Centralized Component Research Articles

ML-Enhanced Live Video Streaming in Offline Mobile Ad Hoc Networks: An Applied Approach

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions is challenging due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts in which an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal is implemented and assessed in a laboratory context, in which the model performance and QoS metrics are analyzed. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% accuracy. Also, the obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.

Communication-Aware Control of Large Data Transmissions via Centralized Cognition and 5G Networks for Multi-Robot Map merging

Multiple modern robotic applications benefit from centralized cognition and processing schemes. However, modern equipped robotic platforms can output a large amount of data, which may exceed the capabilities of modern wireless communication systems if all data is transmitted without further consideration. This research presents a multi-agent, centralized, and real-time 3D point cloud map merging scheme for ceaselessly connected robotic agents. Centralized architectures enable mission awareness to all agents at all times, making tasks such as search and rescue more effective. The centralized component is placed on an edge server, ensuring low communication latency, while all agents access the server utilizing a fifth-generation (5G) network. In addition, the proposed solution introduces a communication-aware control function that regulates the transmissions of map instances to prevent the creation of significant data congestion and communication latencies as well as address conditions where the robotic agents traverse in limited to no coverage areas. The presented framework is agnostic of the used localization and mapping procedure, while it utilizes the full power of an edge server. Finally, the efficiency of the novel established framework is being experimentally validated based on multiple scenarios.

Analysis of approaches and their features to research the dynamics of cryptocurrencies

The purpose of the study is to provide a comparative analysis of approaches to analyzing the trends in cryptocurrency dynamics. The paper analyzes the trends in cryptocurrency development, which has shown an increase in the influence of cryptocurrency on the structure of the financial market. It has been determined that from 2013 to 2023, the capitalization of cryptocurrency market increased almost 1 000 times. However, in recent years, the number of "fake" cryptocurrencies has also increased, so the total number of cryptocurrencies has almost not changed in the last two years. The works of researchers on the analysis of the trends in cryptocurrency exchange rates have been studied, and three main approaches to the analysis have been formed. The main components of the first approach have been investigated, the influence of miners, mining costs, blockchains, and the interaction of mining participants on the formation of exchange rates has been determined. It is found that the necessity to analyze the cryptocurrency market in conjunction with other elements of the financial market is the key aspect of the second approach to the study of trends in the exchange rate of cryptocurrencies. In this approach, cryptocurrency acts as an alternative to centralized components of the financial market and as an element of financial freedom. The study of the works of the third approach allows to identify the main methods and models for analyzing the dynamics of exchange rates, among which the main place is occupied by: models of time series analysis taking into account sentiments (Sentiment-Enriched Time Series Forecasting – SETS models), deep learning models for forecasting of processes with long and short-term memory, recurrent neural networks, and gated recurrent unit models

A scalable, efficient, and secured consensus mechanism for Vehicle-to-Vehicle energy trading blockchain

Vehicle-to-Vehicle (V2V) energy trading has emerged as a promising scheme to relieve the load imposed on the grid without intermediaries. The blockchain has always been regarded as the most potential solution for addressing the security and privacy issues of the Internet of Electric Vehicles (IoEV). The consensus mechanism is the core of the blockchain, it determines the security, efficiency, and scalability of the system. However, consensus mechanisms currently employed in V2V energy trading are traditional algorithms, which are unsuitable for the IoEV due to their high computational power and communication overhead. Therefore, we are motivated to propose a Block Alliance Consensus (BAC) mechanism based on Hashgraph. BAC can maintain the high throughput of the Hashgraph, and it solves the problem that the Hashgraph cannot support the dynamic addition and deletion of nodes if it is directly applied to V2V energy trading. We utilize the sharding technique, and each shard generates a consortium blockchain in accordance with the characteristic of the IoEV. The centralized component is retained to ensure macroeconomic control by state and local governments. We design a cryptography-based leader election combined with a reputation incentive mechanism to fairly elect centralized leader committee and motivate honest electric vehicles (EVs). We implement the BAC consensus and V2V energy trading blockchain (ETB) on the Hyperledger Fabric. The performance and practicality of BAC and the V2V ETB are verified through experiments.

