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Reviews from players regarding different characteristics of an esports game are one of the worthiest sources for the developers to enhance their services or adjust operating strategy. However, little research has been conducted on detecting esports players’ favorite topics dealing with topic modeling. Thus, this paper aims to use a data mining approach to analyze community data in the games domain available on Steam. We collected more than 1.2 million English reviews from four esports games up to August 2020 on Steam. Our contributions in this paper are: (i) we manually build a dataset by filtering out high-quality esports reviews, (ii) we then infer and group reviews into 3 groups with 19 topics, and (iii) we add more contributions to finding the emerging opinions of esports players towards the different topics of esports reviews, which might benefit further research on understanding esports reviews.

The history of the computer science department at the Institute of Mathematics and Informatics of Bulgarian Academy of Sciences since 1963 is briefly described. Starting with small groups of enthusiastic people initiating the new for Bulgaria research in the field of Informatics, nowadays the department can report some significant achievements. The paper presents some of them in three areas—software quality evaluation and management, data mining and semantic analysis, information systems and communities—which mark some key areas of research during the years.

To improve the intelligent image recognition abilities of edge devices, a parallel-optimization-based framework called POWER is introduced in this paper. With FPGA (Field-Programmable Gate Array) as its hardware module, POWER provides well extensibility and flexible customization capability for developing intelligent firmware suitable for different types of edge devices in various scenarios. Through an actual case study, we design and implement a firmware prototype following the specification of POWER and explore its performance improvement using parallel optimization. Our experimental results show that the firmware prototype we implement exhibits good performance and is applicable to substation inspection robots, which also validate the effectiveness of our POWER framework in designing edge intelligent firmware modules indirectly.

Checking the semantic equivalence of operations is an important task in software development. For instance, regression testing is a routine task when software systems are developed and improved, and software package managers require the equivalence of operations in different versions of a package within the same major version. In order to support a good automation of this process, a solid foundation is required. It has been shown that the notion of equivalence is not obvious when non-deterministic features are present. In this paper, we discuss a general notion of equivalence in functional logic programs and develop a practical method to check it. Our method can be integrated in a property-based testing tool which is used in a software package manager to check the semantic versioning of software packages.

This project focuses on the changes in the characteristics and properties of cement slurry while adding different environmentally friendly additives. To properly implement the cementing job, cement should have the desired properties and characteristics. It should have very low permeability, high strength, sufficient thickening time and pump-ability to reach the target depth and the desired density, depending on the conditions of the well. To control the cement properties and obtain the desired characteristics, additives are usually used and mixed with plain cement. In this project, new and novel additives, including cactus powder, hay bran, hay bran ash, rice husk, and rice husk ash were used and mixed separately with the plain cement. The plain and blended cement samples were exposed to various API cement tests, including the compressive strength test, gas-permeability test, fineness test, and density test. This paper focuses mainly on the results of the compressive strength test conducted on the plain cement and rice husk ash, hay bran ash blended with cement. Results showed that the rice husk ash blended cement at a 10% replacement level exhibited the highest value of compressive strength, whereas the other non-ash additives adversely affected the strength of the cement.

Wireless sensor network (WSN) is composed by a set of sensor nodes with low energy consumption and low cost which could sense quantities like humidity, temperature, pressure and send them to the central node. The routing optimization in IoT networks is required taking into account the traffic, congestion, and failure of some or all network services. In fact, low traffic and network congestion means high quality routing in that network. Increasing the network lifetime and improving the routing quality is one of the main concerns of IoT-based sensor networks. In this paper, a new clustering algorithm is proposed to increase the network efficiency in the IoT-based sensor networks using the fuzzy logic and particle swarm optimization (PSO) algorithm. In this approach, the cluster was created in WSN using energy modelling for effective routing of data packages via using fuzzy logic and (PSO). The stimulation results of the proposed method showed higher capabilities by comparison with reported algorithms (e.g. LEACH, FLCFP, HEED, FBCFP) s that were used for energy consumption optimization in WSN.

Visual lifelogging is the process of automatically recording images and other sensor data for the purpose of aiding memory recall. Such lifelogs are usually created using wearable cameras. Given the vast amount of images that are maintained in a visual lifelog, it is a significant challenge for users to deconstruct a sizeable collection of images into meaningful events. In this paper, random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using SenseCam lifelog data streams to identify such events. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to "distinct significant events" in the visual lifelogs. Finally, the cross-correlation matrix C is cleaned by separating the noisy part from the non-noisy part. Overall, the RMT technique is shown to be useful to detect major events in SenseCam images.

