A Study of DAS delays and their Impact on the Wireless Channels with Application to Indoor Localization

This research evaluates the Distributed Antenna Systems (DAS) introduced delays and their effects on the indoor channel in simulcast situations where the effect of delays is most prevalent. Different simulcast cases that form the basic building blocks are analyzed to form an understanding of the problem. Two case studies of important indoor environments are presented. Importance of improving ray tracing simulations to include propagation and DAS delays is highlighted. The paper also introduces a DAS element representation and delay mapping model and explores techniques of engineering DAS delays to optimize location estimation by ranging and RF fingerprinting to achieve E911 mandated accuracy. A brief description is introduced for a Software Defined Radio (SDR) implementation of a Correlation Channel Sounder and the possible application of channel sounding for indoor DAS. The paper suggests procedures to produce a full DAS delay profile and ways to optimize it for location estimation

Bioactivities and potential beneficial properties of propolis ethanolic extract, caffeic acid phenethyl ester, and Arabic coffee beans extract

In recent years, the biological activities of natural products have received much attention because of the increasing interest in human health (Bernardini et al., 2018; Er, 2021; Gyawali and Ibrahim, 2014; Kokoska et al., 2019; Okińczyc et al., 2020). One of the most important natural products that are commonly used for their antimicrobial properties is propolis. It is produced by honeybees from resins and plant exudates. Plants protect themselves from pathogenic microbes primarily by producing secondary metabolites termed phytochemicals, many of which have been isolated and used in medicine for their antioxidant and antimicrobial properties (Berretta et al., 2020). Phytochemical compounds that are promising as antimicrobial agents in humans include all components of propolis (Tiku, 2018). These antimicrobial properties can be recognized by honeybees, which selectively collect these plant products and process them to make propolis (Berretta et al., 2020)

Does Volatility Generate Major and Minor Stocks in Saudi Stocks Market?

This study attempts to answer the main question: are there reciprocal effects between the variances of the stock returns in the Saudi market, also the answer to a sub-question. What are the leading stocks in the Saudi market?. Study selected a sample of five stocks representing the basic materials, banking, services, food and transport sectors (SABIC, Al Rajhi, Etisalat, Almarai and Al Bahri respectively). The data sample for the period from 2011 to 2016 is taken, which represents the lifespan of the five-year plan. Daily stock returns were calculated during this period. Study applies the M GARCH-VEC methodology to estimate stock return variances and then perform a multiple regression of five equations using the ARCH Heteroscedasticity estimator. Results of the analysis show a positive effect between stock return variances as well as a positive automatic variance of all stocks returns variances. Finally, the results of the regression analysis of the various equations show that the returns variances of SABIC and Al Rajhi stocks have a dominant impact on the rest of the stock's returns. So they are considered as leading stocks in the market. While the variances returns of Etisalat, Almarai and Al Bahri have a limited impact on the rest of the stocks variances returns, so they are considered as minor stock

Microgrid Enabling Towards the Implementation of Active Distribution Systems: Planning, Operation, and Energy Trading

Recent years have perceived a substantial surge in interest in green technologies due to the growing awareness about the environmental concerns and the technologies’ development, which have resulted in considerable utilization of DC-based distributed generators (DGs) and loads such as photovoltaic (PV) panels and electric vehicles. This increased penetration has reformed the generation and utilization of electric, resulting in promoting the microgrids (μGs) as a promising candidate for future systems. Despite the well-establishment and the extensive studies of μGs, there is still some debate over having μGs that are purely AC, purely DC, or AC-DC hybrid. Purely AC and purely DC configurations cannot meet the challenges and the new technologies that are expected to emerge in the near future as they require many interfacing converters to accommodate the high penetration of DC DGs and loads. These interfacing converters increase the system costs, the conversion losses, and the system complexity. The aforementioned reasons have resulted in the consensus tending towards a new vision of combining the AC and DC to acquire the benefits of both systems, which calls for further investigation of the AC-DC system compositions. The growing electricity demand, aging of the power system infrastructure, and countries effort to utilize renewable-based DGs have stimulated the concept of isolated μGs.Isolated μGs could allow utilities and developers to defer the installation of new generation capacities, in addition to transmission and distribution capacities upgrades by connecting distributed energy resources. Despite the significant benefits provided by isolated μGs, preserving load-generation balance is comprehensively challenging, given that μGs are dominated by renewable-based DGs, which are characterized by their probabilistic nature and intermittent power. This challenge introduced the interconnection of μGs as a promising solution that enhance the system operation and increase the system reliability. The interconnection of a group ofμGs essentially leads to a (small scale) energy market of interconnected microgrids (IμGs) when these μGs exchange energy with each other. Therefore, it is vital to refine and enhance the way in which players from different μGs construct the interconnected μGs and manage electricity trading. Driven by the aforementioned challenges, the main objective of this thesis is to promote the concept of μG and optimally accommodate the expected increased penetration of DC DGs and DC loads in future systems, and ensure the continuity of power supplied to these future systems through their interconnection and managing the energy trading process. Achieving this target entailed the completion of the following parts: 1) Proposing the bilayer μGs configuration, in addition to its power flow model, at which each node is a universal node that can include two buses with different types of power (AC and DC) or a single bus (AC or DC). The inclusion of the two types of power reduces the number of interfacing converters and allows for the accommodation of the increased penetration of DC DGs and loads besides the existing conventional AC DGs and loads. 2) Proposing a stochastic planning framework for the network configuration of AC-DC bilayer μGs that is capable of minimizing the total system costs through the determination of the optimal BμGconfiguration. 3) Investigating the AC-DC bilayer μGs operation under fault conditions and introducing a multilevel converter with fault confining capability that can isolate the faulty layer, and hence ensures optimal and reliable operation of the healthy layer under fault conditions. 4) The proposal of a stochastic planning framework for the IμGs that minimizes the total system costs and minimizes the loads curtailment under DG failure, while considering the stochastic variations of the renewable-based DGs and loads. 5) Developing an energy trading mechanism that facilitates the power trading between the interconnected μGs, provides full utilization of the renewable output power, minimizes operation cost, and minimizes load curtailment

