{"title":"Decision Support System to Optimize Cloud Service Prioritization for Model Deployment","authors":"Muhammad Zubair Khan, Yugyung Lee, M. K. Khattak","doi":"10.1109/ICICT52872.2021.00033","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00033","url":null,"abstract":"The bio-inspired concept of deep learning has brought a revolution in artificial intelligence. It has challenged several areas including computer vision, signal processing, healthcare, transportation, security, robotics and machine translation. The core idea is to make learning algorithms efficient and convenient to use for solving daily life problems. This technology is still naive and facing multiple challenges like massive data availability, computation and infrastructural cost, resource dependency, efficient resource utilization, model production and platform procurement. Also it is found that most of the structured and unstructured data comes in the form of images, captured through different types of sensors. These images if utilized efficiently, can serve as an effective tool to solve numerous problems. To target above, a resource independent deep learning framework is proposed in this article. This work is an effort towards deploying deep neural network off-premises for medical image analysis to eliminate on-premises resource dependency and making efficient use of pay-as-per-demand paradigm offered by cloud services. This approach not only reduces the overall infrastructural cost but also enables a diverse range of need-based computational resource selection. The proposed work has shown promising results and considered as an effort to promote cloud-based resource independent machine intelligence.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123581237","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}
{"title":"Retinal Image Analysis to Detect Neovascularization using Deep Segmentation","authors":"Muhammad Zubair Khan, Yugyung Lee","doi":"10.1109/ICICT52872.2021.00026","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00026","url":null,"abstract":"The retina has a significant role in early detection of sight-threatening disease symptoms. Most of the ocular complications manifest themselves in retina. The extraction of useful information from this vital resource is a critical task. The recent advancement in artificial intelligence has opened ways to provide rapid assistance in detecting ocular disorders through retinal images. In this article, we have proposed a vessels segmentation model for the early detection of neovascularization. It is a common symptom for patients facing chronic diabetic retinopathy. In neovascularization, the tiny vessels are produced that gets block over time with an extensive amount of sugar content in human blood. The detection of newly formatted tiny blood vessels needs a precise vessels extraction system. Our model has shown promising results on a publicly available retinal image dataset. It has achieved the highest accuracy of 0.9554 with 0.9780 AUC. The underlying research is an effort to produce automated disease detection system. The core function of the proposed system is to analyze the structural variation in vessels of subjects experiencing ocular disease symptoms and to reduce the risk of blindness through early diagnosis.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125273901","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}
Regina Garcia Almonte, Carlo R. Malizon, M. Montano, Jascelynn Olimpiada
{"title":"Sentiment Analysis of Local College in the Philippines using Facebook Posts towards Good Governance: A Framework Proposal","authors":"Regina Garcia Almonte, Carlo R. Malizon, M. Montano, Jascelynn Olimpiada","doi":"10.1109/ICICT52872.2021.00015","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00015","url":null,"abstract":"Good governance means that the institutions are able to meet the needs of their stakeholders. It is participatory and inclusive through considering the opinions and sentiments of the stakeholders for decision-making. To analyze the massive amount of opinions and sentiments, sentiment analysis is necessary. Thus, this study intends to devise and propose a framework for sentiment analysis that will be used by the Local Colleges in the Philippines towards the attainment and maintenance of good governance. The proposed framework presented the phases for sentiment analysis to develop an application/software: data acquisition, data pre-processing, data classification, validation and evaluation, and integration.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123806915","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}
{"title":"Graph Representation of Road Network for Mobility-Impaired Persons","authors":"Bernard H. Ugalde, A. Vinluan, J. Carpio","doi":"10.1109/ICICT52872.2021.00039","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00039","url":null,"abstract":"One of the recurring issues mobility-impaired persons have to deal with is traveling alone in a wheelchair blindly without prior information regarding the accessibility of the planned route. Ordinary people usually choose the shortest path, but people with ambulant disabilities may prefer a longer route that does not include an uphill. The purpose of this paper is to extract the graph representation for people with reduced mobility across Baguio's Central Business District. The PWD ramps and wheelchair passable drop curbs were located with a smartphone GPS. Google Maps was used to verify the coordinates. The road distance was calculated using the Haversine formula as verified using Google Earth. The Lavene's Test for equality of variances and T-test of equality of means were used to check the significant difference between the derived values against Google's data. The derived latitude and longitude using a mobile phone's GPS did not differ significantly from the Google Maps coordinates. Moreover, the study showed that the calculated road distance using the Haversine formula did not vary considerably from the Google Earth distance. As such, the study aims to provide time and safety benefits by presenting a novel model representing the road network as a graph for mobility-impaired persons.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124424922","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}
{"title":"Digital Forensics and Incident Response (DFIR) Challenges in IoT Platforms","authors":"Cornelius Itodo, Said Varlioglu, Nelly Elsayed","doi":"10.1109/ICICT52872.2021.00040","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00040","url":null,"abstract":"The rapid progress experienced in the Internet of Things (IoT) space is one that has introduced new and unique challenges for cybersecurity and IoT-Forensics. One of these problems is how digital forensics and incident response (DFIR) are handled in IoT. Since enormous users use IoT platforms to accomplish their day to day task, massive amounts of data streams are transferred with limited hardware resources; conducting DFIR needs a new approach to mitigate digital evidence and incident response challenges owing to the facts that there are no unified standard or classified principles for IoT forensics. Today's IoT DFIR relies on self-defined best practices and experiences. Given these challenges, IoT-related incidents need a more structured approach in identifying problems of DFIR. In this paper, we examined the major DFIR challenges in IoT by exploring the different phases involved in a DFIR when responding to IoT-related incidents. This study aims to provide researchers and practitioners a road-map that will help improve the standards of IoT security and DFIR.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130476988","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}
