Faulty Hardware Research Articles

Incidents and Impacts on Operator Revenue in the Telecommunications Sector

This study adopted a multiple case-study approach to investigate incidents, their impacts on performance, and revenues in the telecommunications sector using data from Ghana. The study used open-ended qualitative interviews and document review methods. The study performed a thematic analysis with the Atlas TI software program to analyse the qualitative dataset. The findings resulted in a model dubbed the “Telecommunications Sector Incidents Framework”, which reveals that faulty hardware, end-of-system life, cell site congestion, power failure, microwave link failure, fibre failure, and Wi-Fi disconnection are among the incidents prevalent in the telecommunications sector. The framework also reveals that the incidents occur frequently, resulting in an average revenue loss of GH₵2 to 3 million ($182K to $273K) per month. Again, it reveals that employees become demoralized due to a lack of work-life balance, sleepless nights, frustrations, and undue pressure, which affects their productivity levels. With this framework, mobile network operators (MNOs) could get a better understanding of the incidents to keep their occurrences to a manageable level, create an exceptional customer experience by reducing churn, and increase revenues.

Contaminated bone grafts and tuberculosis in three spine surgery patients: a case series

Tuberculosis (TB) is a global health issue affecting millions of people every year. Previous articles displayed cases of TB resulting from contaminated bone grafts used in spinal surgeries. However, deeper understanding about the serious health consequences for patients affected by TB-infected bone grafts is lacking. Here, we discuss three unique patients who contracted TB after undergoing lumbar spinal surgery. We describe three patient cases in which individuals initially presented with back pain, underwent required lumbar spinal fusion surgery with bone graft implants, and, afterwards, contracted TB. All patients were given RIPE therapy, had additional surgery to remove the faulty hardware, and lived with significant and prolonged pain. In addition, patient X experienced night sweats, patient Y had a subcutaneous abscess positive for TB, and patient Z had severe burning pain, rash, and sweats. Altogether, we emphasize the importance of increasing our awareness about the potential risks and complications associated with utilizing contaminated surgical products. We encourage healthcare professionals to take necessary precautions to ensure the safety of their patients by screening bone grafts for potential pathogens and practicing proper sterilization techniques.

Improving Data Transmission Rate with Self Healing Activation Model for Intrusion Detection with Enhanced Quality of Service

Several types of attacks can easily compromise a Wireless Sensor Network (WSN). Although not all intrusions can be predicted, they may cause significant damage to the network and its nodes before being discovered. Due to its explosive growth and the infinite scope in terms of applications and processing brought about by 5G, WSN is becoming more and more deeply embedded in daily life. Security breaches, downed services, faulty hardware, and buggy software can all cripple these enormous systems. As a result, the platform becomes unmaintainable when there are a million or more interconnected devices. When it comes to network security, intrusion detection technology plays a crucial role, with its primary function being to constantly monitor the health of a network and, if any aberrant behavior is detected, to issue a timely warning to network administrators. The current network's availability and dependability are directly tied to the efficacy and timeliness of the Intrusion Detection System (IDS). An Intrusion-Tolerant system would incorporate self-healing mechanisms to restore compromised data. System attributes such as readiness for accurate service, supply identical and correct data, confidentiality, and availability are necessary for a system to merit trust. In this research, self-healing methods are considered that can detect intrusions and can remove with intellectual strategies that can make a system fully autonomous and fix any problems it encounters. In this study, a new architecture for an Intrusion Tolerant Self Healing Activation Model for Improved Data Transmission Rate (ITSHAM-IDTR) is proposed for accurate detection of intrusions and self repairing the network for better performance, which boosts the server's performance quality and enables it to mend itself without any intervention from the administrator. When compared to the existing paradigm, the proposed model performs in both self-healing and increased data transmission rates..

Performance Analysis of An Optical Fiber Communication Network

The introduction of optical fiber has transformed the telecommunication industry and it has played a very important and key part in the information age. Optical fiber is widely preferred for data transmission to other media of communication because of their capability to carry extensive information and its dielectric nature. However, this mode of transmission has faced an issue of high latency which later reduces the throughput as well as reducing the quality of Experience at the customer side. This paper presents how different tests of throughput and latency were carried out using Viavi test kit, analyzed and then after compared the obtained results with the standard defined by IEEE and ITU for conformity. Some of the results conformed with the defined whereas others did not because of different reasons that include congestion of the link, faulty hardware on the network, poor quality of the fiber cable and the distance covered by the optical fiber link. The mitigation measures for the above causes were discussed in this paper and they include upgrading the bandwidth of the link, ensuring the use of quality fiber cables, regular maintenance in order to sight out the faulty components on the link as well as employment of several repeaters on long distance optical fiber links.

