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International Journal of Information Engineering and Electronic Business @ijieeb
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 706
An Investigation on IoT Healthcare Analytics
Статья научная
The Internet of Things makes things to become active participants enabling communication between things and transfer of data among themselves. It has a wide range of applications in various domain such as healthcare. The Internet of Things changes the way of delivering healthcare solution to people. It maintains a smooth relationship between doctors and patients which leads to high quality results in medical care. These are achieved by continuous monitoring of patients by using sensors. The data collected are recorded and used for analytics in future purpose. The analytical solution in healthcare data gives a potential for identification of diseases. This paper concerns the Internet of Things in healthcare and also portrays the technology involved in it. The paper discuss the architectures and services involved in medical care solution. Further the mechanism involved in healthcare analytics and data sources involved in analytics are explained. The various algorithms involved in it are investigated. It also analyses the various challenges in healthcare perspective.
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An Ontology-Based System for Cancer Diseases Knowledge Management
Статья научная
Cancer is a class of diseases characterized by out-of-control cell growth. There are over 200 different types of cancer, and each is classified by the type of cell that is initially affected. This paper discusses the technical aspects of some of the ontology-based medical systems for cancer diseases. It also proposes an ontology based system for cancer diseases knowledge management. The system can be used to help patients, students and physicians to decide what cancer type the patient has, what is the stage of the cancer and how it can be treated. The system performance and accuracy are acceptable, with a cancer diseases classification accuracy of 92%.
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An Overview of Operating Systems Based on Microkernel Technology and their Essential Components
Статья научная
In conventional monolithic operating system architecture, the kernel delivers all the necessary services to the application programs. The microkernel operating system is important in several areas such as industrial control systems, embedded systems, and real-time systems. As the requirements of the operating system increase, the kernel expands in size and increases complexity. The introduction of Operating Systems focusing on Microkernels was due to the difficulties mentioned above caused by Operating Systems with Monolithic kernels. Operating systems based on microkernels offer enhanced security and flexibility to the system. A comprehensive review of eleven distinct operating systems based on the microkernel architecture is presented in this study. Some microkernels provide great advantages like strong security, better performance, and reliability also some microkernels have disadvantages like increased complexity, high cost in making, and low performance. The three main components of the study are process scheduling, memory management, and inter-process communication. This overview provides a comprehension of the various advances in creating operating systems based on microkernel technology. The data sources included books, research papers, and official documentation of individual microkernels.
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An SDDS-Based Architecture for a Real-Time Data Store
Статья научная
Recent prognoses about the future of Internet of Things and Internet Services show growing demand for an efficient processing of huge amounts of data within strict time limits. First of all, a real-time data store is necessary to fulfill that requirement. One of the most promising architecture that is able to efficiently store large volumes of data in distributed environment is SDDS (Scalable Distributed Data Structure). In this paper we present SDDS LH*RT, an architecture that is suitable for real-time applications. We assume that deadlines, defining the data validity, are associated with real-time requests. In the data store a real-time scheduling strategy is applied to determine the order of processing the requests. Experimental results shows that our approach significantly improves the storage Quality-of-service in a real-time environment.
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An approach for forecast prediction in data analytics field by tableau software
Статья научная
The current era is generally treated as the era of data, Users of computer are gradually increasing day by day and vast amount of data is generated from multiple domains such as healthcare- domain, Business related domains etc. The terminology Business Intelligence (BI) generally refers different technologies, applications and practices used for the collection, integration, analysis, and presentation of information of business related domain. The main motive for Business intelligence and analytics are to help in decision making process and to enhance the profit of the organisation. Various business related tools are used to analyze & visualize different types of data which are generated frequently. Tableau prepared its mark on the Field of BI by being one of the first companies to permit business customers the ability to achieve equitably arduous data visualization in a very interesting, drag and drop manner. Tableau will enhance decision making, add operational awareness, and increase performance throughout the organization The presented paper describes different tools used for business intelligence field and provides a depth knowledge regarding the tableau tool. It also describes why tableau is widely used for data visualization purpose in different organization day by day. The main aim of this paper is to describe how easily forecasting and analysis can be done by using this tool ,this paper has explained how easily prediction can be done through tableau by taking the dataset of a superstore and predict the forthcoming sales and profit for the next four quarters of the forthcoming year. In the collected dataset sales and profit details of different categories of goods are given and by using the forecasting method in tableau platform these two measures are calculated for the forthcoming year and represented in a fruitful way. Finally, the paper has compared all the framework used for business intelligence and analytics on the basis of various parameters such as complexity, speed etc.
