Energy-efficient management and highly reliable communication and transmission mechanisms are major issues in Underwater Wireless Sensor Networks (UWSN) due to the limited battery power of UWSN nodes within an harsh underwater environment. In this paper, we integrate the three main techniques that have been used for managing Transmission Power-based Sparsity-conscious Energy-Efficient Clustering (CTP-SEEC) in UWSNs. These incorporate the adaptive power control mechanism that converts to a suitable Transmission Power Level (TPL), and deploys collaboration mobile sinks or Autonomous Underwater Vehicles (AUVs) to gather information locally to achieve energy and data management efficiency (Security) in the WSN. The proposed protocol is rigorously evaluated through extensive simulations and is validated by comparing it with state-of-the-art UWSN protocols. The simulation results are based on the static environmental condition, which shows that the proposed protocol performs well in terms of network lifetime, packet delivery, and throughput.

Nonlinear effects in the optical transmission systems (OTSs) are considered as the major performance limiting factor to provide high transmission rates over ultra-long distances. As the demands for system capacity, transmission range and the number of users is increasing exponentially with the development of mobile broadband, new challenges are being faced by the backbone optical networks. Mainly, the refractive index related non-linearities (RIrNLs) need to be characterized to design an optimal OTS for error-free transmission with provision of wavelength division multiplexing (WDM) to support for multiple channels. This paper provides an estimation technique of RIrNLs for long-haul transmission and their treatment for different channel spacing and the number of channels in a WDM system operating frequency domain multiple in multiple out (FD-MIMO) equalizer based digital signal processing (DSP) receiver and microstrip Chebyshev low pass filter. The main focus of this work is to utilize the existing structure of OTS for RIrNLs treatment with a low cost solution. Thus, by varying the parameters of the third order dispersion parameters, group velocity dispersion parameters, phase modulation dispersion and nonlinear refractive index, the impact of RIrNLs is investigated in detail to enhance the transmission range and capacity of the current OTS. The proposed system is analyzed in terms of range of input power, fiber length and received power for OTS figure of merits including bit error rate (BER) and optical signal-to-noise ratio (OSNR). Using duo-binary modulation, the BER achieved in this work is <${10}^{-5}$ till 500 km range, for maximum number of 32 channels, with 100 Gbps aggregate data rate, which shows the feasibility and effectiveness of our proposed model.

This paper presents a new method of inter-turn short-circuit detection in cage induction motors. The method is based on experimental data recorded during load changes. Measured signals were analyzed using a genetic algorithm. This algorithm was next used in the diagnostics procedure. The correctness of fault detection was verified during experimental tests for various configurations of inter-turn short-circuits. The tests were run for several relevant diagnostic signals that contain symptoms of faults in an examined cage induction motor. The proposed algorithm of inter-turn short-circuit detection for various levels of winding damage and for various loads of the examined motor allows one to state the usefulness of this diagnostic method in normal industry conditions of motor exploitation.

This paper presents a method of inter-turn short-circuit identification in induction motors during load current variations based on a hybrid analytic approach that combines the genetic algorithm and simulated annealing. With this approach, the essence of the method relies on determining the reference matrices and calculating the distance between the reference matric values and the test matrix. As a whole, it is a novel approach to the process of identifying faults in induction motors. Moreover, applying a discrete optimization algorithm to search for alternative solutions makes it possible to obtain the true minimal values of the matrices in the identification process. The effectiveness of the applied method in the monitoring and identification processes of the inter-turn short-circuit in the early stage of its creation was confirmed in tests carried out for several significant state variables describing physical magnitudes of the selected induction motor model. The need for identification of a particular fault is related to a gradual increase in its magnitude in the process of the induction motor’s exploitation. The occurrence of short-circuits complicates the dynamic properties of the measured diagnostic signals of the system to a great extent.