Online intelligent fault diagnosis of redundant sensors in PWR based on artificial neural network

Sensors in the primary circuit of a pressurized water reactor (PWR) are normally designed with redundant structures to improve system safety and reliability. However, reliability of the actual system is often lower than that obtained by theoretical calculation due to the inevitable occurrence of common mode fault (CMF), which is a dependent failure event that can cause multiple failures in redundant channels. CMF may increase the reliability deviation of the system by orders of magnitude and, hence, seriously affects the reliability of the system. To mitigate the CMF of redundant sensors in nuclear power plants, an artificial neural network (ANN) can serve as a data-driven analytic model to monitor sensor parameters, to identify any possible abnormal status of the sensors, and provide an early warning. In this study, by using the high-fidelity dataset obtained in a full-scope PWR simulator as training, validation, and test data, a relevant parameter-based ANN black-box model (RPANN) was established by employing the back-propagation (BP) learning algorithm, which was then defined as an analytic redundancy. Time series-based ANN checking models (TSANNs) were also established for each of the input and output parameters of the RPANN in order to identify its abnormal state based on historical data in the past. When combined with the existing hardware redundancy, the ANN-based analytic redundancy can serve as an online monitoring tool of the hardware status and an online diagnosis strategy for sensor faults. Furthermore, ANN-based analytic redundancy can replace faulty hardware sensors to analytically reconstruct the reading of the monitored sensor parameter without having to reduce the reactor output power or even shut down the reactor for emergency maintenance so that the on-site calibration frequency of hardware sensors in redundant channels can be effectively reduced. This is not only of vital importance in reducing operation and maintenance costs of existing PWR power plants but also plays an important role in building reactor operation schemes with rapid and frequent changes in power output in the future. Simultaneously, the diverse redundancy combining analytic software redundancy and physical hardware redundancy can effectively reduce the threat of CMF of hardware sensors on the operation safety of reactor systems.

Evaluation of a continuous neonatal temperature monitor for low-resource settings: a device feasibility pilot study

ObjectiveEvaluate a novel continuous temperature monitor in a low-resource neonatal ward.DesignWe developed a low-cost continuous neonatal temperature monitor (NTM) for use in low-resource settings. Accuracy of NTM was initially assessed...

The integration of music technology into popular music ensembles: Perspectives of modern band teachers

The increased presence of technology into music education classrooms has coincided to some extent with the increased presence of popular music into school music spaces, especially in the United States. This study examined the integration of music technologies into K-12 (ages 5–18) popular music programmes in New York City (NYC). One hundred sixty-eight music teachers responded to a survey, all of whom had previously participated in a modern band workshop as part of the Amp Up NYC initiative. Results of the study found that many of the challenges of incorporating music technology into modern bands, including lack of access to technology or faulty hardware, are not unique to popular music ensembles. Some of the successes mentioned by the teachers, including songwriting, beat-making and increased student agency, provide a glimpse into the benefits that integrating music technology into modern band classrooms can offer.

Input quality aware convolutional LSTM networks for virtual marine sensors

The harsh environmental conditions in a marine area make continuous observations of it challenging. To temporally or permanently replace faulty hardware sensors, reliable virtual sensors are getting more and more important. This paper introduces a deep learning architecture for a marine virtual sensor application that is able to utilize input quality information. We propose a novel input quality based dropout layer to take advantage of Information about the quality of the input sensors. The virtual sensor models are built upon convolutional and recurrent long short-term memory layers. We apply a time dimensionality reduction method called exPAA that retains finer details from recent values, but past information with less details are also available to the model. As interpretable reliability is important virtual sensors, we include predictive uncertainty based on dropout and Monte Carlo predictions into our neural network. Experimental results show that we perform better than the baseline and our input quality based dropout layer improves on these results even further. We also provide insights on the learned uncertainty intervals as well as the utilized linear and non-linear correlations of the first convolutional layer.

