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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Bharadwaj Thuraka Vikram Pasupuleti Chandra Shikhi Kodete Ravi Swaroop Chigurupati N S Koti Mani Kumar Tirumanadham Vahiduddin Shariff School of Computer Science and Information Systems Northwest Missouri State University Maryville MO USA School of Technology Eastern Illinois University Charleston IL USA Dept. of CSE S R K R Engineering College(A) Bhimavaram India Dept. of CSE Sir C R Reddy College of Engineering Eluru India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

This research relies on a feature selection method termed LasNO to analyse the progress of diabetes prediction. The ANOVA integrated with Lasso regularization identifies significant predictors like Age, BMI, DiabetesPedigreeFunction, and (Glucose). An AdaBoost model with the following characteristics was developed, and the results were exceptional performance metrics: 97.02% accuracy, 87.65% precision, and 82.5% recall. The results of the primary focus on glucose levels to differentiate between events with and without diabetes have been affirmed from the visual analyses. It also calls into attention that due to the appropriate cross-validation, LasNO is very successful on improving the interpretability and the possibility of generalization of the model. Such findings make it clear that efforts towards early detection of the condition and subsequent timely implementation of measures to contain the illness can go quite a long way in enhancing the quality of the lives of people that contract the disease. Further research is likely to be devoted to the assessing of the improved and broadened validation of the dataset as a critical approach for the enhancement and expansion of the model for use in clinics. As a result, this study aims to advance diabetes theragnostic possibilities and healthcare recommendations for better action based on ML approaches enhancing the accuracy of predictions. In this study, approaches to feature selection used for improving the performance while also making the models more understandable are the focus. The idea is to ensure that medical practitioners have reliable tools to undertake early detection and management of diabetes. Thus, the main objective of dealing with patients’ Health-Related Quality of Life is to simultaneously increase the quality of patients’ living while decreasing the costs of their treatment.

关键词： Visualization Accuracy Medical services Predictive models Feature extraction Data models Diabetes Glucose Analysis of variance Diseases

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Assessment of IT Governance Maturity Level for Yemeni Telecom Sector Using COBIT 2019 Framewor006B

Assessment of IT Governance Maturity Level for Yemeni Teleco...

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Emerging technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Abdullatif Ghallab Tahani Alswari Saleh Alhazbi Belal Al-Fuhaidi Mohammed Hadwan Farouk Al-Fahaidy Mohammed Al-Dowail Naseebah Maqtary Department of Computer Science University of Science and Technology Sana'a Yemen Department of IT Open University Malaysia Sana'a Yemen Dept. of Computer Science & Eng Qatar University Doha Qatar Department of IT Qassim University Buraydah Saudi Arabia Department of Electrical Engineering Ibb University Ibb Yemen Department of Information Systems University of Science and Technology Sana’a Yemen

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

information technology (IT) plays a crucial role in business operations most organizations rely on IT resources for gaining competitive advantages and creating innovative and continuous values. This increased the importance of enterprise IT governance (EGIT) and developed the recent version of the control objectives for information and related technology (COBIT), COBIT 2019 framework. It identifies the seven components of an effective EGIT system: processes, organizational structures, information flows and items, people, skills and competencies, policies and procedures, culture, ethics and behavior, services, infrastructure, and applications. The EGIT maturity level (ITGML) assessment helps to align the EGIT with strategic objectives. This study aims to assess the ITGML of the Yemeni telecom sector using COBIT 2019 framework. A quantitative method was applied, with a 73.6% response rate (148 out of 201 questionnaires collected). The study revealed that the current ITGML is 3.48, reflecting a defined maturity level. The findings suggested that IT governance practices based on COBIT 2019 are well documented and standardized within the Yemeni telecom sector.

关键词： Ethics Standards organizations Process control Focusing Companies Documentation Telecommunications Stakeholders Internet of Things information technology

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A Novel Analysis and Detection of Autism Spectrum Disorder in Artificial Intelligence Using Hybrid Machine Learning

A Novel Analysis and Detection of Autism Spectrum Disorder i...

