A Direct Data-Cluster Analysis Method Based On Neutrosophic Set Implication,
2020
University of New Mexico
A Direct Data-Cluster Analysis Method Based On Neutrosophic Set Implication, Florentin Smarandache, Sudan Jha, Gyanendra Prasad Joshi, Lewis Nkenyereya, Dae Wan Kim
Branch Mathematics and Statistics Faculty and Staff Publications
Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine …
Vehicle Operator Attention Monitor,
2020
The University of Akron
Vehicle Operator Attention Monitor, Matthew Krispinsky, Matt Marsek, Matthew Mayfield, Brian Call
Williams Honors College, Honors Research Projects
Motor vehicle operators’ attention levels can be monitored to improve driver safety. By recording and analyzing the drivers eye gaze, hand position, vehicle speed and engine rpm the driver’s attention can be determined. A Raspberry Pi will be the main processing unit. Data will be pulled and analyzed from the OBD-II port on vehicle speed and engine rpm. The system will be powered from a 12V, 4A pin on the OBD-II port connected to the car battery. A webcam will be used to track the pupil location and determine when the driver is looking at the road. A battery powered …
Tabletop Mechanical Tester,
2020
The University of Akron
Tabletop Mechanical Tester, Jamie Dombroski, Brian English, Richard Leffler, Andrew Shirk
Williams Honors College, Honors Research Projects
The need for hands-on and face-to-face experiences in the engineering classroom is very great. The equations, principles, and concepts can all be learned, but without the visual and tactile application, these don’t always sink in or become concrete. A small-scale tensile test machine was designed, sourced, manufactured, and tested for the purpose of being applied in classroom settings to provide this experience to engineering students. Extensive research was performed concerning tensile machines on the market, the essential elements of which are the load cell, grips, crosshead, extensometer, motor, and frame. The raw materials for the frame were purchased and drawings …
Measuring Decentrality In Blockchain Based Systems,
2020
Old Dominion University
Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla
VMASC Publications
Blockchain promises to provide a distributed and decentralized means of trust among untrusted users. However, in recent years, a shift from decentrality to centrality has been observed in the most accepted Blockchain system, i.e., Bitcoin. This shift has motivated researchers to identify the cause of decentrality, quantify decentrality and analyze the impact of decentrality. In this work, we take a holistic approach to identify and quantify decentrality in Blockchain based systems. First, we identify the emergence of centrality in three layers of Blockchain based systems, namely governance layer, network layer and storage layer. Then, we quantify decentrality in these layers …
Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence,
2020
Symbiosis Institute of Technology,Symbiosis International University, MITSOE, MIT-ADT University, Pune, India
Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence, Pooja Kamat, Rekha Sugandhi Dr.
Library Philosophy and Practice (e-journal)
The new industrial revolution called Industry 4.0 is proliferating at its peak. The time is no longer away when the human race is going to witness a huge paradigm shift. Intelligent machines empowered by Artificial Intelligence (AI)will take over the presence of human workers in the industrial manufacturing sector with the target of achieving 100% automation. With the emergence of cut-throat price competition in the product market, it has become equally important to manufacture goods at minimal costs and with the highest quality. Predicting the decrease in machinery efficiency at an earlier stage to accomplish this objective helps to reduce …
The Impact Of E-Commerce On The Development Of Entrepreneurship In Saudi Arabia,
2020
Princess Noura Bint Abdulrahman University
The Impact Of E-Commerce On The Development Of Entrepreneurship In Saudi Arabia, Khulood Al-Mani
Journal of International Technology and Information Management
This paper is based on a Ph.D. study investigating the critical challenges facing e-commerce adoption by entrepreneurs in Saudi Arabia, identifying the major driving factors, barriers, motivations, perceived advantages, potential problems and some practical solutions as well as future expectations from entrepreneurs’ perspectives. From the study findings, a set of practical recommendations were derived for the government, entrepreneurs and investors in Saudi Arabia to consider, to promote ecommerce entrepreneurship in the county.
