Information, Volume 11, Issue 12 (December 2020) – 49 articles

Digital transformation creates challenges in all industries and business sectors. The development of digital transformation has also clearly triggered the emergence of fintech (financial technology) initiatives, which are recognized as some of the most important innovations in the financial industry. These initiatives are developing rapidly, driven in part by the sharing economy, regulations, and information technology. However, research in the field of fintech remains in its infancy. Fintech offers several services, such as funding, payment (including electronic wallets), e-aggregators, e-trading, and e-insurance, and cryptocurrencies such as Bitcoin. This provides an opportunity to more closely examine fintech’s research challenges and trends. This study aims to (1) determine the state of the art of financial technology research; (2) identify gaps in the financial technology research field; and (3) identify challenges and trends for future research potential. The novel proposal in this study includes theoretical contributions regarding financial technology. Using the systematic literature review approach of Kitchenham, in addition to thematic analysis, meta-analysis and observation to validate the quality of literature and analysis, the results of this study provide a theoretical basis fintech research from an information systems perspective, including the formulation of fintech technology concepts and their development. Full article

This paper is devoted to solving the problem of determining the age of the author of the text based on models of deep neural networks. The article presents an analysis of methods for determining the age of the author of a text and approaches to determining the age of a user by a photo. This could be a solution to the problem of inaccurate data for training by filtering out incorrect user-specified age data. A detailed description of the author’s technique based on deep neural network models and the interpretation of the results is also presented. The study found that the proposed technique achieved 82% accuracy in determining the age of the author from Russian-language text, which makes it competitive in comparison with approaches for other languages. Full article

The ever-increasing deployment of autonomous Cyber-Physical Systems (CPSs) (e.g., autonomous cars, UAV) exacerbates the need for efficient formal verification methods. In this setting, the main obstacle to overcome is the huge number of scenarios to be evaluated. Statistical Model Checking (SMC) is a simulation-based approach that holds the promise to overcome such an obstacle by using statistical methods in order to sample the set of scenarios. Many SMC tools exist, and they have been reviewed in several works. In this paper, we will overview Monte Carlo-based SMC tools in order to provide selection criteria based on Key Performance Indicators (KPIs) for the verification activity (e.g., minimize verification time or cost) as well as on the environment features, the kind of system model, the language used to define the requirements to be verified, the statistical inference approach used, and the algorithm implementing it. Furthermore, we will identify open research challenges in the field of (SMC) tools. Full article

Today, many complex multiobjective problems are dealt with using genetic algorithms (GAs). They apply the evolution mechanism of a natural population to a “numerical” population of solutions to optimize a fitness function. GA implementations must find a compromise between the breath of the search (to avoid being trapped into local minima) and its depth (to prevent a rough approximation of the optimal solution). Most algorithms use “elitism”, which allows preserving some of the current best solutions in the successive generations. If the initial population is randomly selected, as in many GA packages, the elite may concentrate in a limited part of the Pareto frontier preventing its complete spanning. A full view of the frontier is possible if one, first, solves the single-objective problems that correspond to the extremes of the Pareto boundary, and then uses such solutions as elite members of the initial population. The paper compares this approach with more conventional initializations by using some classical tests with a variable number of objectives and known analytical solutions. Then we show the results of the proposed algorithm in the optimization of a real-world system, contrasting its performances with those of standard packages. Full article

Currently, there are several challenges that cloud-based healthcare systems around the world are facing. The most important issue is to ensure security and privacy, or in other words, to ensure the confidentiality, integrity, and availability of the data. Although the main provisions for data security and privacy were present in the former legal framework for the protection of personal data, the General Data Protection Regulation (GDPR) introduces new concepts and new requirements. In this paper, we present the main changes and the key challenges of the GDPR and, at the same time, we present how a cloud-based security policy could be modified in order to be compliant with the GDPR, as well as how cloud environments can assist developers to build secure and GDPR compliant cloud-based healthcare systems. The major concept of this paper is dual-purpose; primarily, to facilitate cloud providers in comprehending the framework of the new GDPR and secondly, to identify security measures and security policy rules, for the protection of sensitive data in a cloud-based healthcare system, following our risk-based security policy methodology that assesses the associated security risks and takes into account different requirements from patients, hospitals, and various other professional and organizational actors. Full article

