Intelligent System for Forecasting Failure of Agile Projects

Ahmed Abdelaziz and Alia N

doi:https://doi.org/10.54216/JISIoT.050102

Fusion: Practice and Applications | 2021

Integration of Cultural Digital form and Material Carrier form of Traditional Handicraft Intangible Cultural Heritage

Intangible cultural heritage is the continuous progress of human society. Intangible cultural heritage refers to various traditional cultural expressions that exist in intangible form and are closely related to the lives of the people and inherited from generation to generation. Intangible cultural heritage is a human-oriented living cultural heritage. It emphasizes human-centric skills, experience, and spirit, and is characterized by living changes. What stands out is the intangible attribute, and more emphasis on the quality that does not depend on the material form. The biggest feature of intangible cultural heritage is that it is not divorced from the special life and production methods of the nation, and it is the "living of the nation's personality and national aesthetic habits. "Appears. It exists on the basis of human beings, using voice, image and skills as means of expression, and passing from word to mouth as a cultural chain to continue. It is the most vulnerable part of "living" culture and its traditions. Therefore, for the process of inheriting intangible cultural heritage, the inheritance of people is particularly important. The traditional handicraft intangible cultural heritage is one of the best. However, with the rapid development of society, the living environment of intangible cultural heritage has changed, and the intangible cultural heritage of traditional handicraft industry is rapidly declining or even disappearing. In order to protect traditional handicraft intangible cultural heritage, this article studies the influence of the integration of traditional handcrafted intangible cultural heritage with the form of material carrier, reading and analyzing a large number of related documents using the literature survey method, and according to research needs, through the study of the content of the literature In summary, a questionnaire survey method was adopted to investigate traditional handicraft intangible cultural heritage visitors and inheritors. The results of the survey found that visitors’ satisfaction with the integration of digital forms and physical carrier forms of intangible cultural heritage projects was nearly 30% higher than that of unintegrated forms. Inheritors generally believe that integrated research has better publicity and education for traditional handicraft intangible heritage. The merged handmade intangible cultural heritage items are easy to store, retrieve and query, and at the same time help to preserve the related traditional handmade intangible cultural heritage items safely and for a long time, making the traditional handmade intangible cultural heritage items widely spread and shared around the world.

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Saeed M. Aljaberi mail -

Ali Saadon Al-Ogaili mail

link https://doi.org/10.54216/FPA.050102

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2021

From the Wireless Sensor Networks (WSNs) to the Web of Things (WoT): An Overview

In the last two decades, Wireless Sensor Networks (WSNs) are gaining more popularity, where the concept of WSN always exists when everything connects. Almost of WSN applications cover wide area and large spaces for assessing and monitoring certain phenomenon. Moreover, WSN components have been integrated in daily life objects or things (object, place, and person), so that they could be monitored and controlled. As a result, a new paradigm called the Internet of Things (IoT) connects WSN components to the Internet to be globally monitored and controlled representing the surrounding environmental events and conditions. The future IoT is called the Web of Things (WoT), which visualizes the IoT data (sensory data) using current web tools and services (HTTP, RESTful services). This paper presents an overview of the WSNs, the IoT and its future paradigm (WoT) discussing key elements, main layers, main challenges, and annotation formats. 

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Mina Younan mail -

Sherif Khattab mail -

Reem Bahgat mail

link https://doi.org/10.54216/JISIoT.040201

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2021

Intelligent Image Detection System Based on Internet of Things and Cloud Computing

Images are the most intuitive way for humans to perceive and obtain information, and they are one of the most important sources of information. With the development of information technology, the use of digital image processing methods to locate and identify targets is widely used, so it is particularly important to detect the targets of interest quickly and accurately in the image. The traditional image detection system has the problems of low detection accuracy, long time consumption, and poor stability. Therefore, this paper proposes the design and research of artificial intelligence image detection system based on Internet of Things and cloud computing. The system designed in this article mainly includes three links, namely: image processing analysis design link in cloud computing environment, image feature collection module design link, and image integration detection link. The main technologies used in image processing and analysis in the cloud computing environment are virtualization technology, distributed massive data storage, and distributed computing. In the image feature collection module, before the image is input to the neural network, it is necessary to perform preprocessing operations on the distorted image and perform perspective correction; then use the deep residual network in deep learning to extract features. Finally, there is the image integration detection link. First, the target category judgment and position correction are performed on the regions generated by the candidate region generation network, and then the integrated image detection is performed through the improved target detection method based on the frame difference method. Through simulation experiments, compared with the traditional image detection system, the speed advantage of the artificial intelligence image detection system designed in this paper is obvious in the case of a large increase in the number of images. On images at different pixel levels, the accuracy of the image detection system proposed in this paper is always higher than that of traditional image detection systems, and the CPU usage and memory usage are at a lower level. In addition, within three months, the stability is also at a relatively high level of 0.9.

