In this paper, a decision support system (DSS) is provided to assist the decision-maker in obtaining the best solution for the transportation problem under uncertainty. Fuzzy parameters of the transportation problem are presented by pentagonal fuzzy numbers. The centroid ranking function transforms these pentagonal fuzzy numbers into crisp ones. Then, a novel, improved greedy method named Dhouib-Matrix-TP1 (DM-TP1) is used in order to help the decision-maker promptly find a suitable solution. Specifically, this DSS is composed of three components: the data base component considers a pentagonal fuzzy number; the Model Base component thinks through the original heuristic DM-TP1; and the User Interface component deliberates the convivial graphical output of the generated transportation plan solution using the Python programming language. Experiments in the literature on fuzzy transportation problems show that the novel proposed heuristic, DM-TP1, is easy to understand and allows the decision-maker to handle transportation problems under pentagonal fuzzy numbers. Also, the DM-TP1 is robust and can be applied to find a feasible initial solution in less time.
{"title":"Decision support system using Dhouib-Matrix-TP1 heuristic for pentagonal fuzzy transportation problem","authors":"Souhail Dhouib, Aïda Kharrat, Saima Dhouib, Tole Sutikno","doi":"10.11591/ijeecs.v35.i1.pp642-654","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp642-654","url":null,"abstract":"In this paper, a decision support system (DSS) is provided to assist the decision-maker in obtaining the best solution for the transportation problem under uncertainty. Fuzzy parameters of the transportation problem are presented by pentagonal fuzzy numbers. The centroid ranking function transforms these pentagonal fuzzy numbers into crisp ones. Then, a novel, improved greedy method named Dhouib-Matrix-TP1 (DM-TP1) is used in order to help the decision-maker promptly find a suitable solution. Specifically, this DSS is composed of three components: the data base component considers a pentagonal fuzzy number; the Model Base component thinks through the original heuristic DM-TP1; and the User Interface component deliberates the convivial graphical output of the generated transportation plan solution using the Python programming language. Experiments in the literature on fuzzy transportation problems show that the novel proposed heuristic, DM-TP1, is easy to understand and allows the decision-maker to handle transportation problems under pentagonal fuzzy numbers. Also, the DM-TP1 is robust and can be applied to find a feasible initial solution in less time.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"39 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141704908","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp583-592
Fikri Budiman, E. Sugiarto, Novi Hendriyanto
Image retrieval methods are currently developing towards big data processing. The literature review is focused on image big data extraction with cultural heritage domain as training and testing datasets. The development of image retrieval process starts from content-based using machine algorithms, deep learning to ontology-based. Image recognition research with cultural heritage domain is conducted because of the importance of preserving and appreciating cultural heritage, in this case, cultural heritage images such as Indonesian Batik are discussed. Batik motif images are Indonesian cultural heritage that has thousands of motifs that are grouped into many classes with a non-linear hyperplane. The problem is focused on processing big data that has many classes. Currently research is evolving into knowledge-based image retrieval using ontologies due to semantic gap constraints. The results of this literature study can be the basis for developing research on the application of appropriate deep learning algorithms so as to utilize the hierarchy of classes and subclasses of image ontologies with cultural heritage domains.
{"title":"Review on integration of ontology and deep learning in cultural heritage image retrieval","authors":"Fikri Budiman, E. Sugiarto, Novi Hendriyanto","doi":"10.11591/ijeecs.v35.i1.pp583-592","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp583-592","url":null,"abstract":"Image retrieval methods are currently developing towards big data processing. The literature review is focused on image big data extraction with cultural heritage domain as training and testing datasets. The development of image retrieval process starts from content-based using machine algorithms, deep learning to ontology-based. Image recognition research with cultural heritage domain is conducted because of the importance of preserving and appreciating cultural heritage, in this case, cultural heritage images such as Indonesian Batik are discussed. Batik motif images are Indonesian cultural heritage that has thousands of motifs that are grouped into many classes with a non-linear hyperplane. The problem is focused on processing big data that has many classes. Currently research is evolving into knowledge-based image retrieval using ontologies due to semantic gap constraints. The results of this literature study can be the basis for developing research on the application of appropriate deep learning algorithms so as to utilize the hierarchy of classes and subclasses of image ontologies with cultural heritage domains.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"28 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141713890","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp32-41
A. Senen, Arif Kurniawan, Hasna Satya Dini, Dwi Anggaini
The Timor system is one of the large systems in the East Nusa Tenggara region. Based on the general plan for electricity supply for 2021-2030, there is a plan to interconnect a 2x11 MW wind power plant. The addition of wind power plants will pose a considerable threat to the system due to the intermittency nature of renewable energy plants. Therefore, a comprehensive grid impact study is needed to convince network managers that adding wind farms will not cause disruptions to the system either locally or in general and is expected to strengthen the electricity system. The power flow simulation results, installing a 2x11 MW wind farm on the Timor system can improve voltage quality and reduce losses on both 70 and 150 kV systems. For transient stability, the frequency value on the Timor system still meets the grid code requirements. In addition, the simulation results of the intermittency impact of the wind power plant output show that the Timor system is still in a stable condition. The stability of the rotor angle of the existing power plant when the transient stability simulation is carried out shows that it is still in a balanced condition.