Undoubtedly, one of the most powerful applications that allow symbolic computations is Wolfram Mathematica. However, it turns out that sometimes Mathematica does not give the desired result despite its continuous improvement. Moreover, these gaps are not filled by many authors of books and tutorials. For example, our attempts to obtain a compact symbolic description of the roots of polynomials or coefficients of a polynomial with known roots using Mathematica have often failed and they still fail. Years of our work with theory, computations, and different kinds of applications in the area of polynomials indicate that an application ‘offering’ the user alternative methods of solving a given problem would be extremely useful. Such an application would be valuable not only for people who look for solutions to very specific problems but also for people who need different descriptions of solutions to known problems than those given by classical methods. Therefore, we propose the development of an application that would be not only a program doing calculations but also containing an interactive database about polynomials. In this paper, we present examples of methods and information which could be included in the described project. Full article

The cultural meme is the smallest unit constituting a dynasty′s culture, which has the same inheritance and variability as biological genes. Here, based on the name of cultural relics, we extract cultural memes through semantic word segmentation, word frequency statistics, and the synonym merging method, and construct dynasty cultural meme vectors. We analyzed color, auxiliary, texture, shape, and overall networks of five types of model to construct the culture network, using the social network analysis method, and explored the clustering and degrees of centrality characteristics of cultural memes. We then analyzed the similarities and differences among cultures of the dynasties. The main conclusions are as follows: (1) Cultural memes represent different cultural characteristics of dynasties, and the inheritance and differences among dynasties’ cultures are closely related to their historical background. (2) Prevalence memes construct the cultural label of dynasties, which can roughly restore the cultural appearance of dynasties through fewer prevalence memes. (3) The use of community detection with a cultural meme network can determine the clustering of dynasties′ cultures, and the degree of centrality further reflects the main cultural characteristics presented by successive dynasties. Full article

Object detection for vehicles and pedestrians is extremely difficult to achieve in autopilot applications for the Internet of vehicles, and it is a task that requires the ability to locate and identify smaller targets even in complex environments. This paper proposes a single-stage object detection network (YOLOv3-promote) for the detection of vehicles and pedestrians in complex environments in cities, which improves on the traditional You Only Look Once version 3 (YOLOv3). First, spatial pyramid pooling is used to fuse local and global features in an image to better enrich the expression ability of the feature map and to more effectively detect targets with large size differences in the image; second, an attention mechanism is added to the feature map to weight each channel, thereby enhancing key features and removing redundant features, which allows for strengthening the ability of the feature network to discriminate between target objects and backgrounds; lastly, the anchor box derived from the K-means clustering algorithm is fitted to the final prediction box to complete the positioning and identification of target vehicles and pedestrians. The experimental results show that the proposed method achieved 91.4 mAP (mean average precision), 83.2 F1 score, and 43.7 frames per second (FPS) on the KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) dataset, and the detection performance was superior to the conventional YOLOv3 algorithm in terms of both accuracy and speed. Full article

We applied evolutionary game theory to extend a resource constrained security game model for confidentiality attacks and defenses in an Advanced Metering Infrastructure (AMI), which is a component of IoT-enabled Smart Grids. The AMI is modeled as a tree structure where each node aggregates the information of its children before encrypting it and passing it on to its parent. As a part of the model, we developed a discretization scheme for solving the replicator equations. The aim of this work was to explore the space of possible behaviors of attackers and to develop a framework where the AMI nodes adaptively select the most profitable strategies. Using this model, we simulated the evolution of a population of attackers and defenders on various cases resembling the real life implementation of AMI. We discuss in depth how to enhance security in AMI using evolutionary game theory either by a priori analysis or as a tool to run dynamic and adaptive infrastructure defense. Full article

Due to the growth of users and linked devices in networks, there is an emerging need for dynamic solutions to control and manage computing and network resources. This document proposes a Distributed Wireless Operative System on a Mobile Ad-hoc Network (MANET) to manage and control computing resources in relation to several virtual resources linked in a wireless network. This prototype has two elements: a local agent that works on each physical node to manage the computing resources (e.g., virtual resources and distributed applications) and an orchestrator agent that monitors, manages, and deploys policies on each physical node. These elements arrange the local and global computing resources to provide a quality service to the users of the Ad-hoc cluster. The proposed S.O.V.O.R.A. model (Operating Virtualized System oriented to Ad-hoc networks) defines primitives, commands, virtual structures, and modules to operate as a distributed wireless operating system. Full article

