An ACO Algorithm for Effective Cluster Head Selection

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan

Prophet Muḥammad in Dante’s Divine Comedy: An anxiety of influence

This article explores the century-long topic ‘Dante and Islam’ from the perspective of Harold’s Bloom’s theory of influence. It argues that Dante’s placement of Muḥammad in Inferno 28 could have been caused by an ‘anxiety’ incited by the Islamic influence on the Commedia as first suggested by Miguel Asín Palacios in 1919. With the intention of complementing the close readings of Maria Corti and Karla Mallette, the article’s analysis of the relevant verses in Inferno in light of Bloom’s theory reveals that there could be more to the famous scene of torture than the medieval antagonistic or ambivalent positions from Islam. The article also tackles the history of European and Arab scholarship dealing with the topic, showing that it has been filled with religious, political and nationalistic anxieties, not ending with the censorship of the scene in most contemporary Arabic translations of Dante’s Commedia

Integrating Blockchain with Fog and Edge Computing for Micropayment Systems

Fog computing eliminates the need for a centralized cloud data center as it allows computation to be done by nodes closer to the edge. This helps in improving scalability, latency, and throughput compared to traditional cloud environment. Furthermore, with massive increase of IoT devices in the coming future, current solutions that consider centralized cloud computing may not be suitable. Blockchain has developed as a powerful technology enabling unlimited application and opportunities during the last decade. As both blockchain and fog computing technologies operate on a decentralized framework for operations, their integration can help in driving many technologies forward and provide tremendous advantage in terms of security and cost. Recently, micropayments are adopted into a large number of applications. However, individually processing micropayments will result in higher transaction fees where in some cases transaction fee can exceed the payment value. Due to this reason, traditional cryptocurrency blockchain like Bitcoins is inappropriate for micropayment transactions. As such, using fog computing for micropayment can improve the latency and scalability. On the other side, the increased speed and connection density offered by 5G technology will enable real-time processing of data as well as automated transaction processing between connected devices. The 5G technology will enable the smart devices to make micropayments by processing data more efficiently. This will have far-reaching impact on business financial management. The 6G networks will exhibit more heterogeneity than 5G enabling different types of devices to communicate in an efficient way. This will enhance the micropayment networks where different types of IoT devices will be able to connect and hence process payments and transactions in a more secure way. Integrating this intelligence with big data in blockchain and fog computing will change the traditional business models and support the creation of efficient and fast micropayment systems.This chapter explains the benefits of integrating modern technologies (fog computing, blockchain, 6G, and IoT) to solve the problem of micropayment systems. This is achieved by utilizing the capabilities of each technology (e.g., edge computing, blockchain, evolution of 5G to 6G) to bring intelligence from centralized computing facilities to edge/fog devices allowing for more envisioned applications such as micropayment systems where reliable, cheap, high speed, secure, and reduced latency transaction processing can be achieved. The chapter also highlights the various relationships among these technologies and surveys the most relevant work in order to analyze how the use of these disruptive technologies could potentially improve the micropayment systems functionality. Furthermore, various forms of integration of these technologies and associated applications are discussed, and solutions/challenges are outlined. The chapter also briefly discusses a generic solution to the problem of micropayments by integrating fog computing capabilities, blockchain, and edge computing to provide a practical payment setup that allows customers to issue micropayments in a convenient, fast, and secure manner

DASS-CARE 2.0: Blockchain-Based Healthcare Framework for Collaborative Diagnosis in CIoMT Ecosystem

Due to current Covid-19 pandemic, several countries enforce lock-down to prevent pandemic outspread. Hence, the mode of delivery of health services shall change as physical visits are not allowed. As such, the need of tele-medicine service and remote diagnosis have become a necessity. To provide reliable, safe, secure, and sustainable tele-medicine consultancy services, the supporting IT infrastructure need to be transformed. Therefore, it is necessary to use new generation of information technologies such as loT, Blockchain, and cloud computing to transform the traditional medical systems to smart healthcare systems. In this paper, we propose a proof of concept (PoC) of an ameliorated version of our DASS-CARE framework that supports decentralized, accessible, scalable, and secure access to healthcare services based on Internet of Medical things (IoMT) and Artificial Intelligence (AI). In this paper, we propose DASS-CARE 2.0 that offers more medical services including: (a) the real time health monitoring, (b) the collaborative and secure access to medical records, (c) the storage of medical history diagnosis and prescriptions, and (d)the patient\u27s discharge and bills\u27 payments. The paper concludes with future changes to the framework that can furnish further services

Statistical analysis of factors associated with recent traffic accidents dataset: a practical study

In this paper, we propose a logistic model to fit accidents dataset of 10,000 road crash incidents for the Emirate of Abu Dhabi published in 2020. After cleaning up the dataset, we use descriptive and inferential statistical tools to study the attributes of each variable. Then, we identify the main independent variables that can be incorporated in a general logistic regression model which also includes the interactions between them. Our analysis using the significance level of (alpha = 0.05) found that there is a reduced logistic regression model that can fit the data in which the ‘location of accident’ can be represented using ‘type of accident’ and the ‘age’ of people involved in the accidents. Moreover, the results show that the interaction terms are not significant to be included in the model. Furthermore, the study shows that the odds for accidents by young age group (less than 40 years old) in external streets is 27% higher than the odds for internal streets, and that the odds for sequential type accidents in external streets is 13% higher than the odds for internal streets

An efficient design of 45-nm CMOS low-noise charge sensitive amplifier for wireless receivers

