Sensitive Nodes Research Articles

Comprehensive analysis of ship sinking accidents using Bayesian network

ABSTRACT Sinking accidents can cause catastrophic losses in human, economic resources and environmental damage. Sinking accidents are one of the most common maritime accidents that occur in Indonesia. Therefore, this study aims to analyze the cause-and-effect probability of ship sinkings in Indonesian waters. Bayesian Network method and accident factor level are used to analyze the causal factors of ship sinking accidents. The results found that the Loss of Stability of the vessel is the most sensitive node. An additional take from the investigated sinking is that half of the accidents occurred on passenger vessels, and ships over 25 years old are prone to sinking due to corrosion and lack of proper maintenance. While 70.5% of accident caused by human error that is majorly triggered by unsafe acts. The real-case analysis also performed in this study reveals that eliminating Human Error and ship’s associated factors can reduce the probability of sinking by 17.2%.

Design of a Radiation-Hardened SRAM Cell using 16nm Technology Node

Electronic circuits are exposed to very high energy radiation in the harsh conditions of outer space. This leads to soft errors such as single-event upsets (SEU), double-event upsets (DEU) and single-event transients (SET). The memory circuits are the most susceptible to these soft errors resulting in severe data loss. This paper proposes the design for an SRAM cell that is radiation hardened by design (RHBD). A comparative study of the standard SRAM cell and the RHBD SRAM cell indicates that the proposed design is resilient to SEUs and DEUs. The proposed design is an improvement on the 8T SRAM cell design and includes a 20T triple interlocked cell (TICE) design. The error correction capabilities of both designs are compared by manually injecting bit upsets at crucial nodes in the circuit. It is observed that the TICE design provides a 96.75% and 98.5% improvement over the standard 8T cell for 1-0 and 0-1 bit upsets respectively. The proposed design has been implemented using the 16nm model from the Arizona State University’s Predictive Technology Model (ASU-PTM), and the LTSpice software was used to carry out the simulations. Tools used: LTSpice v17 is the tool used to design the schematic circuits and to obtain the simulation results. The library file used to design the schematic is the 16nm technology node from the library of the Arizona State University’s Predictive Technology Model (ASU-PTM). Methods: To perform a comparative study of the 8T SRAM and 20T TICE, the schematic circuits were designed using the 16nm technology node in LTSpice. A baseline for the expected voltages of logic 0 and logic 1 is established before injecting errors at the sensitive voltage nodes of the circuit. The next step is to manually inject bit upsets at the crucial nodes of the memory cell to induce either a 0-1 upset or a 1-0 upset. The read/write operation is carried out along with the error injection to compare the error mitigation capacity of the circuits. Finally, the results are tabulated to prove that the 20T TICE is resilient to soft errors arising from exposure to high radiation. Results: During the normal operation of the 8T SRAM cell, the observed output voltage corresponding to logic 0 and logic 1 are 25mV and 780mV respectively. The voltage levels increased to 400mV during a 0-1 upset and dropped to 25mV during a 0-1 bit upset. This indicates that the cell is not reliable. In case of the 20T RHBD cell, the voltage levels for the normal operation were 5mV (logic 0) and 780mV (logic 1). The major improvement is shown in the case where the 20T TICE is injected with bit upsets, since it delivers a voltage of just 6mV during a 0-1 bit upset and maintains a voltage of 770mV during a 1-0 bit upset. Conclusion: The work performs the schematic designs for the comparison of the error mitigation capabilities of a 8T SRAM cell and a 20T TICE which is radiation hardened by design. The study proves that the 20T cell is capable of successfully mitigating both a 1-0 bit upset and a 0-1 bit upset

