Service Protocol Research Articles

Planning Service Protocols for Extra-Long Trains with Transfers

This paper presents a modeling framework for optimizing operational protocols of extra-long trains (XLTs) in metro systems (i.e., trains longer than station platforms). With the rising travel demand in megacities, metro systems face challenges such as overcrowded stations, delays, and passenger anxieties. XLTs have been proposed as a promising solution to increase metro line capacity without additional infrastructure construction. The study explores the trade-offs between the additional capacity gained through complex protocols, the potential benefits of protocols with inline transfers, and the importance of effective passenger information systems from both passengers’ and operators’ perspectives. Mathematical programs are proposed to optimize protocols for a given demand distribution and to estimate the maximum line capacity of an XLT system. The benefits of implementing XLTs are evaluated in hypothetical and real-world cases with varying demand distributions and network sizes. The results demonstrate significant capacity increases ranging from 24% to 126% as compared with regular train operations, depending on system parameters and demand distribution. These findings demonstrate promise for using such systems to improve metro line capacity in the real world. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT 25 Conference. Funding: The work was supported in part by the University of Illinois, Urbana Champaign [Grant Grainger STII Seed Fund] and the Zhejiang University-University of Illinois Urbana-Champaign Institute [Grant DREMES-202001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0527 .

OpenVPN is Open to VPN Fingerprinting

VPN adoption has seen steady growth over the past decade due to increased public awareness of privacy and surveillance threats. In response, certain governments are attempting to restrict VPN access by identifying connections using “dual use” DPI technology. To investigate the potential for VPN blocking, we develop mechanisms for accurately fingerprinting connections using OpenVPN, the most popular protocol for commercial VPN services. We identify three fingerprints based on protocol features such as byte pattern, packet size, and server response. Playing the role of an attacker who controls the network, we design a two-phase framework that performs passive fingerprinting and active probing in sequence. We evaluate our framework in partnership with a million-user ISP and find that we identify over 85% of OpenVPN flows with only negligible false positives, suggesting that OpenVPN-based services can be effectively blocked with little collateral damage. Although some commercial VPNs implement countermeasures to avoid detection, our framework successfully identified connections to 34 out of 41 “obfuscated” VPN configurations. We discuss the implications of the VPN fingerprintability for different threat models and propose short-term defenses. In the longer term, we urge commercial VPN providers to be more transparent about their obfuscation approaches and to adopt more principled detection countermeasures, such as those developed in censorship circumvention research.

Analysis of Damage to Network Time Protocol (NTP) Server on Cengkareng Radar Equipment in Perum LPPNPI Branch JATSC

The On The Job Training (OJT) program which will be implemented in 2022-2023 also includes collaboration with the LPPNPI Jakarta Air Traffic Service Center (JATSC) Branch Office. On The Job Training (OJT) involves various divisions that handle various equipment and facilities that support aviation safety, including equipment such as the Network Time Protocol (NTP) Server used to synchronize the time of equipment connected to the server network at the Jakarta Air Traffic Services Center (JATSC), thereby ensuring accurate operating times for all connected equipment. All of these efforts aim to improve safety and efficiency in aviation at the national and international levels. However, in this case, in operation, not all equipment always runs well, as does Network Time Protocol (NTP) server 1 at the LPPNPI Jakarta Air Traffic Services Center (JATSC) Branch. The purpose of this research is that the author wants to solve the problems that occur in On The Job Training (OJT) activities at Perum LPPNPI Jakarta Air Traffic Services Center (JATSC) Branch.

Intelligent model for the detection and classification of encrypted network traffic in cloud infrastructure

This article explores detecting and categorizing network traffic data using machine-learning (ML) methods, specifically focusing on the Domain Name Server (DNS) protocol. DNS has long been susceptible to various security flaws, frequently exploited over time, making DNS abuse a major concern in cybersecurity. Despite advanced attack, tactics employed by attackers to steal data in real-time, ensuring security and privacy for DNS queries and answers remains challenging. The evolving landscape of internet services has allowed attackers to launch cyber-attacks on computer networks. However, implementing Secure Socket Layer (SSL)-encrypted Hyper Text Transfer Protocol (HTTP) transmission, known as HTTPS, has significantly reduced DNS-based assaults. To further enhance security and mitigate threats like man-in-the-middle attacks, the security community has developed the concept of DNS over HTTPS (DoH). DoH aims to combat the eavesdropping and tampering of DNS data during communication. This study employs a ML-based classification approach on a dataset for traffic analysis. The AdaBoost model effectively classified Malicious and Non-DoH traffic, with accuracies of 75% and 73% for DoH traffic. The support vector classification model with a Radial Basis Function (SVC-RBF) achieved a 76% accuracy in classifying between malicious and non-DoH traffic. The quadratic discriminant analysis (QDA) model achieved 99% accuracy in classifying malicious traffic and 98% in classifying non-DoH traffic.

