CONTROLLING CHARGING TRIGGERS AND/OR LIMITS AT A RATING GROUP/SERVICE LEVEL FOR 5G CHARGING

Presented herein is technique that may provide a mobile network operator with the ability to control all charging triggers and/or limits at a Rating Group (RG) level or at a RG and Service Identity (ID) (RG+ServId) level. Hence, a mobile network operator can leverage the technique presented herein in order to better control bandwidth allocation to services within an RG, when desired

CONTROLLING CHANGE CONDITION (CC) TRIGGERS AT A GRANULARITY OF ONLINE VERSUS OFFLINE SERVICES

Presented herein are techniques to provide a mobile network operator with the control to enable triggers at a granularity of online versus offline services and, thus, provide for the ability to control reporting based on demand. The techniques presented herein can help to reduce signaling in that, if a requirement of trigger reporting is for online services, an operator can disable such reporting for offline services. Thus, techniques presented herein will help to make the migration from Fourth Generation (4G) to Fifth Generation (5G) easier for mobile network operators without involving large changes for the mobile network charging subsystem

A Comparative Study of Ensemble-based Forecasting Models for Stock Index Prediction

Stock prices as time series are, often, non-linear and non-stationary. This paper presents an ensemble forecasting model that integrates Empirical Mode Decomposition (EMD) and its variation Ensemble Empirical Mode Decomposition (EEMD) with Artificial Neural Network (ANN) for short-term forecasts of stock index. In first stage, the data is decomposed into a smaller set of Intrinsic Mode Functions (IMFs) and residuals using EMD and EEMD. In the next stage, IMFs and residue are taken as the inputs for the ANN model to train and predict the future stock price. The methodology was tested with weekly Nifty data for a period of 8 years. The results suggest that the ensemble forecast model using aggregation of the decomposed series performs better than traditional ANN and Support Vector Regression Models. Further, trading strategies based on EEMD-ANN models yielded better return on investments than Buy-and-Hold strategy

A Review on Multilingual Text to Speech Synthesis by Syllabifying the Words of Devanagari and Roman

Speech synthesis is process of spoken language as an input text and converted into speech waveforms. This paper describes the text to speech system for Devanagari scripted language and Roman Language. There are many earliest TTS systems are available but for Devanagari and Roman scripts are not available

Electrical and optical properties of dip coated Al-doped ZnO thin films : Effect of Al-concentration, starting solution and sample ageing

Undoped and Aluminum doped Zinc Oxide thin films were synthesized by dip coating technique. The electrical properties of the films were studied due to the Aluminum doping, starting solution aging and sample aging. The sheet resistance of ZnO:Al films was minimum at 2.5 at % whereas carrier concentration is maximum. Both undoped and aluminum doped Zinc Oxide thin films were found to be highly transparent lying in between 65 - 79 % in the wavelength range 367 nm to 1038 nm. The band gap of deposited films changed slightly from 3.22 eV to 3.27 eV