Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.1969
H. Maghfiroh, Joko Slamet Saputro, Berlian Shanaza Andiany, C. Hermanu, Miftahul Anwar, Muhammad Nizam, A. Ma’arif
This research enhances Smart Home Systems by integrating an Automatic Transfer Switch (ATS) for seamless power source switching between the grid and a backup battery, ensuring uninterrupted operation during power disruptions. An Automatic Battery Charging (ABC) system optimizes battery charging based on its condition, improving energy storage and efficiency. The system provides on-site electrical equipment control and sensor data access via a Human Machine Interface (HMI). Remote monitoring and control through the Blynk app offer convenience. Additionally, an energy consumption estimation feature allows users to estimate billing costs, with the Battery State of Charge (SoC) indicating the remaining battery capacity. Hardware testing showed the system's reliability with a 2-4 second ATS response and ±2-second ABC response. This research offers homeowners reliable power continuity and energy optimization. It contributes to IoT-based smart home systems, demonstrating ATS and ABC effectiveness, advancing both theory and practice for modern smart living.
{"title":"Smart Home System With Battery Backup and Internet of Things","authors":"H. Maghfiroh, Joko Slamet Saputro, Berlian Shanaza Andiany, C. Hermanu, Miftahul Anwar, Muhammad Nizam, A. Ma’arif","doi":"10.37385/jaets.v5i1.1969","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.1969","url":null,"abstract":"This research enhances Smart Home Systems by integrating an Automatic Transfer Switch (ATS) for seamless power source switching between the grid and a backup battery, ensuring uninterrupted operation during power disruptions. An Automatic Battery Charging (ABC) system optimizes battery charging based on its condition, improving energy storage and efficiency. The system provides on-site electrical equipment control and sensor data access via a Human Machine Interface (HMI). Remote monitoring and control through the Blynk app offer convenience. Additionally, an energy consumption estimation feature allows users to estimate billing costs, with the Battery State of Charge (SoC) indicating the remaining battery capacity. Hardware testing showed the system's reliability with a 2-4 second ATS response and ±2-second ABC response. This research offers homeowners reliable power continuity and energy optimization. It contributes to IoT-based smart home systems, demonstrating ATS and ABC effectiveness, advancing both theory and practice for modern smart living.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.3247
Krishna Priya M, A. G
A routing protocol used in heterogeneous transport networks for low-power, lossy networks. This is a routing protocol for wireless networks. This protocol follows the same specifications as Zigbee, 6 lopan is IEEE 802.15. 4 Enables both many-to-one and one-to-one communication. To address the need for enhancing in this study proposes a novel methodology called RPL-PG (Routing Protocol for Low-Power and Lossy Networks Priority Generation). Initially sensors like Temperature, Humidity, Vibration, Proximity, Gas and Current Monitoring Sensors are used for smart manufacturing. Consequently, Destination Oriented Directed Acyclic Graph (DODAG) is used for RPL configuration. Based on selected RPL configuration the priority is generated using assign priority count and priority-based queuing. Finally, Fuzzy rules are used to select the RPL path and then update the DODAG finally reached the destination. The study involves setting up a simulated environment using appropriate tools, such as MATLAB. Experimental findings evaluate and compares performance measures, such as Energy Consumption, Network Life Time, Packet Loss Ratio, Packet Delivery Ratio (PDR), E2E Delay, and Network Throughput. The Energy Consumption of the proposed RPL-PG method achieves 43.6 % lower than 38 % and 35.8 % in terms of OMC-RPL and RMA-RP respectively.
