Jawaher Al Washahi, Mithaq Ibrahim Al Qartubi, Jawaher Hamed Al-Hakmani
We did not realize as human beings that the devices around us can communicate with us and communicate with them this is called the Internet of Things(IoT). The IoT is multiple physical objects that communicate using the internet, allowing sending and receiving of data. IoT has its uses that expand to all areas of life, right from waking a person from sleep to putting them back to sleep. IoT has a lot of uses in the field of medicine. Every manufactured medicine is effective only for a particular duration that is already mentioned while we purchase. Medicine that a patient uses becomes fatal when consumed after the date of expiry. The pharmacist often needs more time to make sure that each package of the medication is effective and not expired. Mistakes may occur because of improper storage of the drugs, not checking the expiration date of the medicine, which leads to the distribution of expired medicines to consumers, which leads to many problems. The chemical composition of the drug may change instead of being lifesaving, turn into a deadly poison. Our study aim is to create an IoT device that Contributes to identifying the dispensing of expired medicines by showing notices that alert the pharmacist that the medicine is ineffective, and thus may increase the verification in a short time for the pharmacist and will contribute to improving the reputation of the pharmacy.
{"title":"SMART IDENTIFICATION AND NOTIFICATION OF DRUGS IN MEDICAL PHARMACY USING IOT","authors":"Jawaher Al Washahi, Mithaq Ibrahim Al Qartubi, Jawaher Hamed Al-Hakmani","doi":"10.59461/ijitra.v2i2.47","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.47","url":null,"abstract":"We did not realize as human beings that the devices around us can communicate with us and communicate with them this is called the Internet of Things(IoT). The IoT is multiple physical objects that communicate using the internet, allowing sending and receiving of data. \u0000IoT has its uses that expand to all areas of life, right from waking a person from sleep to putting them back to sleep. IoT has a lot of uses in the field of medicine. Every manufactured medicine is effective only for a particular duration that is already mentioned while we purchase. Medicine that a patient uses becomes fatal when consumed after the date of expiry. \u0000The pharmacist often needs more time to make sure that each package of the medication is effective and not expired. Mistakes may occur because of improper storage of the drugs, not checking the expiration date of the medicine, which leads to the distribution of expired medicines to consumers, which leads to many problems. The chemical composition of the drug may change instead of being lifesaving, turn into a deadly poison. \u0000Our study aim is to create an IoT device that Contributes to identifying the dispensing of expired medicines by showing notices that alert the pharmacist that the medicine is ineffective, and thus may increase the verification in a short time for the pharmacist and will contribute to improving the reputation of the pharmacy.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126356952","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}
The foundation of big data analysis is a massive volume of data. Diabetes is caused by an excess of sugar collected in the blood. Diabetes is one of the most serious chronic health issues. Diabetes sufferers' eyes, hearts, kidneys, and nerves may be damaged if they go undiagnosed. Humans can benefit from automated technologies to assist them in managing their hectic schedules. It inspires us to create a diabetes management scheme for patients that uses an IoT device to track their blood sugar, blood pressure, sports activities, nutrition plan, oxygen level, and ECG data. Machine learning has risen to prominence in healthcare services (HCS) due to its potential to enhance disease prediction. AI and ML approaches have already been used in the HCS field. We give a complete review of DL applications in diabetes in this study. We did a thorough literature review as well as discovered three key areas where this method is used: diabetes diagnosis, glucose control, and diabetes-related complication diagnosis. The search yielded 40 original research articles, from which we summarised essential data on used learning methods, development methods, main outcomes, and performance evaluation baseline techniques. According to the Reviewed Literature, various DL techniques and frameworks attained state-of-the-art performance in many diabetes-related tasks by outperforming conventional ML methods.
