Journal of Applied Research and Technology

Design an on-grid PV system to supply electricity to a school in Babil city using PVsyst software

F. F. Al Sarhan — Wed, 30 Oct 2024 00:00:00 -0600

The world attention is increasingly directed towards solar energy, particularly in countries of high solar radiation rates such as Iraq, due to the limitation of fossil fuel resources and the high pollution rates associated with using them. Engineers and researchers utilize different techniques in order to design the photovoltaic systems with low cost and high performance. This research aims at designing an optimal on-grid PV system to feed a school, located at Babel, Iraq using PVsyst program. The PVsyst methodology includes defining the geographical location of the project, determining the demand electrical load, selecting the type of the PV system components, and finally running the simulation. Detailed results, including the produced energy, loses diagram, economic and environmental evaluations can be obtained. The results show that a PV system comprising of 90 (450 Wp) panels and 3 (12 kWac) inverters on an area of 198 m2 can produce a net output energy at 70.23 MWh. The economic evaluation show that the project cost can be recovered within less than 10 years, and a net positive gain up to 20,000 USD can be attained during the 25 years project lifetime. A huge carbon emission equal to 1279.6 tCo2 can be saved as a result of this PV system installation. There is an obvious need to invest in solar energy for economic and environmental considerations. The main drawback of PV systems installations is the high capital cost. Using commercial packages, particularly PVsyst program, can significantly contributes toward optimizing the system design and hence reducing the project cost.

Presence monitoring system in a data center using facial recognition, multitasking, and an IoT platform

Wed, 30 Oct 2024 00:00:00 -0600

Data processing and telecommunication equipment are installed in facilities called equipment sites. The presence of people in these places is permanently monitored by different means, such as closed-circuit television and through routes by surveillance personnel. However, there are points that are not covered by video cameras, or where there may be a presence, even when the guards are at equipment sites. This paper presents a system based on a mobile robot that travels through the equipment site of a data center to detect the presence of people and attempt to recognize their faces. When a person is detected, the robot sends a WhatsApp alert message through the Twilio Internet of Things (IoT) platform to the phone of the data center administrator. The robot integrates an Arduino board for navigation control and a Raspberry Pi for face recognition using a Local Binary Pattern Histogram algorithm. The test results indicated a recognition accuracy of 99.5%.

Extraction of nickel ions using nanoporous adsorbent material from waste glass

Z. Karm, S. A. Ajeel, B. A. Abdulhussein — Wed, 30 Oct 2024 00:00:00 -0600

This study aims to create a porous glass adsorbent from waste glass to extraction nickel ions from its aqueous solution. The process involves converting waste glass to porous glass using 1:1:1:1 lime, sodium chloride, and sodium bicarbonate, followed by reacting with waste glass at 800 ˚C. The porous glass surface morphology, elemental composition, and functional groups, were analyzed using SEM, EDS, and FT-IR techniques.The outcome parameters used in this study are adsorbent dosage (10 g), contact time (150 min), heavy metal ion concentration (100 mg/l), and pH of 6. The adsorption capacity resulting from these parameters is 9.28 mg/g using the porous extract adsorbent for the extraction of nickel ions from its solutions. According to the findings. The proportion of Ni (II) ions extracted increased, coupled with a rise in the adsorbent dosage, heavy metal ion concentration, contact time, and pH. In addition, the Langmuir isotherm (R² = 0.98,K_L=0.072) has shown better performance than the Freundlich adsorption isotherm (R² = 0.93,N=1.598) for the adsorption of the Ni(II) in this study.

BCI-based real-time processing for implementing deep learning frameworks using motor imagery paradigms

Wed, 30 Oct 2024 00:00:00 -0600

As a cognitive process, motor imagery (MI) includes mentally simulating motor actions in the absence of physical movement. It has a variety of uses, including assistive technologies, medical diagnostics, and rehabilitation. MI paradigms are utilized in conjunction with brain-computer interfaces (BCI), which use electroencephalographic recordings (EEG) because of their high temporal resolution, cheap cost, portability, and non-invasiveness. BCIs apply MI paradigms by directly connecting the human brain to a computer. However, because scalp readings are non-stationary and non-linear, real-time processing of EEG signals is challenging. Furthermore, in order to minimize the impact of outside noise and artifacts, clinical MI methods must be implemented under carefully monitored laboratory conditions. A deep learning model-based approach is shown for analyzing EEG data and giving real-time feedback to a brain-computer interface. Generally, the system's design is portable and low-cost, allowing the MI paradigm to perform under poorly regulated sampling conditions.

