This manuscript studies the structure and reliability of a new type of twinax pairs with dual longitudinal balanced shields and discusses their application in twinax cable assemblies. Twinax pairs with different diameters of high-speed conductors are fabricated for research purposes, and it is shown that the differential insertion loss of the twinax pairs decreases with the increase of the diameter of the high-speed conductors. Twinax pairs with 30 AWG high-speed conductors (30 AWG twinax pairs) are fabricated and tested under temperature conditioning and mechanical bending, and it is found that the 30 AWG twinax pairs exhibit excellent environmental and mechanical reliability. Further, OSFP cable assemblies are made from the 30 AWG twinax pairs fabricated in this work, and experimental results indicate that the twinax pairs are compatible with cable assembly plugs.
One of the core responsibilities of a data center is to provide stability and availability for online services. But the data center frequently faces infrastructure failures and unpredicted irregularities. In order to minimize hardware related failures, data centers must monitor the housing devices for 24 hours and 365 days. Due to various physical and software related failure causes, monitoring has always been a challenging task. A visual inspection by human operators is a reliable method which is widely used for checking device's status. However, growth of number of devices in data centers causes exponential cost growth for visual checks and it is almost impossible to detect anomaly occurrences in real time. Therefore, we have proposed an automatic visual monitoring system for data centers to substitute human visual monitoring. In this paper, we present the overview of the proposed system and show experimental results to evaluate LED detection performance of the system.
Predictive Maintenance in critical infrastructure is a fundamental tool for predicting a failure in advance and for avoiding catastrophic equipment damage that can be prevented and the time-consuming repair scheduling can be executed in time. Artificial Intelligence (AI) based predictive maintenance utilises intelligent data for accurate predictions in order to make immediate interventions on critical assets. In this paper, we propose a 5G-enabled Network Application (NetApp) for predictive maintenance in energy-related critical infrastructures. The proposed NetApp consists of several containerised components responsible for retrieving time-series operational data from a power plant and detecting potential outliers/anomalies regarding the operation of energy generators. For the anomaly detection process, an autoencoder is used. The evaluation results demonstrate the efficiency of the proposed NetApp.
In Cell-Free Massive Multiple-Input Multiple-Output (CF Massive MIMO) systems, channel estimation is one of the key technologies because important components such as linear precoding schemes (e.g., conjugate beamforming and zero-forcing) and transmission power control schemes are based on channel coefficients between access points and users. In this paper, we propose low-rank tensor completion-based channel database for large scale fading coefficients that include path loss and shadowing effects. In the proposed channel database, the large scale fading coefficients are formulated as a low-rank third-order tensor, which is referred to as channel tensor, and these coefficients are stored by means of factor matrices and a core tensor, which are estimated from partially observed coefficients using a low-rank tensor completion technique. The large scale fading coefficients for a newly generated user are obtained from a simple calculation with the core tensor and the factor matrices. The proposed channel database is scalable because the number of elements in the core tensor and the factor matrices can be reduced significantly as compared with the number of elements in the channel tensor. In this paper, we present a basic idea of the proposed channel database and evaluate its basic performance with simulation experiments.
Currently, the wireless train control system introduced by Japanese railway companies has a problem that the installation cost of ground equipment at the time of introduction and the maintenance cost after introduction are relatively high. In order to realize a train control system that reduces ground equipment as much as possible and suppresses both installation and maintenance costs after introduction, a train control system that uses a wireless ad hoc network consisting of wireless LAN terminals without using a base station is proposed. In this paper, a network of the proposed train control system is implemented on a network simulator and the results of performance evaluation of the network are described.