Frequency analysis is often used to investigate the structure of systems representing multi-scale real-world phenomena. In many different environments, functional relationships characterized by a power law have been recognized, but, in many cases this simple model has turned out to be absolutely inadequate and other models have been proposed. In this paper, we propose a general abstract model which constitutes a unifying framework, including many models found in literature, like the mixed model, the exponential cut-off and the log-normal. It is based on a discrete-time stochastic process, which leads to a recurrence relation describing the temporal evolution of the system. The steady state solution of the system highlights the probability distribution, which underlies the frequency behavior. A particular instance of the general model, called cubic-cut-off, was analyzed and tested in a number of experiments, producing good answers in difficult cases, even in the presence of peculiar behaviors. Full article

Nowadays we are witnessing a significant change in content consumption. This, together with the global health situation, has caused some behaviors to accelerate. This research focuses on the specific case of the lockdown in Spain and the coincidence with the launch of the fourth season of Money Heist compared to the launch of season three. Starting with a review of the theoretical framework, in which the related concepts of coronavirus, television, and Video on Demand (VOD) platforms are presented, the importance of transmedia communication is also introduced. The methodological aspect is developed through content analysis and in-depth interviews. The tool used on the first methodology has been Twlets. With regard to the sources, the specific bibliography of the audiovisual sector, the official profile of the series on Twitter and personal interviews with professionals from the communication department of the production company, Vancouver Media, and from the series directing were taken into account. The methodology used to carry out this work has been the analysis of quantitative–qualitative content of the various sources consulted. The results of the study are presented in graphs, crossing the data from the different sources to detect the strategies of marketing and communication used for the release of the fourth season of the series. These results reflect the change in the communication strategy, the behavior of the social audience of the Twitter account of Money Heist (La Casa de Papel) and its relationship with the period of lockdown in Spain. Full article

The conceptual approach in this article follows and analyzes the holistic model of Kuivalainen, Sundqvist, Saarenketo, and McNaughton in 2012, making it analytically fitting to the SMEs’ international strategic groups concerning their international scale and scope. That model, according to our conceptual proposal, needs a methodological readjustment to an effective conformity towards the cross-sectional research. Accordingly, we presented two main considerations. First, we put together a conceptual model, fitted towards the field of top managers’ psychological characteristics as major antecedent of the firms’ international strategy. Second, the proposed conceptual model is methodologically oriented for cross-sectional studies. In relation to the antecedents, we took top managers’ emotional intelligence and cultural intelligence as distinctive capabilities of the firms’ international strategy and as major antecedents of top managers’ networking behaviors. Regarding firms’ international performance as the major conceptual model outcome, a multidimensional approach is taken with financial, strategic, and overall performance. These elements of the international firms are regarded as of major importance within the international firms’ enterprise architecture. Methodologically, we performed a bibliographic review on the fundamental concepts that we present in the model. Concerning the results, we provided a research model that raised a whole set of new leads for research with some proposals for future investigations. Full article

The objective of the article is to reveal an approach to hiding the code of stored programs stored in the database. The essence of this approach is the complex use of the method of random permutation of code symbols related to a specific stored program, located in several rows of some attribute of the database system table, as well as the substitution method. Moreover, with the possible substitute of each character obtained after the permutation with another one randomly selected from the Unicode standard, a legitimate user with the appropriate privileges gets access to the source code of the stored program due to the ability to quickly perform the inverse to masking transformation and overwrite the program code into the database. All other users and attackers without knowledge of certain information can only read the codes of stored programs masked with format preserving. The proposed solution is more efficient than the existing methods of hiding the code of stored programs provided by the developers of some modern database management systems (DBMS), since an attacker will need much greater computational and time consumption to disclose the source code of stored programs. Full article

Mass spectrometry imaging (MSI) is an imaging technique used in analytical chemistry to study the molecular distribution of various compounds at a micro-scale level. For each pixel, MSI stores a mass spectrum obtained by measuring signal intensities of thousands of mass-to-charge ratios ($m/z$-ratios), each linked to an individual molecular ion species. Traditional analysis tools focus on few individual $m/z$-ratios, which neglects most of the data. Recently, clustering methods of the spectral information have emerged, but faithful detection of all relevant image regions is not always possible. We propose an interactive visual analysis approach that considers all available information in coordinated views of image and spectral space visualizations, where the spectral space is treated as a multi-dimensional space. We use non-linear embeddings of the spectral information to interactively define clusters and respective image regions. Of particular interest is, then, which of the molecular ion species cause the formation of the clusters. We propose to use linear embeddings of the clustered data, as they allow for relating the projected views to the given dimensions. We document the effectiveness of our approach in analyzing matrix-assisted laser desorption/ionization (MALDI-2) imaging data with ground truth obtained from histological images. Full article

