Prediction of android ransomware with deep learning model using hybrid cryptography.

In recent times, the number of malware on Android mobile phones has been growing, and a new kind of malware is Android ransomware. This research aims to address the emerging concerns about Android ransomware in the mobile sector. Previous studies highlight that the number of new Android ransomware is increasing annually, which poses a huge threat to the privacy of mobile phone users for sensitive data. Various existing techniques are active to detect ransomware and secure the data in the mobile cloud. However, these approaches lack accuracy and detection performance with insecure storage. To resolve this and enhance the security level, the proposed model is presented. This manuscript provides both recognition algorithms based on the deep learning model and secured storage of detected data in the cloud with a secret key to safeguard sensitive user information using the hybrid cryptographic model. Initially, the input APK files and data are preprocessed to extract features. The collection of optimal features is carried out using the Squirrel search optimization process. After that, the Deep Learning-based model, adaptive deep saliency The AlexNet classifier is presented to detect and classify data as malicious or normal. The detected data, which is not malicious, is stored on a cloud server. For secured storage of data in the cloud, a hybrid cryptographic model such as hybrid homomorphic Elliptic Curve Cryptography and Blowfish is employed, which includes key computation and key generation processes. The cryptographic scheme includes encryption and decryption of data, after which the application response is found to attain a decrypted result upon user request. The performance is carried out for both the Deep Learning-based model and the hybrid cryptography-based security model, and the results obtained are 99.89% accuracy in detecting malware compared with traditional models. The effectiveness of the proposed system over other models such as GNN is 94.76%, CNN is 95.76%, and Random Forest is 96%.

Biosynthesis of TiO2 nano particles by using Rosemary (Rosmarinus officinalis) leaf extracts and its application for crystal dye degradation under sunlight.

Titanium dioxide (TiO2) nanoparticles were prepared through Rosmarinus-officinalis leaf extracts at 90 and 200°C. In this research, the degradations of methylene blues by using TiO2 nanoparticles Sun light radiations were studied. The synthesized materials were characterized using XRDs, UV-Vis, PL, SEM, TEM, EDS and XPS. The results displayed that bio-synthesis temperatures intrude the shapes and sizes of TiO2 nanoparticles. For TiO2-90, micrographs show separable crystalline with irregular morphologies and agglomerate cubic particles. For the other TiO2-200 sample, SEM and TEM micro-imaging shows crumbly agglomerated cubic structures. The XRD shows that the intense peaks observed at angles of 25.37°, 37.19°, 47.81° and 53.89° confirming a highly crystalline oriented as (004), (200), and (105) planes respectively. The optical properties of TiO2 nanoparticles synthesized were conveyed by PL and UV-Vis. The energy band gap calculated was 3.0 eV for both samples; that indicates heating temperature didn't influence the band gap of the samples. The elemental composition Ti and O2 is shown by EDS and XPS. Photo-catalytic experiments discovered that TiO2-90 nanoparticles were well-organized in photo-degradations of MB, likened to TiO2-200. The great activities of TiO2-90 were because of better physicochemical characteristics associated with TiO2-200 effectively degrading MB under photo-light. Photo-degradations of dye under sunlight as plentifully obtainable energy sources by TiO2, synthesized by simpler techniques, can be hopeful to grow an eco-friendly and economical process.

Investigating topic modeling techniques through evaluation of topics discovered in short texts data across diverse domains.

The online channel has affected many facets of an individual's identity, commercial, social policy, and culture, among others. It implies that discovering the topics on which these brief writings are focused, as well as examining the qualities of these short texts is critical. Another key issue that has been identified is the evaluation of newly discovered topics in terms of topic quality, which includes topic separation and coherence. A topic modeling method has been shown to be an outstanding aid in the linguistic interpretation of quite tiny texts. Based on the underlying strategy, topic models are divided into two categories: probabilistic methods and non-probabilistic methods. In this research, short texts are analyzed using topic models, including latent Dirichlet allocation (LDA) for probabilistic topic modeling and non-negative matrix factorization (NMF) for non-probabilistic topic modeling. A novel approach for topic evaluation is used, such as clustering methods and silhouette analysis on both models, to investigate performance in terms of quality. The experiment results indicate that the proposed evaluation method outperforms on both LDA and NMF.

A vehicular network based intelligent transport system for smart cities using machine learning algorithms.