{"title":"An Efficient Exploration on Big Data Analysis in Adolescent Diabetic Prediction with Deep Learning Techniques","authors":"K.MANOHARI","doi":"10.59461/ijitra.v2i2.51","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.51","url":null,"abstract":"The foundation of big data analysis is a massive volume of data. Diabetes is caused by an excess of sugar collected in the blood. Diabetes is one of the most serious chronic health issues. Diabetes sufferers' eyes, hearts, kidneys, and nerves may be damaged if they go undiagnosed. Humans can benefit from automated technologies to assist them in managing their hectic schedules. It inspires us to create a diabetes management scheme for patients that uses an IoT device to track their blood sugar, blood pressure, sports activities, nutrition plan, oxygen level, and ECG data. Machine learning has risen to prominence in healthcare services (HCS) due to its potential to enhance disease prediction. AI and ML approaches have already been used in the HCS field. We give a complete review of DL applications in diabetes in this study. We did a thorough literature review as well as discovered three key areas where this method is used: diabetes diagnosis, glucose control, and diabetes-related complication diagnosis. The search yielded 40 original research articles, from which we summarised essential data on used learning methods, development methods, main outcomes, and performance evaluation baseline techniques. According to the Reviewed Literature, various DL techniques and frameworks attained state-of-the-art performance in many diabetes-related tasks by outperforming conventional ML methods.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"75 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113940720","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}
Nowadays, with the technological improvement, communications with the things become easier. It helps people to live an easier life, live and work smarter as well as take back control of their lives completely. this smart communication is done in an environment that called Internet of Things (IoT) environment. The Internet of Thing is multiple physical objects that communicate using the internet, allowing sending, and receiving of data. Since it’s a data so it's prone to attack in a goal of steal it, change it and so many reasons. In addition, nowadays hackers are everywhere with so many types. So, it needs to protect those data and the devices, if Internet of Things devices doesn't have enough security to protect the system from being compromised, then many threats and attacks will occur. If the administrator does not apply strong security and develop a plan for system and device prevention, the Internet of Things environment will be weak, which will make the system and devices prone to attack. Unauthorized access will be prevented if the login system includes a signature matching system. This research aims to analyze the traffic security and analyze threats and risks using IoT devices from intruders by applying an IDS to the IoT environment. when the attacker will try to enter to the traffic or send any packets to any IoT devices, the intrusion detection system will send an alert to the administrator that there's something wrong need to check, the IDS will detect the attacker's name, type and from which device he tries to enter to the system, it will analyze the traffic system, as well as will prevent the devices and data from threats.
{"title":"Intrusion detection system to advance IoT security environment","authors":"Maha Abullah Al-Dhuhli, Ammar Khamis Al-Mizaini, Miysaa Salim Al-Braiki, Rajesh Natarajan","doi":"10.59461/ijitra.v2i2.48","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.48","url":null,"abstract":"Nowadays, with the technological improvement, communications with the things become easier. It helps people to live an easier life, live and work smarter as well as take back control of their lives completely. this smart communication is done in an environment that called Internet of Things (IoT) environment. The Internet of Thing is multiple physical objects that communicate using the internet, allowing sending, and receiving of data. Since it’s a data so it's prone to attack in a goal of steal it, change it and so many reasons. In addition, nowadays hackers are everywhere with so many types. So, it needs to protect those data and the devices, if Internet of Things devices doesn't have enough security to protect the system from being compromised, then many threats and attacks will occur. If the administrator does not apply strong security and develop a plan for system and device prevention, the Internet of Things environment will be weak, which will make the system and devices prone to attack. Unauthorized access will be prevented if the login system includes a signature matching system. This research aims to analyze the traffic security and analyze threats and risks using IoT devices from intruders by applying an IDS to the IoT environment. when the attacker will try to enter to the traffic or send any packets to any IoT devices, the intrusion detection system will send an alert to the administrator that there's something wrong need to check, the IDS will detect the attacker's name, type and from which device he tries to enter to the system, it will analyze the traffic system, as well as will prevent the devices and data from threats.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114346115","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}
In this paper, Complex Fuzzy Graph (CFG) analyzed and introduced new concepts in CFG such as Spanning CFG, Complete CFG, path, arc, length, connected, strongest path and weakest path of CFG. We derived some properties of self complementary CFG and defined the operations on direct product, Semi strong product and strong product of CFG. Derived Isomorphic CFG with example is given in this paper. Moreover we introduced density of the graph and balanced complex fuzzy graph.
{"title":"Characteristics and Operations of Complex Fuzzy Graphs","authors":"Veeramani Veerapathran, Suresh R.","doi":"10.59461/ijitra.v2i2.57","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.57","url":null,"abstract":"In this paper, Complex Fuzzy Graph (CFG) analyzed and introduced new concepts in CFG such as Spanning CFG, Complete CFG, path, arc, length, connected, strongest path and weakest path of CFG. We derived some properties of self complementary CFG and defined the operations on direct product, Semi strong product and strong product of CFG. Derived Isomorphic CFG with example is given in this paper. Moreover we introduced density of the graph and balanced complex fuzzy graph.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124900034","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}
Early As we all know, how life is interlinked with the technology and the use of AI. AI-powered voice assistants have become an integral part of our lives, intertwining technology and daily tasks. A Personal Virtual Assistant allows a user to command or ask questions in the same manner that they would do with another human and are even capable of doing some basic tasks like opening apps, doing Wikipedia searches without opening a browser, playing music etc, with just a voice command. This project presents the development of a personal desktop assistant using Python, aiming to provide convenience, automation, and assistance to users in their computer-related activities. The assistant incorporates features such as voice recognition, natural language processing, and integration with external APIs to enhance its functionality and user experience. The assistant differentiates itself from existing solutions by offering a highly customizable and extensible platform. Users can tailor the assistant's behavior and functionality to their specific needs, while also benefiting from integration with popular tools and services. The user interface is designed to be intuitive and user-friendly, providing a seamless experience for both novice and experienced users. By creating a personal desktop assistant that combines convenience, automation, and personalized features, this project aims to enhance users' productivity and efficiency in their day-to-day computer tasks.