Performance evaluation of untreated sugarcane bagasse ash as partial replacement of cement on setting time and compressive strength of M15 concrete

S. Olopade, E. Ngene — Wed, 30 Oct 2024 00:00:00 -0600

Due to its escalating cost, cement, the primary component of concrete, has become a significant issue in Nigeria over time. The use of agricultural wastes such as cow bones, periwinkle shells, rice husks,
and sugarcane bagasse as additives to partially replace cement has been made possible by scientific efforts to find alternative and effective materials from large deposits of agricultural wastes. This study examines how adding sugarcane bagasse ash (SCBA) to concrete affects its strength properties. Sugarcane bagasse ash was successfully included in various amounts (0, 2.5, 5.0, 7.5, and 10% by weight of cement). A mix design of 1:2:4 (M15) grade and a water-cement ratio of 0.5 was used to cast 60 concrete cubes measuring (150 x 150 x 150) mm. Concrete's workability and setting time were improved by adding sugarcane bagasse ash to the cement. The outcome revealed a reduction in concrete density with an increase in percentage replacement of sugarcane bagasse ash. Addition of sugarcane bagasse ash to cement increased the concrete's workability and speed of setting. The results showed that concrete density decreased as sugarcane bagasse ash replacement percentage increased. This is not unrelated to the fineness of sugarcane bagasse ash, which makes the cementitious matrix and aggregate interface more intense and lighter. Concrete's compressive strength was discovered to be decreased by the usage of sugarcane bagasse ash. Between 0, 2.5, 7.5, and 10% sugarcane bagasse ash, the average compressive strength measured at 28 days was found to be 25.93, 25.19, 23.70, 20.30, and 18.96 MPa, respectively. 10% sugarcane bagasse ash concentration was suggested as the optimal level to employ for improving concrete characteristics.

Enhancing the electrochemical performance of next-generation 5 V class Li-ion batteries using LiPF6/LiBOB mixed salt electrolyte

Wed, 30 Oct 2024 00:00:00 -0600

Modification of LiPF₆-based electrolytes by simply combining two lithium salts to obtain a mixed electrolyte has been demonstrated as a potential strategy for the next-generation 5 V class lithium-ion battery, hindered by electrolyte decomposition and transition metal dissolution. In this study, LiPF₆/LiBOB mixed salt electrolyte with different LiBOB content (10% and 20%) in EC/DEC/DMC at a ratio of 1:1:1 (v/v) was tested in the high-voltage LiNi_0.5Mn_1.5O₄ (LNMO) cathode to optimize their electrochemical performances. The mixed salt electrolyte performed higher ionic conductivity and better stability window than the baseline LiPF₆ electrolyte. A series of electrochemical measurements, including EIS, CV, and CD, are performed in the half-cell configuration with Li-metal. LiPF₆ electrolytes with 10% LiBOB showed higher discharge capacity up to 133.5 mAh g^-1, better cycle stability up to 1C, and remained stable after 25 cycles. The improved performance of the mixed salt electrolyte can be attributed to the surface-forming ability of LiBOB in providing a stable (Cathode-Electrolyte Interface (CEI) layer. In our finding, the synergistic effect between LiPF₆ and LiBOB has a certain optimal ratio in which the higher ratio of up to 20% tends to decrease the overall electrochemical performance of the high-voltage LNMO cathode.

