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29,922 Article Results

Application of resistance energy model to optimising electric power consumption of a belt conveyor system

10.11591/ijece.v10i3.pp2861-2873
Awingot Richard Akparibo , Erwin Normanyo
Driven by constantly increasing energy demands, prices, environmental impact caused by carbon dioxide emissions and global warming, efficient use of energy is gaining grounds in both public and private enterprises. The energy consumption of belt conveyors can be lowered using energy modelling techniques. In this research, a resistance-based mathematical energy model was utilised in the electrical energy efficiency optimisation of the troughed, inclined belt conveyor system taking into account indentation rolling resistance, bulk solid flexure resistance and secondary resistance as they together contribute 89% resistance to motion. An optimisation problem was formulated to optimise the electrical energy efficiency of the belt conveyor system and subsequently solved using the “fmincon” solver and interior point algorithm of the MATLAB optimisation toolbox. Analysis of simulation results showed that for the same given operating capacities, an average energy saving of about 7.42% and an annual total cost savings of Gh¢ 5, 852, 669.00 (USD 1, 083, 827.59) for a 2592-hour operation can be achieved when the used model and optimisation technique are employed over the constant speed operation.
Volume: 10
Issue: 3
Page: 2861-2873
Publish at: 2020-06-01

Analysis on techniques used to recognize and identifying the Human emotions

10.11591/ijece.v10i3.pp3307-3314
Praveen Kulkarni , Rajesh T. M.
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress of research in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify the proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on the various recognition techniques used to identify the complexity in recognizing the facial expression is presented. This work will also help researchers and scholars to ease out the problem in choosing the techniques used in the identification of the facial expression domain.
Volume: 10
Issue: 3
Page: 3307-3314
Publish at: 2020-06-01

Optimization of 16 nm DG-FinFET using L25 orthogonal array of taguchi statistical method

10.11591/ijeecs.v18.i3.pp1207-1214
Ameer F. Roslan , F. Salehuddin , A.S.M. Zain , K.E. Kaharudin , I. Ahmad
The impact of the optimization using Taguchi statistical method towards the electrical properties of a 16 nm double-gate FinFET (DG-FinFET) is investigated and analyzed. The inclusion of drive current (ION), leakage current (IOFF), and threshold voltage (VTH) as part of electrical properties presented in this paper will be determined by the amendment of six process parameters that comprises the polysilicon doping dose, polysilicon doping tilt, Source/Drain doping dose, Source/Drain doping tilt, VTH doping dose, VTH doping tilt, alongside the consideration of noise factor in gate oxidation temperature and polysilicon oxidation temperature. Silvaco TCAD software is utilized in this experiment with the employment of both ATHENA and ATLAS module to perform the respective device simulation and the electrical characterization of the device. The output responses obtained from the design is then succeeded by the implementation of Taguchi statistical method to facilitate the process parameter optimization as well as its design. The effectiveness of the process parameter is opted through the factor effect percentage on Signal-to-noise ratio with considerations towards ION and IOFF. The most dominant factor procured is the polysilicon doping tilt. The ION and IOFF obtained after the optimization are 1726.88 μA/μm and 503.41 pA/μm for which has met the predictions of International Technology Roadmap for Semiconductors (ITRS) 2013. 
Volume: 18
Issue: 3
Page: 1207-1214
Publish at: 2020-06-01

Confirmatory factor analysis sosiomathematics norm among junior high school student

10.11591/ijere.v9i2.20445
Sri Adi Widodo , T. Turmudi , Jarnawi Afgani Dahlan , Esti Harini , Fitria Sulistyowati
The purpose of this study was to confirm the factors that influence the sociomathematics norm. The method used in this research is the ex post facto. The subjects in this study were seventh-grade junior high school students in the city of Yogyakarta, Indonesia (264 students) taken by cluster random sampling. The instrument used was a sociomathematics norm observation sheet consisting of four factors are (1) the experience of mathematics, (2) the explanation of the mathematics, (3) mathematical differences, (4) mathematical communication. Data analysis using structural equation models with the Confirmatory Factors Analysis. The results showed that the modified path analysis obtained goodness of fit mostly in the fit category, so overall the sample covariance matrix is the same as the estimated covariance matrix.
Volume: 9
Issue: 2
Page: 448-455
Publish at: 2020-06-01

