Journal of Applied Engineering and Technological Science (JAETS)

Microcontroller-Based Intravenous Fluid Monitoring System Design

Thu, 06 Jun 2024 00:00:00 +0700

Intravenous fluids are used to replace the body's fluid and electrolyte balance. This is a crucial need for a patient during treatment, so infusion replacement should not be delayed as it can be fatal to the patient. Medical personnel must always pay attention to the patient's infusion. This has always been a problem because the limited number of medical personnel and the large number of patients often make it difficult for medical personnel to carry out their duties. The development of technology increases human creativity and creates various tools to help humans be more effective, including in dealing with problems in the medical world. Based on this background, the author designed an infusion fluid monitoring system to facilitate nurses in hospitals that lack electrical support and internet networks. This research aims to make an intravenous fluid monitoring tool using a microcontroller effectively and realtime. The research method we use is research and development, while the data analysis method uses comparative quantitative analysis. This research consists of three main parts, namely system input, microcontroller as system processor, and system output as expected. This infusion fluid monitoring uses Load Cell to measure the volume of infusion fluid, RTC module to estimate the time of infusion fluid expiration, LCD as infusion fluid status information, and buzzer as an information alarm if the infusion fluid is detected to run out. The microcontroller used in this research is Arduino Uno. The results showed that infusion fluid has the same pressure as human body fluids (isotonic). Load Cell has a mass reading accuracy value of 99.88%, the accuracy of testing the conversion of intravenous fluid measurements into milliliters of 99.49%, and the number of infusion fluid droplets per minute under normal conditions is 20, with an estimated time out for 8 hours.

Shear Strength Characteristics of Calcium Oxide and Guar Gum Treated Loose Petobo Silty Sand

Yohanes Albrecht Montol, Aswin Lim, Paulus Pramono Rahardjo — Thu, 06 Jun 2024 00:00:00 +0700

This article presents the shear strength characteristics of Petobo Silty Sand which are treated with Calcium Oxide and Guar Gum. The purpose of this experimental works is looking for other binding agents to replace the application of cement which is considered not an environmentally friendly material. The shear strength of treated soils was examined using the direct shear test. Guar gum and Calcium Oxide provides additional cohesion to Petobo silty sand. The cohesion and internal friction angle could increase to about 900 kPa and 47.5°, respectively. The treated sample also shows the dilation behavior in dry conditions. However, after 24 hours soaking period, the soil behavior returned to the contraction behavior. This behavior is unfavorable in the case of the treated sample below the groundwater table. Hence, these two binding agents are effective for dry soil conditions. In addition, Scanning Electron Microscope images of treated silty sand were obtained which aims to examine the microscopic behavior of the fibers and matrices that were formed through the hydration process.

Safety Assessment of Tunnel Lining Structure with Underlying Cavities Based on Fuzzy Comprehensive Evaluation in Mudstone Stratum

Yiming Wang, Haoxuan Wang — Thu, 06 Jun 2024 00:00:00 +0700

This paper presents a study on the structural safety assessment of tunnel linings with underlying cavities based on a fuzzy comprehensive evaluation model in mudstone stratum. The weight and membership degree are determined using an improved method: field data analysis and numerical simulation. Field data analysis revealed that the proportion of cavities in the surrounding rocks of class ? and at the vault was the largest. Cavity length between 1m and 3m and cavity depth between 20cm and 40cm occupied the most significant proportion. Additionally, the impact of defect parameter changes on structural safety was investigated through numerical simulation. It is well known that the lining safety factors are greatly impacted by changes in surrounding rock classifications, cavity locations and depths. In contrast, changes in cavity lengths do not significantly affect the lining safety. The developed fuzzy comprehensive evaluation model consists of factor set, comment set, membership degree and weight set. They are determined according to the previous field data analysis and numerical analysis results. The developed evaluation model is validated by means of the numerical simulation based on the evaluation work of the specific engineering case.

Durian Rind-Based Liquid Smoke as a Natural Preservative for Chicken Meatballs: Effect of Pyrolysis Temperature and Liquid Smoke Concentration

Thu, 06 Jun 2024 00:00:00 +0700

Liquid smoke is produced by the pyrolysis of biomass. The use of liquid smoke has numerous advantages over traditional smoking methods. The liquid smoke market is well-established and growing, providing an opportunity to commercialize biomass pyrolysis. This study aimed to investigate the utility of durian rind, biomass waste rich in lignin, cellulose, and hemicellulose, as a natural preservative to extend the shelf life of chicken meatballs and to mitigate environmental problems caused by the disposal of untreated durian rind waste. Dried durian rinds with approximately 10% water content were pyrolyzed at temperatures of 300°C (T1 liquid smoke), 340°C (T2 liquid smoke), and 380°C (T3 liquid smoke) using a slow pyrolysis reactor in batch conditions to produce crude liquid smoke, which was then purified by distillation at 190°C. Chicken meatballs were then soaked in liquid smoke solutions with concentrations of 1%, 2%, and 3% for 15 minutes, and the meatballs checked for signs of spoilage every 4 hours. Tests for total volatile base nitrogen (TVB-N), in addition to the total plate count (TPC) and most probable number (MPN) of Escherichia coli bacteria, were performed to evaluate the preservation ability of the liquid smoke. The results indicated that both the pyrolysis temperature and liquid smoke concentration affected the preservation time, with a pyrolysis temperature of T3 and liquid smoke concentration of 3% optimum for chicken meatball preservation. Under these conditions, the meatballs could be stored for 56 hours with TVB-N, TPC, and E. coli MPN values of 21.01 mg N/100 g, 5.37 × 10⁴ CFU/g, and 75 MPN/g, respectively. The findings suggest that liquid smoke derived from durian rinds could be used to preserve chicken meatballs.