Most business enterprises are small and medium-sized enterprises (SMEs), and many of them are without a human resource and recruitment department. Thus, one of the challenges that organizations currently face is to find a strategy to retain and attract talent. To overcome this difficulty, enterprises must invest in employer branding policies and be aware of the factors that differentiate them from others when attracting employees. This study aims to develop an employer branding model applicable to SMEs, to increase and enhance the attraction and retention of talents. An exploratory approach based on a quantitative perspective was adopted to develop an employer branding model applied to SMEs, with two major reference employer branding models and frameworks used as the main support. The model of employer branding was applied to SMEs regarding four dimensions, whereby essential questions are asked, namely (1) organizational culture (e.g., do employees have a job description aligned with the corporate culture?), (2) company strategy (e.g., what is the strategy if business volume decreases?), (3) company reputation (e.g., how do you perceive and treat negative feedback?), and (4) reward systems (e.g., do you feel that your employees are motivated intrinsically or extrinsically or both?), ordered by layers based on a logical sequence. The new proposed model is expected to serve as a useful strategic tool and as a basis for attracting, retaining and managing talent, specifically in the SMEs context. This new model provides a set of strategic and competitiveness benefits for SMEs, while contributing to making enterprises more profitable. The model also contributes to SMEs having a better image and reputation, enabling them to stand out from others in the war for talent. Full article

Practitioners and researchers have shown great interest in information-technology (IT)-enabled interactions across partnering firms and developed instruments for measuring it. However, those instruments might have been under criticism as they were developed before the widespread adoption of the new IT applications like video conferences, DingTalk and WeChat Moments among Chinese managers for the last five years. The purpose of this study is to validate the instrument of IT-enabled formal and informal interactions for the contemporary Chinese context. First, the study reviews the literature on IT-enabled interfirm interactions and designs an open questionnaire through in-depth interviews. Answers from 85 pairs of suppliers and manufacturers are coded and the preliminary item pool is generated through the qualitative analysis. Next, a small-scale pretest with 120 manufacturing firms is conducted to purify and modify the item pool. Finally, a large-scale analysis with 336 manufacturing firms is conducted to check the reliability and validity of the measurements. The finalized scale yields six items measuring IT-enabled formal interaction and five items measuring IT-enabled informal interaction, among which six are newly derived in this study. The validated instrument reveals satisfactory reliability and validity and can serve as the basic instruments for future research on IT-enabled interactions. Full article

Under the “Internet+” environment, the R&D intensity of products and services has increased; hence, organizations need to improve their ability to integrate knowledge and technology resources. Knowledge gaps will arise when an organization’s knowledge reserves fail to meet the needs of innovation activities. This research established a network of complete knowledge topics under the “Internet+” environment based on the Word2Vec model. The word vectors and word frequencies of organizational reserve knowledge texts were analyzed to establish an organizational reserve knowledge topic network. The Term Frequency-Inverse Document Frequency algorithm was used to identify the demanded knowledge topic. The satisfaction capability of demanded knowledge in the reserve knowledge topic network was calculated via the eigenvector centrality and the fuzzy evaluation method. The corresponding strategies were then put forward to make up the knowledge gap. Finally, a case study was conducted and compared with SWOT (Strengths, Weaknesses, Opportunities, and Threats) and Venn diagram analysis on the economic and management college of a university in Beijing to verify the effectiveness of this method. Full article

In this article a completely objective decoherence mechanism is hypothesized, operating at the level of the elementary particles of matter. The standard quantum mechanical description is complemented with a phenomenological evolution equation, involving a scalar curvature and an internal time, distinct from the observable time of the laboratory. This equation admits solutions internal to the wave function collapse, and the classical instantons connected to these solutions represent de Sitter micro-spaces identifiable with elementary particles. This result is linked in a natural way to other research programs tending to describe the internal structure of elementary particles by means of de Sitter spaces. Both the possible implications in particle physics and those deriving from the conversion of quantum information (qubits) into classical information (bits) are highlighted. Full article

