Image Compression Using Permanent Neural Networks for Predicting Compact Discrete Cosine Transform Coefficients

This study proposes a new image compression technique that produces a high compression ratio yet consumes low execution times. Since many of the current image compression algorithms consume high execution times, this technique speeds up the execution time of image compression. The technique is based on permanent neural networks to predict the discrete cosine transform partial coefficients. This can eliminate the need to generate the discrete cosine transformation every time an image is compressed. A compression ratio of 94% is achieved while the average decompressed image peak signal to noise ratio and structure similarity image measure are 22.25 and 0.65 respectively. The compression time can be neglected when compared to other reported techniques because the only needed process in the compression stage is to use the generated neural network model to predict the few discrete cosine transform coefficients

Securing Fog Federation from Behavior of Rogue Nodes

As the technological revolution advanced information security evolved with an increased need for confidential data protection on the internet. Individuals and organizations typically prefer outsourcing their confidential data to the cloud for processing and storage. As promising as the cloud computing paradigm is, it creates challenges; everything from data security to time latency issues with data computation and delivery to end-users. In response to these challenges CISCO introduced the fog computing paradigm in 2012. The intent was to overcome issues such as time latency and communication overhead and to bring computing and storage resources close to the ground and the end-users. Fog computing was, however, considered an extension of cloud computing and as such, inherited the same security and privacy challenges encountered by traditional cloud computing. These challenges accelerated the research community\u27s efforts to find practical solutions. In this dissertation, we present three approaches for individual and organizational data security and protection while that data is in storage in fog nodes or in the cloud. We also consider the protection of these data while in transit between fog nodes and the cloud, and against rogue fog nodes, man-in-the-middle attacks, and curious cloud service providers. The techniques described successfully satisfy each of the main security objectives of confidentiality, integrity, and availability. Further we study the impact of rogue fog nodes on end-user devices. These approaches include a new concept, the Fog-Federation (FF): its purpose to minimize communication overhead and time latency between the Fog Nodes (FNs) and the Cloud Service Provider (CSP) during the time the system is unavailable as a rogue Fog Node (FN) is being ousted. Further, we considered the minimization of data in danger of breach by rogue fog nodes. We demonstrate the efficiency and feasibility of each approach by implementing simulations and analyzing security and performance

Homogeneous and heterogeneous breast phantoms for UWB imaging

This paper presents the fabrication of homogeneous and heterogeneous breast phantoms for experimental breast cancer detection use. The phantoms were developed for UWB imaging technique. The fabrication materials were affordable and the process was minimal. Experiments showed that the use of these phantoms was successful

Marvellous real in the Middle East: a comparative study of magical realism in contemporary women’s fiction

Magical realism has been studied extensively in relation to Latin America and subsequently in other parts of the world, yet the Middle East has not received adequate attention in academic scholarship. This PhD study examines a selection of contemporary female-authored narratives from the Middle East to establish an understanding of the practice of magical realism in this region. The selected texts for this study are: Raja Alem’s Fatma and My Thousand and One Nights; Shahrnush Parsipur’s Women Without Men and Touba and the Meaning of Night; Elif Shafak’s The Bastard of Istanbul and Gina B. Nahai’s Moonlight on the Avenue of Faith. This study firstly explores the concept of magical realism as a mode of writing and determines its relationship to the Middle Eastern context. It then evaluates the texts under scrutiny by examining how the narrative of magical realism is constructed and what the sources are of the magical component in these texts, specifically in relation to Middle Eastern mythology. It also investigates the ideological aspect behind the employment of magical realism and whether it serves any political goal. The analysis of the selected texts is approached from three standpoints, that is, from literary, mythological and ideological perspectives. I argue that magical realism serves various purposes and that it is applied from perspectives that can be regarded as marginal to their communities’ dominant values, to subvert mainstream ideology. I also demonstrate that the Middle East is a crucial place to investigate magical realism because of the numerous complex cultural values that interact with each other in this region, and which enrich the practice of magical realism

A meta-analysis of meta-analyses of the effectiveness of FIFA injury prevention programmes in soccer

