Link Information Research Articles

Content and quantity of highlights and annotations predict learning from multiple digital texts

Learning from multiple texts is an essential yet challenging academic task. Thus, a persistent need in the field is identifying those strategies that will support students' learning from multiple texts, and facilitating their use. In this study, we adopt a quasi-experimental design to examine how the use of digital annotations, allowing undergraduates (N = 278) to identify and, potentially, link important concepts across texts, can be used to foster learning from multiple texts. Additionally, we examine students' digital highlights and annotations under four different strategy conditions, assigned to elicit different forms of processing found to be effective in prior work. These conditions included asking students to highlight and annotate (a) important or relevant information in texts, (b) connections or links across texts (i.e., intertextual reasoning condition), (c) information in texts facilitating evaluation, and (d) difficult to understand information (i.e., metacognitive monitoring condition). Some differences were found in students' rendering of highlights and annotations across strategy conditions, however, no differences in multiple text comprehension and integration performance were found across strategy conditions. Still, membership in the metacognitive monitoring strategy condition, relative to the relevance condition, as well as students’ highlighting of information supporting evaluation (i.e., source information, statistical evidence), and accessing of references during reading were predictive of multiple text comprehension and integration. Thus, this study contributes to theory by providing further evidence of strategies (e.g., metacognitive monitoring, evaluation) supportive of multiple text learning and introduces a promising means whereby such strategy use may be fostered.

Spinel lithium titanate anode/polyether sulfone nanocomposite synthesized by pulsed laser ablation method for optoelectronic applications

Nowadays, to increase the usage of energy storage applications like electric cars or stationary storage, the cost of these manufacturers must be reduced. Our present study focuses on an alternate electrode production approach to suit the needs of today's lithium ion battery’s cost efficiency by using an eco-friendly method, the pulsed laser ablation method in liquid media technique, which was used for the first time to synthesize spinel lithium titanate anode, Li4Ti5O12 nanoparticles (LTO NPs), and incorporate them with polyether sulfone (PES) in just one step to form a PES/LTO nanocomposite. The evidence from XRD showed that the nanocomposite film is formed as a crystalline phase from a cubic spinel structure corresponding to LTO, with crystalline sizes around 9.4 nm. Furthermore, SEM revealed a semi-spherical distribution of LTO NPs throughout the PES matrix. Also, the elemental analysis provides the elemental peaks for C, S, Ti, and O, and no other elemental peaks do, confirming their purity. Moreover, the FT-IR investigation affirmed the interaction between PES and LTO NPs via the sulfone group with the breakage of the sulfur and oxygen double bond and the formation of a new link between SOLa and SOTi that may be responsible for the emergence of this band. Also, the absorption study confirmed the formation of localized states between occupied and unoccupied molecular orbital bands is made feasible by the chemical linkages between PES chains and LTO NPs. As a result of the dielectric investigation, LTO NPs are a good choice for usage as dopants to enhance the electrical characteristics of PES polymer. Overall, the PES/LTO nanocomposite films' improved dielectric and optical properties make them appropriate for energy storage applications.

Dynamic community detection including node attributes

Community detection is an important task in social network analysis. It is generally based on the links of a static network, where groups of connected nodes can be found. Real-world problems, however, are often characterized by behavior that changes over time. In such cases, we need dynamic community detection algorithms because they better capture the underlying dynamics. Furthermore, the inclusion of node attributes provides a more robust approach since dynamic attribute values could also indicate changes in the communities. We propose an algorithm for COmmunity DEtection in Dynamic Attributed NETworks (CoDeDANet), which allows us to find groups in dynamic attributed networks using both the link and node information. In the first phase, based on spectral clustering, the attributes’ importance is optimized in a setting that joins the nodes’ features with a topological structure. In a second phase, tensors are used to consider not only current but also past information. The algorithm was tested on four synthetic networks and two real-world social networks. The results show that CoDeDANet outperforms the other state-of-the-art community detection algorithms.