Resource-Intensive Fuzzing for MQTT Brokers: State of the Art, Performance Evaluation, and Open Issues

Pub/sub messaging is a promising design pattern that relies on a centralized component called the broker, which routes messages to different devices. Due to its prominent role, the broker must be capable of providing high quality services under heavy workload. In this letter, we evaluate the resource consumption of state-of-the-art fuzzing frameworks, thereby understanding the degree to which brokers are tested before deployment. Our results attest that only one framework shows the most promise for memory-intensive testing, outperforming its counterparts by more than 20%. We conclude the letter by highlighting shortcomings that prevent existing frameworks from consuming considerable system resources.

DistriTrust: Distributed and low-latency access validation in zero-trust architecture

Enterprise networks typically use perimeter-based security to protect their IT resources from security threats originating from outside the enterprise perimeter. In such networks, connection requests from devices residing inside the perimeter are implicitly assumed to be trusted. However, in practice, a considerable fraction of cyberattacks emanate from inside the enterprise network making the perimeter-based trust assumption unrealistic. Zero-trust architecture (ZTA) is an emerging alternative to perimeter-based security, where each connection request for accessing an enterprise resource goes through stringent security checks and validation irrespective of the location of the requesting device. In ZTA, every connection request is authenticated and authorized by a trusted centralized component called the policy decision point (PDP) and subsequently granted (or denied) access to the requested resource. However, the centralized nature of the PDP often makes it vulnerable to various attacks such as compromise of secret keys, impersonation and denial of service. In this article, we propose DistriTrust which distributes trust across multiple PDPs using the notion of threshold signatures. However, involving multiple PDPs also increases latency. In order to keep latency as low as possible, we study different threshold signature schemes and identify a suitable scheme for DistriTrust. We also discuss the security properties achieved by DistriTrust. Finally, we analyze the asymptotic performance of DistriTrust and report the experimental results as well.

A social identity perspective on conformity to cyber aggression among early adolescents on WhatsApp

AbstractCyber aggressive behaviors such as nonconsensual image sharing, nasty comments, and social exclusion frequently take place on WhatsApp. These behaviors often involve group processes, where adolescents conform to peers’ behaviors. WhatsApp is pre‐eminently suited for group‐communication among adolescents, and, thus, may facilitate conformity to such behaviors. However, research on conformity on WhatsApp is scarce. Therefore, the aim of this study was to examine if and how the social identity perspective on group behavior may explain cyber aggression on WhatsApp. Specifically, we examined how social identification relates to conformity to cyber aggression on WhatsApp. In a preregistered survey, 647 early adolescents answered questions about social identification with group members and conformity to behavior of a WhatsApp group. Hierarchical multiple regression and moderated mediation analyses point toward an indirect, positive relation between the centrality component of social identification and conformity to cyber aggression, mediated by perceived social pressure to conform. These findings contribute to the literature by extending the social identity perspective to conformity on WhatsApp. Further exploration of this research line within the field of cyber aggression is warranted, because this can help improve applied interventions to reduce conformity to cyber aggression.

Low-dose naltrexone is effective and well-tolerated for modulating symptoms in patients with neuropathic corneal pain

