Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR) algorithm was used, which represents a load balancing (LB) algorithm that is applied to schedule and distributes data among fog servers by reading CPU and memory values of these servers in order to improve system performance. The results proved that DWRR algorithm provides high throughput which reaches 3290 req/sec at 919 users. A lot of research is concerned with distribution of workload by using LB techniques without paying much attention to Fault Tolerance (FT), which implies that the system continues to operate even when fault occurs. Therefore, we proposed a replication FT technique called primary-backup replication based on dynamic checkpoint interval on FC. Checkpoint was used to replicate new data from a primary server to a backup server dynamically by monitoring CPU values of primary fog server, so that checkpoint occurs only when the CPU value is larger than 0.2 to reduce overhead. The results showed that the execution time of data filtering process on the FC with a dynamic checkpoint is less than the time spent in the case of the static checkpoint that is independent on the CPU status.
In this research, optical absorption data (the imaginary part of the dielectric function Ɛ2 as a function of photon energy E) were re-analyzed for three samples of a-Si:H thin films using derivative methods trying to investigate the ambiguity that accompany the interpretation of the optical data of these film in order to obtainm the optical energy gap (Eg) and the factor (r) which in concerned with the density of state distribution near the mobility edge directly without the need for a pre- assumption for the factor r usually followed in traditional methods such as the Tauc plot. The derivative method was used for two choices for the factor q (which in connected with the dependence of the dipole matrix element on the photon energy ) for
... Show MoreThis study deals with interpretation of stratigraphic and structural of Khlesia area north-west Iraq in Nineveh province, near the Iraq- Syria border, by using 2D seismic data. Synthetic trace are prepared by using available data of the well (Kh-1) using Geoframe program to define and picking the reflectors on seismic section. These reflectors are: (Within Fatha and Kurra Chine reflectors) representing Middle Miocene and Late Triassic ages respectively. A listric growth normal fault is affecting the stratigraphic succession, and normal fault as a result of collision of Arabian plate with Eurasian plate. In addition, minor normal faults (Dendritic and Tension) are developed on the listric normal growth fault
... Show MoreLoanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette
... Show MoreThe reduction to pole of the aeromagnetic map of the western desert of Iraq has been used to outline the main basement structural features. Three selected magnetic anomalies are used to determine the depths of their magnetic sources. The estimated depths are obtained by using slope half slope method and have been corrected through the application of a published nomogram. These depths are compared with previous published depth values which provide a new look at the basement of the western desert in addition to the thickness map of the Paleozoic formations. The results shed light on the important of the great depths of the basement structures and in turn the sedimentary cover to be considered for future hydrocarbon exploration
This research is focused on an interpretive of 2D seismic data to study is reinterpreting seismic data by applying sufficient software (Petrel 2017) of the area between Al-Razzazah Lake and the Euphrates river belonging to Karbala'a and Al-Anbar Governorates, central Iraq. The delineation of the sub-surface structural features and evaluation of the structure of Najmah and Zubair Formations was done. The structure interpretation showed that the studied area was affected by normal fault bearing (NW-SE) direction with a small displacement. In contrast, time and depth maps showed monocline structures (nose structures) located in the western part of the studied area.
In the last decade, the web has rapidly become an attractive platform, and an indispensable part of our lives. Unfortunately, as our dependency on the web increases so programmers focus more on functionality and appearance than security, has resulted in the interest of attackers in exploiting serious security problems that target web applications and web-based information systems e.g. through an SQL injection attack. SQL injection in simple terms, is the process of passing SQL code into interactive web applications that employ database services such applications accept user input such as form and then include this input in database requests, typically SQL statements in a way that was not intende
... Show MoreData centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le
... Show MoreIn this paper, time spent and the repetition of using the Social Network Sites (SNS) in Android applications are investigated. In this approach, we seek to raise the awareness and limit, but not eliminate the repeated uses of SNS, by introducing AndroidTrack. This AndroidTrack is an android application that was designed to monitor and apply valid experimental studies in order to improve the impacts of social media on Iraqi users. Data generated from the app were aggregated and updated periodically at Google Firebase Real-time Database. The statistical factor analysis (FA) was presented as a result of the user’s interactions.
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreModern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
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