{"title":"Priority RPL for IOT Based Smart Manufacturing Industries","authors":"Krishna Priya M, A. G","doi":"10.37385/jaets.v5i1.3247","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.3247","url":null,"abstract":"A routing protocol used in heterogeneous transport networks for low-power, lossy networks. This is a routing protocol for wireless networks. This protocol follows the same specifications as Zigbee, 6 lopan is IEEE 802.15. 4 Enables both many-to-one and one-to-one communication. To address the need for enhancing in this study proposes a novel methodology called RPL-PG (Routing Protocol for Low-Power and Lossy Networks Priority Generation). Initially sensors like Temperature, Humidity, Vibration, Proximity, Gas and Current Monitoring Sensors are used for smart manufacturing. Consequently, Destination Oriented Directed Acyclic Graph (DODAG) is used for RPL configuration. Based on selected RPL configuration the priority is generated using assign priority count and priority-based queuing. Finally, Fuzzy rules are used to select the RPL path and then update the DODAG finally reached the destination. The study involves setting up a simulated environment using appropriate tools, such as MATLAB. Experimental findings evaluate and compares performance measures, such as Energy Consumption, Network Life Time, Packet Loss Ratio, Packet Delivery Ratio (PDR), E2E Delay, and Network Throughput. The Energy Consumption of the proposed RPL-PG method achieves 43.6 % lower than 38 % and 35.8 % in terms of OMC-RPL and RMA-RP respectively.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.3041
Silviana Nur Faizah, Lia Nur Atiqoh Bela Dina, Ari Kartiko, Muhammad Anas Ma`arif, Moch. Sya'roni Hasan
Phet simulation is a computer-based practicum simulation medium that helps to increase students’ engagement and understanding through concept visualization. Even though there have been numerous studies on the Technology Acceptance Model (TAM) related to Phet simulation, the TAM study of Phet simulation combined with certain learning methods is rarely observed. We propose an advanced version of TAM by including the external variables of system quality, user characteristics, and instructor. This study is a quantitative design with a descriptive, explanatory type. This model was tested using an online questionnaire disseminated to 49 students that finished taking basic natural sciences subjects using Phet simulation based on problem-based learning. The result showed that system quality has an effect on perceived usefulness, perceived ease of use has an effect on behavioral intention of use, behavioral intention of use has an effect on actual usage, and there is no relationship between instructor quality on perceived usefulness. Grit on perceived ease of use, learner anxiety, and perceived usefulness on the behavioral intention of use. These findings have implications regarding user acceptance of Phet simulation combined with certain learning methods, specifically problem-based learning.
{"title":"Student Acceptance Study of PhET Simulation with an Expanded Technology Acceptance Model Approach","authors":"Silviana Nur Faizah, Lia Nur Atiqoh Bela Dina, Ari Kartiko, Muhammad Anas Ma`arif, Moch. Sya'roni Hasan","doi":"10.37385/jaets.v5i1.3041","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.3041","url":null,"abstract":"Phet simulation is a computer-based practicum simulation medium that helps to increase students’ engagement and understanding through concept visualization. Even though there have been numerous studies on the Technology Acceptance Model (TAM) related to Phet simulation, the TAM study of Phet simulation combined with certain learning methods is rarely observed. We propose an advanced version of TAM by including the external variables of system quality, user characteristics, and instructor. This study is a quantitative design with a descriptive, explanatory type. This model was tested using an online questionnaire disseminated to 49 students that finished taking basic natural sciences subjects using Phet simulation based on problem-based learning. The result showed that system quality has an effect on perceived usefulness, perceived ease of use has an effect on behavioral intention of use, behavioral intention of use has an effect on actual usage, and there is no relationship between instructor quality on perceived usefulness. Grit on perceived ease of use, learner anxiety, and perceived usefulness on the behavioral intention of use. These findings have implications regarding user acceptance of Phet simulation combined with certain learning methods, specifically problem-based learning.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.2248
Rizky Aulia Rahman, D. N. Ramadan, S. Hadiyoso, Siti Sarah Maidin, I. D. Irawati
Oyster mushroom (Pleurotus Ostreatus) is a fungus-like plant that is often cultivated in Indonesian agriculture. Oyster mushroom is raised by manipulating environmental parameters, so that it can grow in the provided Kumbung. Oyster mushroom requires a temperature that is used, which ranges from 23°-28°C, for humidity used between 70% -90% and for light intensity it requires light of ±300 lux. In this study, a system was designed to carry out automatic monitoring and control in real time based on the Internet of Things (IoT) which integrates DHT22 humidity and temperature sensors, BH1750 light intensity sensors and NodeMCU as a microcontroller with measurement results sent to the Firebase database. In addition, a water pump connected to the sprayer nozzle is installed in this system to maintain the humidity of the oyster mushroom curd. From the test results, the system can work automatically to stabilize temperature, humidity, and light intensity according to the ideal parameters.