In regulated organizations, norms may come from various regulation sources imposed by different institutions. With possibly conflicting values and interests, inconsistencies are likely to occur among these norms, e.g., one norm obliges some actions to be done while another norm prohibits the same actions. In this paper, we propose a formalization of norm conflicts based on the normative states of interrelated norms. Then via operationalizing the normative structure based on Colored Petri Nets, we propose a method for detecting such conflicts.

One of the problems in disease prevention and epidemics control is the large level of uncertainty present in the solved problems. If an optimization of targeted vaccination scheme is attempted, the evaluation of solutions usually involves simulating the non-deterministic spreading of the disease. However, the non-determinism of the epidemic dynamics is just one of the sources of uncertainty in this problem. This paper studies another source of uncertainty in optimization of targeted vaccination schemes, which is the existence of non-diagnosed cases of the disease.

Hassin et al. [9] consider the Max-Exp-Cover-R problem to study the facility location problem on a graph in the presence of unreliable links when the link failure is according to the Linear Reliability Order (LRO) model. They showed that for unbounded R the problem is polynomial time solvable and for \(R=1\) and planar graphs the problem is NP-Complete. In this paper, we study the Max-Exp-Cover-1 problem under the LRO edge failure model. We obtain a fixed parameter tractable algorithm for Max-Exp-Cover-1 problem for bounded treewidth graphs, parameterized by the treewidth. We extend the Baker’s technique (Baker, J. ACM 1994) to obtain PTAS for Max-Exp-Cover-1 problem under the LRO model on planar graphs. We observe that the coverage function of the Max-Exp-Cover-R problem is submodular and the problem admits a \((1-1/e)\)-approximation for any failure model in which the expected coverage of a set by another set can be computed in polynomial time.

Ambient Assisted Living (AAL) services are emerging as context-awareness solutions to support elderly people’s autonomy. The context-aware paradigm makes applications more user-adaptive. In this way, context and user models expressed in ontologies are employed by applications to describe user and environment characteristics. The rapid advance of technology allows creating context server to relieve applications of context reasoning techniques. Specifically, the Next Generation Networks (NGN) provides by means of the presence service a framework to manage the current user’s state as well as the user’s profile information extracted from Internet and mobile context. This paper propose a user modeling ontology for AAL services which can be deployed in a NGN environment with the aim at adapting their functionalities to the elderly’s context information and state.

The biopsychosocial (BPS) model proposes that health is best understood as a combination of bio-physiological, psychological and social determinants, and thus advocates for a far more comprehensive investigation of the relationships between ‘mind-body’ health. For this holistic analysis, we need a suitable measure to indicate participants’ ‘biological’ stress. With the advent of wearable sensor devices, health monitoring is becoming easier. In this study, we focus on bio-physiological indicators of stress, from wearable devices using the heart-rate data. The analysis of such heart-rate data presents a set of practical challenges. We review various measures currently in use for stress measurement and their relevance and significance with the wearables’ heart-rate data. In this paper, we propose to use the novel ‘peak heart-rate count’ metric to quantify level of ‘biological’ stress. Real life biometric data obtained from digital health intervention program was considered for the study. Our study indicates the significance of using frequency of ‘peak heart-rate count’ as a ‘biological’ stress measure.

Understanding and deciphering the processes proceeding near the surface are the urgent tasks of contemporary mineralogy and geochemistry, which are especially important for resolving ecological challenges and developing principles of rational environmental management. The paper presents our systematized data published about the thermodynamics of selenites, which are formed in the weathering zone of the sulfide ores, and determines approaches to quantitative physicochemical modeling of their formation conditions. The activities of components in natural waters beyond the zones of natural (oxidation zones) and man-made contamination with selenium (a ΣSe = 10−9, a ΣFe = 10−5, a ΣCu = 10−7, a ΣZn = 5 × 10−7, a ΣCo = 10−8, a ΣNi = 6 × 10−8, and a ΣPb = 10−8) and in waters formed in the oxidation zone (a ΣSe = 10−5–10−4, a ΣFe = 10−2, a ΣCu = 10−2, a ΣZn = 10−2, a ΣCo = 10−3, a ΣNi = 10−2, a ΣPb = 10−4) have been estimated. Eh–pH diagrams were calculated and plotted using the Geochemist’s Workbench (GMB 7.0) software package. The database comprises the thermodynamic parameters of 46 elements, 47 main particles, 48 redox pairs, 551 particles in solution, 624 solid phases, and 10 gases. The Eh–pH diagrams of the Me–Se–H2O systems (Me = Cu, Pb, Co, Ni, Fe, Zn) were plotted for the average contents of these elements in underground water and for their contents in oxidation zones of sulfide deposits. The formation of Co, Ni, Fe, Cu, Zn, and Pb selenites and selenates at the surface is discussed.