{"title":"Grid impact analysis on wind power plant interconnection in strengthening electricity systems","authors":"A. Senen, Arif Kurniawan, Hasna Satya Dini, Dwi Anggaini","doi":"10.11591/ijeecs.v35.i1.pp32-41","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp32-41","url":null,"abstract":"The Timor system is one of the large systems in the East Nusa Tenggara region. Based on the general plan for electricity supply for 2021-2030, there is a plan to interconnect a 2x11 MW wind power plant. The addition of wind power plants will pose a considerable threat to the system due to the intermittency nature of renewable energy plants. Therefore, a comprehensive grid impact study is needed to convince network managers that adding wind farms will not cause disruptions to the system either locally or in general and is expected to strengthen the electricity system. The power flow simulation results, installing a 2x11 MW wind farm on the Timor system can improve voltage quality and reduce losses on both 70 and 150 kV systems. For transient stability, the frequency value on the Timor system still meets the grid code requirements. In addition, the simulation results of the intermittency impact of the wind power plant output show that the Timor system is still in a stable condition. The stability of the rotor angle of the existing power plant when the transient stability simulation is carried out shows that it is still in a balanced condition.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"103 S2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141696038","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp292-300
M. V. Unni, J. S., Jacob Joseph Kalapurackal, Saba Fatma
Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision.
{"title":"Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles","authors":"M. V. Unni, J. S., Jacob Joseph Kalapurackal, Saba Fatma","doi":"10.11591/ijeecs.v35.i1.pp292-300","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp292-300","url":null,"abstract":"Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"36 S2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141698366","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp601-609
Chaitra Soppinahally Nataraju, D. K. Sreekantha, K. Sairam
Wireless body area networks (WBANs), featuring wearable and implantable devices for collecting physiological data are increasingly critical in healthcare for enabling continuous remote monitoring, diagnostic improvements, and treatment optimization. Secure communication within WBANs is essential to protect sensitive health data from unauthorized access and manipulation. This paper introduces a novel secure digital (SD)- human body communication (HBC) Transceiver (TR) system, tailored for WBAN applications, that prioritizes security and offers significant enhancements in size, power efficiency, speed, and data transmission efficiency over current solutions. Leveraging a combination of frequency-selective (FS) digital transmission with walsh codes (WCs) or quadrature amplitude modulation (QAM), and incorporating one-round encryption and decryption modules, the system complies with the IEEE 802.15.6 standard, ensuring broad compatibility. Specifically, the QAM-based SD-HBC TR system exhibits a 4% reduction in chip area, a 7.6% increase in operating frequency, a 3.4% decrease in power consumption, a 27.5% reduction in latency, and improvements of 33% in throughput and 35.5% in efficiency. Importantly, it achieves a bit error rate (BER) of up to 10-8 , demonstrating high reliability across communication methods. This research significantly advances secure communication in WBANs, offering a promising approach for enhancing the reliability, efficiency, and security of healthcare monitoring technologies.
