Quantifying the Second-Level Digital Divide on Sub-National Level

Digital divide, the gap in the access to the world of digital technologies and the socio-economic opportunities that they create is an important phenomenon of the XXI century. This gap may exist between countries, regions within a country or socio-demographic groups, creating the classes of “digital have and have nots”. While the 1st-level divide (the difference in opportunities to access the digital networks) was demonstrated to diminish with time, the issues of 2nd level divide (the difference in skills and usage of digital systems) and 3rd level divide (the difference in effects obtained from digital technology) may grow. The paper offers a systemic review of literature on the measurement of the digital divide, noting the certain conceptual stagnation due to the lack of effective instruments that would capture the complex nature of the phenomenon. As a result, many important concepts do not receive the empiric exploration they deserve. As a solution the paper suggests a composite Digital Life Index, that studies separately the digital supply and demand across seven independent dimensions providing for 14 subindices. The Index is based on Internet-borne data, a distinction from traditional research approaches that rely on official statistics or surveys. The application of the model to the study of the digital divide between Russian regions and between cities in China have brought promising results. The paper advances the existing methodological literature on the 2nd level digital divide and can also inform practical decision-making regarding the strategies of national and regional digital development.

Factors in a Sustainability Assessment of New Types of Closed Cavity Façades

With the current increase in CO2 emissions and global warming, the sustainability of both existing and new solutions must be assessed on a wide scale. As the implementation of closed cavity façades (CCF) is on the rise, various factors must be included in the analysis of new types of CCF. This paper aims to cover the relevant factors included in the sustainability assessment of new types of CCF. Several mathematical models are being used to describe the physical behavior of CCF. Depending on the type of CCF, they cover the main factors which affect the durability of the façade: thermal behavior of various elements in the façade, stress and deflection of the glass panels, pressure and the moisture control in the cavity. CCF itself represents a complex system in which all mentioned factors must be considered mutually. Still, the façade is only an envelope of a more complex system, the building. Choice of the façade dictates the heat loss and the heat gain, thermal comfort of inner space, natural lighting, and ventilation. Annual energy consumption for heating, cooling, lighting, and maintenance costs will present the operational advantages or disadvantages of the chosen façade system in economic and environmental aspects. Still, the only operational viewpoint is not all-inclusive. As the building codes constantly demand higher energy efficiency as well as transfer to renewable energy sources, the ratio of embodied and lifetime operational energy footprint of buildings is changing. With the drop in operational energy CO2 emissions, embodied energy emissions present a larger and larger share in the lifecycle emissions of the building. Taking all into account, the sustainability assessment of a façade, as well as other major building elements, should include all mentioned factors during the lifecycle of an element. The challenge of such an approach is a timescale. Depending on the climatic conditions on the building site, the expected lifetime of a glazed façade can exceed 25 years. In such a timespan, some of the factors can be estimated more precisely than the others. However, the ones depending on the socio-economic conditions are more likely to be harder to predict than the natural ones like the climatic load. This work recognizes and summarizes the relevant factors needed for the assessment of a new type of CCF, considering the entire lifetime of a façade element in an environmental aspect.

Detection of Arcobacter and Helicobacter pylori Contamination in Organic Vegetables by Cultural and PCR Methods

The most demanded organic foods worldwide are those that are consumed fresh, such as fruits and vegetables. However, there is a knowledge gap about some aspects of organic food microbiological quality and safety. Organic fruits and vegetables are more exposed to pathogenic microorganisms due to surface contact with natural fertilizers such as animal manure, wastes and vermicompost used during farming. Therefore, the objective of this work was to study the contamination of organic fresh green leafy vegetables by two emergent pathogens, Arcobacter spp. and Helicobacter pylori. For this purpose, a total of 24 vegetable samples, 13 lettuce and 11 spinach were acquired from 10 different ecological supermarkets and greengroceries and analyzed by culture and PCR. Arcobacter spp. was detected in five samples (20%) by PCR, four spinach and one lettuce. One spinach sample was found to be also positive by culture. For H. pylori, the H. pylori VacA gene-specific band was detected in 12 vegetable samples (50%), 10 lettuces and two spinach. Isolation in the selective medium did not yield any positive result, possibly because of low contamination levels together with the presence of the organism in its viable but non-culturable form. Results showed significant levels of H. pylori and Arcobacter contamination in organic vegetables that are generally consumed raw, which seems to confirm that these foods can act as transmission vehicles to humans.

Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle

This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

MLOps Scaling Machine Learning Lifecycle in an Industrial Setting

Machine learning has evolved from an area of academic research to a real-world applied field. This change comes with challenges, gaps and differences exist between common practices in academic environments and the ones in production environments. Following continuous integration, development and delivery practices in software engineering, similar trends have happened in machine learning (ML) systems, called MLOps. In this paper we propose a framework that helps to streamline and introduce best practices that facilitate the ML lifecycle in an industrial setting. This framework can be used as a template that can be customized to implement various machine learning experiments. The proposed framework is modular and can be recomposed to be adapted to various use cases (e.g. data versioning, remote training on Cloud). The framework inherits practices from DevOps and introduces other practices that are unique to the machine learning system (e.g.data versioning). Our MLOps practices automate the entire machine learning lifecycle, bridge the gap between development and operation.

Block-Based 2D to 3D Image Conversion Method

With the advent of three-dimension (3D) technology, there are lots of research in converting 2D images to 3D images. The main difference between 2D and 3D is the visual illusion of depth in 3D images. In the recent era, there are more depth estimation techniques. The objective of this paper is to convert 2D images to 3D images with less computation time. For this, the input image is divided into blocks from which the depth information is obtained. Having the depth information, a depth map is generated. Then the 3D image is warped using the original image and the depth map. The proposed method is tested on Make3D dataset and NYU-V2 dataset. The experimental results are compared with other recent methods. The proposed method proved to work with less computation time and good accuracy.

Combined Safety and Cybersecurity Risk Assessment for Intelligent Distributed Grids

As more parts of the power grid become connected to the internet, the risk of cyberattacks increases. To identify the cybersecurity threats and subsequently reduce vulnerabilities, the common practice is to carry out a cybersecurity risk assessment. For safety classified systems and products, there is also a need for safety risk assessments in addition to the cybersecurity risk assessment to identify and reduce safety risks. These two risk assessments are usually done separately, but since cybersecurity and functional safety are often related, a more comprehensive method covering both aspects is needed. Some work addressing this has been done for specific domains like the automotive domain, but more general methods suitable for, e.g., Intelligent Distributed Grids, are still missing. One such method from the automotive domain is the Security-Aware Hazard Analysis and Risk Assessment (SAHARA) method that combines safety and cybersecurity risk assessments. This paper presents an approach where the SAHARA method has been modified to be more suitable for larger distributed systems. The adapted SAHARA method has a more general risk assessment approach than the original SAHARA. The proposed method has been successfully applied on two use cases of an intelligent distributed grid.

Exponential Stability of Linear Systems under a Class of Unbounded Perturbations

In this work, we investigate the exponential stability of a linear system described by x˙ (t) = Ax(t) − ρBx(t). Here, A generates a semigroup S(t) on a Hilbert space, the operator B is supposed to be of Desch-Schappacher type, which makes the investigation more interesting in many applications. The case of Miyadera-Voigt perturbations is also considered. Sufficient conditions are formulated in terms of admissibility and observability inequalities and the approach is based on some energy estimates. Finally, the obtained results are applied to prove the uniform exponential stabilization of bilinear partial differential equations.

JEWEL: A Cosmological Model Due to the Geometrical Displacement of Galactic Object Like Black, White and Worm Holes

Stellar objects such as black, white and worm holes can be the subject of speculative reasoning if represented in a simplified and geometric form in order to be able to move them; and the cosmological model is one of the most important contents in relation to speculations that can then open the way to other aspects that are not strictly speculative but practical, precisely in the Universe represented by us. In this work, thanks to the hypothesis of a very large number of black, white and worm holes present in our Universe, we imagine that they can be moved; it was therefore thought to align them on a plane and following a redistribution, and the boundaries of this plane were ideally joined, giving rise to a sphere that has the stellar objects examined radially distributed. Thanks to geometrical displacements of these stellar objects that do not make each one of them lose their functionality in the region in which they are located, at the end of the speculative process it is possible to highlight a spherical layer that allows a flow from the outside and inside this spherical shell allowing to relate to other external and internal spherical layers; this aspect that seems useful to describe the universe we live in, for example inside one of the spherical shells just described. The name "Jewel" was chosen because, imagining the speculative process present in this work at the end of steps, the cosmological model tends to be "luminous". This cosmological model includes, for each internal part of a generic layer, different and numerous moments of our universe thanks to an eternal flow inward. There are many aspects to explore, one of these is the connection between the outermost and the inside of the spherical layers.