Identifying vital nodes for yeast network by dynamic network entropy

BackgroundThe progress of the cell cycle of yeast involves the regulatory relationships between genes and the interactions proteins. However, it is still obscure which type of protein plays a decisive role in regulation and how to identify the vital nodes in the regulatory network. To elucidate the sensitive node or gene in the progression of yeast, here, we select 8 crucial regulatory factors from the yeast cell cycle to decipher a specific network and propose a simple mixed K2 algorithm to identify effectively the sensitive nodes and genes in the evolution of yeast.ResultsConsidering the multivariate of cell cycle data, we first utilize the K2 algorithm limited to the stationary interval for the time series segmentation to measure the scores for refining the specific network. After that, we employ the network entropy to effectively screen the obtained specific network, and simulate the gene expression data by a normal distribution approximation and the screened specific network by the partial least squares method. We can conclude that the robustness of the specific network screened by network entropy is better than that of the specific network with the determined relationship by comparing the obtained specific network with the determined relationship. Finally, we can determine that the node CDH1 has the highest score in the specific network through a sensitivity score calculated by network entropy implying the gene CDH1 is the most sensitive regulatory factor.ConclusionsIt is clearly of great potential value to reconstruct and visualize gene regulatory networks according to gene databases for life activities. Here, we present an available algorithm to achieve the network reconstruction by measuring the network entropy and identifying the vital nodes in the specific nodes. The results indicate that inhibiting or enhancing the expression of CDH1 can maximize the inhibition or enhancement of the yeast cell cycle. Although our algorithm is simple, it is also the first step in deciphering the profound mystery of gene regulation.

Electron-Induced Single-Event Effect in 28 nm SRAM-Based FPGA

As the feature size of integrated circuit decreases, the critical charge of single-event effect decreases as well, making nano-scale devices more susceptible to the high-energy charged particles during their application in space. Here, we study the electron-induced single-event effect in 28 nm static random-access memory (SRAM)-based field programmable gate array (FPGA) utilizing high-energy electrons with energy of 1 MeV~5 MeV. The experimental results demonstrate that the 3 MeV electrons can cause single-event functional interrupts (SEFIs) in FPGA, while the electrons with other energies cannot. To further explore the mechanism of electron-induced SEFIs in this nanoscale FPGA, we combined Monte Carlo, Technology Computer-Aided Design (TCAD), and Simulation Program with Integrated Circuit Emphasis (SPICE) simulations. It is revealed that the SEFI was mainly caused by the direct ionization effect of high-energy electrons, and the SEFI was related to the interactions between multiple sensitive nodes.

Privacy protection and utility trade-off for social graph embedding

In graph embedding protection, deleting the embedding vector of a node does not completely disrupt its structural relationships. The embedding model must be retrained over the network without sensitive nodes, which incurs a waste of computation and offers no protection for ordinary users. Meanwhile, the edge perturbations do not guarantee good utility. This work proposed a new privacy protection and utility trade-off method without retraining. Firstly, since embedding distance reflects the closeness of nodes, we label and group user nodes into sensitive, near-sensitive, and ordinary regions to perform different strengths of privacy protection. The near-sensitive region can reduce the leaking risk of neighboring nodes connecting to sensitive nodes without sacrificing all of their utility. Secondly, we use mutual information to measure privacy and utility while adapting a single model-based mutual information neural estimator to vector pairs to reduce modeling and computational complexity. Thirdly, by keeping adding different noise to the divided regions and reestimating the mutual information between the original and noise-perturbed embeddings, our framework achieves a good trade-off between privacy and utility. Simulation results show that the proposed framework is superior to state-of-the-art baselines like LPPGE and DPNE.

Deep reinforcement learning based latency-energy minimization in smart healthcare network

Significant breakthroughs in the Internet of Things (IoT) and 5G technologies have driven several smart healthcare activities, leading to a flood of computationally intensive applications in smart healthcare networks. Mobile Edge Computing (MEC) is considered as an efficient solution to provide powerful computing capabilities to latency or energy sensitive nodes. The low-latency and high-reliability requirements of healthcare application services can be met through optimal offloading and resource allocation for the computational tasks of the nodes. In this study, we established a system model consisting of two types of nodes by considering nondivisible and trade-off computational tasks between latency and energy consumption. To minimize processing cost of the system tasks, a Mixed-Integer Nonlinear Programming (MINLP) task offloading problem is proposed. Furthermore, this problem is decomposed into task offloading decisions and resource allocation problems. The resource allocation problem is solved using traditional optimization algorithms, and the offloading decision problem is solved using a deep reinforcement learning algorithm. We propose an Online Offloading based on the Deep Reinforcement Learning (OO-DRL) algorithm with parallel deep neural networks and a weight-sensitive experience replay mechanism. Simulation results show that, compared with several existing methods, our proposed algorithm can perform real-time task offloading in a smart healthcare network in dynamically varying environments and reduce the system task processing cost.