This paper describes the challenges that arise during quality control of deep vibro-compaction works on land reclamation projects realized in the Middle East. The aim of deep vibro-compaction is to densify the fill to a certain relative density Dr and thereby assure certain minimal criteria related to the soil behavior such as stiffness and resistance against liquefaction. For quality control of the compaction works, the achieved relative density throughout the hydraulic fill can be measured indirectly by performing Cone Penetration Tests (CPT). The targeted relative density is linked to a cone resistance curve calculated with well-known and established correlation methods like Schmertmann [1] or Baldi [2]. However, the use of these empirical correlations in calcareous sand is questionable because they are not suitable to reproduce the characteristics of these sands. Almeida et al. [3] have shown that carbonate sands show significantly lower qc-values than silica sands under similar conditions which can lead to unattainable target cone resistance values demanded by the client.

This paper presents a novel method for modelling the growth of agents undergoing clonal expansion. Using the concept of plasmids, clonal agents are broken into components which can be judged independently of the agents themselves. These components can be redistributed by objects analogous to bacteriophages. Full algorithms for the model are given, and results of an implementation provided. The work presented in this paper has significant implications for the field of clonal expansion.

This paper describes an alternative approach for videogame procedural content generation focused on providing authors direct control on what gameplay ensues from the generated content. An architecture is proposed that allows designers to define, beforehand, target gameplay indicators, and then generates content for an existing base-design that achieves those same indicators in actual gameplay sessions with human players. Besides providing a description of this architecture, a trial intent on giving evidence of the approach's feasibility is presented. This experiment used an altered version of 'Infinite Mario Bros.' level generator, built to evolve design parameters so as to achieve 3 target gameplay indicators. Employing a Genetic Algorithm in generation of new parameter values, and using 25 players to test the end results, the platform was able to generate parameters that achieved, with precision, the values for those indicators. This result provides evidence of the approach's feasibility, hinting at its potential use for real-life design processes.

The paper presents a text mining approach to identifying and analyzing technological trajectories. The main problem addressed is the selection of documents related to a particular technology. These documents are needed to detect a trajectory of technology. The approach includes new keyword and keyphrase detection method, word2vec embeddings-based similar document search method and fuzzy logic-based methodology for revealing technology dynamics. USPTO patent database was used for experiments. The database contains more than 4.7 million documents from 1996 to 2020. Self-driving car technology was chosen as an example. The result of the experiment shows that the developed methods are useful for effective searching and analyzing information about given technologies.

This paper deals with the problem of local buckling caused by uniaxial stretching of an infinite plate with a circular hole or with circular inclusion made of another material. As the Young’s modulus of the inclusion approaches that of the plate, the critical load increases substantially. When these moduli coincide, stability loss is not possible. This paper also shows the difference between them when the inclusion is softer than the plate and when the inclusion is stiffer than the plate. Computational models show that instability modes are different both when the inclusion is softer than the plate and when the inclusion is stiffer than the plate. The case when plate and inclusion have the same modulus of elasticity, but different Poisson’s ratio is investigated too. It is also discussed here the case when a plate with inclusion is under biaxial tension. For each ratio of the modulus of elasticity of plate versus inclusion it’s obtained the range of the load parameters for which the loss of stability is impossible.