{"title":"A Smart Kumbung For Monitoring and Controlling Environment in Oyster Mushroom Cultivation Based on Internet of Things Framework","authors":"Rizky Aulia Rahman, D. N. Ramadan, S. Hadiyoso, Siti Sarah Maidin, I. D. Irawati","doi":"10.37385/jaets.v5i1.2248","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.2248","url":null,"abstract":"Oyster mushroom (Pleurotus Ostreatus) is a fungus-like plant that is often cultivated in Indonesian agriculture. Oyster mushroom is raised by manipulating environmental parameters, so that it can grow in the provided Kumbung. Oyster mushroom requires a temperature that is used, which ranges from 23°-28°C, for humidity used between 70% -90% and for light intensity it requires light of ±300 lux. In this study, a system was designed to carry out automatic monitoring and control in real time based on the Internet of Things (IoT) which integrates DHT22 humidity and temperature sensors, BH1750 light intensity sensors and NodeMCU as a microcontroller with measurement results sent to the Firebase database. In addition, a water pump connected to the sprayer nozzle is installed in this system to maintain the humidity of the oyster mushroom curd. From the test results, the system can work automatically to stabilize temperature, humidity, and light intensity according to the ideal parameters.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.2503
Arif Ridho Lubis, Habibi Ramdani Safitri, I. Irvan, M. Lubis, A. Al-Khowarizmi
In the natural language processing field, there are several sub-fields that are very closely related to information retrieval, such as the automatic text summarization sub-field. obtained from the convolutional T5 and Seq2Seq models in summarizing text on hugging faces found features that can affect text summary such as upper- and lower-case letters which have an impact on changing the understanding of the text of the document. This study uses a combination of parameters such as layer dimensions, learning rate, batch size, and the use of Dropout to avoid model overfitting. The results can be seen by evaluating metrics using ROUGE. This study produces a value of ROUGE-1 on 4 documents that are tested which produces an average of 0.8 which is the optimal value, for ROUGE-2 on 4 documents that are tested which results in an average of 0.83 which is an optimal value while ROUGE-L on 4 documents conducted tests that produce an average of 0.8 which is the optimal value for the summary model.
{"title":"Improving Text Summarization Quality by Combining T5-Based Models and Convolutional Seq2Seq Models","authors":"Arif Ridho Lubis, Habibi Ramdani Safitri, I. Irvan, M. Lubis, A. Al-Khowarizmi","doi":"10.37385/jaets.v5i1.2503","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.2503","url":null,"abstract":"In the natural language processing field, there are several sub-fields that are very closely related to information retrieval, such as the automatic text summarization sub-field. obtained from the convolutional T5 and Seq2Seq models in summarizing text on hugging faces found features that can affect text summary such as upper- and lower-case letters which have an impact on changing the understanding of the text of the document. This study uses a combination of parameters such as layer dimensions, learning rate, batch size, and the use of Dropout to avoid model overfitting. The results can be seen by evaluating metrics using ROUGE. This study produces a value of ROUGE-1 on 4 documents that are tested which produces an average of 0.8 which is the optimal value, for ROUGE-2 on 4 documents that are tested which results in an average of 0.83 which is an optimal value while ROUGE-L on 4 documents conducted tests that produce an average of 0.8 which is the optimal value for the summary model.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.3211
Ummu Ajirah Abdul Rauf, Nusra Izzaty Aziz, Nor Amirah Syairah Zulkarnaini, Mazzlida Mat Deli, Maryam Jamilah Asha’ari, ‘Ainul Huda Jamil, Siti Intan Nurdiana Wong Abdullah
In management practise and research, the university-maritime industry collaborations (UMICs) have grown in significance. This trend is reinforced by the necessity for innovation in the current industry environment and the desire of policymakers to commercialise knowledge from academia. Much less is known about these collaborations, although significant research efforts have been made to identify the success factors for these collaborations. Therefore, the aim of this study is to identify and explore the key factors that strengthen UMICs and propose a framework to enhance collaboration, so that a research agenda for the future will be developed based on an assessment of the existing literature. This study adopted a method of systematic literature review using published and unpublished theoretical literature to conduct analysis using five research databases in order to propose a framework aimed at identifying the key factors to strengthen UMICs. The findings of this study concluded that effective communication, trust, and adequate fund resources are essential for UMICs to succeed. Open communication channels, mutual trust, and shared vision can help build strong partnerships, while adequate funding can support research and development of new technologies, practices, and solutions. Based on previous research, none of them treated combined fund resources, effective communication, and trust as an independent variables towards UMICs relationship specifically. Hence, this study fills the gap by proposing a framework to test the relationship between fund resources, effective communication, and trust towards UMICs. Thus, the proposed framework can be used as a benchmark to strengthen UMICs in the future. This study also will encourage the managers in the maritime industry to drive innovation, establish strategic collaborations, actively involve stakeholders, and foster innovation and economic growth in the maritime industry to strengthen UMICs. The existing limited body of knowledge and literature will also benefit from this study.
