External Network Research Articles

Knowledge-based Dual External Attention Network for peptide detectability prediction

Accurate prediction of peptide detectability plays a crucial role in various proteomics data analyses such as peptide identification and protein quantification. To improve the precision of peptide detectability prediction, we propose a novel approach called the Knowledge-based Dual External Attention Network (KDEAN). KDEAN introduces several innovative elements to enhance its representation and prediction capabilities. Firstly, it extracts valuable knowledge-based features from peptide sequences to facilitate the pattern recognition process. Secondly, KDEAN adopted dual networks to separately train peptide sequences from both the forward and backward directions, capturing comprehensive information. Thirdly, an external attention mechanism is utilized to identify and understand the connections between different peptide samples. The structure of KDEAN enables long-term dependency learning from both directions of the peptide sequences. Extensive evaluations on four testing datasets demonstrate that KDEAN outperforms existing methods, achieving a higher average performance in peptide detectability prediction. Additionally, comprehensive ablation studies confirm the effectiveness and advantages of key components in KDEAN, including knowledge-based feature representation, dual network architecture, and external attention.

Zero Trust Security Model for Enterprise Networks

Zero Trust (ZT) is security model and follow the concept of ânever trust, always verifyâ. ZT require to strict identity verification for devise and clients trying to access recourses on private networks regardless of whether they are sitting within or outside the networks. As opposed to perimeter-based architecture, which makes the assumption that all internal network parties are trusted and all external network parties are untrusted. In enterprise network the internal network parties is automatically seen as trusted entities granting them access to network resources. The insider threat actor has been successful in exploiting their access. So that, enterprise networks become more exposed to inside and outside threads. As a result, we need to add the zero-trust principle to the enterprise network to protect it from the inside. In this paper, the ZT model, is assumed inside the militarized zone. There may be a threat to the sensitive data. Any internal company network users cannot manipulation on his computer without permission from the administrator this is done by the group policies that have been implemented in ZT. This model has been shown to be quite effective in protecting the sensitive data against unauthorized access and also the manipulation by the insider user. Following that, an attack originating from inside of the network was launched against the enterprise and zero trust network. In the enterprise network, the network was effectively attacked, and the attack’s validity was also increased to fully penetrate the enterprise. The attack did not succeed in the zero-trust network because the attacker cannot pass the User Account Control (UAC) to gain the NT authority.

Exploring the use of social media and online methods to engage persons with lived experience and healthcare professionals in creating research agendas: Lessons from a pediatric cancer research priority-setting partnership.

Social media is increasingly used to engage persons with lived experience and healthcare professionals in research, however, there remains sparse guidance on how to effectively use social media to engage these groups in research agenda-setting. Here we report our process and experience utilizing a social media campaign to engage Canadians within the pediatric cancer community in a research priority-setting exercise. Following the James Lind Alliance method, we launched a priority-setting partnership (PSP) to develop a child with cancer-, survivor-, family member-, and healthcare professional-based Canadian pediatric cancer research agenda. Social media-based strategies were implemented to recruit participants for two PSP surveys, including preparatory activities, developing a website, launching graphics and advertisements, and engaging internal and external networks. Descriptive statistics of our data and analytics provided by the platforms are used presently to report our process. The framework we implemented involved preparing for social media use, identifying a target audience, developing campaign content, conducting the campaign, refining the campaign as needed, and evaluating its success. Our process resulted in a substantial social media-based reach, good survey completion rates, and a successfully developed pediatric cancer community-specified research agenda. Social media may represent a useful approach to engage persons with lived experience and healthcare professionals in research agenda development. Based on our experience, we present strategies to increase social media campaign engagement that may be useful to those seeking to conduct health research priority-setting exercises.

