Third-party Interference Research Articles

Experimental Verification on Deep Learning based Monitoring Algorithms for Early Detection of Damage in Buried Pipelines

Recent increases in buried pipeline damage accidents due to third-party interference have significantly heightened attention towards buried pipeline monitoring. Especially, as the sudden damage can lead to large-scale leakage, there is a necessity for preemptive response and maintenance. However, the application of a structural health monitoring approach is difficult, since the extensive network of buried pipelines, stretching over thousands of kilometers, exhibits diverse noise environments and propagation characteristics. As a result, challenges within the buried pipeline system frequently lead to damages being overlooked. In this study, introduces a deep learning-based pipeline damage monitoring algorithm, specifically designed to early detection of accidents caused by third-party interference. This algorithm integrates a CNN-based anomaly detection model, advanced signal processing for data preprocessing, and TDoA-based source localization. The training and test data set are the acquisition under completely independent conditions, which has been experimentally validate for applicability across various environments for buried pipelines. Moreover, both the training and test dataset acquisition were performed using accelerometers on in-service buried pipelines, each with diameters of 1,100 mm, 1,200 mm, and 2,200 mm, extending over lengths ranging from approximately 200 to 500 meters. Despite the independent conditions of the datasets, our study yielded over 95% accuracy in early detection, with the results being in good agreement with the actual excavate locations.

Navigating Environmental Stewardship: A Review of Construction Industry Practices in Developed Countries

Due to rapid urbanization, the construction industry has expanded significantly to meet human needs. Controlling environmental impacts in the construction sector has become a major global issue. The implementation of environmental management practices in the construction sector has contributed to protecting the environment through various management methods. This review aims to provide an overview of environmental management practices in the construction industry in developed countries, including a review of the types of environmental management practices and government policies for adopting these practices. The current status of these practices in developed countries is discussed, as well as the barriers and prospects for environmental management practices. Challenges include behavior adoption, lack of material standardization, monitoring difficulties, and inefficient formation of temporary organizations. Cooperation among construction parties presents coordination issues, exacerbating uneven cost distribution and neglect of environmental impacts. Adoption of ISO 14001 Environmental Management Systems faces hurdles such as lack of management involvement, third-party interference, and lack of guidelines. Initiatives like Green Star struggle due to poor enforcement and organizational issues, hindering sustainable development. To accomplish the goal of sustainable development, additional environmental factors have been taken into account and discussed.

The Third-party Intervention in Determining Price A comparative study

The absence of legislative regulation in Iraq regarding the issue of third-party interference in determining the price, and the many legal problems raised by this interference, the dispute over the legal jurisprudence in so far its rules is concerned, and the differences in the court's approaches as well motivates us to do this research. The research is done to determine the legal rule so as to set peace among the contact parties. And the study shows that the third party involved in determining the price is any person to whom the effect of the contract is not directed, and his job is considered as a combination of agency and contracting if he receives a payment. However, if it is unpaid, it is subject to the general theory of the contract, because it cannot be compatible with any contract. It also states that the contract associated with this permission is considered a suspended contract on a probable suspended condition, in which the third party determines the price, and whose decision obliges the parties and the court unless he exceeds its proposed authority permitted by the contract or commits a serious error. And the study sums up that the French legislator has explicitly stipulated the possibility of third party intervention in determining the price, while the general rules in Iraqi and Egyptian legislations are relied upon to find the legal basis for its intervention. The study attempts to delve into all the jurisprudential and judicial disputes regarding the spects in the subject of the study to recommend to the legislator by adding legislative texts that provide direct solutions to the problematic area.The study recommends jurisprudence and the judiciary to adopt solutions that would be compatible with available and proposed legislative texts.

An End-to-End Artificial Intelligence of Things (AIoT) Solution for Protecting Pipeline Easements against External Interference-An Australian Use-Case.

