 50. Based on distribution maps of seismic vulnerability index and impact of buildings damage seemed for suitability. For further research, it needs to survey to the east (klaten) and south (Bantul, DIY) to determine a full distribution maps of seismic vulnerability index.

Keywords: amplification factor, dominant frequency, microzonation analysis, seismic vulnerability index

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Authors: Vanisa Damayanti Yuningsih

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Employee professionalism is certainly the hope for every company to create a good working environment. Emotional intelligence is one of the factors that determine the success of professionalism, for, in emotional intelligence, an employee can control his ego and can understand and understand his coworkers and thus create a dynamic environment in which to work. Each employee is encouraged to have professionalism in order to optimize his resources. This professionalism is shown by employees being able to do their work and taking responsibility in their profession by involving controlled feelings and emotions. The problem which is drawn from this research is how emotional intelligence can affect the professional attitudes of employees. The purpose of this research is to find out how far emotional intelligence goes in the professional manner of employees.

Keywords: professionalism, emotional intelligence, work environment, company

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Authors: Somayyeh Karimiyan

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To evaluate the seismic vulnerability of vital offshore structures with the highest possible precision, Nonlinear Time History Analyses (NLTHA), is the most reliable method. However, since it is very time-consuming, a quick procedure is greatly desired. This paper presents a quick method by combining the Push Over Analysis (POA) and the NLTHA. The POA is preformed first to recognize the more critical members, and then the NLTHA is performed to evaluate more precisely the critical members’ vulnerability. The proposed method has been applied to jacket type structure. Results show that combining POA and NLTHA is a reliable seismic evaluation method, and also that none of the earthquake characteristics alone, can be a dominant factor in vulnerability evaluation.

Keywords: jacket structure, seismic evaluation, push-over and nonlinear time history analyses, critical members

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Authors: Bahadir Aydin

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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.

Keywords: information, intelligence cycle, knowledge, tacit Knowledge

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Authors: Evangelos Tsakalos, Maria Kazantzaki, Eleni Filippaki, Yannis Bassiakos

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The coastal areas of the Mediterranean have been extensively affected by the transgressive event that followed the Last Glacial Maximum, with many studies conducted regarding the stratigraphic configuration of coastal sediments around the Mediterranean. The coastal zone of the Messologi area, western Greece, consists of low relief beaches containing low cliffs and eroded dunes, a fact which, in combination with the rising sea level and tectonic subsidence of the area, has led to substantial coastal. Coastal vulnerability assessment is a useful means of identifying areas of coastline that are vulnerable to impacts of climate change and coastal processes, highlighting potential problem areas. Commonly, coastal vulnerability assessment takes the form of an ‘index’ that quantifies the relative vulnerability along a coastline. Here we make use of the coastal vulnerability index (CVI) methodology by Thieler and Hammar-Klose, by considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates, and mean significant wave height as well as mean tide range to assess the present-day vulnerability of the coastal zone of Messologi area. In light of this, an impact assessment is performed under three different sea level rise scenarios, and adaptation measures to control climate change events are proposed. This study contributes toward coastal zone management practices in low-lying areas that have little data information, assisting decision-makers in adopting best adaptations options to overcome sea level rise impact on vulnerable areas similar to the coastal zone of Messologi.

Keywords: coastal vulnerability index, coastal erosion, sea level rise, GIS

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Shabnam

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The purpose of this study was to see importance of successful intelligence in education which can enhance achievement. There are a number of researches which have tried to apply psychological theories of education and many researches emphasized the role of thinking and intelligence. While going through the various researches, it was found that many students could learn more effectively than they do, if they were taught in a way that better matched their patterns of abilities. Attempts to apply psychological theories to education can falter on the translation of the theory into educational practice. Often, this translation is not clear. Therefore, when a program does not succeed, it is not clear whether the lack of success was due to the inadequacy of the theory or the inadequacy of the implementation of the theory. A set of basic principles for translating a theory into practice can help clarify just what an educational implementation should (and should not) look like. Sternberg’s theory of successful intelligence; analytical, creative and practical intelligence provides a way to create such a match. The results suggest that theory of successful intelligence provides successful interventions in classrooms and provides a proven model for gifted education. This article presents principles for translating a triarchic theory of successful intelligence into educational practice.