AB179. SOH24AB_275. Clinical audit on postanaesthetic patient handover to National Health Service protocol in University Hospital Limerick recovery room by anaesthetic non-consultant hospital doctors

AB179. SOH24AB_275. Clinical audit on postanaesthetic patient handover to National Health Service protocol in University Hospital Limerick recovery room by anaesthetic non-consultant hospital doctors

Enhanced Approaches for Safeguarding Communication Channels from Illicit Messages

This research project presents a comprehensive strategy aimed at mitigating the pervasive threat of human trafficking through the innovative application of machine learning methodologies. The primary objective revolves around the development and deployment of sophisticated algorithms to identify and intercept human trafficking- related communications. Leveraging the power of Support Vector Machine (SVM) classification, the system meticulously scrutinizes textual data streams, flagging messages indicative of trafficking activities for further investigation. Moreover, our approach extends beyond mere message analysis by incorporating cutting-edge Utilize Convolutional Neural Network (CNN) models for performing facial recognition, age estimation, and gender identification. By harnessing the rich visual information embedded in images and videos, the system enhances its capability to identify potential victims and perpetrators with unprecedented accuracy and efficiency. A pivotal component of our solution is the seamless integration of an alert mechanism facilitated by a Simple Mail Transfer Protocol (SMTP) server. This critical feature ensures that pertinent authorities are promptly notified upon the detection of suspicious activities, enabling swift and decisive intervention. Through this amalgamation of advanced technological frameworks, our research endeavors to empower law enforcement agencies and humanitarian organizations in their tireless efforts to combat the heinous crime of human trafficking. In essence, this research represents a significant stride towards the realization of a technologically fortified defense against the exploitation of vulnerable individuals. By amalgamating state-of-the- art machine learning techniques with real-time alert systems, we aspire to create a formidable deterrent against the perpetrators of this egregious crime, thereby Ensuring the protection of human dignity and advocating for social justice.

Enhanced Algorithm for Modular Isomorphism Problem Resolution in Small Group Orders

Radius centralizes logins and passwords. This is a server protocol. It should be noted that the server, Radius, manages authentication for clients, routers and switches. Radius is simply a remote authentication protocol used to centralize authentication data and manage user connections to remote services. This protocol relies primarily on a server (DARIUS server), linked to an identification base (database, LDAP directory, etc.). A Radius client, called NAS (Network Access Server), acting as intermediary between the end-user and the server. All transactions between the Radius client and the server are encrypted. It works on the basis of a scenario similar to : a user sends a request to the NAS to authorize a remote connection. The NAS in turn forwards the request to the Radius server. The latter consults the requested identification database to find out the type of identification scenario requested for the user. Either the current scenario is suitable, or another identification method is requested from the user. This protocol thus returns one of the four responses we'll discuss in the rest of this article : ACCEPT : identification successful, REJECT : identification failed, CHALLENGE : the Radius server requests additional information from the user and proposes a challenge. Following the above authentication phase, an authentication phase begins, in which the server returns the user's authorizations. In this article, as a network manager, we're concerned with setting up means of access control, and to do this, we have to square a kind of circle : simplicity for the user, reliability of the mechanisms, high level of security, all while using available standards as much as possible.

