Energy Analysis for the Compaction of Jerash Cohesive Soil

The aim of this research is to study the effect of compaction energy on Jerash cohesive soil. Qualitative and quantitative analyses of soil compaction energy with relation to unit weight and moisture content are conducted. These analyses spot the light on energy savings performed for soil compaction. The study shows that as the compaction energy increases;the unit weight of the Jerash cohesive soil increases and the optimum water content decreases. Generally, a soil with low moisture content is less vulnerable to compaction than a soil with high moisture content. But when the moisture content is too high, all the soil pores are filled with water, so that the soil becomes less compressible where the unit weight and strength characteristics decrease. The optimum energy value and optimum water content are thus of great concern. The effect of energy on soil unit weight is very large as the energy increases from 400 to 1400 KJ/m3 and after that level;the effect of energy on soil unit weight is very small. Consequently, optimal compaction energy ranges from 1200 up to value 1400 KJ/m3, where 50 to 60 blows can be applied and the optimal correlated water content is between 14% - 15%.

Effect of Using Stone Cutting Slurry Waste (Al-Khamkha) on the Compaction Characteristics of Jerash Cohesive Soil

The aim of this research is to study the effect of using (Al-KHAMKHA) is stone cutting slurry waste local name in JORDAN on the unit weight and moisture content of Jerash cohesive soil Al-Khamkha which is the local name of the stone cutting slurry waste which is produced during the cutting operation, This water carries large amounts of stone powder, which leads to complex nature of environmental problem so these waste material needs to be utilized meaningfully in economic way. The degree of compaction of a soil is measured in terms of its dry unit weight Al-Khamkha mixed with Jerash cohesive soil at different amount ranges from 0%, 5%, 10%, 15%, up to 50% and compaction characteristics of Jerash cohesive soil without and with different amount of Al-Khamkha was studied. This investigation show that as the amount of Al-Khamkha increase from 0% to 15%, the dry unit weight of Jerash cohesive soil increase from 14.4 KN/m3 at 0% of Al-Khamkha to 16.5 KN/m3 at 15% and after that .any increase of Al-Khamkha decrease the dry unit weight. On the other hand, the optimum water content of the Jerash cohesive soil was increases with increasing the percentage of Al-Khamkha on the cohesive soil.

Phishing Attacks Detection Using EnsembleMachine Learning Algorithms

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based institutions.Data indicates a persistent rise in phishing attacks.Moreover,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to identify.Hence,it is imperative to utilize sophisticated algorithms to address this issue.Machine learning is a highly effective approach for identifying and uncovering these harmful behaviors.Machine learning(ML)approaches can identify common characteristics in most phishing assaults.In this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing datasets.After that,we used the normalization technique on the dataset to transform the range of all the features into the same range.The findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and F1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random Forest(RF)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best results.While in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction process.Also,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense mechanisms.This paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world settings.Our proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive framework.This integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT systems.We evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated attacks.Our research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive quality.Our model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security paradigms.Through our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of IoT.Our model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat landscape.This achievement marks a significant stride towards protecting the integrity of IoT infrastructure,ensuring operational resilience,and building privacy in this groundbreaking technology.

SOME INEQUALITIES OF HERMITE-HADAMARD TYPE FOR s-CONVEX FUNCTIONS

In this paper several inequalities of the left-hand side of Hermite-Hadamard’s inequality are obtained for s-convex functions.

A Review on Constructed Wetlands Components and Heavy Metal Removal from Wastewater

Constructed wetlands are man-made complex of substrates, emergent/submergent vegetation, and water. Constructed wetlands have been known as an efficient and low-cost treatment process. Constructed wetland is a natural treatment system that physical, chemical, and biological processes occur when water, soil, plants, and microorganisms interact. They are considered as natural treatment ecosystems that are designed to take advantages of the natural processes to provide wastewater treatment. Constructed wetlands treat different types of wastewaters such as municipal, industrial, agricultural, and storm water. The removal of heavy metals within wetlands is performed generally by plant uptake and by adsorption onto sediments. Heavy metal treatment examples and some specifications and regulations are finally discussed.

Artificial Intelligence for Speech Recognition Based on Neural Networks

Speech recognition or speech to text includes capturing and digitizing the sound waves, transformation of basic linguistic units or phonemes, constructing words from phonemes and contextually analyzing the words to ensure the correct spelling of words that sounds the same. Approach: Studying the possibility of designing a software system using one of the techniques of artificial intelligence applications neuron networks where this system is able to distinguish the sound signals and neural networks of irregular users. Fixed weights are trained on those forms first and then the system gives the output match for each of these formats and high speed. The proposed neural network study is based on solutions of speech recognition tasks, detecting signals using angular modulation and detection of modulated techniques.