{"title":"Hardware-realized secure transceiver for human body communication in wireless body area networks","authors":"Chaitra Soppinahally Nataraju, D. K. Sreekantha, K. Sairam","doi":"10.11591/ijeecs.v35.i1.pp601-609","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp601-609","url":null,"abstract":"Wireless body area networks (WBANs), featuring wearable and implantable devices for collecting physiological data are increasingly critical in healthcare for enabling continuous remote monitoring, diagnostic improvements, and treatment optimization. Secure communication within WBANs is essential to protect sensitive health data from unauthorized access and manipulation. This paper introduces a novel secure digital (SD)- human body communication (HBC) Transceiver (TR) system, tailored for WBAN applications, that prioritizes security and offers significant enhancements in size, power efficiency, speed, and data transmission efficiency over current solutions. Leveraging a combination of frequency-selective (FS) digital transmission with walsh codes (WCs) or quadrature amplitude modulation (QAM), and incorporating one-round encryption and decryption modules, the system complies with the IEEE 802.15.6 standard, ensuring broad compatibility. Specifically, the QAM-based SD-HBC TR system exhibits a 4% reduction in chip area, a 7.6% increase in operating frequency, a 3.4% decrease in power consumption, a 27.5% reduction in latency, and improvements of 33% in throughput and 35.5% in efficiency. Importantly, it achieves a bit error rate (BER) of up to 10-8 , demonstrating high reliability across communication methods. This research significantly advances secure communication in WBANs, offering a promising approach for enhancing the reliability, efficiency, and security of healthcare monitoring technologies.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"254 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141711627","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp397-404
Reshma Nadaf, Satish S. Bhairannawar
The importance of crucial current technical advancements, particularly those centered on the cryptography process such as Cryptographic advanced encryption standard (AES) hardware architectures are gaining momentum with respect to improving the speed and area optimizations. In this paper, we have proposed a novel architecture to implement AES on a reconfigurable hardware i.e., field programmable gate arrays (FPGA). The controller in AES algorithm is responsible to generate the signals to perform operations to generate the 128 bits ciphertext. The proposed controller uses multiplexer and synchronous register-based approach to obtain area and speed efficient on the FPGA hardware. The entire architecture of AES with proposed controller is implemented on Virtex 5, Virtex 6, and Virtex 7series using XilinxISE 14.7 and tested for critical path delay, frequency, slices, efficiency and throughput. It is observed that all the parameters are improved compared to existing architectures achieving the throughput of 32.29, 40.01, and 43.01 Gbps respectively. The key benefit of this approach is the high level of parallelism it displays in a quick and efficient manner.
{"title":"An efficient controller-based architecture for AES algorithm using FPGA","authors":"Reshma Nadaf, Satish S. Bhairannawar","doi":"10.11591/ijeecs.v35.i1.pp397-404","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp397-404","url":null,"abstract":"The importance of crucial current technical advancements, particularly those centered on the cryptography process such as Cryptographic advanced encryption standard (AES) hardware architectures are gaining momentum with respect to improving the speed and area optimizations. In this paper, we have proposed a novel architecture to implement AES on a reconfigurable hardware i.e., field programmable gate arrays (FPGA). The controller in AES algorithm is responsible to generate the signals to perform operations to generate the 128 bits ciphertext. The proposed controller uses multiplexer and synchronous register-based approach to obtain area and speed efficient on the FPGA hardware. The entire architecture of AES with proposed controller is implemented on Virtex 5, Virtex 6, and Virtex 7series using XilinxISE 14.7 and tested for critical path delay, frequency, slices, efficiency and throughput. It is observed that all the parameters are improved compared to existing architectures achieving the throughput of 32.29, 40.01, and 43.01 Gbps respectively. The key benefit of this approach is the high level of parallelism it displays in a quick and efficient manner.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"59 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141716231","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp247-254
Mehmet Nasuhcan Türker, Taner Arsan
Ultra-wideband (UWB) technology is renowned for its exceptional performance in fast data transmission and precise positioning. However, it faces sensitivity challenges when the tagged object is not in direct line of sight, resulting in position inaccuracies. Applying the federated Kalman filter (FKF), this research focuses on mitigating position deviation induced by non-line-of-sight (NLOS) scenarios in UWB technology. The utilization of the FKF in NLOS scenarios has demonstrated a noteworthy reduction in position deviation. This study uses the FKF to analyze measurements taken under line-of-sight (LOS) and NLOS conditions within indoor settings. The outcomes of this study provide a promising foundation for future research endeavors in the field of UWB technology, emphasizing the potential for improved performance and accuracy in challenging operational environments.