New Stream of The Indonesian Economy: Economic Empowerment and Islamic Entrepreneurship Culture In Islamic Boarding School

This paper aims to reveal the empowerment process carried out by BLKK Islamic boarding school and diagnose potential aspects that can be developed in realizing the goal of economic empowerment of Islamic boarding schools. This type of research is field research using a qualitative approach with locus on seven BLKK Islamic boarding schools in four regions, namely; district and city of Blitar, city of Kediri, district of Tulungagung, and district of Trenggalek. Through Kurt Lewin's theory of social change which includes three stages; unfreezing, moving, and refreezing, this paper finds that in the unfreezing and moving stages, all BLKK Islamic Boarding Schools are running well as program assistance is still running. However, at the refreezing stage, many BLKKs were difficult to develop. Because this stage needs to a spirit of entrepreneurship and independence that can take advantage of the existing potential, such as; the open mind set of the Islamic boarding school, the figures and influence of the kiai who can expand the external collaboration network, spreading alumni throughout the communities, and the BLKK building and equipment used as a production house and a place to improve the quality of human resources. The implication is the importance of the entrepreneurial attitude of Islamic boarding school BLKK managers in realizing the economic empowerment of Islamic boarding schools

Supervision and early warning of abnormal data in Internet of Things based on unsupervised attention learning

With the continuous development of artificial intelligence and big data, more and more communication protocols have appeared in the network connection. Because the network protocol content specification should not need to obtain the content of the common protocol by any means, it faces different attacks, which increases the complexity of network security detection to an unlimited extent. The absolute security analysis of the content of the relevant data protocol is not too limited. Based on the content of the unknown binary number protocol in the Internet of Things, this paper does the reverse research. To address the inefficiency, learning is focused on the inverse aspect of the content processing logic of the protocol for unsupervised execution attention. This paper proposes a method based on the name of the Dirichlet process mixture model normal field and the unknown protocol of the Internet of Things. It also establishes the behavioral criteria that process the logical inference least squares method to infer the content of the target protocol. Based on the original external characteristics of abnormal data in the Internet of Things, the neural network model of attention mechanism and the model checking of variational self-encoder are chosen. An innovative multi-dimensional spatial neural network model with a centralized control mechanism is taken to extract the spatial relevant information from the original external features, which are regarded as the intermediate external features. The intermediate extrinsic features are input to a variational self-encoder for computation and reconstruction. The experimental results verify that the time required by the proposed model is 45% less than that of the traditional structure. The flow processing improves by 36.7% compared with the optimization of the parameter control function. The specific method only relies on the original external characteristics of the Internet of Things traffic and can achieve better data anomaly detection and classification under the condition of not significantly improving the detection time. The abnormal data detection scheme of the Internet of Things designed in this paper not only fills the detection gap of the current mainstream Internet of Things system which lacks an autonomous supervision mechanism, but also effectively blocks external network intrusion and further improves the management authority verification system. It plays an indispensable role in the long-term stable operation of the Internet of Things platform.

Co-Constructing Mentalizing Contexts in Therapeutic Work with Adolescents-Exploring Resilience in Social Support Networks

ABSTRACT Adolescence, a transformative phase of human development, is marked by a growing need for social support. During this pivotal period, young individuals grapple with the challenges of identity formation, emotional regulation, and forging meaningful relationships. Research has underscored the significance of a robust social network in fostering resilience and promoting mental well-being. In this exploration, we consider the evolving landscape of adolescent support, drawing insights from the concept of Mentalization-Based Therapy (MBT), especially from the specialized treatment model explicitly designed for adolescents, known as Mentalization-Based Treatment for Adolescents (MBT-A). MBT-A is an approach that emphasizes establishing a therapeutic alliance, epistemic trust, and mentalizing within an adolescents’ therapy and social context. This approach includes forming a dynamic external support network to help the young person remain connected with their social environment. Through two case examples, we illuminate how this approach aims to strengthen mentalizing within peer groups and the wider social contexts adolescents live within. This paper will consider the various ways in which therapists might step outside the activity of individual therapeutic sessions to address mentalizing barriers preventing the adolescent from accessing everyday social support. In this process, we encourage creativity and multiple participant involvement, challenging the boundaries of perceived therapeutic practice.

How Do External Networks and Strategic Targeting Impact Open Innovation in the Global Auto Industry

This research examines the interactions between open innovation (OI) strategies and competitive behavior in global automotive assemblers and suppliers. We show that these firms behave differently when engaging external networks to limit downside risks when dealing with competitors (and rivals). Specifically, we find that firms cross external firm boundaries for incremental, but not radical technology projects using nominal external links. Our results are aligned with emerging innovation trends in the auto industry where the locus of innovation has evolved upstream in the digital age, from final assemblers to suppliers. This study provides support for a theory to explain inter-firm competitive dynamics within OI contexts. In particular, it provides an explanation for boundary selection criteria when engaged in OI projects. We conclude with implications for theory and practice and provide guidance for potential future research.