{"title":"Personal A.I. Desktop Assistant","authors":"Mahesh T R","doi":"10.59461/ijitra.v2i2.58","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.58","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000Early As we all know, how life is interlinked with the technology and the use of AI. AI-powered voice assistants have become an integral part of our lives, intertwining technology and daily tasks. A Personal Virtual Assistant allows a user to command or ask questions in the same manner that they would do with another human and are even capable of doing some basic tasks like opening apps, doing Wikipedia searches without opening a browser, playing music etc, with just a voice command. This project presents the development of a personal desktop assistant using Python, aiming to provide convenience, automation, and assistance to users in their computer-related activities. The assistant incorporates features such as voice recognition, natural language processing, and integration with external APIs to enhance its functionality and user experience. \u0000The assistant differentiates itself from existing solutions by offering a highly customizable and extensible platform. Users can tailor the assistant's behavior and functionality to their specific needs, while also benefiting from integration with popular tools and services. The user interface is designed to be intuitive and user-friendly, providing a seamless experience for both novice and experienced users. By creating a personal desktop assistant that combines convenience, automation, and personalized features, this project aims to enhance users' productivity and efficiency in their day-to-day computer tasks. \u0000 \u0000 \u0000 \u0000 \u0000","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129130425","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}
This paper surveys the current state of data management in the Internet of Things (IoT). It begins by outlining the challenges and opportunities that data management in IoT presents. Firstly, data management deals with the technical challenges and solutions related to data management in IoT, including data acquisition, storage, and integration. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Secondly, the requirement of IoT for data management extends offline storage, query processing, and transaction management activities into online-offline communication and storage dual operations, and the idea of data management is broadened. This is accomplished by IPv6, as well as IoT-specific capabilities and protocols including CoAP, HTTP, and WebSocket. Users may track, monitor, and manage devices with Internet of Things (IoT) device management, ensuring that they operate effectively and securely after deployment. Finally, the paper discusses the various applications of IoT based on the concept of data management in IoT. Numerous more objects, including wearables, medical equipment, houses, cities, farms, industries, and workplaces, are being interacted with by billions of sensors. The IoT platforms assist in establishing and maintaining criteria to enhance and preserve data appropriately. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Smart gadgets automate processes so we may save time by controlling the environment. The most valuable data is protected by edge devices for data management, which also lowers bandwidth costs. These also offer excellent performance, data ownership, and cheap maintenance costs.
{"title":"Data Management in IoT: A Detailed Survey","authors":"Jerome Oswald Ebenezer, Calduwel Newton","doi":"10.59461/ijitra.v2i2.49","DOIUrl":"https://doi.org/10.59461/ijitra.v2i2.49","url":null,"abstract":"This paper surveys the current state of data management in the Internet of Things (IoT). It begins by outlining the challenges and opportunities that data management in IoT presents. Firstly, data management deals with the technical challenges and solutions related to data management in IoT, including data acquisition, storage, and integration. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Secondly, the requirement of IoT for data management extends offline storage, query processing, and transaction management activities into online-offline communication and storage dual operations, and the idea of data management is broadened. This is accomplished by IPv6, as well as IoT-specific capabilities and protocols including CoAP, HTTP, and WebSocket. Users may track, monitor, and manage devices with Internet of Things (IoT) device management, ensuring that they operate effectively and securely after deployment. Finally, the paper discusses the various applications of IoT based on the concept of data management in IoT. Numerous more objects, including wearables, medical equipment, houses, cities, farms, industries, and workplaces, are being interacted with by billions of sensors. The IoT platforms assist in establishing and maintaining criteria to enhance and preserve data appropriately. The paper concludes with a set of recommendations for the development of effective data management strategies in the context of IoT. Smart gadgets automate processes so we may save time by controlling the environment. The most valuable data is protected by edge devices for data management, which also lowers bandwidth costs. These also offer excellent performance, data ownership, and cheap maintenance costs.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123467240","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}
S. H K, K Praghnya Iyer, Himaja K R, Rahisha Pokharel