The Fuel System Modification To Strengthen Achievement And The Prospect Of Utilizing Gasoline Ethanol Blended With Water Injection

Thu, 06 Jun 2024 00:00:00 +0700

This research proposes a fuel system conversion from a carburetor to an electronic fuel injection (EFI), to save fossil fuels using gasoline-ethanol combined with water injection. Beneficial as an offer for Indonesian motorcycle environmental friendliness in terms of exhaust emissions. The goal of this study is to improve engine performance and accommodate technology for the deployment of ethanol gasoline implementations. The experiment was conducted using fuel with a ration octane number (RON) of 92, gasoline-ethanol was executed up to E25 then applied water injection (Wi). The results show that converting a conventional carburetor to EFI and additional water injection increases engine performance, mileage, and reduces exhaust emissions.

The Role of Artificial Intelligence in Providing People With Privacy: Survey

Salar Adil Raees, Mohammed Al-Tamimi — Thu, 06 Jun 2024 00:00:00 +0700

Images privacy involves assessing the amount of information leakage from images, assessing risks associated with identification, and examining controls on this information. It was discussed various types of protection available and most commonly used in providing privacy to a person in images, including single-stage and two-stage detection algorithms. The results of each algorithm are organized in detailed tables, and the [YOLO] algorithm expands on all versions. The paper also clarifies the dataset used for testing the algorithms and its relevance to achieving desired results. It presents a comprehensive understanding of the process of detecting persons in digital images and assesses various tools and algorithms for recognizing persons, faces, and identities. It added an extensive examination of the several methods used to identify persons in digital images, with a specific emphasis on safeguarding their privacy. The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. The study concluded that using the yolov8 algorithm in conjunction with blurring techniques effectively conceals individuals' information in digital images while maintaining the integrity of the overall image. The research paper's implications and information can practically contribute to the development of algorithms for detecting and protecting people in digital images, as well as the development of applications in this field. Theoretically, it can enhance understanding of the process of detecting and protecting people, and potentially contribute to the development of new theories in the field of protection and discovery.

Effect of Laser Distance Measurement for Fatigue Crack Detection on Aluminium Plate Using Laser Doppler Vibro-Meter

Thu, 06 Jun 2024 00:00:00 +0700

Fatigue cracks can occur because the material is unable to withstand the load applied repeatedly. A nonlinear vibroacoustic method was introduced to overcome this problem. This is because this method is one of the best solutions because it is suitable for detecting fatigue cracks which is sensitive enough to detect small cracks. The aim of the research is to determine the effect of laser distance measurements on fatigue crack detection using the vibroacoustic method. Therefore, there are steps or procedures that include test object preparation, tensile testing, dynamic tensile testing, and modal analysis. Three different vibration modes are selected to excite the low frequency modes. The vibroacoustic method is a method based on the propagation of high frequency sound waves in solid structures with low frequency excitation. The trained output signal will be converted from the time domain to the frequency domain supported by the use of MATLAB software. The analysis results show that there is a significant influence on the detection of fatigue cracks in aluminum using the vibration acoustic method. The analyzed data shows that measuring the laser distance will influence the crack detection process.

An Analytical Study on the Most Important Methods and Data Sets Used to Identify People Through ECG: Review

Abdullah Najm Abed Alzaki, Mohammed Al-Tamimi — Thu, 06 Jun 2024 00:00:00 +0700

The electrocardiogram is a topic of great importance from a medical and biometric perspective, especially recently, as researchers have begun to search for new biometric methods other than the palm print, fingerprint, or iris as alternative systems. Researchers discovered that ECG has unique features that are not common among humans, making it a good topic for researchers in biometric systems for identifying people. In this research paper, the goal is to shed light on the most important basic concepts that are related to ECG in terms of the methods used by researchers and in terms of the most critical data sets used by researchers, and also to shed light on some previous studies that achieved a high rate of citations, and also to shed light on the most important basic concepts that make Its features are unique and intelligence methods can be used effectively.