РОЛЬ АМБИДЕКСТРАЛЬНОГО ЛИДЕРСТВА В ИННОВАЦИОННОЙ ЭКОСИСТЕМЕ

The purpose of this article is to demonstrate the importance of dual leadership roles in the innovation ecosystem to create organizational innovation. A highly capable leader directs a team to create a new product or service, creating internal and external organizational networks and co mmunications between different ecosystem participants, including experts, researchers, inventors, government and aca- demia. The methodological approach is based on a systematic literature review to develop proposals de- scribing the role of ambidextral leader ship in the innovation ecosystem. The concepts of «ambidextral lead- ership», «innovation», «ecosystem», «innovative ecosystem», as well as the process of organizing the network are analyzed. It is concluded that leadership styles play a key role in an organ ization's business success, with ambidextral leadership having a direct and meaningful impact on the building and success of an inno- vation ecosystem.

Analysis of internal and external influencing factors of individual entrepreneurial intention: An empirical study based on global Entrepreneurship Survey

Entrepreneurial activities are the power source of promoting a country’s economic development and social progress. Entrepreneurial intention can well predict entrepreneurial activities. Based on the framework of integration analysis, this paper explores the external and internal factors that affect individual entrepreneurial intention. The binary logistic regression method was used to analyze 121,613 valid data samples from 48 countries in the 2018 Adult Population Survey (APS). The results show that entrepreneurial opportunity, entrepreneurial network, entrepreneurial ability, entrepreneurial attitude, and other internal and external factors have significant positive effects on individual entrepreneurial intention. At the same time, the interaction of internal and external factors has a significant positive effect on individual entrepreneurial intention. The interaction of internal and external factors also has significant positive impact on individual entrepreneurial intention. Individual willingness to start a business is influenced by multiple factors such as entrepreneurial network, entrepreneurial opportunity, entrepreneurial ability, and entrepreneurial attitude. It is a comprehensive balance of an individual’s possible risks, benefits, and abilities to start a business, and a comprehensive result of wanting to do something (external opportunities and network relations), ability (knowledge and skills), and daring to do something (risk attitude).

Superhydrophobic pressure-responsive pressure sensors based on an inner–outer synergistic conductive network of GAF/PDMS

We used a simple method to prepare a superhydrophobic pressure-sensitive sensor based on the internal and external synergistic conductive networks of graphene fragments and polydimethylsiloxane sponges.

A Location Analysis and Modeling Approach for Optimizing Public Access to an Automated External Defibrillator Network

A Location Analysis and Modeling Approach for Optimizing Public Access to an Automated External Defibrillator Network

Virtual Private Network—Firewall Integration for Wireless Local Area Network Improvement against Jammers

Wireless networks are susceptible to many security problems since the wireless medium is open. Jammer (jamming attack) is the most important problems in wireless networks. It is denial-of-service attack in which attackers send malicious signals or messages on a channel that is intended for normal traffic by intentionally interfering with the network. One of the solutions is the development of tunneling technology as an attempt to secure communication networks. Virtual Private Network (VPN) tunneling technology when integrated with firewall would provide a suitable security. In this study, number of Jammers would interfere with the normal operation of the network resulting in performance degradation of network. These Jammers decrease throughput and increase delay and data dropped. The aim of this study is to improve the performance of Wireless Local Area Network (WLAN) by integrating Firewall with VPN in number of different Riverbed Modeler simulation scenarios which it is utilized in this study for video and data applications. Firewall is a technology employed to regulate the level of network connectivity. It can block unauthorized access from an external network to an internal network’s resources. In this study, the tunneling technology of VPN was integrated with firewall to improve the performance by increasing the throughput and decreasing delay and data dropped. The firewall would block any access to the server from the workstations and the VPN would filter the packets to allow a specific access to the specific server. The results showed that VPN when integrated with firewall increased the throughput from 1,350,000 to 1,500,000 bits/sec and decreased the delay from 0.0054 sec to 0.0047 sec and data dropped from 7,800 to 5,000 bits/sec so that this study proved that VPN incorporated with firewall provides a good throughput and delay improvement for wireless local area network.