Smart cities and the Internet of Things have enabled the integration of communicating devices for efficient decision-making. Notably, traffic congestion is one major problem faced by daily commuters in urban cities. In developed countries, specialized sensors are deployed to gather traffic information to predict traffic patterns. Any traffic updates are shared with the commuters via the Internet. Such solutions become impracticable when physical infrastructure and Internet connectivity are either non-existent or very limited. In case of developing countries, no roadside units are available and Internet connectivity is still an issue in remote areas. Internet traffic analysis is a thriving field of study due to the myriad ways in which it may be put to practical use. In the intelligent Internet-of-Vehicles (IOVs), traffic congestion can be predicted and identified using cutting-edge technologies. Using tree-based decision-tree, random-forest, extra-tree, and XGBoost machine learning (ML) strategies, this research proposes an intelligent-transport-system for the IOVs-based vehicular network traffic in a smart city set-up. The suggested system uses ensemble learning and averages the selection of crucial features to give high detection accuracy at minimal computational costs, as demonstrated by the simulation results. For IOV-based vehicular network traffic, the tree-based ML approaches with feature-selection (FS) outperformed those without FS. When contrasted to the lowest KNN accuracy of 96.6% and the highest SVM accuracy of 98.01%, the Stacking approach demonstrates superior accuracy as 99.05%.

Maintenance of crack with infilling polymer modified mortar for shear deficient of reinforced concrete beam.

Being a developing country, Pakistan needs sustainable and cost-effective strengthening/ retrofitting solution to be adopted/ practiced in the construction industry. The research reported in this paper was aimed to study the effectiveness of PMM, an indigenous product, for repairing reinforced concrete beams, resulting more effective and cost benefiting repair and strengthening for restoration of pre-cracked RC structures. This article presents the research results of experimental investigation conducted for repairing of cracks in shear deficient reinforced concrete (RC) beams with locally available novel material polymer modified mortar (PMM). A total of 6 beams; divided in three groups i.e. short beams, medium beams and deep beams with varying depths and same mix design were tested to four point loading under monotonic loading conditions until failure loads. Afterwards, these beams were repaired with PMM and cured with water for 72 h for retesting until failure. Load at first crack and at failure, crack pattern and deflections were recorded for all specimens during testing. Results from the experimental investigation indicate that load carrying capacity of the repaired beams was significantly restored in comparison to the control specimens. However, repaired specimens of medium group showed more improvement in load carrying capacity as compared with those of repaired specimens of short and deep group. The specimens of medium group restored up to 90% of their original load carrying capacity. The ductility is improved significantly for all shear critical repaired RC beams up to opening of cracks. Sudden brittle failure was observed after opening of repaired cracks. The contribution of PMM to load carrying capacity was found more significant for medium beams as compared to short and deep beams. The results of this study indicated that application of polymer modified mortar is effective technique for repairing of cracks in shear deficient RC beams.

Numerical modelling on geotechnical features of soil mixture using recycled tire crumb to strengthen the seismic isolation in building.

In this research, the performance pertaining to tire crumb obtained from scrap tire processing plants is discussed. These tire crumbs are blended with soil at a 30% ratio. When subjected to seismic load, the performance of the 30% tire crumb combination is superior to the 0% tire crumb combination. The investigation is classified into two phases. Phase 1 of the study involves conducting an experimental investigation by applying cyclic loads to a model footing that was resting on the soil with and without tire crumbs. This study reveals that a 30% tire crumb combination achieves optimum energy absorption and minimal footing stiffness, which is a crucial component needed for base isolation. Additionally, using the PLAXIS 2D software package, finite element analysis was carried out during the second phase of the study. For this study, a three-story residential building close to the border between India and Nepal is used. Three different disastrous seismic excitations are applied to the building. From this analytical analysis, it is reported that a 60-70% reduction in acceleration is attained for 30% tire crumb combination with soil. Therefore, from the two phases, it is evaluated that the inclusion of tire crumbs with soil is an excellent seismic base isolation material.

Seasonal variations in the phenolic profile, antioxidant activity, and mineral content of south Indian black tea (Camellia sinensis (L.) O. Kuntze).

In the Anamallais region of south India, crop shoots from the UPASI-3, UPASI-9, UPASI-17, Assam seedlings, and TRI-2043 cultivars were examined for seasonal variations in total phenolics, antioxidant activity, and minerals during four harvest seasons: summer (January to March), premonsoon (April and May), monsoon (June to September), and winter (October to December) of two consecutive years. The total phenolics of all cultivars were lower in monsoon period and grew over rest of the seasons and it was greater during summer. Crop shoot antioxidant activity as measured by the DPPH radical scavenging experiment exhibited a similar pattern to total phenolics. Summer was the season with the highest antioxidant activity across all cultivars, followed by premonsoon, winter, and monsoon. On the other hand, the employed cultivars differed noticeably in terms of seasonal change of minerals. These results appear to indicate that the harvest period is hypercritical in deciding the antioxidant potency of tea crop shoots.