Lightweight Block and Stream Cipher Algorithm: A Review

Suaad Ali Abead, Nada Hussein M. Ali — Thu, 06 Jun 2024 00:00:00 +0700

Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable. Fortunately, various lightweight encryption algorithms could be used to increase defense against various attacks to preserve the privacy and integrity of such applications. In this study, an overview of lightweight encryption algorithms, and methods, in addition, a modern technique for these algorithms also will be discussed. Besides, a survey for the algorithm that would use minimal power, require less time, and provide acceptable security to low-end IoT devices also introduced, Evaluating the results includes an evaluation of the algorithms reviewed and what was concluded from them. Through the review, we concluded that the best algorithms depend on the type of application used. For example, Lightweight block ciphers are one of the advanced ways to get around security flaws.

Effect of High Temperature Heating on Chemical Compounds in Magnesium Composite Materials

Rezza Ruzuqi, Eko Tavip Maryanto — Thu, 06 Jun 2024 00:00:00 +0700

The development of magnesium composite-based seawater battery anode technology is actively pursued, especially in its ability to transmit and store electrical energy. However, many overlook the possibility that significant temperature changes during the process may lead to chemical compound alterations, potentially affecting the battery's performance. Therefore, this research examines the changes in chemical compounds in magnesium composite-based seawater battery anodes caused by high temperatures. In this study, the synthesis process of magnesium composite material composed of MgAlSnMn with variations of Manganese (wt.-%) 14.8, 15, 15.2, 15.4, 15.6. Then it was milled for 60 minutes. Next, the materials were pelletized using a manual compacting machine with a diameter and compressive strength of 10 mm and 150 kg/cm²respectively. After that, all materials were sintered at 750⁰C with a muffle furnace for 60 minutes. In this study, XRD equipment was utilized to determine chemical compound changes. The results indicate that magnesium composite materials undergo significant chemical compound alterations at high temperatures, including MgO (Magnesium Oxide Periclase), Al18Mg3Mn2, and the remaining Al elements. This could potentially disrupt the performance of seawater batteries when applied. It is hoped that further research will be conducted in the future to enhance the quality and performance of the product.

Agro-Food Supply Chain Risk Assessment: A Review Based on Technique and Approach

Daniel Bunga Paillin, Machfud Machfud, Hartrisari Hardjomidjojo, Muhammad Romli — Thu, 06 Jun 2024 00:00:00 +0700

Risk assessment in agro-food supply chains is crucial in managing the complexity and uncertainty associated with food product production, distribution, and consumption. This study aims to classify risks and mapping techniques or approaches used in risk assessment of agro-food product supply chains. Mapping technique or approaches to risk assessment of agro-food supply chains was carried out based on the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework, which consists of several stages of identification, screening eligibility, and inclusion, resulting in a total of 72 relevant journal articles. They were selected from 58 different journals with high-impact factors and rankings. The literature review results show that agro-food's supply chain risk classification has much to do with risk assessment: macro-level risk, operational risk outside the company, and internal risk. Furthermore, the most studied agro-food products are general food (44%), horticultural products (28%), meat products (11%), dairy products (10%), fishery products (6%) and bread products (1%). The techniques and approaches most widely used in assessing the risk of the agro-food supply chain are semi-quantitative (49.3%), quantitative (31.5%), mixed (12.3%), and qualitative (6.9%). A better knowledge of the topic being addressed in the research community is sped up by identifying these techniques and approaches since the literature on supply chain risk management for agro-food is voluminous, complicated, and challenging to grasp.

Lung Nodule Detection For CT-Guided Biopsy Images Using Deep Learning

B. Prashanthi, S.P. Angelin Claret — Thu, 06 Jun 2024 00:00:00 +0700

The recent advancements in artificial intelligence enhance the detection and classification of lung nodules via computed tomography scans, addressing the critical need for early diagnosis of lung cancer. The lung cancer when identified at the earlier stages, the chance of survival is higher. The methodology encompasses a modern deep-learning approach applied to a private dataset obtained from the Barnard Institute of Radiology at Madras Medical College, Chennai, which has been granted ethical approval. The results from applying the proposed Convolutional Neural Network model are promising, with an accuracy of 99.3% in malignancy detection, signifying a notable advancement in the precise diagnosis of lung cancer through non-invasive imaging techniques. Beyond academia, the findings of this study have significant implications for real-world healthcare settings. By providing a reliable and automated solution for lung nodule detection, this research contributes to early diagnosis and personalized treatment strategies for lung cancer patients. The value of the present work lies in its potential to reduce morbidity through the early detection of lung cancer, thus contributing to both clinical practice and the ongoing development of AI applications in healthcare. Our research may serve as a model for further studies in digital health care at Madras Medical College, aiming to improve patient outcomes through technology-driven diagnostics.

A Bibliometric Article Regarding Twin Technology In Technology Management For The Year 2019-2025: Industry In Malaysia

Thu, 06 Jun 2024 00:00:00 +0700

The purpose of this research is to analyze the application of digital twin technology in the efficient management of new innovative technology. The research is directed to perform a bibliometric analysis of the subject topic. The relevancy of the research can be underlined by the fact that digital twin technologies are a popular concept of Industry 4.0. In addition, this research is advantageous to identify the application of digital twin technology in efficient technology management, especially in Malaysia. As a scope, it would highlight possible use cases of digital twin technology. The review of existing literature highlighted that digital twin technology has serious use case potential in supply chain operations. Whereas other scholars argue that digital twin technology can bring out major disruptive innovations to improve the internal competencies of major manufacturing firms. The methodology for the research involves the use of secondary data with bibliometric analysis. It has been identified in the findings that there is a rise in research associated with digital twin technology between the timelines from 2019 to 2022. Furthermore, Chinese Academies are most active in propagating research on variables like digital twins.