Keywords: successful intelligence, analytical, creative and practical intelligence, achievement, success, resilience

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Richard Wolfel, Amy Richmond

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Urban resilience and vulnerability are critical concepts in the modern city due to the increased sociocultural, political, economic, demographic, and environmental stressors that influence current urban dynamics. Urban scholars need help explaining urban resilience and vulnerability. First, cities are dominated by people, which is challenging to model, both from an explanatory and a predictive perspective. Second, urban regions are highly recursive in nature, meaning they not only influence human action, but the structures of cities are constantly changing due to human actions. As a result, explanatory frameworks must continuously evolve as humans influence and are influenced by the urban environment in which they operate. Finally, modern cities have populations, sociocultural characteristics, economic flows, and environmental impacts on order of magnitude well beyond the cities of the past. As a result, the frameworks that seek to explain the various functions of a city that influence urban resilience and vulnerability must address the complex adaptive nature of cities and the interaction of many distinct factors that influence resilience and vulnerability in the city. This project develops a taxonomy and framework for organizing and explaining urban vulnerability. The framework is built on a well-established political development model that includes six critical classes of urban dynamics: political presence, political legitimacy, political participation, identity, production, and allocation. In addition, the framework explores how environmental security and technology influence and are influenced by the six elements of political development. The framework aims to identify key tipping points in society that act as influential agents of urban vulnerability in a region. This will help analysts and scholars predict and explain the influence of both physical and human geographical stressors in a dense urban area.

Keywords: urban resilience, vulnerability, sociocultural stressors, political stressors

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Authors: Mounir Ait Belkacem, Mehdi Boukri, Omar Amellal, Nacim Yousfi, Abderrahmane Kibboua, Med Naboussi Farsi, Mounir Naili

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The North of Algeria is located in a seismic zone, then earthquakes are probably the most likely natural disaster that would lead to major lifeline disruption. The adequate operation of lifelines is vital for the economic development of regions under moderate to high seismic activity. After an earthquake, the proper operation of all vital systems is necessary, for instance hospitals for medical attention of the wounded and highways for communication and assistance for victims.In this work we apply the knowledge of pipeline vulnerability to the water supply system, sanitary sewer pipelines (waste water), and telephone in Constantine (Algeria).

Keywords: lifeline, earthquake, vulnerability, pipelines

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Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises has been growing at a phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several artificial intelligence (AI/ML) and business intelligence (BI) tools and technologies available in the marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information, and intelligence components, and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise

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Authors: Sherry Ann Ganase, Sandra Sookram

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This study examines adaptation measures and factors that influence adaptation decisions in Bequia by using multiple linear regression and a structural equation model. Using survey data, the results suggest that households are knowledgeable and concerned about climate change but lack knowledge about the measures needed to adapt. The findings from the SEM suggest that a positive relationship exist between vulnerability and adaptation, vulnerability and perception, along with a negative relationship between perception and adaptation. This suggests that being aware of the terms associated with climate change and knowledge about climate change is insufficient for implementing adaptation measures; instead the risk and importance placed on climate change, vulnerability experienced with household flooding, drainage and expected threat of future sea level are the main factors that influence the adaptation decision. The results obtained in this study are beneficial to all as adaptation requires a collective effort by stakeholders.

Keywords: adaptation, Bequia, multiple linear regression, structural equation model

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Authors: Adandé Belarmain Fandohan

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Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: Neta Kela Madar, Tali Teeni-Harari, Tamar Icekson, Yaron Sela

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This paper proposes and empirically tests a theoretical model positing relationships between dispositional optimism, emotional intelligence, and entrepreneurial intention. To author's best knowledge, this study examined for the first time the role of dispositional optimism together with emotional intelligence as predictors of entrepreneurial intentions. The study findings suggest that optimism may increase entrepreneurial intentions indirectly by enhancing emotional intelligence/ model formulation is based on a random survey of students (N= 227). Model parameter estimation was supported by Structural Equation Modeling (SEM). Results indicate that students’ optimism and emotional intelligence are associated with increased levels of entrepreneurial intention. Additionally, the present study argues that emotional intelligence mediates the positive relationship between optimism and entrepreneurial intention. Theoretical and practical implications of this model are discussed.

