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The quick development of technology not only makes life easier but also raises several security concerns, so cyber security has become very important and vital research area, rather an inevitable part of computer system. Still, various research being done on the development of effective intrusion detection system (IDS). An IDS is one of the suspicious network activities. An IDS is used to identify many types of malicious actions that can undermine a computer system's protection and confidence. Recently, ensemble algorithms are applied in IDS in order to identify and classify the security threats. In this paper author intends to do a brief review of various Ensemble learning Algorithms in ML, which are most frequently used in IDS for several applications; with specific interest in dataset and metric. This work provides broad study and investigation on current literature, the gap for improving and creating efficient IDS can be determined. [ABSTRACT FROM AUTHOR]

In recent times, the interaction between human beings and computers has become an increasing field of research due to its wide application of computational systems. Determination of the current state of human psychological problems, one of the most relevant techniques is emotion recognition. The dynamic behavior of human is crucial for its interpretation. So, Facial emotion recognition (FER) is an important research area for detection the of different facial emotions. In this paper, we proposed an Unconstrained Minimum Average Correlation Energy (UMACE) filter as a classifier for facial emotion recognition. We are applying this proposed method in the CK+ database and it can give a better recognition rate. [ABSTRACT FROM AUTHOR]

In this paper, technical and statistical analysis of Smart Living, one of the most important aspects of the next generation, has been provided with detailed information. Smart living refers to using technology and the internet of things (IoT) to pursue a more efficient, controllable, and productive lifestyle. In this century, with the increase in the global population, smart living is a significantly important criterion to ensure equal opportunities for all. Here a complete overview and case implementation are discussed, followed by an analysis of statistical data about the demand for smart living from a Techno-Socio point of view. Lastly, a few aspects and issues of Smart Living have been discussed, and a proposal is given to improvise it further for future research and possible implementation. [ABSTRACT FROM AUTHOR]

Health of Livestock is one of the growing concerns in today's world due to the increased population and the increased need for Dairy products. So, a regular checkup is required to improve the cattle's life duration and be kept in good health. Many dairies and farms have many farm animals, making it tough to care for them and routinely monitor the health of dairy cattle. The livestock health monitoring system aims to monitor each cattle's health. In this system, we use the Internet of Things and machine learning to observe the aspects of cattle's physical characteristics like temperature, heart rate, etc. In this paper, we have discussed the existing approaches to monitoring cattle's health and location tracking. Finally, a method has been discussed to improve the efficiency of the process. [ABSTRACT FROM AUTHOR]

For proper monitoring of irrigation system, a smarter way of looking into this is very necessary. In this paper a smarter irrigation system is proposed which can monitor the moisture level of the crops and according to that feed the water to the different crops in the field. This smart system is comprising with an Arduino board alongside with a moisture sensor. Alongside with the smart irrigation system implementation of the renewables is also added here, Pumps are being feed by the PV system for maximizing the profit in electricity bill for the farmers. Electricity bill without using the renewables and with renewables is compared here, considering the installation cost of the PV system. Battery storage system is also considered for the intermittent nature of the renewable energy. By implementing solar customer benefit is also shown in this study. [ABSTRACT FROM AUTHOR]

In this paper a MPPT based impedance source solar powered inverter is designed to convert solar power to an alternating supply. First a boost converter is built to transform variable input voltage to a fixed DC voltage of desired magnitude and then it is fed to the impedance source inverter. MPPT algorithm is used to track the maximum power while controlling the duty cycle of the boost converter. The integration of MPPT with impedance source converter (ZSI) is primarily motivated by its efficiency in power conversion and reliability, making it a favorable choice for various distributed generation power applications compared to voltage source inverters. In this paper, an analysis is conducted on a three-phase impedance source inverter using a straightforward boost control method. The analysis focuses on key aspects such as the boosted output voltage, total harmonic distortion (THD) of line current, voltage stress on switches, generation of shoot-through states, and converter gain. Simulation is carried out in MATLAB Simulink environment and the results are presented to verify the theoretical findings [ABSTRACT FROM AUTHOR]

The development of smart industries and cities is expected to have profound effects, and the rapid advancement of smart gadgets may cause safety and security problems. In order to increase training and learning opportunities while simultaneously addressing the considerable challenges that educational institutions will face, higher education 4.0 will make use of modern technologies. By examining the key components, traits, and motivators of education 4.0, this paper intends to contribute to the development of smart education for a smart city. [ABSTRACT FROM AUTHOR]

Now days the impact of climate change in India are mostly affected to the agriculture field, most of the agricultural crops are being badly affected in terms of their performance of the crop. The crop yield is used to predict in advance because of its harvest, its help the farmers for taking good decisions in marketing. The results of knowing crop yield and building prototype for the purpose of easily available to the farmer. Thus, for such kind of data analysis in the crop, there are different techniques and algorithms to predict the crop in a field. In this we have used image processing algorithm. The data used are images are taken from the drone system. Our approach starts by seeing rows inside the area (or acre) and finding all the trees in a crop yield, by this knowing the size of plant in the crop can be easily to store the data of plants. Lately there has been a wide source of spatial photogrammetry available for agriculture. Most of this data gives new information about the crops. By analysis of crop statics and methods have not been widely performed due to limitations on the images and software involved. The classification was also validated by comparing dozens of trees in the field, with excellent results. The purpose of this paper is to provide farmers with a method for quickly and automatically classifying trees by size, regardless of the presence or absence of problems, so that they can more easily monitor the health of individual trees and gain a better grasp on how those trees are distributed across a given area. [ABSTRACT FROM AUTHOR]