In the digital world of today, where there is an infinite amount of content to consume, including movies, books, videos, articles, and so on, finding content that appeals to one's tastes has become challenging. On the other hand, providers of digital content want to keep as many people using their service for as long as possible. This is where the recommender system comes into play, where content providers suggest content to users based on their preferences. Web applications that offer a variety of services and automatically suggest some services based on user interest increasingly rely on recommendation systems. Different business services each play a significant role in the success of the current marketing field. The personalize recommendation technique is one of the most valuable tools for providing personalized service on websites. When it comes to e-Commerce's online marketing efforts, this strategy is extremely useful. To build the proposal framework, the cooperative sifting is exceptionally helpful advances in the field of recommender frameworks. The accuracy of recommendation engines is the source of many issues in today's web. Therefore, a variety of strategies are utilized to enhance the recommendation system's diversity and accuracy. When generating recommendations, the fundamental recommender systems typically take one of the following into account: The Content-Based Filtering, which is based on the user's preferences, it describes things, and we use keywords other than the user's profile to show what the user likes and dislikes. To put it another way, CBF algorithms suggest products that people have liked in the past or products that are similar to them. It looks at what you've liked in the past and suggests the best match, Or a collaborative filtering system makes recommendations for items based on how similar users and/or items are measured. The CF system only suggests products that are popular with similar types of users. The development of a movie recommendation system with category-based recommendations, more precise results, increased efficiency, and overcoming the cold start are the goals of this system.
{"title":"Personalized Movie Recommendation System","authors":"S. H K, K Praghnya Iyer, Himaja K R, Rahisha Pokharel","doi":"10.59461/ijitra.v2i1.40","DOIUrl":"https://doi.org/10.59461/ijitra.v2i1.40","url":null,"abstract":"In the digital world of today, where there is an infinite amount of content to consume, including movies, books, videos, articles, and so on, finding content that appeals to one's tastes has become challenging. On the other hand, providers of digital content want to keep as many people using their service for as long as possible. This is where the recommender system comes into play, where content providers suggest content to users based on their preferences. Web applications that offer a variety of services and automatically suggest some services based on user interest increasingly rely on recommendation systems. Different business services each play a significant role in the success of the current marketing field.\u0000The personalize recommendation technique is one of the most valuable tools for providing personalized service on websites. When it comes to e-Commerce's online marketing efforts, this strategy is extremely useful. To build the proposal framework, the cooperative sifting is exceptionally helpful advances in the field of recommender frameworks. The accuracy of recommendation engines is the source of many issues in today's web. Therefore, a variety of strategies are utilized to enhance the recommendation system's diversity and accuracy. When generating recommendations, the fundamental recommender systems typically take one of the following into account: The Content-Based Filtering, which is based on the user's preferences, it describes things, and we use keywords other than the user's profile to show what the user likes and dislikes.\u0000To put it another way, CBF algorithms suggest products that people have liked in the past or products that are similar to them. It looks at what you've liked in the past and suggests the best match, Or a collaborative filtering system makes recommendations for items based on how similar users and/or items are measured. The CF system only suggests products that are popular with similar types of users. The development of a movie recommendation system with category-based recommendations, more precise results, increased efficiency, and overcoming the cold start are the goals of this system.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131439523","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}
For the last few decades cloud computing is a blooming word in the field of computer science. Cloud computing is a fast growing technology; it provides various services to the user through internet on demand. Now a days, people in busy move, they use Cloud to store and retrieve data at anywhere, any time without use of any physical storage devices like pen drive, compact disc etc . Enormous features of cloud, most of the small and large scale organizations outsource their data in cloud data storage. With the widespread application of cloud, huge amount of users are incorporated in public cloud, it may lead to vulnerable attacks. So security and privacy is an important factor in cloud environment. This security problem can be solved by various ways. Cryptography is one of the techniques to secure user data in cloud. Researchers can use various cryptographic algorithms to implement the security in cloud storage. This paper focuses the summative analysis of researches, in cloud security from 2018-2022. This survey paper provides solution to researchers who have their work in cloud.