{"title":"Strengthening the University-Maritime Industry Collaborations (UMICs): Technology Issues","authors":"Ummu Ajirah Abdul Rauf, Nusra Izzaty Aziz, Nor Amirah Syairah Zulkarnaini, Mazzlida Mat Deli, Maryam Jamilah Asha’ari, ‘Ainul Huda Jamil, Siti Intan Nurdiana Wong Abdullah","doi":"10.37385/jaets.v5i1.3211","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.3211","url":null,"abstract":"In management practise and research, the university-maritime industry collaborations (UMICs) have grown in significance. This trend is reinforced by the necessity for innovation in the current industry environment and the desire of policymakers to commercialise knowledge from academia. Much less is known about these collaborations, although significant research efforts have been made to identify the success factors for these collaborations. Therefore, the aim of this study is to identify and explore the key factors that strengthen UMICs and propose a framework to enhance collaboration, so that a research agenda for the future will be developed based on an assessment of the existing literature. This study adopted a method of systematic literature review using published and unpublished theoretical literature to conduct analysis using five research databases in order to propose a framework aimed at identifying the key factors to strengthen UMICs. The findings of this study concluded that effective communication, trust, and adequate fund resources are essential for UMICs to succeed. Open communication channels, mutual trust, and shared vision can help build strong partnerships, while adequate funding can support research and development of new technologies, practices, and solutions. Based on previous research, none of them treated combined fund resources, effective communication, and trust as an independent variables towards UMICs relationship specifically. Hence, this study fills the gap by proposing a framework to test the relationship between fund resources, effective communication, and trust towards UMICs. Thus, the proposed framework can be used as a benchmark to strengthen UMICs in the future. This study also will encourage the managers in the maritime industry to drive innovation, establish strategic collaborations, actively involve stakeholders, and foster innovation and economic growth in the maritime industry to strengthen UMICs. The existing limited body of knowledge and literature will also benefit from this study.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.3019
Dita Putri Purnama, Anas Hidayat, M. K. Afdhol, Fiki Hidayat
Biopolymer from Green Grass Jelly Leaves attracts attention due to its friendlier environmental profile and cost-effectiveness in providing raw materials. This research aims to explore the potential of biopolymers from Green Grass Jelly Leaves as an alternative to synthetic polymers in an effort to increase oil recovery involving sequential pretreatment, extraction, and characterization stages to obtain essential pectin compounds. This experiment centers on a biopolymer sourced from Green Grass Jelly Leaves, involving sequential steps of pretreatment, extraction, and characterization to obtain essential pectin compounds. Characterization employed scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). The recorded peak viscosity for Green Grass Jelly Leaves biopolymer was 2.04 cp at 3000 ppm concentration, contrasting with pectin's 1.98 cp viscosity. In comparison, industrial biopolymer Xanthan Gum displayed significantly higher viscosity at 95.01 cp for 3000 ppm concentration. Thermal stability assessment under reservoir conditions (30°C and 60°C) demonstrated that Green Grass Jelly Leaves biopolymer pectin exhibited peak viscosities of 55.29 cP and 51.77 cP at 3000 ppm concentration, respectively. These results show that the comparison between biopolymer and synthetic polymer is not too far and there is an increase in viscosity as the concentration increases, which can increase sweep efficiency.
{"title":"Extraction of Green Grass Jelly Leaves as An Alternative Biopolymer in Polymer Flooding","authors":"Dita Putri Purnama, Anas Hidayat, M. K. Afdhol, Fiki Hidayat","doi":"10.37385/jaets.v5i1.3019","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.3019","url":null,"abstract":"Biopolymer from Green Grass Jelly Leaves attracts attention due to its friendlier environmental profile and cost-effectiveness in providing raw materials. This research aims to explore the potential of biopolymers from Green Grass Jelly Leaves as an alternative to synthetic polymers in an effort to increase oil recovery involving sequential pretreatment, extraction, and characterization stages to obtain essential pectin compounds. This experiment centers on a biopolymer sourced from Green Grass Jelly Leaves, involving sequential steps of pretreatment, extraction, and characterization to obtain essential pectin compounds. Characterization employed scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). The recorded peak viscosity for Green Grass Jelly Leaves biopolymer was 2.04 cp at 3000 ppm concentration, contrasting with pectin's 1.98 cp viscosity. In comparison, industrial biopolymer Xanthan Gum displayed significantly higher viscosity at 95.01 cp for 3000 ppm concentration. Thermal stability assessment under reservoir conditions (30°C and 60°C) demonstrated that Green Grass Jelly Leaves biopolymer pectin exhibited peak viscosities of 55.29 cP and 51.77 cP at 3000 ppm concentration, respectively. These results show that the comparison between biopolymer and synthetic polymer is not too far and there is an increase in viscosity as the concentration increases, which can increase sweep efficiency.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.2806