The objective of this paper is to introduce a new current-mode precision full-wave rectifier configuration using a single inverted Z-copy current differencing buffered amplifier (IZC-CDBA) and two nMOSFETs. The unique feature of the proposed configuration is that it can produce simultaneously both the inverting and non-inverting rectified outputs without changing its architecture. The use of only active components makes the configuration more suited for IC implementation. Moreover, it features low input impedance and high output impedance, making it fully cascadable. In addition, the new design enjoys extremely high-frequency operations. The effects of non-ideal transfer gain and parasitic impedances on the designed circuit are also explored. The functionality of the proposed circuit is tested by PSPICE simulations for two distinct types of IZC-CDBA realization. The CMOS-based realization is checked through TSMC 0.18 µm level-7 technology parameters. The average DC current output, input dynamic range (± 450 µA), power consumption, temperature, total harmonic distortion (below – 30.2 dB), noise, and Monte-Carlo studies are performed to judge the efficiency level. The findings of the simulations match up nicely with the theoretical analysis. As an application of the suggested full-wave rectifier, RMS and average value computation for a sinusoidal signal is also provided. [ABSTRACT FROM AUTHOR]

In this paper a gesture control motorized skateboard is implemented. The operations like moving at constant speed, acceleration, regenerative breaking is performed by our model. The skateboard is controlled by gesture of hand in gloves via sensors. In recent decades skateboarding has expanded from recreation into a form of transportation. Skateboarders appear to use roadways much as other non-motorized modes do. The work is another leap in that direction where a simple, efficient and affordable way of transport for short-distance transportation has been developed. [ABSTRACT FROM AUTHOR]

Cervical cancer is a form of cancer that develops in the cells of the cervix, which links the uterus to the vagina. Cervical cancer can often be prevented by attending the cervical screening, which aims to find and treat changes to cells before they turn into cancer. Pap smear images are a more popular technique for screening cervical cancer. The nucleus and cytoplasm are present in the smear cell images. The spread of cancer is determined by the shape and structure of the nucleus. Thus, nucleus segmentation is an important step in cancer detection. However, overlapping, poor contrast, uneven staining, and other factors make cervical nucleus segmentation difficult. This paper proposes a new segmentation method for the cervical nucleus using digital image processing. In our proposed method, image processing techniques are employed to segment the nucleus. This method mainly compared the performance of using Red Green Blue (RGB) channels and Hue, Saturation, and Value (HSV). The best two channels from each two-colored image representation are compared, where the V channel is the best among H and S channels. On the other hand, G chancel is the best among the G and B channels. Therefore, the best two channels are compared, and the segmentation using the G channel is the best among all, with a sensitivity of 94.3%, specificity of 94.6% and precision of 88.3%. The main impact of this paper will be to assist doctors in diagnosing cervical cancer-based segmentation of the nucleus in Pap smear images. [ABSTRACT FROM AUTHOR]

Online shopping has become an alternative way for people in buying things, especially in the middle of the novel coronavirus (COVID-19) outbreak crisis. Besides, it is also making life easier. The problem with online shopping is when sometimes customer could not able to receive the goods when nobody at home. And it also involved safety considerations as in normal case, the good will be left outside the premises by the courier when the recipient not at home the good might be stolen. This paper aimed to design a Smart Home Package Mailbox to secure the delivery packages receive safely with good condition by reducing the problems occurring during the delivery. The Smart Home Package Mailbox is a hardware that operates by using the Quick Response (QR) code to communicate with its system. It has two compartments level which levels two for receiving package and level one for storing the received packages. Two main android applications have been developed to support the project system. The Smart Postman application is for the postman to open the mailbox door and update data in the database. While Smart Home Mailbox application is for users to track the delivery and receive notification. Once the sending package is put inside the mailbox, the sender and the recipient will be notified regarding the delivered package. This project is able to increase courier management efficiency as well as packages being delivered within expected time with good condition. [ABSTRACT FROM AUTHOR]

Minimization of the cost of generation for any utilities is crucial to ensure the utilities will be able to maintain continuous supply and their survivability. Non-optimal amount of power generated by all generating stations in a country will possibly lead to monetary loss and ineffective operation of the power system. Thus, a robust and reliable optimization technique is the prerequisite to ensuring the lowest cost of generation can be achieved. This paper proposes a hybridized optimization technique that integrates the element of evolutionary programming (EP) into the barnacle mating optimizer (BMO), termed Hybrid Evolutionary Programming-Barnacles Mating Optimization (HEBMO). HEBMO is utilized to address the convex economic dispatch in a power transmission system. Its implementation on the IEEE 30-Bus Reliability Test System (RTS) in addressing the convex ED is remarkable, through the comparison with the traditional EP and BMO. The cost of generations in chosen cases such as base case conditions, stress conditions due to real power, and reactive power increments revealed the superiority of the proposed HEBMO over EP and BMO. [ABSTRACT FROM AUTHOR]

