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ARPN Journal of Engineering and Applied Sciences                               April 2022  |  Vol. 17  No. 8
   
Title: Effect of intensity of light and distance for decolonization in direct red wastewater by photo Fenton oxidation
Author (s): Hameed R. Dawood Alamery and Ali A. Hassan
Abstract:

In this paper, the decolonization of direct red wastewater, by photo-Fenton oxidation designed aimed at decontamination of industrial wastewater. The experimentations be situated designed by a response surface method comprising the effect of the irradiation time (30-120 min.), hydrogen peroxide (20-100 ppm), ferrous sulphate (4-20 ppm), Temperature (25-60 C) and pH (3-9). Then and at the optimum values of these conditions (120 min, 60 ppm of H2O2, 13 ppm of ferrous sulphate, temperature 25 C and pH 6) was 98.5% organic removal from simulated wastewater, and studied belongings of Intensity and Distance from UV Light on simulated wastewater. The results show that the increase in the Intensity of UV light increases the removal and the proximity of the pollutant to the UV light increases the removal.

   

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Title: Image classifier differentiating tumour from healthy MRI scans using Convolutional Neural Networks
Author (s): Jessica S. Velasco, August C. Thio-Ac, Gilbert B. Hollman, Benedicto N. Fortalezaa, Felix Kenjie F. Thio-Ac, Jonard Bryan S. Cabanding, Jetlee E. Dumandan, Lean Karlo S. Tolentino and Roel M. Mendoza
Abstract:

This study was created using a simple algorithm that may be implemented on MRI scan machines to aid medical professionals in making a more accurate decision by having a second opinion. The system is inspired on a smartphone-based skin disease classifier which was implemented with multiple techniques of data augmentation. It is also trained on multiple pre-trained and untrained algorithms for machine learning application. The raw data of MRI has a dimension of 50 x 50 and in colored form. When worked on raw data it did not yield great results having only an 80% accuracy and a 50% validation accuracy after. We implemented data augmentation techniques to increase the accuracy and to implement a reasonable comparison among the different CNN models. The data was resized and recolored to a monochrome to have the same dimensions and tone to have a better prediction on the data. These images were then trained on a well-known pre-trained Convolutional Neural network (CNN) and a small model comprising of 3 layers for control independent variable. At first, we only got 90% as the best validation accuracy that belongs to the untrained 3-layer algorithm. However, decreasing learning rate to 0.0001 increased our best validation accuracy from 90% to 95% that validation accuracy belonging to VGG 16 and 19.

   

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Title: Synthesis by a two-step method of the thin film semiconductor CsPbBr3
Author (s): T. Muqoz, G. Gordillo, M. A. Reinoso, J. I. Clavijo Penagos and O. G. Torres
Abstract:

Thin films of PbBr2 were synthesized on glass substrate by Physical Vapor Deposition (PVD) and thin films of CsPbBr3 were synthesized by Dip Coating Method of a film of PbBr2 in a solution of CsBr in methanol. The crystalline system corresponding to CsPbBr3 was identified crystallographically by X-ray diffraction and the desired stoichiometry was found from a three-dip test with a film anneal time at 100 0 C for a time of 20 minutes. The morphology of the PbBr2 and CsPbBr3 films was studied by scanning electron microscopy (SEM), the structural change and the variation in grain size were analyzed as a function of the annealing temperature and the formation of CsPbBr3, an increase was observed in the grain size after the annealing of the PbBr2 film and subsequently in the formation of CsPbBr3. Finally, the optical properties of the material were evaluated by optical reflectance measurements and an optical band gap of 2.31 eV and absorption coefficients of 6x104 cm-1 were obtained for the fundamental absorption and 5x104 cm-1 for the near ultraviolet. The band gap of the material was also determined using the band structure diagram obtained from Heyd-Scuseria-Ernzerhof (HSE) density functionalities and a value of 2.30 eV was obtained.

   

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Title: Biodiesel production from castor oil: Mixing optimization during transesterification
Author (s): Hisham E. Hassan, Yaser M. Asal, Ahmad M. Mohammad and Islam M. Al-Akraa
Abstract:

With the growing warning for accrediting the traditional combustion of fossil fuels for energy production, not only for their limited supply but also for their environmental risks (air pollution, climate change, . etc), it became necessary to realize alternative greener and abundant sources for energy. Instead, the interest to sustain biodiesel for the energy production has recently been renewed as a replacement for petroleum diesel in conventional diesel engines. This was due to its renewable nature, low toxicity, high degradability and unique physical properties (high flash points & lubrication). Castor oil, in particular, appeared promising for biodiesel production with extremely low cloud and pour points; making it suitable for tropical climates. Blending petroleum diesel with castor oil biodiesel has been proven efficient for enhancing both the environmental effect and the kinematic flow properties of the mineral fuel. Nonetheless, because of the current market price of conventional diesel, the blended product appeared cost-ineffective; steering research to tune the use of castor oil biodiesel alone. In this study, a simple method is recommended to produce biodiesel from castor oil by a transesterification process. The effect of mixing time of oil and alcohol is optimized with a thorough analysis to optimize the best condition for the biodiesel production.