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Ossama Embarak mail -

Mhmed Algrnaodi mail

link https://doi.org/10.54216/JISIoT.040202

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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International Journal of Wireless and Ad Hoc Communication | 2021

Geological Landslide Disaster Monitoring Based on Wireless Network Technology

With the comprehensive influence of natural evolution and human activities, the damage degree of geological disasters is increasing. How to effectively early warning geological disasters has become a problem of concern. How to effectively provide early warning of geological disasters has become a concern of people. This research mainly discusses the geological landslide disaster monitoring based on wireless network technology. First, establish two important early warning indicators of rainfall and geological landslide displacement. The monitoring system is powered by a rechargeable 12V lithium battery, combined with solar panels, which can be charged when the sun is full to ensure the stable operation of the system. The AT45DB161B chip with 16M bytes storage capacity is selected to store data such as geological landslide displacement and rainfall. Use Microsoft SQL Server 2008 database management system to complete database content query, addition, modification, and deletion operations. The TLP521-2 photocoupler is used to isolate the GPIO interface of STM32 from the external unit to improve the anti-interference ability. The communication between the field data collector and the monitoring center data server adopts the GPRS packet data transmission method based on the TCP/IP protocol. Currently, the PDU in the network is an IP data packet. The realization of the TCP/IP protocol at the field data collector is all completed in the master single-chip microcomputer. Use SIEMENSMC35GSM/GPRS module as data transmission terminal. The monitoring results show that the absolute error of the test data does not exceed 6mm in the horizontal distance, the vertical height difference does not exceed 9mm. The results show that the monitoring of geological landslide based on wireless network technology improves the accuracy of distance estimation and reduces the positioning error, which can provide scientific guidance for the planning, monitoring and early warning of landslide area.

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Xiaohui Yuan mail -

Reem Atassi mail

link https://doi.org/10.54216/IJWAC.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2021

Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications

In recent years, a variety of wired and wireless network communication protocols in the field of industrial control have become increasingly mature. The purpose of this paper is to provide a Shared network communication bandwidth optimization management algorithm for large-scale industrial networked control systems in Internet of things applications. This algorithm is based on the generalized geometric convex optimization method and can realize the optimal allocation of Shared network communication bandwidth resources. L2 networked control systems is used in this paper for the establishment of various numerical relations between the control performance and the communication network parameters. Based on the generalized geometric convex optimization method for the numerical relationship between convex analysis and fitting, convexity, and with the convex analysis and the numerical relationship between convexity fitting as constraint conditions, the results of integrity for networked control systems with large-scale resource allocation target will share the optimal management of network resources as a generalized geometric convex optimization problem. Using convex optimization software package for optimizing the optimal global solution of management problem, i. e. the optimal allocation of resources, the algorithm realizes the stability of each networked control system and achieve optimal L2 control performance. It is concluded that the predetermined transmission rate between the network node one and network node two, the data flow information sent by the network node two to the network node one is read, the delay time and packet loss rate between the two nodes are determined, the delay time is reduced by about 8 seconds, and the packet loss rate is greatly reduced by 78%.

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M. Z. A. Ab Kadir mail -

Mhmed Algrnaodi mail -

Ahmed N. Al-Masri mail

link https://doi.org/10.54216/IJWAC.020103

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2022

A Multi-level Features Fusion Model for Network Communication based on Machine Learning

Today's societies couldn't function without elaborate networks of communication. Many problems remain unresolved, but novel approaches to these problems are constantly being offered. Many of the problems plaguing existing works, such as high characteristic design cost, challenging feature selection, poor real-time performance, etc., stem from their focus on a wide range of characteristics. Worse still, the difficulty in training models due to data imbalance results in a poor detection rate for aberrant samples. To achieve a more effective and robust model, we present a multi-level feature fusion (MFFusion) model that utilizes a combination of data temporal, byte, and statistical characteristics to extract relevant information from different angles. Too far, MFFusion has outperformed the state-of-the-art on several real-world network datasets in terms of prediction performance and false alarm rate. We also use MFFusion for anomaly detection in an IoT network, using the most recent IoT malicious traffic information. The experimental results demonstrate the adaptability of MFFusion and its suitability for identifying network anomalies in an IoT context with system performance.