Real-Time Lane Detection for Driver Assistance System

Traffic problem is more serious, as the number of vehicles is growing. Most of the road accidents were caused by carelessness of drivers. To reduce the number of traffic accidents and improve the safety and efficiency of traffic for many years around the world and company studies have been conducted on intelligent transport systems (ITS). Intelligent vehicle, (IV) the system is part of a system which is designed to assist drivers in the perception of any dangerous situations before, to avoid accidents after sensing and understanding the environment around itself. In this paper, it proposes architecture for driver assistance system based on image processing technology. To predict possible Lane departure, camera is mounted on the windshield of the car to determine the layout of roads and determines the position of the vehicle on line Lane. The resulting sequence of images is analyzed and processed by the proposed system, which automatically detects the Lane lines. The results showed of the proposed system to work well in a variety of settings, In addition computer response system is inexpensive and almost real time.

Design and Implementation of Double Base Integer Encoder of Term Metrical to Direct Binary

The digital processing signal is one of the subdivisions of the analog digital converter interface;data transfer rate in modern telecommunications is a critical parameter. The greatest feature of parallel conversion rate (4-bit parallel Flash 5/s converter) is designed and modeled in 0.18 micron CMOS technology. Low speed swing operation as analog and digital circuits leads to high speed of low power operation power with 70 mVt 1.8 V A/D converter from the power dissipated during operation in the 5 GHz range. Average offset is used to minimize the effect of the bias of a comparator. This paper contains the 8-bit encoder of the metrical term code to direct binary code decreasing power consumption, which is shown by results and comparison with other designs using computer simulation. The results of the flash ADC time-interleaved are a more significant improvement in terms of power and areas than those previously reported.

Applications and Prospects of Fiber Reinforced Concrete in Industrial Floors

Upon the view of this work, industrial floor is a vital structure due to its relation to quality of production, labor comfort, and human health. Flooring costs may reach 20% of single-story building construction expenditure, and the consumption of concrete for floors may come to 40% - 50% of the total size of concrete. Thereby, the efficient design of floor will reduce materials consumption and labor, and will increase the endurance of the floor. Fiber reinforcement reduces the thickness of the subfloor about 20% - 30%, hence enabling to reduce the consumption of cement and fillers. The use of fiber meshes will enable to save 30% - 40% of steel. Despite the flexible use of fiber in concrete reinforcement saves effort and money, still fiber reinforced concrete is lacking additional regulations in Jordan.

Isolation of Pathogenic Gram-Negative Bacteria from Urinary Tract Infected Patients

This study investigated the susceptibility pattern of different bacteria isolated from urinary tract infection to different antibiotics. 83 uropathogen bacteria were isolated from 300 urine samples taken from patients attended to Tikrit Teaching Hospital from March, 2011 through February, 2012. The patients were males and females aged between 4 days to 95 years. Bacteria obtained from urine samples were cultured and tested for antimicrobial susceptibility to 16 kinds of antibiotics. Urine samples were cultured on different media and incubated, thereafter bacteria were isolated and purified by streaking four times on the same media;isolates were identified depending on morphological, microscopic, and biochemical characteristics. The isolated strains of bacteria were tested for their susceptibility to some antibiotics using disk diffusion method. The antagonistic activity was evaluated by observing a clear zone of inhibition growth. The results showed that the bacterial species of Eschericia coli, Proteus mirabilis, Klebsiella pneumonia, Citrobacter diversus, Citrobacter freundii, Enterobacter aerogenes, Yersinia pestis, Pseudomonas aeruginosa, Klebsiella oxytoca and Hafnia alvei were identified in 44 (53%), 18 (21.7%), 4 (4.8%), 4 (4.8%), 3 (3.6%), 3 (3.6%), 3 (3.6%), 2 (2.4%), 1 (1.2%) and 1 (1.2%), respectively, of the isolates. The results of antimicrobial susceptibility test showed that 83 (100%) isolates were resistant to Ampicillin, Rifampicin and Erythromycin. 75 (90.3%) isolates were resistant to Cefotaxime, 67 (80.7%) isolates were resistant to Tobramyci. 66 (79.5%), 65 (78.3%), 56 (67.4%) and 48 (57.8%) isolates showed susceptibility to Nalidixic acid, Tetracycline, Nitrofurantoin, Chloramphenicol, respectively. 45 (54.2%) isolates were resistant to Azithromycin, Norfloxacin and Ciprofloxacin. Meropenem, Gentamicin, Amikacin, and Imipenem show significant effect on 35 (42.1%), 32 (38.5%), 27 (32.5%) and 1 (1.2%) isolates, respectively. In conclusion, significant bacteria count isolated from urine samples is pathogenic. The most effective antibiotic in inhibiting the bacterial growth was Imipenem while Ampicillin, Rifampicin and Erythromycin showed no effect on all 83 isolates (100%).