A 45nm AND 65nm CMOS IMPLEMENTATION OF 12T SRAM CELL WITH SOFT ERROR READ STABILITY OF MULTINODE UPSET RECOVERABILITY FOR AEROSPACE APPLICATION

With technology advancing rapidly, the size of transistors and the distance between them is decreasing quickly. This reduction in size is causing the critical charge of sensitive nodes in SRAM cells to decrease, making them more susceptible to soft errors, especially in aerospace applications. When a radiation particle strikes a open node in a standard 6T SRAM cell, the storage data in the cell can be changed, leading to a single-event upset (SEU). To address this issue, a new Soft Error Read and write Stability improves Low Power 12T (SARP12T) SRAM cell has been introduced in this study to reduce the impact of SEUs. The performance of SARP12T has been compared to other recently developed soft-error-aware SRAM cells like QUCCE12T, QUATRO12T, RHD12T, RHPD12T, and RSP14T. SARP12T is designed for the recoverability of all stored data in sensitive nodes even if they are affected by radiation strikes. Additionally, SARP12T can overcome single-event multi-node upsets (SEMNUs) that may happened at its sensitive node pair. This proposed cell also boasts the higher read stability, as the storage node holding '0' can regain from any upset during read operations. Moreover, SARP12T consumes the minimum amount of hold power, has greater write ability, and lower write delay compared to other similar cells. Despite a almost greater read delay and higher read and write energy consumption, the improvements in the proposed SARP12T cell make it a promising solution for mitigating soft errors in SRAM cells

The Study on Single-Event Effects and Hardening Analysis of Frequency Divider Circuits Based on InP HBT Process.

The single-event effects (SEEs) of frequency divider circuits and the radiation tolerance of the hardened circuit are studied in this paper. Based on the experimental results of SEEs in InP HBTs, a transient current model for sensitive transistors is established, taking into account the influence of factors such as laser energy, base-collector junction voltage, and radiation position. Moreover, the SEEs of the (2:1) static frequency divider circuit with the InP DHBT process are simulated under different laser energies by adding the transient current model at sensitive nodes. The effect of the time relationship between the pulsed laser and clock signal are discussed. Changes in differential output voltage and the degradation mechanism of unhardened circuits are analyzed, which are mainly attributed to the cross-coupling effect between the transistors in the differential pair. Furthermore, the inverted output is directly connected to the input, leading to a feedback loop and causing significant logic upsets. Finally, an effective hardened method is proposed to provide redundancy and mitigate the impacts of SEEs on the divider. The simulation results demonstrate a notable improvement in the radiation tolerance of the divider.

Soft-Error Reduction and Enhancement of Write Stability and Hold Power Optimization by using 12T SRAM for Aerospace Applications

As the technology has rapidly evolved and also high-speed task implementation has come into picture the chance for an error to occur has also increased though there are many precision algorithms to increase the precision of the system significantly this paper proposes one such error reducing application for aerospace applications. Using a Quadruple Cross-Coupled Latch-Based 10T and 12T SRAM Bit-Cell Designs for Highly Reliable Terrestrial Applications (QUCCE12T) is more susceptible to data loss as the QUCCE12T SRAM has high sensitivity and the sensitive nodes are at higher risk. To reduce this, we propose to use Soft-Error Reduction and Enhancement of Write Stability and Hold Power Optimization by using 12T SRAM (SREWH12T). Basically, the initial thought is to reduce the soft error created by voltage drops by passing the data through the inverters. The Single Event Upset (SEU) that arise in the usage of QUCCE12T SRAM can be recovered using a SREWH12T SRAM instead. The sensitive components of SREWH12T have the capability to recover their data even in cases where the values have been altered by radiation impact. The SREWH12T SRAM cell to mitigate upsets, compares it with other cells, and demonstrates its superior performance in terms of soft-error tolerance, recovery from upsets and having low power consumption. Furthermore, the added advantage of SREWH12T cell is that it can recover from Single Event Multiple Nodes Upset (SEMNU). Average power consumed by SREWH12T is 2.988363e-007 watts. Along with this the SREWH12T SRAM can provide high write stability due to its recovery rate. All these added advantages and recovery of data all comes at high utility range and with slightly high read energy consumption, which is very minimal, the system also exhibits slightly high read delay.