The research was undertaken using a qualitative approach. Data collection techniques involved in-depth, semi-structured interviews, with (1) e-commerce entrepreneurs, and (2) government authorities, educational initiatives and private support …
Blockchain Adoption Model For The Global Banking Industry,
2020
Coventry University
Blockchain Adoption Model For The Global Banking Industry, Zaina Kawasmi, Evans Akwasi Gyasi, Deneise Dadd
Journal of International Technology and Information Management
Blockchain has become the new hype term in the business world for the last decade. Due to the new technology’s characteristics and innovative applications, it is being adopted globally in a wide number of industries including the banking industry, yet no adoption model is provided to guide this process. This research aims to contribute to facilitating the successful adoption and implementation of the blockchain new technology in the banking industry. Building on the assumption that the blockchain’s adoption in banking will be directed by the regulations and best practices guidelines of the global banking regulatory bodies and practitioner, this research …
Table Of Contents Jitim Vol 29 Issue 1, 2020,
2020
California State University, San Bernardino
Table Of Contents Jitim Vol 29 Issue 1, 2020
Journal of International Technology and Information Management
Table of contents
Table Of Contents Jitim Vol 29 Issue 3, 2020,
2020
California State University, San Bernardino
Table Of Contents Jitim Vol 29 Issue 3, 2020
Journal of International Technology and Information Management
Table of contents
A Probabilistic Machine Learning Framework For Cloud Resource Selection On The Cloud,
2020
University of the Pacific
A Probabilistic Machine Learning Framework For Cloud Resource Selection On The Cloud, Syeduzzaman Khan
University of the Pacific Theses and Dissertations
The execution of the scientific applications on the Cloud comes with great flexibility, scalability, cost-effectiveness, and substantial computing power. Market-leading Cloud service providers such as Amazon Web service (AWS), Azure, Google Cloud Platform (GCP) offer various general purposes, memory-intensive, and compute-intensive Cloud instances for the execution of scientific applications. The scientific community, especially small research institutions and undergraduate universities, face many hurdles while conducting high-performance computing research in the absence of large dedicated clusters. The Cloud provides a lucrative alternative to dedicated clusters, however a wide range of Cloud computing choices makes the instance selection for the end-users. This thesis …
Table Of Contents Jitim Vol 29 Issue 2, 2020,
2020
California State University, San Bernardino
Table Of Contents Jitim Vol 29 Issue 2, 2020
Journal of International Technology and Information Management
Table of contents
Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data,
2019
University of Pennsylvania
Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang
Computer Science Faculty Research
Background: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause computational challenges to applying conventional survival analysis. Results: We propose a novel biologically interpretable pathway-based sparse deep neural network, named Cox-PASNet, which integrates high-dimensional gene expression data and clinical data on a simple neural network architecture for survival analysis. Cox-PASNet is biologically interpretable where nodes in the neural network correspond to biological genes and pathways, while capturing the nonlinear …
Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities,
2019
Universitas Ahmad Dahlan, Indonesia
Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao
Knowledge Engineering and Data Science
The signal produced by human brain waves is one unique feature. Signals carry information and are represented in electrical signals generated from the brain in a typical waveform. Human brain wave activity will always be active even when sleeping. Brain waves will produce different characteristics in different individuals. Physical and behavioral characteristics can be identified from patterns of brain wave activity. This study aims to distinguish signals from each individual based on the characteristics of alpha signals from brain waves produced. Brain wave signals are generated by giving several mental perception tasks measured using an Electroencephalogram (EEG). To get different …
Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms,
2019
Universitas Brawijaya, Indonesia
Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms, Retno Dewi Anissa, Wayan Firdaus Mahmudy, Agus Wahyu Widodo
Knowledge Engineering and Data Science
There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate …
