Tokens Shuffling Approach for Privacy, Security, and Reliability in IoHT under a Pandemic

Privacy and security are unavoidable challenges in the future of smart health services and systems. Several approaches for preserving privacy have been provided in the Internet of Health Things (IoHT) applications. However, with the emergence of COVID-19, the healthcare centers needed to track, collect, and share more critical data such as the location of those infected and monitor social distancing. Unfortunately, the traditional privacy-preserving approaches failed to deal effectively with emergency circumstances. In the proposed research, we introduce a Tokens Shuffling Approach (TSA) to preserve collected data’s privacy, security, and reliability during the pandemic without the need to trust a third party or service providers. TSA depends on a smartphone application and the proposed protocol to collect and share data reliably and safely. TSA depends on a proposed algorithm for swapping the identities temporarily between cooperated users and then hiding the identities by employing fog nodes. The fog node manages the cooperation process between users in a specific area to improve the system’s performance. Finally, TSA uses blockchain to save data reliability, ensure data integrity, and facilitate access. The results prove that TSA performed better than traditional approaches regarding data privacy and the performance level. Further, we noticed that it adapted better during emergency circumstances. Moreover, TSA did not affect the accuracy of the collected data or its related statistics. On the contrary, TSA will not affect the quality of primary healthcare services

Demand Disaggregation for Non-Residential Water Users in the City of Logan, Utah, USA

Non-residential users contribute to a significant portion of the total water delivered by water supplying agencies. However, a very limited number of studies have attempted to investigate the water use behavior of non-residential users. With the emergence of newer “smart” meters, water use now can be measured and recorded at a very high temporal frequency. Smart meters can help determine total water use, timing, and component end uses to better understand water use practices by non-residential users. Water end use disaggregation is the process of separating the water used by each fixture or process within a facility. This is useful because having a breakdown of the consumption of all end uses may encourage users to consume less water and gives them indications on how to do so. This project involved collecting and working with three different datasets with three different temporal scales (monthly billing data, 5-minute water use data, and 5-second water use data). We analyzed monthly billing data to solicit potential participating facilities for the study. For each participating facility, new smart devices were installed on their existing water meters, including an advanced water meter register and a pulse counting data logger. The newer registers logged and transmitted data to a web-accessible data portal at 5-minute intervals, while the pulse counters recorded water use at 5- second intervals. These devices enabled us to measure the timing and volume of different water uses (e.g., indoor versus outdoor versus industrial processes uses). In this project, we identified different water use events, average water used by each end use (from plumbing fixtures to industrial machinery), variability in end uses (faucets/toilets versus showers), variability in use by the type of user (manufacturing facilities versus assisted living homes), and the impact of the business type on the water use

Solving hybrid-vehicle routing problem using modified simulated annealing

In this paper, we consider the hybrid vehicle routing problem (HVRP) at which the vehicle consumes two types of power: fuel and electricity. The aim of this problem is to minimize the total cost of travelling between customers, provided that each customer is visited only once. The vehicle departs from the depot and returns after completing the whole route. This optimization problem is solved using a modified simulated annealing (SA) heuristic procedure with constant temperature. This approach is implemented on a numerical example and the results are compared with the SA algorithm with decreasing temperature. The obtained results show that using the SA with constant temperature overrides the SA with decreasing temperature. The results indicate that SA with decreasing temperature needs twice the number of iterations needed by the SA with constant temperature to reach a near optimum solution

A Comprehensive and Effective Framework for Traffic Congestion Problem Based on the Integration of IoT and Data Analytics

This research was funded by the Deanship of Scientific Research, Islamic University of Madinah, Saudi Arabia, under Tamayuz research grant number 2/710.Traffic congestion is still a challenge faced by most countries of the world. However, it can be solved most effectively by integrating modern technologies such as Internet of Things (IoT), fog computing, cloud computing, data analytics, and so on, into a framework that exploits the strengths of these technologies to address specific problems faced in traffic management. Unfortunately, no such framework that addresses the reliability, flexibility, and efficiency issues of smart-traffic management exists. Therefore, this paper proposes a comprehensive framework to achieve a reliable, flexible, and efficient solution for the problem of traffic congestion. The proposed framework has four layers. The first layer, namely, the sensing layer, uses multiple data sources to ensure a reliable and accurate measurement of the traffic status of the streets, and forwards these data to the second layer. The second layer, namely, the fog layer, consumes these data to make efficient decisions and also forwards them to the third layer. The third layer, the cloud layer, permanently stores these data for analytics and knowledge discoveries. Finally, the fourth layer, the services layer, provides assistant services for traffic management. We also discuss the functional model of the framework and the technologies that can be used at each level of the model. We propose a smart-traffic light algorithm at level 1 for the efficient management of congestion at intersections, tweet-classification and image-processing algorithms at level 2 for reliable and accurate decision-making, and support services at level 4 of the functional model. We also evaluated the proposed smart-traffic light algorithm for its efficiency, and the tweet classification and image-processing algorithms for their accuracy.Deanship of Scientific Research, Islamic University of Madinah, Saudi Arabia 2/71