Online Energy Consumption Optimization in WPCNs With Time-Varying Energy Storage Efficiency

This work considers a wireless powered communication network (WPCN), in which wireless nodes store the energy from an energy access point in their batteries for subsequent data transmission. An online energy consumption optimization strategy is proposed for adaptively determining the beamforming vector, data routing, network operation mode and transmitted power based only on the current state of WPCN. In most existing results, the energy/data transmission of WPCNs is based on the ideal battery models and the energy storage efficiencies therein are always assumed to be non-zero constants. Since the energy storage efficiency of batteries may be affected by the ambient environment or aging in real-time, this work considers a WPCN with a time-varying energy storage efficiencies sequence and correspondingly develops an improved Lyapunov optimization strategy to offset the impact of the time-varying energy storage efficiencies. More importantly, a distributed strategy is proposed to optimize the cooperation of wireless nodes over unrestricted numbers of hops, and thus the energy access point does not require channel state information of all data links and the data backlog queues of all nodes during the solving process. Accordingly, the computational burden at the energy access point is greatly reduced due to the use of this distributed strategy. Under this strategy, the time-averaged expected energy consumption of WPCN can be within a bounded gap of the minimum energy required to maintain stability of the network. Finally, the theoretical analysis is further corroborated by simulation results.

Multi-Stage Machine Learning Model for Hierarchical Tie Valence Prediction

Individuals interacting in organizational settings involving varying levels of formal hierarchy naturally form a complex network of social ties having different tie valences (e.g., positive and negative connections). Social ties critically affect employees’ satisfaction, behaviors, cognition, and outcomes—yet identifying them solely through survey data is challenging because of the large size of some organizations or the often hidden nature of these ties and their valences. We present a novel deep learning model encompassing NLP and graph neural network techniques that identifies positive and negative ties in a hierarchical network. The proposed model uses human resource attributes as node information and web-logged work conversation data as link information. Our findings suggest that the presence of conversation data improves the tie valence classification by 8.91% compared to employing user attributes alone. This gain came from accurately distinguishing positive ties, particularly for male, non-minority, and older employee groups. We also show a substantial difference in conversation patterns for positive and negative ties with positive ties being associated with more messages exchanged on weekends, and lower use of words related to anger and sadness. These findings have broad implications for facilitating collaboration and managing conflict within organizational and other social networks.

System characteristics and matrix tools for evaluating innovative business models of youth tourism

This scientific article is devoted to the issues of identifying innovative business models of youth tourism based on two scientific approaches: functional-innovative (customized business model, virtual tourism platform, franchising business model) and holistic (shared tourism platforms, outdoor co-working tourism, organization of youth hostels, mobile karaoke bars and pub for youth, developing tourism programs (including package tours) for social networks, couchsurfing tours for youth, personalized tourism offers for young people, the organization of «combo tours» (combination of several types of tourism), crowdsourcing tourism, organization of tours in the format of «digital nomads», organization of tree tours, transformational tourism, digital tourism, organization of tours with ATVs, mopeds and bicycles). Furthermore, the study was able to identify conceptual business models that describe the specific characteristics and components of the different types of youth tourism: close interaction between tour operator, travel agency and end consumer based on the use of digital solutions; partial involvement of tour operators and travel agencies in the design of the tourist offer or without; involvement of third parties not directly connected with the tourism market; the presence of a large number of intermediaries; pronounced customization of services; participation of the main players in the tourist market of service organizations through intermediaries; organization of trips without physical departure using digital tools; close interaction of individuals in the process of organizing trips based on digital platforms. In the work, a scientometric and content analysis of search queries was conducted to identify important research areas within the framework of the scientific problems considered by the authors (the total amount of information used for the study was 4309 scientific documents; at the same time, the number of search queries processed in Google Trends was 4 units with an average observation period of 5 years); in addition, the distinguishing features of classic and innovative business models, including those related to the tourism business, were identified, a matrix for the correspondence of conceptual and specific business models of youth tourism was created, as well as their distribution according to three selected criteria: the level of formation of tourist interest and personalization, the degree of involvement of the tourist in the process of providing tourist services. It is also important to note that based on the results of the study, a conceptual scheme for the correlation of organizational functions and the formation of structural units and organizational links within a tourism company in the selection of the optimal innovative business model for youth tourism was developed.