Deshya Wijesundera, Thilina Perera, Dilina Dehigama, T. Srikanthan
{"title":"Incorporating Compiler Optimization in Software Estimation for FPGA-based Embedded Processors*","authors":"Deshya Wijesundera, Thilina Perera, Dilina Dehigama, T. Srikanthan","doi":"10.1109/ICICT52872.2021.00030","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00030","url":null,"abstract":"The embedded processors beside the traditional FPGA fabric in FPGA-based System-on-Chip (SoC) devices make them an attractive alternative for realizing the software portions of the application while using the FPGA fabric for hardware acceleration. Traditional performance evaluation of applications on these embedded processors require design expertise and costly commercial tools or hardware for each processor. Thus, software based performance estimation techniques that eliminate these requirements are considered a viable alternative. However, estimation techniques which can be applied across different embedded processors do not account for compiler optimizations. This paper proposes a framework for software estimation of embedded processors that incorporates compiler optimizations. The proposed technique relies on a neural network estimation model instead of FPGA synthesis and execution-based techniques, that necessitates costly commercial tools and hardware, and does not require design expertise. Experimental evaluations on the Intel Nios II processor show an average accuracy of 92.5% with a R2 value of 0.9977 for the neural network, which highlights the suitability of the proposed technique.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132842388","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}
{"title":"Deep Space Relay Resource Planning Model Based on Sliding Time Window","authors":"Xin Liu, Jiangtao Fei, Shuang Liang, Pengde Ma, Xiaoping Li, Jungang Chen, Zhen Zhang","doi":"10.1109/ICICT52872.2021.00037","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00037","url":null,"abstract":"When a deep space probe enters into the back of the celestial body, it cannot directly communicate with the earth for TT&C (Telemetry, Tracking & Control) and data transmission. As a transfer station for communication between the earth TT &C station and the deep space probe, the deep space satellite realizes all-weather data transmission between the earth and deep space probe. Because of the exclusivity of the deep space relay satellite communication link, several deep space probes compete for relay resources. Aiming at the problem of relay resource planning for deep space probes, this paper proposes a deep space relay resource planning algorithm based on sliding time window, designs hierarchical planning and scheduling architecture of relay resources, and realizes automatic planning and allocation of relay resources and unified scheduling and management. The practical application results show that the algorithm can meet the requirements of resource planning for celestial backside exploration tasks, improve the efficiency of resource allocation and reduce the rate of resource fragmentation.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123965884","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}
{"title":"Effect of JPEG compression on Sensor-based Image Forensics","authors":"S. Chakraborty","doi":"10.1109/ICICT52872.2021.00025","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00025","url":null,"abstract":"For the forensic task of camera identification and manipulation localization, the most promising and widely used algorithms are the ones based on Photo-Response Non-Uniformity (PRNU) or the camera sensor noise. However, the performance of camera identification and manipulation localization is strongly affected by JPEG compression. Typically, for images with lower quality factors, the accuracy of camera identification as well as manipulation localization reduces considerably. In this article, we present the results of a large scale demonstration on how JPEG compression has an influence on the performance of camera identification and manipulation localization. Our results on three popular datasets indicate that camera identification works even for a quality factor as low as thirty. Also we found that false positives increase significantly for PRNU-based manipulation localization.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125778340","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}
{"title":"Functional Hazard Analysis for Engineering Safe Software Requirements","authors":"V. N. Tran, L. Tran, V. Tran","doi":"10.1109/ICICT52872.2021.00031","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00031","url":null,"abstract":"Functional Hazard Analysis (FHA) is an inductive hazard analysis method used to evaluate the potential causes and hazardous consequences of a system's functional failures. Software safety uses the FHA to assess the software contribution to the system hazards and identify software improvement opportunities. The FHA integrates risk-driven and quality assurance-driven approaches into a single safety analysis method for safe software requirements engineering. Our paper reviews the use of the MIL-STD-882E FHA to support the development of software requirements for safety-critical systems. First, we summarize the distinguishing features of the FHA as a hazard analysis method. Second, we explain how to use this method to identify software safety risks and recommend software safety improvements in the software requirements engineering process.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127192055","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}
Abdelrahman M. Ezz, Ashraf Nabil, Waleed Ali, Mohammed Abdou, Mark Azer, Ibrahim Farag, Motaz Agamawi
{"title":"Digital Gate: Automotive Gateway to Automation Platforms","authors":"Abdelrahman M. Ezz, Ashraf Nabil, Waleed Ali, Mohammed Abdou, Mark Azer, Ibrahim Farag, Motaz Agamawi","doi":"10.1109/ICICT52872.2021.00036","DOIUrl":"https://doi.org/10.1109/ICICT52872.2021.00036","url":null,"abstract":"Technology is evolving aggressively everyday around us in different domains. In addition, IoT is being involved in different fields to facilitate people's daily life routines with the help of trigger-action platforms (such as Zapier, IFTTT, Integromat, etc.). These platforms help end-users create a set of workflows that integrate various devices. On the other hand, the proliferation of sensors mounted on vehicles nowadays produced huge data from cars, yet not fully utilized. Recently vehicles' industry incorporated more technologies to increase connectivity, thus increasing the level of comfort and luxury, This paper explores and presents the Digital Gate system and its advantages. Digital Gate system aims to connect the vehicle's network (including CAN, Flexray, Ethernet, etc.) to cloud computation platforms as well as to the automation platforms and vice versa. Moreover, Digital Gate system provides the capability of creating proof of concepts (POCs) and prototypes for automotive developers. Also, it facilitates and accelerate the development cycle.","PeriodicalId":359456,"journal":{"name":"2021 4th International Conference on Information and Computer Technologies (ICICT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123051638","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}