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31,456 Article Results

Classification of mammograms based on features extraction techniques using support vector machine

10.11591/csit.v2i3.p121-131
Enas Mohammed Hussein Saeed , Hayder Adnan Saleh , Enam Azez Khalel
Now mammography can be defined as the most reliable method for early breast cancer detection. The main goal of this study is to design a classifier model to help radiologists to provide a second view to diagnose mammograms. In the proposed system medium filter and binary image with a global threshold have been applied for removing the noise and small artifacts in the pre-processing stage. Secondly, in the segmentation phase, a hybrid bounding box and region growing (HBBRG) algorithm are utilizing to remove pectoral muscles, and then a geometric method has been applied to cut the largest possible square that can be obtained from a mammogram which represents the ROI. In the features extraction phase three method was used to prepare texture features to be a suitable introduction to the classification process are first order (statistical features), local binary patterns (LBP), and gray-level co-occurrence matrix (GLCM), finally, SVM has been applied in two-level to classify mammogram images in the first level to normal or abnormal, and then the classification of abnormal once in the second level to the benign or malignant image. The system was tested on the MAIS the Mammogram image analysis Society (MIAS) database, in addition to the image from the Teaching Oncology Hospital, Medical City in Baghdad, where the results showed achieving an accuracy of 95.454% for the first level and 97.260% for the second level, also, the results of applying the proposed system to the MIAS database alone were achieving an accuracy of 93.105% for the first level and 94.59 for the second level.
Volume: 2
Issue: 3
Page: 121-131
Publish at: 2020-11-01

Performance evaluation of blockchains in the internet of things

10.11591/csit.v1i3.p93-97
Tanweer Alam
The idea of blockchains technology (BT) in the internet of things (IoT) is to allow the physical things to trust in the transactions held within the IoT network. The BT is a distributed, decentralized, publicly shared its digital ledger and secured technology to eternally record the transactions across the shared database. The BT in IoT can be called Trust Machine to eliminate the intermediates and enables the physical things to trust with each other. This research evaluates the performance of BT in IoT. The simulated results are tested and can be used in the sustainable development of the integration of BT and IoT.
Volume: 1
Issue: 3
Page: 93-97
Publish at: 2020-11-01

The effect of optimizers in fingerprint classification model utilizing deep learning

10.11591/ijeecs.v20.i2.pp1098-1102
Farah F. Alkhalid
Fingerprint is the most popular way to identify persons, it is assumed a unique identity, which enable us to return the record of specific person through his fingerprint, and could be useful in many applications; such as military applications, social applications, criminal applications… etc. In this paper, the study of a new model based deep learning is suggested. The focus is directed on how to enhance the training model with the increase of the testing accuracy by applying four scenarios and comparing among them. The effects of two dedicated optimizers are shown and their contrast enhancement is tested. The results prove that the testing accuracy is 85.61% for “Adadelta” optimizer, whereas for “Adam” optimizer, it is 91.73%.
Volume: 20
Issue: 2
Page: 1098-1102
Publish at: 2020-11-01

Comparison study of machine learning classifiers to detect anomalies

10.11591/ijece.v10i5.pp5445-5452
Nisha P Shetty , Jayashree Shetty , Rohil Narula , Kushagra Tandona
In this era of Internet ensuring the confidentiality, authentication and integrity of any resource exchanged over the net is the imperative. Presence of intrusion prevention techniques like strong password, firewalls etc. are not sufficient to monitor such voluminous network traffic as they can be breached easily. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database.Thus, the need for real-time detection of aberrations is observed. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database. Machine learning classifiers are implemented here to learn how the values of various fields like source bytes, destination bytes etc. in a network packet decides if the packet is compromised or not . Finally the accuracy of their detection is compared to choose the best suited classifier for this purpose. The outcome thus produced may be useful to offer real time detection while exchanging sensitive information such as credit card details.
Volume: 10
Issue: 5
Page: 5445-5452
Publish at: 2020-10-01