Solar Energy Sustainability in Jordan

Jordan is a country with highly fossil fuel deficiency and thus other energy sources are needed to be explored. Solar energy in Jordan is highly recognized as a good source of energy and an excellent substitute to the fossil fuel. The solar energy in this article is obtained via data bases and modeling techniques for the specified place coordinate and angle of inclination. The angles of sun irradiations are different throughout the year;therefore solar energy needs to be magnified by optimizing the angle of inclination of solar cells. In this research, the optimized angles throughout the year are obtained to be in the range: 10°-60°. Solar energy can serve the residential building, the findings of this research show that every 1 m2 of the solar cell may contribute to about 60%-70% of customer needs of electricity throughout the year. The application of solar energy concept in the design of building will play an important role in energy sustainability.

Adaptive Neuro-Fuzzy Logic System for Heavy Metal Sorption in Aquatic Environments

In this paper, adaptive neuro-fuzzy inference system ANFIS is used to assess conditions required for aquatic systems to serve as a sink for metal removal;it is used to generate information on the behavior of heavy metals (mercury) in water in relation to its uptake by bio-species (e.g. bacteria, fungi, algae, etc.) and adsorption to sediments. The approach of this research entails training fuzzy inference system by neural networks. The process is useful when there is interrelation between variables and no enough experience about mercury behavior, furthermore it is easy and fast process. Experimental work on mercury removal in wetlands for specific environmental conditions was previously conducted in bench scale at Concordia University laboratories. Fuzzy inference system FIS is constructed comprising knowledge base (i.e. premises and conclusions), fuzzy sets, and fuzzy rules. Knowledge base and rules are adapted and trained by neural networks, and then tested. ANFIS simulates and predicts mercury speciation for biological uptake and mercury adsorption to sediments. Modeling of mercury bioavailability for bio-species and adsorption to sediments shows strong correlation of more than 98% between simulation results and experimental data. The fuzzy models obtained are used to simulate and forecast further information on mercury partitioning to species and sediments. The findings of this research give information about metal removal by aquatic systems and their efficiency.

Root Analogous Solid Waste Management System (RA-MSW for Biocells)

Root Analogous Municipal Solid Waste System “RA-MSW” is a novel management system that manages waste, biogas, and leachate in bioreactor landfill. Different than conventional disposal at landfills, waste is penetrated by synthetic roots that serve dual mission for biogas collection and leachate recirculation. RA-MSW roots are permeable hydropho- bic polymer material that are formed on-place or prefabricated at factory from recyclable material available on the dumping area. Since the material is hydrophobic, it does not contain water in the voids providing more space for gas transport and collection. The roots are also interchangeably used for leachate recirculation where the parameters of wa- ter content, nutrients, pH, and temperature are optimized to enhance biogas production simultaneously with leachate treatment. RA-MSW provides new approach of waste management and control;it has new virtues of landfill operation;new material medium for biogas collection;new biocell design configuration;new manipulation for leachate and biogas. The approach adds new merits for solid waste management, bio-energy utilization, and the concept of 5 R’s cycle for MSW management.

Effects of Stone Cutting Powder (Al-Khamkha) on the Properties of Self-Compacting Concrete

Most of the construction materials research now concerns on investigation of construction materials that is locally produced at a rate and cost compatible with the pace of construction. The present paper is concerned with investigation of fresh and hardened properties of self-compacting concrete (SCC) produced from local available materials in JORDAN. The produced SCC contains the local stone cut waste powder which is called Al-KHAMKHA in JORDAN with different replacement of (0%, 10%, and 25%) of fine silica aggregate;?the study also investigatesthe effects of SP33 super?plasticizer which is used by different doses (1%, 1.5% and 2%) for cement. The slump flow and the compressive strength of SCC were studied and the experimental results indicate the possibility of using Al-KHAMKHA in the production of SCC as the results showed that the compressive strength of the SCC with 10 % replacement by al-khamkha together with 1% SP33?super plasticizer was higher compared to pure SCC without al-khamkha;?the results also showed that as al-khamkha content increased the slump flow decreased.