Algorithms are increasingly being used and recognized for their ability to improve the performance of diagnostic tools such as contemporary electrocardiogram (ECG). For instance, evidence from previous studies reveals that QRS enhancement and detection algorithms have enabled the ECG device to measure and classify heartbeat more accurately. Based on the review of the previous works on QRS detection in ECG, this paper examines the key components of the ECG, QRS detection features, the different techniques used for developing QRS enhancement and detection algorithms as well as the criteria for evaluating their performance. [ABSTRACT FROM AUTHOR]

The use of filters in medical devices have not only expanded tremendously but they have also become an important part of the electrocardiography (ECG). Filters are considered essential to the ECG device because they enable the device to separate and restore its contaminated and distorted signals as well as enhance its performance. Based on the review of the previous works on filters, this paper provides insight into their nature and uses as well as examines several of the most common filtering techniques used in ECG. [ABSTRACT FROM AUTHOR]

Cervical cancer is a major cause of mortality among women worldwide, and early detection is crucial for successful treatment. However, the interpretation of cervical whole slice images can be challenging due to poor image quality. This paper presents a study on the use of histogram techniques to enhance the quality of cervical whole slice images. The aim of the study is to improve the visibility of important structures in the image, such as blood vessels and cell nuclei, for more accurate diagnosis and treatment of cervical cancer. The study used histogram equalization and stretching techniques to enhance the contrast and brightness of cervical whole slice images. Experiments were conducted to test the effectiveness of these techniques in improving the image quality. The results show that the enhanced images are of higher quality and are easier to interpret than the original images. The histogram equalization technique improved the visibility of structures in the image by increasing the contrast, while the histogram stretching technique improved the brightness and color balance. In conclusion, this study demonstrates the effectiveness of histogram techniques in enhancing the quality of cervical whole slice images for better diagnosis and treatment of cervical cancer. The use of these techniques can greatly improve the visibility of important structures in the image and lead to more accurate diagnosis and treatment. These findings can have important implications for the development of more effective screening and diagnostic methods for cervical cancer. [ABSTRACT FROM AUTHOR]

The number of new books that appear on the market makes it difficult for readers to find books that meet their needs and desires. There are many new books every year. Sometimes there are productions with the same or similar titles but with different authors or publishers. The content may be other, even though the title is identical. It may also happen that a similarly titled book is a sequel to an earlier one. Therefore, this paper will focus on a content-based book recommendation system. The book content used in the system is the book title. The system provides book recommendations with book titles that are the same or similar to the book selected by the user. The way the system works is to extract the book title feature with Term Frequency-Inverse Document Frequency (TF-IDF). Then, all book titles are compared with cosine similarity. There are two kinds of results from this book recommendation system. First, 20 books are similar to the book selected by the user, where the 20 books have a similarity level above 50%. Second, 20 books have a similarity level below 50%. Both types of results are offered to users to be selected according to their preferences. [ABSTRACT FROM AUTHOR]

Microservices architecture is a modern approach to software development that offers numerous benefits over traditional monolithic architecture, including increased agility, availability, and fault tolerance. However, migrating from a monolithic architecture to a microservices architecture, can be a complex and challenging process. This paper provides an overview of the key steps involved in migrating to a microservices architecture, as well as the four main metrics for estimating migration costs. By adhering to the suggested evaluation metrics while assessing the ten approaches, organizations can determine the most appropriate strategy for transitioning to a microservices architecture. This approach can harness the advantages of heightened agility, improve availability and enhance fault tolerance. Future research could focus on developing more sophisticated evaluation metrics and conducting case studies of successful microservices implementations. [ABSTRACT FROM AUTHOR]

One of the alternative applications of microwave photonics is hybrid Radio over Fiber (RoF) and Visible Light Communication (VLC) systems, which combines the advantages of radio frequency and optical communication together with wireless optical communication. In this paper, a hybrid radio over optical fiber and VLC system has been designed and simulated using OptiSystem Software by applying a Continuous Wave (CW) Laser at wavelength 1550 nm for optical fiber communication and 450 nm Visible Light LED for VLC system. The 8 Gbps of data was transmitted over 40 km of the fiber length and 3 m of VLC link with a Millimeter Wave (mmWave) frequency at 40 GHz. The proposed design system is analyzed based on the effect when varies the propagation distance for both fiber and VLC. The results show that as the number of fiber lengths increases, the BER performance is degraded until threshold limit 10−9. It is also shown that the proposed hybrid design system is working well even at a very high data rate of 8 Gbps for each user channel. The results also demonstrate that Non-Return Zero (NRZ) modulation technique has contributed to the better performance of the systems compared to Return Zero (RZ). [ABSTRACT FROM AUTHOR]