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An information-based integration framework to support building construction industry
Статья научная
Information integration provides the basis for effective team work. The research work is aimed at for-mulating a framework of information integration to sup-port the building construction industry. A conceptual model was created based on the requirements obtained from the industry. Qualitative research and quantitative research were adopted for the study which involves ex-pert opinion, data requirements and data collection method, data analysis and sensitizing concepts. Questionnaire was developed and administered based on the information obtained from the interview. Drawing on the interviews and the questionnaires administered, a framework was developed to harness the information needed for construction projects. This paper provides members such as land surveyor, contractor, quantity surveyor, engineers, architect and project manager in a team the platform to execute their work from anywhere and anytime without delay. The major advantages of this framework are: to provide members of a building construction team to work from anywhere and at any time and to articulate their activities in a way that can help develop positive work culture. Finally, the framework will enable information system developer develop a system to support building construction work activities.
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An optimized model for breast cancer prediction using frequent itemsets mining
Статья научная
This presented research paper mainly studies the frequent itemsets mining approach for finding the most important attribute to overcome the existing problems in the extraction of relevant information by using data mining approaches from a huge amount of dataset. Firstly a state of art diagram for prediction is designed and data mining classifier like naive bayes, support vector machine, decision tree, k- nearest neighbour are compared and then proposed methodology with new techniques are proposed. Moreover, a new attribute filtering association frequent itemsets mining algorithm is presented. Then, by analyzing the feasibility of the proposed algorithm, the data mining classification classifier is compared. As a result, SVM produces the best result among all the classifier with attribute filtrating and without attribute filtrating. With attribute filtrating algorithm enhances the accuracy of all the other classifier.
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Analysis Method of Internet Advertising-Marketing Information’s Dynamic Changes
Статья научная
In the article internet advertising-marketing information’s dynamic changes, indicator parameters of that characterizes effectiveness of internet advertising campaign have been analysed. For evaluation of advertising activities, analysis of dynamic changes to obtain and calculation values of selective parameters have been researched. In equal time intervals obtained values from indicator parameters that is obtained with their values value matrix can be created. In order to eliminate inequal time intervals it is recommended interpolated operations should be conducted. Therefore, by selecting parameters which have statistical communication, through using experimental values of these parameters model has been established for evaluation of effectiveness of Internet advertising campaign.
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Статья научная
Geographic information system is a computer-based information system that is used to store, examine, integrate, manipulate, and display data related to the earth's surface. Melak is a non-governmental organization that was born out of concern about the increasing destruction of natural resources, and the increasingly marginalized local or indigenous people in managing natural resources and the increasingly rapid expansion of large-scale oil palm plantations which in fact threatens not only the existence of forests, but also threatens the existence of the forest. humans and other living things. Melak plays an important role in mapping the location of oil palm plantations and agriculture as well as knowing the number of oil palm tree trunks managed by organizations and independent smallholders. The purpose of this study is to design a system that can be used for mapping agricultural land and plantations using a database as a storage medium.
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Analysis and Design of Prefetching Framework for Mozilla Firefox
Статья научная
The presence of number of web sites has increased the user's attraction towards web objects. This tremendous use came up with the future requests prediction depending upon the current and past access behaviour. Use of Internet has boomed up a lot since the last decade. This use also came with the heavy load on the internet. In today's world, speed plays a significant role and hence the speed augmentation is one of the biggest issues. For this, web latency reduction by prefetching is one of the good ideas. For the same, web prefetching is performed, where user's next expected requests are prefetched in the web cache of the web browser. A browser is basically a GUI based application program, which provides a platform for running Internet. Mozilla Firefox is a web browser, which is in very much use these days. This paper provides an analysis of Mozilla Firefox prefetching technique (link and DNS prefetching) and then designs a new prefetching scheme for the same. The experimental results are performed in Matlab 5.0. The results show that the designed prefetching framework is more efficient in terms of the cache hit ratio.
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Analysis and prediction of individual stock prices of financial sector companies in NIFTY50
Статья научная
Prediction of the stock market is currently a big business opportunity for the data analytic solution providers. As the vast range of factors influencing the stock market index are available, it is essential to find the relation between those macroeconomic variables with company share prices and predict the accurate results. Our research is analyzing different relation between the prediction and individual stock prices of financial sector companies in National Stock Exchange 50(NIFTY 50). To make a strong portfolio the selection of different companies is one of the vital decisions we should attempt for a good investment. Trending researches regarding financial forecast are based on the accuracy of the models that how well National Stock Exchange (NSE) index values can be predicted. There is significant literature survey available on the prediction of the stock market as well as its pricing. NIFTY 50 is one of the well-known indexes in India for the investors seeking a good investment. In our research, we attempt, to forecast the stock values of different organizations of Banking and Financial sectors in NIFTY 50. Before including the factors to forecast share market index we are trying to find the relation between different factors and indices of those companies. The study empirically proves that the proposed model is precise to be used in real time stock prediction which can benefit the sellers, investors and stakeholders in their real time savings, investment, and speculation.