Freedom of choice and network "echo effects" of information consumption

The mechanisms of media personalization and separation in network communication on the principle of like-mindedness stimulate the formation of "echo chambers" and "filter bubbles". The social network phenomenon indicated by these metaphors is the subject of research, and the concepts themselves are considered as close, but not identical. The purpose of the study is to identify factors affecting the effectiveness of filtering algorithms, the user's ability to make informed choices and self–organization in the process of information consumption. The analysis of the causes and consequences of selective strategies of online information consumption is carried out on the basis of the communicative - activity approach, the theory of virtual reality Zh. Baudrillard, concepts of digital media by K. Sunstein, E. Pariser and R. Fletcher. The results of foreign and domestic studies of communication practices on various social platforms are used as an empirical basis. The research approaches presented in the scientific literature allow us to focus on the technological and logical-semantic perspective of the analysis of stable forms of network communication. According to the authors, the interdependence of filtering algorithms and value dominants of information consumption leaves the user with a chance to independently choose a "consumer basket". The duality in obtaining personalized content is emphasized: on the one hand, it is convenience, saving effort, on the other - the one-dimensionality of the world picture in the information bubble. Based on this, freedom of choice is characterized as the right to active choice and the right not to choose, consciously delegating it to neural network filters. In conclusion, the authors identified internal and external network factors for reducing the effectiveness of filtering algorithms: the interpretation of user behavior by artificial intelligence; the functioning of rational confrontational communication; the opportunistic conceptualization of echo effects; the availability of means of conscious counteraction. Incentives for reasonable information consumption, technological and cognitive ways of protecting and rationalizing user behavior are highlighted.

Modeling of malicious code propagation in the industrial control network

With the development of digitalization, industrial control network have more connections and open to external network, which breaks their “isolation” from Internet and makes them more vulnerable to be attacked especially by malicious code. To model and analyze the impact of different containment strategies for attacks by malicious code in the industrial control network, the SUIQMR model is established to simulate malicious code propagation. Since the industrial control network is often coupled with Internet, industrial control coupling network is also considered in the SUIQMR model and the containment strategies of quarantine,benign worms and honeypot are added into the model to evaluate their effect against malicious code propagation.The simulation results show the effectiveness of our model.

On Cooperative Federated Defense to Secure Multi-Access Edge Computing

The research of cyber security for Multi-access Edge Computing (MEC) has not yet received a great interest. Specifically, the attack detection issue is considered as a major concern since the MEC network, which handles attractive information, is prone to several internal and external network attacks. Recently, the Federated Learning (FL) and Generative Adversarial Network (GAN) have been used to detect and prevent attacks from targeting the wireless mobile networks. In this article, we present the state of the art of MEC attack detection and defense frameworks which incorporate FL and GAN algorithms. Moreover, we propose a new cyber defense framework based on a Federated Generative Adversarial Network (FedGAN) algorithm and non-cooperative game to improve over time the precision of attack detection.

Modeling, Integration and Simulation of the Photovoltaic Power Plant Considering LVRT Capability and Transient Voltage Stability

This paper investigates how high photovoltaic energy penetration impacts dynamic performance and voltage regulation of the modified IEEE-9 bus grid. The transmission power system was modeled and simulated using PSCAD-EMTDC software to conduct the study. Load flow analysis is implemented to explore the power system’s capability to incorporate the desired photovoltaic power. Moreover, the study is based on time response simulations to grid disturbances. The supply and control of reactive power from solar power generation plants are becoming critical issues to study because they can facilitate the integration of PV in power grids under different operating conditions. Network-related faults like a PV solar power plant event outage, a three-phase short-circuit at a conventional bus, and a voltage dip at the PV solar power plant have been considered. The results will help identify the protective devices and strategies needed to maintain the stability and reliability of the system operation and transient analysis of the network under external power network fault and recovery operation. Thus, it has practical significance for real utility studies. Moreover, this comprehensive study will be a valuable guide for assessing and improving the grid’s performance under the study of any other grids, which also gives the vast potential and need for solar energy penetration into the grid systems.