A mobile ad hoc network (MANET) is a group of autonomous mobile nodes that wirelessly communicate with each other to form a wireless dynamic topology network. It works without requiring any centralized pre-existing administration units (infrastructure less network). There are many studies that focus on improving source-destination route stability and lifetime by modifying the existing MANET routing protocols. In this paper, a fuzzy-based approach is proposed to enhance the ad hoc on-demand distance vector (AODV) reactive routing protocol’s performance by selecting the most trusted nodes to construct the route between the source and destination nodes. In this scheme, the nodes’ parameters, such as residual energy, node mobility, and number of hop counts, are fed through a fuzzy inference system to compute the value of the node trust level, which can be used as a metric to construct an optimal path from source to destination. The results of the simulation show that the proposed approach performs better than the traditional AODV routing protocol and minimum battery cost routing protocol in terms of average control overhead, packet delivery ratio, network throughput, and average end-to-end delay. The file in this item is the publisher version (published version) of the article.

For load balancing in cloud computing environment, scheduling algorithm are used. This paper analyses the research on scheduling algorithms. Further, using cloudsim simulation tools, evaluation of performance of the three algorithms i.e. First Come First Serve (FCFS), Generalized Priority (GP) and Shortest Job First (SJF) was carried out. Three algorithms were compared by varying both virtual machines (VM) and cloudlets, keeping constant VM and increasing Cloudlets, varying the nature of tasks. For all the three algorithms, as the number of cloudlets increases, execution time increases. Generalized Priority algorithm (GP) has lower execution time than both First Come First Serve (FCFS) and Shortest Job First (SJF) algorithms. For homogeneous type of tasks, execution time of FCFS is lower and for heterogeneous type of tasks, execution time of GP is lower. Homogeneous tasks required less execution time than Heterogeneous tasks.

In this paper I deal with both direct and indirect reports. Direct reporting in schizophrenic discourse has to be interpreted in context and thus everything we say about direct reports involves elucidating the context of use and thus providing indirect reports of direct reports. The context includes the imaginary voice (an auditory hallucination) and a situation in which the patient makes complaints to institutional figures about his own situation. According to a series of recent and very important studies, psychotic language ‘disorders’ would manifest essentially schizophrenic patients’ pragmatic difficulties.

The inclusion of people with cerebral palsy is not an easy path, because many of them preserve their cognitive abilities, despite being unable to speak, walk, or even both. This paper presents a study on the games applied in the education of people with cerebral palsy using Brain Computer Interface (BCI). Children affected by Cerebral Palsies have a disturbance in the control of their postures and body movements as a result of a brain injury. These injuries are the result of several causes. The most frequent is linked to the lack of oxygen flow to the brain, occurring either during or immediately after birth. The objective of the current research is to study the evaluation of the game we developed, called Questing Ruins. The methodology used was that of qualitative approach and case study. At the end we present Questing Ruins, an adventure game for entertainment and environmental awareness.

In northern Brazil, deformational structures control various features of the morphology. These structures are ductile shear zones and regional foliations formed during the brasiliano orogeny in the late proterozoic, and faults formed during the rifting of the margin in the Jurassic—cretaceous and in the late cretaceous and Cenozoic. The morphology features related to these structures include mainly residual alignment of ridges, fault-controlled valleys, and structural fault scarps. In this perspective, this paper presents a review about the morphostrutural control played by brittle and ductile basement structures on the relief in northeastern brazil. Our study indicates that continental denudation have been controlled by both differential erosion and tectonics. In this aspect, the exhumation along NE-SW and E-W striking shear zones originates lineaments, which confine the drainage channels and guide the dissection and sometimes fluvial aggradation. This process results in ridges and valleys that control the flow channels, which become indicators of shear zones and faults. This process is also observed in sedimentary basins, where dissection along fault zones form tectonic valleys that constitute the geomorphic expression of the fault reactivation.

The business environment is rapidly undergoing changes, and they need a prompt adaptation to the enterprise business systems. The process models have abstract behaviors that can apply to diverse conditions. For allowing to reuse a single process model, the configuration and customisation features can support the design improvisation. However, most of the process models are rigid and hard coded. The current proposal for automatic code generation is not devised to cope with rapid integration of the changes in business coordination. Domain-specific Rules (DSRs) constitute to be the key element for domain specific enterprise application, allowing changes in configuration and managing the domain constraint with-in the domain. In this paper, the key contribution is conceptualisation of the do-main model, domain model language definition and specification of domain model syntax as a source visual modelling language to translate into domain specific code. It is an input or source for generating the target language which is do-main-specific rule language (DSRL). It can be applied to adapt to a process constraint configuration to fulfil the domain-specific needs.