Handwriting Character Recognition Usingvector Quantization Technique,
2019
Universitas Mulawarman, Indonesia
Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi
Knowledge Engineering and Data Science
This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal variant of network architecture in the recognition process is a variation of learning rate of 0.02, a maximum epoch of 5000 and a hidden layer of 90 neurons which was the result of recognition based on feature 8. Based on these variations, the obtained performance with a mean square error (MSE) of 0.0306 and the time required during the learning …
Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method,
2019
Universitas Negeri Malang, Indonesia
Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto
Knowledge Engineering and Data Science
The development of Indonesia's imports fluctuate over years. Inability to anticipate such rapid changes can cause economic slump due to inappropriate policy. For instance, recent years imports in rice led to the extermination of rice reserves. The reason is to maintain the market price of rice in Indonesia. To overcome these changes, forecasting the amount of imports should assist the Government in determining the optimum policy. This can be done by utilizing an algorithm to forecast time series data, in this case the amount of imports in the next few months with a high degree of accuracy. This study uses …
Comparison Of Naïve Bayes Algorithm And Decision Tree C4.5for Hospital Readmission Diabetes Patientsusing Hba1c Measurement,
2019
Universitas Negeri Malang, Indonesia
Comparison Of Naïve Bayes Algorithm And Decision Tree C4.5for Hospital Readmission Diabetes Patientsusing Hba1c Measurement, Utomo Pujianto, Asa Luki Setiawan, Harits Ar Rosyid, Ali M. Mohammad Salah
Knowledge Engineering and Data Science
Diabetes is a metabolic disorder disease in which the pancreas does not produce enough insulin or the body cannot use insulin produced effectively. The HbA1c examination, which measures the average glucose level of patients during the last 2-3 months, has become an important step to determine the condition of diabetic patients. Knowledge of the patient's condition can help medical staff to predict the possibility of patient readmissions, namely the occurrence of a patient requiring hospitalization services back at the hospital. The ability to predict patient readmissions will ultimately help the hospital to calculate and manage the quality of patient care. …
Effective Fuzzing Framework For The Sleuthkit Tools,
2019
Louisiana State University and Agricultural and Mechanical College
Effective Fuzzing Framework For The Sleuthkit Tools, Shravya Paruchuri
LSU Master's Theses
The fields of digital forensics and incident response have seen significant growth over the last decade due to the increasing threats faced by organizations and the continued reliance on digital platforms and devices by criminals. In the past, digital investigations were performed manually by expert investigators, but this approach has become no longer viable given the amount of data that must be processed compared to the relatively small number of trained investigators. These resource constraints have led to the development and reliance on automated processing and analysis systems for digital evidence. In this paper, we present our effort to develop …
Algorithms For Designing Processes Of Electronic Interactive Services,
2019
Tashkent university of information technologies(TUIT), Uzbekistan
Algorithms For Designing Processes Of Electronic Interactive Services, Ozod Radjabov
Bulletin of TUIT: Management and Communication Technologies
Today, the integration of electronic interactive services is based on the correct placement of algorithms to ensure solidarity in information systems, the design stages of information systems based on interactive services and the corresponding events, the implementation of functions in a strict sequence.
On I/O Performance And Cost Efficiency Of Cloud Storage: A Client's Perspective,
2019
Louisiana State University and Agricultural and Mechanical College
On I/O Performance And Cost Efficiency Of Cloud Storage: A Client's Perspective, Binbing Hou
LSU Doctoral Dissertations
Cloud storage has gained increasing popularity in the past few years. In cloud storage, data are stored in the service provider’s data centers; users access data via the network and pay the fees based on the service usage. For such a new storage model, our prior wisdom and optimization schemes on conventional storage may not remain valid nor applicable to the emerging cloud storage.
In this dissertation, we focus on understanding and optimizing the I/O performance and cost efficiency of cloud storage from a client’s perspective. We first conduct a comprehensive study to gain insight into the I/O performance behaviors …