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Innovative Data Communication technologies and Application (ICIDCA), International Conference on

作者： Senthil G. A R. Prabha J. Nithyashri Suganthi. P I. Thamarai Sridevi S Department of Information Technology Agni College of Technology Chennai India Department of Electronics and Communication Engineering Sri Sai Ram Institute of Technology Chennai India Dept. of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai City Campus Chennai India Dept. of Computer Science and Engineering Sri Ramachandra Engineering and Technology Chennai India

Heart Disease or Cardiovascular Disease refers to the range of heart conditions like cardiac arrest, coronary artery disease. Heart disease can be very well hindered through certain lifestyle changes. There is a significant increase in the mortality rate recently due to the distinctive heart diseases. Machine learning uses mathematical models to work efficiently with the enormous amount of data. It plays a crucial role in medical science in the prediction of distinctive diseases. Cardiologists inspects the heart functionality using electrocardiography, computed tomography. These tests are quite expensive for a common man. Recent times, the life span of a human is guaranteed only with the support of medications. As prevention is better than the cure, machine learning helps to predict the vulnerability of a heart disease with few elemental symptoms and health factors. It is been fed by the basic data of the patients like age and sex. Machine learning helps to predict the vulnerability in advance which provides the cardiologists with great acumen for the adaption of the treatment. Machine learning algorithms have proven to produce reliable and accurate output with the help of the inputs. The algorithms used in the article include K-Nearest Neighbour (KNN) and decision tree classifier which is compared to yield the desired and efficient output.

关键词： Heart Support vector machines Autism Machine learning algorithms Neural networks Machine learning Prediction algorithms

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An Architectural Approach for Enhanced Data Interoperability Across Building systems

An Architectural Approach for Enhanced Data Interoperability...

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Cloudification of the Internet of Things (CIoT)

作者： Peter Yefi Sikandar Ejaz Ramanunni Parakkal Menon Ursula Eicker Yann-Gaël Guéhéneuc Computer Science and Software Engineering Dept. Concordia University Montreal Canada Institute for Information Systems Engineering Concordia University Montreal Canada German Aerospace Center Institute for Solar Research Jülich Germany NextGen Cities Institute Concorida University Montreal Canada

ISBN: (数字)9798350356717

ISBN: (纸本)9798350356724

Access to building data is crucial for creating portable applications and improving building operation and energy efficiency. Ensuring data transmutability is essential for facilitating research and overcoming the diverse data representation, management, and collection methods across various building management systems.(BMSs). Different BMSs use multiple interfaces for data exchange. Some BMSs provide Application Programming Interfaces (APIs) for data exchanges, while others have gateways connecting to cloud services for application subscription and data access. This study introduces a five-layered architecture that describes how client applications, researchers, and other interested stakeholders can exchange data with different BMSs. Our objective is to help researchers and practitioners understand the various ways of accessing transmutable (capable of being transformed into a compatible format) data from BMSs, regardless of the building management system a building uses. Through transmutable access to building systems. data, we aim to enable transferable energy-efficient-related applications for buildings. We evaluate our work with a building model of the Varennes Library in Varennes, QC, Canada. The building model includes information about the building, floors, rooms, electric meter and historical time series data of the meter, weather station and its historical time series data. The model also has carbon dioxide concentration sensors, temperature sensors, humidity sensors, and historical time series data of the sensors. We include two test client programs to show how they access the transmutable data of the building through a model. We conclude that the five-layered architecture facilitates the exchange of transmutable data across diverse BMSs, making it a valuable tool for researchers and practitioners.

关键词： Temperature sensors Meters Architecture Buildings Time series analysis Data models Energy efficiency Sensors Stakeholders Building management systems

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A new framework to protect privacy of location from malicious applications 8

A new framework to protect privacy of location from maliciou...