FairGap: Fairness-Aware Recommendation via Generating Counterfactual Graph

The emergence of Graph Neural Networks (GNNs) has greatly advanced the development of recommendation systems. Recently, many researchers have leveraged GNN-based models to learn fair representations for users and items. However, current GNN-based models suffer from biased user–item interaction data, which negatively impacts recommendation fairness. Although there have been several studies employing adversarial learning to mitigate this issue in recommendation systems, they mostly focus on modifying the model training approach with fairness regularization and neglect direct intervention of biased interaction. In contrast to these models, this article introduces a novel perspective by directly intervening in observed interactions to generate a counterfactual graph (called FairGap) that is not influenced by sensitive node attributes, enabling us to learn fair representations for users and items easily. We design FairGap to answer the key counterfactual question: “Would interactions with an item remain unchanged if a user’s sensitive attributes were concealed?”. We also provide theoretical proofs to show that our learning strategy via the counterfactual graph is unbiased in expectation. Moreover, we propose a fairness-enhancing mechanism to continuously improve user fairness in the graph-based recommendation. Extensive experimental results against state-of-the-art competitors and base models on three real-world datasets validate the effectiveness of our proposed model.

Wind-Induced Vibration Analysis of a Pentagonal Three–Four Strut Hybrid Open-Type Cable Dome

Previous research has confirmed that the newly proposed pentagonal three–four strut hybrid cable dome exhibits superior static performance compared to traditional cable domes, though its dynamic characteristics still require further study. Cable domes are wind-sensitive structures, and the results of a wind-induced vibration analysis are beneficial for the selection and construction of cable domes. In this study, a finite element model of a new open-type cable dome with a span of 120 m is established. The MATLAB 2017a programming language is employed to simulate pulsating winds, followed by a nonlinear dynamic analysis to analyze the wind-induced vibrations of the structure. The reliability of the pulsating wind model is confirmed by comparing the simulated spectrum with the target spectrum. Moreover, a wind-induced vibration time history analysis is performed to obtain the node displacement and internal force of components wind vibration coefficients, aiding in the approximation of pulsating winds with average winds in a wind-resistant design. Furthermore, a parametric analysis is carried out, ranking nodes and components based on sensitivity. The result shows that the structure exhibits the strongest wind resistance when the rise–span ratio is f/l=0.07 and the thickness–span ratio is h/l=0.08. Notably, the outer upper chord node, 2a, and the inner lower chord hoop cable, H1, are identified as the most sensitive node and component within the structure, respectively. Overall, the structure demonstrates excellent wind resistance performance, and the maximum wind vibration coefficient value remains below 3.

An efficient radiation hardening SRAM cell to mitigate single and double node upset soft errors

Various charged particles in space, including α- particles, neutrons, heavy ions, and photons, create stability and reliability concerns in memory circuits. Furthermore, these particles generate an ion track within the memory device, which disrupts the storage bit. The standard 6T SRAM is very susceptible to this upset. To address this issue, several authors proposed radiation-hardened SRAM cells. Most of the works consider adding redundant nodes to the memory cell. This study shows a new RHBD-14T SRAM memory cell with redundant nodes to deal with the soft error problem. The proposed RHBD-14T memory cell performance is compared to that of recent reliable radiation-hardened memory cells such as SEA-14T, QCCS-12T, NRHC-14T, RHMC-12T, HPHS-12T, SIMR-18T, SERSC-16T, RHWC-12T. The proposed RHBD-14T cell protects against single and double-node disruptions by considering minimum sensitive nodes layout area separation concept. Furthermore, proposed RHBD-14T exhibits 1.45x/ 1.06x/ 1.54x/ 1.25x/ 2.86x/ 1.39x/ 1.31x/ 1.57x times greater read stability than existing SEA-14T/ QCCS-12T/ NRHC-14T/ RHMC-12T/ HPHS-12T/ SIMR-18T/ SERSC-16T/ RHWC-12T memory cells.