Digital Weather Stations as a Part of Wind Power Station

This paper mainly studies Weather Stations part of the wind power station. The use of wind energy in practice is carried out using the facilities of the wind in which the kinetic energy of the windscreen flow is converted into mechanical energy wind speed, then electrical energy alternator. The effective operation of the wind turbine is dependent on the direction of the wind. Speed air density, which in turn depends on the temperature and humidity. Thus, the speed of the wind worked effectively in its composition must include the weather. Meteorological station also performs the role of prevention. When the sharp wind speed or increase wind speed above the maximum value, it sends a signal to the lock assembly wind to prevent wind turbine technology from damage. The work of the meteorological stations design as part of the Wind Energy Station is considered. The complex technical devices are used for its implementation. A set of technical means used to its implementation and designed system consists of a temperature, humidity, wind speed, wind direction and rain gauge sensors that are connected to PIC16f876A microcontroller.

A New Enhanced Arabic Light Stemmer for IR in Medical Documents

This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem,especially in medical documents.Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data.One of the main challenges facing the light stemming algorithm is cutting off the input word,to extract the initial segments.When initiating the light stemmer with strong initial segments,the final extracting stems and roots will be more accurate.Therefore,a new enhanced segmentation based on deploying the Direct Acyclic Graph(DAG)model is utilized.In addition to extracting the powerful initial segments,the main two procedures(i.e.,stems and roots extraction),should be also reinforced with more efficient operators to improve the final outputs.To validate the proposed enhanced stemmer,four data sets are used.The achieved stems and roots resulted from our proposed light stemmer are compared with the results obtained from five other well-known Arabic light stemmers using the same data sets.This evaluation process proved that the proposed enhanced stemmer outperformed other comparative stemmers.

Three-Dimensional Scenes Restore Using Digital Image

Encryption and decryption method of three-dimensional objects uses holograms computer-generated and suggests encoding stage. Information obtained amplitude and phase of a three-dimensional object using mathematically stage transforms overlap stored on a digital computer. Different three-dimensional images restore and develop the system for the expansion of the three-dimensional scenes and camera movement parameters. This article talks about these kinds of digital image processing algorithms as the reconstruction of three-dimensional model of the scene. In the present state, many such algorithms need to be improved in this paper proposing one of the options to improve the accuracy of such reconstruction.

GA-Fuzzy Decision Support System for Mercury Removal in Natural Waters

The idea of this research is to apply sustainability and augment efficiency of the aquatic systems by intelligent tools. This paper exploits fuzzy logic approach as a flexible methodology for providing supplementary information about mercury removal in natural waters. Fuzzy logic generates information on Hg behaviour in water according to its uptake by bio-species and adsorption by sediments. Fuzzy Decision Support System (FDSS) comprises knowledge base (i.e. premises and conclusions), fuzzy sets, and fuzzy rules. Knowledge base and rules are being built manually and by algo- rithm. GA-FDSS incorporates genetic algorithm GA to build optimal approximation for knowledge base, fuzzy sets, and rules. The role of integrating GA with FDSS is to train knowledge base and rules automatically from available data, hence FDSS models and predicts conclusion acquired. The findings of this research show more than 95% correlation between observed data and soft computed data. The optimal biological uptake occurs at pH of 5.5. The optimal sedi-ment adsorption occurs at pH of 8. The final mercury concentration calculated in natural waters is about 7 ? 10–8 mole/L. The results show that the removal efficiency of mercury by natural waters approaches 97%. Consequently the obtained fuzzy logic informative hierarchy is proficient to manage metals removal by aquatic systems.

Solar Energy Optimization through Seasons: Case Study in Jordan

Solar energy in Jordan is recognized high amongst in the world. The solar energy cultivation needs to be magnified by optimizing the angle of inclination of solar cells. The angle of inclination in this work is not fixed but variable throughout the year, and consequently the angle is optimized for seasons. In this research, the optimized angles for seasons in Jordan are obtained as: 60? for Winter (November to February), 30? for Spring (March and April), 10? for Summer (May to August), and 30? for Fall (September and October). The optimized cultivated energy throughout all seasons in the year equals about 2490 kWh/m2. The residential customer consumption of electricity is 2475 kWh/customer per year. Therefore, according to Jordan, if the sun energy is converted efficiently to electricity, it will be worthy to apply for residential building for which each customer should have some area of solar cells to overcome the needs of energy. In addition, with some wise management of electricity in the daylight period, fossil fuel consumption will be minimized. Hence, combining solar energy concept in the design of building is an important step in sustainable development of green energy.