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8th International Conference on Computing for Sustainable Global Development, INDIACom 2021

作者： Alharbi, Awad Saleh Halikias, George Abi Sen, Adnan Ahmed Yamin, Mohammad School of Mathematics Computer Science and Engineering Dept. of Electrical and Electronic Engg. London United Kingdom Islamic University Faculty of Computer and Information Systems Al-Madinah Saudi Arabia Research School of Computer Science Australian National University Canberra Australia

ISBN: (纸本)9789380544434

Location-based applications have become very popular in recent years, especially during the ongoing COVID-19 pandemic. The pandemic has intensified the trend towards applications for electronic purchases and delivery services, to provide customers the facility of buying from anywhere and anytime, with great ease. However, there are some issues with these kind of purchases and delivery services. In particular, the data collected by these applications has the potential of having their security and privacy breached. Thus, trust of the service provider cannot be taken for granted. In fact, the service provider may prove to be a source of real danger to the privacy of users, especially if the service provider itself is a malicious party. Thus, it is difficult for the user to determine which applications can be trusted, and who to share their home or business location with. To solve this problem, in this research, we propose a new central platform that enables users to gather all of their (main) locations and control access to these locations in one place. Then the user can share them with other applications, such as link with hash-code included in a quick response (QR) barcode without the need to save their data in any application database. Moreover, the QR-code will be deactivated once it is used by the service provider, after the order is delivered. Therefore, the service provider will not be able to exploit the data stored in it, which means greater protection for the user's privacy. The system will offer other features for the user and the service provider as well. We have also implemented this system in a real manner to confirm its ability to improve the level of service in electronic purchase applications, in addition to improving the level of privacy of users' data. © 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth.

关键词： COVID-19

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AI in Agriculture: Yield Optimization and Food Security

AI in Agriculture: Yield Optimization and Food Security

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Technological Advancements in Computational sciences (ICTACS), International Conference on

作者： Lavanya Chavan Rishikesh Kumbhalkar Poorva Agrawal Nitin Rakesh R. Parvathi Mohammad Shahid Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Dept. of Smart Computing School of Computer Science Engineering and Information Systems Vellore Institute of Technology (VIT) Vellore India Noida Institute of Engineering and Technology Greater Noida India

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

Artificial Intelligence (AI) is remarkably automating the agricultural methods. In this process, AI is helping to optimize yield, and improving food security in a world with growing population and environmental concern(s). AI technology integration in agriculture is the focus of this paper which includes predictive analytics, machine learning and IoT. These applications led to precision farming and resource management which lead to efficient use of resources. The discussion on the benefits of AI in increasing productivity and sustainability is based on the summarization of the latest literature and empirical studies. Yet, these technologies bring along their own issues such as initial capital investment to implement the systems.in emergence economies as well as the need for the rapid upgrading of the infrastructure and human capital. This research demonstrates that AI has the potential to change agriculture radically, while at the same time acknowledging the pending problems that hinder full-fledged implementation.

关键词： Training Food security Agriculture Resource management Artificial intelligence Sustainable development Socioeconomics Optimization Farming Investment

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Implementation and Application of an Intelligibility Protocol for Interaction with an LLM

arXiv

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arXiv 2024年

作者： Srinivasan, Ashwin Bania, Karan Shreyas, V. Mestha, Harshvardhan Liu, Sidong Dept. of Computer Science & Information Systems BITS Pilani Goa Campus Goa India APPCAIR BITS Pilani Goa India Dept. of Chemistry BITS Pilani Goa Campus Goa India Dept. of Electrical and Electronics Engineering BITS Pilani Goa Campus Goa India Centre for Health Informatics Macquarie University Sydney Australia

Our interest is in constructing interactive systems.involving a human-expert interacting with a machine learning engine on data analysis tasks. This is of relevance when addressing complex problems arising in areas of science, the environment, medicine and so on, which are not immediately amenable to the usual methods of statistical or mathematical modelling. In such situations, it is possible that harnessing human expertise and creativity to modern machine-learning capabilities of identifying patterns by constructing new internal representations of the data may provide some insight to possible solutions. In this paper, we examine the implementation of an abstract protocol developed for interaction between agents, each capable of constructing predictions and explanations. The PXP protocol, described in [12] is motivated by the notion of "two-way intelligibility" and is specified using a pair of communicating finite-state machines. While the formalisation allows the authors to prove several properties about the protocol, no implementation was presented. Here, we address this shortcoming for the case in which one of the agents acts as a "generator" using a large language model (LLM) and the other is an agent that acts as a "tester" using either a human-expert, or a proxy for a human-expert (for example, a database compiled using human-expertise). We believe these use-cases will be a widely applicable form of interaction for problems of the kind mentioned above. We present an algorithmic description of general-purpose implementation, and conduct preliminary experiments on its use in two different areas (radiology and drug-discovery). The experimental results provide early evidence in support of the protocol’s capability of capturing one- and two-way intelligibility in human-LLM in the manner proposed in [12]. © 2024, CC BY.