SOLIPSISM AS A FACTOR IN CONTENT PERSONALIZATION: PRACTICE OF INTERNET JOURNALISM

There is little research on how online journalists work to convince the public, on how online media technologies work. This article presents the research results of theoretical research on the possibility of convincing users in the sociopolitical and socioeconomic aspects of understanding content. Therefore, many users are well aware of the creation and consumption of information within the functional boundaries of the Internet, analyzing the goal of identifying gaps in the individual meaning of the audience about the content. The objective of this article is to highlight the phenomenon of solipsism in online journalism as a standard postmodernist attempt of journalists to embed their own social experience in the individual space of man. As a results of processing the material, we came to the following conclusions. 1. The hypothesis of solipsism in online journalism assumes a certain level of civic competence. 2. The formation of strong organizational and content links between Internet media and its regular audience is generally identified by the interests, programs and forms of such actions that have value. 3. The production of online media of its own content prefers a clearly defined sociopolitical line, which leads to the suppression of idiosyncrasy, diversity and dissent. 4. The context of solipsism establishes the freedom of the audience up to its right to neglect the activities of the media in general. 5. The author can react painfully and effectively in any available way to the activities of any Internet publication. 6. The audience can act as a separate author-each content, which evaluates the practice of any online publication, using, in particular, places of mass communication.

Distributed Scheduling With Centralized Coordination for Scalable Wireless Mesh Networking

A coordinated carrier sense multiple access (C-CSMA) scheme is developed to schedule packet transmissions in multihop wireless networks. It integrates distributed scheduling and centralized coordination at different time scales. At a small time scale, a distributed scheduling algorithm, which is incorporated into CSMA, runs on each node to determine key parameters for CSMA. These parameters are optimized by ensuring multiple network attributes, i.e., average link date rate, node transmission probability, and the conditional probability of a link being selected for transmission, approaching their corresponding optimal values at a large time scale, e.g., a few seconds. Such optimal values are obtained from a centralized algorithm running on a portal node. The algorithm collects topology, link, and traffic information from the network at a large time scale and determines the attributes above to fulfill the optimal tradeoff between throughput and fairness. Since the distributed algorithm is shepherded by the centralized algorithm, C-CSMA has high scalability: first, it achieves long-term optimal performance with low information collection overhead; second, it schedules packet transmissions in a distributed way and responds quickly to changes in networks. It is proved that network attributes resulting from the distributed scheduling algorithm converge to optimal values provided by the centralized algorithm. Simulation experiments demonstrate that the convergence speed is fast. Moreover, extensive simulation results show that C-CSMA achieves much higher throughput, better fairness, and lower delay than existing scheduling schemes under different carrier sensing thresholds and traffic conditions.

Temporal motif-based attentional graph convolutional network for dynamic link prediction

Dynamic link prediction is an important component of the dynamic network analysis with many real-world applications. Currently, most advancements focus on analyzing link-defined neighborhoods with graph convolutional networks (GCN), while ignoring the influence of higher-order structural and temporal interacting features on link formation. Therefore, based on recent progress in modeling temporal graphs, we propose a novel temporal motif-based attentional graph convolutional network model (TMAGCN) for dynamic link prediction. As dynamic graphs usually contain periodical patterns, we first propose a temporal motif matrix construction method to capture higher-order structural and temporal features, then introduce a spatial convolution operation following a temporal motif-attention mechanism to encode these features into node embeddings. Furthermore, we design two methods to combine multiple temporal motif-based attentions, a dynamic attention-based method and a reinforcement learning-based method, to allow each individual node to make the most of the relevant motif-based neighborhood to propagate and aggregate information in the graph convolutional layers. Experimental results on various real-world datasets demonstrate that the proposed model is superior to state-of-the-art baselines on the dynamic link prediction task. It also reveals that temporal motif can manifest the essential dynamic mechanism of the network.

Cooperative multi-camera vehicle tracking and traffic surveillance with edge artificial intelligence and representation learning

Traffic surveillance cameras are the eyes of the Intelligent Transportation Systems (ITS). However, they are currently isolated and can only extract information from each of their fixed views. To track vehicles across multiple cameras and help public agencies collect link travel time and speed information, an Edge-empowered Cooperative Multi-camera Sensing (ECoMS) System is proposed. ECoMS system presents a novel algorithmic and edge-server cooperative system construct to push edge computing and multi-camera re-identification workflow serving for traffic sensing based on Internet of Things (IoT) architecture. On the algorithm side, ECoMS system proposes a featherlight edge-based computer vision framework for vehicle detection, tracking, and features selection process in a real-time manner. Then, by only sending the objects’ representations to the server, the high-bandwidth data transmission and the heavy post-processing system can be abandoned. Furthermore, a hierarchical clip-based deep vehicle re-identification framework is proposed and integrated into the ECoMS system, and significantly outperforms other state-of-the-art methods by 4%–8% on Rank-1 accuracy. Finally, to balance the accuracy level of different camera pairs, a collaborative cross-camera traffic information estimation framework based on kernel density estimation with kernel smoother is implemented, which can get the precise link and region traffic information together with distributions (less than 1.01 KL distance). By maximizing the cooperation of the computational resources, orchestrating the data transmission and integrating road network graph features in the system, the ECoMS can precisely model the network-scale traffic information in a flexible, cost-effective, and scalable workflow. To the author’s best knowledge, ECoMS is the first multi-camera vehicle tracking and traffic monitoring system based on cooperative IoT architecture.

