#### 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)

##### Conference Information
Name: 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Date: 2019-7-11 - 2019-7-12

#### Latest articles from this conference

Kangkan Bhakta, , Abdullah-Al Nahid,
Published: 1 July 2019
Abstract:
Motors are the driving force of our industrial world, as they power approximately 85% of all rotating machines. This revolutionary invention has been through radical changes before entering into the commercial industries, and their present forms are very reliable, to say the least. However, despite being so robust, induction motors are not entirely fault-proof and are more vulnerable to the internal faults than the external ones. Among the internal faults, certain types of bearing faults are more frequent, and their effects range from various performance-related issues to hard motor breakdowns. Fortunately, the recent advancements in the fields of Digital Signal Processing and Machine Learning allow us to detect these bearing faults and Figure out their origins, which in turn enables us to preserve their health and take measures against breakdowns. Through vibration analysis, this paper proposes a powerful method to detect these faults and differentiate among them based on the location of their occurrence within the bearing. Utilizing a well-known signal processing technique called Discrete Cosine Transform and Decision Tree classifier, this method is capable of classifying the motor bearing states with a 99.4% accuracy.
Abid Hassan Mitul, Munjure Mowla
Published: 1 July 2019
Abstract:
In spite of having great potential supremacy, device-to-device (D2D) communications are facing lack of implementation in large scale. Insufficient bandwidth with high interference in the micro wave ($\mu$Wave) band is the crucial complication behind it. Enabling D2D communications in millimeter wave (mmWave) band is considered as an alternative solution to these problems. However, line-of-sight (LOS) is a prerequisite for D2D devices to enable links in mmWave bands. In this paper, a distributed method is considered by which D2D devices can detect the existing LOS link for mmWave communication and further perform beam alignment. If there is scarcity of LOS link, this method permits the D2D devices to switch to $\mu$Wave band. Stochastic geometry is considered for system modeling and analysis of this method. Various network criteria such as reference distance, blockage density, frequency, gain of antenna, beam width, density of D2D transmitters, power for D2D and path loss exponents for both LOS and NLOS links are taken into account for analyzing D2D network SINR (signal-to-interference-plus-noise-ratio) coverage probability against SINR threshold. Simulation results reveal that this distributed method has the better coverage probability compared to independently implied mmWave and $\mu$Wave communication.
A. S. M. Badrudduza, M. Z. I. Sarkar, M. K. Kundu, D. K. Sarker
Published: 1 July 2019
Abstract:
A secure multicasting framework is considered in this paper to investigate the secrecy performance of a single-input multiple-output (SIMO) system in which a single antenna source transmits private message to multiple receivers in the presence of multiple eavesdroppers. All the receivers and eavesdroppers are equipped with multiple antennas. The perfect secrecy is obtained when evasedroppers can not be able to decode any transmitted information. Considering independent and identically distributed (i.i.d) Rician-K fading channels, the mathematical expressions for the probability of non-zero secrecy multicast capacity, the ergodic secrecy multicast capacity and the secure outage probability for multicasting are derived in closed-forms. Numerical results are provided to show the impact of the diversity provided by the multiple antennas at the receivers. In addition, the impact of Rician factor, K on the secrecy capacity and outage behaviour of the proposed multicasting scenario is also demonstrated. The performance analysis includes the Rayleigh fading scenario as a special case of Rician-K fading channel and focuses the performance comparison between Rician-K and Rayleigh fading channels.
Farhana Binte Sufi, Julio Daniel Dondo Gazzano, Fernando Rincon Calle, Juan Carlos Lopez Lopez
Published: 1 July 2019
Abstract:
Real-time video image processing requires video compression techniques. Efficient Motion Estimation (ME) and Motion Compensation (MC) algorithms and their successful hardware implementation are the key to video compression. Work on developing and implementing efficient ME and MC algorithms for multi-camera systems is ongoing. The low power consumption yet high speed of Heterogeneous Reconfigurable Devices such as Field Programmable Gate Arrays (FPGA) can be suitable for implementation of real-time optic flow computation using multi-camera systems. This paper focuses on a search into the current state-of-the-art for multi-camera motion tracking. It has been found the tracking systems mainly focused on people and vehicle tracking in both indoor and outdoor conditions, tracking under occlusion, tracking for surveillance, single and multi-view tracking, etc. The review search also found use of multi-camera tracking in the medical sector, such as multi-camera tracking systems for respiratory motion tracking. Research on this field has not been explored much and this holds possibilities for further work.
Munjure Mowla, Ashiqur Rahman, Iftekhar Ahmad
Published: 1 July 2019
Abstract:
