A Socio-Technical Approach to Cyber-Risk Assessment

Evaluating the levels of cyber-security risks within an enterprise is most important in protecting its information system, services and all its digital assets against security incidents (e.g. accidents, malicious acts, massive cyber-attacks). The existing risk assessment methodologies (e.g. eBIOS, OCTAVE, CRAMM, NIST-800) adopt a technical approach considering as attack factors only the capability, intention and target of the attacker, and not paying attention to the attacker’s psychological profile and personality traits. In this paper, a socio-technical approach is proposed in cyber risk assessment, in order to achieve more realistic risk estimates by considering the personality traits of the attackers. In particular, based upon principles from investigative psychology and behavioural science, a multi-dimensional, extended, quantifiable model for an attacker’s profile is developed, which becomes an additional factor in the cyber risk level calculation.

The Flashnews as a Commercial Session of Political Marketing: The Content Analysis of the Embedded Political Narratives in Non-Political Media Products

Political communication in Hungary has undergone a significant change in the 2010s. One element of the transformation is the Flashnews. This media product was launched in March 2015 and since then 40-50 blocks are broadcasted, daily, on 5 channels. Flashnews blocks are condensed news sessions, containing the summary of political narratives. It starts with the introduction of the narrator, then, usually four news topics are presented and, finally, the narrator concludes the block. The block lasts only one minute and, therefore, it provides a blink session into the main narratives of political communication at the time. Beyond its rapid pace, what makes its avoidance difficult is that these blocks are always in the first position in the commercial break of a non-political media product. Although it is only one minute long, its significance is high. The content of the Flashnews reflects the main governmental narratives and, therefore, the Flashnews is part of the agenda-setting capacity of political communication. It reaches media consumers who have limited knowledge and interest in politics, and their use of media products is not politically related. For this audience, the Flashnews pops up in the same way as commercials. Due to its structure and appearance, the impact of Flashnews seems to be similar to commercials, imbedded into the break of media products. It activates existing knowledge constructs, builds up associational links and maintains their presence in a way that the recipient is not aware of the phenomenon. The research aims to examine the extent to which the Flashnews and the main news narratives are identical in their content. This aim is realized with the content analysis of the two news products by examining the Flashnews and the evening news during main sport events from 2016 to 2018. The initial hypothesis of the research is that Flashnews is a contribution to the news management technique for an effective articulation of political narratives in public service media channels.

Modelling for Roof Failure Analysis in an Underground Cave

Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Optimal and Critical Path Analysis of State Transportation Network Using Neo4J

A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Prevalence, Associated Factors, and Help-Seeking Behavior of Psychological Distress among International Students at the National University of Malaysia

Depression, anxiety, and stress are associated with decreased role functioning, productivity, and quality of life. International students are more prone to psychological distress as they face many stressors while studying abroad. The objectives of the study were to determine the prevalence and associated factors of depression, anxiety, and stress among international students, their help-seeking behavior, and their awareness of the available on-campus mental support services. A cross-sectional study with a purposive sampling method was performed on 280 international students at Universiti Kebangsaan Malaysia (UKM) between the age of 18 and 35 years. The Depression Anxiety Stress Scale-21 (DASS-21) questionnaire was used anonymously to assess the mental health of students. Socio-demographic, help-seeking behavior, and awareness data were obtained. Independent sample t-test, one-way ANOVA test, and multiple linear regression were used to explore associated factors. The overall prevalence of depression, anxiety, and stress among international students were 58.9%, 71.8%, and 53.9%, respectively. Age was significantly associated with depression and anxiety. Ethnicity showed a significant association with depression and stress. No other factors were found to be significantly associated with psychological distress. Only 9.6% of the international students had sought help from on-campus mental support services. Students who were aware of the presence of such services were only 21.4% of the participants. In conclusion, this study addressed the gap in the literature on the mental health of international students and provided data that could be used in intervention programs to improve the mental health of the increasing number of international students in Malaysia.

The Net as a Living Experience of Distance Motherhood within Italian Culture

Motherhood is an existential human relationship that lasts for the whole life and is always interwoven with subjectivity and culture. As a result of the brain drain, the motherhood becomes motherhood at distance. Starting from the hypothesis that re-signification of the mother at distance practices is culturally relevant; the research aims to understand the experience of mother at a distance in order to extrapolate the strategies of management of the empty nest. Specifically, the research aims to evaluate the experience of a brain drain’s mother, who created a blog that intends to take care of other parents at a distance. Actually, the blog is the only artifact symbol of the Italian culture of motherhood at distance. In the research, a Netnographic Analysis of the blog mammedicervelliinfuga.com is offered with the aim of understanding if the online world becomes an opportunity to manage the role of mother at a distance. A narrative interview with the blog creator was conducted and then the texts were analyzed by means of a Diatextual Analysis approach. It emerged that the migration projects of talented children take on different meanings and representations for parents. Thus, it is shown that the blog becomes a new form of understanding and practicing motherhood at a distance.