High-pressure pipelines are critical for transporting hazardous materials over long distances, but they face threats from third-party interference activities. Preventive measures are implemented, but interference accidents can still occur, making the need for high-quality detection strategies vital. This paper proposes an end-to-end Artificial Intelligence of Things (AIoT) solution to detect potential interference threats in real time. The solution involves developing a smart visual sensor capable of processing images using state-of-the-art computer vision algorithms and transmitting alerts to pipeline operators in real time. The system's core is based on the object-detection model (e.g., You Only Look Once version 4 (YOLOv4) and DETR with Improved deNoising anchOr boxes (DINO)), trained on a custom Pipeline Visual Threat Assessment (Pipe-VisTA) dataset. Among the trained models, DINO was able to achieve the best Mean Average Precision (mAP) of 71.2% for the unseen test dataset. However, for the deployment on a limited computational-ability edge computer (i.e., the NVIDIA Jetson Nano), the simpler and TensorRT-optimized YOLOv4 model was used, which achieved a mAP of 61.8% for the test dataset. The developed AIoT device captures the image using a camera, processes on the edge using the trained YOLOv4 model to detect the potential threat, transmits the threat alert to a Fleet Portal via LoRaWAN, and hosts the alert on a dashboard via a satellite network. The device has been fully tested in the field to ensure its functionality prior to deployment for the SEA Gas use-case. The AIoT smart solution has been deployed across the 10km stretch of the SEA Gas pipeline across the Murray Bridge section. In total, 48 AIoT devices and three Fleet Portals are installed to ensure the line-of-sight communication between the devices and portals.

An intelligent control for reducing third-party interference in oil and gas pipeline using Deep Q-Networks (DQN)

An intelligent control for reducing third-party interference in oil and gas pipeline using Deep Q-Networks (DQN)

Optimizing natural gas pipeline risk assessment using hybrid fuzzy bayesian networks and expert elicitation for effective decision-making strategies

Natural gas pipelines are susceptible to external and internal risk factors, such as corrosion, environmental conditions, external interferences, construction and design faults, and equipment failures. Bayesian Networks (BN) is a promising risk assessment approach widely used to evaluate these risk factors. One of BN's inherent limitations is its inability to accurately capture statistical dependencies and causal relationships, which can be overcome by incorporating expert elicitation into BN. To account for uncertainty and vagueness in assessing pipeline failure risks, fuzzy set theory (FST) can be combined with BN, commonly known as Fuzzy Bayesian Networks (FBN). This study developed an FBN framework that uses linguistic variables to calculate fuzzy probability (FPr) through domain expert elicitation, and crisp probabilities (CPr) are computed using historical incident data from the Pipeline and Hazardous Materials Safety Administration (PHMSA). Based on the findings from the case study of the Midwest region of the USA, external factors, i.e., third-party interference, outside force, and other incidents, significantly impact pipeline performance and reliability. Diagnosis inference indicates that in the Midwest region of the USA, pipeline material and age are critical factors leading to corrosion failure by threatening pipeline integrity. The findings from this study suggested that a targeted risk mitigation strategy is paramount for minimizing the risks associated with pipeline networks.

Selecting a Monitoring Technology for a Control System of Distributed Oil Production Facilities

The article proposes the structure of a SCADA system for monitoring and control of oil production facilities that are distributed over a large area. The main emphasis is on the selection of technology that will enable effective monitoring of the equipment of each oil well. Factors such as reliability, ease of use, availability of protection against third-party interference, as well as availability and accessibility of an open-source software code were taken into account. After reviewing the most common software platforms, a system based on Prometheus and Grafana was selected. It is a combination of the Prometheus time series database server and the Grafana information visualization and analysis system. The important factors that determined the choice of this platform were the availability of the open source code and a large library of ready-made templates for displaying the well parameters in real time. An example of the created visualization window of the dynamometer card of the well, built on the basis of the experimentally recorded data, is presented.

Dynamic risk assessment model for third-party damage to buried gas pipelines in urban location class upgrading areas

Buried gas pipeline leakage accidents caused by third-party interference in urban location class upgrading areas are time-varying and can cause serious consequences. This study proposed an integrated dynamic risk assessment model to address this issue. First, a bow-tie model combining a fault tree (FT) with an event tree (ET) was used to construct an overall evolutionary process from basic events to accidents and thus mapped into a Bayesian network (BN). The prior probabilities of basic events in FT and safety barriers in ET were determined by four types of methods, and the critical basic events were identified by sensitivity analysis. By integrating the Hierarchical Bayesian analysis method with time-varying precursor data, the dynamic probability updating of critical basic events and safety barriers was achieved, enabling adaptation of accident probabilities using BN. Then, a dynamic calculation method for accident consequences was proposed by integrating the appropriate leakage rates with a new time-varying method for calculating fatalities. Finally, a new risk matrix method was proposed to dynamically evaluate the risk level by integrating the accident probabilities with the consequences. A case study showed that the proposed model could dynamically evaluate the integrated accident risk, providing explicitly quantified support for risk management and emergency rescue of buried gas pipeline networks in urban location class upgrading areas.

