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Combining serial and parallel decoding for turbo codes

10.11591/ijeecs.v24.i2.pp896-903
Mohammed AlMahamdy , Naser Al-Falahy
Reducing the decoding latency of the turbo codes is important to real-time applications. Conventionally, the decoding of the turbo codes (TC) runs in serial fashion, which means only one of the constituent soft decoders runs at a time. Parallel decoding (PD) refers to running the soft decoders in parallel. Although it delivers the output faster (compared to the serial decoding (SD)), it affects the bit- and frame-error rates. This paper proposes a decoding procedure that combines both PD and SD. It bridges the two decoding modes to determine the best combination scheme to achieve the required level of performance at an acceptable decoding latency. Presented results show how this procedure can mitigate the performance degradation at a slight increase in the decoding latency.
Volume: 24
Issue: 2
Page: 896-903
Publish at: 2021-11-01

ZigBee based data collection in wireless sensor networks

10.11591/ijict.v10i3.pp212-224
Cuong V. Nguyen , Alberto E. Coboi , Nam V. Bach , Anh TN. Dang , Trang TH. Le , Huy P. Nguyen , Minh Tuan Nguyen
Wireless sensor networks (WSN), referring to groups of technologies wirelessly controlled, are widely used in many different fields, agriculture, medical, military, etc. These technologies are mainly used for monitoring physical or environmental conditions, such as temperatures, sound, pressure, and so on. In WSN fields, there are technologies as Wi-Fi, radio frequency (RF), Bluetooth, ZigBee, Z-Wave, and so on. Furthermore, there is one of this technology that offers more outstanding futures to provide more energy-saving and long distances of transmissions compared to other technologies, and that is Zigbee technology, and this had become for many applications, the first high-quality to use and consequently the most used in WSNs. In Zigbee aided WSNs, are included three main devices used to communicate data, that is a Zig-Bee coordinator (network coordinator), ZigBee router, and ZigBee end-devices. The data sensed is transmitted from sensor nodes through coordinators to a base-station (BS), this device (coordinator), collects the data, stores it in a memory, processes, and finally forward to the next suitable nodes or the BS. This research presents the concepts and discussions of Zigbee technologies used in WSNs. Utmost ZigBee communication technologies are revised and analyzed, as well as simulation results with different scenarios are addressed comprehensively. Proposals for advance applications in WSNs are presented. Suggestions for future developments are provided
Volume: 10
Issue: 3
Page: 212-224
Publish at: 2021-10-05

MATLAB based design and performance analysis of electronically commutated BLDC motor

10.11591/ijeecs.v24.i1.pp22-28
Issa Etier , Anci Manon Mary A. , Nithiyananthan Kannan
The main objective of this research work is to design the electronically communtated brushless direct current (BLDC) motor and analysis its performance in MATLAB environment. The use of BLDC engine is expanding daily, the performance analysis is progressively significant and the consumer loyalty is significant. In light of the ranking and requirements, the BLDC engine is planned. The BLDC motor is widely used in a variety of fields. Low ripple input supply and a suitable speed controller are needed to achieve desired motor output. The output of BLDC motors, such as torque, voltage, and speed response, is examined in this paper. The controller parameters have been fine-tuned to improve motor speed. It has been discovered that a three phase voltage source inverter (VSI) fed BLDC motor with a fractional-order proportional-integral-derivative (FOPID) controller provides superior BLDC motor response. The outcomes are broke down utilizing the MATLAB programming.
Volume: 24
Issue: 1
Page: 22-28
Publish at: 2021-10-01

Improvements in space radiation-tolerant FPGA implementation of land surface temperature-split window algorithm

10.11591/ijece.v11i5.pp3844-3854
Assaad El Makhloufi , Nisrine Chekroun , Noha Tagmouti , Samir El Adib , Naoufal Raissouni
The trend in satellite remote sensing assignments has continuously been concerning using hardware devices with more flexibility, smaller size, and higher computational power. Therefore, field programmable gate arrays (FPGA) technology is often used by the developers of the scientific community and equipment for carrying out different satellite remote sensing algorithms. This article explains hardware implementation of land surface temperature split window (LST-SW) algorithm based on the FPGA. To get a high-speed process and real-time application, VHSIC hardware description language (VHDL) was employed to design the LST-SW algorithm. The paper presents the benefits of the used Virtex-4QV of radiation tolerant series FPGA. The experimental results revealed that the suggested implementation of the algorithm using Virtex4QV achieved higher throughput of 435.392 Mbps, and faster processing time with value of 2.95 ms. Furthermore, a comparison between the proposed implementation and existing work demonstrated that the proposed implementation has better performance in terms of area utilization; 1.17% reduction in number of Slice used and 1.06% reduction in of LUTs. Moreover, the significant advantage of area utilization would be the none use of block RAMs comparing to existing work using three blocks RAMs. Finally, comparison results show improvements using the proposed implementation with rates of 2.28% higher frequency, 3.66 x higher throughput, and 1.19% faster processing time.
Volume: 11
Issue: 5
Page: 3844-3854
Publish at: 2021-10-01

