Experimental programs based test results has been used as a means to find out the response of individual elements of structure. In the present study involves investigated behavior of five reinforced concrete deep beams of dimension (length 1200 x height 300 x width150mm) under two points concentrated load with shear span to depth ratio of (1.52), four of these beams with hallow core and
retrofit with carbon fiber reinforced polymer CFRP (with single or double or sides Strips). Two shapes of hallow are investigated (circle and square section) to evaluated the response of beams in case experimental behavior. Test on simply supported beam was performed in the laboratory & loaddeflection, strain of concrete data and crack pattern of

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Capacitive–resistive humidity sensors based on polythiophene (P3HT) organic semiconductor as an active material hybrid with three types of metallic nanoparticles (NP) (Ag, Al, and Cu) were synthesized by pulsed laser ablation (PLA). The hybrid P3HT/metallic nanoparticles were deposited on indium-tin-oxide (ITO) substrate at room temperature. The surface morphology of theses samples was studied by using field emission scanning electron micrographs (FE-SEM), which indicated the formation of nanoparticles with grain size of about 50nm. The electrical characteristics of the sensors were examined as a function of the relative humidity levels. The sensors showed an increase in the capacitance with variation in the humidity level.  Whil

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

In modern era, which requires the use of networks in the transmission of data across distances, the transport or storage of such data is required to be safe. The protection methods are developed to ensure data security. New schemes are proposed that merge crypto graphical principles with other systems to enhance information security. Chaos maps are one of interesting systems which are merged with cryptography for better encryption performance. Biometrics is considered an effective element in many access security systems. In this paper, two systems which are fingerprint biometrics and chaos logistic map are combined in the encryption of a text message to produce strong cipher that can withstand many types of attacks. The histogram analysis o

Iron–phthalocyanine (FePc) organic photoconductive detector was fabricated using pulsed laser deposition (PLD) technique to work in ultraviolet (UV) and visible regions. The organic semiconductor material (iron phthalocyanine) was deposited on n-type silicon wafer (Si) substrates at different thicknesses (100, 200 and 300) nm. FePc organic photoconductive detector has been improved by two methods: the first is to manufacture the detector on PSi substrates, and the second is by coating the detector with polyamide–nylon polymer to enhance the photoconductivity of the FePc detector. The current–voltage (I–V) characteristics, responsivity, photocurrent gain, response time and the quantum efficiency of the fabricated photoconduc

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The