The use of behavioural biometrics, such as movement patterns and keystroke dynamics, in human identity recognition research to strengthen smartphone security is growing. Users usually secure their phones with a PIN or pattern. This paper uses a smartphone keystroke dynamic open dataset with user age information. This Open Dataset is known as the RHU-Keystroke Dynamics dataset. A dataset classification study was conducted utilising the Weighted K-nearest neighbour (W-KNN) method in order to identify the three age categories with the highest accuracy. The four keystroke features that have been collected in this open dataset are used for this classification. The highest average accuracy obtained from this W-KNN method is 83%. The results of the study are explained with a Confusion Matrix diagram and a Receiver Operating Characteristic (ROC) graph. A classification study using this method has successfully increased accuracy and can be utilized in the use of software, as demonstrated in the results of the study. It is expected that future studies will apply other classification methods to keystroke dynamics. [ABSTRACT FROM AUTHOR]

Behavioral biometric traits are not fully distinguished in recognition tasks, but they can improve the overall performance of biometric recognition systems by adding them. The behavioral biometric studied in this paper is related to keystroke dynamic. This paper examines the touch keystroke dynamics of computer users for the purpose of identifying their culture by using four different SVM kernels. It has been confirmed that racial classifications can be made by gathering keystroke data from 250 respondents representing various culture in Malaysia. Results show that different culture categories display different typing patterns. The classification is made using four SVM kernels and a comparison of the accuracy results is shown. The four kernels are Linear, Quadratic, Cubic and Fine Gaussian. The linear kernel has provided the highest accuracy and consistent readings compared to other kernels for the four features evaluated for dynamic keystrokes, namely press-press time, release-release time, press-release time and release-press time. The linear kernel has the highest accuracy reading of 92.4% for classification using press-press time features for the Malay vs Chinese category. [ABSTRACT FROM AUTHOR]

This work deals with the bulk density of differently shaped raw materials, considering recycled, shredded film, spheroidal shaped virgin bulk material and two different cylindrical shaped polypropylene pellets. The mass flow rate and the pressure buildup behavior of single screw extruders, which are frequently used for the recycling of polymers, are strongly influenced by the shape of the raw material. The differences mainly affect the solids conveying zone, where the external coefficient of friction and the bulk density in the screw channel largely influence the behavior. In single screw extrusion applications, higher bulk density usually leads to a higher mass flow rate and a better pressure build-up behavior. In this paper, the density of differently shaped bulk materials is analyzed in detail at high pressures and high temperatures comparable to the conditions existing during extrusion. Especially the density of shredded film was not investigated in detail till now. It is shown that the density of virgin material and the two different cylindrical shaped pellets behave in a similar way, while the shredded film differs from the others. [ABSTRACT FROM AUTHOR]

Pipes in heat exchanger systems are usually made of metallic materials to achieve a high level of thermal conductivity and thus high efficiency. However, substitution with polymer materials has a great potential. Plastics save weight, can be produced at lower cost and emissions, and are ideal for use in corrosive or chemically aggressive environments, where most metals fail. The challenge, however, is their much lower thermal conductivity in comparison. To reduce this disadvantage, fillers are used to transport thermal energy through the less conductive polymer matrix. In fact, high filler ratios are required to achieve an acceptable level of thermal conductivity for heat exchanger systems. However, these high filler ratios have a significant impact on the material properties of the polymer, such as the flexibility, which is drastically reduced. The result is a brittle material with limited suitability for use in heat exchanger systems. This paper describes a novel approach to effectively increase the thermal conductivity of polymer materials by optimizing the orientation of anisotropic filler particles by die design. Standard pipe extrusion dies result in continuous shear forces in the direction of extrusion. Accordingly, the resulting filler network has a higher thermal conductivity in the axial direction of the pipe than radially through the pipe wall. However, radial heat transfer is essential in pipe heat exchanger systems. To improve this, various die designs for targeted radial alignment of filler particles are discussed in this paper. Furthermore, the potential for improvement of the die designs is investigated. So far, the most efficient die design achieves an increase in thermal conductivity of up to 74 % compared to a standard pipe extrusion die. [ABSTRACT FROM AUTHOR]

The appearance of the interior and exterior of modern cars is characterized by a variety of chromed parts. Due to the lightweight construction requirements to reduce fuel consumption or to maximize the range of electric vehicles, the use of metallic parts is adversarial. Typically, these parts are injection molded parts made of ABS or PC/ABS and subsequently electroplated. If the requirements on mechanical properties increase, mineral-filled polyamide 6 (PA6) is often used. The particles and their distribution are primarily responsible for the surface quality of the electroplated parts. Unfortunately, the rejection rate of electroplated PA6 is up to 30 %. Therefore, in this paper, the particle distribution in the boundary layer was investigated for different operating points by performing computational fluid dynamics (CFD) simulations using ANSYS Fluent. The simulations were executed for a microscopic section in the boundary layer and the boundary conditions were derived from a macroscopic simulation assuming continuous material properties using Sigmasoft. Particle interactions were also set using the DEM-collision-model. Significant process parameters for the particle distribution in the surface layer were determined and correlated with surface parameters from real experiments. [ABSTRACT FROM AUTHOR]