Maximizing Nitrate Absorption of Agricultural Waste Water in a Tubular Microalgae Reactor by Adapting the Illumination Spectrum

Microalgae-based photobioreactors (PBR) for Life Support Systems (LSS) are currently being investigated for future space missions such as a crewed base on planets or moons. Biological components may help reducing resupply masses by closing material mass flows with the help of regenerative components. Via photosynthesis, the microalgae use CO2, water, light and nutrients to provide oxygen and biomass for the astronauts. These capabilities could have synergies with Earth applications that tackle current problems and the developed technologies can be transferred. For example, a current worldwide discussed issue is the increased nitrate and phosphate pollution of ground water from agricultural waste waters. To investigate the potential use of a biological system based on the ability of the microalgae to extract and use nitrate and phosphate for the treatment of polluted ground water from agricultural applications, a scalable test stand is being developed. This test stand investigates the maximization of intake rates of nitrate and quantifies the produced biomass and oxygen. To minimize the required energy, for the uptake of nitrate from artificial waste water (AWW) the Flashing Light Effect (FLE) and the adaption of the illumination spectrum were realized. This paper describes the composition of the AWW, the development of the illumination unit and the possibility of non-invasive process optimization and control via the adaption of the illumination spectrum and illumination cycles. The findings were a doubling of the energy related growth rate by adapting the illumination setting.

Multi-Agent Searching Adaptation Using Levy Flight and Inferential Reasoning

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Adaptive Envelope Protection Control for the below and above Rated Regions of Wind Turbines

This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Exploring Dynamics of Regional Creative Economy

The aim of this paper is to build a vision of the utilization of creative industry competences in industrial and services firms connected to Kymenlaakso region, Finland, smart specialization focus areas. Research indicates that creativity and the use of creative industry’s inputs can enhance innovation and competitiveness. Currently creative methods and services are underutilized in regional businesses and the added value they provide is not well grasped. Methodologically, the research adopts a qualitative exploratory approach. Data is collected in multiple ways including a survey, focus groups, and interviews. Theoretically, the paper contributes to the discussion about the use creative industry competences in regional development, and argues for building regional creative economy ecosystems in close co-operation with regional strategies and traditional industries rather than as treating regional creative industry ecosystem initiatives separate from them. The practical contribution of the paper is the creative vision for the use of regional authorities in updating smart specialization strategy as well as boosting industrial and creative & cultural sectors’ competitiveness. The paper also illustrates a research-based model of vision building.

Second Language Development with an Intercultural Approach: A Pilot Program Applied to Higher Education Students from a Escuela Normal in Atequiza, Mexico

The importance of developing multi-language abilities in our global society is noteworthy. However, the necessity, interest, and consciousness of the significance that the development of another language represents, apart from the mother tongue, is not always the same in all contexts as it is in multicultural communities, especially in rural higher education institutions immersed in small communities. Leading opportunities for digital interaction among learners from Mexico and abroad partners represents scaffolding towards, not only language skills development but also intercultural communicative competences (ICC). This study leads us to consider what should be the best approach to work while applying a program of ICC integrated into the practice of EFL. While analyzing the roots of the language, it is possible to obtain the main objective of learning another language, to communicate with a functional purpose, as well as attaching social practices to the learning process, giving a result of functionality and significance to the target language. Hence, the collateral impact that collaborative learning leads to, aims to contribute to a better global understanding as well as a means of self and other cultural awareness through intercultural communication. While communicating through the target language by online collaboration among students in platforms of long-distance communication, language is used as a tool of interaction to broaden students’ perspectives reaching a substantial improvement with the help of their differences. This process should consider the application of the target language in the inquiry of sociocultural information, expecting the learners to integrate communicative skills to handle cultural differentiation at the same time they apply the knowledge of their target language in a real scenario of communication, despite being through virtual resources.

Supervisor Controller-Based Colored Petri Nets for Deadlock Control and Machine Failures in Automated Manufacturing Systems

This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Banking Risk Management between the Prudential and the Operational Approaches

Since the nineties, all Moroccan banking institutions have to respect an arsenal of prudential ratios. The respect of these prudential measures aims to ensure the financial system stability. In order to do so, regulatory authorities tried to reduce the financial and operational risks incurred by the banking entities. Meanwhile, regulatory authorities demanded a balance sheet management work from banks. They also asked them to establish a management control system to manage operational risk, as well as an effort in terms of incurred risk-based commitments. Therefore, the prudential approach has a macroeconomic nature and it is presented as a determinant of the operational, microeconomic approach. This operational approach takes the form of a strategy that each banking entity must develop to manage the different banking risks. This study seeks to analyze the problem of risk management between the prudential and the operational approaches. It was processed through a literature review followed by an analysis of the Moroccan banking sector’s performance. At first, we will reconcile the inductive logic and then, the analytical one. The first approach consists of analyzing the phenomenon from a normative and conceptual perspective, while the second one will consist of considering the Moroccan banking system and analyzing the behavior of Moroccan banking entities in terms of risk management and performance. The results identified a favorable growth in terms of performance, despite the huge provisioning effort made to meet the international standards and the harmonization of the regulations.

