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29,922 Article Results

Disease prediction in big data healthcare using extended convolutional neural network techniques

10.11591/ijaas.v9.i2.pp85-92
Asadi Srinivasulu , Asadi Pushpa
Diabetes Mellitus is one of the growing fatal diseases all over the world. It leads to complications that include heart disease, stroke, and nerve disease, kidney damage. So, Medical Professionals want a reliable prediction system to diagnose Diabetes. To predict the diabetes at earlier stage, different machine learning techniques are useful for examining the data from different sources and valuable knowledge is synopsized. So, mining the diabetes data in an efficient way is a crucial concern. In this project, a medical dataset has been accomplished to predict the diabetes. The R-Studio and Pypark software was employed as a statistical computing tool for diagnosing diabetes.  The PIMA Indian database was acquired from UCI repository will be used for analysis. The dataset was studied and analyzed to build an effective model that predicts and diagnoses the diabetes disease earlier.
Volume: 9
Issue: 2
Page: 85-92
Publish at: 2020-06-01

Inverse kinematic analysis of 3 DOF 3-PRS PM for machining on inclined prismatic surfaces

10.11591/ijra.v9i2.pp135-142
Hishantkumar Rashmikantbhai Patel , Yashavant Patel
Parallel Manipulators (PMs) are family members of modern manipulators based on the closed loop structural architecture. 3-PRS (prismatic, revolute, spherical) manipulator with 3DOF is investigated for its machining capability on prismatic surfaces as it possesses greater structural stiffness, higher pay load caring capacity, more precision compare to serial manipulators as well as less accumulation of errors at joints within a constrained workspace. The said manipulator can be utilized in various fields of application such as precise manufacturing, medical surgery, space technology and many more. In this paper, the primary focus on usage of parallel manipulator in industrial applications such as drilling and grooving on inclined work part surface. Inverse kinematic solutions are used for drilling, square and round profiles on inclined surface using parallel manipulator.
Volume: 9
Issue: 2
Page: 135-142
Publish at: 2020-06-01

A multi-color based features from facial images for automatic ethnicity identification model

10.11591/ijeecs.v18.i3.pp1383-1390
Mohd Zamri Osman , Mohd Aizaini Maarof , Mohd Foad Rohani , Nilam Nur Amir Sjarif , Nor Saradatul Akmar Zulkifli
Ethnicity identification for demographic information has been studied for soft biometric analysis, and it is essential for human identification and verification. Ethnicity identification remains popular and receives attention in a recent year especially in automatic demographic information. Unfortunately, ethnicity identification technique using color-based feature mostly failed to determine the ethnicity classes accurately due to low properties of features in color-based. Thus, this paper purposely analyses the accuracy of the color-based ethnicity identification model from various color spaces. The proposed model involved several phases such as skin color feature extraction, feature selection, and classification. In the feature extraction process, a dynamic skin color detection is adapted to extract the skin color information from the face candidate. The multi-color feature was formed from the descriptive statistical model. Feature selection technique applied to reduce the feature space dimensionality. Finally, the proposed ethnicity identification was tested using several classification algorithms. From the experimental result, we achieved a better result in multi-color feature compared to individual color space model under Random Forest algorithm.
Volume: 18
Issue: 3
Page: 1383-1390
Publish at: 2020-06-01

Assessment big data in Nigeria: Identification, generation and processing in the opinion of the experts

10.11591/ijere.v9i2.20339
Nkechi Patricia-Mary Esomonu , Martins Ndibem Esomonu , Lydia Ijeoma Eleje
As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and processed, and identifies the problems of generating and processing assessment big data in Nigeria. Through purposive sampling technique forty-five experts in education assessment and research were selected. The instruments for data collection were interview and documents. The data collected were analysed using descriptive statistics to answer the five research questions that guided the research. The results of the investigation showed that the internal and external examinations and assessments from secondary schools, and course work results in universities were identified by more than 95.5% of the experts interviewed as the major sources of assessment data in Nigeria. The major problem in generating and processing assessment big data from the experts’ opinions is low awareness on the need/advantages of assessment big data with the highest mean rating (4.29±0.76). Many data are not analysed and a lot of information are lost. Recommendation was made amongst others on the need for the stakeholders to create awareness on the importance of big data in the modern education system to improve learner’s performance.
Volume: 9
Issue: 2
Page: 345-351
Publish at: 2020-06-01