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Статья научная
Personal Health Record or we know as the medical record in Indonesia has its regulations relating to ownership, confidentiality and authorization from the authorities to provide medical record entries to their ownership. Not many health facilities in Indonesia that digitize medical record data storage and there are still many health facilities that use third parties to manage medical record data. This raises problems such as data access, data exchange, privacy, security and approval among the people involved in it. In this case, the doctor is authorized to provide the patient’s medical record, according to the examination results that have been carried out by the patient. Blockchain technology or distributed ledger technology seems to offer a solution to some of the problems encountered. Blockchain is a digital ledger of verified transactions that are locked chronologically in an encrypted chain. This platform uses a decentralized approach that allows the information to be distributed and that each piece of distributed information or commonly known as data have shared ownership. Based on these functional needs, Blockchain technology Ethereum can be a solution. Ethereum blockchain provides smart contract features that are stateful and Turing-completeness, so that it can be used to store data and execute complex operations. This study provides an overview of how blockchain technology can be a solution to problems that arise related to the storage of patient medical record data in Indonesia. While the InterPlanetary File System (IPFS) is used to accommodate file sharing requirements.
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Статья научная
The previous research revealed some functional coupling among nodes in model of motor control in human brain, which described nondirectional synchronous actions among these nodes during movement-readiness state. However, causal relationships among these nodes, which represent some directional interactions in movement-readiness state, are still lack. In the present study, we used functional magnetic resonance imaging (fMRI) and conditional Granger causality (CGC) method to investigate the interactions in model of motor control in left hand’s movement readiness state. Our results showed that upper precuneus (UPCU) and cingulated motor area (CMA) revealed net causal influences with contra lateral supplementary motor areas and contra lateral caudate nucleus during the left hand’s movement-readiness state. The net causal flows among these nodes can construct a closed circuit, which is similar as the circuit found in monkey’s brain and in human’s brain in right hand’s movement readiness state. This confirmed that there was an intrinsic circuit for motor control in either right hand’s or left hand’s movement readiness. Moreover, the results of Out-In degrees indicated that bilateral primary sensorimotor areas revealed competitive relationship during left hand’s movement-readiness.
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Analysis of Quantum Algorithms with Classical Systems Counterpart
Статья научная
In this note, we look into two quantum algorithms, Deutsch-Josza's and Shor's algorithms. An attempt made to analyze classical as well as quantum parts computation. With that, analyze classical as well quantum parts complexities.
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Статья научная
This study was based on changes in the work environment, from a pandemic to a post-pandemic state where employee performance began to increase. This study aimed to analyze the performance of employees who have improved based on environmental factors and communication through motivation as a mediator variable. This study was quantitative descriptive research with data collection using questionnaires. The population was employees of PT. Givaudan Indonesia, as an observation unit referred to as census techniques. Data analysis used Partial Least Square (PLS) based on the Structural Equation Model (SEM). The result of the study was the work environment has a positive and significant effect on motivation. The work environment has a positive but not significant effect on employee performance. Communication has a positive but not significant effect on motivation. Communication has a positive and significant effect on employee performance. Motivation has a negative and insignificant effect on employee performance. The work environment has a negative and insignificant effect on employee performance through motivation. Communication negatively and insignificantly affects employee performance through motivation. The work environment and communication simultaneously have a positive and significant effect on motivation. Work environment and communication as well as motivation simultaneously have a positive and significant effect on employee performance. The conclusion of this study shows that the work environment and communication affect performance, while motivation does not affect employee performance.
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Analysis of amazon product reviews using big data- apache pig tool
Статья научная
We live in the era of digital technologies where data is increasing day by day at a very high rate. The data is further popularly classified as ‘Big Data’ because of its velocity, veracity, variety and its huge volume. This data could be unstructured, semi-structured or structured as it is divergent in nature. In this work, we would assess various categories of Amazon Product Reviews, the large datasets that contain around 144 million reviews in total. The datasets consists of Product reviews collected from Amazon, each having various numbers of attributes of 11 different categories. The motive of this work is to find and compare the ratings of the products during the lifespan of the product reviews. Another goal of this work is to help Amazon regarding the listing of the products in their database. This work aims to relate user’s ratings and reviews to discover how beneficial and good a product is [6]. User ratings are collected and are analyzed based on different categories (datasets) which gives an insight as to which product performs good and what are the problems associated to a certain non-performing product.