Bold Headlines of Urban Eyescapes: A Computational Approach of Urban Mapping via Digital Surveying and Eye-Tracking Technologies

The sensory stimuli from the urban environment are often distinguished as subtle structures that derive from experiencing the city. The experience of the urban environment is also related to the social relationships and memories that complete the 'urban eyescapes' and the way individuals can recall them. Despite the fact that the consideration of urban sensory stimuli is part of urban design, currently the account of visual experience in urban studies is hard to be identified. This article explores ways of recording how the senses mediate one's engagement with the urban environment. This study involves an experiment in the urban environment of the Copenhagen city centre, with 20 subjects performing a walking task. The aim of the experiment is to categorize the visual 'Bold Headlined Stimuli’ (BHS) of the examined environment, using eye-tracking techniques. The analysis allows us to identify the Headlining Stimuli Process, (HSP) in the select urban environment. HSP is significantly mediated by body mobility and perceptual memories and has shown how urban stimuli influence the intelligibility and the recalling patterns of the urban characteristics. The results have yielded a 'Bold Headline list' of stimuli related to: the spatial characteristics of higher preference; the stimuli that are relevant to livability; and the spatial dimensions easier to recall. The data of BHS will be used in cross-disciplinary city analysis. In the future, these results could be useful in urban design, to provide information on how urban space affects the human activities.

A Constructivist Approach and Tool for Autonomous Agent Bottom-up Sequential Learning

During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Mapping the Digital Landscape: An Analysis of Party Differences between Conventional and Digital Policy Positions

Although digitization is a buzzword in almost every election campaign, the political parties leave voters largely in the dark about their specific positions on digital issues. In the run-up to the 2019 elections in Switzerland, the ‘Digitization Monitor’ project (DMP) was launched in order to change this situation. Within the framework of the DMP, all 4,736 candidates were surveyed about their digital policy positions and values. The DMP is designed as a digital policy supplement to the existing ‘smartvote’ voting advice application. This enabled a direct comparison of the digital policy attitudes according to the DMP with the topics of the ‘smartvote’ questionnaire which are comprehensive in content but mainly related to conventional policy areas. This paper’s main research goal is to analyze and visualize possible differences between conventional and digital policy areas in terms of response patterns between and within political parties. The analysis is based on dimensionality reduction methods (multidimensional scaling and principal component analysis) for the visualization of inter-party differences, and on standard deviation as a measure of variation for the evaluation of intra-party unity. The results reveal that digital issues show a lower degree of inter-party polarization compared to conventional policy areas. Thus, the parties have more common ground in issues on digitization than in conventional policy areas. In contrast, the study reveals a mixed picture regarding intra-party unity. Homogeneous parties show a lower degree of unity in digitization issues whereas parties with heterogeneous positions in conventional areas have more united positions in digital areas. All things considered, the findings are encouraging as less polarized conditions apply to the debate on digital development compared to conventional politics. For the future, it would be desirable if in further countries similar projects to the DMP could emerge to broaden the basis for conclusions.

A Goal-Driven Crime Scripting Framework

Crime scripting is a simple and effective crime modeling technique that aims to improve understanding of security analysts about security and crime incidents. Low-quality scripts provide a wrong, incomplete, or sophisticated understanding of the crime commission process, which oppose the purpose of their application, e.g., identifying effective and cost-efficient situational crime prevention (SCP) measures. One important and overlooked factor in generating quality scripts is the crime scripting method. This study investigates the problems within the existing crime scripting practices and proposes a crime scripting approach that contributes to generating quality crime scripts. It was validated by experienced crime scripters. This framework helps analysts develop better crime scripts and contributes to their effective application, e.g., SCP measures identification or policy-making.

Design and Māori Values: A Rebrand Project for the Social Enterprise Sector

This paper details a rebrand design project developed for a non-profitable organization called Te Roopu Waiora (TRW), which is currently located in Auckland, Aotearoa New Zealand. This social enterprise is dedicated to supporting the Māori community living with sensorial, physical and intellectual disabilities (whānau hauā). As part of a year three bachelor design brief, the rebrand project enabled students to reflect on Kaupapa Māori principles and appropriately address the values of the organisation. As such, the methodology used a pragmatic paradigm approach and mixed methods design practices involving a human-centred design to problem solving. As result, the student project culminated in the development in a range of cohesive design artefacts, aiming to improve the rentability and perception of the brand with the audience and stakeholders.

Model Free Terminal Sliding Mode with Gravity Compensation: Application to an Exoskeleton-Upper Limb System

This paper deals with a robust model free terminal sliding mode with gravity compensation approach used to control an exoskeleton-upper limb system. The considered system is a 2-DoF robot in interaction with an upper limb used for rehabilitation. The aim of this paper is to control the flexion/extension movement of the shoulder and the elbow joints in presence of matched disturbances. In the first part, we present the exoskeleton-upper limb system modeling. Then, we controlled the considered system by the model free terminal sliding mode with gravity compensation. A stability study is realized. To prove the controller performance, a robustness analysis was needed. Simulation results are provided to confirm the robustness of the gravity compensation combined with to the Model free terminal sliding mode in presence of uncertainties.