This paper selects 213 opening addresses by Chinese university presidents between 2003 and 2015, synchronically and diachronically, this paper has devoted itself to the study of the usage of words and characters in those addresses, the contents as a whole. The location and the time those speeches were delivered have also been taken into consideration. By comparing the words and characters used in those addresses to Lexicon of Common Words in Contemporary Chinese, this paper shows that vocabulary used in addresses doesn’t change dramatically with time going diachronically, and the themes and focuses of the speeches tend to vary from time to time. This paper classifies the speeches into certain types according to the frequently and individually used words, analyzes the features of their contents. The conclusion is that universities have put more emphasis on cultivating spirits, quality, ability and virtue.

The LoRaWAN is one of the new low-power wide-area network (LPWAN) standards applied to Internet of Things (IoT) technology. The key features of LPWAN are its low power consumption and long-range coverage. The LoRaWAN 1.1 specification includes a basic security scheme. However, this scheme could be further improved in the aspect of key management. In this paper, LoRaWAN 1.1 security is reviewed, and enhanced LoRaWAN security with a root key update scheme is proposed. The root key update will make cryptoanalysis of security keys in LoRaWAN more difficult. The analysis and simulation show that the proposed root key update scheme requires fewer computing resources compared with other key derivation schemes, including the scheme used in the LoRaWAN session key update. The results also show the key generated in the proposed scheme has a high degree of randomness, which is a basic requirement for a security key.

Sampling theory has been studied in a variety of function spaces and our purpose here is to develop the theory in a Fourier algebra setting. This aspect is not as well-known as it might be, possibly because the approximate sampling theorem, central to our discussion, had what could be called a mysterious birth and a confused adolescence. We also discuss functions of the familiar bandlimited and bandpass types, showing that they too have a place in this Fourier algebra setting. This paper combines an expository and historical treatment of the origins of exact and approximate sampling, including bandpass sampling, all in the Fourier algebra setting. It has two objectives. The first is to provide an accessible and rigorous account of this sampling theory. The various cases mentioned above are each discussed in order to show that the Fourier algebra, a Banach space, is a broad and natural setting for the theory. The second objective is to clarify the early development of approximate sampling in the Fourier algebra and to unravel its origins.

Wireless sensor network is defined as homogeneous or heterogeneous system containing large number of sensors namely called as nodes used to monitor different environments in cooperatives. WSN is composed of sensor nodes (SN), base stations (BS) and cluster head (CH). The popularity of wireless sensor network has been increased day by day exponentially due to its wide range of application. The applications of wireless sensor networks are air traffic control, healthcare systems, home services, military services, industrial & building automations, network communications, VAN etc. The advantage of WSN is that it is very easy to install in critical regions where normal network cannot be set. Thus the wide range of applications attracts attacker. To secure from different types of attacks mainly intruder, intrusion detection system based on dynamic state context and hierarchical trust in WSNs (IDSHT) is proposed. The trust evaluation is carried out in hierarchical way. The trust of sensor nodes is evaluated by cluster head (CH) whereas trust of cluster head is evaluated by neighbor cluster head or base stations. Hence the content trust, honest trust and interactive trust is put forward by combining direct evaluation and feedback based evaluation in the fixed hop range. In this way the complexity of trust management is carried in hierarchical manner and trust evaluation overhead is minimized. This proposed work addresses the security issues of wireless sensor network. A more prominent intrusion detection system based on context level and trust level is introduced. This mechanism achieves more than 90% accuracy in detection of routing attack and sinkhole attack. The architecture suggested in this paper is used to develop two level of trust model. Accuracy of 90% and 95% is expected in intrusion detection and context text detection respectively.

The importance of assessing the overall behaviour of buildings considering the contribution of non-structural infills has been nowadays widely recognised. Indeed, infills can trigger fragile mechanisms of structural members preventing the evolution of dissipative mechanisms and can play an important role in the verifications at damageability limit states, especially in the case of strategic structures for which often high performance levels are required, including the full operativity (i.e. absence of damage to both structural and non-structural members) after severe earthquakes, in order to guarantee the building occupancy during the emergency management. With reference to a case study, the paper presents a simplified approach for estimating the stiffness of masonry infill walls through expeditious dynamic impact tests on infills. The case study is constituted by a laboratory real-scale mock-up for which a complete dynamic identification is carried out before and after the realization of infill masonry walls. The adopted procedure is then validated through results from a refined finite element model of the mock-up in which infills are modelled adopting stiffnesses obtained from the proposed approach.