ResfEANet: ResNet-fused External Attention Network for Tuberculosis Diagnosis using Chest X-ray Images

Pulmonary tuberculosis (TB), the most prevalent form of TB, remains a major global public health concern, contributing to more than a million deaths each year. The accurate and timely diagnosis of this disease is of paramount importance for effective control and treatment. Chest X-ray (CXR) images have emerged as a valuable tool for screening lung diseases, including TB, owing to their cost-effectiveness and non-invasiveness. Despite advancements in technology, the challenges associated with interpreting CXR images persist, primarily due to the scarcity of trained radiologists. This underscores the pressing need for an automated and cost-effective computer-aided system capable of diagnosing TB, assisting medical practitioners in distinguishing between TB-positive and negative CXR scans. In response to this need, we introduce an innovative approach called ResNet-fused External Attention Network (ResfEANet). This network excels in accurately classifying TB from CXR images, achieving remarkable levels of accuracy and sensitivity. ResfEANet is built upon ResNet and incorporates an External Attention mechanism, albeit with fewer residual network blocks than ResNet-50 resulting in a relatively shallow network with fewer layers. This approach proves highly effective in feature extraction and yields competitive results in the classification of TB. Our method was employed to train a model that demonstrated an impressive accuracy rate of 97.59% and a remarkable sensitivity of 100% in binary classification tasks with optimal computational cost. These outcomes suggest that our proposed approach has the potential to serve as a valuable secondary tool in clinical decision-making, providing crucial assistance to radiologists and healthcare professionals.

A robust hybrid model with low energy consumption for biosensor nano-networks

The biosensor nano-network consists of mobile nano-nodes, nano-routers and micro-gateways in various levels of hierarchy. In the human body, the energy is harvested by the nano-devices by transforming various forms of energy into electrical energy. Simultaneously, the energy is consumed to collect and transmit data to the external network. So, a proper balance between energy harvesting and energy consumption is required. The current multi-path routing enables data flooding, using energy from numerous redundant nodes along the path. Whereas, single-path routing has the drawback of packet loss. In this article, we propose a hybrid model with low energy consumption and minimal packet loss. We grouped the nano-nodes into clusters by which the redundancy is avoided to a great extent. The nano-nodes communicate with a cluster primary node using a Lightweight Secure Directed Diffusion multi-path protocol, and the primary nodes communicate with the nano-router using Energy Conserving Routing single-path protocol at the layer-1 of our model. In the conventional models, the micro-gateway communication with the nano-routers created energy irregularities. So, we come up with a query routing protocol at the layer-2 that chooses a particular nano-router for communication with the micro-gateway. As a result, the energy consumption at the micro-gateway is decreased.

CSR and new product development performance in transition economies: roles of internal capabilities, external networks, and dysfunctional competition

ABSTRACT Despite abundant research on corporate social responsibility (CSR) outcomes, few studies have examined whether CSR contributes to new product development (NPD) performance. Existing studies argue that CSR increases firms’ innovation activities and launches more new products, however, these arguments have yet to fully extend to the understanding of underlying mechanisms in the CSR-NPD relationship and how CSR fosters NPD performance in different scenarios, especially in transition economies. Building on the resource-based view, social capital theory, and structuration theory, this paper hypothesizes that the CSR influence on NPD performance is mediated by internal capabilities and external networks and moderated by dysfunctional competition. Using empirical data of 219 small and medium-sized firms in China, we find that CSR not only directly increases firms’ NPD performance but also has positive effects on internal capabilities and external networks, which in turn improve NPD performance. Moreover, as one of the most representative institutional environments in transition economies, dysfunctional competition strengthens the effects of CSR on internal capabilities and external networks. This research contributes to the CSR and NPD literature in transition economies and offers strategic guidance to innovating firms in transition economies on how to foster and benefit from CSR initiatives, NPD managers should comprehend the coevolution of CSR, innovation, and institutional environments in transition economies.

Who decides which trucks to buy? Implications for electrifying freight fleets

This study characterizes fleets’ decisions to operate medium- and heavy-duty fossil fuel-powered trucks and compares those decisions with fleets’ consideration of electric trucks. Based on interviews with decision-makers in 25 such organizations, we describe the social context of truck acquisition decision-making. We use concepts of organizational structure and external network heterogeneity to create a typology of decision-making. We use the typology to compare decisions regarding fleets’ actual and prospective consideration and use of conventional vs. electric trucks. The results describe who is involved in truck decision-making and provides insights into the organizational structures and external networks of fleets that have and those who have not acquired electric trucks. We identify fleet types that may require additional support to transition to electric trucks. This support may include connecting fleets with new or additional external actors to facilitate medium- and heavy-duty truck electrification.