Keywords: entrepreneurial intentions, emotional intelligence, optimism, dispositional optimism

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Authors: Nadjah Chergui, Narhimene Boustia

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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: context, default, exception, vulnerability

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Authors: Zerihun Yohannes Amare Id, Bernhard Freyer, Ky Serge Stephane, Ouéda Adama, Blessing Mudombi, Jean Nzuma, Mekonen Getachew Abebe, Adane Tesfaye, Birtukan Atinkut Asmare, Tesfahun Asmamaw Kassie

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The study was conducted in Ethiopia (Zege Catchment) (ZC), Zimbabwe (Upper Save Catchment) (USC), and Burkina Faso (Nakambe Catchment) (NC). The study utilized a quantitative approach with 180 participants and complemented it with qualitative methods, including 33 key informant interviews and 6 focus group discussions. Households in ZC (58%), NC (55%), and US (40%) do not cover their household food consumption from crop production. The households rely heavily on perennial cash crops rather than annual crop production. Exposure indicators in ZC (0.758), USC (0.774), and NC (0.944), and sensitivity indicators in ZC (0.849) and NC (0.937) show statistically significant and high correlation with vulnerability. In the USC, adaptive capacity (0.746) and exposure (0.774) are also statistically significant and highly correlated with vulnerability. Vulnerability levels of the NC are very high (0.75) (0.85 female and 0.65 male participants) compared to the USC (0.66) (0.69 female and 0.61 male participants) and ZC (0.47) (0.34 female and 0.58 male participants). Female-headed households had statistically significantly lower vulnerability index compared to males in ZC, while male-headed households had statistically significantly lower vulnerability index compared to females in USC and NC. The reason is land certification in ZC (80%) is higher than in the US (10%) and NC (8%). Agroforestry practices variables across the study catchments had statistically significant contributions to households' adaptive capacity. We conclude that agroforestry practices do have substantial benefits in increasing women's adaptive capacity and reducing their vulnerability to climate change and food insecurity.

Keywords: climate change vulnerability, agroforestry, gender, food security, Sub-Saharan Africa

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Authors: Nitin Joseph

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Objectives: This study was done to assess emotional intelligence levels and to find out its association with socio demographic variables and perceived stress among medical students. Material and Methods: This study was done among first and second year medical students. Data was collected using a self-administered questionnaire. Results: Emotional intelligence scores was found to significantly increase with age of the participants (F=2.377, P < 0.05). Perceived stress was found to be significantly more among first year (t=1.997, P=0.05). Perceived stress was found to significantly decrease with increasing emotional intelligence scores (r = – 0.226, P < 0.001). Conclusion: First year students were found to be more vulnerable to stress than their seniors probably due to lesser emotional intelligence. As both these parameters are related, ample measures to improve emotional intelligence needs to be supported in the training curriculum of beginners so as to make them more stress free during early student life.

Keywords: emotional intelligence, medical students, perceived stress, socio demographic variables

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Authors: Rosario Carmona

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This article aims to discuss the importance of indigenous people participation in climate change mitigation and adaptation. Specifically, it analyses different understandings of climate vulnerability among diverse actors involved in climate change policies in Chile: indigenous people, state officials, and academics. These data were collected through participant observation and interviews conducted during October 2017 and January 2019 in Chile. Following Karen O’Brien, there are two types of vulnerability, outcome vulnerability and contextual vulnerability. How vulnerability to climate change is understood determines the approach, which actors are involved and which knowledge is considered to address it. Because climate change is a very complex phenomenon, it is necessary to transform the institutions and their responses. To do so, it is fundamental to consider these two perspectives and different types of knowledge, particularly those of the most vulnerable, such as indigenous people. For centuries and thanks to a long coexistence with the environment, indigenous societies have elaborated coping strategies, and some of them are already adapting to climate change. Indigenous people from Chile are not an exception. But, indigenous people tend to be excluded from decision-making processes. And indigenous knowledge is frequently seen as subjective and arbitrary in relation to science. Nevertheless, last years indigenous knowledge has gained particular relevance in the academic world, and indigenous actors are getting prominence in international negotiations. There are some mechanisms that promote their participation (e.g., Cancun safeguards, World Bank operational policies, REDD+), which are not absent from difficulties. And since 2016 parties are working on a Local Communities and Indigenous Peoples Platform. This paper also explores the incidence of this process in Chile. Although there is progress in the participation of indigenous people, this participation responds to the operational policies of the funding agencies and not to a real commitment of the state with this sector. The State of Chile omits a review of the structure that promotes inequality and the exclusion of indigenous people. In this way, climate change policies could be configured as a new mechanism of coloniality that validates a single type of knowledge and leads to new territorial control strategies, which increases vulnerability.

Keywords: indigenous knowledge, climate change, vulnerability, Chile

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Authors: P. W. Tsai, J. W. Chen, C. W. Chen, C. Y. Chen

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In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.

Keywords: half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method

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Authors: Ardalan Tofighi Soleimandarabi

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Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

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Authors: Chao Xu

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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Bernabeo R. Alberto

Abstract:

With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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