At present, additive manufacturing with polymers already allows the economical production of components in individual pieces or small quantities with good application-specific properties and a high degree of individualization and complexity. However, additive manufacturing processes are still associated with many manual post-processing steps and thus high costs. Consequently, series applications for additively manufactured parts fail today in most cases due to the high process costs as well as the lack of quality assurance tools. For the economic use of additive series production, the above-mentioned hurdles must be overcome. In order to be able to investigate powder-based additive manufacturing processes comprehensively up to the depowdered component, the research institution Neue Materialien Bayreuth GmbH (Germany) is currently setting up a demonstration factory for selective laser sintering (SLS) with polymers. This article presents the concept of this unique research environment. The demonstration factory represents the entire processing chain including automated de-powdering, surface cleaning, part identification and inline quality assurance. All subcomponents are connected to a central IOT platform. In addition to the parts workflow, the closed powder circuit is also the subject of consideration. With detailed in-line and at-line analytics along the process chain, the entire SLS process can be evaluated, potential problems during processing can be identified, process stability can be improved, and part properties can be precisely assigned. This paper presents the relevant methods. End-to-end digitization enables a transparent visualization of all media and material flows as well as a part-related life cycle assessment. The research infrastructure described here offers the optimal prerequisites for the establishment of robust manufacturing strategies and thus an economical use of SLS technology for series components. [ABSTRACT FROM AUTHOR]

The increasing demand for energy-efficient methods for vulcanizing rubber extrudates requires the optimization and further development of existing vulcanization processes. Vulcanization by microwave irradiation makes it possible to introduce the energy required for heating directly into the material by means of dielectric losses. Microwave heating requires the polarity of the rubber compound so that the electromagnetic wave can vibrate the polar components in the compound. This oscillation results in internal friction, which leads to an increase in the temperature of the rubber compound. However, the polarity of rubber compounds is reduced due to corrosion protection, especially in the automotive sector. This requires optimization of the process parameters in the microwave crosslinking process. For this purpose, it is necessary to specifically adapt the setting variables of the electromagnetic wave as well as the geometry of the heating chamber to the different rubber compounds. The heating studies presented in this paper were performed with a solid-state microwave device using a nitrile butadiene rubber. The results show a material specific excitation frequency of the rubber compound in the range of 2436 MHz and 2478 MHz. In addition, investigations of the waveguide length of the microwave unit show that the geometry of the waveguide has a significant influence on the absorption behavior of the electromagnetic energy. In laboratory tests with optimized settings, 90% of the applied electromagnetic energy was converted into heat in the extrudate. In comparison, conventional processes such as hot air vulcanization have an efficiency of only 33%. In subsequent temperature tests of the extrudate surface, a temperature maximum was found in the center of the extrudate. This makes microwave technology an ideal complement to hot air vulcanization. [ABSTRACT FROM AUTHOR]

Gelling polymers, used for the fabrication of hydrogels, are employed for various applications in medical engineering. The present paper explores a novel approach for the additive manufacturing of polypropylene-hydrogel composites by applying laser-based powder bed fusion of powder blends at ambient temperatures, hence allowing for the integration of additives sensitive to heat degradation. Based on applying superposed fractal exposure strategies for the temporally and spatially discretized melting of prepared powder blends, the processing of composites containing a proportion of up to 75% of agarose can be demonstrated. Prepared specimens depict a water absorption exceeding 100 wt-% while exhibiting non-linear, progressive mechanical properties under compressive stress and enhanced stress relaxation similar to human cartilage tissue. The results illustrate the suitability of fractal exposure strategies for the processing of materials sensitive to heat degradation with divergent thermal properties. Furthermore, the proposed approach provides a novel process route for the fabrication of functionalized polymer components, representing a foundation for the integration of hydrogels for medical applications, such as drug delivery applications and functionalized, load-bearing scaffolds. [ABSTRACT FROM AUTHOR]

Natural rheologic balancing is being state-of-the-art in developing polymer melt channels for extrusion dies or hot runners in injection molding. For this, flow path lengths and channel diameters in a manifold system are defined identical on all paths and thus those channels are considered to be identical in pressure drop and cavity filling, respectively in mass flow distribution. However, the changes in direction of the melt flow due to the deflection of the melt are in most cases neglected but have a significant impact on the flow field in downstream components. Strong deflections, as they occur in conventional manifold systems, can be avoided by the use of additive manufacturing methods. However, the bionic design leads to curved melt channels which, when naturally balanced, may differ completely from one another regarding their overall course and curvature. Therefore, unequal mass flow distributions or cavity fillings occur in such geometries. The aim of this paper is to investigate the influence of channel curvature on the balancing of additively manufactured melt channels. For this purpose, a test specimen is designed and the curvature collectives along the neutral fibers are evaluated. The overall objective is a more specific balancing with respect to the mass flow distribution. The results indicate the necessity of considering the channels' curvature in the designing process in order to achieve a homogeneous melt distribution. [ABSTRACT FROM AUTHOR]