   

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Title: Kinematics and singularity analysis of 3-PRS parallel kinematic mechanism
Author (s): Liaquat Ali Khan, Muhammad Faizan Shah, Muhammad Ramiz and Kamran Nazir
Abstract:

Parallel manipulators have gained a lot of attraction from the research community. They come in various configurations. This paper mainly addresses the issues regarding kinematics and singularity analysis of prismatic revolute and spherical (3-PRS) parallel mechanism. A comprehensive and simple approach is presented to estimate the detailed kinematics, and singularity model of 3-PRS mechanism. For kinematic analysis first CAD model of the proposed 3 PRS mechanism is made using Autodesk inventor professional software. Starting with the inverse kinematics an analytical model is derived. For forward kinematics both analytical and numerical analysis are performed to ensure the efficiency of the presented methodology and results are compared with the presented CAD model which are closely related to each other. The singularity analysis is also done and presented in this paper.

   

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Title: YAW movement identification of an unmanned aerial vehicle using a frequency domain method
Author (s): Faiber Robayo Betancourt, Fredy H. Martmnez S. and Daniel Suesczn-Dmaz
Abstract:

In this work, a frequency domain method based on the Transfer Function Analyzer (TFA) technique to identify the yaw movement of an unmanned aerial vehicle (UAV) helicopter was presented. This study's contribution was to use a variable sample time instead of the traditional fixed sample time. The Transfer Function Analyzer identification was compared with an identification method using CIFER (Comprehensive Identification from Frequency Responses), a commercially available tool designed for aircraft identification. The two results were quite close for the two experiments.

   

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Title: Energy efficient cluster based approach for load balancing in WSN
Author (s): Hyder Ali Hingoliwala and Gandharba Swain
Abstract:

During the last decade there has been a rapid growth of wireless sensor technology. Wireless sensor networks (WSNs) are widely deployed for a variety of applications. In WSN the sensor nodes are operating with limited battery power, so consumption of energy should be done very carefully to make the network long lasting. Therefore, efficient power utilization is a major concern for the researchers. This paper proposes an extended energy efficient clustering algorithm (EEECA) for load balancing in WSNs. It works in three phases, (i) initialization phase, (ii) setup phase, and (iii) transmission phase. In initialization phase, the network is splitted into number of clusters and for each cluster a cluster head (CH) is selected based on residual energy and mean distance. During setup phase, the base station (BS) sends routing information to all the sensor nodes informing about their CH. A sensor node knows the distance from any other node within the cluster and computes its transmission power. The base station allocates time division multiple access (TDMA) to the cluster nodes. In transmission phase, the sensor nodes in each cluster transmit data to cluster head as per the allocation of transmission time. The CH aggregates all the data and compresses it and sends it to the BS. The algorithm has been simulated using Java and Jung Simulator. Its performance has been estimated by the parameters like throughput, energy consumption, residual energy, and network energy. These results are also compared with the existing algorithms. It is found after analysis of the results that proposed algorithm shows better results in all the above parameters.

   

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Title: Economical comparative study for lighting systems using energy consumption factor
Author (s): A. E. H. Gaballah, E. M. El-Moghazy and Alaaeldin Abdelmageed
Abstract:

The paper presents a comparative study of some commercial LED lamps for indoor lighting using the energy consumption factor. This article focuses on providing a suitable level of illumination utilizing LED lighting bulbs of various wattages to illuminate a 50-square-meter area, as well as their energy consumption. The CIE publication (S008/E-2001) has recommended an illumination level of 500 lux for indoor workplaces such as offices. The study has included three sets of commercial LED lamps purchased from three companies designated as E, T, and V. Each set included three duplicated lamps with different wattages such as 9, 12, and 15 Watt for repeatability. Thus, a summary of the measured photometric and electric parameters for these lamps was measured to assess their energy consumption.