Tuning of different controlling techniques for magnetic suspending system using an improved bat algorithm

10.11591/ijece.v10i3.pp2402-2415
Nizar Hadi Abbas
In this paper, design of proportional- derivative (PD) controller, pseudo-derivative-feedback (PDF) controller and PDF with feedforward (PDFF) controller for magnetic suspending system have been presented. Tuning of the above controllers is achieved based on Bat algorithm (BA). BA is a recent bio-inspired optimization method for solving global optimization problems, which mimic the behavior of micro-bats. The weak point of the standard BA is the exploration ability due to directional echolocation and the difficulty in escaping from local optimum. The new improved BA enhances the convergence rate while obtaining optimal solution by introducing three adaptations namely modified frequency factor, adding inertia weight and modified local search. The feasibility of the proposed algorithm is examined by applied to several benchmark problems that are adopted from literature. The results of IBA are compared with the results collected from standard BA and the well-known particle swarm optimization (PSO) algorithm. The simulation results show that the IBA has a higher accuracy and searching speed than the approaches considered. Finally, the tuning of the three controlling schemes using the proposed algorithm, standard BA and PSO algorithms reveals that IBA has a higher performance compared with the other optimization algorithms
Volume: 10
Issue: 3
Page: 2402-2415
Publish at: 2020-06-01

The best parameters selection using pso algorithm to solving for ito system by new iterative technique

10.11591/ijeecs.v18.i3.pp1638-1645
Karam Adel Abed , Abeer Abdulkhaleq Ahmad
The main aim of this study is to obtain the best approximate solution for the nonlinear Ito system by applying the new iterative method, A new technique has been proposed that combines the new iterative method with the particle optimization algorithm. The most important distinctive of this work is the analysis of errors between the exact solution of the system and the approximate solutions, which showed us that these approximate solutions of the proposed technique in particular have high accuracy because they converge significantly from the exact solution.
Volume: 18
Issue: 3
Page: 1638-1645
Publish at: 2020-06-01

Binary operation based hard exudate detection and fuzzy based classification in diabetic retinal fundus images for real time diagnosis applications

10.11591/ijece.v10i3.pp2305-2312
Arun Pradeep , X Felix Joseph
Diabetic retinopathy (DR) is one of the most considerable reasons for visual impairment. The main objective of this paper is to automatically detect and recognize DR lesions like hard exudates, as it helps in diagnosing and screening of the disease. Here, binary operation based image processing for detecting lesions and fuzzy logic based extraction of hard exudates on diabetic retinal images are discused. In the initial stage, the binary operations are used to identify the exudates. Similarly, the RGB channel space of the DR image is used to create fuzzy sets and membership functions for extracting the exudates. The membership directives obtained from the fuzzy rule set are used to detect the grade of exudates. In order to evaluate the proposed approach, experiment tests are carriedout on various set of images and the results are verified. From the experiment results, the sensitivity obtained is 98.10%, specificity is 96.96% and accuracy is 98.2%.  These results suggest that the proposed method could be a diagnostic aid for ophthalmologists in the screening for DR.
Volume: 10
Issue: 3
Page: 2305-2312
Publish at: 2020-06-01

OPF for large scale power system using ant lion optimization: a case study of the Algerian electrical network

10.11591/ijai.v9.i2.pp252-260
Ramzi Kouadri , Ismail Musirin , Linda Slimani , Tarek Bouktir
This paper presents a study of the optimal power flow (OPF) for a large scale power system. A metaheuristic search method based on the Ant Lion Optimizer (ALO) algorithm is presented and has been confirmed in the real and larger scale Algerian 114-bus system for the OPF problem with and without static VAR compensator (SVC) devices. To get the highest impact of SVC devices in terms of improving the voltage profile, minimize the total generation cost and reduction of active power losses, the ALO algorithm was applied to determine the optimal allocation of SVC devices. The results obtained by the ALO method were compared with other methods in the literature such as DE, GA-ED-PS, QP, and MOALO, to see the efficiency of the proposed method. The proposed method has been tested on the Algerian 114-bus system with objective functions is the minimization of total generation cost (TGC) with two different vectors of variables control.
Volume: 9
Issue: 2
Page: 252-260
Publish at: 2020-06-01

