Walaa M. El-Sayed, Hazem M. El-Bakry and Salah M. El-Sayed
Wireless sensor networks (WSNs) are periodically collecting data through randomly dispersed sensors (motes), which typically consume high energy in radio communication that mainly…
Abstract
Wireless sensor networks (WSNs) are periodically collecting data through randomly dispersed sensors (motes), which typically consume high energy in radio communication that mainly leans on data transmission within the network. Furthermore, dissemination mode in WSN usually produces noisy values, incorrect measurements or missing information that affect the behaviour of WSN. In this article, a Distributed Data Predictive Model (DDPM) was proposed to extend the network lifetime by decreasing the consumption in the energy of sensor nodes. It was built upon a distributive clustering model for predicting dissemination-faults in WSN. The proposed model was developed using Recursive least squares (RLS) adaptive filter integrated with a Finite Impulse Response (FIR) filter, for removing unwanted reflections and noise accompanying of the transferred signals among the sensors, aiming to minimize the size of transferred data for providing energy efficient. The experimental results demonstrated that DDPM reduced the rate of data transmission to ∼20%. Also, it decreased the energy consumption to 95% throughout the dataset sample and upgraded the performance of the sensory network by about 19.5%. Thus, it prolonged the lifetime of the network.
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Iman El-Sayed Hossam Hegazy and Ossama El-Sayed Hossam Hegazy
In 2017, 50 percent of Syrian refugee applications in Egypt were submitted by females. However, a suitable integration strategy for this target group remains obscure since the…
Abstract
Purpose
In 2017, 50 percent of Syrian refugee applications in Egypt were submitted by females. However, a suitable integration strategy for this target group remains obscure since the available approaches focus mainly on male integration. That is due to the assumption that women refugees are mere followers to men who socially and economically dominate the families in the Middle East. Accordingly, the integration of the Syrian women refugees in society, as well as in the market, proceeds spontaneously without clear visions and therefore with delays. The paper aims to discuss this issue.
Design/methodology/approach
To methodologically understand the circumstances of the aforementioned group expert, focused and narrative “episode interviews” have been conducted. Alexandria, Egypt’s second capital, is the research case study as well as the researchers’ hometown. Thus, it allows following a “descriptive comparative analysis” process between the three Alexandrian districts, with different urban fabric: “Al-Nkhil Agamy” gated community, “El-Asafra/Sidi Becher” informal settlement and “New Borg El-Arab” new city.
Findings
Yet, it is unknown what criteria the Syrian women refugees set for choosing their accommodation. Similarly, the obstacles they encounter, especially the ones preventing their integration, are ambiguous. Even their daily life, which might give insights into the barriers they face, due to their status, is unclear. These are the gaps this paper tackles, in addition to the refugees’ immaterial cultural impact in the host society.
Originality/value
Finally, but also importantly, the topic has been seldom researched in Alexandria, in comparison with Cairo. Therefore, this paper aims at qualitatively hearing of the Syrian refugees’ voices in order to enhance their societal interaction and coexistence in Alexandria.
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Muhammad Riaz, Shu Jinghong and Muhammad Nadeem Akhtar
The main goal of this study is to analyze how monetary debt effects firm behavior of 167 registered manufacturing companies in G-7 countries.
Abstract
Purpose
The main goal of this study is to analyze how monetary debt effects firm behavior of 167 registered manufacturing companies in G-7 countries.
Design/methodology/approach
The sample of the present study is taken from the listed firms in G-7 countries. For the building companies, the yearly financial statements of 2007–2018 have been taken from world stock exchange and Thomson Reuters Data Stream. In this study, regression analysis are directed with panel data over the period of 2007–2018 using ordinary least square summary statistics, correlation matrix and generalized method moments. Data were analyzed by employing E Views and Stata 13 software.
Findings
The significant findings of the current study indicated that fixed assets, tangible assets, taxes, net cash and profitability have positive association with debt level.
Research limitations/implications
The current work include only registered manufacturing firms in G-7 countries. Moreover, ownership types are not accounted for in this study.
Practical implications
The current analysis is an empirical investigation of antecedents of debt regarding G-7 countries with up-to-date data. Various regression inquires have been made to design the models using different measures of debt and measure of firm performance indicators. These works will assist G-7 countries firms to know the effects of identified factors on time raising debt level.
Originality/value
The current work has been finalized using genuine data of yearly reports and database. This study incorporated antecedents of debt, which have limited discourse in prior literature. Furthermore, this study explores the connection between debt level and firm performance of G-7 countries.