Optimal length of decomposition sequences composed of imperfect gates

Quantum error correcting circuitry is both a resource for correcting errors and a source for generating errors. A balance has to be struck between these two aspects. Perfect quantum gates do not exist in nature. Therefore, it is important to investigate how flaws in the quantum hardware affect quantum computing performance. We do this in two steps. First, in the presence of realistic, faulty quantum hardware, we establish how quantum error correction circuitry achieves reduction in the extent of quantum information corruption. Then, we investigate fault-tolerant gate sequence techniques that result in an approximate phase rotation gate, and establish the existence of an optimal length $$L_{\text {opt}}$$Lopt of the length L of the decomposition sequence. The existence of $$L_{\text {opt}}$$Lopt is due to the competition between the increase in gate accuracy with increasing L, but the decrease in gate performance due to the diffusive proliferation of gate errors due to faulty basis gates. We present an analytical formula for the gate fidelity as a function of L that is in satisfactory agreement with the results of our simulations and allows the determination of $$L_{\text {opt}}$$Lopt via the solution of a transcendental equation. Our result is universally applicable since gate sequence approximations also play an important role, e.g., in atomic and molecular physics and in nuclear magnetic resonance.

Measuring the Impact of Memory Errors on Application Performance

Memory reliability is a key factor in the design of warehouse-scale computers. Prior work has focused on the performance overheads of memory fault-tolerance schemes when errors do not occur at all, and when detected but uncorrectable errors occur, which result in machine downtime and loss of availability. We focus on a common third scenario, namely, situations when hard but correctable faults exist in memory; these may cause an “avalanche” of errors to occur on affected hardware. We expose how the hardware/software mechanisms for managing and reporting memory errors can cause severe performance degradation in systems suffering from hardware faults. We inject faults in DRAM on a real cloud server and quantify the single-machine performance degradation for both batch and interactive workloads. We observe that for SPEC CPU2006 benchmarks, memory errors can slow down average execution time by up to 2.5 $\times$ . For an interactive web-search workload, average query latency degrades by up to 2.3 $\times$ for a light traffic load, and up to an extreme 3746 $\times$ under peak load. Our analyses of the memory error-reporting stack reveals architecture, firmware, and software opportunities to improve performance consistency by mitigating the worst-case behavior on faulty hardware.

Estimation of Tree Stem Attributes Using Terrestrial Photogrammetry with a Camera Rig

We propose a novel photogrammetric method for field plot inventory, designed for simplicity and time efficiency on-site. A prototype multi-camera rig was used to acquire images from field plot centers in multiple directions. The acquisition time on-site was less than two minutes. From each view, a point cloud was generated using a novel, rig-based matching of detected SIFT keypoints. Stems were detected in the merged point cloud, and their positions and diameters were estimated. The method was evaluated on 25 hemi-boreal forest plots of a 10-m radius. Due to difficult lighting conditions and faulty hardware, imagery from only six field plots was processed. The method performed best on three plots with clearly visible stems with a 76% detection rate and 0% commission. Diameters could be estimated for 40% of the stems with an RMSE of 2.8–9.5 cm. The results are comparable to other camera-based methods evaluated in a similar manner. The results are inferior to TLS-based methods. However, our method is easily extended to multiple station image schemas, something that could significantly improve the results while retaining low commission errors and time on-site. Furthermore, with smaller hardware, we believe this could be a useful technique for measuring stem attributes in the forest.

SensoTrust: Trustworthy Domains in Wireless Sensor Networks

Wireless sensor networks (WSNs) based on wearable devices are being used in a growing variety of applications, many of them with strict privacy requirements: medical, surveillance, e-Health, and so forth. Since private data is being shared (physiological measures, medical records, etc.), implementing security mechanisms in these networks has become a major challenge. The objective of deploying a trustworthy domain is achieving a nonspecific security mechanism that can be used in a plethora of network topologies and with heterogeneous application requirements. Another very important challenge is resilience. In fact, if a stand-alone and self-configuring WSN is required, an autosetup mechanism is necessary in order to maintain an acceptable level of service in the face of security issues or faulty hardware. This paper presents SensoTrust, a novel security model for WSN based on the definition of trustworthy domains, which is adaptable to a wide range of applications and scenarios where services are published as a way to distribute the acquired data. Security domains can be deployed as an add-on service to merge with any service already deployed, obtaining a new secured service.

