Journal of ICT Research and Applications最新文献_第3页

Accuracy of Various Methods to Estimate Volume and Weight of Symmetrical and Non-Symmetrical Fruits using Computer Vision 利用计算机视觉估计对称和非对称水果体积和重量的各种方法的准确性

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-12-27 DOI: 10.5614/itbj.ict.res.appl.2022.16.3.2

Hurriyatul Fitriyah

{"title":"Accuracy of Various Methods to Estimate Volume and Weight of Symmetrical and Non-Symmetrical Fruits using Computer Vision","authors":"Hurriyatul Fitriyah","doi":"10.5614/itbj.ict.res.appl.2022.16.3.2","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.3.2","url":null,"abstract":"Many researchers have used images to measure the volume and weight of fruits so that the measurement can be done remotely and non-contact. There are various methods for fruit volume estimation based on images, i.e., Basic Shape, Solid of Revolution, Conical Frustum, and Regression. The weight estimation generally uses Regression. This study analyzed the accuracy of these methods. Tests were done by taking images of symmetrical fruits (represented by tangerines) and non-symmetrical fruits (represented by strawberries). The images were processed using segmentation in saturation color space to get binary images. The Regression method used Diameter, Projection Area, and Perimeter as features that were extracted from the binary images. For symmetrical fruits, the best accuracy was obtained with the Linear Regression based on Diameter (LDD), which gave the highest R2 (0.96 for volume and 0.93 for weight) and the lowest RMSE (5.7 mm3 for volume and 5.3 gram for volume). For non-symmetrical fruits, the highest accuracy for non-symmetric fruits was given by the Linear Regression based on Diameter (LRD) and Linear Regression based on Area (LRA) with an R2 of 0.8 for volume and weight. The RMSE for LRD and LRA for strawberries was 3.3 mm3 for volume and 1.4 grams for weight.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45102373","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}

引用次数: 0

Compact and Robust MFCC-based Space-Saving Audio Fingerprint Extraction for Efficient Music Identification on FM Broadcast Monitoring 紧凑稳健的基于MFCC的节省空间音频指纹提取用于调频广播监控中的高效音乐识别

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-12-27 DOI: 10.5614/itbj.ict.res.appl.2022.16.3.3

Myo Thet Htun

{"title":"Compact and Robust MFCC-based Space-Saving Audio Fingerprint Extraction for Efficient Music Identification on FM Broadcast Monitoring","authors":"Myo Thet Htun","doi":"10.5614/itbj.ict.res.appl.2022.16.3.3","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.3.3","url":null,"abstract":"The Myanmar music industry urgently needs an efficient broadcast monitoring system to solve copyright infringement issues and illegal benefit-sharing between artists and broadcasting stations. In this paper, a broadcast monitoring system is proposed for Myanmar FM radio stations by utilizing space-saving audio fingerprint extraction based on the Mel Frequency Cepstral Coefficient (MFCC). This study focused on reducing the memory requirement for fingerprint storage while preserving the robustness of the audio fingerprints to common distortions such as compression, noise addition, etc. In this system, a three-second audio clip is represented by a 2,712-bit fingerprint block. This significantly reduces the memory requirement when compared to Philips Robust Hashing (PRH), one of the dominant audio fingerprinting methods, where a three-second audio clip is represented by an 8,192-bit fingerprint block. The proposed system is easy to implement and achieves correct and speedy music identification even on noisy and distorted broadcast audio streams. In this research work, we deployed an audio fingerprint database of 7,094 songs and broadcast audio streams of four local FM channels in Myanmar to evaluate the performance of the proposed system. The experimental results showed that the system achieved reliable performance.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47138589","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}

引用次数: 1

Energy Consumption Prediction Using Data Reduction and Ensemble Learning Techniques 基于数据约简和集成学习技术的能耗预测

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-12-27 DOI: 10.5614/itbj.ict.res.appl.2022.16.3.1

M. Ahmada, Saiful Akbar

引用次数: 0

A Questions Answering System on Hadith Knowledge Graph 基于圣训知识图谱的问答系统

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-10-11 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.6

Kemas Wiharja, D. Murdiansyah, M. Z. Romdlony, Tiwa Ramdhani, Muhammad Ramadhan Gandidi