In plastics processing, polymers are plasticized so that they can be further processed into end products or semi-finished products in the extrusion process. On the way from the raw material or granulate to the end product, the polymer is processed at least once on screw machines. In order to achieve an increase in throughput while maintaining product quality, the extrusion process must be optimally designed. Since the construction and testing of prototypes is very costly and time-consuming, only empirical values and simulations remain as reference points for screw design. However, state-of-the-art simulations do not allow sufficiently accurate predictions of the expected product quality. Up to now, product and melt quality can only be determined in experimental investigations and as a function of various process properties such as pressure variations and degree of melting. In this paper, the cause-effect relationships are demonstrated experimentally for the first time in an extensive extrusion test program. Since good melt quality has a significant influence on product properties, suitable criteria for assessing and evaluating melt quality are first selected and verified by experimental investigations. In order to determine the influence of changes in the geometry of a screw design on melt quality, two different screw geometries of a barrier screw and a standard three-zone screw as well as the influence of two combinations of shear and mixing parts were investigated. Thermal and material homogeneity were used as criteria for melt quality. Based on this, the relationships between input and output parameters are described in an analytical model. The integration of the model into extrusion simulations then enables the prediction of the expected melt and product quality. [ABSTRACT FROM AUTHOR]

When growing plants, it is important to ensure good protection from weather conditions (hail, frost, wind...) and from animals (birds, insects, wild pigs...) to improve plant growth and increase production and quality. For this reason, plants are grown in covering systems (greenhouses) where covering materials play a major role. The covering material can be in the form of film and as such has an extremely low price, easy application, resistance to cracking and low weight. However, films also have certain disadvantages such as a shorter service life due to atmospheric influences, reduction of transparency and water vapor condensation. Regarding the tendency to use film for a longer time, this paper analyzes the effect of aging on the viscoelastic properties of polyethylene (PE) as well as ethylene tetrafluoroethylene (ETFE). Viscoelastic properties were analyzed using dynamic mechanical analysis (DMA). The film made of ethylene tetrafluoroethylene (ETFE) has better properties but is in a higher price range. [ABSTRACT FROM AUTHOR]

Decomposition of organic matter is sensitive to air flow, humidity and temperature, thus appropriate conditions are needed for effective composting which are achieved through a correct composter design. The paper focuses on a simulation analysis for the injection molding process of the bottom part of a composter. Contemporary injection molding machines require fine tuning to ensure successful mold filling and the attainment of satisfactory product quality. Addressing plastic product design from a manufacturing perspective helps ease challenges related to injection molding process and mold design. Process optimization commonly involves variables such as injection pressure, injection time, packing pressure, packing pressure holding time, melt temperature, mold cavity temperature and features of the cooling system. To ensure consistent product quality, it's crucial to optimize process parameters for specific cases due to substantial variability among injection molding input parameters. The use of Moldex3D software aids in identifying locations of critical values of defects, such as shrinkage and warpage. Warpage and shrinkage defects are minimized by Design of Experiments (DOE) optimization method. The results show that simulation, combined with optimization techniques, significantly improves product quality and process efficiency. Reducing warpage is achievable by extending the packing pressure time and using a lower coolant temperature. However, while extending the packing pressure time and reducing the melt temperature have a marginal effect on reducing shrinkage, higher cooling temperatures, as predicted, results in diminished shrinkage. [ABSTRACT FROM AUTHOR]

In blown film extrusion, spiral mandrel dies are the most common die design. This type of die assembly consists of three main components dividing the course of the melt into a 90° deflection, an n-fold star division and the spiral mandrel itself. Conventional manufacturing processes are used to manufacture the components. Therefore, shaping inside the die is usually limited to straight-line flow paths particularly in the area of the melt deflection and distribution. Partially, this leads to inhomogeneous flow patterns as fillets can only be integrated sparsely due to the limitations of the manufacturing technologies. The use of additive manufacturing, on the other hand, offers the possibility of realising channels that are freely routed between the inlet and outlet, resulting in a gentler melt deflection. In a previous research project, a blown film die assembly consisting of a primary and a secondary distribution was additively manufactured. Many advantages were achieved by the additive primary distribution alone through the free design of the melt channels. This paper introduces a new die design concept containing a retrofit solution for conventional spiral mandrel dies which substitutes the conventional primary distribution with an additively manufactured one. For this, the die design developed in the preceding project is adapted to replace the conventional primary distribution and can be combined with an existing spiral mandrel manufactured conventionally. As spiral mandrels are well established in the industry and as they are expensive components, they are retained. In this way, the advantages of both concepts, such as the gentle melt deflection and the avoidance of weld lines, are combined. Additionally, it was possible to achieve improvements in terms of residence time and purgeability. Further work needs to be done to adjust the designing process to remedy the deterioration in mass flow distribution. [ABSTRACT FROM AUTHOR]

While for several decades composites have been manufactured mainly from thermosets, such as epoxy- or polyester-based resins, a clear trend towards using thermoplastic matrix systems has recently emerged. Their reversible melting behavior gives them several advantages, including better recyclability and faster and more easily automated production. Increasing the productivity of thermoplastic composite manufacturing processes requires appropriate, reliable inline quality assurance systems. Optical coherence tomography (OCT), originally developed for biomedical applications, has been proven to be a powerful tool for non-destructive testing and characterization of unidirectional (UD) fiber-reinforced thermoplastic tapes made from glass fibers. Previous offline OCT measurements on a test rig demonstrated the reliability and robustness of the method in detecting visually apparent tape defects, such as gaps and fiber breakages and – one of the most critical bulk defects – insufficiently impregnated fiber regions. In this work, inline OCT measurements were performed on stationary Polycarbonate (PC)/glass fibers (GF) UD tapes in an industrial-scale production line. Systematic experimental analyses were carried out in which the OCT sensor was moved across the tape width, and the influences of (i) single scan sampling rate, (ii) single scan averaging, and (iii) sensor travel speed on measurement accuracy and data size were evaluated. Measurement accuracy was validated using optical microscopy. Optimal sensor settings were derived to improve the inline capability of the measurement approach under real production conditions. [ABSTRACT FROM AUTHOR]

