The current study was conducted on 504(Ros-308) broiler chicks during the period 28/9/2017-9/11/2018to determine the effect of heat shock in early age and additives such as ginseng in three levels on birds weight and feedconsumption. Results showed that the exposure to high temperature (38-400C) lead to significant decrease (p≤≤≤≤≤0.05 (inaverage body weight at7 day of age and significant decrease in body weight in birds expousured to high temperature inthe periods 2, 4 and 6 hours compared with control (Table 1). Significant decrease in live body weight when exposure to2hr compared with 6hr namely (138.54) and (144.21), respectively while no significant difference between 2 and 4h.Results showed no significant effect in body weight in control group compared with the group that fed on diet containginseng extract with or without vitamins and minerals. Interaction between exposure time and ginseng extract on bodygain weight all ages, the height body gain was noticed in P0G2 at 24days at age (514.78 gm). While, the lowest value wasin P6G0 (275.78) Accumulative body gain was differed significantly P2G2(2514.22 gm) compared with P6G0(2054.45 gm)
Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering
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For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.
Equilibrium adsorption isotherm for the removal of trifluralin from aqueous solutions using ? –alumina clay has been studied. The result shows that the isotherms were S3 according Giels classification. The effects of various experimental parameters such as contact time, adsorbent dosage, effect of pH and temperature of trifluralin on the adsorption capacities have been investigated. The adsorption isotherms were obtained by obeying freundlich adsorption isotherm with (R2 = 0.91249-0.8149). The thermodynamic parameters have been calculated by using the adsorption process at five different temperature, the values of ?H, ?G and ?S were (_1.0625) kj. mol-1, (7.628 - 7.831) kj.mol-1 and (_2.7966 - _2.9162) kg.
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In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.