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Mahmoud A. Zaher mail -

Nabil M. Eldakhly mail

link https://doi.org/10.54216/IJWAC.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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International Journal of Neutrosophic Science |

SVN-Ostrowski Type Inequalities for h-convex functions

We would like to state well-known Ostrowski inequality via the h-convex function by using the SVN-Reimann integrals. In addition, we establish some SVN-Ostrowski type inequalities for the class of functions whose derivatives in absolute values at certain powers are h-convex functions by using different techniques including Holder’s inequality and power mean inequality. We are introducing very first time that the class of h-convex function, which is the generalization of many important classes including the class of Godunova-Levin s-convex, s-convex in the 2nd kind and hence contains the class of convex functions. It also contains the class of P-convex functions and a class of Godunova-Levin functions. In this way, we also capture the results with respect to the convexity of functions.

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AliHassan mail

link

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Fusion: Practice and Applications | 2021

A Comparative Analysis and Prediction over Bitcoin Price Using Machine Learning Technique

Bitcoin is one of the primary computerized monetary forms to utilize peer innovation to work with moment installments. The free people and organizations who own the overseeing figuring control and take part in the bitcoin network—bitcoin "miners"— are accountable for preparing the exchanges on the blockchain and are persuaded by remunerations (the arrival of new bitcoin) and exchange charges paid in bitcoin. These excavators can be considered as the decentralized authority implementing the believability of the bitcoin network. New bitcoin is delivered to the excavators at a fixed yet occasionally declining rate. There is just 21 million bitcoin that can be mined altogether. As of January 30, 2021, there are around 18,614,806 bitcoin in presence and 2,385,193 bitcoin left to be mined. This paper will predict the nature of bitcoin price because according to the reports of the past few years. The year 2020-present appeared to be a good time for bitcoin because, during this time duration, bitcoin has seen huge ups and downs. This paper will use various Machine Learning Techniques for the predictive analysis of bitcoin to accurately predict the price's nature. As the price of bitcoin depends upon various factors, and these factors directly affect the price, i.e., multiple factors of bitcoin are dependent on each other. After analyzing the results from multiple research papers and review papers, we discovered each algorithm has its advantages and disadvantages when predicting the bitcoin value. Keeping in mind all the findings, we will find algorithms that predict the bitcoin price accurately and without fewer disadvantages. So, if we go as per assumptions, regression would be the best choice for predicting the bitcoin value, but there are others algorithms also. So, in this paper, we will see the results of the multiple algorithms and then choose the correct algorithm after analyzing the results of all the implemented algorithms. This paper also includes the implementation of the comparison charts with each algorithm so that it will be easy to analyze the findings of each algorithm.

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Meenu Gupta mail -

Riya Srivastava mail

link https://doi.org/10.54216/FPA.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2021

Intelligent Web Information Extraction Model for Agricultural Product Quality and Safety System

With the development of society, people pay more and more attention to the safety of food, and relevant laws and policies are gradually introduced and being improved. The research and development of agricultural product quality and safety system has become a research hot spot, and how to obtain the Web information of the system effectively and quickly is the focus of the research, so it is essential to carry out the intelligent extraction of Web information for agricultural product quality and safety system. The purpose of this paper is to solve the problem of how to efficiently extract the Web information of the agricultural product quality and safety system. By studying the Web information extraction methods of various systems, the paper makes a detailed analysis and research on how to realize the efficient and intelligent extraction of the Web information of the agricultural product quality and safety system. This paper analyzes in detail all kinds of template information extraction algorithms used at present, and systematically discusses a set of schemes that can automatically extract the Web information of agricultural product quality and safety system according to the template. The research results show that the proposed scheme is a dynamically extensible information extraction system, which can independently implement dynamic configuration templates according to different requirements without changing the code. Compared with the general way, the Web information extraction speed of agricultural product quality safety system is increased by 25%, the accuracy is increased by 12%, and the recall rate is increased by 30%.

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Mohammad Ali Tofigh mail -

Zhendong Mu mail

link https://doi.org/10.54216/JISIoT.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2021

Intelligent System for Forecasting Failure of Agile Projects

Revealing the failure of agile software projects is a great challenge faced by software companies. This paper focuses on the using of intelligent techniques such as fuzzy logic, multiple linear regressions, support vector machine, neural network to address this challenge. This paper also presents a review of some works related to this area of interest. In this paper, the researchers propose an approach for revealing the failure of agile software projects based on two intelligent techniques: fuzzy logic and multiple linear regressions (MLR). MLR is used to determine crucial failure factors of agile software projects. Fuzzy logic is used for revealing failure of agile software projects. 

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Ahmed Abdelaziz and Alia N Mahmoud mail

link https://doi.org/10.54216/JISIoT.050102

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new