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A Hybrid Model Based on Constraint OSELM, Adaptive Weighted SRC and KNN for Large-Scale Indoor Localization

150 150 MIMOS Berhad

Authors:

Hengyi Gan, Mohd Haris Md Khir, Gunawan Witjaksono Djaswadi and Nordin Ramli;

 

Abstract:

In this paper, a novel hybrid model based on the constraint online sequential extreme learningmachine (COSELM) classier with adaptive weighted sparse representation classication (WSRC) and knearest neighbor (KNN) is proposed for the WiFi-based indoor positioning system. It is referred to as A Fast-Accurate-Reliable Localization System (AFARLS). AFARLS exploits the speed advantage of COSELMto reduce the computational cost, and the accuracy advantage of WSRC to enhance the classicationperformance, by utilizing KNN as the adaptive sub-dictionary selection strategy. The understanding isthat the original extreme learning machine (ELM) is less robust against noise, while sparse representationclassication (SRC) and KNN suffer a high computational burden when using the over-complete dictionary.AFARLS unies their complementary strengths to resolve each other’s limitation. In large-scale multi-building and multi-oor environments, AFARLS estimates a location that considers the building, oor, andposition (longitude and latitude) in a hierarchical and sequential approach according to a discriminativecriterion to the COSELM output. If the classier result is unreliable, AFARLS uses KNN to achieve the bestrelevant sub-dictionary. The sub-dictionary is fed to WSRC to re-estimate the building and the oor, whilethe position is predicted by the ELM regressor. AFARLS has been veried on two publicly available datasets,theEU Zenodoand theUJIIndoorLoc. The experimental results demonstrate that AFARLS outperforms thestate-of-the-art algorithms on the former dataset, and it provides near state-of-the-art performance on thelatter dataset. When the size of the dataset increases remarkably, AFARLS shows that it can maintain itsreal-time high-accuracy performance

 

Source:

IEEE Access V7 2019

Towards Formulating Dynamic Model for Predicting Defects in System Testing using Metrics in Prior Phases

150 150 MIMOS Berhad

Authors:

Muhammad Dhiauddin Mohamed Suffian, Dayang Norhayati Abang Jawawi, Rd.Rohmat Saedudin and Mohd Adham Isa

 

Abstract:

Many studies have been carried out in formulating software defect prediction but it is of limited knowledge that those studies emphasized on predicting defects in system testing phase. This study specifically focuses on establishing a prediction model for system testing defects by exploiting metrics prior to system testing under V-model development. The initiative helps independent testing team to prevent as many defects as possible from escaping to production environment. The proposed model analyzes development-related and testing-related metrics collected from requirement, design and construction phases in determining which of those could significantly predict defects at the start of system testing. By applying statistical analysis to those metrics, this model able to formulate one generalized mathematical equation for predicting defects in system testing. The model applies 95% prediction interval to ensure the accuracy of the prediction.

 

Source:

International Journal of Integrated Engineering 2018, Vol. 10 No.6

High Voltage Graphene Nanowall Trench MOS Barrier Schottky Diode Characterization for High Temperature Applications

150 150 MIMOS Berhad

Authors:

Rahimah Mohd Saman, Sharaifah Kamariah Wan Sabli , Mohd Rofei Mat Hussin, Muhammad Hilmi Othman, Muhammad Aniq Shazni Mohammad Hani and Mohd Ismahadi Syono

 

Abstract:

Graphene’s superior electronic and thermal properties have gained extensive attentionfrom research and industrial sectors to study and develop the material for various applicationssuch as in sensors and diodes. In this paper, the characteristics and performance of carbon-basednanostructure applied on a Trench Metal Oxide Semiconductor MOS barrier Schottky (TMBS) diodewere investigated for high temperature application. The structure used for this study was siliconsubstrate with a trench and filled trench with gate oxide and polysilicon gate. A graphene nanowall(GNW) or carbon nanowall (CNW), as a barrier layer, was grown using the plasma enhanced chemicalvapor deposition (PECVD) method. The TMBS device was then tested to determine the leakagecurrent at 60 V under various temperature settings and compared against a conventional metal-basedTMBS device using TiSi2as a Schottky barrier layer. Current-voltage (I-V) measurement data wereanalyzed to obtain the Schottky barrier height, ideality factor, and series resistance (Rs) values. FromI-V measurement, leakage current measured at 60 V and at 423 K of the GNW-TMBS and TiSi2-TMBSdiodes were 0.0685 mA and above 10 mA, respectively, indicating that the GNW-TMBS diode has highoperating temperature advantages. The Schottky barrier height, ideality factor, and series resistancebased ondV/dln(J)vs.Jfor the GNW were calculated to be 0.703 eV, 1.64, and 35 ohm respectively.

 

Source:

Applied Sciences 2019; 9, 1587

Graphene field-effect transistor simulation with TCAD on top-gate dielectric influence

150 150 MIMOS Berhad

Authors:

Muhamad Amri Ismail, Khairil Mazwan Mohd Zaini, Mohd Ismahadi Syono

 

Abstract:

This paper presents the influence of top-gate dielectric material for graphene field-effect transistor(GFET) using TCAD simulation. Apart from silicon-based dielectric that is typically used for top-gate structure, other high-dielectric constant (high-k) dielectric materials namely aluminum oxide and hafnium oxide are also involved in the analysis deliberately to improve the electrical properties of the GFET. The unique GFET current-voltage characteristics against several top-gate dielectric thicknesses are also investigated to guide the wafer fabrication engineers during the process optimization stage. The improvement to critical electrical parameters of GFET in terms of higher saturation drain current and greater on/off current ratio shows that the use of high-k dielectric material with very thin oxide layer is absolutely necessary.

 

Source:

Telecommunication, Computing, Electronics and Control; Vol 17, No 4: August 2019

New Weight Function for Adapting Handover Margin Level over Contiguous Carrier Aggregation Deployment Scenarios in LTE-Advanced System

150 150 MIMOS Berhad

Authors:

Ibraheem Shayea, Mahamod Ismail, Rosdiadee Nordin, Mustafa Ergen, Norulhusna Ahmad, Nor Fadzilah Abdullah, Abdulraqeb Alhammadi, and Hafizal Mohamad

 

Abstract:

In this paper, an Adaptive Handover Margin algorithm based on Novel Weight Function (AHOM-NWF) is proposed through Carrier Aggregation operation in Long Term Evolu-tion—Advanced system. The AHOM-NWF algorithm automatically adjusts the Hando-ver Margin level based on three functions, f(SINR),f(TL)andf(v), which are evaluated as functions of Signal-to-Interference-plus-Noise-Ratio (SINR), Traffic Load (TL), and User’s velocity (v) respectively. The weight of each function is taken into account in order to estimate an accurate margin level. Furthermore, a mathematical model for estimating the weight of each function is formulated by a simple model. However, AHOM-NWF algorithm will contribute for the perspective of SINR improvement, cell edge spectral effi-ciency enhancement and outage probability reduction. Simulation results have shown that the AHOM-NWF algorithm enhances system performance more than the other considered algorithms from the literature by 24.4, 14.6 and 17.9%, as average gains over all the con-sidered algorithms in terms of SINR, cell edge spectral efficiency and outage probability reduction respectively.

 

Source:

Wireless Personal Communications, Volume 106 / 2019