Enhancing generalization in Federated Learning with heterogeneous data: A comparative literature review

Federated Learning (FL) is a collaborative training paradigm whereby a global Machine Learning (ML) model is trained using typically private and distributed data sources without disclosing the raw data. The approach paves the way for better privacy guarantees, improved overall system scalability, and sustainability. In this context, Federated Averaging (FedAvg) is a representative FL algorithm adopting a client–server protocol that operates in synchronous rounds, where selected learners contribute to the global model via local model updates, trained using their private data, while a server entity aggregates the local contributions, producing the new-generation global model as a weighted average of the local ones. However, when clients possess (highly) dissimilar data, the FedAvg technique becomes ineffective due to divergence in client models. Consequently, FedAvg-trained models struggle to generalize when presented with unseen data from the global distribution. In this research paper, we conduct a systematic review of state-of-the-art approaches proposed to counteract global model performance degradation in the presence of heterogeneous data.To this end, we compile an original taxonomy, highlighting the main algorithmic approaches and mechanisms behind each identified category. Advancing the current body of knowledge, we empirically evaluate the generalization performance on visual tasks of various methods under moderate and significant levels of data heterogeneity, as common practice within the surveyed literature. In addition, the paper benchmarks the performance of hybrid techniques, resulting as a combination of client- and server-side algorithmic tweaks, by shedding light on some associated performance tradeoffs. While recognizing other relevant issues in FL, such as device heterogeneity and energy consumption, which have a non-negligible impact on the learning process, these well-investigated topics are not the main focus of this article.

Roadmap to safety: a single center study of evidence-informed approach to placenta accreta spectrum.

To assess the impact of an evidence-informed protocol for management of placenta accreta spectrum (PAS). This was a retrospective cohort study of patients who underwent cesarean hysterectomy (c-hyst) for suspected PAS from 2012 to 2022 at a single tertiary care center. Perioperative outcomes were compared pre- and post-implementation of a standardized Multidisciplinary Approach to the Placenta Service (MAPS) protocol, which incorporates evidence-informed perioperative interventions including preoperative imaging and group case review. Intraoperatively, the MAPS protocol includes placement of ureteral stents, possible placental mapping with ultrasound, and uterine artery embolization by interventional radiology. Patients suspected to have PAS on prenatal imaging who underwent c-hyst were included in the analysis. Primary outcomes were intraoperative complications and postoperative complications. Secondary outcomes were blood loss, need for ICU, and length of stay. Proportions were compared using Fisher's exact test, and continuous variables were compared used t-tests and Mood's Median test. There were no differences in baseline demographics between the pre- (n = 38) and post-MAPS (n = 34) groups. The pre-MAPS group had more placenta previa (95% pre- vs. 74% post-MAPS, p = 0.013) and prior cesarean sections (2 prior pre- vs. 1 prior post-MAPS, p = 0.012). The post-MAPS group had more severe pathology (PAS Grade 3 8% pre- vs. 47% post-MAPS, p = 0.001). There were fewer intraoperative complications (39% pre- vs.3% post-MAPS, p < 0.001), postoperative complications (32% pre- vs.12% post-MAPS, p = 0.043), hemorrhages >1l (95% pre- vs.65% post-MAPS, p = 0.001), ICU admissions (59% pre- vs.35% post-MAPS, p = 0.04) and shorter hospital stays (10 days pre- vs.7 days post-MAPS, p = 0.02) in the post-MAPS compared to pre-MAPS patients. Neonatal length of stay was 8 days longer in the post-MAPS group (9 days pre- vs. 17 days post-MAPS, p = 0.03). Subgroup analyses demonstrated that ureteral stent placement and uterine artery embolization (UAE) may be important steps to reduce complications and ICU admissions. When comparing just those who underwent UAE, patients in the post-MAPS group experienced fewer hemorrhages greater five liters (EBL >5l 43% pre- vs.4% post-MAPS, p = 0.007). An evidence-informed approach to management of PAS was associated with decreased complication rate, EBL >1l, ICU admission and length of hospitalization, particularly for patients with severe pathology.

Emergency Medical Services Protocols for Assessment and Treatment of Patients with Ventricular Assist Devices.

Patients with ventricular assist devices (VADs) represent a growing population presenting to Emergency Medical Services (EMS), but little is known about their prehospital care. This study aimed to characterize current EMS protocols in the United States for patients with VADs. States with state-wide EMS protocols were included. Protocols were obtained from the state EMS website. If not available, the office of the state medical director was contacted. For each state, protocols were analyzed for patient and VAD assessment and treatment variables. Of 32 states with state-wide EMS protocols, 21 had VAD-specific protocols. With 17 (81%) states noting a pulse may not be palpable, protocols recommended assessing alternate measures of perfusion and mean arterial pressure (MAP; 15 [71%]). Assessment of VAD was advised through listening for pump hum (20 [95%]) and alarms (20 [95%]) and checking the power supply (15 [71%]). For treatment, EMS prehospital consultation was required to begin chest compression in three (14%) states, and mechanical (device) chest compressions were not permitted in two (10%) states. Contact information for VAD coordinator was listed in a minority of five (24%) states. Transport of VAD equipment/backup bag was advised in 18 (86%) states. This national analysis of EMS protocols found VAD-specific EMS protocols are not universally adopted in the United States and are variable when implemented, highlighting a need for VAD teams to partner with EMS agencies to inform standardized protocols that optimize these patients' care.