引用次数: 0

Towards Enhancing Keyframe Extraction Strategy for Summarizing Surveillance Video: An Implementation Study 改进监控视频总结关键帧提取策略的实现研究

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-09-23 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.5

B. O. Sadiq, H. Bello-Salau, Latifat Abduraheem-Olaniyi, B. Muhammed, Sikiru Olayinka Zakariyya

{"title":"Towards Enhancing Keyframe Extraction Strategy for Summarizing Surveillance Video: An Implementation Study","authors":"B. O. Sadiq, H. Bello-Salau, Latifat Abduraheem-Olaniyi, B. Muhammed, Sikiru Olayinka Zakariyya","doi":"10.5614/itbj.ict.res.appl.2022.16.2.5","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.2.5","url":null,"abstract":"The large amounts of surveillance video data are recorded, containing many redundant video frames, which makes video browsing and retrieval difficult, thus increasing bandwidth utilization, storage capacity, and time consumed. To ensure the reduction in bandwidth utilization and storage capacity to the barest minimum, keyframe extraction strategies have been developed. These strategies are implemented to extract unique keyframes whilst removing redundancies. Despite the achieved improvement in keyframe extraction processes, there still exist a significant number of redundant frames in summarized videos. With a view to addressing this issue, the current paper proposes an enhanced keyframe extraction strategy using k-means clustering and a statistical approach. Surveillance footage, movie clips, advertisements, and sports videos from a benchmark database as well as Compeng IP surveillance videos were used to evaluate the performance of the proposed method. In terms of compression ratio, the results showed that the proposed scheme outperformed existing schemes by 2.82%. This implies that the proposed scheme further removed redundant frames whiles retaining video quality. In terms of video playtime, there was an average reduction of 27.32%, thus making video content retrieval less cumbersome when compared with existing schemes. Implementation was done using MATLAB R2020b.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41421766","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}

引用次数: 0

Breast Cancer Diagnosis in Women Using Neural Networks and Deep Learning 用神经网络和深度学习诊断女性乳腺癌

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-09-09 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.4

O. Fagbuagun, O. Folorunsho, Lawrence Bunmi Adewole, Titilayo Akin-Olayemi

引用次数: 3

Strengthening INORMALS Using Context-based Natural Language Generation 使用基于上下文的自然语言生成来增强INORMALS

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-08-31 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.1

Soni Yora, A. Barmawi

{"title":"Strengthening INORMALS Using Context-based Natural Language Generation","authors":"Soni Yora, A. Barmawi","doi":"10.5614/itbj.ict.res.appl.2022.16.2.1","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.2.1","url":null,"abstract":"The noiseless steganography method that has been proposed by Wibowo can embed up to six characters in the provided cover text, but more than 59% of Indonesian words have a length of more than six characters, so there is room to improve Wibowo’s method. This paper proposes an improvement of Wibowo’s method by modifying the shifting codes and using context-based language generation. Based on 300 test messages, 99% of messages with more than six characters could be embedded by the proposed method, while using Wibowo’s method this was only 34%. Wibowo’s method can embed more than six characters only if the number of shifting codes is less than three, while the proposed method can embed more than six characters even if there are more than three shifting codes. Furthermore, the security for representing the number of code digits is increased by introducing a private key with the probability of guessing less than 1, while in Wibowo’s method this is 1. The naturalness of the cover sentences generated by the proposed method was maintained, which was about 99% when using the proposed method, while it was 98.61% when using Wibowo’s method.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45706613","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}

引用次数: 0

Context-Aware Sentiment Analysis using Tweet Expansion Method 基于推特展开法的情境感知情感分析

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-08-31 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.3