An Optimization Model for Appraising Intrusion-Detection Systems for Network Security Communications:Applications, Challenges, and Solutions

Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authenticity, and accessibility, may be jeopardized if breaches are not detected. Different organizations currently utilize a variety of tactics, strategies, and technology to protect the systems’ credibility in order to combat these dangers. Safeguarding approaches include establishing rules and procedures, developing user awareness, deploying firewall and verification systems, regulating system access, and forming computer-issue management groups. The effectiveness of intrusion-detection systems is not sufficiently recognized. IDS is used in businesses to examine possibly harmful tendencies occurring in technological environments. Determining an effective IDS is a complex task for organizations that require consideration of many key criteria and their sub-aspects. To deal with these multiple and interrelated criteria and their sub-aspects, a multi-criteria decision-making (MCMD) approach was applied. These criteria and their sub-aspects can also include some ambiguity and uncertainty, and thus they were treated using q-rung orthopair fuzzy sets (q-ROFS) and q-rung orthopair fuzzy numbers (q-ROFNs). Additionally, the problem of combining expert and specialist opinions was dealt with using the q-rung orthopair fuzzy weighted geometric (q-ROFWG). Initially, the entropy method was applied to assess the priorities of the key criteria and their sub-aspects. Then, the combined compromised solution (CoCoSo) method was applied to evaluate six IDSs according to their effectiveness and reliability. Afterward, comparative and sensitivity analyses were performed to confirm the stability, reliability, and performance of the proposed approach. The findings indicate that most of the IDSs appear to be systems with high potential. According to the results, Suricata is the best IDS that relies on multi-threading performance

Rural Fishermen Benefit From the Activities of Cooperative Societies in Aswan Governorate, Egypt

The research aimed to identify the degree of benefit and satisfaction of rural fishermen with the activities and services provided by cooperative societies for rural fishermen in Aswan Governorate. The research carried out on a random sample of rural fishermen which consisting of 302 respondents. Data were collected by personal interview questionnaire. Percentages, frequency distribution, graph and weighted average were used to show and describe the research data. Excel was used to prepare the graphs. Spearman’s correlation coefficient for ranks was used to determine the relationship between the search variables by SPSS. Results were showed that: The most beneficial activities were: lending to fishermen and their families, establishing and managing fish farms, establishing centers for collecting fish, which are arranged in descending order with a weighted average respectively (2.85, 2.82, 2.71). The degree of satisfaction of the respondents was high with one of the services provided by cooperative societies were: issuing official papers, with a weighted average of 2.69. The degree of benefit of the respondents was positively related to years of work in fishing, age, and the number of years of education. The degree of respondents' satisfaction was positively correlated with age, years of education, level of ambition, years of work in fishing at the significant level 0.01, 0.05. The most important suggestions for activating the role of fishermen's cooperative societies were: the necessity of insuring fishermen and their boats (99.7%), providing protection for fishermen's families (99.3%), and helping to solve problems (98%)

An Improved Binary Grey-Wolf Optimizer with Simulated Annealing for Feature Selection

This paper proposes improvements to the binary grey-wolf optimizer (BGWO) to solve the feature selection (FS) problem associated with high data dimensionality, irrelevant, noisy, and redundant data that will then allow machine learning algorithms to attain better classification/clustering accuracy in less training time. We propose three variants of BGWO in addition to the standard variant, applying different transfer functions to tackle the FS problem. Because BGWO generates continuous values and FS needs discrete values, a number of V-shaped, S-shaped, and U-shaped transfer functions were investigated for incorporation with BGWO to convert their continuous values to binary. After investigation, we note that the performance of BGWO is affected by the selection of the transfer function. Then, in the first variant, we look to reduce the local minima problem by integrating an exploration capability to update the position of the grey wolf randomly within the search space with a certain probability; this variant was abbreviated as IBGWO. Consequently, a novel mutation strategy is proposed to select a number of the worst grey wolves in the population which are updated toward the best solution and randomly within the search space based on a certain probability to determine if the update is either toward the best or randomly. The number of the worst grey wolf selected by this strategy is linearly increased with the iteration. Finally, this strategy is combined with IBGWO to produce the second variant of BGWO that was abbreviated as LIBGWO. In the last variant, simulated annealing (SA) was integrated with LIBGWO to search around the best-so-far solution at the end of each iteration in order to identify better solutions. The performance of the proposed variants was validated on 32 datasets taken from the UCI repository and compared with six wrapper feature selection methods. The experiments show the superiority of the proposed improved variants in producing better classification accuracy than the other selected wrapper feature selection algorithms