US wildlife trade data lack quality control necessary for accurate scientific interpretation and policy application

AbstractInternational wildlife trade data are frequently used by government agencies, conservation organizations, and scientific researchers to study and protect species from overexploitation and prevent the spread of invasive species and introduction of zoonotic pathogens. Inaccurate data can lead to mistaken conclusions by researchers, the development of unsuccessful remedial conservation actions, and provide government officials with incorrect views of detrimental trade. The U.S. Fish and Wildlife Service (USFWS) maintains the world's most comprehensive national dataset of legal and illegal international wildlife trade recorded by individual shipments and species in its Law Enforcement Management Information System (LEMIS). Although the importance of LEMIS data is not to be understated, the errors and inconsistencies contained therein have not previously been adequately recognized or studied. Based on firsthand experiences with the creation and application of LEMIS data, this manuscript describes a variety of errors, biases, omissions, and an overall lack of data quality assurance. An independent audit of the LEMIS wildlife trade database and the service's policies, procedures, and protocols for managing this system is needed. Additional recommendations are also offered to develop better management standards and bring greater resources for managing LEMIS, asking the nongovernmental organization and intergovernmental organization user communities to play a role.

Hybrid Privacy Preserving Federated Learning Against Irregular Users in Next-Generation Internet of Things

While federated learning (FL) is a well-known privacy-preserving (PP) solution, recent studies demonstrate that it still has privacy problems and vulnerabilities, particularly in the context of the Next Generation Internet-of-Things (NG-IoT). Attackers on the server can potentially retrieve sensitive information such as data tabs and memberships. Additionally, current FL studies often overlook critical FL issues such as user dropout and low-quality data, which are prevalent in NG-IoT environments. In this article, we propose a privacy-preserving federated model in hybrid terms based on synchronous + asynchronous manner. This federated model removes the fundamental issues of FL-enabled NG-IoT environments while applying Two-Trapdoor Homomorphic Encryption (TTHE) to ensure the privacy and confidentiality of all components in the proposed model. Furthermore, our server protocol removes the effect of irregular users. In this regard, to control the impact of user dropout, we developed the hybrid LEGATO algorithm, which is asynchronous. To tackle users with low-quality data, we utilize the data-sharing method. Security analysis of the proposed model guarantees correctness, auditing, and PP in a federated setup. Also, in the performance evaluation, we achieved a high level of functionality and accuracy compared to peer works, while system overheads are shown to be lower.

Diet quality and nutritional status in children with human immunodeficiency virus.

Background: Poor diet quality in children and adolescents may contribute to decreased immunity and lead to an increased risk of opportunistic diseases. Aim: To investigate diet quality and its relationship to nutritional status in human immunodeficiency virus (HIV)-infected pediatric patients (HIV-PIHIV). Methods: We conducted a cross-sectional study with 87 patients aged between 6 and 19 years carried out in two University Hospitals. Diet quality was analyzed by an adapted Healthy Eating Index (HEI) and nutritional status. The association between HEI with body mass index-for-age (BMI-for-age) and height-for-age was performed using a linear regression model. Clinical, maternal, anthropometric, and dietary data were collected through a semi-structured questionnaire, based on nutrition service protocols. Results: Diet quality was intermediate (median IAS = 54.8 interquartile range: 47.5 to 65.9 points), due to low consumption of fruits, vegetables, and dairy products and high empty calories and sodium by the PPIHIV. The multivariate regression model indicated that HEI was not significant for explaining BMI-for-age [β = -0.01; 95% CI = (-0.03; 0.01); p 0.40] nor height-for-age [β = 0.01; 95% CI = (-0.02; 0.03); p 0.51]. However, it was observed that adolescents showed 1 Z-score [95% CI = (-1.6; -0.44); p 0.001] a reduction in BMI-for-age compared with children, and those black patients showed an increase in BMI-for-age Z-score of 0.57 [95% CI = (0.7; 1.1); p 0.03] compared with non-blacks. Conclusion: The diet quality of the HIV-infected children and adolescents was below desired. No association was found between diet quality and inadequate nutritional status of HIV-PIHIV.