Object tracking using motion flow projection for pan-tilt configuration

10.11591/ijece.v10i5.pp4687-4694
Luma Issa Abdul-Kreem , Hussam K. Abdul-Ameer
We propose a new object tracking model for two degrees of freedom mechanism. Our model uses a reverse projection from a camera plane to a world plane. Here, the model takes advantage of optic flow technique by re-projecting the flow vectors from the image space into world space. A pan-tilt (PT) mounting system is used to verify the performance of our model and maintain the tracked object within a region of interest (ROI). This system contains two servo motors to enable a webcam rotating along PT axes. The PT rotation angles are estimated based on a rigid transformation of the the optic flow vectors in which an idealized translation matrix followed by two rotational matrices around PT axes are used. Our model was tested and evaluated using different objects with different motions. The results reveal that our model can keep the target object within a certain region in the camera view.
Volume: 10
Issue: 5
Page: 4687-4694
Publish at: 2020-10-01

A novel adaptive schema to facilitates playback switching technique for video delivery in dense LTE cellular heterogeneous network environments

10.11591/ijece.v10i5.pp5347-5367
Saleh Ali Alomari , Mowafaq Salem Alzboon , Mohammad Subhi Al-Batah , Belal Zaqaibeh
The services of the Video on Demand (VoD) are currently based on the developments of the technology of the digital video and the network’s high speed. The files of the video are retrieved from many viewers according to the permission, which is given by VoD services. The remote VoD servers conduct this access. A server permits the user to choose videos anywhere/anytime in order to enjoy a unified control of the video playback. In this paper, a novel adaptive method is produced in order to deliver various facilities of the VoD to all mobile nodes that are moving within several networks. This process is performed via mobility modules within the produced method since it applies a seamless playback technique for retrieving the facilities of the VoD through environments of heterogeneous networks. The main components comprise two servers, which are named as the GMF and the LMF. The performance of the simulation is tested for checking clients’ movements through different networks with different sizes and speeds, which are buffered in the storage. It is found to be proven from the results that the handoff latency has various types of rapidity. The method applies smooth connections and delivers various facilities of the VoD. Meantime, the mobile device transfers through different networks. This implies that the system transports video segments easily without encountering any notable effects.In the experimental analysis for the Slow movements mobile node handoff latency (8 Km/hour or 4 m/s) ,the mobile device’s speed reaches 4m/s, the delay time ranges from 1 to 1.2 seconds in the proposed system, while the MobiVoD system ranges from 1.1 to 1.5. In the proposed technique reaches 1.1026 seconds forming the required time of a mobile device that is switching from a single network to its adjacent one. while the handoff termination average in the MobiVoD reaches 1.3098 seconds. Medium movement mobile node handoff latency (21 Km/ hour or 8 m/s) The average handoff time for the proposed system reaches 1.1057 seconds where this implies that this technique can seamlessly provide several segments of a video segments regardless of any encountered problems. while the average handoff time for the MobiVoD reaches 1.53006623 seconds. Furthermore, Fast movement mobile node handoff latency (390 Km/ hour or 20 m/s). The average time latency of the proposed technique reaches 1.0964 seconds, while the MobiVoD System reaches to 1.668225 seconds.
Volume: 10
Issue: 5
Page: 5347-5367
Publish at: 2020-10-01

Power fuzzy adaptive control for wind turbine

10.11591/ijece.v10i5.pp5262-5273
Yacine Hocini , Ahmed Allali , Houari Merabet Boulouiha
In recent years, wind energy has become one of the most promising renewable energy sources. The doubly-fed induction generator (DFIG) is currently the most common type of generator used in wind farms. This paper describes an approach for the independent control of the active and reactive power of the variable-speed DFIG. This paper deals with the control of the active and reactive powers in a DFIG designed for a wind system. The simulation model including a 7 KW - DFIG driven by a wind turbine, a PWM inverter and the proposed control strategy are developed and implemented using Matlab Simulink.
Volume: 10
Issue: 5
Page: 5262-5273
Publish at: 2020-10-01

Improving color quality and luminous flux of white LED utilizing triple-layer remote phosphor structure

