In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic

Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

Gypseous soils are widely distributed and especially in Iraq where arid area of hot climatic is present. These soils are considered as problematic soils; therefore this work attends to improve the geotechnical properties of such soil and reduce the dangers of collapse due to wetting process. In this research, undisturbed soil sample of 30 % gypsum content from Karbala city is used. The Single Oedometer collapse test is used in order to investigate the collapse characteristics of natural soil and after treatment with 3%, 6%, 9%, 12% and 15% of Cutback Asphalt. Moreover, two selected additive percentages (9% and 12%) are used to evaluate the suitability of using the Cutback Asphalt for improvement of the bearing capacity o

The Iraqi houses flattening the roof by a concrete panel, and because of the panels on the top directly exposed to the solar radiation become unbearably hot and cold during the summer and winter. The traditional concrete panel components are cement, sand, and aggregate, which have a poor thermal property. The usage of materials with low thermal conductivity with no negative reflects on its mechanical properties gives good improvements to the thermal properties of the concrete panel. The practical part of this work was built on a multi-stage mixing plan. In the first stage the mixing ratio based on the ratios of the sand to cement. The second stage mixing ratios based on replacing the coarse aggregate quantities with the

Modern 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

    Lipase was extracted by Sodium acetate buffer (pH=6; 0.05M) Containing 0.1M NaCl. Enzyme content of crude extract was concentrated by gradual addition of ammonium sulfate at 30-60% saturation. The dialyzed extract was purified on ion-exchange chromatography through DEAE–Cellulose and gel-filtration chromatography through sephacryl S-200 column. The specific activity, enzyme yield and fold purification were 54.06 unit/mg, 42.6% and 10.88 respectively. The molecular weight of the Lipase was 43.651 KDa as determined by gel-filtration chromatography through sephacryl S-200 column. Partial purified lipase used for the improvement of the flavor of butter fat after 12 hours for storage.