The co-kneader is a single-screw extruder, which performs an oscillating motion in extrusion direction additionally to rotating. The four rows of kneading pins along the cylinder walls combined with the interrupted screw flights make a high mixing possible, while enabling gentle processing at manageable shear forces and exact temperature control. Although the co-kneader is used for a wide variety of material systems as polyvinylchloride or polyamide and especially for special applications in the industry, its process design is mainly based on experimental trials. Therefore, an analytical model which allows a description of polymer melting and flow in the kneader was developed by Rudloff et al. In this previous work satisfactory simulation results could be achieved when using a retaining ring at the end of the melting zone which causes material backlog. This enables to define the melting start at the begin of the first mixing element and to assume a fully filled melting zone as well as apply dispersed melting models. However, if the co-kneader is operated without a retaining ring, the pellets can pass through the melting zone and only plastic deformation occurs, until the melt film is formed further towards the die by heat conduction. In this paper, a first model approach of plastic energy dissipation (PED) for Co-Kneaders is developed to specify the start of melting more precisely for all configurations. In the model, the energy dissipation was formulated as a function of granulate geometry and weight, mechanical material parameters and degree of granulate deformation. This allows to extend the existing dispersive melting model to include the melting contribution from PED. [ABSTRACT FROM AUTHOR]

As the Internet of Things (IoT) becomes more widely used, the danger of information leakage, the danger of information leakage, data leakage and theft of the internet of things is continuous increasing, as the communication channel for data transfer is open to the public. A considerable portion of this data includes sensitive and personal information for the user and the company as well. Because of the openness, distributed nature, and lack of control over the entire IoT environment, the number of attack vectors for bad users is significant. End-users must trust the system for the IoT to become a viable service platform. Consequently, in critical infrastructures like smart home, smart city, smart healthcare, and smart industry, information security and privacy are the major concern in the Internet of Things. In this paper, we present an information concealment strategy using steganography to protect communication in critical IoT infrastructure. RGB photographs are employed as the information carrier. Deep layers of low-distortion image channels in the least significant bit (LSB) are used to hide the data to be used as a data marker. Both mathematically and experimentally, we evaluate our method. We display mathematically that the striker's analysis cannot expect the current information. The proposed strategy outperformed previous strategies in terms of imperceptibility and capacity, as well as resilience to steganalysis attacks like histogram analysis, as demonstrated experimentally. [ABSTRACT FROM AUTHOR]

DeepFake, DeepFake detection, and face detection technologies have a strong relationship. DeepFake techniques have become a serious threat to celebrities, the general public, and the judiciary, which relies on visual media as evidence in criminal cases. DeepFake detection methods are responsible for detecting DeepFake through a series of procedures, the first and most significant of which is face detection. Note that face detection approaches are used in several methods to detect faces in photos, including those in DeepFake generating and DeepFake detection. Hence, the first part of this paper describes the concept of face detection and three of its tools, two of which are frequently utilized in DeepFake detection (Multi-Task Cascaded Convolutional Networks (MTCNN) and Dlib). MediaPipe has not yet been employed in this field to study and evaluate the performance of these tools through a practical comparison. Consequently, a group of modern DeepFake detection methods proposes a new taxonomy based on extracting the features utilized in each. Lastly, datasets of photos from DeepFake detection experiments were used to determine which one posed a genuine challenge to the three tools. The results presented that the MediaPipe tool is the best in accuracy, 99.3%, and the dataset Open Forensic (OF) is the most challenging due to the many mistakes generated when its works on it. [ABSTRACT FROM AUTHOR]

This paper discussed the transmission dynamics of discrete SEIR model. It is possible to determine the prerequisites for the endemic and disease-free equilibria, as well as their local stability. In addition to demonstrating the validity of our findings, the numerical simulations also display more sophisticated dynamical characteristics such as the chaos phenomena, flip bifurcation, and Hopf bifurcation. These findings demonstrate that, as compared to models for both continuous and discrete epidemics exhibits far richer dynamical features. [ABSTRACT FROM AUTHOR]

In this paper, we study certain kinds of bi-derivations, giving describe and constitution of the notions of bi-centralizer on a prime Г-ring. Another results also are obtained for a bi-(centralizer, revers centralizer) and Jordan bi-(centralizer, revers centralizer) on a Г-ring 퓝 = 퓡 × 퓡 concerning with a prime Г-ring 퓡. The concepts of left (resp. right) bi-(centralizer, revers centralizer), Jordan left (resp. right) bi-(centralizer, revers centralizer) and left (resp. right) triple bi-(centralizer, revers centralizer) on a Г-ring 퓝 are introduced. We also investigate condition, if 퓡 is a 2-torsion free ring, then every Jordan left bi-(centralizer, revers centralizer) on 퓝 is left Bi-(centralizer, revers centralizer). [ABSTRACT FROM AUTHOR]