PurposeNeuropathic corneal pain (NCP) is caused by damage or disease of the somatosensory nervous system that innervates the cornea and presents with symptoms of pain or persistent unpleasant sensations, such as burning, dryness, or light sensitivity. This retrospective study aims to assess the efficacy and tolerability of low-dose naltrexone (LDN) in refractory NCP patients. MethodsFifty-nine NCP patients with a centralized component treated with oral LDN 4.5 mg at bedtime for at least four weeks were identified. Thirty out of 59 patients who had a baseline pain score ≥4 on the visual analogue scale had completed the ocular pain assessment survey (OPAS) and presented persistent pain, despite instillation of topical anesthetic drops, were included. Changes in pain scores, comorbidities, side effects, among others, were analyzed. Change in ocular pain scores (scale 0–10) and quality of life (QoL) scores (scale 0–100%) were the main endpoints. ResultsMean age (years ± SD) was 45.60 ± 19.30 with a white (80.00%) female (73.33%) predominance. Duration of LDN use was 14.87 ± 11.25 months, and the duration of NCP before treatment was 17.53 ± 17.29 months. Eight patients used LDN as a monotherapy, whereas the remaining used it as an adjunct therapy. LDN resulted in a 49.22% decrease in mean pain score from 6.13 ± 1.93 to 3.23 ± 2.60 (p < 0.001). Mean QoL scores by the OPAS were 5.84 ± 2.57 at the first visit and improved to 3.77 ± 2.91 at the last visit (p = 0.023). Common side effects were vivid dreams, headaches, and stomachache. ConclusionLDN was effective and well-tolerated for NCP treatment.

Efficacy and tolerability of nortriptyline in the management of neuropathic corneal pain

PurposeNeuropathic corneal pain (NCP) is a recently acknowledged disease entity. However, there is no consensus in potential treatment strategies, particularly in patients with a centralized component of pain. This study aims to assess the efficacy and tolerability of the tricyclic antidepressant, nortriptyline, among NCP patients. MethodsPatients with clinically diagnosed NCP and a centralized component of pain, treated with oral nortriptyline, who had recorded pain scores as assessed by the ocular pain assessment survey at the first and last visit were included. Patients were excluded if they had any other ocular pathology that might result in pain or had less than 4 weeks of nortriptyline use. Demographics, time between visits, concomitant medications, systemic and ocular co-morbidities, duration of NCP, side effects, ocular pain scores, and quality of life (QoL) assessment were recorded. ResultsThirty patients with a mean age of 53.1 ± 18.5 were included. Male to female ratio was 8:22. Mean ocular pain in the past 24 h improved from 5.7 ± 2.1 to 3.6 ± 2.1 after 10.5 ± 9.1 months (p < 0.0001). Twelve patients (40.0%) had equal to or more than 50% improvement, 6 patients (20.0%) had 30–49% improvement, 6 patients (20.0%) had 1–29% improvement, 4 patients (13.3%) did not improve, while 2 patients (6.7%) reported increase in pain levels. Mean QoL improved from 6.0 ± 2.5 to 4.3 ± 2.4 (p = 0.019). Eight patients (26.6%) discontinued treatment due to persistent side effects, despite improvement by 22.4%. ConclusionNortriptyline was effective in relieving NCP symptoms in patients with centralized component and insufficient response to other systemic and topical therapies who tolerated the drug for at least 4 weeks. Nortriptyline may be used in the management of patients with NCP.

Design of E-office system in vocational school Diponegoro University using code igniter framework

E-Office is an administrative and centralized component of the organization where data, information and communication are stored and disseminated through several forms of telecommunications. The main advantage of the E-Office system is that it can reduce paper usage. The other advantages are centralized data store, quickly data access, accurately and real time using the internet network and can make reports quickly based on existing data. With all the advantages of E-Office system, Vocational School of Diponegoro University is committed to using its services, especially in the process of managing correspondence documents. It is necessary to design and create an application based on E-Office that is used at Vocational School of Diponegoro University. This research is intended to build an application or information system based on E-Office system to handle the management of correspondence documents at the Vocational School of Diponegoro University by utilizing web-based applications. Information system design uses MVC concept on code igniter framework. With E-Office system, management of correspondence documents can be done more quickly and can be done anywhere. The impact is that service time for stakeholders is becoming faster.