Exploring the mobility in the Madrid Community

Displacements within urban spaces have attracted particular interest among researchers. We examine the journeys that happen in the Madrid Community considering 24 travel typologies and 1390 administrative areas. From an origin–destination (OD) matrix, four classes of major flows are characterised through coarse-graining: hotspot–non-hotspots, non-hotspot–hotspots, hotspots–hotspots, non-hotspot–non-hotspot. In order to make comparisons between them with respect to spatial and temporal patterns, several statistical tests are performed. The spatial activity as well as transition probabilities between administrative zones are also analysed. The mobility network’s topology is examined (some parameters such as maximal connected components, average degree, betweenness, and assortativity as well as the k-cores are checked). A model describing the formation of links between zones (existence of at least one trip between them) is constructed based on certain measures of affinity between areas.

A developer-oriented recommender model for the app store: A predictive network analytics approach

While thousands of new mobile applications (i.e., apps) are being added to the major app markets daily, only a small portion of them attain their financial goals and survive in these competitive marketplaces. A key to the quick growth and success of relatively less popular apps is that they should make their way to the limited list of apps recommended to users of already popular apps; however, the focus of the current literature on consumers has created a void of design principles for app developers. In this study, employing a predictive network analytics approach combined with deep learning-based natural language processing and explainable artificial intelligence techniques, we shift the focus from consumers and propose a developer-oriented recommender model. We employ a set of app-specific and network-driven variables to present a novel approach for predicting potential recommendation relationships among apps, which enables app developers and marketers to characterize and target appropriate consumers. We validate the proposed model using a large (>23,000), longitudinal dataset of medical apps collected from the iOS App Store at two time points. From a total of 10,234 network links (recommendations) formed between the two data collection points, the proposed approach was able to correctly predict 8,780 links (i.e., 85.8 %). We perform Shapley Additive exPlanation (SHAP) analysis to identify the most important determinants of link formations and provide insights for the app developers about the factors and design principles they can incorporate into their development process to maximize the chances of success for their apps.

Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021-2022.

Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses. An exponential random graph model (ERGM) was used to assess the effect of 'at-risk contacts', 'same owners', 'in-bound/out-bound risk windows overlap', 'genetic differences', 'geographic distances', 'same species', and 'poultry company' on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables 'same poultry company' (Est. = 0.548, C.I. = [0.179; 0.918]) and 'risk windows overlap' (Est. = 0.339, C.I. = [0.309; 0.368]) were associated with a higher probability of link formation, while the 'genetic differences' (Est. = -0.563, C.I. = [-0.640; -0.486]) and 'geographic distances' (Est. = -0.058, C.I. = [-0.078; -0.038]) indicated a reduced probability. The integration of epidemiological data with genomic analyses allows us to monitor the epidemic evolution and helps to explain the dynamics of lateral spreads casting light on the potential diffusion routes. The 2021-2022 epidemic stresses the need to further strengthen the biosecurity measures, and to encourage the reorganization of the poultry production sector to minimize the impact of future epidemics.

Stability of Complete and Star Multiplex Networks

We propose a concept of stability for multiplex networks. First, a utility function combining benefits and costs from network connections is introduced. The utilities significantly influence incentives of players in link formation and, consequently, network structure. Costs are derived from direct links connecting players. We examine the stability conditions of multiplex networks with special network structures, in particular, complete and star network in all layers, and compare the stability conditions for two different type of benefits (with and without decay).