A soft error upset hardened 12T-SRAM cell for space and terrestrial applications

Various charged particles in space, including alpha particles, neutrons, heavy ions, and photons, pose reliability and stability concerns for memory circuits. These particles also create an ion track in the memory chip, disrupting the storage bit. The standard 6T SRAM is particularly susceptible to these disturbances. Several researchers suggest employing radiation-hardened SRAM cells to solve this problem. Most studies examine the inclusion of redundant nodes in the memory cell to recover the lost bit. This paper shows a new SEUH-12T SRAM memory cell with redundant nodes to deal with the soft error problem. The proposed SEUH-12T memory cell performance is compared to that of reliable radiation-hardened memory cells such as Quatro-10T, We-Quatro-12T, QCCS-12T, STS-10T, RHMC-12T, and RHWC-12T. The proposed SEUH-12T cell protects against single and multiple node disruptions by considering minimum sensitive nodes layout area separation concept. Furthermore, proposed SEUH-12T exhibits 8.5×/ 6.3×/ 5.6×/ 1.4×/ 1.2×/ 1.4×/ 1.04× times greater read stability than existing 6T-SRAM/ Quatro-10T/ We-Quatro-12T/ QCCS-12T/ STS-10T/ RHMC-12T/ RHWC-12T memory cells.

Novel Radiation Hardened DSOT-MRAM Read Peripheral Circuit With Reduced Sensitive Nodes

Novel Radiation Hardened DSOT-MRAM Read Peripheral Circuit With Reduced Sensitive Nodes

Optimal configuration of distributed wind turbines with D-STATCOMs for improving voltage recovery capability of sensitive nodes

Optimal configuration of distributed wind turbines with D-STATCOMs for improving voltage recovery capability of sensitive nodes

Estimation of the location of inter-area oscillations and their interactions in electrical power systems using Lyapunov modal analysis

Modern large-scale electrical power systems face serious stability threats in the form of low-frequency oscillations. Based on the recently proposed Lyapunov modal analysis framework, this study proposes a method for estimating the location and structure of inter-area oscillations as well as their interactions on the graph of an electrical power system. This method combines the known approaches of modal analysis and spectral decomposition of Lyapunov functions. In contrast to conventional modal analysis, modal indicators that consider the energy of voltage disturbances accumulated over time are proposed rather than the instantaneous dynamics of an individual perturbation. These indicators help analyze not only the location and structure of individual inter-area oscillations but also the geometry and structure of their pair-wise interactions in terms of the mutual action of modes, which is produced in the nodes over time. Motivational examples that illustrate the benefits of the proposed energy-based indicators are discussed. In test experiments using the New England IEEE 68 bus system, the proposed method is compared with the network modeshapes method to assess the locations of the nodes and ties that are critical for the selected inter-area oscillations. In a scenario experiment, the locations of the most sensitive nodes at the resonant modal interaction are examined. The proposed method can be used to analyze the resonance phenomena that arise in modern EPSs, especially in connection with the growth of renewable energy sources and the active use of thyristor converters. Novel approach can improve various control methods used for damping inter-area oscillations, optimal placement of sensors and stabilizers, and the analysis of voltage stability.

Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm

The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the impact is different when a leak occurs in different nodes. In this study, sensitivity functions of different nodes were obtained according to the influence of the leakage of each node on the water distribution network. Combined with the water pressure correlation and water pressure sensitivity between nodes, the monitoring range of monitoring points and the water demand of covering nodes of monitoring points were taken as objective functions to build an optimal layout model. Taking a pipeline network in Qingdao as an example, the model was solved by using multi-objective White Whale Optimization and NSGA-II. By comparing the operation results of the four cases, it was found that the monitoring points found using multi-objective White Whale Optimization show better searching ability in terms of the sensitivity functions of different nodes.