Study of recovery factor and CO(2) storage behavior in a reservoir using numerical simulation

D. Tomalá, M. Gutiérrez, C. Quirumbay, S. Iturralde — Wed, 30 Oct 2024 00:00:00 -0600

In this study, the behavior of the recovery factor during the displacement and storage phases of carbon dioxide (CO₂) in an Ecuadorian reservoir was investigated by numerical simulation. Continuous injection and CO₂ WAG methods were used. The methodology included field data collection, creation of a static reservoir model, configuration of the PVT model with CMG software, construction of a dynamic model in GEM-CMG based on rock-fluid properties, and evaluation of CO₂ injection scenarios. After a screening analysis, the optimal scenario was identified and the performance of the recovery factor over time was studied. The results indicated that, during the 8 years of simulation, the recovery factor with continuous injection was 28%, while with the WAG method it reached 31%. It was concluded that WAG was the most efficient method. Regarding storage, it was observed that continuous injection was able to store 83% of the CO₂ in the reservoir.

Graphene nano particles to improve lightning dissipation on transmission lines

Wed, 30 Oct 2024 00:00:00 -0600

Lightning is the primary cause of outages for many high voltage transmission lines. One approach to reduce the frequency of these outages is the improvement of the grounding system using chemical ground enhancers to better disperse transient or fault currents into the soil. In this paper, the objective is to use graphene nano particles to improve the performance of commercial ground enhancers by exploration of 15 different commercial graphene nano particles used to reformulate 19 commercial ground enhancers and one natural ground enhancer. Incorporation of nano graphene particles is by high shear mixing method. The results show reduction in two of the commercial ground enhancers’ resistivity values by a factor of 60. Moreover, lightning impulse tests show that the use of graphene reduce deterioration of the ground enhancer, which can occur after high current events, thereby prolonging its efficacy. Due to the superior electrical conductivity and chemical stability of the graphene, the reformulated ground enhancers improve short-term performance in managing lightning current impulses, and provide a solution, which is likely to perform better over long periods. However, the compatibility of the constituent parts of the formulation is critical to long-term performance.

Automation of agricultural machinery: Development and validation of a portable automation module for oil palm plantation machinery

Wed, 30 Oct 2024 00:00:00 -0600

The primary objective of this project is to create a portable automation module that should be suitable for various heavy machines in agriculture. To begin, the OREC Bull Mower machine was chosen as the initial pilot study. Five major machine components were identified through meticulous analysis, laying the groundwork for the automation process. Several functions, including gear shifting, clutch operation, and other critical tasks, were successfully automated. Extensive testing and measurements were performed to identify the best actuators for precise and efficient control. The actuators and controllers were thoughtfully integrated into the enclosure, resulting in a versatile automation module that can be programmed for remote or autonomous operation. Lab and on-site testing proved the module's efficacy in real-world scenarios, validating its successful implementation. While the project has produced promising results, future improvements are required, particularly in mechanical fitting, design for assembly, and the use of reliable electronic components.

Intelligent inspection and quality control of table olives

S. Makni, I. Fourati Kallel, M. A. Triki — Wed, 30 Oct 2024 00:00:00 -0600

Quality is a key factor of product-marketing in the field of agriculture and food industry. A number of researches have suggested the use of vision computer systems and machine learning (ML) techniques essentially to inspect imperfection surfaces and defects in fruit products. Following the trend, this paper still relies on the use of vision computer system by assuring an intelligent detection of table olive defect, with a certainty of its quality control. The specifically exploited computer vision system consists of automatically extracting the texture, colour, and shape features mainly from the global thresholding segmented image. With reference to the extracted features, the newly introduced system has the capacities of distinguishing between the defected and the healthy olive fruits rapidly and effectively at the same time. Subsequently, it is capable of identifying and specifying the diseased table olive. This system is also helpful for estimating the table olive size automatically. The experimental findings are indicative of the high accuracy of the binary classification algorithm, reaching 99, 32%, the average processing time for just one olive is about 0.4 s, which could meet the requirements of the real-time applications, and the error in estimating the size of the table olives does not exceed 10%.