{"title":"An Empirical study of Hybrid Cryptographic Algorithms","authors":"Kalvikkarasi, Dr.Saraswathi A","doi":"10.59461/ijitra.v2i1.50","DOIUrl":"https://doi.org/10.59461/ijitra.v2i1.50","url":null,"abstract":"For the last few decades cloud computing is a blooming word in the field of computer science. Cloud computing is a fast growing technology; it provides various services to the user through internet on demand. Now a days, people in busy move, they use Cloud to store and retrieve data at anywhere, any time without use of any physical storage devices like pen drive, compact disc etc . Enormous features of cloud, most of the small and large scale organizations outsource their data in cloud data storage. With the widespread application of cloud, huge amount of users are incorporated in public cloud, it may lead to vulnerable attacks. So security and privacy is an important factor in cloud environment. This security problem can be solved by various ways. Cryptography is one of the techniques to secure user data in cloud. Researchers can use various cryptographic algorithms to implement the security in cloud storage. This paper focuses the summative analysis of researches, in cloud security from 2018-2022. This survey paper provides solution to researchers who have their work in cloud.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126036746","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}
Early detection of cancer sickness leads to rapid treatment, reducing the risk of morbidity and mortality. The diagnosis of oral cancer continues to be a challenge for dental careers, particularly in the location, evaluation, and review of early-stage oral disease. Due to the lack of optimal analysis using conventional methods, oral cancer is identified and grouped using AI at an early stage. AI techniques are used to show the movement and treatment of dangerous locations and may accurately predict future disease effects. AI techniques are used to show the movement and treatment of dangerous locations and may accurately predict future disease effects. A combination of expert AI and highlight determination calculations produces improved results in the early detection and forecast of oral cancer. The main goal and commitment of this audit study is to summarize the use of AI technologies for accurate early prediction of oral malignant development.
{"title":"Early Detection of Cancer using Machine Learning (ML) Techniques","authors":"T. Mahesh, Vinoth Kumar","doi":"10.59461/ijitra.v2i1.24","DOIUrl":"https://doi.org/10.59461/ijitra.v2i1.24","url":null,"abstract":"Early detection of cancer sickness leads to rapid treatment, reducing the risk of morbidity and mortality. The diagnosis of oral cancer continues to be a challenge for dental careers, particularly in the location, evaluation, and review of early-stage oral disease. Due to the lack of optimal analysis using conventional methods, oral cancer is identified and grouped using AI at an early stage. AI techniques are used to show the movement and treatment of dangerous locations and may accurately predict future disease effects. AI techniques are used to show the movement and treatment of dangerous locations and may accurately predict future disease effects. A combination of expert AI and highlight determination calculations produces improved results in the early detection and forecast of oral cancer. The main goal and commitment of this audit study is to summarize the use of AI technologies for accurate early prediction of oral malignant development.","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125319314","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}
The internet is essential for ongoing contact in the modern world, yet its effectiveness might lessen the effect known as intrusions. Any action that negatively affects the targeted system is considered an intrusion. Network security has grown to be a major issue as a result of the Internet's rapid expansion. The Network Intrusion Detection System (IDS), which is widely used, is the primary security defensive mechanism against such hostile assaults. Data mining and machine learning technologies have been extensively employed in network intrusion detection and prevention systems to extract user behaviour patterns from network traffic data. Association rules and sequence rules are the main foundations of data mining used for intrusion detection. Given the Auto encoder algorithm's traditional method's bottleneck of frequent itemsets mining, we provide a Length-Decreasing Support to Identify Intrusion based on Data Mining, which is an upgraded Data Mining Techniques based on Machine Learning for IDS. Based on test results, it appears that the suggested strategy is successful
{"title":"Implementation of Machine Learning-Based Data Mining Techniques for IDS","authors":"Mahesh T R, V Vivek, Vinoth Kumar","doi":"10.59461/ijitra.v2i1.23","DOIUrl":"https://doi.org/10.59461/ijitra.v2i1.23","url":null,"abstract":"The internet is essential for ongoing contact in the modern world, yet its effectiveness might lessen the effect known as intrusions. Any action that negatively affects the targeted system is considered an intrusion. Network security has grown to be a major issue as a result of the Internet's rapid expansion. The Network Intrusion Detection System (IDS), which is widely used, is the primary security defensive mechanism against such hostile assaults. Data mining and machine learning technologies have been extensively employed in network intrusion detection and prevention systems to extract user behaviour patterns from network traffic data. Association rules and sequence rules are the main foundations of data mining used for intrusion detection. Given the Auto encoder algorithm's traditional method's bottleneck of frequent itemsets mining, we provide a Length-Decreasing Support to Identify Intrusion based on Data Mining, which is an upgraded Data Mining Techniques based on Machine Learning for IDS. Based on test results, it appears that the suggested strategy is successful","PeriodicalId":187267,"journal":{"name":"International Journal of Information Technology, Research and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133555625","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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