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Analysis of the New Generation source-to-source Compilers Using the Google Web Toolkit
Статья научная
The role of source-to-source compilers nowadays increases faster since each high-level language is in a need to gain more recognition in each field of development. One of the fields that became very popular in the last ten years is web development, where the browsers became the “machines” of our everyday life. They are relevant and powerful, and the only drawback they have is that they only understand one language, that is JavaScript. The need of other languages to be included in the client side of the web development, created the steam for source-to-source compiling, sometimes referred as Transpiling, where one high level language as Java, C, C# and many others are translated mostly, but not solely, to JavaScript. A famous tool that is well recognized is Google Web Toolkit (GWT) which translates Java source code to JavaScript source code. The core of this tool is the compiler which is covered in great details in this paper. Main goal and benefit of this paper is to analyze and compare the difference of the process of translation to JavaScript by transpiler to the process of “normal” compiling and to highlight key aspects of this process.
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Analysis of the Time Trends of Precipitation over Mediterranean Region
Статья научная
Time trends of precipitation in the north of Algeria from meteorological radar are analysed. A probabilistic approach presented here proposes to study the evolution of the rainfall phenomenon in two distinct study areas, one located in sea and other located in ground. A decision criterion is established and based on radar reflectivity in order to classify the precipitation events located in both areas. At each radar observation, a state of precipitation is classified, either convective (heavy precipitation) or stratiform (average precipitation) both for the "sea" and for the "ground". In all, a time series of precipitation composed of three states; no raining, stratiform precipitation and convective precipitation, is obtained for each of the two areas. Thereby, we studied and characterized the behavior of precipitation in time by a Markov chain of order one with three states. Transition probabilities are calculated. The results show that rainfall is well described by a Markov chain of order one with three states. Indeed, the stationary probabilities, which are calculated by using the Markovian model, and the actual probabilities are almost identical.
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Analysis on Shape Image Retrieval Using DNN and ELM Classifiers for MRI Brain Tumor Images
Статья научная
The problem of searching a digital image in a very huge database is called Content Based Image Retrieval (CBIR). Shape is a significant cue for describing objects. In this paper, we have developed a shape feature extraction of MRI brain tumor image retrieval. We used T1 weighted image of MRI brain tumor images. There are two modules: feature extraction process and classification. First, the shape features are extracted using techniques like Scale invariant feature transform (SIFT), Harris corner detection and Zernike Moments. Second, the supervised learning algorithms like Deep neural network (DNN) and Extreme learning machine (ELM) are used to classify the brain tumor images. Experiments are performed using 1000 brain tumor images. In the performance evaluation, sensitivity, specificity, accuracy, error rate and f-measure are five measures are used. The Experiment result shows that highest average accuracy has got at Zernike Moments– 99%. So, Zernike Moments are better than SIFT and Harris corner detection techniques. The average time taken for DNN- 0.0901 sec, ELM- 0.0218 sec. So, ELM classifier is better than DNN. It increases the retrieval time and improves the retrieval accuracy significantly.
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Analyzing the Energy Efficiency and Sustainability Implications of IoT Tools in Smart Homes
Статья научная
This research endeavors to provide a thorough and insightful analysis of Internet of Things (IoT) tools within the context of smart homes. As the IoT continues to revolutionize the domestic landscape, understanding the integration, functionality, and user experience of these tools becomes paramount. The study surveys and categorizes prevalent IoT tools, encompassing sensors, processors, actuators, and databases. Integration capabilities are scrutinized, emphasizing interoperability and compatibility to ascertain the seamless incorporation of diverse IoT tools. Functional roles and contributions of each tool are dissected to illuminate their impact on automation, inter-connectivity, and overall control mechanisms in smart homes. The research extends its gaze to the user experience, exploring factors such as ease of use, reliability, and customization options, shaping the holistic perspective of IoT tools’ impact on residents. Realworld implementations and case studies provide tangible insights into practical applications, while surveys and interviews capture user perspectives, forming a comprehensive view of the challenges and limitations associated with these tools. This study contributes valuable insights for informed decision-making, empowering both users and developers to navigate the evolving landscape of IoT tools within the realm of smart homes.
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