Risk Assessment Maturity Level of Academic Information System Using ISO 27001 System Security Engineering-Capability Maturity Model

Thu, 06 Jun 2024 00:00:00 +0700

Risk measurement from standard operating procedures implemented by an institution determines the level of maturity of a service system at that institution. The government's determination of the Tri Dharma of Higher Education consists of education and teaching, research, and community service. These activities must be implemented in the academic information system of every university in Indonesia. Appropriate and fast academic services depend on information technology and adequate and trained human resources (HR). Factors that influence information system security determine the stability of application services. The ISO/IEC 27001:2005 standard is an international benchmark for measuring the level of maturity and security risks of an application. Risk assessment in standard operating procedures in organizations can use the ISO/IEC 27001 standard. This research aims to determine the current level of Academic Information System (AIS) service by measuring maturity and security risks. Three clauses measure the maturity level of information security controls with the ISO 27001 System Security Engineering-Capability Maturity Model (SSE-CMM). These research respondents are educational work units at the Science and Technology Faculty in UIN Syarif Hidayatullah Jakarta. This research method uses quantitative research methods. This research results show the maturity level of information security in the academic information system based on three clauses as the embodiment of the stability of the academic administration activities services at the Science and Technology Faculty. The measurement results reveal that the average score of information security controls on AIS is 3.51, which means good or average standard processing has been carried out following procedures.

Big Data Approach to Sentiment Analysis in Machine Learning-Based Microblogs: Perspectives of Religious Moderation Public Policy in Indonesia

Mhd. Furqan, Ahmad Fakhri Ab. Nasir — Thu, 06 Jun 2024 00:00:00 +0700

The concept of religious moderation encompasses three key aspects, namely moderate thinking and understanding, moderate behavior, and moderate religious worship. With advancements in information technology, people now have the means to express their opinions through microblogs, pertaining to issues of religious moderation initiated by the Ministry of Religion of Indonesia. This study aims to evaluate public policies introduced by the Ministry of Religion regarding religious moderation such as changes in the halal logo, transfer of authority for halal certification, and regulations on the volume of loudspeakers in the mosque. Public opinions collected as the big data to get the information about public sentiment with those issues. Sentiment analysis was conducted on three primary microblogs such as Twitter, Instagram and YouTube using six machine learning algorithms. These include Naïve Bayes, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Bagging Classifier, Random Forest, and Gradient Boosting Classifier. The test results showed the highest accuracy is Gradient Boosting reached 82.27%.

Morphology of 925 Silver Powder Particles Produced From Gas Atomization

Montri Kawsuk, Surat Wannasrib, Sirichai Torsakula — Thu, 06 Jun 2024 00:00:00 +0700

In order to examine the impact of metal water temperature and gas flow rate on the production of 925 silver alloy powder via closed-coupled nozzle and gas atomization process with nitrogen gas as the production medium, and since the morphology of the powder particles could not account for the influence of these variables, the aim was to comprehend and propose a new approach for a general framework for studying the influence of such factors. As a consequence, an investigation was conducted into the impact of these two variables on the morphology, which was characterized by roundness values. Particle size and distribution information can be conveyed to facilitate interpretation. According to the results of the experiment, the gas flow rate and metal water temperature influence the particle morphology in terms of particle size and distribution with respect to roundness. The particle size distribution of metal powders is more restricted and the particle roundness increases. This is due to the fact that the particle morphology plays a critical role in determining which metal powder particles are suitable for forming metal powder workpieces via various production methods. The gas flow rate and metal water temperature influence the particle size distribution, roundness value, and significant size of 925 silver alloy powder.

Development of a Game-Based Learning: Airfield Lighting System Simulator Using Virtual Reality and Augmented Reality

Thu, 06 Jun 2024 00:00:00 +0700

This study aimed to develop an innovative learning tool, AIRLIT, as an alternative practical system to enhance the learning of Airfield Lighting System (ALS) among Diploma IV Airport Engineering Technology (DIV-TRBU) cadets. The motivation behind this research stemmed from the necessity to address the challenges faced in ALS practical learning due to limited access to airport facilities. The research methodology is Waterfall Model, encompassing phases: analysis, design, implementation, system testing, and maintenance. User needs were thoroughly analyzed, particularly those of DIV-TRBU cadets, through observations and interviews with subject matter experts. The resulting AIRLIT application offers immersive simulations of ALS operations, including AR recognition of lighting tools/materials and VR visualization of airport layouts. This research succeeded in developing the AIRLIT application, and system testing revealed positive outcomes, with the significant value for pair 1 is 0.000 < 0.05, so there is a difference in the average learning outcomes of cadets for the experimental class pre-test and the experimental class post-test. The significant value of pair 2 is 0.000 < 0.05, so there is a difference in the average learning outcomes of cadets for the control class pre-test and the control class post-test. The Independent sample test shows a difference in cadet learning outcomes between the learning model using AIRLIT and the conventional model, and this result indicates the effectiveness of AIRLIT in improving cadets' learning experiences and outcomes. Overall, this research underscores the significance of incorporating innovative technologies into educational practices, paving the way for enhanced learning experiences and outcomes in airport engineering training programs. The theoretical implication of this study lies in its contribution to integrating AR technology into educational settings, enhancing engagement and experiential learning. Practically, AIRLIT provides a valuable tool for ALS learning, addressing the limitations of traditional practical training methods.