Bashar Tahayna, R. Ayyasamy, Rehan Akbar

{"title":"Context-Aware Sentiment Analysis using Tweet Expansion Method","authors":"Bashar Tahayna, R. Ayyasamy, Rehan Akbar","doi":"10.5614/itbj.ict.res.appl.2022.16.2.3","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.2.3","url":null,"abstract":"The large source of information space produced by the plethora of social media platforms in general and microblogging in particular has spawned a slew of new applications and prompted the rise and expansion of sentiment analysis research. We propose a sentiment analysis technique that identifies the main parts to describe tweet intent and also enriches them with relevant words, phrases, or even inferred variables. We followed a state-of-the-art hybrid deep learning model to combine Convolutional Neural Network (CNN) and the Long Short-Term Memory network (LSTM) to classify tweet data based on their polarity. To preserve the latent relationships between tweet terms and their expanded representation, sentence encoding and contextualized word embeddings are utilized. To investigate the performance of tweet embeddings on the sentiment analysis task, we tested several context-free models (Word2Vec, Sentence2Vec, Glove, and FastText), a dynamic embedding model (BERT), deep contextualized word representations (ELMo), and an entity-based model (Wikipedia). The proposed method and results prove that text enrichment improves the accuracy of sentiment polarity classification with a notable percentage.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48984080","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}

引用次数: 3

Medium Access Control Protocol for High Altitude Platform Based Massive Machine Type Communication 基于高空平台的大型机型通信介质访问控制协议

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-08-31 DOI: 10.5614/itbj.ict.res.appl.2022.16.2.2

Veronica Windha Mahyastuty, I. Iskandar, H. Hendrawan, M. S. Arifianto

{"title":"Medium Access Control Protocol for High Altitude Platform Based Massive Machine Type Communication","authors":"Veronica Windha Mahyastuty, I. Iskandar, H. Hendrawan, M. S. Arifianto","doi":"10.5614/itbj.ict.res.appl.2022.16.2.2","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.2.2","url":null,"abstract":"Massive Machine Type Communication (mMTC) can be used to connect a large number of sensors over a wide coverage area. One of the places where mMTC can be applied is in wireless sensor networks (WSNs). A WSN consists of several sensor nodes that send their sensing information to the cluster head (CH), which can then be forwarded to a high altitude platform (HAP) station. Sensing information can be sent by the sensor nodes at the same time through the same medium, which means collision can occur. When this happens, the sensor node must re-send the sensing information, which causes energy wastage in the WSN. In this paper, we propose a Medium Access Control (MAC) protocol to control access from several sensor nodes during data transmission to avoid collision. The sensor nodes send Round Robin, Interrupt and Query data every eight hours. The initial slot for transmission of the Round Robin data can be either randomized or reserved. Analysis performance was done to see the efficiency of the network with the proposed MAC protocol. Based on the series of simulations that was conducted, the proposed MAC protocol can support a WSN system-based HAP for monitoring every eight hours. The proposed MAC protocol with an initial slot that is reserved for transmission of Round Robin data has greater network efficiency than a randomized slot.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44020077","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}

引用次数: 0

A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes 基于安全目的的文本度量来检测盈利和非营利网站的分类器

IF 0.6

Journal of ICT Research and Applications Pub Date : 2022-05-17 DOI: 10.5614/itbj.ict.res.appl.2022.16.1.6

Yahya M. Tashtoush, Dirar A. Darweesh, Omar M. Darwish, B. Alsinglawi, Rasha Obeidat

{"title":"A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes","authors":"Yahya M. Tashtoush, Dirar A. Darweesh, Omar M. Darwish, B. Alsinglawi, Rasha Obeidat","doi":"10.5614/itbj.ict.res.appl.2022.16.1.6","DOIUrl":"https://doi.org/10.5614/itbj.ict.res.appl.2022.16.1.6","url":null,"abstract":"Currently, most organizations have a defense system to protect their digital communication network against cyberattacks. However, these defense systems deal with all network traffic regardless if it is from profit or non-profit websites. This leads to enforcing more security policies, which negatively affects network speed. Since most dangerous cyberattacks are aimed at commercial websites, because they contain more critical data such as credit card numbers, it is better to set up the defense system priorities towards actual attacks that come from profit websites. This study evaluated the effect of textual website metrics in determining the type of website as profit or nonprofit for security purposes. Classifiers were built to predict the type of website as profit or non-profit by applying machine learning techniques on a dataset. The corpus used for this research included profit and non-profit websites. Both traditional and deep machine learning techniques were applied. The results showed that J48 performed best in terms of accuracy according to its outcomes in all cases. The newly built models can be a significant tool for defense systems of organizations, as they will help them to implement the necessary security policies associated with attacks that come from both profit and non-profit websites. This will have a positive impact on the security and efficiency of the network.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43710726","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}

引用次数: 1