Accurate three-dimensional (3D) image segmentation techniques have become increasingly important for medical image analysis in general, and for spinal vertebrae image analysis in particular. The complexity of vertebrae shapes, gaps in the cortical bone and internal boundaries pose significant challenge for image analysis. In this paper, we describe a level set image segmentation framework that integrates prior shape knowledge and local geometrical features to segment both normal and fractured spinal vertebrae. The prior shape knowledge is computed via kernel density estimation whereas the local geometrical features is captured through an edge-mounted Willmore energy. While the shape prior energy draws the level set function towards possible shape boundaries, the Willmore energy helps to capture the detail shape and curvature information of the vertebrae. Experiment on CT images of normal and fractured spinal vertebrae demonstrate promising results in 3D segmentation.

This paper presents an approach for rapidly adjustable embedded trace online monitoring of multi-core systems, called RETOM. Today, most commercial multi-core SoCs provide accurate runtime information through an embedded trace unit without affecting program execution. Available debugging solutions can use it to reconstruct the run offline, but usually for up to a few seconds only. RETOM employs a novel online reconstruction technique that makes the program run available outside the SoC and allows for evaluating a specification formulated in the stream-based specification language TeSSLa in real time. The necessary computing performance is provided by an FPGA-based event processing system. In contrast to other hardware-based runtime verification techniques, changing the specification requires no circuit synthesis and thus seconds rather than minutes or hours. Therefore, iterated testing and property adjustment during development and debugging becomes feasible while preserving the option of arbitrarily extending observation time, which may be necessary to detect rarely occurring errors. Experiments show the feasibility of the approach.

Paper deals with an issue of computer simulation of glass pressing. Attention is paid to accuracy of numerical outputs. Simple forming process—isothermal compression of a glass cylinder is chosen for virtual modelling. The constitutive behaviour of shaped glass is assumed to be nonlinear viscoelastic, based on general Maxwell model. Both viscoelastic response and relaxation behaviour of samples made of lead crystal are evaluated. Computer outputs are verified with experimental measurements in the viscosity range of 107–1010 Pa s. In this paper results at temperature 611 °C (corresponding viscosity 107.4 Pa s) and 587 °C (viscosity 108 Pa s) are presented. Uniaxial deformation was carried out at various constant pressing rates (in the interval 0.1–8 mm s−1).

How do we assure that a scientific result is sound, that no fraud has been committed and we do guarantee scientific progress in this new era of big scientific data? In order to guarantee reproducibility, especially in the biomedical sciences one need to give access to third parties to analytical datasets (either raw or processed), software used, code developed by the researchers, a very detailed description of the methodology as well as all the relevant metadata. We want to argue that that sharing data is mandatory in order for science to progress. Each published paper should not be seen as an untouchable revealed truth, but as an opportunity of dialogue, confrontation and verification. This can be done only if all raw data are shared and each researcher has the right tools to reproduce an experiment.

It is an important issue to design a highly reliable information network that is robust against network failures. As a method for design of a robust network, there is an approach of protection, which decreases link failure probability by backup mechanism and fast recovery mechanism. It is desirable to protect all links; however, link protection needs much cost. Therefore, it is necessary to find the small number of links to be protected so that a network resulting from failure of any non-protected links satisfies constraints of quality. In this paper, we propose a method to design an information network satisfying multiple constraints by using an efficient data structure, Zero-suppressed Binary Decision Diagram (ZDD). This method holds the set of the feasible solutions satisfying each constraint by ZDD, and it determines the intersection of the sets of the feasible solutions for all constraints by the calculation of ZDD. Thus, the method can determine the sets of the feasible solutions satisfying the multiple constraints simultaneously, and finally it determines the optimum solution. This approach also makes it easy to change or to add constraints.