General concepts of multi-sensor data-fusion based SLAM

10.11591/ijra.v9i2.pp63-72
Jan Klečka , Karel Horák , Ondřej Boštík
This paper is approaching a problem of Simultaneous Localization and Mapping (SLAM) algorithms focused specifically on processing of data from a heterogeneous set of sensors concurrently. Sensors are considered to be different in a sense of measured physical quantity and so the problem of effective data-fusion is discussed. A special extension of the standard probabilistic approach to SLAM algorithms is presented. This extension is composed of two parts. Firstly is presented general perspective multiple-sensors based SLAM and then thee archetypical special cases are discuses. One archetype provisionally designated as "partially collective mapping" has been analyzed also in a practical perspective because it implies a promising options for implicit map-level data-fusion.
Volume: 9
Issue: 2
Page: 63-72
Publish at: 2020-06-01

Internet of things: security requirements, attacks and counter measures

10.11591/ijeecs.v18.i3.pp1520-1530
Maria Imdad , Deden Witarsyah Jacob , Hairulnizam Mahdin , Zirawani Baharum , Shazlyn Milleana Shaharudin , Mohd Sanusi Azmi
Internet of Things (IoT) is a network of connected and communicating nodes. Recent developments in IoT have led to advancements like smart home, industrial IoT and smart healthcare etc. This smart life did bring security challenges along with numerous benefits. Monitoring and control in IoT is done using smart phone and web browsers easily.  There are different attacks being launched on IoT layers on daily basis and to ensure system security there are seven basic security requirements which must be met. Here we have used these requirements for classification and subdivided them on the basis of attacks, followed by degree of their severity, affected system components and respective countermeasures. This work will not only give guidelines regarding detection and removal of attacks but will also highlight the impact of these attacks on system, which will be a decision point to safeguard  system from high impact attacks on priority basis.
Volume: 18
Issue: 3
Page: 1520-1530
Publish at: 2020-06-01

Control system design of duct cleaning robot capable of overcoming L and T-shaped ducts

10.11591/ijra.v9i2.pp123-134
Myeong In Seo , Woo Jin Jang , Junhwan Ha , Kyongtae Park , Dong Hwan Kim
This study introduces the control method of duct cleaning robot that enables real-time position tracking and self-driving over L-shaped and T-shaped duct sections. The developed robot has three legs and is designed to flexibly respond to duct sizes. The position of the robot inside the duct is identified using the UWB communication module and the location estimation algorithm. Although UWB communication has relatively large distance error within the metal, the positional error was reduced by introducing appropriate filters to estimate the robot position accurately. TCP/IP communication allows commands to be sent between the PC and the robot and to receive live images of the camera attached to the robot. Using Haar-like and classifiers, the robot can recognize the type of duct that is difficult to overcome, such as L-shaped and T-shaped duct, and it moves successfully inside the duct according to the corresponding moving algorithms.
Volume: 9
Issue: 2
Page: 123-134
Publish at: 2020-06-01

Conflicting opinions in connection with digital superintelligence

10.11591/ijai.v9.i2.pp336-348
Ahmed Al-Imam , Marek A. Motyka , Mariusz Z. Jędrzejko
In 1964, Nikolai Kardashev proposed the Kardashev scale, a system for measuring the extent of technological advancement of a civilization based on the magnitude of energy consumption. We are approaching an inevitable type-1 civilization, and artificial superintelligence superior to that of humans can concur with a higher-hierarchy Kardashev civilization. We aim to survey public opinions, specifically video gamers, worldwide compared to those in Poland, concerning artificial general intelligence and superintelligence. We implemented an amalgam of cross-sectional and longitudinal analyses of the database of literature and Google search engine. The geographic mapping of surface web users who are interested in artificial superintelligence revealed the top ten contributing countries: Iran, Mexico, Colombia, Brazil, India, Peru, South Africa, Romania, Switzerland, and Chile. Developing countries accounted for 54.84% of the total map. Polish people were less enthusiastic about artificial general intelligence and superintelligence compared with the rest of the world. Futuristic technological innovations imply an acceleration in artificial intelligence and superintelligence. This scenario can be pessimistic, as superintelligence can render human-based activities obsolete. However, integrating artificial intelligence with humans, via brain-computer interface technologies, can be protective. Nonetheless, legislation in connection with information technologies is mandatory to regulate upcoming digital knowledge and superintelligence.
Volume: 9
Issue: 2
Page: 336-348
Publish at: 2020-06-01