ФОРМУВАННЯ ОБРАЗУ ЛЕСІ УКРАЇНКИ В КИТАЙСЬКОМОВНОМУ ЛІТЕРАТУРНОМУ ПРОСТОРІ: ПСИХОЛІНГВІСТИЧНІ ТА СОЦІОКУЛЬТУРНІ ОСОБЛИВОСТІ ВЗАЄМОДІЇ МІЖ АВТОРОМ І ПЕРЕКЛАДАЧЕМ

Background. In the 20th century, Chinese literary scholars, in particular, Mao Dun, Ge Baoquan, and others, became actively interested in Lesya Ukrainka's work, which resulted in a number of translations of the writer's works into Chinese in the 1920s and 1990s. Taking into account the historical context of events in Chinese society during the 20th century, as well as analyzing the themes of the translated works of the Ukrainian poetess, the ideological prerequisites for the creation of these works were revealed. This research article focuses on the peculiarities of psycholinguistic interaction between the image of the author and the translator and analyses the impact of this interaction on the formation of a communicative link between them. In addition, the article analyses the image of women in China in the early 20th century, which allows us to identify analogies between the images of Lesia Ukrainka and the nineteenth-century Chinese poetess Qiu Jin (秋瑾，1875-1907), known for her anti-Manchu and revolutionary views. Methods. By using the imagological method and the method of contextual analysis, we analyzed the image of Lesia Ukrainka in Chinese culture, studied the historical background of its formation and the general trend of the development of the image of a woman in twentieth-century China. The historical and literary method and the method of data analysis were also used to compare the images of Lesya Ukrainka and Qiu Jin in the Chinese literary space. Results. The study found that most of Lesia Ukrainka's translations conveyed the ideas of love and longing for the country, patriotism, and the struggle for independence, which resonated with the ideological ideas of China in the 20th century and the image of an exemplary Chinese woman of that time, it was also emphasized in Soviet literary historiography (M. Zerov, S. Yefremov), which often served as a source for Chinese writers, thus forming a clichéd image of Lesya Ukrainka as a strong revolutionary fighting for the ideas of her country. Nevertheless, the kinship of Lesia Ukrainka's and Qiu Jin's creative leitmotifs, experiences and life paths complemented the already formed image of the Ukrainian writer with elements of heroism and poetry borrowed from the figure of Qiu Jin, which gave Lesia and her work in the Chinese literary environment elements of romanticism. Conclusions . In conclusion, the article is put forward that it is the association with Qiu Jin that has significantly influenced the images and symbolism of Chinese translations of Lesia Ukrainka's poetry, which requires further detailed study of the texts of translations from the point of view of the imagological aspect.

Об институционализации роли и места крупного бизнеса в решении проблем социально-экономического развития страны

The article considers the role and place of large companies in ensuring the transition of the domestic economy to an innovative sociallyoriented trajectory of functioning and development. It is noted that the leading role of large companies (previously – plants, and now, as a rule, multi-branch holdings) is usually associated with the industrialization processes and the formation of the 2-nd technological mode. At the same time in Russia factors and circumstances of spatial development of the country play a significant role, having a significant impact on the formation of features of the transition to the 4th technological mode. Large companies are expected to play the role of “anchor” participants in the processes of formation and development of horizontal links and interactions of small and medium-sized companies. Implementation of the above-mentioned potentialities of large companies has its own peculiarities due to their specific spatial organization. Under the influence of priorities of market nature in the economy of the country, and especially in individual regions, there can be increased fragmentation of production and technological links and enhanced importance of the initial raw materials redistribution. Overcoming the development of the situation in this direction involves purposeful indicative planning. According to the author, it is based primarily on the priorities and goals of scientific and technological policy.

Dumbbells, chains, and ribbons: anisotropic self-assembly of isotropic nanoparticles.

Functionalizing the surface of metal nanoparticles can assure their stability in solution or mediate their self-assembly into aggregates with controlled shapes. Here we present a computational study of the colloidal aggregation of gold nanoparticles (Au NPs) isotropically functionalized by a mixture of charged and hydrophobic ligands. We show that, by varying the relative proportion of the two ligands, the NPs form anisotropic aggregates with markedly different topologies: dumbbells, chains, or ribbons. In all cases, two kinds of connections keep the aggregates together: hydrophobic bonds and ion bridges. We show that the anisotropy of the aggregates derives from the NP shell reshaping due to the formation of the hydrophobic links, while ion bridges are accountable for the "secondary structure" of the aggregates. Our findings provide a general physical principle that can also be exploited in different self-assembled systems: anisotropic/directional aggregation can be achieved starting from isotropic objects with a soft, deformable surface.