An examining the static and dynamic mechanical characteristics of milled ramie root reinforced polyester composites.

This research works discuss about the effective utilization of waste Ramie Root, that has been in reinforced polyester composites, powdered fillers that have not been treated are used. Four different composites plate were formed with compression moulding technique process consisting of 20, 30 and 40% of Powdered Ramie Root with 80, 70 and 60% unsaturated polyester resin, respectively. The maximum mechanical properties were observed for the composite with 30:70 weight volume percentages of milled ramie root synthetic reinforced polyester. The findings show that the glass transition temperature, storage modulus, and loss factors all rise when the composition of composites changes. Additionally, the powder cohesion force (bonding strength) has a greater impact on dynamic mechanical properties. Thermo-gravimetric the inclusion of Ramie Root powder caused the thermal deterioration peak of the composite to move from 370 °C to 418 °C, according to analysis (TGA) conducted under flowing oxygen. According to the measurement of water absorption, the ideal weight ratio of Fiber: Unsaturated Polyester Resin is 30:70, which modifies the fibres' surfaces and ensures optimal adhesion between the fibre and matrix in composite materials. Scanning electron microscopic investigation is done to ascertain the fracture behaviour of the composite. As a result of their stability, high tensile strength, and bending stiffness, the produced composites can be used in light-load applications by material technologists.

Development of alkali activated paver blocks for medium traffic conditions using industrial wastes and prediction of compressive strength using random forest algorithm.

Geopolymer is an environment friendly construction material that could be synthesized using either the natural source or the industrial byproducts such as flyash and GGBS. The characteristics of the Geopolymer rely on the proportion of the flyash and GGBS and the concentration of the activator solution used. In this research work, the effect of partial replacement of flyash with GGBS in proportions such as 0, 10, 20, 30 and 40% is investigated. Also Molarity of NaOH are tested from 8 to 14 M and both the parameters are optimized. In this optimized Geopolymer concrete, the utilization of iron slag as a partial substitute for river sand in various proportions such as 10, 15, 20, 25, 30 35, 40 and 45% are investigated. The optimized Geopolymer concrete with iron slag is investigated for its performance as a paver block with incorporation of banana fiber in proportions such as 0, 0.5, 1 and 1.5 and is compared with conventional cement concrete paver block. The results show that there is a significant enhancement in the properties of Geopolymer concrete with the different levels of optimization and the utilization of natural banana fiber. The developed sustainable paver block was found to with stand medium traffic conditions as per IS 15658:2006. Further this study employed random forest (RF) algorithm for the prediction of compressive strength of geopolymer concrete specimens for the variable parameters such as molarity of alkaline solution, Flyash/GGBS ratio and partial replacement of river sand with iron slag. The performance evaluation parameters represented high accuracy of developed RF model. This research work unleashes a heft potential of Geopolymer concrete to develop economical eco-friendly sustainable paver blocks to the society through mitigation of environmental strain on the ecosystem.

Regression analysis on forward modeling of diffuse optical tomography system for carcinoma cell detection.

The forward model design was employed in the Diffuse Optical Tomography (DOT) system to determine the optimal photonic flux in soft tissues like the brain and breast. Absorption coefficient (mua), reduced scattering coefficient (mus), and photonic flux (phi) were the parameters subjected to optimization. The Box-Behnken Design (BBD) method of the Response Surface Methodology (RSM) was applied to enhance the Diffuse Optical Tomography experimental system. The DC modulation voltages applied to different laser diodes of 850 nm and 780 nm wavelengths and spacing between the source and detector are the two factors operating on three optimization parameters that predicted the result through two-dimensional tissue image contours. The analysis of the Variance (ANOVA) model developed was substantial (R2 = > 0.954). The experimental results indicate that spacing and wavelength were more influential factors for rebuilding image contour. The position of the tumor in soft tissues is inspired by parameters like absorption coefficient and scattering coefficient, which depend on DC voltages applied to the Laser diode. This regression method predicted the values throughout the studied parameter space and was suitable for enhancement learning of diffuse optical tomography systems. The range of residual error percentage evaluated between experimental and predicted values for mua, mus, and phi was 0.301%, 0.287%, and 0.1%, respectively.