Analysis and Design of Finite Alphabet Iterative Decoders Robust to Faulty Hardware

This paper addresses the problem of designing LDPC decoders robust to transient errors introduced by a faulty hardware. We assume that the faulty hardware introduces errors during the message passing updates and we propose a general framework for the definition of the message update faulty functions. Within this framework, we define symmetry conditions for the faulty functions, and derive two simple error models used in the analysis. With this analysis, we propose a new interpretation of the functional Density Evolution threshold previously introduced, and show its limitations in case of highly unreliable hardware. However, we show that under restricted decoder noise conditions, the functional threshold can be used to predict the convergence behavior of FAIDs under faulty hardware. In particular, we reveal the existence of robust and non-robust FAIDs and propose a framework for the design of robust decoders. We finally illustrate robust and non-robust decoders behaviors of finite length codes using Monte Carlo simulations.

Frequency/voltage wide‐area measurements over transmission control protocol/internet protocol communication network for generator trip identification concerning missed data

Wide-area frequency/voltage measurements are used to observe and record changes in power system operating conditions. This study introduces an application of the frequency/voltage (F/V) wide-area measurements for identifying the generator trips. These measurements are received from the frequency disturbance recorders (FDRs). The FDRs transmit their measurements over the transmission control protocol/internet protocol-based communication network to the data concentrator server (DCS) hosted at Helwan University. The transmitted data from FDRs to the DCS using IP protocol cannot guarantee the quality of service while it provides the best effort delivery for data packets. Missed data at the DCS are expected as a result of number of factors including packet drop because of network congestion, buffer overflow at the source or destination, corrupted packets rejected in-transit or faulty networking hardware. The study introduces a new technique to compensate the missed data using principal component analysis in order to determine a specific signature and properties for each generator trip in the power system network. These signatures are compared with recorded signatures using minimum distance classification to determine a probable match. The real-time measurements collected at DCS showed that some data are missed because of the previously mentioned factors.

Adiabatic quantum programming: minor embedding with hard faults

Adiabatic quantum programming defines the time-dependent mapping of a quantum algorithm into an underlying hardware or logical fabric. An essential step is embedding problem-specific information into the quantum logical fabric. We present algorithms for embedding arbitrary instances of the adiabatic quantum optimization algorithm into a square lattice of specialized unit cells. These methods extend with fabric growth while scaling linearly in time and quadratically in footprint. We also provide methods for handling hard faults in the logical fabric without invoking approximations to the original problem and illustrate their versatility through numerical studies of embeddability versus fault rates in square lattices of complete bipartite unit cells. The studies show that these algorithms are more resilient to faulty fabrics than naive embedding approaches, a feature which should prove useful in benchmarking the adiabatic quantum optimization algorithm on existing faulty hardware.

Congestion Control in Packet Switched Wide Area Networks using a Feedback Model

In a complex world, where networking expands very rapidly, the network stability of flow of bandwidth played a vital role in transmitting packets. Hence, it was imperative to find solution to the problem of congestion especially in the follow of bandwidth stability. Congestion in computer networking is caused by so many factors. Some of the signs are packet loss, queuing delay resulting from overloading the buffer, faulty hardware devices, intermixing of old and new technologies and unstable flow of bandwidth resulting from positive feedback A negative feedback mechanism was added to the network. Feedback was developed using both control and queuing theory. The congested signalling was tested for stability using control theory. Kendall notation was used to determine both arrival and service rates with all the queue disciplines. Matlab was used to simulate the model. Bode plots and impulse responses were used to analyse the performance of the improved model. The results showed that flow of bandwidth was stable with increase in service rate of packets and decrease in the probability of routers not accepting packets. This shows that adopting dynamic explicit feedback model reduced congestion by minimal packet drops, balanced flow of bandwidth, converges to fairness and minimized amplitude of oscillation.

PHC-007 Deployment of Bar Code Medicines Administration to Control the Administration of Medicines in Geriatric Units

BackgroundOf the errors occurring in drug treatment, about 24% take place during the step of administration (Mission nationale d’expertise et d’audit hospitaliers (MeaH) 2008). Poon et al, showed in 2010...