With the advent of Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies, the networking infrastructures are becoming increasingly agile in their attempts to offer the quality of services needed by the users, maximizing the efficiency of infrastructure utilization. This in essence mandates the statistical multiplexing of demands across the infrastructures of different Network Providers (NPs), which would allow them to cope with the increasing demand, upgrading their infrastructures at a slower pace. However, to enjoy the benefits of statistical multiplexing, a trusted authority to govern it would be required. At the same time, blockchain technology aspires to offer a solid advantage in such untrusted environments, enabling the development of decentralized solutions that ensure the integrity and immutability of the information stored in the digital ledger. To this end, in this paper, we propose a blockchain-based solution that allows NPs to trade their (processing and networking) resources. We implemented the solution in a test-bed deployed on the cloud and we present the gathered performance results, showing that a blockchain-based solution is feasible and appropriate. We also discuss further improvements and challenges. Full article

Nowadays, we are witnessing a shift in the way emergencies are being managed. On the one hand, the availability of big data and the evolution of geographical information systems make it possible to manage and process large quantities of information that can hugely improve the decision-making process. On the other hand, digital humanitarianism has shown to be very beneficial for providing support during emergencies. Despite this, the full potential of combining automatic big data processing and digital humanitarianism approaches has not been fully realized, though there is an initial body of research. This paper aims to provide a reference architecture for emergency management that instantiates the NIST Big Data Reference Architecture to provide a common language and enable the comparison of solutions for solving similar problems. Full article

Road pavements need adequate maintenance to ensure that their conditions are kept in a good state throughout their lifespans. For this to be possible, authorities need efficient and effective databases in place, which have up to date and relevant road condition information. However, obtaining this information can be very difficult and costly and for smart city applications, it is vital. Currently, many authorities make maintenance decisions by assuming road conditions, which leads to poor maintenance plans and strategies. This study explores a pathway to obtain key information on a roadway utilizing drone imagery to replicate the roadway as a 3D model. The study validates this by using structure-from-motion techniques to replicate roads using drone imagery on a real road section. Using 3D models, flexible segmentation strategies are exploited to understand the road conditions and make assessments on the level of degradation of the road. The study presents a practical pipeline to do this, which can be implemented by different authorities, and one, which will provide the authorities with the key information they need. With this information, authorities can make more effective road maintenance decisions without the need for expensive workflows and exploiting smart monitoring of the road structures. Full article

Crowd Crowd counting is not simply a matter of counting the numbers of people, but also requires that one obtains people’s spatial distribution in a picture. It is still a challenging task for crowded scenes, occlusion, and scale variation. This paper proposes a global and local attention network (GLANet) for efficient crowd counting, which applies an attention mechanism to enhance the features. Firstly, the feature extractor module (FEM) uses the pertained VGG-16 to parse out a simple feature map. Secondly, the global and local attention module (GLAM) effectively captures the local and global attention information to enhance features. Thirdly, the feature fusing module (FFM) applies a series of convolutions to fuse various features, and generate density maps. Finally, we conduct some experiments on a mainstream dataset and compare them with state-of-the-art methods’ performances. Full article

There is low adoption of Information Technologies (IT) in the administration of small bovine production systems which causes that most decisions are made based on the experience of the administrators and not based on data. This study proposes a methodological strategy to improve the adoption and appropriation of a Decision Support System (DSS) in the aforementioned kind of systems. The strategy includes gamification elements in the training supported in three IT tools, which help with the understanding of the connection between the tools. The tools are a simulation model, a serious video game, and the DSS. The design and development of the strategy used Design and Development Research and Case Study, System Dynamics to develop the simulation model and a Rational Unified Process to develop the serious video game and the DSS. The methodology was implemented in Santander, Colombia with informative sessions and working with producers in aided simulated environments with the goal of getting participants to use the proposed tools in their environments in a voluntary, autonomous, lasting way. Results showed the impact of the ludic and pedagogical components for the appropriation of the technology. 22 months after finishing the aided sessions 34% of the farmers show appropriation of the DSS and use it on their farms. Full article