Determination of Superior Commodities For The Development of Small and Medium Industries in Kampar Regency

Dewi Diniaty, Anas Miftah Fauzi, Titi Candra Sunarti, Sapta Raharja, Fiora Helmi — Thu, 06 Jun 2024 00:00:00 +0700

The small and medium industries based on superior commodities potentially developed in Kampar Regency, as of its second-largest share contribution of GDP after the agriculture sector. The problem faced in developing small and medium industries is the diverse and varied nature of these enterprises, both in terms of quantity and scope, which leads to unfocused management of potential commodities and types of businesses. A technopark is one of the alternative strategies to develop small and medium industries based on superior commodities. Determining superior commodities is an initial step in developing small and medium industries through technoparks. The purpose of this study is to identify the superior commodities that will be developed in small and medium industries through technoparks in Kampar Regency, Riau Province. Data collection techniques were conducted through literature studies and expert interviews, using purposive sampling. The determination of commodities was done through LQ and SSA. The data used were horticultural crop production from 2017-2021. The study results indicate that pineapples are a superior commodity due to their extensive distribution in five sub-districts, boasting the largest harvest areas, abundant raw materials, and regional potential with LQ >1 and SSA > 0. The development of small and medium industries based on pineapple as a superior commodity through technopark can create economic value in the Kampar Regency.

Pest Control System on Agricultural Land using IoT Electronic Controller

Thu, 06 Jun 2024 00:00:00 +0700

This research aims to assist farmers in controlling plant pests, birds and insect, by applying an appropriate electronic technology. The system operates in an automatic and remote-controlled modes using IoT technology. We used a solar powered systems that are environmentally friendly with zero carbon emissions, as an energy source for the systems. The test results showed that the bird pest control system worked well according to the automatic and remote-control modes design. We compare those two methods to evaluate the most effective between those two methods. Bird pest control using two actuators, sound and movement, outsmart control using only sound by success ratio 70:50. The insect pest control system worked well with the remote-control mode through Telegram application on farmers’ smartphones.

Design of An Automatic Temperature Recorder for Fishery Vessels Using Internet of Things Technology

Hadi Purwanto, Maman Hermawan, Chandra Nainggolan, Berbudi Wibowo — Thu, 06 Jun 2024 00:00:00 +0700

Fishery products, especially capture fisheries, must be safe and high-quality. The treatment of captured fish from capture to consumption is crucial to maintaining its quality. Temperature impacts fish quality. Fish putrefaction can be prevented at a specific temperature. Maintaining optimal fish quality requires temperature monitoring at the holding hatch of fish captured on board. Indonesia requires hatches with fish storage to have automatic temperature recorders and monitors. Inspections by authorities who issued certifications of acceptable fish handling practices found many breaches on Indonesian fishing vessels without automatic temperature monitoring systems. Indonesian fishery exports to the EU have been rejected due to the lack of automatic temperature recording systems on fishing vessels. Existing automatic temperature recording equipment for fishing vessels does not meet technical and legal requirements. The lack of autonomous temperature monitoring devices on fishing vessels was solved via design thinking in an exploratory study. Thus, fishing vessel temperature recording devices were designed using Internet of Things technology. Literature is utilized to choose resources. Hatch temperature recorder, MAX 31865 module, and PT100 thermocouple sensor use ESP 32 as a microprocessor. Raspberry Pi4 controls, displays, and stores data. This fish hatch temperature recorder has a GPS module for coordinates. This utility manages display and storage with Home Assistant software. Commercial low-temperature recorders are utilized for comparison testing. Before calibration, the pesuotokapi tool had a variance coefficient of 9.39%, whereas the comparison tool had 12.09%. The pesuotokapi tool has a coefficient of variation of 11.96% after calibration, whereas the comparison tool had 13.28%. The pesuotokapi tool regularly yields a lower coefficient of variation than the comparison tool. This shows that the pesuotokapi tool generates data with less divergence from the average recorded temperature than the comparison tool. Pesuotokapi devices regularly outperform comparator devices in temperature before calibration, improving fish hold quality.