Validation of learning environment inventory for secondary school contexts

10.11591/ijere.v9i2.20444
Nurulhuda Md Hassan , Norliza Abdul Majid , Nur Khairunnasuha Abu Hassan
This study was conducted to describe the validation of learning environment inventory (LEI) for secondary school contexts. A survey method was used for data collection through the 20-item LEI. This study consists of two phases. In Phase 1, an exploratory factor analysis (EFA) was conducted using the Statistical Package for Social Sciences (SPSS 21) involving data collected from 150 students, which resulted in the extraction of four factors related to learning environment; (a) Learner-centered, (b) Knowledge-centered, (c) Assessment-centered, and (d) Community-centered. A confirmatory factor analysis (CFA) was carried out in Phase 2 with a new sample (N = 268) which resulted in strong model fit estimation. Such results confirmed the factor structure of Phase 1 and resulted in a final 12-item scale, which may be considered as an acceptable model.
Volume: 9
Issue: 2
Page: 379-384
Publish at: 2020-06-01

Features detection based blind handover using kullback leibler distance for 5G HetNets systems

10.11591/ijai.v9.i2.pp193-202
Adnane El Hanjri , Aawatif Hayar , Abdelkrim Haqiq
The Fifth Generation of Mobile Networks (5G) is changing the cellular network infrastructure paradigm, and Small Cells are a key piece of this shift. But the high number of Small Cells and their low coverage involve more Handovers to provide continuous connectivity, and the selection, quickly and at low energy cost, of the appropriate one in the vicinity of thousands is also a key problem. In this paper, we propose a new method, to have an efficient, blind and rapid handover just by analysing Received Signal probability density function instead of demodulating and analysing Received Signal itself as in classical handover. The proposed method exploits KL Distance, Akaike Information Criterion (AIC) and Akaike weights, in order to decide blindly the best handover and the best Base Station (BS) for each user
Volume: 9
Issue: 2
Page: 193-202
Publish at: 2020-06-01

Particle swarm optimization algorithms with selective differential evolution for AUV path planning

10.11591/ijra.v9i2.pp94-112
Hui Sheng Lim , Shuangshuang Fan , Christopher K.H. Chin , Shuhong Chai , Neil Bose
Particle swarm optimization (PSO)-based algorithms are suitable for path planning of the Autonomous Underwater Vehicle (AUV) due to their high computational efficiency. However, such algorithms may produce sub-optimal paths or require higher computational load to produce an optimal path. This paper proposed a new approach that improves the ability of PSO-based algorithms to search for the optimal path while maintaining a low computational requirement. By hybridizing with differential evolution (DE), the proposed algorithms carry out the DE operator selectively to improve the search ability. The algorithms were applied in an offline AUV path planner to generate a near-optimal path that safely guides the AUV through an environment with a priori known obstacles and time-invariant non-uniform currents. The algorithm performances were benchmarked against other algorithms in an offline path planner because if the proposed algorithms can provide better computational efficiency to demonstrate the minimum capability of a path planner, then they will outperform the tested algorithms in a realistic scenario. Through Monte Carlo simulations and Kruskal-Wallis test, SDEAPSO (selective DE-hybridized PSO with adaptive factor) and SDEQPSO (selective DE-hybridized Quantum-behaved PSO) were found to be capable of generating feasible AUV path with higher efficiency than other algorithms tested, as indicated by their lower computational requirement and excellent path quality.
Volume: 9
Issue: 2
Page: 94-112
Publish at: 2020-06-01

Welding station monitoring system using internet of thing (IOT)