Centralization and decentralization: Coastal management pattern changes since the late 19th century, Jiangsu Province, China

With rapid industrialization over the Asian-Pacific coastal region, sustainable management has received increased levels of attention. The way to construct the sustainable management mode suitable for local characteristics becomes an important issue; it requires an in-depth understanding of local management practices changes and historical culture. In this respect, there is a lack of comprehensive discussions on centralized/decentralized management pattern change for this region. Based on historical document analysis for the Jiangsu coast, we reconstruct the evolution of coastal management modes. Here we show that coastal management in Jiangsu has witnessed repeated transitions between centralized and decentralized mode, encompassing four periods: traditional management before the late 19th century, the decentralized practice in the early 20th century, the centralized management associated with the planned economic system from the 1950s–1980s, and the decentralized management in response to the adoption of a market economic system after the 1980s. The driving forces for the changes identified include geomorphological changes, population growth and social-economic regime shifts. We propose that, to optimize coastal management, a hybrid model should be established to take into account both centralized and decentralized components. Although coastal management is decentralization-oriented in most western countries, in the Asia-Pacific coastal regions, local conditions and historical features should be taken into account to adjust the balance between centralized and decentralized variables in the management. With the increasing attention to ecosystem health in China, together with future climate changes and population dynamics, the centralized component should be re-considered within the hybrid model.

Materialism and Well-Being Revisited: The Impact of Personality

Although the negative link between materialism and well-being has been confirmed by results from many empirical studies, mechanisms underlying this association still remain partially unexplained. The issue is addressed in this article in two ways. Firstly, the nature of the components of materialism is examined, and secondly—the article demonstrates that personality (particularly neuroticism and narcissism) is one of the important factors linking materialism and well-being. The article presents the results of three empirical studies, in which three main assumptions were verified—that the components of materialism, i.e. acquisition centrality, acquisition as a pursuit of happiness and possession-defined success, have dissimilar impacts on well-being, that materialists with high and low levels of neuroticism and narcissism differ with regard to well-being, and that neuroticism and narcissism mediate the relationship between materialism and well-being. The studies were based on self-reports and utilized well-known, established questionnaire measures of materialism, personality and well-being. The results showed that each component of materialism was associated with well-being in a slightly different way. Of the three possession-defined happiness was the strongest predictor of all aspects of well-being examined and the centrality component was not associated with any of them. Materialists with a high level of neuroticism and low level of grandiose narcissism experienced diminished well-being in comparison to materialism with a low level of neuroticism and high level of grandiose narcissism. Neuroticism and grandiose narcissism were both significant mediators, acting contrary to each other—neuroticism lowered well-being, whereas grandiose narcissism elevated it.

Nuoxus: A proactive caching model to manage multimedia content distribution on fog radio access networks

One of the most recently proposed 5G architectures, Fog Radio Access Network or F-RAN, has the same cloud computing-based approach of C-RANs while giving additional storage and processing power to the edge nodes so that they can address network activities. The main problem of F-RANs is the intense data traffic in the fronthaul, which is the centralized physical channel used to connect the antennas (F-APs) to the BBU pool. To minimize this bottleneck, we propose the Nuoxus model, whose objective is to cache multimedia content in the edge of the network. By taking advantage of the hierarchical structure of F-RANs, Nuoxus content replacement policy analyses the similarity of requests amongst the children nodes to define the relevance of storing a requested content in cache. It also uses this process to proactively suggest to nodes located lower in the network hierarchy the caching of relevant content. The state-of-the-art analysis reveals Nuoxus as the first model to explore the nodes' request history to perform proactive caching without relying on external and centralized components. Furthermore, the developed proof-of-concept shows significant gains when compared to other caching strategies.

Antecedents of the Intention and Behavior Toward Purchase of Counterfeit Luxury Goods in an Emerging Economy: a Study of Young Vietnamese Consumers

This study examines some antecedents of the intention and behavior toward buying counterfeit luxury goods among young consumers in Vietnam, an Asian emerging economy. The data was obtained from university undergraduate students in Hanoi, the capital of Vietnam. The results of structural equation modeling show support for most of our hypotheses. The findings indicate that materialism (the centrality component) has positive impact on attitude toward purchase of counterfeit luxury goods. Attitude and subjective norm toward counterfeit luxury goods are found to be positively related to purchase intention, while perceived behavioral control is not found to have a direct impact on purchase intention. In addition, perceived behavioral control and purchase intention are found to be significant predictors of purchase behavior. The research findings are discussed and implications for managers and policy makers are provided.&#x0D;