The vocabulary space of the Semantic Web includes more than 500 vocabularies according to the Linked Open Vocabularies (LOV) initiative that maintains the directory list and provides search functionality on top of the curated data. Domain experts and researchers have populated it to facilitate the interpretation and exchange of information in the Web of Data. The abundance of vocabularies and terms available in the LOV space, on one hand aims to cover the major knowledge management needs, but on the other hand it could be cumbersome for a non-expert or even a vocabulary expert to find the correct way through the collection. To address this problem, we present an approach that helps to identify the most appropriate set of LOV vocabulary terms for a given Web content context by leveraging the existing dynamics within the LOV graph and the usage patterns in the LOD cloud. The paper describes the framework architecture that enables the discovery of vocabularies; it focuses on the corresponding metrics and algorithm, and discusses the outcomes of the applied experiments.

This paper presents the problems of robust asymptotic stability of fractional-order discrete-time linear systems with uncertainty. It is assumed that the system matrix is the interval matrix and the fractional order \(\alpha \) satisfies \(0< \alpha < 1\). The new robust stability conditions are given based on the matrix measure and Gershgorin’s theorem for the interval matrices. The considerations are illustrated by numerical examples.

Reverse DNS (rDNS) is regularly used as a data source in Internet measurement research. However, existing work is polarized on its reliability, and new techniques to collect active IPv6 datasets have not yet been sufficiently evaluated. In this paper, we investigate active and passive data collection and practical use aspects of rDNS datasets. We observe that the share of non-authoritatively answerable IPv4 rDNS queries reduced since earlier studies and IPv6 rDNS has less non-authoritatively answerable queries than IPv4 rDNS. Furthermore, we compare passively collected datasets with actively collected ones, and we show that they enable observing the same effects in rDNS data. While highlighting opportunities for future research, we find no immediate challenges to the use of rDNS as active and passive data-source for Internet measurement research.

Let \(\tau \) be a type of nets. Synthesis consists in deciding whether a given labelled transition system (TS) A can be implemented by a net N of type \(\tau \). In case of a negative decision, it may be possible to convert A into an implementable TS \(A'\) by relabeling edges that previously had the same label differently: Label-splitting is the problem to decide for a TS A and a natural number \(\kappa \) whether there is an implementable TS B with at most \(\kappa \) labels, which is derived from A by splitting labels. In this paper, we show that label-splitting is NP-complete if \(\tau \) corresponds to the type of flip-flop nets or some flip-flop net derivatives.

This chapter outlines the benefits of Design Thinking as a creative framework for innovation that can be applied to projects and organisations across government, business and the public sector. It includes a short history of the Design Thinking approach to set context and define the concept. However, much of the ensuing discussion and evaluation of ideas and methods is based on recent publications, papers and journal articles to give a current view of academic and practitioner activities. At the heart of the approach is a people-centred focus, and the chapter discusses the role of Inclusive Design and design ethnography in underpinning Design Thinking. It outlines five principles: Involve People, Translate Design Thinking into Design Doing, Create Value and Capture Value, Follow the Arc of Design Thinking and Navigate Complexity. It aims to give an overarching view of Design Thinking, demonstrating the value that it can bring to diverse areas of research and application. Challenges and observations for progressing the approach are also noted.

Developing the capabilities to read and comprehend text is fundamental for the development of children. Traditionally, the comprehension process is stimulated by educational interventions carried out by primary school educators, who aim, e.g., at retracing temporal relations among main events of a story. While a dual-coding approach pairing verbal and pictorial information proves to be successful, existing proposals for the visualization of a story’s events and their relationships seems dedicated mostly to computational linguists or information engineers rather than children and educators. The FP7 European project TERENCE faced this issue creating the first adaptive learning system for text comprehension for primary school children. The paper, after a review on the state-of-art of visual representation of temporal relations, discusses the TERENCE choices for achieving a children-oriented approach.

Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future states predicted by deep neural networks. This paper analyzes new ways of encoding the inputs and outputs of DeepStack’s deep counterfactual value networks based on traditional abstraction techniques, as well as an unabstracted encoding, which was able to increase the network’s accuracy.

Bike-sharing is becoming popular in the world, providing a convenient service for citizens. The system has to redistribute bikes among different stations frequently to solve the imbalance of spatial distribution. Real-time monitoring doesn’t solve this problem well, since it takes too much time to redistribute the bike and affects the user experience. In this paper, we first analyze the influence of factors such as time, weather, the location of stations. Then we cluster neighboring stations with similar usage pattern, and propose a lagged variable to simulate the effect of weather conditions in usage number. Finally, a multiple factor regression model with ARMA error (MFR-ARMA) is proposed to predict the check-out/in number of bikes in each cluster in a period of time. Evaluation dataset is from New York Bike Sharing System. The prediction results of the model are compared with four baseline methods. The experiments show a lower RMSLE and ER for check-out/in number prediction in our model.