ASR-FANET: An adaptive SDN-based routing framework for FANET

10.11591/ijece.v11i5.pp4403-4412
Alaa Taima Albu-slaih , Hayder Ayad Khudhair
Flying ad hoc network (FANET) is widely used in many military, commercial and civilian applications. Compared with mobile adhoc network (MANET) and vehicular ad hoc network (VANET), FANET holds unique characteristics such as high mobility, intermittent links and frequent topology changes, which cause a challenging task in the design of routing protocols. A novel adaptive software defined networking (SDN)-based routing framework for FANET called ASR-FANET is proposed in this article to solve the above challenges. The ASR-FANET framework is mainly composed of three important parts, which are the topology discovery mechanism, statistics gathering mechanism and route computation mechanism. In topology discovery mechanism, the periodic information about network topology is collected, including nodes and links. In statistics gathering mechanism, the status of the wireless network connection and flight statistics are collected. In route computation mechanism, the optimal path is calculated based on link costs. The performance of ASR-FANET framework is also has been evaluated by comprehensive simulations. The simulation results show that proposed framework is much better than other traditional protocols in packet delivery fraction, average end to end delay, normalized routing load, packet loss and throughput.
Volume: 11
Issue: 5
Page: 4403-4412
Publish at: 2021-10-01

Evolutionary approach to secure mobile telecommunication networks

10.11591/ijeecs.v24.i1.pp357-366
Abdelkader Ghazli , Adda Alipacha , Naima Hadj Said
A series of encryption algorithms called A5 is used to secure mobile telephone communications, producing a pseudo-random sequence that will be exclusive OR (XORed) with the data flowing in the air interface in order to secure them. These algorithms are essentially composed of shift registers with linear feedback, controlled generally by a function or with another register in order to favor the randomness character of the keystream generated. Evolutionary algorithms are bioinspired calculation methods, whose principle is inspired by the theory of evolution, which consists in evolving a set of solutions to a problem given in order to find better results. This paper presents an improvement of the A5/1 algorithm by an evolutionary approach based on the use of particle swarm optimization algorithm (PSO) in order to limit some weaknesses and drawbacks found in the conventional A5/1 version, which have been cryptanalysed and several attacks have been published such as time memory trade off attacks and guess and determine attacks. Our technique does not alter the A5/1's architecture, but it does help to improve its shifting system by an evolutionary approach, which guarantees the quality of the keystream generated and makes it more complex and more secure.
Volume: 24
Issue: 1
Page: 357-366
Publish at: 2021-10-01

Decision support system on quality assessment of the prospective civil servant’s education and training using fuzzy method

10.11591/ijeecs.v24.i1.pp519-529
Aris Susanto , Omar Wahid , Hazriani Hazriani , Yuyun Yuyun
This study aims to develop a decision support system using the fuzzy method in order to assess the quality of education and training of prospective civil servants and highlight possible improvement considerations. The assessment consists of six criterias, namely coaches, lecturers, preachers, mentors, examiners, and administrators. Based on the evaluation result of the quality level of each criterion, it is obtained that the top two criterion are examiners and preachers, followed by coaches, lecturers, advisors, and the lowest is organizer. In addition, the quality of the civil servant class III training is better than the class II civil servant training. It also shows that the value of the organizers criterion has different level of satisfactions. Overall, the quality of the training (according to the participants' opinion) was very good with a score of 92.50 for training class II and 95.20 for training class III. Furthermore, it is necessary to conduct research to determine the quality of the training each year by looking at the achievements of the participants. The >system testing obtained an accuracy of 100%, whichs implies that the system can be used to assess the quality of education and training appropriately.
Volume: 24
Issue: 1
Page: 519-529
Publish at: 2021-10-01

Artificial neural network technique for improving prediction of credit card default: A stacked sparse autoencoder approach

10.11591/ijece.v11i5.pp4392-4402
Sarah A. Ebiaredoh-Mienye , E. Esenogho , Theo G. Swart
Presently, the use of a credit card has become an integral part of contemporary banking and financial system. Predicting potential credit card defaulters or debtors is a crucial business opportunity for financial institutions. For now, some machine learning methods have been applied to achieve this task. However, with the dynamic and imbalanced nature of credit card default data, it is challenging for classical machine learning algorithms to proffer robust models with optimal performance. Research has shown that the performance of machine learning algorithms can be significantly improved when provided with optimal features. In this paper, we propose an unsupervised feature learning method to improve the performance of various classifiers using a stacked sparse autoencoder (SSAE). The SSAE was optimized to achieve improved performance. The proposed SSAE learned excellent feature representations that were used to train the classifiers. The performance of the proposed approach is compared with an instance where the classifiers were trained using the raw data. Also, a comparison is made with previous scholarly works, and the proposed approach showed superior performance over other methods.
Volume: 11
Issue: 5
Page: 4392-4402
Publish at: 2021-10-01