Dyeing ability of C. longa L. and T. stans (L.) Juss. Ex Kunth on unmordanted and mordanted silk and cotton fabrics

O. B. Ovonramwen, G. R. Eshiokhai — Wed, 30 Oct 2024 00:00:00 -0600

The work was on the extraction of both the C. longa rhizomes and the petals of T. stans using four different solvents (ethanol, ethyl acetate, water, and n-hexane). The dyeing potential of the C. longa and T. stans extracts was evaluated on cotton and silk fabrics without or with mordants using potash alum, phosphomolybdic acid, iron (II) sulphate, and tartaric acid at varied temperatures and tested for colour fastness properties (wash and light fastness). The pH and absorbance of the dye bath before and after dyeing were studied. However, cotton, which is cellulosic, was better dyed than silk, which is proteinous, which showed a better choice for fabrics dyeing at 80 °C; hence, it had a good colour efficiency. Iron (II) sulphate exhibited complexes in the octahedral configuration of the coordination six with CH₂O- of cotton and NH₃⁺ and COO^- of silk fabric. In addition, it was also observed that the higher the dyeing temperature, the greater the dyeing intensity. The spectroscopic characterization of the extracts was determined with the help of UV-Vis and FTIR. The UV-Vis and FTIR spectral analyses revealed the chromophore, auxochrome groups, and functional groups, respectively, within the extracts. Curcumin and rutin were identified as being responsible for the dyeing of the fabric.

Comparison of machine learning algorithms for dengue virus (DENV) classification

Y. V. Exebio-Chepe, J. A. Bravo-Ruiz, V. A. Tuesta-Montesa — Wed, 30 Oct 2024 00:00:00 -0600

Dengue, transmitted by the Aedes aegypti mosquito, necessitates accurate case classification for effective management. The research focuses on leveraging machine learning algorithms to enhance diagnosis and streamline control strategies. Utilizing a dataset from a public hospital, encompassing 21,157 cases categorized by period, outcome, gender, age, symptoms, and origin (autochthonous or imported), the study conducted a comparative analysis of Support Vector Machine, Random Forest, and Artificial Neural Network algorithms. The dataset was divided into 70% (14,809 cases) for training and 30% (6,348 cases) for testing. Results unveiled the Artificial Neural Network as the frontrunner, exhibiting an impressive 86.47% accuracy and a robust 92.91% recall in the classification of dengue-related cases. This underscores the potential of machine learning in refining dengue diagnosis and facilitating more efficient control strategies, offering a promising avenue for combating this vector-borne disease.

Optimising acceptability using a user-centred design approach of a robotic software in Industry 4.0: A case study

M. Boutrouille, E. Loup-Escande — Wed, 30 Oct 2024 00:00:00 -0600

While robotics and collaborative robotics are becoming increasingly commonplace in industry, operators do not always have full control over these tools. The aim of our robotics software is to give operators back the power to act. A user-centered design approach (UCD, ISO 9241-210, 2019), through four steps, has therefore been put in place within Industry 4.0. The first study aims to understand and specify the context of use through three objectives: to understand the organizational context in which the robotic software is to be designed and implemented, to characterize the end users via primary personas, and to take an interest in the operators' work in order to predict likely future situations and guide the development of the new work tool. The second study aims to specify user requirements using a card sort based on different criteria (ergonomic, UX). The third study presents the design solutions for version 2 of the robotics software. The fourth study evaluates and compares the practical acceptability (UX, usefulness, usability, mental load) and social acceptability (intent to use) of the first and second versions of the robotic software. Our results show, among other things, a significant improvement in acceptability for the second version of the software, suggesting greater acceptability of this technology thanks to the UCD approach.

Mobile crawler robot for seed sowing and route planning through neuro-diffuse control

J. Figueroa, M. Yarad, M. Montaño, O. Gomez, R. Rovira — Wed, 30 Oct 2024 00:00:00 -0600

The main objective of this project is to build a mobile terrestrial robot that allows the sowing of seeds of various types of plants that are cultivated in an artisanal way. A structure based on tracked locomotion has been designed that involves the use of several sensors, DC motors, and control systems based on two Arduino boards, which together allow the mobile robot to interact with the irregular environment through which it moves. The locomotion process carried out by the seeding robot is configured through an HMI interface implemented on a touch screen, where the user chooses the type and quantity of seeds to be sown so that the robot then follows an autonomous rectilinear trajectory which is supervised and corrected utilizing a neuro-diffuse control such as ANFIS. In addition, the mobile robot has a battery feeding and charging system through solar panels, which gives it complete autonomy to carry out the work entrusted to it.