An efficient data exchange mechanism for chained network functions

Thanks to the increasing success of virtualization technologies and processing capabilities of computing devices, the deployment of virtual network functions is evolving towards a unified approach aiming at concentrating a huge amount of such functions within a limited number of commodity servers. To keep pace with this trend, a key issue to address is the definition of a secure and efficient way to move data between the different virtualized environments hosting the functions and a centralized component that builds the function chains within a single server. This paper proposes an efficient algorithm that realizes this vision and that, by exploiting the peculiarities of this application domain, is more efficient than classical solutions. The algorithm that manages the data exchanges is validated by performing a formal verification of its main safety and security properties, and an extensive functional and performance evaluation is presented.

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components.

A Decentralized MAC Protocol for Unfairness Problems in Coexistent Heterogeneous Cognitive Radio Networks Scenarios With Collision-Based Primary Users

Cognitive radio (CR) is introduced to improve spectrum efficiency by unlicensed usage when a licensed band is idle. These devices monitor licensed users to find spectral opportunities for transmission. A cognitive radio network (CRN) is defined as a structure, which is constructed by both licensed users and unlicensed CR users. In an effort to improve spectrum efficiency, CR users' spectrum issues have been widely studied over the last few years. However, the existing solutions are not capable of dealing with the following scenario: multiple CRNs operating simultaneously without a centralized coordinator. This issue is often referred to as a coexistence problem of heterogeneous CRNs. This problem is caused in a distributed framework of CRNs without a centralized component to negotiate spectrum usages with one another. The system characteristics of these heterogeneous networks are different; thus, the fairness issue between CR users must be considered. In this paper, a decentralized solution that does not limit the hardware capacity of a CR device is proposed as an added fairness feature. Several Markov chain models are proposed to study these unfairness conditions, and a medium access control layer approach is introduced. Numerical and simulation results are presented to verify the proposed solution.

Mitigation of Collaborative Blackhole Attack using TRACEROUTE mechanism with Enhancement in AODV Routing Protocol

MANET is multi-hop network in which collection of mobile nodes is self configurable and co-operates together for communicating data without the need of any centralized component for management. Due to this dynamic nature of topology and infrastructure less frame in MANET, these nodes have to rely on each other for data transmission in multi-hop fashion and thus are prone to packet drop attacks like Blackhole attack, CoOperative Blackhole attack, etc and various types of data security attacks. In this paper, Solutions are proposed to detect Collaborative co-operative Blackhole attack in MANET. We introduced the mechanism of TRACEROUTE that helps in detecting the source of collaborative Blackhole attack and thus break the collaboration by eliminating and marking source of Collaboration between those malicious nodes. AODV routing protocol is enhanced by introducing new field that helps in finding the optimal, secure and reliable routes. These Solutions are compared with W-AODV for Packet Delivery Ratio, Control load, accuracy in Blackhole detection and accuracy in Blackhole detection.

Characteristics and Potential Biomarkers for Chronic Pain in Patients with Sickle Cell Disease