Fatima Esmail Sadeq, Ziyad Tariq Mustafa Al-Ta’i
Identifying people at distance is an important task in daily life Because of the increase in terrorism. Biometrics is a better solution to overcome personal identity problems, and this applies to soft biometrics also. Soft biometric are features that can be extracted remotely and do not require cooperation with people. This paper introduces a comparison between human face recognition and human gait recognition using soft biometric features. Nine face attributes and nine gait attributes are taken from a dataset built by researchers. The constructed dataset is composed from (66) videos for (33) persons. Features are extracted using Haar and MediaPipe methods. The extracted features are classified using enhanced convolutional neural network. This work achieves an accuracy of 95.832% in human face recognition and an accuracy of 89.583% in human gait recognition. From the above results it turns out that the proposed method achieved promising results with regard to Recognize people remotely
{"title":"Comparison Between Face and Gait Human Recognition Using Enhanced Convolutional Neural Network","authors":"Fatima Esmail Sadeq, Ziyad Tariq Mustafa Al-Ta’i","doi":"10.37385/jaets.v5i1.2806","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.2806","url":null,"abstract":"Identifying people at distance is an important task in daily life Because of the increase in terrorism. Biometrics is a better solution to overcome personal identity problems, and this applies to soft biometrics also. Soft biometric are features that can be extracted remotely and do not require cooperation with people. This paper introduces a comparison between human face recognition and human gait recognition using soft biometric features. Nine face attributes and nine gait attributes are taken from a dataset built by researchers. The constructed dataset is composed from (66) videos for (33) persons. Features are extracted using Haar and MediaPipe methods. The extracted features are classified using enhanced convolutional neural network. This work achieves an accuracy of 95.832% in human face recognition and an accuracy of 89.583% in human gait recognition. From the above results it turns out that the proposed method achieved promising results with regard to Recognize people remotely","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.3413
Tamara Hameed Yousiaf, Mohammed S. H. Al-Tamimi
The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.
{"title":"The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review","authors":"Tamara Hameed Yousiaf, Mohammed S. H. Al-Tamimi","doi":"10.37385/jaets.v5i1.3413","DOIUrl":"https://doi.org/10.37385/jaets.v5i1.3413","url":null,"abstract":"The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139184583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-10DOI: 10.37385/jaets.v5i1.1785
Fitri Ayu, G. Ganefri, Dedy Irfan, A. Huda, Des Suryani
Learning Graphic Design requires a high level of visualization, especially for design concepts or 3D interior design. If this material is only taught through guided practice in class, the learning outcomes will certainly not be optimal, especially for vocational graduates in the current digital era. The research aims to test the practicality of digital learning applications based on augmented reality technology as a learning medium for 3D interior graphic design. The type of research is Research and Development (R&D) with the Borg and Gall Method, data collection techniques using Likert scale questionnaires, applications built using Blender for modelling, Unity 3D for Augmented Reality Implementation, Android Studio for designing applications, Firebase for database storage, and Fiqma to design the interface design. This research produces a digital learning application that is used for learning 3D interior graphic design which is equipped with learning needs such as classrooms, and communication rooms and is based on Augmented Reality technology so that the resulting interior design objects can be displayed in real-time. Aiken's V formula is used to test the practicality of digital learning applications. The research results showed that the average Aiken's V score from lecturers was 85.22% in the practical category, and students in the small group test was 82.96% and students in the large group test was 83.04% in the practical category. So, it can be concluded that the use of the DiGi.AR application based on Augmented Reality is good and practical for learning 3D graphic design.
学习平面设计需要较高的可视化水平，尤其是设计概念或三维室内设计。如果仅通过课堂上的指导练习来教授这些材料，学习效果肯定不会理想，尤其是对于当前数字化时代的职业毕业生而言。本研究旨在测试基于增强现实技术的数字化学习应用作为三维室内平面设计学习媒介的实用性。研究类型为研究与开发（R&D），采用博格法（Borg）和盖尔法（Gall Method），数据收集技术采用李克特量表调查问卷，应用软件构建采用 Blender 建模，Unity 3D实现增强现实，Android Studio设计应用软件，Firebase存储数据库，Fiqma设计界面设计。这项研究制作了一个数字学习应用程序，用于学习三维室内平面设计，该应用程序配备了教室和交流室等学习需求，并基于增强现实技术，使生成的室内设计对象可以实时显示。艾肯 V 公式用于检验数字化学习应用的实用性。研究结果表明，讲师在实用性类别中的平均艾肯 V 得分为 85.22%，学生在小组测试中的平均艾肯 V 得分为 82.96%，学生在大组测试中的平均艾肯 V 得分为 83.04%。因此，可以得出结论，使用基于增强现实技术的 DiGi.AR 应用程序学习三维平面设计具有良好的实用性。
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