Ultra low bitrate retinal image compression using integer lifting scheme and subband encoder

10.11591/ijeecs.v24.i1.pp295-307
Yassine Habchi , Ameur Fethi Aimer , Mohammed Beladgham , Riyadh Bouddou
Recently, ophthalmic clinics have seen many complaints related to retinal diseases. The degree of clarity of the blood vessels (BV) in the eye can be an important indicator of some diseases affecting the retina such as diabetic retinopathy. To diagnose it, we need to intervene more than a medical team, especially in some difficult cases, through the exchange of medical images obtained by photography. This method has contributed significantly to the production of large data that can quickly saturate transmission, storage systems and increase processing time, so the need to compress images efficiently without modifying the content before transmission represents a major challenge. This paper provides an effective method for compressing color retinal images (CRI), which relies on the use of an integer lifting scheme (ILS) based on cohen daubechies-feaveau wavelet (CDFW9/7) and the set partitioning in hierarchical trees (SPIHT) to encode large coefficients. The obtained results demonstrate that the suggested method reduce algorithmic complexity, improve the retinal image quality and achieves high objective parameters values for ultra-low bitrate compared to the conventional methods.
Volume: 24
Issue: 1
Page: 295-307
Publish at: 2021-10-01

Active tremor control in human-like hand tremor using fuzzy logic

10.11591/ijeecs.v24.i1.pp108-115
Hafiz Bin Jamaludin , Azizan As'arry , R. Musab , Khairil Anas Md Rezali , Raja Mohd Kamil Bin Raja Ahmad , Mohd Zarhamdy Bin Md. Zain
Tremoris the vibration in sinusoidal orientation that is experienced regularly by a person with Parkinson’s disease (PD), which disturbs their daily activities. One solution that may be used to counter this tremor effect is by developing an active tremor control system in LabVIEW for linear voice coil actuator (LVCA), where the system uses proportional (P) controller and various types of fuzzy logic controller (FLC) as a hybrid controller to reduce tremor vibration. From this research, it can be concluded that the best controller for tremor reduction is the P+FLC 1st set of rules, compared to P+FLC 2nd set of rules, and P controller only, with the highest percentage of 88.39% of tremor reduction with the actual tremor vibration of PD patients as the reference result. The P+FLC 2nd set of rules has the highest percentage of tremor reduction with a value of 86.81%, whereas P controller only has the highest tremor reduction percentage of 67.10%. This percentage of tremor reduction is based on the power spectral density (PSD) values, in which it represents the intensity of the tremor vibration. This experimental study can be used as an initial step for researchers and engineers to design and develop an anti-tremor device in the future.
Volume: 24
Issue: 1
Page: 108-115
Publish at: 2021-10-01

Improved fingerprinting performance in indoor positioning by reducing duration of the training phase process

10.11591/ijeecs.v24.i1.pp236-244
Andika Muharam , Abdi Wahab , Mudrik Alaydrus
Wireless sensor network (WSN) can be used as a solution to find out the position of an object that cannot be reached by global positioning system (GPS), for example to find out the position of objects in a room known as Indoor Positioning. One method in indoor positioning that can be used is fingerprinting. Inside there are two main work phases, namely training and positioning. The training phase is the process of collecting received signal strength indication (RSSI) data levels from each sensor Node reference that will be used as a reference value for the positioning phase. The more sensor Nodes used, the longer the processing time needed in the training phase. This research focussed on the duration of the training phase, the implementation of which are used 4 sensor Nodes, namely Zigbee (IEEE 802.15.4 protocol) arranged according to mesh network topology, one as Node X (positioning target) and 3 as reference Nodes. There are two methods used in the training phase, namely fixed target parameter (FTP) and moving target parameter (MTP). MTP took 5 seconds faster than FTP in terms of the duration of RSSI data collection from each reference Node. 
Volume: 24
Issue: 1
Page: 236-244
Publish at: 2021-10-01

Integrated data aggregation with fault-tolerance and lifetime energy-aware adaptive routing in coffee plantations using WSNs