Amplifiers are widely used in signal receiving circuits, such as antennas, medical imaging, wireless devices and many other applications. However, one of the most challenging problems when building an amplifier circuit is the noise, since it affects the quality of the intended received signal in most wireless applications. Therefore, a preamplifier is usually placed close to the main sensor to reduce the effects of interferences and to amplify the received signal without degrading the signal-to-noise ratio. Although different designs have been optimized and tested in the literature, all of them are using larger than 100 nm technologies which have led to a modest performance in terms of equivalent noise charge (ENC), gain, power consumption, and response time. In contrast, we consider in this paper a new amplifier design technology trend and move towards sub 100 nm to enhance its performance. In this work, we use a pre-well-known design of a preamplifier circuit and rebuild it using 45 nm CMOS technology, which is made for the first time in such circuits. Performance evaluation shows that our proposed scaling technology, compared with other scaling technology, extremely reduces ENC of the circuit by more than 95%. The noise spectral density and time resolution are also reduced by 25% and 95% respectively. In addition, power consumption is decreased due to the reduced channel length by 90%. As a result, all of those enhancements make our proposed circuit more suitable for medical and wireless devices

Domestic Debt and Economic Growth in Jordan An Empirical Analysis

Jordan’s economy is among the smallest in the Middle East, with insufficient supplies of water, oil, and other natural resources underlying the government's heavy reliance on foreign assistance. Other economic challenges for the government include chronic high rates of poverty, unemployment, inflation, and a large budget deficit. The study investigates the impact of debt on economic growth in Jordan applying the OLS technique for the period of 2000 to 2014. The study indicates that the stock of domestic debt affects the economic growth positively and statistically significant. This indicates that loans partially were utilized by the government for investment oriented projects. On the other hand, the increasing figure of the public debt indicates that the rest used for private and public consumption purposes, which do not bring any return. The study also indicates that the domestic debt servicing affects the economic growth negatively in Jordan. This result is due to the fact that huge amount of money goes for non-development expenditures and also the rest goes for unnecessary expenditures. The study suggests some policies which should be taken by the government to decrease both domestic debt and domestic debt servicing. Keywords: Domestic debt, Economic growth , Jordan Economy

Industrial Investment in Ma'an Governorate, Obstacles, Opportunities and Successful Projects

Industrial investment is one of the most important factors that help achieving sustainable economic development. This study aims to explore the obstacles, which constrain industrial investments in Ma'an Governorate (located in south Jordan) and the incentives to promote these investments. It also aims to explore investment projects with successful future opportunities. A survey on government and private departments’ managers, individual entrepreneurs, and professionals in Ma’an Governorate was conducted for data collection. A total of 300 questionnaires were distributed. Out of this number, only 186 were returned. The response rate was about 58%. One-sample t-test and descriptive statistics showed that there are obstacles facing industrial investments, on the other side it showed that there are real incentives for industrial investments. The research findings show that the Governorate of Ma'an is eligible to attract various industrial projects, which have opportunities to be highly successful in the future such as glass factories, plastics, marble, clothing, and construction materials industries. This study recommends Jordanian government to improve basic infrastructure, promote private industrial investments and exploit the opportunities in the area through directing industrial investments towards the available resources. It also recommends promoting the governorate of Ma'an through media and highlights the prospects of success in various fields of industrial investment in a positive way. Keywords: Industrial Investment, investment obstacles, investment opportunities, future investment projects, Ma’an Governorate

Probabilistic analysis of security attacks in cloud environment using hidden Markov models

© 2020 John Wiley & Sons, Ltd. The rapidly growing cloud computing paradigm provides a cost-effective platform for storing, sharing, and delivering data and computation through internet connectivity. However, one of the biggest barriers for massive cloud adoption is the growing cybersecurity threats/risks that influence its confidence and feasibility. Existing threat models for clouds may not be able to capture complex attacks. For example, an attacker may combine multiple security vulnerabilities into an intelligent, persistent, and sequence of attack behaviors that will continuously act to compromise the target on clouds. Hence, new models for detection of complex and diversified network attacks are needed. In this article, we introduce an effective threat modeling approach that has the ability to predict and detect the probability of occurrence of various security threats and attacks within the cloud environment using hidden Markov models (HMMs). The HMM is a powerful statistical analysis technique and is used to create a probability matrix based on the sensitivity of the data and possible system components that can be attacked. In addition, the HMM is used to provide supplemental information to discover a trend attack pattern from the implicit (or hidden) raw data. The proposed model is trained to identify anomalous sequences or threats so that accurate and up-to-date information on risk exposure of cloud-hosted services are properly detected. The proposed model would act as an underlying framework and a guiding tool for cloud systems security experts and administrators to secure processes and services over the cloud. The performance evaluation shows the effectiveness of the proposed approach to find attack probability and the number of correctly detected attacks in the presence of multiple attack scenarios

A Time Tree Medium Access Control for Energy Efficiency and Collision Avoidance in Wireless Sensor Networks

This paper presents a medium access control and scheduling scheme for wireless sensor networks. It uses time trees for sending data from the sensor node to the base station. For an energy efficient operation of the sensor networks in a distributed manner, time trees are built in order to reduce the collision probability and to minimize the total energy required to send data to the base station. A time tree is a data gathering tree where the base station is the root and each sensor node is either a relaying or a leaf node of the tree. Each tree operates in a different time schedule with possibly different activation rates. Through the simulation, the proposed scheme that uses time trees shows better characteristics toward burst traffic than the previous energy and data arrival rate scheme