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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
ISSN : 25024752     EISSN : 25024760     DOI : -
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Articles 67 Documents
Search results for , issue "Vol 22, No 1: April 2021" : 67 Documents clear
Economic technology analysis of LTE advanced pro dual spectrum licensed and unlicensed access using discounted cash flow methods Setiyo Budiyanto; Erman Al Hakim; Fajar Rahayu
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp342-351

Abstract

Since implementing the long term evolution (LTE) technology, the surge in data service traffic has increased, causing an increase in demand spectrum, which has resulted in gaps in capacity requirements. Wireless service providers can respond to LTE technology updates. With LTE advanced pro technology that utilizes unlicensed spectrum technology can provide solutions to increase capacity and throughput. In this study, LTE advanced pro planning by capacity method to find the number of eNodeB and using the discounted cash flow method to analyze the feasibility of the costs to be invested in the implementation of the LTE. The results of the four simulated scenarios concluded that the number of eNodeB from the IV scenario with 20 MHz bandwidth at 1800 MHz frequency and 20 MHz bandwidth at 5 GHz frequency amounted to 23 sites, with a positive NPV value of $ 271,936.96, IRR of 14.91%, and for payback period occurred in the 3rd year. Thus the fourth scenario is feasible to be implemented.
Enhancing the feature-based 3D deformable face recognition using hybrid PCA-NN Cahyo Darujati; Supeno Mardi Susiki Nugroho; Deny Kurniawan; Mochamad Hariadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp215-221

Abstract

Facial recognition is one of the most important advancements in image processing. An important job is to build an automated framework with the same human capacity’s for recognizing face. The face is a complex 3D graphical model, and constructing a computational model is a challenging task. This paper aims at a facial detection technique focused on the coding and decoding of the facial feature object theory approach to data. One of the most natural and common principal component analysis (PCA) method. This approach transforms the face features into a minimal set of basic attributes, peculiarities, which are the critical components of the original learning image collection (or the training package). The proposed technique is a combination of the PCA system and the identification of components using the neural network (NN) feed-forward propagation method. This experiment proves that recognition of deformed 3D face is doable. By taking into account almost all forms of feature extraction and engineering, the NN yields a recognition score of 95%.
Geometric control of quadrotor UAVs using integral backstepping Ali Bouchaib; Rachid Taleb; Ahmed Massoum; Saad Mekhilef
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp53-61

Abstract

The traditional quadcopter control systems should deal with two common problems. Namely, the singularities related to the inverse kinematics and the ambiguity linked to the quaternion representation of the dynamic model. Moreover, the stability problem due to the system nonlinearity and high degree of coupling. This paper provides a solution to the two issues by employing a geometrical integral-backstepping control system. The integral terms were added to improve system ability to track desired trajectories. The high-level control laws are considered as a virtual control and transmitted to the low-level to track the high-level commands. The proposed control system along with the quadcopter dynamic model were expressed in the special Euclidean group SE(3). Finally, the control system robustness against mismatching parameters was studied while tracking various paths.
Mobility-prediction and energy optimization for multi-channel multi-interface ad hoc networks in the presence of location errors Hassan Faouzi; Mohammed Boutalline
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp315-325

Abstract

We present a mobility-prediction and energy optimization solution for multi-channel multi-interface (MCMI) ad hoc networks in the presence of location errors. This solution includes routing of the MCMI communication links that adapt to dynamic channel, traffic conditions, interference and mobility of nodes. We start first with implementing a novel cross-layer routing solution in order to share information between network and MAC layer, the benefit of this technique is to collect information about the channel quality and residual energy of the nodes and send them directly to the network layer. Next, we present a mobility-prediction model using Kalman filter to predict accurate locations and enhance routing performance, through estimating link duration and selecting reliable routes. The performance of proposed mechanism is measured using NS2.35 simulations with different scenarios and varying load in a network. Comparative analysis of simulation results shows better performance of our protocol (ME-MCMI AODV) in terms of reducing end-to-end delay, total dropped packets and increasing network lifetime and packet delivery ratio (PDR).
Improved Lagrangian relaxation generation decision-support in presence of electric vehicles Hossein Zeynal; Zuhaina Zakaria; Ahmad Kor
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp598-608

Abstract

Decision making strategies for resources available in macro/micro scales have long been a critical argument. Among existing methods to address such a mixed-binary optimization model, lagrangian relaxation (LR) found universal acceptance by many utilities, offering a fast and accurate answer. This paper aims at retrofitting the solution way of LR algorithm by dint of meta-heuristic cuckoo search algorithm (CSA). When integrating CSA into LR mechanism, a tighter duality gap is catered, representing more accurate feasible solution. The key performance of CSA exhibits a head start over other classical methods such as gradient search (GS) and newton raphson (NR) when dealt with the relative duality gap closure in LR procedure. Further, electric vehicles (EV) with its associated hard constraints are encompassed into model to imperiling the proposed CSA-LR if encountered with nonlinear fluctuation of duality gap. Simulation results show that the proposed CSA-LR model outperforms the solution quality with/without EV as compared with conventional NR-LR method.
Hybrid sliding PID controller for torsional vibrations mitigation in rotary drilling systems Chafiaa Mendil; Madjid Kidouche; Mohamed Zinelabidine Doghmane
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp146-158

Abstract

During the drilling process, the drilling system devices can be exposed to several types of phenomena incited by lateral, axial, and torsional vibrations. The latter can lead to severe damages if they are not efficiently controlled and quickly mitigated. This research work is focused on the torsional vibrations, which are stimulated by the nonlinear dynamical interaction between the geological rocks and the drill bit. Wherein, a model with three degrees of freedom was designed to demonstrate the severity of the stick-slip phenomenon as consequence of torsional vibrations. The main objective of this study was to design a robust controller based on hybridizing a conventional PID controller with sliding mode approach in order to mitigate rapidly the torsional vibrations. Moreover, a comparative study between PI, PID and sliding mode controllers allowed us to emphasize the effectiveness of the new hybrid controller and improve the drilling system performances. Furthermore, the chattering phenomenon in the sliding surface was overcome by using the saturation function rather than the sign function. The obtained results proved the usefulness of the proposed controller in suppressing the stick-slip phenomenon for smart industrial drilling systems.
e-SimNet: a visual similar product recommender system for E-commerce Ssvr Kumar Addagarla; Anthoniraj Amalanathan
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp563-570

Abstract

Visual similarity recommendations have an immense role in E-commerce portals. Fetching the appropriate similar products and suggesting to the buyers based on the product image's visual features is complex. Here in our research, we presented an efficient E-commerce similar product network model (e-SimNet) for visually similar recommendations. To achieve our objective, we have performed image feature extraction and generating embeddings using deep learning techniques and built an Index tree using the approximate nearest neighbor oh yeah (ANNOY) algorithm. Further, we have fetches top-N the near similar items using distance measure. We have benchmarked our model in terms of accuracy, error rate, and results show that better than other state-of-the-art approaches with 96.22% of accuracy.

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