FIFA has a Medical and Research Centre (F-MARC) which has designed a comprehensive programme targeting muscle strength, kinaesthetic awareness, and neuromuscular control during static and dynamic movements to decrease injury risk for soccer players. A number of meta-analyses now exist on how effective FIFA's programmes to prevent and reduce injury actually are, with various degrees of injury reduction reported. This research aimed to carry out a systematic review and to meta analyse the existing meta-analyses so that a conclusion can be drawn on how effective the injury programmes are. Relevant studies were identified by searching five databases for the period January 1990 till 1 July 2018. Results of each meta-analysis were combined together using risk ratios (RR) in a summary meta-analysis. QUOROM checklist and AMSTAR 2 assessment were used to assess the quality of reporting and methodology in the meta-analyses. Four meta-analyses met the inclusion criteria covering fifteen primary studies. All four meta-analyses scored quite highly on QUOROM, but two were rated by AMSTAR 2 as moderate quality and two were found to be of critically low quality. An overall risk reduction of 34% [RR= 0.66 (0.60 - 0.73)] for all injuries and a reduction of 29% [RR= 0.71 (0.63 - 0.81)] for injuries to the lower limbs were revealed by this meta-analysis of meta-analyses. Combining every previous meta-analysis into a single source in this paper produced decisive evidence that the risk of injuries while playing soccer is reduced as a result of FIFA's injury prevention programmes

Implementing ISO 14001 and Environmental Performance Evaluation: A Logistic Regression Model

Due to the growing popularity of environmental management systems and the ongoing debate among practitioners and researchers concerning the influence of environmental management systems on environmental performance, there is a need to assess how the implemented environmental management systems impact the environment. The current study examines the relationship between the guidelines provided by the ISO 14031 and ISO 14001 standards from three aspects, namely, utilizing information and data, planning for environmental performance and reviewing and improving environmental performance. This study will utilize a binary logistic regression to model and analyse the link between ISO 14001 and ISO 14031 using a 7-point Likert scale questionnaire. A total of 590 companies operating within the Saudi Arabia industrial sector were invited to take part in the study. The collection of data using questionnaires lasted from January to March 2019, and the results were analysed and compared with those of related studies. The model included a dependent variable representing whether the company is certified or not for ISO 14001 and 13 independent variables representing the main ISO 14031 guidelines. The research findings revealed that the developed model predicts 92.8% of the values, and the remaining 7.2% of the values are not covered. Thirteen independent variables were positively correlated with the dependent variable, indicating that the company is certified. The results of this study contribute significantly to the determination of the relationship between environmental performance and ISO 14001 certification

Mutated N-ras does not induce p19arf in CO25 cell line

The mouse cell line (CO25) used in this study was transfected with a glucocorticoid inducible mutated human N-ras oncogene under transcriptional control of the steroid-sensitive promoter of the mouse mammary tumors virus long terminal repeat MMTV-LTR. This study was aimed to investigate the expression of p19arf and MDM2 genes under the effect of N-ras oncogene induction and to invent the role of p19arf, MDM2 in N-ras pathway during various periods (12, 24, 48, 72, 96 h) using western blotting method. The levels of â-actin proteins in the same periods were our control group. The observations showed no increase of p19arf protein expression in normal, cancer and differentiated CO25 cells. MDM2 was accumulated until 72 h and after 96 h, it showed a dramatical decrease while β-actin levels were increased correlated to the volume of protein loaded to the gel. Because of the role of p19arf as tumor suppressor and p53-MDM2 linker, it is highly recommended to  investigate the relationship between N-ras and p53 and MDM2 in the same system to recognize the molecule that may play a linker molecule between p53 and MDM2 in p19arf lack system.Key words: Oncogene, N-ras, p19arf, myoblast, CO25 cells, differentiation, MDM2

Experimental approximation of breast tissue permittivity and conductivity using NN-based UWB imaging

This paper presents experimental study to distinguish between malignant and benign tumors in early breast cancer detection using Ultra Wide Band (UWB) imaging. The contrast between dielectric properties of these two tumor types is the main key. Mainly water contents control the dielectric properties. Breast phantom and tumor are fabricated using pure petroleum jelly and a mixture of wheat flour and water respectively. A complete system including Neural Network (NN) model is developed for experimental investigation. Received UWB signals through the tumor embedded breast phantom are fed into the NN model to train, test and determine the tumor type. The accuracy of the experimental data is about 98.6% and 99.5% for permittivity and conductivity respectively. This leads to determine tumor dielectric properties accurately followed by distinguish between malignant and benign tumors. As malignant tumors need immediate further medical action and removal, this findings could contribute to save precious file in near future