ПРИХОВАНИЙ ВПЛИВ НА РЕЦИПІЄНТА У РЕКЛАМІ СОЦІАЛЬНОЇ МЕРЕЖІ “FACEBOOK”

The development of the information society has an impact not only on the quality of life of people, but also on the formation of new communication links. The rapid penetration of information technology into different areas of our lives has contributed to the global spread of the Internet, in which social networks are actively used for communication. For advertisers, social networks provide unique opportunities for rapid dissemination of information and direct contact with consumers. The specifics of advertising communication are not only informing the recipient about goods or services, but also influencing him/her through various means. The article raises the problem of discourse of social networks, where various manipulative strategies, tactics and techniques of influence are used when communicating in virtual space. Attention is focused on communicative and pragmatic techniques of manipulative influence on the consciousness of consumers in Ukrainian-language advertising texts of the social network “Facebook”. It is noted that in order to implement the strategy of manipulative influence, advertisers resort to various tactics. The most common of them is the transaccentuation tactic, which consists in forming a positive mood through shifting the emphasis from buying the advertised product or service to receiving pleasant emotions and sensations. Transaccentuation is most often transferred to a feeling of joy, happiness, comfort, peace, help, the absence of obstacles. A value-oriented tactic is also used, which is aimed at activating positive value guidelines in the mind of the addressee and their association with the advertised product or service. In analyzed advertising texts, the following basic values are most often manipulated: freedom, security, rest, family. Less common is the tactic of masking – the creation in an advertising message of such a position of the addressee, which allows you to play different roles in order to transfer communication with the addressee to the plane of personal communication (position of the mentor, interlocutor, adviser).

Coordination of the Development of Renewable Energy and Small Business as a Mechanism for Ensuring the Sustainable Development of Russia

The article deals with the development of renewable energy in Russia, taking into account the coordination of this sector with small and medium-sized businesses. The aim of the study is to theoretically substantiate the strategy for the transition to renewable energy based on small and medium-sized businesses and to develop practical recommendations using the example of solar energy in Russia. The methodological basis of the article is the general organizational science of tectology A.A. Bogdanov, which was subsequently developed in the general theory of systems by L. von Bertalanffy. On the basis of a system analysis of a transformable energy complex, the authors carried out a theoretical justification for the emergence of synergy as a result of the involvement of small and medium-sized businesses in the development of renewable energy. It is shown that the formation of new links between small and medium-sized businesses and renewable energy has a positive effect, consisting in diversifying the country's fuel and energy balance and reducing the negative anthropogenic impact on nature without increasing electricity prices for end consumers. Using the example of installing solar panels on the vertical enclosing surfaces of buildings and structures with the involvement of small and medium-sized businesses, the reserves currently not fully used for the development of solar energy, mainly in the northern and eastern regions of Russia, without withdrawing territories from economic circulation, have been identified. The information base of the study is the data of the International Energy Agency, IRENA, and the Photovoltaic Geographical Information System. A graphical method was used to determine the feasibility of installing solar panels in different regions, taking into account seasonal fluctuations in the intensity of insolation, as well as the dependence of the coefficient of conversion of sunlight energy into electricity on temperature and snow cover albedo. The results of the study can be recommended for countries with similar natural and environmental conditions to Russia.

Secrecy Outage Analysis of Relay Aided Multiuser Scheduling for Wireless Networks in the Face of Co-Channel Interference

In this paper, we analyze the secrecy outage probability of a relay aided multiuser network which consists of a cluster head (CH), a decode-and-forward (DF) relay, and multiple users in the presence of an eavesdropper and co-channel interference (CCI). Firstly, we propose two relay aided multiuser scheduling (RMS) schemes to improve the secrecy outage performance of the network by considering the availability of channel state information (CSI) of CCI links, including the partial CSI based RMS (PCSI-RMS) scheme and the full CSI based RMS (FCSI-RMS) scheme. For comparison purposes, the relay aided round-robin scheduling (RRRS) scheme is also employed as a baseline. Then, we derive closed-form expressions for the proposed PCSI-RMS and FCSI-RMS schemes as well as the RRRS scheme in terms of their exact and asymptotic secrecy outage probabilities over Rayleigh fading channels in the face of CCI. Finally, numerical results show that the secrecy outage performance of the proposed PCSI-RMS and FCSI-RMS schemes is better than that of the RRRS scheme, where FCSI-RMS achieves the best secrecy outage performance. With an increase of the number of users, the secrecy outage performance of the PCSI-RMS and FCSI-RMS schemes is significantly improved, while that of the RRRS scheme keeps unchanged, which demonstrates the benefits of adopting the proposed PCSI-RMS and FCSI-RMS schemes against eavesdropping in CCI environments. Moreover, there is an optimal power allocation factor between the CH and the relay, which makes the network have the best secrecy outage performance.