Second law assessment of di methyl ether and its mixtures in domestic refrigeration system.

Dimethyl ether (DME) and its blend of refrigerants (R429A, R435A, and R510A) are considered in this study's second law analysis as potential replacements for R134a. The performance of various refrigerants in a vapour compression refrigeration system is examined using the Design package CYCLE D. The software REFPROP 9.0 is used to extract all of the thermal and physical parameters of DME and its blend of refrigerants. The Second law performance parameters such as Efficiency Defects, Entropy generation and ExergyEfficiency are discussed. The refrigerants R429A and R510A are more energy efficient than R134a across a condensing temperature range of 30 to 55 °C at - 10 °C evaporation temperature. R134a was exceeded by R429A and R510A in terms of exergetic efficiency by 2.08 and 0.43%, respectively. In comparison to other losses in different components, the compressor's exergy loss is larger at 37-40% of the total exergy loss. By employing RE170 and its blends, the Vapour Compression Refrigeration System often performs better under the second law than R134a.The result shows that the efficiency defects in the compressor are the largest, followed by the condenser and evaporator. Thus, the design improvement of a compressor is of at most importance to improve the system performance by lowering the overall irreversibility.

A mathematical analysis of mass transfer phenomena with chemical reaction over the flow of Sisko ferronanofluid across a permeable surface.

Mathematically study mass transfer phenomena involving chemical reactions in the flow of Sisko Ferro nanofluids through the porous surface. Three ferronano particles, manganese-zinc ferrite (Mn1/2Zn1/2Fe2O4), cobalt ferrite (CoFe2O4), and nickel-zinc ferrite (Ni-Zn Fe2O4) are considered with water (H2O) and ethylene glycol (C2H6O2) as base liquids. Appropriate resemblance transitions are used to convert the governing system of a nonlinear PDE to a linear ODE. The Runge-Kutta method, as extended by the shooting technique, is used to accomplish the reduction governing equations. The effects of various associated parameters on fluid concentration and mass transfer rate are investigated: magnetic criterion (M), Siskofluid material factor (A), Solid volume fraction (ϕ) for nanofluids, permeability parameter (Rp), Chemical reaction criterion (γ), Brownian motion factor (Nb), and Thermophoretic parameters (Nt). The current findings indicate that the diffusion proportion of Sisko Ferronanofluid Ni-Zn Fe2O4-H2O and CoFe2O4-H2O is higher than that of Ni-Zn Fe2O4-C2H6O2 and CoFe2O4-C2H6O2 respectively but it is opposite in the case of Mn-Zn ferrite. The comparison study was carried out to validate the precision of the findings.

An analysis of environment effect on ethanol blends with plastic fuel and blend optimization using a full factorial design.

There is a growing amount of plastic waste that needs to be properly disposed of in order to protect the environment from the negative effects of increasing reliance on plastic products. Recent interest has focused on chemical recycling as a means of reducing plastic's negative environmental effects. Converting waste plastics into basic petrochemicals allows them to serve as hydrocarbon feedstock or fuel oil through pyrolysis operations. Scientists have taken a keen interest in the production of bioethanol from renewable feedstocks due to its potential as a source of energy and alternative fuel. Due to its beneficial effects on the environment, ethanol has emerged as a promising biofuel. In this paper, energy recovered from low-density polyethylene and high-density polyethylene waste was converted into an alternative plastic fuel and evaluated for its environmental impact with the blending of ethanol in a diesel engine. Ternary fuel blends with 20%, 30%, and 40% waste plastic fuel and 10%, 15%, and 20% ethanol with standard diesel were tested. The study found that blending 10% ethanol with 20% plastic fuel decreased fuel consumption by around 7.9% compared to base diesel. Carbon monoxide emissions are reduced by about 10.2%, and hydrocarbon emissions are reduced by about 13.43% when using the same ternary blend. The optimum values of fuel consumption and emissions were obtained by full factorial design for a ternary fuel blend of 10% ethanol and 20% plastic fuel at the full load condition.

Growth, yield, and yield variables of onion (Allium Cepa L.) varieties as influenced by plantspacing at DambiDollo, Western Ethiopia.