关键词： Machine learning

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Performance Evaluation of WLAN Access Points Selection Metrics for Fingerprinting based Localization

Performance Evaluation of WLAN Access Points Selection Metri...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Sohaib Bin Altaf Khattak Moustafa M. Nasralla Maged Abdullah Esmail Mohamed Marey Nikumani Choudhury Smart Systems Engineering Lab College of Engineering Prince Sultan University Riyadh Kingdom of Saudi Arabia Dept. of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Hyderabad India

abstract Reliability and cost are essential elements to consider in all engineering network designs. In RF-localization systems. reliability can be defined as seamless coverage with precise and accurate localization. Cost-efficiency aims to reduce the infrastructure while simultaneously maintaining high accuracy. Both the cost and reliability can be associated with Access Points (APs) deployment. Therefore, it is paramount to study how to optimize the APs placement in RF-localization systems. To select the optimal AP configuration, different selection metrics are proposed. This paper investigates different AP placement and optimization strategies for WLAN fingerprinting indoor localization systems. Performance of selection metrics are evaluated experimentally in a realistic indoor environment. A fingerprinting database is developed by a grid spacing of 2m using 7 WLAN APs, by collecting Received Signal Strength (RSS) values using an Android smartphone app. The experimental results show, the AP configuration obtained by the metric combining the fingerprint difference metric with the geometric dilution of precision, results in high localization accuracy.

关键词： Location awareness Performance evaluation Wireless LAN Costs Fingerprint recognition Reliability engineering Minimization

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Repairing with Zero Skip Cost

arXiv

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arXiv 2024年

作者： Zhang, Wenqin Chee, Yeow Meng Dau, Son Hoang Etzion, Tuvi Kiah, Han Mao Luo, Yuan School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Dept. of Industrial Systems Engineering and Management National University of Singapore Singapore School of Computing Technologies RMIT University MelbourneVIC Australia Computer Science Faculty Technion Israel Institute of Technology School of Physical and Mathematical Sciences Nanyang Technological University Singapore

To measure repair latency at helper nodes, we introduce a new metric called skip cost that quantifies the number of contiguous sections accessed on a disk. We provide explicit constructions of zigzag codes and fractio...

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A Study on the Impact of Gender, Employment Status and Academic Discipline on Cyber Hygiene: A Case Study of University of Nigeria, Nsukka

arXiv

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arXiv 2023年

作者： Ugwu, Celestine Ezema, Modesta Ome, Uchenna Ofusori, Lizzy Olebera, Comfort Ukwandu, Elochukwu Department of Computer Science University of Nigeria Nsukka Nigeria School of Management Information Technology & Governance University of KwaZulu-Natal Westvillle Campus Durban South Africa Dept. of Computer Science Faculty of Physical Science Imo State University Owerri Nigeria Dept. of Applied and Computing Engineering Cardiff School of Technologies Cardiff Metropolitan University United Kingdom

The COVID-19 pandemic has helped amplify the importance of Cyber Hygiene. As the reliance on the Internet and IT services increased during the pandemic. This in turn has introduced a new wave of criminal activities such as cybercrimes. With the emergent of COVID-19 which lead to increase in cyber-attacks incidents, the pattern and sophistication, there is an urgent need to carry out an exploratory study to find out users’ level of cyber-hygiene knowledge and culture based on gender, employment status and academic discipline. Above this, with many organisations providing for dual mode work pattern or remote and in-person as the pandemic subsides, this study remains very relevant and hence the aim to investigate the cyber-hygiene knowledge and compliance of university students and employees of the University of Nigeria, Nsukka (UNN). In addition, it attempts to verify the relationship between demographics such as gender, employment status and academic discipline on cyber hygiene culture among students and employees. The sample population is made of employees and students of UNN, where the employees are either academic staff or non-academic staff. The sample size consisted of three hundred and sixteen (316) participants, one hundred and eight-seven (187) of whom were females and one hundred and twenty-nine (129) were males. The results offer some useful insight on cyber hygiene practices at the university © 2023, CC BY-NC-SA.

关键词： COVID-19

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