A Comparison of Levelised Cost of Energy of Different Energy Sources for Irrigated Shallot Farming in Some Coastal Regions of Ghana

Thu, 06 Jun 2024 00:00:00 +0700

This study assessed the technical and economic viability of Poldaw wind pumps for irrigates shallot cultivation in the Keta Municipality in Ghana. Technical analyses of 4 versions of the Poldaw pump is conducted to determine if it they can supply the water requirements for irrigated shallot farming. The Levelized Cost of Energy (LCOE) of wind energy for irrigation over a period of 20 years is also calculated and compared with that of grid electricity, diesel, petrol and premix fuels as alternative energy sources for irrigated shallot farming in the area. At a hub height of 10 m, the 5.0 m Poldaw was found to be capable of supplying the daily water requirements for irrigated shallot farming in the area. In addition, its LCOE is better than those of petrol, diesel and premix fuel. Grid electricity lost its slight advantage on LCOE when the Poldaw pump was assessed for hub heights of 12 m and higher. The findings of the study suggest that the 5.0 m Poldaw pump is a viable alternative to pumps powered by other energy sources currently used for irrigated shallot farming in the Municipality.

The Essential Components of Metaverse-based Mixed Reality for Machinery Vocational Schools

Thu, 06 Jun 2024 00:00:00 +0700

Every nation is interested in the best practices of those with high enrolment in vocational schools and low young unemployment rates. We'd like to build robust systems that can deal with issues like the quick pace of technology development and the mismatch between supply and demand in the job market. Since Mark Zuckerberg rebranded the company as Meta in 2021, the Metaverse has seen a rise in popularity. The same can be said about mixed reality, which is currently in the spotlight following the release of Microsoft's first HoloLens. The authors propose a mixed reality as a means of resolving the problem of inadequately meeting the demand for skilled workers. The purpose of this study is to help machinery vocational schools decide whether or not to adopt a mixed reality as a teaching and learning tool by identifying the most important components of a metaverse-based mixed reality for such institutions and which metaverse type mixed reality belongs to. This study uses a methodology that is developed by the authors to accommodate the true or natural flow of this research. The results of this study are to provide the essential elements of mixed reality systems as the mixed reality systems are not part of any metaverse type. The implication of this study is since mixed reality is the combination of several metaverse types, the essential elements of mixed reality systems are taken from the components of the other metaverse types. The results of this study are to be a guide of what needs to be prepared before implementing a mixed reality system.

Advancements in Chemical Materials: Exploring Smart Storage Equipment and Protection Systems (Review)

Samah Kamil, Mohammed Nasser Hussain Al-Turfi, Riyadh S. Almukhtar — Thu, 06 Jun 2024 00:00:00 +0700

The growing dependence on chemicals across industries has emphasized the importance of storage solutions to ensure safety and environmental sustainability. Smart storage systems, equipped with cutting-edge technologies, offer opportunities to tackle these issues guaranteeing best dealing and handling. This study evaluates chemical storage equipment and protection systems' role in increasing safety and sustainability in storage practices and roles. This evaluation included a decade-long literature examination of papers, patents, and industry reports. The analysis examined safety assessments, regulatory compliance, and storage system applications. The study examined IoT, AI, sophisticated detectors, and sensors to improve storage safety and reduce the effect for environmental sustainability. Results showed breakthroughs in sensor technologies, systems integration, and AI algorithms for real-time storage facility monitoring, danger identification, and predictive analytics. Smart storage solutions reduce hazards, ensure compliance, and protect the environment. However, prices, integration issues, and data security concerns were noted. Overall, this review sheds light on chemical smart storage systems and their future. It shows how technology improves safety and sustainability and identifies topics for further research.

Exploring The Financial Dynamics Of Green Building Adoption: Insights From Indonesia

Thu, 06 Jun 2024 00:00:00 +0700

This research purpose is to offer insights to property owners and developers whose focus tends to be solely on the initial costs of green buildings, and aligning with the requirements set forth by Minister of Public Works and Public Housing Regulation No. 21 of 2022, effective from 2022, which mandates green buildings to obtain Building Structure Approval (PBG) and Functional Worthiness Certificate (SLF). Drawing from the 2013-2018 Green Building Council Indonesia (GBCI) report, which indicates a mere 2% certification rate for buildings exceeding 12 floors, this study seizes the opportunity to delve into how green building considerations influence financial decisions. Surveying 102 experienced respondents in green building practices, this research employs green building factor analysis, value engineering, life cycle cost analysis, and Structural Equation Modeling (SEM)-PLS to scrutinize the factors influencing cost performance in green buildings. The findings spotlight 10 critical green building factors pivotal for securing certification, alongside unveiling correlations between initial costs, operational costs, and life cycle costs. Anticipated outcomes encompass facilitating compliance with Minister of Public Works and Public Housing Regulation No. 21 of 2021, and nurturing the development of green buildings in Indonesia. Implications span regulatory compliance, informed financial strategies, green building advancement, and knowledge dissemination. This study aims to simplify comprehension of the financial ramifications of green buildings, furnishing practical guidance for developers in navigating the intricacies of cost-sustainability equilibrium.