OPTIMASI INFRASTRUKTUR JARINGAN VLAN TRUNKING PROTOCOL MENGGUNAKAN SIMULASI PACKET TRACER PADA PT. RUKUN SEJAHTERA TEKNIK

Modern companies with many floors and rooms need computer network technology to support operational activities. The computer network at PT Rukun Sejahtera Teknik often causes data transmission failures and unstable computer network systems that cause network performance to fall and become unresponsive. the purpose of this research is to design a Virtual Local Area Network using the VLAN Trunking Protocol (VTP) method and Packet Tracer Simulation to improve network performance and limit the access rights of each user. The type of this research is qualitative with field study methods by conducting observations for two weeks. Observations include the existing Local Area Network (LAN) network and the problem of slow data transmission on the existing network. The results of testing the network design with the configuration of the VLAN Trunking Protocol (VTP) server and client mode, show that the switch configured in VTP client mode cannot add and change the VLAN that has been set. The ping test results show that computers in each room cannot access networks outside of different VLAN networks. It proves that the network design is as planned and running well.

Development And Validation of A Scale For Measuring Petro Retail Service Quality: A Bilateral Approach

Purpose: Global retail fuel markets are being disrupted by a number of broad themes that are being highlighted by the emergence of alternative energy, new mobility models, and elevated customer expectations that are centered around convenience and personalization. Consumers express a need for individualized products and services that take into account each individual. Digital is becoming the norm in the new situation. The changing purchasing habits of customers are a result of technological advancements. As a result, factors affecting the consumer experience have also changed. The purpose of the study is to ascertain Petro Retail's service quality scale from an Indian standpoint. &#x0D; Design /Methodology/ Approach: The study was conducted from October to December 2022 at fuel stations in Mumbai and Ranchi with face-to-face interviews with OMC officials at HQ and field levels. The primary data was collected through a Quantitative field studyanalysedlyzed using suitable statistical tools. Exploratory Sequential Mixed Method design ( Qual-Quan ) was followed for the study.&#x0D; Findings and Originality: Technology advancements significantly impact consumers and industries and transform people's lifestyles and behaviour. Predictive analytics, artificial intelligence, and the Internet of Things are important components in developing customer-facing projects that result in the creation of service protocols for improved purchasing experiences.&#x0D; Technology adoption in petroleum retail is dispersed, with IoT, automation, and AI/ML-based technological solutions being tested in isolated ways without a centralized understanding of the whole value chain. Utilizing assets more efficiently is the main goal of this type of technology adoption. Nevertheless, few applications have been explored to improve consumer purchasing behavior, such as identification and satisfaction. In the digital age, IoT is altering customer expectations and controlling the experience in India's petroleum retail industry from the viewpoints of both service providers and customers (a dyadic approach). Accordingly, the service quality has also evolved over a period of time. There is very limited work carried out on the Petro Retail service quality. The scale developed with the bilateral approach shall help academians and industry managers to understand the service quality in petro retail, and the “BISQUE” constract can be used for measuring the same. The study is one of its kind on the aspect of petro retail.

Harnessing the Power of Supercomputers: Solving Complex Mathematical Problems and Queueing Theory

Supercomputers represent the pinnacle of computational power, offering unparalleled capabilities to tackle complex mathematical problems across various domains. This paper provides a comprehensive overview of the ways supercomputers are utilized in solving intricate mathematical issues, ranging from understanding the nature of these problems to exploring the challenges and future directions in the field. Supercomputers play a critical role in the practical applications of queueing theory across various industries by enabling the analysis and optimization of complex systems that involve waiting lines and service processes. In telecommunications networks, for instance, supercomputers are used to model and optimize traffic flow, ensuring efficient data transmission and minimal latency. By simulating network conditions under different traffic loads and service protocols, supercomputers help identify optimal resource allocations and configurations, significantly improving network reliability and performance. This capability is crucial for managing the ever-increasing data demands of modern communication systems.

Modbus Extension Server Implementation for BIoT-Enabled Smart Switch Embedded System Device.