Comprehensive investigation of coherent optical OFDM-RoF employing 16QAM external modulation for long-haul optical communication system

10.11591/ijece.v10i3.pp2607-2616
Anas Ali Hussien , Adnan Hussein Ali
Given the growing need for long haul transmission that requires a high rate of data, the orthogonal frequency division multiplexing scheme (OFDM), is regarded as a technique with high potentials for high-capacity optical networks. OFDM transmits over both optical and wireless channels, with the data distributed over a huge amount of the subcarrier, and the data is distributed over a huge number of subcarriers. OFDM achieves RF signal for a long-haul transmitting by utilizing Radio over Fiber (RoF) system, which is known to produce higher orthogonality of the OFDM modulated signal designed for the wireless network. RoF systems comprise of heterogeneous networks designed through the use of wireless and optical links. The aim of this paper is to carry out an investigation of the performance of the external modulation in RoF links, while analyzing the shortcomings caused by the various elements of the optical system. The Mach–Zehnder modulator (MZM) can be applied in external modulation, and exhibits a more robust performance when implemented with the OFDM modulation technique.
Volume: 10
Issue: 3
Page: 2607-2616
Publish at: 2020-06-01

Quranic verse finder: a tool for speech preparation using quranic verses

10.11591/ijeecs.v18.i3.pp1616-1623
Maslina Abdul Aziz , Irfan Fikri Azni , Wan Faezah Abbas , Mohd Izuan Hafez , Nur Nafhatun Md Shariff
This paper presents a mobile application called the Quranic Verse Finder. The main idea of this study is to develop a mobile application to help preachers in preparing their speech text. Based on preliminary investigation, the minimum time for a preacher to prepare a speech for a given topic is 3 hours. This process is very time consuming since the speech needs to refer to different source of reference such as the Quran and Hadith. The existing Quran search on the website or mobile application are from unknown source of reference. Therefore, to solve the problems mentioned above, this application offers an efficient method to search and identify any Quran verses for reference. With this application, the user can identify the juz number, the name of the Surah, which number of verses in the Surah and the meaning of the verses of a specific verse. The Quranic Verse Finder is different from other existing Quran Search applications due to its bilanguage feature. This application provides Malay and English translation. It also has other special features such as Bookmark that allows specific Quran verse to be saved for later reference. Moreover, due to the current trends, the Quranic Verse Finder allows user to share it using popular social media sites such as Facebook and Twitter.
Volume: 18
Issue: 3
Page: 1616-1623
Publish at: 2020-06-01

Enrich multi-channel P2P VoD streaming based on dynamic replication strategy

10.11591/ijaas.v9.i2.pp110-116
K.T. Meena Abarna , T. Suresh
Peer-to-Peer Video-on-Demand (VoD) is a favorable solution which compromises thousands of videos to millions of users with completeinteractive video watching stream. Most of the profitable P2P streaming groupsPPLive, PPStream and UUSee have announced a multi-channel P2P VoD system that approvals user to view extra one channel at a time. The present multiple channel P2P VoD system resonant a video at a low streaming rate due to the channel resource inequity and channel churn. In order to growth the streaming capacity, this paper highlights completely different effective helpers created resource balancing scheme that actively recognizes the supply-and-demand inequity in multiple channels. Moreover, peers in an extra channel help its unused bandwidth resources to peers in a shortage channel that minimizes the server bandwidth consumption. To provide a desired replication ratio for optimal caching, it develops a dynamic replication strategy that optimally tunes the number of replicas based on dynamic popularity in a distributed and dynamic routine. This work accurately forecasts the varying popularity over time using Auto-Regressive Integrated Moving Average (ARIMA) model, an effective time-series forecasting technique that supports dynamic environment. Experimental assessment displays that the offered dynamic replication strategy which should achieves high streaming capacity under reduced server workload when associated to existing replication algorithms.
Volume: 9
Issue: 2
Page: 110-116
Publish at: 2020-06-01

Classification of instagram fake users using supervised machine learning algorithms