10.11591/ijece.v10i5.pp5168-5174
Nguyen Thi Phuong Loan , Nguyen Doan Quoc Anh
In this manuscript, we presented a research that enhance the performance of WLED using the multi-phosphor configuration. The phosphor layers in the research are separated from each other to achieved better luminous efficiency, however, it makes controlling color light quality more complex. Another issue is finding out the whether two layers of phosphor or three layers of phosphor is better in improving color quality. The research addressed this issue by analyzing the optical aspects of the respective WLEDs that employ these structure. The studied aspects are quality indicators such as luminous efficacy (LE), and color uniformity, color rendering index (CRI), color quality scale (CQS). The results of the experiments in this research, which come from the employment of WLEDs with 2 color temperatures 5600 K and 8500, suggest that WLED with three phosphor layers is better in CRI, CQS, LE. This type of phosphor structure also limits the color deviation significantly, thus, improves the color uniformity. This results is verifies with Mie theory, therefore, can be applied as reference or guideline for production of better WLEDs
Volume: 10
Issue: 5
Page: 5168-5174
Publish at: 2020-10-01

Framework for propagating stress control message using heartbeat based IoT remote monitoring analytics

10.11591/ijece.v10i5.pp4615-4622
Eisha Akanksha
Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study.
Volume: 10
Issue: 5
Page: 4615-4622
Publish at: 2020-10-01

Performance assessment of a 619kW photovoltaic power plant in the northeast of peninsular Malaysia

10.11591/ijeecs.v20.i1.pp9-15
M. Nirrmahl Raj , Jagadeesh Pasupuleti
Photovoltaic (PV) power plants are becoming widely implemented and in larger scale around the world. Understanding performance criteria is crucial in the benchmark of PV plants and ascertaining performance requirements during both design and operational stage of a PV plant. performance ratio (PR) and capacity factor (CF) are two generally accepted benchmarks for the assessment of a grid connected PV plant. However, within the South East Asia region, and especially within Malaysia, there is a lack of compilation and benchmark for the PR and CF values of existing and operational PV plants. This lack of data is disadvantageous for the designing and assessment of performance of any PV plants in the area. Thus, the focus of this study is to assess the PR and CF performance a 619kW PV plant in the Northeast of Peninsular Malaysia, with the ultimate goal of proposing a standard. From the continuous operation of the said PV plant for the duration of one year, the plant energy production has been obtained and is compared with the simulated energy generation model. Based on the comparison, the plant is determined to be operating with PR value of 0.77 and CF value of 12%. The plant is evaluated to be operating within benchmark values. These values not only verify the performance of the studied PV plant, they also present a form of comparison for future studies.
Volume: 20
Issue: 1
Page: 9-15
Publish at: 2020-10-01

An energy optimization with improved QOS approach for adaptive cloud resources

10.11591/ijece.v10i5.pp4881-4891
Danthuluri Sudha , Sanjay Chitnis
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Volume: 10
Issue: 5
Page: 4881-4891
Publish at: 2020-10-01

Development and testing of a thai website accessibility evaluation tool

10.11591/ijece.v10i5.pp4900-4909
Kewalin Angkananon , Mike Wald , Piyabud Ploadaksorn
This paper deals with the important problem that there is no help with the accessibility evaluations of Thailand’s web by developing and evaluating a new method and tool online, WebThai2Access, with experts, developers, and users with disabilities. This tool was evaluated by 30 developers, 30 hearing impaired people, 30 visually impaired people, and 30 elderly people. The developers evaluated the websites whereas experimental tasks were given to each disabled group based on the problems they had accessing web information. The developers found WebThai2Access very usable and the 15 test criteria were reliable for evaluating websites. The lower and upper 95% limits for confidence ratings of developers were minus or plus 10% for YouTube and Pantip websites and minus or plus 3% with the blind association website. The 95% lower and upper limits of confidence were minus or plus 5% for hearing impaired users, minus or plus 2% for elderly users and minus or plus 0% for visually impaired users. The results therefore showed WebThai2Access was reliable and accessible for developers whose evaluations reasonably well predicted website accessibility for users with disabilities.
Volume: 10
Issue: 5
Page: 4900-4909
Publish at: 2020-10-01