This paper presents the methodology for integrated product development and design. Gears reduction drive was chosen as example. For design process, advance 3D methods and technologies were used, technologies such as: 3D geometric parametric modeling of virtual prototype, simulation of working principles, manufacturing of real prototype using additive manufacturing (3D printing) and usage of augmented reality. In conclusion part of the paper, using results from this research, advantages of integrated product development and design are highlighted, with special focus on influence of this methodology on students education at Faculty of Mechanical Engineering in the field of mechanical power transmissions.

This paper examines what law as an aspect of the humanities could contribute to sustainability. It proposes that corporate tax can be viewed as a social ‘value’ or ‘ethic’ enshrined in law and potentially channelled towards sustainable social structures and system. The corporate vehicle is seen as an equitable wealth generation mechanism and taxation is one of the tools through which corporations can contribute to society. It examines the use of corporation tax in the United Kingdom as an exemplar. The paper also identifies the limitations of expressing such social values through law, as law can be a rigid tool for reflecting progressive concepts, often resulting in gaps through which there can be ‘strategic’ compliance. The paper suggests that an explicit focus on the link between corporate tax and the sustainability agenda may create the additional moral impetus for compliance with the law.

Efficient Global Optimization (EGO) is a well established iterative scheme for solving computationally expensive optimization problems. EGO relies on an underlying Kriging model and maximizes the expected improvement (EI) function to obtain an infill (sampling) location. The Kriging model is in turn updated with this new truly evaluated solution and the process continues until the termination condition is met. The serial nature of the process limits its efficiency for applications where a batch of solutions can be evaluated at the same cost as a single solution. Examples of such cases include physical experiments conducted in batches for drug design and material synthesis, and computational analyses executed on parallel infrastructure. In this paper we present a multi-objective formulation to deal with such classes of problems, wherein instead of a single solution, a batch of solutions are identified for concurrent evaluation. The strategies use different objectives depending on the archive of the evaluated solutions. The performance the proposed approach is studied on a number of unconstrained and constrained benchmarks and compared with contemporary MO formulation based approaches to demonstrate its competence.

In this paper, we propose a novel approach for unsupervised change detection by integrating visual attention mechanism which has the ability to find the real changes between two images. The approach starts by generating a difference image using the differential method. Subsequently, an entropy-based saliency map is generated in order to highlight the changed regions which are regarded as salient regions. Thirdly, a fusion image is generated using difference image and entropy-based saliency map. Finally, the K-means clustering algorithm is used to segment the fusion image into changed and unchanged classes. To demonstrate the effect of our approach, we compare it with the other four state-of-the-art change detection methods over two datasets, meanwhile extensive quantitative and qualitative analysis of the change detection results confirms the effectiveness of the proposed approach, showing its capability to consistently produce promising results on all the datasets without any priori assumptions.

This paper presents a comprehensive systematic literature review of information classification (IC) enablers. We propose a classification based on the well-known levels of management: strategic, tactical and operational. The results reveal that a large number of enablers could be adopted to increase the applicability of IC in organizations. The results also indicate that there is not one single enabler solving the problem, but rather several enablers can influence the adoption.

This paper explores the impact of gendered context on the female entrepreneurship environment in Estonia. Having introduced comprehensive structural and institutional reforms in the 1990s, Estonia is now one of the most developed and progressive post-Soviet bloc countries. Most global rankings place Estonia towards the top of their lists, presenting it as an example of long-term successful economic and fiscal policy, with effective structural reforms and state governance. Nevertheless, the women entrepreneurship rate in Estonia is surprising, with women entrepreneurs constituting only 5% of the women in the active labor force in 2012. This is significantly lower than the EU-28 average entrepreneurship rate, and one of the lowest in Europe. This paper aims to contribute to the field of entrepreneurship, illustrating how the extent of entrepreneurship is linked to its social context. A sample of 20 women entrepreneurs was taken from the main cities in Estonia (Tallinn, Tartu, Narva and Kurresaare) to explain the experience of female entrepreneurs.