Applications of IoT-Enabled Smart Model: A Model For Enhancing Food Service Operation in Developing Countries

Thu, 06 Jun 2024 00:00:00 +0700

The dining sector in developing countries faces numerous challenges, including inefficiencies in order handling, resource management, and ensuring food quality and customer privacy. Traditional methods often lead to delays, errors, and dissatisfaction. This paper proposes a quick-witted, intelligent order-handling system utilizing the Internet of Things (IoT) to address these challenges and enhance the overall dining experience. We present a comprehensive approach to developing and implementing an IoT-based automated order-handling system tailored to restaurants' specific needs and challenges in developing countries, highlighting the importance of technology in enhancing operational efficiency and customer satisfaction. The proposed automated secure order-handling system using IoT demonstrates significant potential for improving efficiency and customer satisfaction in the dining sector. By addressing common problems through advanced technology, this system offers a sustainable solution that enhances the dining experience while ensuring food orders' validity, quality, and privacy. We analyzed the potential impact of implementing such a system in developing countries, focusing on economic and operational benefits.

The Impact of Modified Atmosphere Storage Treatment on Glucose Levels and Mass Transfer Coefficients: A Study Based on Fruit Skin Thickness

Agri Suwandi, Wina Libyawati, Esti Mulatsari — Thu, 06 Jun 2024 00:00:00 +0700

Modified atmosphere storage (MAS) has been proven for decades able to decelerate the respirate rate of fruits. The sluggish respirate rate increases the shelf life of fruits. The after-effects of MAS treatment have been investigated from the installation design until gas composition in the storage, however the investigation about the correlation between the treatment level and the fruits characteristic is still limited on the flavor, color, and weight. Therefore, the research goal is to investigate the MAS treatment result based on skin thickness. A series of experiments with full factorial arrangement and three replications, is set in a storage installation. Skin thickness is classified in to three levels, which are thin, medium, and thick. Each level is represented respectively by orange, banana, and watermelon. Both fruits with and without MAS treatment are quantified by measuring glucose level, to make a comparation. The outcome of the research from measurement shows fruits which undergo MAS treatment have lower glucose levels than the ones without the treatment, but the weight remains the same. The mass transfer coefficient with the thickness became a baseline for sudden exchange in the storage.

Identification of Landslide Hazard in Residential Area Kubang Tangah District, Sawahlunto

Thu, 06 Jun 2024 00:00:00 +0700

The residential area in Kubang Tangah, Sawahlunto, is an area that has the potential for significant landslide hazard. With rapid residential growth and environmental change, risks to the security and well-being of residents are becoming increasingly prominent. This research aims to identify factors that trigger landslide hazard and analyze potential risks in the residential context of Kubang Tangah. Analysis of regional geotechnical and topographic characteristics, land use modeling, and review of the impact of human activities on slope stability. The analysis method uses the Plaxis 2D program to obtain slope safety factors in the Kubang Tangah residential area, Sawahlunto. The research results show that residential areas in Kubang Tangah have a high level of landslide risk, influenced by slope, soil type, and changes in land use. Varying rainfall levels significantly contribute to the potential for landslide hazard. Mitigation recommendations are suggested to involve wise land use changes, strengthening infrastructure, and increasing public awareness of the dangers of landslides.

Malaria Disease Prediction Based on Convolutional Neural Networks

Dhrgam AL Kafaf, Noor N. Thamir, Samara S. AL-Hadithy — Thu, 06 Jun 2024 00:00:00 +0700

This study delves into the investigation of the efficacy of Convolutional Neural Networks (CNNs) in identifying malaria through the examination of cell images. The dataset employed encompasses a total of 27,558 images, harvested from the renowned Malaria Cell Images Dataset on Kaggle, encompassing cells of diverse nature. The architectonics of the CNN model is meticulously devised, comprising of six blocks and three interconnected blocks, thereby rendering an efficient extraction of features and subsequent classification of the cells. Creative paraphrasing: Various strategies such as dropout, batch normalization, and global average pooling are artfully utilized to refine and fortify the model, ensuring its robustness and adaptability. In order to confront the challenge of diminishing gradient and facilitate the attainment of convergence, the activation function known as Rectified Linear Unit (ReLU) is ingeniously employed. Assessing the efficacy of the model via a perplexity grid produces outcomes. Exhibiting a precision rate of 99.59%, a specificity measure of 99.69%, an Sensitivity of 99.40%, F1 Measurement of 99.44%, and a Precision of 99.48, it showcases its capacity to effectively distinguish betwixt malaria-afflicted cells and unafflicted cells. The focal point of this research highlights the substantial potential of CNNs in facilitating the automated identification of malaria using image analysis. By harnessing their unique architecture and regularization techniques, CNNs have the capability to enhance the results and potentially bring about better outcomes in areas with prevalent cases of malaria.