Onion (Allium cepa L.) is an important bulb plant grown worldwide. Proper use of the agronomic practice has undoubtedly contributed to growing crop yields. The right level of any farming practice, like the distance between plants, plant density, date of planting, and time of harvest, can produce the wanted outcomes. Therefore, this research was piloted to evaluate the influence of plant spacing on the development of bulb harvest-related traits of onion varieties in Dambi Dollo University, Western Ethiopia, in 2021. Three onion varieties (Adama red, Monarch, Nafis) and four intra-row spaces (6 cm, 8 cm, 10 cm, and 12 cm) in factorial combinations were settled by a complete randomized block design which was simulated three times. The findings of the study indicate that all the factors related to crop growth and bulb yield of onion varieties were mainly influenced by different kinds and plant spacing. Conversely, the collaboration of these two factors did not affect all other factors, but the interaction of the two factors had a great effect on the days to maturity measured in this study. The highest plant height was registered on the onion planted at a distance of 10 cm (59.83 cm) and 12 cm (59.08 cm) distance between plants. The high commercial yields (34.44 t ha-1) and entire bulb yield (35.40 t ha-1) were found in the Nafis variety. The highest marketable yields (31.12 ha-1) and entire marketable yield (31.78 ha-1) were recorded on an onion plant planted 10 cm between plants. Therefore, in the research area, farmers can use a variety of Nafis and a 10 cm distance between plants to increase their onion production.

Efficiency of Ferritin bio-nanomaterial in reducing the pollutants level of water in the underground corridors of metro rail using GIS.

The underground developments are likely to deteriorate the water quality, which causes damage to the structure. The pollutant levels largely affect the aquifer properties and alter the characteristics of the water quality. Ferritin nanoparticle usage proves to be an effective technology for reducing the pollutant level of the salts, which are likely to affect the underground structure. The observation wells are selected around the underground Metro Rail Corridor, and the secondary observation wells are selected around the corridors. Ferritin is a common iron storage protein as a powder used in the selected wells identified in the path of underground metro rail corridors. Water sampling was done to assess the water quality in the laboratory. The water quality index plots for the two phases (1995-2008) and (2009-2014) using GIS explains the water quality scenario before and after the Ferritin treatment. The Ferritin treatment in water was very effective in reducing the pollutants level of Fluoride and sulphate salts which is likely to bring damage to the structure.

Biosynthesis of TiO2 nanoparticles by Caricaceae (Papaya) shell extracts for antifungal application.

Titanium dioxide nanoparticles (TiO2 NPs) were prepared by Caricaceae (Papaya) Shell extracts. The Nanoparticles were analyzed by UV-Vis spectrums, X-ray diffractions, and energy-dispersive X-rays spectroscopy analyses with a scanning electron microscope. An antifungal study was carried out for TiO2 NP in contradiction of S. sclerotiorums, R. necatrixs and Fusarium classes that verified a sophisticated inhibitions ratio for S. sclerotiorums (60.5%). Germs of pea were individually preserved with numerous concentrations of TiO2 NPs. An experience of TiO2 NPs (20%, 40%, 80% and 100%), as well as mechanisms that instigated momentous alterations in seed germinations, roots interval, shoot lengths, and antioxidant enzymes, were investigated. Associated with controls, the supreme seeds germinations, roots and plant growth were perceived with the treatments of TiO2 NPs. Super-oxide dis-mutase and catalase activities increased because of TiO2 NPs treatments. This advocates that TiO2 Nanoparticles may considerably change antioxidant metabolisms in seed germinations.

Influence of capillary tube length on the performance of domestic refrigerator with eco-friendly refrigerant R152a.

The household heating and cooling system often use the capillary device. The use of the helical capillary eliminates the need for lightweight refrigeration devices in the system. Capillary pressure is noticeably affected by the capillary geometric parameters, such as length, mean diameter, and pitch. This paper is concerned with the effects of the capillary length on the performance of the system. Three separate length capillary tubes were used in the experiment. The data on R152a were studied under various conditions to assess the impact of varying the length. Maximum COP is obtained at an evaporator temperature of - 12 °C and capillary length of 3.65 m. The result is drawn that the system performance enhances when the capillary length is improved to 3.65 m when compared to 3.35 m and 3.96 m. As a result, as the capillary length increases up to a specific amount, the system's performance improves. The findings from the experiment were compared with those from the computational fluid dynamics (CFD) analysis.

Factors Associated with the Prevalence of Hepatitis B among Volunteer Blood Donors at Jimma Blood Bank, South Ethiopia.