10.11591/ijeecs.v18.i3.pp1319-1330
Ernie Mazuin Mohd Yusof , Mohd Ismail Yusof , Rafidah Ali , Izzat Hilmi Harjimi , Qasidah Kamarul Bahrin
In oil and gas industry, productivity is very important as the industry involves high cost and can be considered as a large-scale industry. Therefore, time and budget should be kept minimal to avoid loss to the oil and gas company. An example of lack of productivity in the industry is there are many complaints in the oil and gas industry that welders do not perform their job on time. Therefore, this project discussed about a system that can be used to monitor these welding stations. This system is important because it can help supervisors track the welding works from afar or anywhere using internet of things (IoT). To achieve that, a system must consist of hardware and software that are capable of connecting to the internet and monitor the welding works. In this project, the hardware chosen were Arduino Uno for data processing, ESP8266 to connect the microcontroller to the internet, voltage sensor to detect the voltage of the welding machine and a website to show the data taken. Other than that, this system was able to warn the welder of overvoltage of the welding machine. Thus, the system solved the problem of welders not performing their job on time. Supervisors were also able to monitor the job of welders to ensure maximum productivity. Based on the testing done on the system, the prototype was able to work as intended. The welding station monitoring system was able to detect welding usage, measure voltage values of welding and send the data to IoT for monitoring.
Volume: 18
Issue: 3
Page: 1319-1330
Publish at: 2020-06-01

Prediction prices of basrah light oil using artificial neural networks

10.11591/ijece.v10i3.pp2682-2689
Maysaa Abd Ulkareem Naser
The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial from oil prices collapse are both consumers and developed countries. Iraq economy is a one-sided economy which is completely depends on oil revenue to charge the economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decrease the development of economic activity. The study of forecast oil prices is considered among the most complex studies because of the different dynamic variables that affects the strategic goods. Moreover, the laws of economics controlling the prices of oil such as the supply and demand law. Some other variables that control the oil prices are the political conditions when these conditions contribute to the world production. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regards, for example, Artificial Neural Networks. In this study, an artificial neural network (FFNN) is adopted to extract the complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008–2018) in Iraq
Volume: 10
Issue: 3
Page: 2682-2689
Publish at: 2020-06-01

Decomposition of color wavelet with higher order statistical texture and convolutional neural network features set based classification of colorectal polyps from video endoscopy

10.11591/ijece.v10i3.pp2986-2996
A. S. M. Shafi , Mohammad Motiur Rahman
Gastrointestinal cancer is one of the leading causes of death across the world. The gastrointestinal polyps are considered as the precursors of developing this malignant cancer. In order to condense the probability of cancer, early detection and removal of colorectal polyps can be cogitated. The most used diagnostic modality for colorectal polyps is video endoscopy. But the accuracy of diagnosis mostly depends on doctors' experience that is crucial to detect polyps in many cases. Computer-aided polyp detection is promising to reduce the miss detection rate of the polyp and thus improve the accuracy of diagnosis results. The proposed method first detects polyp and non-polyp then illustrates an automatic polyp classification technique from endoscopic video through color wavelet with higher-order statistical texture feature and Convolutional Neural Network (CNN). Gray Level Run Length Matrix (GLRLM) is used for higher-order statistical texture features of different directions (Ɵ = 0o, 45o, 90o, 135o). The features are fed into a linear support vector machine (SVM) to train the classifier. The experimental result demonstrates that the proposed approach is auspicious and operative with residual network architecture, which triumphs the best performance of accuracy, sensitivity, and specificity of 98.83%, 97.87%, and 99.13% respectively for classification of colorectal polyps on standard public endoscopic video databases.
Volume: 10
Issue: 3
Page: 2986-2996
Publish at: 2020-06-01

Artificial fish swarm optimization algorithm for power system state estimation

10.11591/ijeecs.v18.i3.pp1130-1137
Surender Reddy Salkuti
In this paper, the power system state estimation (SE) problem is formulated as a general non-linear programming problem with equality constraints and boundary limits on the state variables. The proposed SE problem is solved using an evolutionary based Artificial Fish Swarm Optimization Algorithm (AFSOA). The AFSOA is a global search algorithm based on the characteristics of fish swarm and its autonomous model. The detailed algorithm with its flow chart is presented in this paper. To show the effectiveness of the proposed SE approach, six bus test system is considered. The obtained results are compared with other algorithms reported in the literature.
Volume: 18
Issue: 3
Page: 1130-1137
Publish at: 2020-06-01
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