{"title":"Improving non-line-of-sight situations in indoor positioning with ultra-wideband sensors via federated Kalman filter","authors":"Mehmet Nasuhcan Türker, Taner Arsan","doi":"10.11591/ijeecs.v35.i1.pp247-254","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp247-254","url":null,"abstract":"Ultra-wideband (UWB) technology is renowned for its exceptional performance in fast data transmission and precise positioning. However, it faces sensitivity challenges when the tagged object is not in direct line of sight, resulting in position inaccuracies. Applying the federated Kalman filter (FKF), this research focuses on mitigating position deviation induced by non-line-of-sight (NLOS) scenarios in UWB technology. The utilization of the FKF in NLOS scenarios has demonstrated a noteworthy reduction in position deviation. This study uses the FKF to analyze measurements taken under line-of-sight (LOS) and NLOS conditions within indoor settings. The outcomes of this study provide a promising foundation for future research endeavors in the field of UWB technology, emphasizing the potential for improved performance and accuracy in challenging operational environments.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141697587","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp133-139
Nashaat M. Hussain Hassan, Mahmoud A. Moussa, Mohamed Hassan M. Mahmoud
In recent times, companies and institutions globally are increasingly adopting automated systems for recording employee attendance due to the inefficiency and error-prone nature of traditional methods. Face recognition is the fastest, most natural, and most accurate way to identify someone, despite its difficulty. Remote deployment and control of the technology using internet of things (IoT) protocols provides real-time attendance data worldwide. We use the Haar-cascade algorithm to detect and extract features and the adaptive boost algorithm confused with convolutional neural network (CNN) algorithm to recognize the face in our proposed smart attendance system. Per frame, the proposed system recognizes multiple faces. Face recognition in 18 conditions was designed into the proposed system to ensure its versatility. The system's graphical user interface (GUI) was made for average users. This work is more important because IoT technology records student attendance and sends data to authorities. We use Raspberry Pi 4 and camera module for our suggested system. Python and OpenCV libraries tested the multiple face image recognition proposal in 18 situations under four conditions. Single-face image recognition was compared to other methods. In most cases, the proposed method was 100% accurate and outperformed related methods.
{"title":"CNN and Adaboost fusion model for multiface recognition based automated verification system of students attendance","authors":"Nashaat M. Hussain Hassan, Mahmoud A. Moussa, Mohamed Hassan M. Mahmoud","doi":"10.11591/ijeecs.v35.i1.pp133-139","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp133-139","url":null,"abstract":"In recent times, companies and institutions globally are increasingly adopting automated systems for recording employee attendance due to the inefficiency and error-prone nature of traditional methods. Face recognition is the fastest, most natural, and most accurate way to identify someone, despite its difficulty. Remote deployment and control of the technology using internet of things (IoT) protocols provides real-time attendance data worldwide. We use the Haar-cascade algorithm to detect and extract features and the adaptive boost algorithm confused with convolutional neural network (CNN) algorithm to recognize the face in our proposed smart attendance system. Per frame, the proposed system recognizes multiple faces. Face recognition in 18 conditions was designed into the proposed system to ensure its versatility. The system's graphical user interface (GUI) was made for average users. This work is more important because IoT technology records student attendance and sends data to authorities. We use Raspberry Pi 4 and camera module for our suggested system. Python and OpenCV libraries tested the multiple face image recognition proposal in 18 situations under four conditions. Single-face image recognition was compared to other methods. In most cases, the proposed method was 100% accurate and outperformed related methods.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"7 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141700739","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}
URL stands for uniform resource locator are the addresses of the unique resources on the internet. We all need URLs to access any type of resource on the internet, such as any web page, and document. Sometimes URLs can be long, irrelative and unattractive and unable to send sometimes via email. So, for this, we proposed a URL shortener web application based on the Python-Django platform which is fast and makes your long URLs in the shortest form which you can share on social media platforms. It makes all the messy, unattractive URLs short and shareable. Writing paper proposed a premium section in our application that gives access to the customizable URLs and analytics of your shorten URLs. Customizable URLs are the URLs you create by your own keywords. By creating a premium profile with the application, you can create your own URLs by using your own keywords. We have considered security a major part of the application that prevents the short URLs from being hacked or redirected to any advertising website or content. We store all the data related to the URL to show you the best view of your analytics and update it regularly. Main contribution in this field that for web application that provides users with a fast, secure and shortest URL for their using long URLs. Comparatively to other services that are currently available, the application provides superior security, availability, and confidentiality.