Efficient Sensor Node Selection for Observability Gramian Optimization.

Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-invariant, and discrete-time dynamical system are examined under the assumption of independent and identically distributed measurement noise. This study offers two novel selection algorithms, namely an approximate convex relaxation method with the Newton method and a gradient greedy method, and confirms the performance of the selection methods, including a convex relaxation method with semidefinite programming (SDP) and a pure greedy optimization method proposed in the previous studies. The matrix determinant of the observability Gramian was employed for the evaluations of the sensor subsets, while its gradient and Hessian were derived for the proposed methods. In the demonstration using numerical and real-world examples, the proposed approximate greedy method showed superiority in the run time when the sensor numbers were roughly the same as the dimensions of the latent system. The relaxation method with SDP is confirmed to be the most reasonable approach for a system with randomly generated matrices of higher dimensions. However, the degradation of the optimization results was also confirmed in the case of real-world datasets, while the pure greedy selection obtained the most stable optimization results.

A High-Reliability 12T SRAM Radiation-Hardened Cell for Aerospace Applications.

The static random-access memory (SRAM) cells used in the high radiation environment of aerospace have become highly vulnerable to single-event effects (SEE). Therefore, a 12T SRAM-hardened circuit (RHB-12T cell) for the soft error recovery is proposed using the radiation hardening design (RHBD) concept. To verify the performance of the RHB-12T, the proposed cell is simulated by the 28 nm CMOS process and compared with other hardened cells (Quatro-10T, WE-Quatro-12T, RHM-12T, RHD-12T, and RSP-14T). The simulation results show that the RHB-12T cell can recover not only from single-event upset caused by their sensitive nodes but also from single-event multi-node upset caused by their storage node pairs. The proposed cell exhibits 1.14×/1.23×/1.06× shorter read delay than Quatro-10T/WE-Quatro-12T/RSP-14T and 1.31×/1.11×/1.18×/1.37× shorter write delay than WE-Quatro-12T/RHM-12T/RHD-12T/RSP-14T. It also shows 1.35×/1.11×/1.04× higher read stability than Quatro-10T/RHM-12T/RHD-12T and 1.12×/1.04×/1.09× higher write ability than RHM-12T/RHD-12T/RSP-14T. All these improvements are achieved at the cost of a slightly larger area and power consumption.

A Soft-Error-Immune Quadruple-Node-Upset Tolerant Latch

With the continuous technology scaling of integrated circuits, storage devices are more and more easily affected by soft errors. In order to improve the reliability of storage devices and reduce overhead especially in terms of power dissipation effectively, this paper proposes a Soft-Error-Immune Quadruple-Node-Upset tolerant latch (Quad-SIRI). The latch consists of two interlocked SIRI (Soft-error-immune) SRAM cells for dual modular redundancy. Considering the characteristic of radiation-induced voltage pulse, the SIRI is designed with stacked transistors to tolerate single-node-upset and reduce sensitive nodes and area overhead. Quad-SIRI latch achieves low area overhead because of fewer transistors. Quad-SIRI latch achieves low power consumption because of clock-gating technique. However, pass transistors and stacked transistors result in small critical charge of the latch. HSPICE simulation in 22nm CMOS technology shows that, compared with quadruple-node-upset tolerant latches (LCQNUSR, QNUTL and 4NUHL), Quad-SIRI latch achieves the smallest delay, power and area, at the cost of smaller critical charge. Extensive variation analysis shows that Quad-SIRI latch is less sensitive to temperature and voltage variation in terms of power consumption and less sensitive to temperature variation in terms of delay. So, compared with the existing latches, Quad-SIRI latch makes a good trade-off among delay, power, area and critical charge, and thus it is a good choice for radiation hardening by design in spaceborne applications with low energy particle striking.