Vaso-occlusive episodes (VOE) or pain crises are a hallmark of sickle cell disease (SCD), with increasing recognition that a significant portion of SCD patients develop chronic pain. In the landmark PiSCES study (Smith et al), patients reported pain on 55% days, with ~30% reporting pain on >90% days. Thus, the episodic, nociceptive pain (VOE) in younger patients, evolves into a chronic pain syndrome, with neuropathic and centralized components in some adults. Kutlar et al (Blood, 2014), reported on the association of different pain related phenotypes (pain diaries, frequency of hospitalizations/ED visits, pressure pain threshold) with polymorphisms in candidate genes in 167 SCD patients, providing evidence that multiple signaling pathways and mechanisms are likely involved.In this study, 12 SCD subjects with "chronic pain", defined by reported pain >50% of days in pain diaries collected over 6 months, were enrolled (SCD-CP). 17 SCD patients who did not have chronic pain (SCD-NCP), and 9 non-SCD African-Americans (C) were enrolled as controls. Informed consent was obtained. Age, gender, Hb F levels, HU usage, and pressure pain algometer readings were recorded from SCD subjects. 8 ml of blood (EDTA) was collected from subjects at "steady state" and from normal controls. Plasma was separated and kept at -80 C until the assay. Plasma tryptase and Substance P levels were assayed by ELISA using kits from Biomatik, Inc. (catalog # EKU07922) and Enzo Life Sciences (Catalog #ADI-900-018), respectively. SCD-CP patients were significantly older than SCD-NCP: mean age 41 vs 32.2 (p=0.033). The pressure pain algometer readings did not differ significantly between SCD-CP and SCD-NCP at three sites (trapezius, ulna, masseter, p= 0.67-0.74). There were 12/17 patients on HU (70.6%) among SCD-NCP, and 6/12 (50%) among SCD-CP (p=0.435). Similarly, Hb F levels were not significantly different (14.7% in SCD-CP, vs 11.7% in SCD-NCP, p=0.446). Opioid use (average morphine equivalent as mg/day) was significantly higher in the chronic pain group (11.45 mg/day, vs 2.92 mg/day, p=0.015). Plasma tryptase and substance-P levels are shown in the table:Table 1Tryptase (pg/ml)Substance-P (pg/ml)SCD-CP1388.6 ±519.87221.1±7742.7SCD-NCP1023.64±221.045983.1±3473.0Control768.9±416.163939.7±1350.1The difference in substance-P levels did not reach significance across groups by ANOVA (p=0.337) or in pairwise comparison between groups. However, tryptase levels were significantly different across groups by ANOVA (p=0.00615). Pairwise comparisons between two groups showed that tryptase levels were significantly different between SCD-CP and controls (p=0.0053).These results highlight characteristics of SCD patients with chronic pain: they are older, have a higher use of opioids, and have significantly higher tryptase levels. These observations support previous findings that age is a significant factor in transition to chronic pain in SCD. Higher dose of opioid use in SCD-CP could result from dose escalation to control pain; conversely, it could be argued that higher opioid use itself could be a factor in development of chronic pain through opioid-induced hyperalgesia. To our knowledge, this is the first study of plasma tryptase levels in SCD, in relation to different pain phenotypes. Tryptase is released into plasma with degranulation of mast cells and leads to inflammation, anaphylaxis, urticaria, and neuropathic pain. It binds PAR2 (protease activated receptor 2), releasing inflammatory mediators and substance P, inducing neurogenic inflammation. Elevated tryptase levels are found in systemic mastocytosis, and the newly recognized Mast Cell Activation Syndrome (MCAS). Vincent et al (Blood, 2013) showed that mast cell activation played an important role in neurogenic inflammation and chronic pain in a mouse model of SCD. They also demonstrated that inhibition of mast cell activation, via c-kit knockout or with imatinib or cromolyn sodium improved neurogenic inflammation and chronic pain. Two recent case reports (Murphy et al, Stankovic et al) document significant improvement in pain in SCD patients who developed CML, during treatment with imatinib. These observations, and the findings of our pilot study, not only suggest a novel mechanism and biomarker for chronic pain in SCD, but also a potential therapeutic target by inhibition of mast cell activation via c-kit pathway, or stabilization with cromolyn. DisclosuresNo relevant conflicts of interest to declare.

From data to the decision: A software architecture to integrate predictive modelling in clinical settings.

The application of statistics and mathematics over large amounts of data is providing healthcare systems with new tools for screening and managing multiple diseases. Nonetheless, these tools have many technical and clinical limitations as they are based on datasets with concrete characteristics. This proposition paper describes a novel architecture focused on providing a validation framework for discrimination and prediction models in the screening of Type 2 diabetes. For that, the architecture has been designed to gather different data sources under a common data structure and, furthermore, to be controlled by a centralized component (Orchestrator) in charge of directing the interaction flows among data sources, models and graphical user interfaces. This innovative approach aims to overcome the data-dependency of the models by providing a validation framework for the models as they are used within clinical settings.