Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (CS) subjected to similar conditions (the same temperature category). The outcomes indicated that including silica fume particles in mortar mixtures lowered the amount and width of microcracks, upgraded the mass-loss performance, lowered crystalline calcium hydroxide, and reinforced the cement paste, which explained the improvement in residual mechanical strengths.
Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's
... Show MoreThe prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices
... Show MoreThe ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
... Show MoreOpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtain
... Show MoreThe research aims to design a narrow-band frequency drive amplifier (1.5GHz -1.6GHz), which is used to boost the transmitter amplifier's input signal or amplify the GPS, GlONASS signals at the L1 band.
The Power Amplifier printed circuit board (PCB) prototype was designed using InGaP HBT homogeneous technology transistor and GaAs Heterojunction Bipolar Transistor (HBT) transistor. Two models have been compared; one of the models gave 16dB gain, and the other gave 23dB when using an input power signal (-15dBm). The PCB consumes 2.4W of power and has a physical dimension of 11 x 4 cm.
Silybum marianum, from which silymarin (SM) is extracted, is a medicinal herb. In the Biopharmaceutics Classification System, it is of the class II type, meaning it is almost completely insoluble in water. It has a number of therapeutic properties, including anti-inflammatory as well as properties that promote wound healing.
This research target is to promote the dissolution and solubility of SM by employing a technique called solid dispersion and then incorporating the formula of solid dispersion into a topical gel that can be used for wound healing.
Solid dispersion is a technique used to enhance solubility and dissolve pharmaceuticals that are not water-soluble. This method is widely used because of its low cos
... Show MoreRap songs often feature artists who utilize explicit language to convey feelings such as happiness, sorrow, and anger, reflecting audience expectations and trends within the music industry. This study intends to conduct a socio-pragmatic analysis of explicit, derogatory, and offensive language in the songs of the American artist Doja Cat, employing Hughes’ (1996) Swearing Word Theory, Jay’s (1996) Taboo Words Theory, Luhr’s (2002) classification of social factors for sociolinguistic examination, Salager’s (1997) categories of hedges for pragmatic assessment, and Austin’s (1965, 1989) theory of speech acts. The researchers collected the data using the AntConc corpus analysis tool. The data shows the singer’s frequent use
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices
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