Modelling turn away intention of information technology professionals in Bangladesh: a partial least squares approach

10.11591/ijece.v10i5.pp4973-4981
Md. Shohel Arman , Rozina Akter , Imran Mahmud , T. Ramayah
Despite, Bangladesh produces many IT graduates each year but only one tenth of total graduates contribute in IT development sector. In order to keep the contribution to economy through IT development, it is crucial for IT industry to know the factors that influence turn away of IT graduates. In this paper, building upon role stress theory, we develop a research model to explore the influence of workplace exhaustion and threat of professional obsolescence (TPO). Data were gathered from 185 IT professionals from 15 different IT companies through survey questionnaire. The structural equation modelling technique was used to test the paths. The results suggests that strong influence of TPO on turn-away intentions. Result also suggests significant roles of work overload, family-career conflict and control over career and workplace exhaustion on turn away intention. This paper contributes to the body of work dedicated to helping us better understand the turn away behaviour from the workplace exhaustion and TPO perspectives. From the viewpoint of practice, this research sheds light on some of the challenges that the IT industry might face when making strategy and policy to control turn away from IT profession in Bangladesh
Volume: 10
Issue: 5
Page: 4973-4981
Publish at: 2020-10-01

Standalone photovoltaic array fed induction motor driven water pumping system

10.11591/ijece.v10i5.pp4534-4542
Atarsia Loubna , Toufouti Riad , Meziane Salima
Due to the absence of energy transmission lines connected to the water pumping sites in remote areas, problems related to the electrical power outages and the environmental degradation caused by fossil fuel. For this one of the most conceived solutions is the photovoltaic water pumping technology which has the advantage of being sustainable and respectful of the environment to supply water to rural areas. To ensure the need of water, especially for domestic use and small communities, in this article, the photovoltaic energy system for autonomous water pumping using the induction motor was presented, particularly adapted to the isolated regions. Pumping system consists of four photovoltaic (PV) panels, boost converter, inverter, induction motor, centrifugal pump and a storage tank. In this study, the output power of a PV solar cell is fully used by proposing the P&O algorithm, where it is used to follow a maximum power point tracking (MPPT) technique. The recommended system is designed, modeled and simulated on the MATLAB/Simulink platform. The efficiency of the proposed algorithm is observed with variable solar sunshine.
Volume: 10
Issue: 5
Page: 4534-4542
Publish at: 2020-10-01

Pre-trained classification of scalp conditions using image processing

10.11591/ijeecs.v20.i1.pp138-144
Shafaf Ibrahim , Zarith Azuren Noor Azmy , Nur Nabilah Abu Mangshor , Nurbaity Sabri , Ahmad Firdaus Ahmad Fadzil , Zaaba Ahmad
Scalp problems may occur due to the miscellaneous factor, which includes genetics, stress, abuse and hair products. The conventional technique for scalp and hair treatment involves high operational cost and complicated diagnosis. Besides, it is becoming progressively important for the payer to investigate the value of new treatment selection in the management of a specific scalp problem. As they are generally expensive and inconvenient, there is an increasing need for an affordable and convenient way of monitoring scalp conditions. Thus, this paper presents a study of pre-trained classification of scalp conditions using image processing techniques. Initially, the scalp image went through the pre-processing such as image enhancement and greyscale conversion. Next, three features of color, texture, and shape were extracted from each input image, and stored in a region of interest (ROI) table. The knowledge of the values of the pre-trained features is used as a reference in the classification process subsequently. A technique of support vector machine (SVM) is employed to classify the three types of scalp conditions which are alopecia areata (AA), dandruff and normal. A total of 120 images of the scalp conditions were tested. The classification of scalp conditions indicated a good performance of 85% accuracy. It is expected that the outcome of this study may automatically classify the scalp condition, and may assist the user on a selection of suitable treatment available.
Volume: 20
Issue: 1
Page: 138-144
Publish at: 2020-10-01
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