Background: Hepatitis B is a severe, widespread infectious disease of the liver that affects millions of people around the world. It is one of the life-threatening liver infections caused by the hepatitis B virus (HBV). HBV is the cause of up to 80% of cases of primary liver cancer. Due to the potential risk associated with HBV infection, it is important to study the factors which are associated with the seropositive volunteers. Objective: The purpose of this study was to identify factors associated with seropositivity for the hepatitis B virus among volunteers who donated blood at the Jimma Blood Bank in southern Ethiopia. Methods: Cross-sectional research was conducted on blood donors who came to the Jimma Blood Bank to donate their blood. Three hundred and fifty-nine volunteer blood donors who arrived at the Jimma Blood Bank were investigated face-to-face in order to collect sociodemographic characteristics and risk factors for HBV infection. The data were analyzed using statistical software SPSS version 20.0. The association between the risk factor for HBV infection and HBV infection was determined using chi-square tests. Result: In total, there were 359 participants; their mean age was 22.5, among which 161 (44.8%) were males. Out of 359 volunteers, 13 (3.6%) were seropositive for HBsAg. The test positivity rate among males was 7/198 (3.54%), while the rate among females was 6/161 (3.7%). More than 3/4 of those who tested positive were under the age of 40. Chi-square analysis showed that volunteers whose income was between 12 and 26.84 USD were less likely to have the infectious disease than those whose income was less than 11.84 USD per month (p=0.042). Conclusion: The prevalence of HBV was found to be 3.6% among selected volunteers. It was found that, out of 20 volunteers, 13 had infection. Chi-square analysis showed that HBV infection was associated with low monthly income and the use of unsafe therapeutic injections.

Biological approach synthesis and characterization of iron sulfide (FeS) thin films from banana peel extract for contamination of environmental remediation.

Biological approach synthesis and characterization of Iron Sulfide (FeS) thin films from banana peel extract for contamination remediation of environment studied. Iron chloride, Sodium thiosulfate and Ethylene-di-amine-tetra acetate (EDTA) were used as precursor solutions without further purification. The nanoparticle of banana peel was extracted and prepared with synthesized FeS thin films and analyzed by X ray-diffraction for structural examination, Scanning electron microscope (SEM) for surface morphological analysis, Ultra-violet-visible-spectrometer (UV-Vis) and photo-luminescence spectro-photo-meter (P-L) for optical characterizations. XRD peaks are shown with recognized to (110), (200), (310), and (301) crystalline planes. The occurrence of this deflection peak are recognised the FeS crystal segment of the tetragonal crystalline systems. SEM micrographs of the films prepared biological method show the distribution of grains, which cover the surface of the substrate completely and are uniform and films deposited purely have defects. The photo-luminescence, absorbance, and transmittance strength of banana peel extract FeS thin film is greater than pure FeS thin films in which wide-ranging and symmetries groups were perceived. In the present study, the comparison of pure FeS thin films and Nano synthesized banana peel extract with FeS thin films was studied. It is observed that Nano synthesized banana fibre absorbs higher than pure FeS thin films in solar cell application. Finally, green synthesis is an ecofriendly, easy and cheap promising method for the fabrication of thin films for solar cell applications.

Energy recovery of waste plastics into diesel fuel with ethanol and ethoxy ethyl acetate additives on circular economy strategy.

The widespread use of plastic goods creates huge disposal issues and environmental concerns. Increasing emphasis has been paid to the notion of a circular economy, which might have a significant impact on the demand for plastic raw materials. Post-consumer plastics recycling is a major focus of the nation's circular economy. This study focuses on energy recovery from waste plastics as an alternative fuel source to meet the circular economy demand. Waste plastic fuel produced through pyrolysis has been claimed to be utilized as a substituted fuel. This work focuses to determine the performance and emission standards of Waste Plastic Fuel (WPF) generated from the pyrolysis of High-Density Polyethylene (HDPE) in a single-cylinder Direct Injection Diesel Engine (DIDE). Three different ratios of WPF were combined with 10% ethanol and 10% ethoxy ethyl acetate as an oxygenated additive to create quaternary fuel blends. The ethanol has a low viscosity, a high oxygen content, a high hydrogen-to-carbon ratio as favourable properties, the quaternary fuel results the improved brake thermal efficiency, fuel consumption and reduced emissions. The blend WEE20 exhibits 4.7% higher brake thermal efficiency, and 7.8% reduced fuel consumption compared to the diesel. The quaternary fuel blends demonstrated decreased carbon monoxide of 3.7 to 13.4% and reduced hydrocarbons of 2 to 16% under different load conditions.