Source location and anomaly detection for damage identification of buried pipelines using kurtosis-based transfer function

The failure of buried pipelines can lead to serious consequences such as explosions, environmental pollution, settlement, as well as economic loss. To prevent these outcomes, it is crucial to identify the causes of failure and monitor their signs. One of the main causes of failure is unexpected third-party interference (TPI), which is particularly challenging to detect. Regarding to this issue, this study proposes a new algorithm for monitoring impact damage, which can be used for prompt response and damage prevention. The algorithm is integrated into the system using two approaches. The first approach focuses on detecting the location of the damage (referred to as source location). A kurtosis-based transfer function was newly proposed to selecting the optimal frequency band for time-difference-of-arrival based source location, resulting in accurate pinpointing of damage, even in a noisy environment. The second approach is used to determine whether impact damage has actually occurred by observing newly suggested features in both the time and frequency domains (referred to as anomaly detection). These features evaluate the presence of damage and the similarity between signals. As a result, it was evaluated that the field applicability was higher than that of conventional methods, and the superiority of the proposed method was also verified through field experiments. The method proposed in this study is expected to enable immediate response when the integrity of the buried pipelines is on the line of failure due to TPI.

Third-party intervention and post-conflict behaviour in agonistic encounters of pigs (Sus scrofa)

BackgroundThird-party interference in agonistic contests entails a deliberate intervention in an ongoing fight by a bystanding individual (third party) and may be followed by post-conflict social behaviour to provide support to a specific individual. The mechanisms behind third-party intervention are, however, still largely understudied. The aim of this study was to investigate third-party interference, with the predictions that (1) the interferer derives benefits from its action by winning a fight, (2) that patterns of intervention depend on familiarity, (3) that dyadic fights last longer than triadic fights, and (4) that interferers engage in non-agonistic social behaviours afterwards. Pre-pubertal pigs (Sus scrofa) (n = 384) were grouped with one familiar and four unfamiliar conspecifics (all non-kin) to elicit contests for dominance rank. Third-party interference was analysed for the first 30 min after grouping, along with the behaviour (nosing or aggression), contest duration, contest outcome, and interferer behaviour after the fight (post-conflict social behaviour).ResultsThree types of interference were observed: non-agonistic involvement (nose contact) by the interferer in a dyadic fight; a triadic fight with each of three contestants fighting one opponent at a time; and triadic fights with two opponents jointly attacking the third one (two-against-one fights). The likelihood of a third-party intervention to occur did not depend on the presence of a familiar animal in the fight. However, once intervention was triggered, interferers attacked unfamiliar fight initiators more than familiar ones. Two-against-one fights lasted longer than other triadic fights and occurred more often when both initial contestants were females. Results of 110 triadic fights (out of 585 fights in total) revealed that interferers were more likely to win compared to the initial opponents at equal body weight. The most common post-conflict behaviour displayed by the interferer was agonistic behaviour towards another group member, independently of familiarity.ConclusionsThe general lack of discrimination for familiarity suggests interference is not driven by support to familiar individuals in pigs. The results show that intervening in an ongoing fight gives the interferer a high chance of contest success and may be a strategy that is beneficial to the interferer to increase its dominance status.

POTENTIAL OPPORTUNITIES OF BLOCKCHAIN TECHNOLOGY IN STREAMLINING THE MALAYSIAN COMMERCIAL OFFICE BUILDING OPERATION MANAGEMENT PROCESS

Managing commercial real estate is extremely complex and cumbersome and involves many stakeholders who provide access to and modify a variety of information. This led to some common issues with traditional commercial real estate management such as lack of transparency, third-party interference, the complexity of the agreements, record keeping and security, and absence of real-time data. Accordingly, blockchain technology is anticipated to address the issues of data openness, trustworthiness, and correctness in the global real estate market. This research aims to discover the potential opportunities that blockchain could offer in streamlining the commercial office building operation management process. A conceptual framework of blockchain-based technology adoption in the current Malaysian commercial office building operation management process was developed based on the literature review and focus group discussion (FGD). The framework was underpinned by four core operation management that emerge from the research findings including financial, administrative, technical, and promotional management.