A Study of Learning to Enhance Career Skills Consistent with Disruptive Innovation in the Creative Strategies for Advertising Course

This project is a study of learning activities of creating experience from actual work performance to enhance career skills and technological usage abilities for uses in advertising career work performance for undergraduate students who enroll in the Creative Strategies for Advertising Course. The instructional model consisted of two learning approaches: (1) simulation-based learning, which is the learning with the use of simulations of working in various sections of creative advertisement work with their own work process and steps as well as the virtual technology learning in advertising companies; and (2) project-based learning, which is the learning that the learners engage in actual work performance based on the process of creating and producing creative advertisement works to be present on new media channels. The results of learning management showed that the effects on the students in various aspects were as follows: (1) the students had experience in the advertising process at the higher level; and (2) the students had work performance skills from the actual work performance that enabled them to possess the abilities to create and present their own work; also, they had created more efficient work outcomes and disseminated them on new media channels at a better level.

Experimental Testbed to Compare 4G and 5G Industrial IoT Connections in Simulated Based Control System

This paper considers the advent of 5G and the use of it in a Based Control System (BCS), posing as a basic concept the question of what the real differences and practical improvements are compared to 4G. To this purpose, a testbed hardware simulator has been designed and built where identical machines with the same sensors and management systems will communicate with different radio access network connections. This allows an objective statistical comparison of performance on the real functioning and improvement of the infrastructure with the Industrial Internet of Things (IIoT) connected to it.

Fuzzy Power Controller Design for Purdue University Research Reactor-1

The Purdue University Research Reactor-1 (PUR-1) is a 10 kWth pool-type research reactor located at Purdue University’s West Lafayette campus. The reactor was recently upgraded to use entirely digital instrumentation and control systems. However, currently, there is no automated control system to regulate the power in the reactor. We propose a fuzzy logic controller as a form of digital twin to complement the existing digital instrumentation system to monitor and stabilize power control using existing experimental data. This work assesses the feasibility of a power controller based on a Fuzzy Rule-Based System (FRBS) by modelling and simulation with a MATLAB algorithm. The controller uses power error and reactor period as inputs and generates reactivity insertion as output. The reactivity insertion is then converted to control rod height using a logistic function based on information from the recorded experimental reactor control rod data. To test the capability of the proposed fuzzy controller, a point-kinetic reactor model is utilized based on the actual PUR-1 operation conditions and a Monte Carlo N-Particle simulation result of the core to numerically compute the neutronics parameters of reactor behavior. The Point Kinetic Equation (PKE) was employed to model dynamic characteristics of the research reactor since it explains the interactions between the spatial and time varying input and output variables efficiently. The controller is demonstrated computationally using various cases: startup, power maneuver, and shutdown. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the reactor power to follow demand power without compromising nuclear safety measures.

Multi-Criteria Nautical Ports Capacity and Services Planning

This paper is a result of implemented research on proposed introduced methodology for nautical ports capacity planning by introducing a multi-criteria approach of defined criteria in the Adriatic Sea region. The purpose was analyzing the determinants - characteristics of infrastructure and services of nautical ports capacity allocated, especially nowadays due to COVID-19 pandemic, as crucial for successful operation of nautical ports. Giving the importance of the defined priorities for short-term and long-term planning is essential not only in terms of the development of nautical tourism, but also in terms of developing the maritime system, but unfortunately this is not always carried out. Evaluation of the use of resources should follow from a detailed analysis of all aspects of resources bearing in mind that nautical tourism used resources in a sustainable manner and generates effects in the tourism and maritime sectors. Consequently, identified multiplier effect of nautical tourism, which should be defined and quantified in detail, should be one of the major competitive products on the Croatian Adriatic and the Mediterranean. Research of nautical tourism is necessary to quantify the effects and required planning system development. In the future, the greatest threat to long-term sustainable development of nautical tourism can be its further uncontrolled or unlimited and undirected development, especially under pressure markedly higher demand than supply for new moorings in the Mediterranean. Results of this implemented research are applicable to nautical ports management and decision makers of maritime transport system development. This paper will present implemented research and obtained result - developed methodology for nautical port capacity planning - Port Capacity Planning Multi-criteria decision-making. A proposed methodological approach of multi-criteria capacity planning includes four criteria (spatial - transport, cost - infrastructure, ecological and organizational criteria, and additional services). The importance of the criteria and sub-criteria is evaluated and carried out the basis for a sensitivity analysis of the importance of the criteria and sub-criteria. Based on the analysis of the identified and quantified importance of certain criteria and sub-criteria as well as sensitivity analysis and analysis of changes of the quantified importance scientific and applicable results will be presented. These obtained results have practical applicability by management of nautical ports in the planning of increasing capacity and further development and for the adaptation of existing nautical ports. The obtained research is applicable and replicable in other seas and results are especially important and useful in this COVID-19 pandemic challenging maritime development framework.