The industrial control and automation sector has invested in the development and standardization of new wireless (WirelessHART, ISA 100.11a, and WIA-PA) and wired (Profibus/Profinet, Modbus, and LonWORK) solutions aimed at automating processes to support standard monitoring and control functions from the perspective of addressing critical applications, as well as those integrated within the Building Internet of Things (BIoT) concept. Distributed data acquisition and control systems allow modern installations to monitor and control devices remotely. Various network protocols have been proposed to specify communication formats between a client/gateway and server devices, with Modbus being an example that has been widely implemented in the latest industrial electrical installations. The main contribution made in this paper concerns the completion of the Modbus Extension (ModbusE) specifications for the server station in the classical Modbus communication architecture, as well as their implementation and testing in an STM32F4 kit. A general-purpose control architecture is proposed for BIoT sector, comprising both intelligent touch switches and communication protocols of which the Modbus protocol is used extensively for the monitoring and control part, especially between clients, smart switches, and devices. The specific contributions concern the presentation of a scientific and practical implementation of improved specifications and their integration as software modules on ModbusE protocol server stations. A client station with a VirtualComm USB PC connection is also implemented in the lab to test the operation of the proposed server with specific Modbus applications.

Assessing Invasive Carp in the Neosho River‐Grand Lake System of Kansas and Oklahoma

Invasive carp populations have purported a negative influence on native biota at high densities. These invasive fishes (i.e., bighead carp Hypophthalmichthys nobilis, silver carp Hypophthalmichthys molitrix, grass carp Ctenopharyngodon idella, and black carp Mylopharyngodon piceus) each exhibit similar life history characteristics. In the Neosho River‐Grand Lake system (i.e., John Redmond Reservoir, Kansas, downstream to Grand Lake O’ the Cherokees, Oklahoma), only bighead carp and grass carp have been documented to date. The distribution and status of bighead carp throughout this system were previously unknown due to limited historical data and low abundance. While few bighead carp are encountered within this system, grass carp exhibited relatively higher abundance a were used to provide insights into bighead carp. Captures of both species were used to inform management and suppression efforts. Sampling locations (n = 18) were established for environmental DNA analyses throughout the Neosho River‐Grand Lake system. We sampled 13 sites using a suite of gears for standardized targeted fish sampling. All invasive carp were measured, sexed, and otoliths removed for ageing and microchemical analysis. Grass carp were processed for ploidy testing following the U.S. Fish and Wildlife Service protocol. Environmental DNA analyses generated positive results for the eDNA presence of bighead carp and silver carp. Otolith age estimates suggest fish are long lived and supported by multiple year classes. Additionally, a sampled two‐year‐old grass carp demonstrates spawning and recruitment potential. Otolith microchemistry suggests largescale broad movement patterns. Ploidy testing confirmed the first documented evidence of diploid grass carp in the Neosho River‐Grand Lake system and revealed reproductive viability. Our results may provide future insights into locations for containment, removal, and/or eradication.

“Visibility” at Italian natural parks: preliminary data from the first-ever pilot project by ENEA and CUFAA

“Visibility” is meant as the greatest distance at which an observer can see a distant object in contrast with the horizon and, when referred to a landscape, it depends on the optical characteristics of the atmosphere, somehow linked to the presence of air pollutants. Visibility can hence become a useful indicator of air quality and the project Visibility, representing the first case of visibility monitoring in Europe, aims to apply this approach within the Italian National Parks as natural areas with a significant fruition vocation. The goal is to test the U.S. National Park Service protocol I.M.PRO.V.E. (Interagency Monitoring of PROtected Visual Environment) for the quantification of a coefficient that describes the light extinction (Bext) as a function of different chemical-physical parameters associated with molecules dispersed in the air, and the Circeo National Park (LT) was selected for the “pilot” action, with the positioning of the measuring instruments for atmospheric pollution evaluation at the Lago dei Monaci site. 24-hours samplings were performed in spring-summer 2021 and winter 2021/2022, to measure the air concentration of PM2.5 and PM10 particulate matter, sulfates and nitrates, elemental carbon and organic carbon, metals and trace elements and the gaseous species nitrogen dioxide, with the consequential calculation of the Bext. The visual detection of the degree of air transparency was performed by a panoramic camera pointed in the direction of the “landmark” Monte Circeo, taken as a reference for the definition of long-distance visibility.

A Distributed Ledger-A ssisted Robust and Trusted Service Protocol for VANETs

A Distributed Ledger-A ssisted Robust and Trusted Service Protocol for VANETs