Early Detection and Identification of Damage in In-Service Waterworks Pipelines Based on Frequency-Domain Kurtosis and Time-Shift Coherence

Buried pipelines, such as waterworks pipelines, are critical for transmitting essential resources and energy in modern cities, but the risk of pipeline failure, especially due to third-party interference, is a major concern. While various studies have focused on leak detection in waterworks pipelines, research on preventing impact damage is limited. To address this issue, this study proposes a novel algorithm that utilizes energy and similarity measurements for impact detection and compares it theoretically to existing leak-detection methods. The proposed algorithm utilizes frequency-domain kurtosis to determine the frequency band on which the energy of the impact signals is concentrated, along with a time-shift coherence function to measure the similarity of the signals. The application of the source location using the filtered signals enables accurate detection of the location of third-party interference. The proposed algorithm aims to ensure the safety and to prevent failures of buried pipelines. To verify the feasibility of the proposed algorithm, an excavation experiment using a backhoe was conducted on an in-service waterworks pipeline with a diameter of 2200 mm and a burial depth of 3 m. This experiment confirmed the effectiveness of the proposed algorithm in preventing failures of buried pipelines and demonstrated its practical applicability in the field. The experiment also validated the algorithm’s ability to detect third-party interference damage at various points.

URGENSI KAFA'AH DALAM MEMPERTAHANKAN KELUARGA DARI CAMPUR TANGAN ORANG TUA

This paper focuses on building family resilience from third-party intervention, which in this paper is parents/in-laws. The definition of a happy family is a family filled with mutual love, affection, protection and respect. However, the definition of a happy family above will not be achieved without the reconception of love and balance from the beginning and beyond as an effort to fortify the intervention of parents/in-laws. The application of the concept of harmony and balance in this study is one of the responsive efforts to create a stronghold of family resilience against the problematic intervention of parents/in-laws in the household life of their children/in-laws. This type of library research uses the descriptive-analytic method to obtain and analyze all the data obtained. The results of this study explain that it takes hard work and support between husband and wife to prevent third-party intervention as a trigger for household breakdown. Factors that influence parents to interfere in their children's households, namely: living in the same house, still close to the place of residence, lack of income from the son-in-law/child (economy), lack of affection from parents, lack of communication with in-laws and incompatibility between parents/in-laws and children/children in law. Anticipating the above, as an effort to build family resilience from third-party interference is to apply the concept of love and balance that each party can understand and good communication based on faith so that it can present an attitude of love and understanding and ultimately family harmony can be formed.

UAV-based MEC-assisted automated traffic management scheme using blockchain

In this paper, an automated real-time traffic management scheme is proposed by using unmanned aerial vehicles (UAV) in an effective and secured way. However, owing to the low computational capability and limited battery capacity of a UAV, multi-access edge computing (MEC) is applied to enhance the performance of an automated UAV-based traffic management scheme. Additionally, blockchain technology is introduced in the automated traffic management scheme to store the traffic record for providing network repudiation and avoiding any third-party interference with the network. An algorithm is developed based on the concept of a pairwise compatibility graph for the UAV-assisted automated traffic management scheme wherein a deep learning (DL) model is used for vehicle detection. Moreover, a two-phase authentication mechanism is proposed for a faster and secure verification process of the registered devices in the proposed scheme. Finally, a result analysis is conducted based on the security analysis and performance analysis to verify the effectiveness of the proposed scheme.

Sex (similarities and) differences in friendship jealousy

Friendships provide material benefits, bolster health, and may help solve adaptive challenges. However, a recurrent obstacle to sustaining those friendships—and thus enjoying many friendship-mediated fitness benefits—is interference from other people. Friendship jealousy may be well-designed for helping both men and women meet the recurrent, adaptive challenge of retaining friends in the face of such third-party interference. Although we thus expect several sex similarities in the general cognitive architecture of friendship jealousy (e.g., it is attuned to friend value), there are also sex differences in friendship structures and historical functions, which might influence the inputs of friendship jealousy (e.g., the value of any one friendship). If so, we should also expect some sex differences in friendship jealousy. Findings from a reanalysis of previously-published data and a new experiment, including both U.S. student and adult community participants (N = 993), provide initial support for three predicted sex differences: women (versus men) report greater friendship jealousy at the prospective loss of best friends to others, men (versus women) report greater friendship jealousy at the prospective loss of acquaintances to others, and men's (but not women's) friendship jealousy is enhanced in the context of intergroup contests.