Video Categorization Using Data Mining

Video categorization using data mining is the area of the research that aims to propose adeveloped method based on Artificial Neural Network (ANN), which could be used to classify video files into different categories according to the content. In order to test this method, the classifications of video files are discussed. The applied system proposes that the video could be categorized in two classes. The first one is educational while is noneducational. The classification is conducted based on the motion using optical flow. Several experiments were conducted using Artificial Neural Network (ANN) model. The research facilitate access to the required educational video to the learners students, especially novice students. This research objective is to investigate how the effect of motion feature can be useful in such lassification. We believe that other effects such audio features, text features, and other factors can enhance accuracy, but this requires wider studies and need more time. The accuracy of results in video classification to educational and non-educational through technique 3 fold cross validation and using (ANN) model is 54%. This result may can be improved by introducing other factors mentioned above

STUDIES ON THE SUDANESE INDIGENOUS AFRICAN TOAD BUFO SPP. (Amphibia): PARTIAL CHARATERIZATION OF ANTIBACTERIAL PEPTIDES AND PROTEINS OF THE PARATOID GLAND

The parotoid gland secretion of Bufo spp., obtained by manual compression, was found to contain 23.1-41.2% (w/w) of total protein. Gel filtration chromatography showed the existence of four fractions of peptides and proteins responsible for antibacterial activity. Thin layer chromatography showed seven Ninhydrin-positive spots in addition to the origin, in the parotoid gland secretion of Bufo spp. Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis revealed the existence, in the crude secretion, of 2 bands of proteins (P1 and P2) and 2 bands of peptides (P3 and P4) with various molecular weights

Numerical nonlinear analysis of RC beans with un-strengthened and CFRP-strengthened opening drilled under service loads within shear zones

Current research paper deals with reinforced concrete (R.C.) beams numerical modeling and suggested strengthening procedure if it is required to create an opening within their shear zones. Strengthening is assumed to be achieved during different service load application conditions. Reinforced Concrete beams with rectangular or circular opening in shear zone; as critical regions; sustain two concentrated system of loads are tested till failure before and after performing suggested opening assessing technique by means of Carbon Fibers Reinforced Polymer sheets (CFRP). The main aim of this research is simulating real practice situation where the beam is subjected to service loads, supported temporary by means of hydraulic jacks, opening is created and strengthening is performed then jacking supports are released. Results of achieved numerical nonlinear modeling are introduced and influence of strengthening achieving on improving assessed beams almost structural behavior such as initial cracking loads, load deflection curves, cracking patterns, failure loads & modes for reference (without opening), main un-strengthened control beams, and CFRP strengthened opening beams are introduced and analyzed in details. Some important conclusions & recommendations for designer and executive engineers are stated

The Impact of Global Financial Crisis on Presented and Returned Checks in Jordan

The purpose of this study is to investigates the effect of global financial crisis (GFC) on the presented and returned checks in Jordan i.e. cause-affect perspective research. The imperial data were collected from the Jordanian Department of Statistics, Central Bank of Jordan, and New York Stock Exchange (NYSE) market data base; the data covered 15 years from 1999 to 2013 to run the analysis. A Bivariate Pearson Correlation and Multiple Regressions were used to test the relationships between GFC and presented and returned checks and the effect GFC on presented and returned checks. A Bivariate Pearson correlation analysis shows that there is a strong significant correlation between presented checks and returned checks. Also, it shows that there is a significant relationship between Dow Jones market drop and increased presented checks. However, it shows that there is no significant correlation between Dow Jones drop and the returned checks. The multiple regressions show that there is a positive effect for GFC on presented checks for clearance in Jordan, and there is a negative effect for GFC on returned checks in Jordan. Generalizing Jordanian results to other countries may be questionable. Therefore, this study recommends extending the analysis to other Arab countries to mitigate the issue of generalizing conclusions on other countries. This study also may be considered as an initiative study which considered the effect of GFC on presented and return checks in Jordan.

Strengthening of Edge and Corner Columns using Concrete Jackets

Strengthening of columns using concrete jackets depends on friction at the interface between them. So strengthening of edge and corner columns in only one story needs a large cross section area due to the shortage of friction length which leads to architectural issues. This research aims to study strengthening the edge and corner columns using a concrete Jacket in more than one story which increases the friction area between the Jacket and the original column. As a result, the load transferred from original column to the jacket will be increased. Thirteen models were done using ANSYS program to study the effect of various factors on the Jacket capacity such as the number of strengthened floors, the Jacket type (two sides or three sides), and whether there were shear connectors or not. The results showed that in the case of the edge and corner columns, it is preferable to strengthen the column by making a concrete Jacket on at least two or three floors to increase the surface area, which leads to increase the friction and thus increases the capacity of the strengthened column by an acceptable percentage. The results of ANSYS models were compared with the Indian code IS 15988 (2013) and the results were shown differently because the code equations depend on the presence of a full bond between the concrete column and the Jacket, which does not occur, but rather the load is transferred by friction between the Jacket and the original column. Doi: 10.28991/cej-2021-03091716 Full Text: PD