In recent times, unmanned aerial vehicles (UAVs) create opportunities to support numerous civilian and military applications using its ad hoc network characteristics. However, several challenges still exist due to fast changing topology and limited communication range. Therefore, mobility models play a crucial role to enhance network performances by analyzing packet transmission and node movement. In this research, five mobility models, e.g., Boundless, Column, Manhattan Grid, Nomadic, and Random Way Point are presented for strategic comparative analysis in UAV networks. Moreover, the performance analysis of different network parameters (i.e., packet delivery ratio, normalized routing load, end to end delay, jitter, throughput, packet drop, and control overhead) are illustrated in case of AODV routing protocol for these models.
Published: 1 July 2019
Milon Uddin, Tanvir Hassan Mojumder, S.M. Nasif Shams
Published: 1 July 2019
Abstract:
Solar cell efficiency is subjected to some innate variables such as Open Circuit Voltage (Voc), Short Circuit Current (Isc), and Fill Factor (FF). Parasitical elements have effect on these variables. Resistive elements are known shunt resistances and series resistance. Shunt resistance in solar panel happens due to deficiencies. Volume shunts can occur due to impurities like metal particles defilement or aluminum particle defilement while making grid fingers are nearly inconceivable to remove except damaging experimental the solar cell. In many cases, frequently occurred edge shunts caused by cracks, spots can be eliminated with different available techniques. During the making of solar cell, edge isolation process can be applied on the solar cells that affects IV characteristics of solar cell, which is critical to the efficiency. In this research work, wet chemical etching method by combination of Hydrochloric acid, Nitric acid and Nitric acid (HNA solution). This combined solution is used for experimental procedure. In experimental results, it is observed that etching with the acid solution improves the IV characteristics of solar cells and hence it ameliorates the power curves. Efficiency before etching solar cells was 3.17% and 3.90%. After etching the solar cell efficiency increase up to 5.53% and 5.31% respectively.
Tanbin Islam Rohan, Awan- Ur Rahman, Abu Bakar Siddik, Monira Islam, Salah Uddin Yusuf
Published: 1 July 2019
Abstract:
Due to breast cancer, a number of women die every year. With an early diagnosis, breast cancer can be cured. Prognosis and early detection of cancer types have become a necessity in cancer research. Thus, a reliable and accurate system is required for the classification of benign and malignant tumor types of breast cancer. This paper explores a supervised machine learning model for classification of malignant and benign tumor types from Wisconsin Breast Cancer dataset retrieved from UCI machine learning repository. The dataset has 458 (65.50%) of benign data and 241 (34.50%) of malignant data, the total of 699 instances, 11 features and 10 attributes. Random Forest (RF) ensemble learning method is implemented with AdaBoost algorithm manifest improved metrics of performance in binary classification between tumor classes. For more accurate estimation of model prediction performance, 10-fold cross-validation is applied. The structure provided accuracy of 98.5714% along with sensitivity and specificity of 100% and 96.296% respectively in the testing phase. Matthews Correlation Coefficient is calculated 0.97 which validates of the structure being a pure binary classifier for this work. The proposed structure outperformed conventional RF classifier for classifying tumor types. Additionally, this model enhances the performance of conventional classifiers.
Abdullah Al Mamun, Kaushik Deb
Published: 1 July 2019
Abstract:
In Intelligent Transportation System (ITS) vehicle detection from the road image is very important for drivers and pedestrians awareness. Detection of vehicles from the road area is important to prevent the accident or collisions. This paper proposes a method for improving traffic control and management system for different condition of roads. Four basic steps based on appearance are presented in our proposed method. Initially, to segment the object, we use pitch color from the road image. In the next step, labeling and filtering is applied on foreground objects for getting the region of interest (ROI). Then, for extracting features we use Haar-like feature on ROI. Finally, test images are classified by support vector machine (SVM) classifier for recognizing the vehicle, which provides high accuracy with a very fast and reliable detection rate. Various road images were used with a variety of conditions to test proposed method and results are presented to prove it effectiveness. Moreover, it will satisfy the needs of ITS.
Shaon Sarker, Most. Farzana Khatun, Sheikh Rashel Al Ahmed,
Published: 1 July 2019
Abstract:
In this study, a comprehensive idea of designing multilayer antireflection coating (ARC) on the solar cell and minimization of the overall reflectance are provided. A theoretical model for the optimization of multilayer antireflection coating for solar cell has been presented on the basis of optical interference transfer-matrix theory. Also, PCID simulation has been carried out to understand the performance of silicon solar cell of antireflection coating. Reflectance calculation for various single, double and three ARCs on silicon substrate are presented. Optical reflection values were deduced with this transfer-matrix formulation via a personal computer using MATLAB program. The reflection loss has been calculated lower than 34.66%, 8.47%, and 5.71% using single, double, and three layers respectively with high refractive index materials. External quantum efficiencies (EQEs) of 65.34% and 81.81% were obtained for the single and double layers ARCs on silicon substrate. It was also observed that the thickness of the antireflection coating should be less about 200 nm. Therefore, it is suggested that the antireflection layers proposed in this study effective to improve the efficiency of solar cell.