Modification of Load Calculation in The Dijkstra Algorithm to Achieve High Throughput and Low Latency on 5G Networks

Eko Kuncoro Adiyanto, Sri Wahjuni, Hendra Rahmawan — Thu, 06 Jun 2024 00:00:00 +0700

throughput for high-resolution remote video surveillance. 5G cellular network as today's most advanced wireless technology will be the perfect match for Agriculture 4.0 requirements. In its maturity process, the 5G network requires various optimizations, one of which is by making route algorithm calculation modifications in terms of determining the best route for a data packet from a data source to a data destination. To achieve this goal, it requires research in the form of experiments using network simulator. Software Define Network (SDN) as network programmability is used to modify route in Dijkstra algorithm calculation, and run several use case that simulate 5G network characteristic. By adding bandwidth utilization and latency parameters into the routing algorithm calculations, 5G requirements such as packet loss below 1% and latency below 5ms are successfully achieved. These positive results may be further tested on real 5G networks, if in the future this research also gets positive results in testing on a real 5G network, then cellular network customers will be able to experience an increase in service quality.

Lean Knowledge Management in The Adoption of Traceability Technology For Halal Perishable Food Supply Chain: a Systematic Literature Review

Thu, 06 Jun 2024 00:00:00 +0700

This research was perfomed to provide a comprehensive Systematic Literature Review (SLR) on the mutually beneficial link between Lean and Knowledge Management (LKM). The primary focus was to highlight the crucial role of LKM as an enabler in empowering perishable food supply chains (PFSC) to effectively embrace traceability technology, ensuring the integrity of halal supply chains. The research was carried out using the SLR method and adhered to the procedures of the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA). In total, 65 articles from the Scopus database, published in various journals over 22 years were chosen, mapped, and evaluated. Furthermore, there were several featured forms of mutual collaboration between Lean and Knowledge Management (KM). The implementation of LKM in halal supply chain traceability for perishable food was still absent from the literature. Efficient (lean) KM processes for business actors turned knowledge into added value for the PFSC. The vital role of LKM as an enabler for PFSC in adopting traceability technology, which is characterized as fast-changing technology and highly knowledge-centric, is by eliminating wasteful knowledge so could advance responsiveness, efficiency, and flexibility. Considering the important role of LKM as an enabler of PFSC to address complex challenges in traceability technology adoption, collaborative interdisciplinary research is needed. Academic publications exploring the incorporation of lean and KM in the context of PFSC were relatively scarce. This SLR represented one of the pioneering efforts to investigate the amalgamation and its potential to overcome obstacles and inhibitors in the adoption of traceability technology.

Analysing The Causes of Management and Production Delays in The Implementation of Construction Project Work

Putri Lynna Luthan, Nathanael Sitanggang, Syahreza Alvan, Wisnu Prayogo — Thu, 06 Jun 2024 00:00:00 +0700

This study aims to analyse the causes of delays in the implementation of construction projects caused by management (owners/consultants) and production (contractors). The research sample consists of 56 respondents who are directly involved in the implementation of construction projects (owners, consultants, contractors, field supervisors, and estimators). The quantitative data analysis technique used was descriptive analysis technique, while the qualitative data obtained by interviewing 5 construction project experts was analysed by qualitative descriptive method. To analyse the causes of delays in project implementation, an analysis technique using the Relative Importance Index (RII) formula was used with a reference value of RII> 0.710. The results showed that 1) the average RII on management factors was 0.895> 0.710. This means that management factors (owner/consultant) can cause delays in the implementation of construction projects; 2) the average RII on production factors is 0.917> 0.710. This means that production factors (contractors) can cause delays in the implementation of construction projects. This means that production factors (contractors) can cause delays in the implementation of construction projects. This research is directly useful for construction service providers and contributes to the development of Project / Construction Management science.

Preparation, Synthesis and Characterization of La(1-x)Sr(x)MnO3 Alloy

Thu, 06 Jun 2024 00:00:00 +0700

Magnetic particles have been used for hyperthermia by inserting ferromagnetic material into tumor tissue. La_(1-x)Sr_(x)MnO₃ is one of the best candidates for hyperthermia due to higher magnetic at ambient temperature and their Curie temperature easily adjusted. This research synthesized La_(1-x)Sr_(x)MnO₃ using the ball milling technique. Several heat treatments were also conducted after ball milling processing. Various investigations, including SEM-EDS, XRD, DSC, and VSM, were conducted. LaMnO₃ has a hexagonal structure, which has the space group R -3 c. From the diffraction pattern seen in LaMnO₃ and La_0.9Sr_0.1MnO₃ seen at angles 32.376 and 32.706, it looks separate like the database diffraction pattern. In La_0.9Sr_0.1MnO₃, these two peaks are seen to be increasingly separated. In contrast to the diffraction patterns of La_0.7Sr_0.3MnO₃ and La_0.5Sr_0.5MnO₃ at an angle of 32.376, there is a decrease in intensity. The specific heat capacity of the alloy with Sr substitution of 0.3 has a greater value than that without substitution and the lowest occurs in the alloy with Sr substitution of 0.1. The magnetization value for Sr substitution is 0.3 higher than for other alloys.

Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)

Qaswaa Khaled Abood — Thu, 06 Jun 2024 00:00:00 +0700

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was adopted, which is considered a challenge for researchers because it includes different age groups. Many diseases, and the results obtained by the system were 96% accurate.