{"title":"URL shortener for web consumption: an extensive and impressive security algorithm","authors":"Saikat Gochhait, Yogesh Singh Rathore, Irina Leonova, Mahima Shanker Pandey, Bal Krishna Saraswat, Santosh Kumar Maurya, Hare Ram Singh, Nidhi Bansal","doi":"10.11591/ijeecs.v35.i1.pp284-291","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp284-291","url":null,"abstract":"URL stands for uniform resource locator are the addresses of the unique resources on the internet. We all need URLs to access any type of resource on the internet, such as any web page, and document. Sometimes URLs can be long, irrelative and unattractive and unable to send sometimes via email. So, for this, we proposed a URL shortener web application based on the Python-Django platform which is fast and makes your long URLs in the shortest form which you can share on social media platforms. It makes all the messy, unattractive URLs short and shareable. Writing paper proposed a premium section in our application that gives access to the customizable URLs and analytics of your shorten URLs. Customizable URLs are the URLs you create by your own keywords. By creating a premium profile with the application, you can create your own URLs by using your own keywords. We have considered security a major part of the application that prevents the short URLs from being hacked or redirected to any advertising website or content. We store all the data related to the URL to show you the best view of your analytics and update it regularly. Main contribution in this field that for web application that provides users with a fast, secure and shortest URL for their using long URLs. Comparatively to other services that are currently available, the application provides superior security, availability, and confidentiality.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141690753","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 : 2024-07-01DOI: 10.11591/ijeecs.v35.i1.pp222-237
Joselyn Zapata-Paulini, M. Cabanillas-Carbonell
Parkinson's is a neurodegenerative disease that generally affects people over 60 years of age. The disease destroys neurons and increases the accumulation of α-synuclein in many parts of the brain stem, although at present its causes remain unknown. It is therefore a priority to identify a method that can detect the disease, and this is where machine learning models become important. This study aims to perform a comparative analysis of machine learning models focused on the early detection of Parkinson's disease. Logistic regression (LR), support vector machines (SVM), decision trees (DT), extra trees classifiers (ETC), K-nearest neighbors (KNN), random forests (RF), adaptive boosting (AdaBoost) and gradient boosting (GB) algorithms are described and developed to identify the one that offers the best performance. In the training stage, we used the Oxford University dataset for Parkinson's disease detection, which has a total of 23 attributes and 195 records on patient voice recordings. The article is structured into six sections, such as introduction, related work, methodology, results, discussions, and conclusions. The metrics of accuracy, sensitivity, F1 count, and precision were used to measure the models' performance. The results position the KNN model as the best predictor with 95% accuracy, precision, sensitivity, and F1 score.
{"title":"Evaluation of machine learning algorithms in the early detection of Parkinson's disease: a comparative study","authors":"Joselyn Zapata-Paulini, M. Cabanillas-Carbonell","doi":"10.11591/ijeecs.v35.i1.pp222-237","DOIUrl":"https://doi.org/10.11591/ijeecs.v35.i1.pp222-237","url":null,"abstract":"Parkinson's is a neurodegenerative disease that generally affects people over 60 years of age. The disease destroys neurons and increases the accumulation of α-synuclein in many parts of the brain stem, although at present its causes remain unknown. It is therefore a priority to identify a method that can detect the disease, and this is where machine learning models become important. This study aims to perform a comparative analysis of machine learning models focused on the early detection of Parkinson's disease. Logistic regression (LR), support vector machines (SVM), decision trees (DT), extra trees classifiers (ETC), K-nearest neighbors (KNN), random forests (RF), adaptive boosting (AdaBoost) and gradient boosting (GB) algorithms are described and developed to identify the one that offers the best performance. In the training stage, we used the Oxford University dataset for Parkinson's disease detection, which has a total of 23 attributes and 195 records on patient voice recordings. The article is structured into six sections, such as introduction, related work, methodology, results, discussions, and conclusions. The metrics of accuracy, sensitivity, F1 count, and precision were used to measure the models' performance. The results position the KNN model as the best predictor with 95% accuracy, precision, sensitivity, and F1 score.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141705828","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}
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