Libretto Thematology in Rossini's Operas and Its Formation by the Composer

The present study examines the way Gioachino Rossini’s librettos are selected and formed demonstrating the evolutionary trajectory of the composer during his operatic career. Rossini, a dominant figure in the early 19th century Italian opera, is demanding in his choice of librettos and has a preference for subjects inspired by European literature, of his time or earlier. He begins his operatic career with farsae and operas buffae, but he mainly continues with operas seriae, to end it with a grand opera that conforms to the spirit of romanticism as manifested in Paris of his time. His farsae, operas buffae and comic operas in general are representative of the trends of the time: in some the irrational and the exaggeration prevail, in others the upheavals, others are semi-serious and emotional with a happy ending and others are comedies with more realistic characters, but usually the styles are mixed and complement each other. The stories that refer to his modern era unfold mocking human characters, beliefs attitudes and their expressions in every day habits, satirizing current affairs, presenting innovative elements in dramatic intervention and dealing with a variety of social and national issues. Count Ory, his final comic work, consists of a complex witty urban comic opera entwined with romantic sensitivity. The themes he chooses for his operas seriae are characterized by tragic passion, take place in the era of the Trojan War, the Roman Empire, the Middle Ages, and the Age of the Crusades and are set in Italy, England, Poland, Greece, Switzerland, Israel and Egypt. In his early works he sketches the characters remotely, objectively and with static, reflexive emotional expression and a happy ending. Then he continues with operas for the San Carlo Theater, which are characterized by experimentation and innovation to end up his Italian operatic career with the ostensibly backward but in fact tragic Semiramis followed in Paris by William Tell, his ultimate dramatic achievement. There are indirect references to burning issues of his era but the censorship of the time does not allow direct reference to topics that would upset the status quo. In addition, Rossini lives in a temporal period of peace after the Napoleonic Wars and by temperament he resists openly engaging in political strife. Furthermore, the need for survival necessitates the search for the more profitable contracts. In conclusion, Rossini, as a liberal personality, shapes his librettos without interruptions or setbacks, with ideas that come out after a lot of thought and a strong sense of purpose. He moves from the moral and aesthetic clarity of the classic tradition of his early works to a more elaborate and morally ambiguous romantic style in a moderate and hesitant way.

Cyber Security Enhancement via Software-Defined Pseudo-Random Private IP Address Hopping

Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicates via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Mobile Robot Control by Von Neumann Computer

The digital control system of mobile robots (MR) control is considered. It is shown that sequential interpretation of control algorithm operators, unfolding in physical time, suggests the occurrence of time delays between inputting data from sensors and outputting data to actuators. Another destabilizing control factor is presence of backlash in the joints of an actuator with an executive unit. Complex model of control system, which takes into account the dynamics of the MR, the dynamics of the digital controller and backlash in actuators, is worked out. The digital controller model is divided into two parts: the first part describes the control law embedded in the controller in the form of a control program that realizes a polling procedure when organizing transactions to sensors and actuators. The second part of the model describes the time delays that occur in the Von Neumann-type controller when processing data. To estimate time intervals, the algorithm is represented in the form of an ergodic semi-Markov process. For an ergodic semi-Markov process of common form, a method is proposed for estimation a wandering time from one arbitrary state to another arbitrary state. Example shows how the backlash and time delays affect the quality characteristics of the MR control system functioning.

Data-Driven Decision-Making in Digital Entrepreneurship

Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Performance Evaluation of an Ontology-Based Arabic Sentiment Analysis

Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic ABSA approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Spatial Correlation of Channel State Information in Real LoRa Measurement

The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially LoRaWAN. In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated with each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems to get access to a wider band.

Networked Implementation of Milling Stability Optimization with Bayesian Learning

Machining instability, or chatter, can impose an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the TU Wien, Vienna, Austria. The recorded data from a milling test cut were used to classify the cut as stable or unstable based on a frequency analysis. The test cut result was used in a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculated the probability of stability as a function of axial depth of cut and spindle speed based on the test result and recommended parameters for the next test cut. The iterative process between two transatlantic locations was repeated until convergence to a stable optimal process parameter set was achieved.