The Internet of Things (IoT) has created new and challenging opportunities for data analytics. The IoT represents an infinitive source of massive and heterogeneous data, whose real-time processing is an increasingly important issue. IoT applications usually consist of multiple technological layers connecting ‘things’ to a remote cloud core. These layers are generally grouped into two macro levels: the edge level (consisting of the devices at the boundary of the network near the devices that produce the data) and the core level (consisting of the remote cloud components of the application). The aim of this work is to propose an adaptive microservices architecture for IoT platforms which provides real-time stream processing functionalities that can seamlessly both at the edge-level and cloud-level. More in detail, we introduce the notion of $\mu$-service, a stream processing unit that can be indifferently allocated on the edge and core level, and a Reference Architecture that provides all necessary services (namely Proxy, Adapter and Data Processing $\mu$-services) for dealing with real-time stream processing in a very flexible way. Furthermore, in order to abstract away from the underlying stream processing engine and IoT layers (edge/cloud), we propose: (1) a service definition language consisting of a configuration language based on JSON objects (interoperability), (2) a rule-based query language with basic filter operations that can be compiled to most of the existing stream processing engines (portability), and (3) a combinator language to build pipelines of filter definitions (compositionality). Although our proposal has been designed to extend the Senseioty platform, a proprietary IoT platform developed by FlairBit, it could be adapted to every platform based on similar technologies. As a proof of concept, we provide details of a preliminary prototype based on the Java OSGi framework. Full article

While security is often recognized as a top priority for organizations and a push for competitive advantage, repeatedly, Internet of Things (IoT) products have become a target of diverse security attacks. Thus, orchestrating smart services and devices in a more open, standardized and secure way in IoT environments is yet a desire as much as it is a challenge. In this paper, we propose a model for IoT practitioners and researchers, who can adopt a sound security thinking in parallel with open IoT technological developments. We present the state-of-the-art and an empirical study with IoT practitioners. These efforts have resulted in identifying a set of openness and security thinking criteria that are important to consider from an IoT ecosystem point of view. Openness in terms of open standards, data, APIs, processes, open source and open architectures (flexibility, customizability and extensibility aspects), by presenting security thinking tackled from a three-dimensional point of view (awareness, assessment and challenges) that highlight the need to develop an IoT security mindset. A novel model is conceptualized with those characteristics followed by several key aspects important to design and secure future IoT systems. Full article

Social sciences and humanities (SSH) research is divided across a wide array of disciplines, sub-disciplines and languages. While this specialization makes it possible to investigate the extensive variety of SSH topics, it also leads to a fragmentation that prevents SSH research from reaching its full potential. The TRIPLE project brings answers to these issues by developing an innovative discovery platform for SSH data, researchers’ projects and profiles. Having started in October 2019, the project has already three main achievements that are presented in this paper: (1) the definition of main features of the GOTRIPLE platform; (2) its interoperability; (3) its multilingual, multicultural and interdisciplinary vocation. These results have been achieved thanks to different methodologies such as a co-design process, market analysis and benchmarking, monitoring and co-building. These preliminary results highlight the need for respecting diversity of practices and communities through coordination and harmonization. Full article

Mason’s gain formula can grow factorially because of growth in the enumeration of paths in a directed graph. Each of the (n − 2)! permutation of the intermediate vertices includes a path between input and output nodes. This paper presents a novel method for analyzing the loop gain of a signal flow graph based on the transform matrix approach. This approach only requires matrix determinant operations to determine the transfer function with complexity O(n³) in the worst case, therefore rendering it more efficient than Mason’s gain formula. We derive the transfer function of the signal flow graph to the ratio of different cofactor matrices of the augmented matrix. By using the cofactor expansion, we then obtain a correspondence between the topological operation of deleting a vertex from a signal flow graph and the algebraic operation of eliminating a variable from the set of equations. A set of loops sharing the same backward edges, referred to as a loop group, is used to simplify the loop enumeration. Two examples of feedback networks demonstrate the intuitive approach to obtain the transfer function for both numerical and computer-aided symbolic analysis, which yields the same results as Mason’s gain formula. The transfer matrix offers an excellent physical insight, because it enables visualization of the signal flow. Full article

This paper focuses on recommender system for agriculture in Mali called SyrAgri. The goal is to guide and improve the quality-of-experience of farmers by offering them good farming practices according to their needs. Two types of recommendations are essentially taken into account: the recommendation of crops and the recommendation of farming practices based on some predefined criteria which are: yield, life cycle of the crop, type of soil, growing season, etc. SyrAgri also informs farmers about crop rotation and the similarity between different types of crops based on the following parameters: crop families, growing seasons and appropriate soil types. For the development of this system a hybrid recommendation approach was used: demographic, semantic and collaborative methods. Each method is adapted to a specific stage of a user’s visit to the system. The demographic approach is first activated in order to offer recommendations to new users of the system, which resolves the concept of cold start (immediate inclusion of a new item or a new user in the system). The semantic approach is then activated to recommend to the user items (crops, agricultural practices) semantically close to those (s)he has appreciated. Finally, the collaborative approach is used to recommend items that similar users have liked. Full article