Lacrosse Helmet Facemask Removal

Facemask removal (FMR) is required to access the airway of a catastrophically injured football or ice hockey athlete. However, the best method of caring for the helmeted lacrosse athlete with suspected catastrophic injury remains unclear. To evaluate the effects of sex and grip strength on the speed and ease of use of various FMR methods across different lacrosse helmet types. Cross-sectional study. Setting : Athletic training laboratory. Fourteen athletic trainers (7 men, 7 women). Removal method (cordless screwdriver [CSD], Face Mask Extractor 2 [FMX], pruner, Trainer's Angel [TA]), helmet type (Cascade CPX, Cascade Pro7, Riddell Revolution, Brine Triumph, Warrior Venom), and sex. Facemask removal time and participant-reported ease of use of the removal method (6-point Likert scale). We found a 2-way interaction for removal method and sex only for the ease-of-use scores (F3,246 = 4.67, P = .01). A main effect for removal method for time (F3,200 = 19.41, P < .001) and ease of use (F3,200 = 53.78, P < .001) was seen. The fastest times (32.32 ± 11.70 seconds) and highest ease-of-use scores (4.94 ± 0.30) were recorded for the CSD. We noted a main effect for helmet type only for time (F4,200 = 5.34, P < .001), with the fastest removal times (72.75 ± 74.67 seconds) recorded for the CPX. We discovered a main effect for sex only for time (F1,200 = 17.57, P < .001), with slower times recorded for women (115.51 ± 110.80 seconds) than men (75.71 ± 83.87 seconds). We found correlations between FMR time and grip strength only when using the FMX (r = -0.40, P = .001), pruner (r = -0.26, P = .04), and TA (r = -0.26, P = .047). Based on our results, FMR of lacrosse helmets should be attempted with a CSD. We recommend carrying a pruner as a backup cutting tool in case the CSD fails, practicing FMR regularly, and inspecting helmets for faulty hardware to reduce the chance of CSD failure.

ROSY

In the nanometer era, there has been a steady decline in the semiconductor chip manufacturing yield due to various contributing factors, such as wearout and defects due to complex processes. One of the strategies to alleviate this issue is to recover and use faulty hardware at gracefully degraded performance. A common, though naive, recovery strategy followed in the context of general purpose multicore systems is to disable the cores with faults and use only the fully functional cores. Such a coarse-granular solution is suboptimal, as the disabled cores would have many working modules which go un-utilized. The Resurrecting Operating SYstem (ROSY) presented in this paper is a step towards the development of an operating system that can work on faulty cores by adapting itself to hardware faults using software workarounds, and and utilize their working components. We consider many realistic fault models and present software workarounds for them. We have developed a framework which can be trivially plugged into a fullyfeatured x86 based OS kernel to demonstrate the feasibility of the proposed ideas. Performance evaluation using SPEC benchmarks and real-world applications show that the performance degradation of the depleted cores executing ROSY is on an average between 1.6x to 4x, depending on the fault type.

Automatic Identification of Vehicles with Faulty Automatic Vehicle Location and Control Units in London Buses' iBus System

The accuracy of vehicle location plays a pivotal role in several applications for bus network operations such as service control, warnings about low bridges, accurate prediction of bus arrival times, and traffic signal priority, as well as when historical operational data are used to measure network performance. In the context of iBus, an automatic vehicle location and control system deployed on all 8,400 buses operated by London Bus Services Limited (London Buses), tests demonstrated that the solution based on the Global Positioning System (GPS) provides location accuracy within 10 to 12 m 95% of the time; this timing is sufficient to support operational needs. To meet that level of location accuracy, the system must operate with a high degree of availability and accuracy on all vehicles. The challenge is to install, maintain, and repair vehicles so that they can operate at the required levels of performance under harsh operating conditions. Buses have many components—including the odometer, gyrocompass, aerials, WiFi, and power units—that can fail. This paper presents three approaches that London Buses uses to identify vehicles that have faulty hardware. One technique has also proved to be beneficial in testing new navigation software releases and in identifying design and parameterization problems that affect the quality of the navigation solution. The results will interest those involved with testing, maintenance, and repair of GPS-based vehicle fleets. These methods have helped ensure that London Buses can successfully observe 98% of all operated bus stop visits.