10.11591/ijeecs.v24.i1.pp376-385
Roshan Zameer Ahmed , Sravani K. , Shilpa S. Chaudhari , S. Sethu Selvi , S. L. Gangadharaiah
The pest namely coffee white stem borer (CWSB) has harmed the economic progress of many emerging countries as a result of arabica coffee’s agricultural products. The boring activity causes the stem to shrink, fade in color, and acquire translucent margins across the stem. The pest multiplier can be controlled by capturing the location with the utilization of a wireless sensor networks (WSNs) and blocking its exit point at the user end. In this work, we propose an integrated data aggregation with faulttolerance and lifetime energy-aware adaptive routing (IDALAR) approach to transfer the sensed pest location data. The efficient packet format and statistical models based routing between clusterheads (CHs) and base station (BS) is proposed considering the availability of resources such as message overhead, algorithmic complexity, residual energy, and control overhead are all used to calculate its performance.
Volume: 24
Issue: 1
Page: 376-385
Publish at: 2021-10-01

Development of ontology-based model to support learning process in LMS

10.11591/ijeecs.v24.i1.pp507-518
Hussein Ali Ahmed Ghanim , László Kovács
E-Learning is an important support mechanism for educational systems to increase the efficiency of the education process including students and teachers. The current e-learning systems typically lack the level of metacognitive awareness, adaptive tutoring, and time management skills and have not always met the expectations of the learners as required. In this study, we introduce a novel ontological model for the learning process in the e-learning domain. In the framework, we have built a domain ontology that represents knowledge of the learning, the outcome domain ontology covers the whole learning process. We focused on the learning process ontology model conceptualizing knowledge constructions, such as learning courses, and we present the created course and learning process ontology in detail. In this work, we considered three layers of learning process. The top layer defines a general framework of learning process, conceptual model layer, defines the framework of the actual process of the learning process and course ontology model contains the knowledge unit of the learning process. The prototype ontology is constructed in protégé and managed by Java web ontology language-application programming interface (OWL-API). As a result, our model can solve the problems of current e-tutor systems. Also, it can be used for different domain in e-tutor systems. It can reach the characteristics of standardization, reusability, flexibility, and open knowledge. By applying this model, we can avoid applying isolated databases. The constructed ontology can be used in the future to control adaptive intelligent e-tutor frameworks.
Volume: 24
Issue: 1
Page: 507-518
Publish at: 2021-10-01

Lifetime centric load balancing mechanism in wireless sensor network based IoT environment

10.11591/ijece.v11i5.pp4183-4193
Veerabadrappa Veerabadrappa , Booma Poolan Marikannan
Wireless sensor network (WSN) is a vital form of the underlying technology of the internet of things (IoT); WSN comprises several energy-constrained sensor nodes to monitor various physical parameters. Moreover, due to the energy constraint, load balancing plays a vital role considering the wireless sensor network as battery power. Although several clustering algorithms have been proposed for providing energy efficiency, there are chances of uneven load balancing and this causes the reduction in network lifetime as there exists inequality within the network. These scenarios occur due to the short lifetime of the cluster head. These cluster head (CH) are prime responsible for all the activity as it is also responsible for intra-cluster and inter-cluster communications. In this research work, a mechanism named lifetime centric load balancing mechanism (LCLBM) is developed that focuses on CH-selection, network design, and optimal CH distribution. Furthermore, under LCLBM, assistant cluster head (ACH) for balancing the load is developed. LCLBM is evaluated by considering the important metrics, such as energy consumption, communication overhead, number of failed nodes, and one-way delay. Further, evaluation is carried out by comparing with ES-Leach method, through the comparative analysis it is observed that the proposed model outperforms the existing model.
Volume: 11
Issue: 5
Page: 4183-4193
Publish at: 2021-10-01

Source side pre-ordering using recurrent neural networks for English-Myanmar machine translation

10.11591/ijece.v11i5.pp4513-4521
May Kyi Nyein , Khin Mar Soe
Word reordering has remained one of the challenging problems for machine translation when translating between language pairs with different word orders e.g. English and Myanmar. Without reordering between these languages, a source sentence may be translated directly with similar word order and translation can not be meaningful. Myanmar is a subject-objectverb (SOV) language and an effective reordering is essential for translation. In this paper, we applied a pre-ordering approach using recurrent neural networks to pre-order words of the source Myanmar sentence into target English’s word order. This neural pre-ordering model is automatically derived from parallel word-aligned data with syntactic and lexical features based on dependency parse trees of the source sentences. This can generate arbitrary permutations that may be non-local on the sentence and can be combined into English-Myanmar machine translation. We exploited the model to reorder English sentences into Myanmar-like word order as a preprocessing stage for machine translation, obtaining improvements quality comparable to baseline rule-based pre-ordering approach on asian language treebank (ALT) corpus.
Volume: 11
Issue: 5
Page: 4513-4521
Publish at: 2021-10-01
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