Quantitative risk assessment methodology of installation process for deepwater oil and gas equipment

Proper installation of deepwater oil and gas equipment is a prerequisite to ensure its service life. Deepwater equipment faces many challenges during installation, such as the complexity of the installation process and uncertainty of the environment. Thus, risk assessment is necessary to guide personnel in avoiding and addressing potential problems during the installation of deepwater equipment. This study proposes a quantitative risk assessment method of installation process for deepwater oil and gas equipment based on fuzzy Bayesian networks (FBNs). First, the flow chart of deepwater oil and gas equipment in installation process is translated into a main Bayesian networks (BNs). Second, risk factors in different stages of installation are determined from human, management, equipment, environment and third-party interference, and entire risk assessment model is established. Finally, the FBN model is quantitatively analyzed by introducing fuzzy set theory. An empirical study on the installation process of subsea blowout preventer (BOP) is conducted. The results show that the failure of the subsea BOP installation is a small probability event, and equipment factors have the most prominent effect on the installation process. The sensitivity analysis results are consistent with the quantitative analysis. The corresponding improvement measures are proposed according to the analysis results.

Applying Ethical Issues in Research Statistical Analysis and Their Relation to Human Actions

Researchers in calculating or measuring statistics use research tools or software, and researchers must apply research ethics. However, many researchers are negligent in research ethics, especially in using statistics. It is related to the relationship and the actions of the researchers themselves. Thus, if ethical norms in research are not applied, there is falsifying, fabrication, and misrepresenting data that does not support the truth. The researcher’s responsibility seems to be lost, and the honesty of the researcher disappears. The actions of researchers or humans like that happen a lot and make research useless. This article discusses the dishonesty of researchers, third-party interference, and conflicts of interest. So, it becomes a fatal error. Therefore, the ideal of scientific perfection, where researchers must think critically and scientifically, feel or act and have reliability in measurement, is unpredictable.

MODIFIED FOG-BASED TRUST METHOD OF DATA MONITORING FOR MULTI-SENSOR CONFIGURATION SYSTEMS

.A modified Fog-based trust method to prevent third-party interference in establishing trust relationships between sensors and cloud service providers in multi-sensor systems is considered. Trust in behavior between nodes is established at the level of wireless sensor networks; in the nodes and objects data at the Fog layer. With more detailed data analysis of the latter, it becomes possible to monitor the trust status of the entire network, detect data attacks and recover from misjudged nodes. Fog layer can be built as a reliable third party. Experiment results show that the proposed trust mechanism is inherent in advantage due to reducing energy consumption and ensuring the trust state of Edge nodes and whole the network as well as detecting hidden attacks on data and recovering nodes.

Notes: Commodus usus, exclusive trade rights and public policy in lease: Masstores (Pty) Ltd v Pick ’n Pay Retailers (Pty) Ltd

In Masstores (Pty) Ltd v Pick ’n Pay Retailers (Pty) Ltd 2017 (1) SA 613 (CC) the Constitutional Court found that the personal right of exclusive trade in the lease contract was contrary to public policy and not worthy of protection. To do so, the court relied on the ‘competition principle’ — that the competitor who delivers the best or fairest (most reasonable) performance must achieve victory, while the one rendering the weakest (worst) performance must suffer defeat. The court was of the view that, as a general proposition, third parties have no legal duty not to infringe contractually derived exclusive rights to trade. According to the majority, exclusive trading rights make the competitive field uneven. The court emphasised that the boni mores must be understood in terms of the values of the Constitution, and that the values contained in the Bill of Rights are a crucial tool in the development of the common law. Although the majority judgment focused on the delict of unlawful third-party interference in a contractual relationship and the nature of interdicts, the judgment relates also to the question of the personal right to commodus usus in a lease contract, and the remedies available to vindicate this right. The intersection of these issues is investigated in this note.

Dynamic reliability model for subsea pipeline risk assessment due to third-party interference

The accidents of subsea pipelines due to third-party interference often result in catastrophic impacts, therefore, risk assessment has progressively become substantial to ensure the safety and reliability of the systems. However, the current risk analysis approaches are unable to minimize the uncertainties in the analysis due to the high demands of the qualitative inputs. The Bayesian network approach is believed to be able to provide answers to such a problem. The main advantage of this technique is that it allows the inference model and predictive analysis for constructing the current and future performance of the system based on the observed evidence. These can be achieved by introducing the subsea pipeline’s accident history and operational data in the model for developing the conditional probability distribution of each variable in the analysis. This paper proposes a dynamic reliability model for subsea pipeline risk assessment due to third-party interference based on the Bayesian approach. This technique is combined with fault tree and the finite element models for producing a reliable risk assessment framework for subsea pipelines. It is expected that the proposed model will be able to minimize the number of qualitative inputs in the analysis and also provides dynamic results for estimating the risk level of the subsea pipeline throughout its service life.