   

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Title: Identification of diseases and lesions in the coffee leaf using a convolutional model
Author (s): Fredy H. Martmnez S., Holman Montiel A. and Edwar Jacinto G.
Abstract:

The planting and commercialization of coffee is an important source of economic resources and commercial dynamizer for many developing countries, particularly with economies that are strongly dependent on agricultural production, as is the case of Colombia. Coffee is the most important export product of the country and enjoys a high reputation for its quality and flavor. Although the country has done a lot of research to develop the sector, investment in technology is very low, and most of its cultivation for export (of the highest quality) is done by small coffee families without a high degree of technology, and without major resources to access it. The quality of the coffee bean is strongly sensitive to various diseases induced by environmental conditions, fungi, bacteria, and insects, which directly and strongly affects the economic income of the entire production chain and the country. In many cases the diseases are rapidly transmitted, causing great economic losses. A quick and reliable diagnosis would have an immediate effect on reducing losses, which is why the development of a low-cost embedded system capable of making reliable diagnoses in the hands of peasant farmers is proposed. In this article, we propose the development of a software model capable of identifying in real-time the possible disease of a plant from an image of a leaf. For this, we use a DenseNet convolutional neural network trained with 1250 images corresponding to five categories that include the most important diseases of the plant. Laboratory tests show that the proposed model is capable of operating on a low-cost embedded system with a high-performance rate by correctly categorizing the plant's leaves against an unknown set.

   

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Title: A review of the significance of feed water temperature on the health of a steam boiler
Author (s): Davis F., Okwabi R. and Oman E. K.
Abstract:

This paper presents a review of the significance of feed water temperature on the health of the steam boiler. Feed water temperature was identified as one of the main parameters that influence the health of the steam boiler due to its strong correlation to performance. This review is influenced by the fact that considerable knowledge abounds in research work about the effect of feed water temperature on the health of steam boilers but they are scattered. In this review an attempt is made to assemble the information in a compact manner to call attention to the importance of feed water temperature in relation to the health of steam boilers to assist in boiler design and maintenance by engineers and technicians. The effect of other factors, examples; quality of feed water on boiler performance have also been captured in this review. From the study, a minimum increase in boiler feed water temperature is recognized as a progression to improve the steam boiler efficiency (a minimum rise in boiler feed water temperature of about 20 degrees Celsius is estimated to improve boiler efficiency by 3 to 4 per cent). By using deaerators whose main purpose is to remove dissolved gases in the feed water and in the process increasing quality of the feed water and its temperature, we succeed in reducing the temperature gradient between the feed water and its tubes resulting in reduction of thermal fatigue and shocks in the alloyed steel walls. This improves the health of the steam boiler.

   

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Title: Hybrid mixed basis vector based direction of arrival estimation using Sparse Bayesian Learning Algorithm
Author (s): Mamatha M. C. and H. C. Sateesh Kumar
Abstract:

Antenna with Non-uniform linear array is sophisticated for the reconfigurable antenna setup. This paper deals with the DOA estimation of signals with non-uniform linear array setup adopting the sparse representation based implementation. A Mixed basis vector based sparse representation is adopted in this paper to predict the DOA estimation. MATLAB based implementation is carried out for the DOA estimation for non-uniform linear array setup and estimation accuracy is analyzed for the proposed work. Estimation accuracy is found from different waveforms generated from the results which involve graphs like Signal to Noise Ratio versus Mean Square Error. The results thus obtained are compared with the traditional methods to validate the performance of the results obtained from the proposed method.

   

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Title: A sustainable approach to a Cartesian robotic ARM
Author (s): R. Swarnalatha, Swetha Perial, Samar Kulsoom and Saaima Anwar
Abstract:

This research deals with the construction and designing of a sustainable robotic arm with five degrees of freedom and memory. The entire setup was simulated using the Arduino UNO microcontroller and Arduino IDE software. The arm designed can perform basic useful functions including but not limited to, picking up and placing objects in desired locations. The arm has great flexibility and is highly adjustable owing to the five degrees of freedom it possesses. This investigation deals with the designing and implementation process of a fully functioning robotic arm. The robotic arm is created to move around with five degrees of freedom across a plane in order to increase the range of activities it can perform. The movements of the arm can be recorded and replayed making it useful to carry out redundant functions present in the daily routine of man. The arm is made up of environment friendly materials so as to attain sustainability and not further lead to environmental degradation. The robotic arm and its features are explained in detail along with the pertinent need for sustainability. The construction and circuitry involving the internal and external connections concerned are discussed along with the program code executed on Arduino.

   

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Title: Automatic control systems in the development of document management components based on SaaS solutions
Author (s): Diana R. Grigoreva, Gulnara A. Gareeva, Ruslan R. Basyrov and Aigul G. Faizullina
Abstract:

Small businesses face unique challenges in operating their own IT infrastructure. Among them is the ability to have and maintain data centers capable of supporting business. Even IT services companies may not have the expertise to manage an IT infrastructure. As a result, small businesses tend to use Internet resources to meet business needs. An increase in the efficiency of small businesses with the help of SaaS solutions is presented in terms of resource costs for the deployment and maintenance of infrastructure in the field of document management. When the developed system components are introduced to the enterprise, its overall efficiency will increase due to organized work with documented information and reduce the use of company resources associated with the costs of deploying a document management system.

   

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