10.11591/ijece.v10i3.pp2763-2772
Kristo Radion Purba , David Asirvatham , Raja Kumar Murugesan
On Instagram, the number of followers is a common success indicator. Hence, followers selling services become a huge part of the market. Influencers become bombarded with fake followers and this causes a business owner to pay more than they should for a brand endorsement. Identifying fake followers becomes important to determine the authenticity of an influencer. This research aims to identify fake users' behavior, and proposes supervised machine learning models to classify authentic and fake users. The dataset contains fake users bought from various sources, and authentic users. There are 17 features used, based on these sources: 6 metadata, 3 media info, 2 engagement, 2 media tags, 4 media similarity. Five machine learning algorithms will be tested. Three different approaches of classification are proposed, i.e. classification to 2-classes and 4-classes, and classification with metadata. Random forest algorithm produces the highest accuracy for the 2-classes (authentic, fake) and 4-classes (authentic, active fake user, inactive fake user, spammer) classification, with accuracy up to 91.76%. The result also shows that the five metadata variables, i.e. number of posts, followers, biography length, following, and link availability are the biggest predictors for the users class. Additionally, descriptive statistics results reveal noticeable differences between fake and authentic users.
Volume: 10
Issue: 3
Page: 2763-2772
Publish at: 2020-06-01

Blockchain outlook for deployment of IoT in distribution networks and smart homes

10.11591/ijece.v10i3.pp2787-2796
Heliasadat Hosseinian , Hossein Shahinzadeh , Gevork B. Gharehpetian , Zohreh Azani , Mahdi Shaneh
Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed.
Volume: 10
Issue: 3
Page: 2787-2796
Publish at: 2020-06-01

Efficient two-stage cryptography scheme for secure distributed data storage in cloud computing

10.11591/ijece.v10i3.pp3295-3306
Rabab F. Abdel-Kader , Samar H. El-sherif , Rawya Y. Rizk
Cloud computing environment requires secure access for data from the cloud server, small execution time, and low time complexity. Existing traditional cryptography algorithms are not suitable for cloud storage. In this paper, an efficient two-stage cryptography scheme is proposed to access and store data into cloud safely. It comprises both user authentication and encryption processes. First, a two-factor authentication scheme one-time password is proposed. It overcomes the weaknesses in the existing authentication schemes. The proposed authentication method does not require specific extra hardware or additional processing time to identity the user. Second, the plaintext is divided into two parts which are encrypted separately using a unique key for each. This division increases the security of the proposed scheme and in addition decreases the encryption time. The keys are generated using logistic chaos model theory. Chaos equation generates different values of keys which are very sensitive to initial condition and control parameter values entered by the user. This scheme achieves high-security level by introducing different security processes with different stages. The simulation results demonstrate that the proposed scheme reduces the size of the ciphertext and both encryption and decryption times than competing schemes without adding any complexity.
Volume: 10
Issue: 3
Page: 3295-3306
Publish at: 2020-06-01

A business model canvas for crowdfunding platform: case study of crowdfunding platforms in Malaysia

10.11591/ijeecs.v18.i3.pp1287-1294
Muhammad Hakim Bin Nadir , Syaripah Ruzaini Syed Aris , Norjansalika Janom , Fauziah Ahmad , Noor Habibah Arshad , Nor Shahniza Kamal Bashah
Crowdfunding allows entrepreneurs raise fund to help subsidizing their project. In other country, crowdfunding platform has become famous. In the contrary, it is yet to be trend in Malaysia. Financing using internet still irrelevant among Malaysian citizen. Without a proper guideline and strong crowdfunding platform based in Malaysia as a benchmark, it is hard to convince entrepreneurs and funders to consider crowdfunding as an option to fund a project. This research thus proposed business model canvas which can be applied by the crowdfunding platform organizations to manage their business and operation more efficiently. Case study method has been employed with two techniques of data collection: interview and document review. Two crowdfunding platforms based in Malaysia participated in the case study. The findings show that both crowdfunding platforms have fundamental business model elements that made of a solid foundation as a crowdfunding platform. These results offer insight into crowdfunding environment and how it links to another necessary part of business for it to function as a successful business. Nine building blocks fits well in the crowdfunding platform business model elements namely partner network, core competency, key resources, value proposition, customer relationship, distribution channel, customer segments, cost structure and revenue stream. Interestingly, the findings revealed another imperative element that should be part of the canvas: risk management.
Volume: 18
Issue: 3
Page: 1287-1294
Publish at: 2020-06-01
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