Let R be a commutative ring with 1 and F be a left unitary R-module. In this paper, we give a generalization for the notions of compressible (retractable) Modules. We study Semi-T-Small Compressible Modules and Semi-T-Small Retractable Modules. We give some of their advantages, properties, characterizations and example. We moreover study the relation between them and some classes of modules. [ABSTRACT FROM AUTHOR]

Adaptive Cruise Control (ACC) systems are widely used in modern vehicles to enhance driving comfort and safety. The design of an effective controller for ACC is crucial for achieving smooth and efficient vehicle following behavior. In this paper, the mathematical model of the normal linear system and the adaptive cruise control system (ACCS) of the electric vehicle (EV) are developed. Consequently, these systems are simulated using Matlab to analyze the output responses of the system before being controlled. Additionally, the proportional-integral-Derivative (PID) control is designed to compensate for the performance of the developed EV systems to get a better response. After that, a new optimization method is applied to tune the PID controller parameters known as "electric charged particle optimization" (ECPO). Additionally, the simulated outcomes for both PID-controlled systems are displayed in the result section. The effectiveness of the suggested controller and the new optimization method are then compared. Additionally, using the reference input, the tracking of the ACC electric car system has been achieved at 98%. [ABSTRACT FROM AUTHOR]

The aim of this paper is to design neural network (NN) for solving the singular perturbation problems of partial differential equations. The modified neuro system (MNS1) using a polynomial of second degree to replace each component in the training set. The foundament of this process is to variation each x in the input vector training set x → = (x1, x2, ..., xn), xj∈[a, b] the polynomial ξ (x) = λ 2 (x 2 + x + 1) , λ ∈(a, b). We were able to determine the appropriate value within a certain range, which has a significant impact on the accuracy of the solution. Our numerical results showed that (MNS1) method is better and more accuracy, of course, the main reason for this point connected with the chosen value of λ. Finally, the method of updating the neural network was clarified through the numerical results, which were compared to traditional methods, and through which we proved the accuracy of the solution and the rapidity of convergence. [ABSTRACT FROM AUTHOR]

This paper presents a photovoltaic device model of perovskite materials with (p-i-n) configuration for numerical simulation using the Solar Cell Capacitance Simulator (SCAPS) package software. The PV research community can use SCAPS, a thin film solar cell numerical device simulator, free of cost. This study illustrates the ideal behaviour of different thicknesses of polycrystalline thin film perovskite solar cells. To fabricate perovskite solar cells with high efficiency and reasonable material parameter selection, this simulation study will be helpful. The P-type layer is made of hole transport materials, HTM, as a Poly(3-hexylthiophene-2,5-diyl) polymer, P3HT, and the intrinsic layer is CH3NH3PbI3 perovskite and the n-type layer is composed of two layers of ZnO1.5-x /PCBMx, Zink oxide(ZnO), and [6,6]-Phenyl-C61 butyric acid methyl ester (PCBM), respectively, where x is the thickness of the PCBM. The performance parameters of solar cells, capacitance, conductance and impedance were studied under variable thickness (x=0, 0.3, 0.6, 0.9, 1.2, 1.5) µm with fixation of the parameters and other conditions in the simulation calculation process. The best performance of the solar cell in the simulation models was obtained when the electron transport materials, ETM, layer was composed of ZnO only, x=0 µm, under solar radiation intensity of 1000 W/m2. [ABSTRACT FROM AUTHOR]

Within the last twenty years, the world has witnessed a data explosion, and Arabic is the world's fifth most used textual communication language. The main challenge for document classification is a lack of label information; unstructured textual data is available everywhere. It is obvious that human label assignment is time-consuming and labor-intensive. Automated processes alone cannot assign class labels to a large number of texts while simultaneously updating the classification model. However, in scenarios with a few labeled examples and a large number of unlabeled examples, semi-supervised machine learning (SSL) can significantly enhance performance. SSL combines labeled and unlabeled data to build a more accurate classification model. Any supervised algorithm can be quickly adapted to use an SSL approach using a self-learning algorithm. As SSL in this paper, this work converted seven traditional classifiers from supervised behavior into a semi-supervised one; moreover, it contributed the use of the co-training algorithm on Arabic text, again using the seven classifiers, it used two different views rather than dividing one view into two views, each view being used to train the cooperating classifier. To increase the reliability of our work, experiments have been done on three reliable global datasets (SANAD, OSAC, and CNN). The results have been calculated for precision, recall, F-Score, and accuracy, the performance reached more than 97%. [ABSTRACT FROM AUTHOR]

In this paper, the effects of deleting and addition an edge from the graph G is studied on the even some domination number Yes(G). These effects are discussed when the removed and addition edge is incident on two vertices both of them belong to the even some dominating set V-D or D or on vertex in D and the other in V-D. [ABSTRACT FROM AUTHOR]

Demand-side management (DSM) is an effectual approach by coordinating utility management and routinely tracking energy usage, the intelligent grid assists in controlling energy demand and promotes its efficiency. However, the paper aims to utilize Linear programming optimization algorithms as an effective tool for managing energy demand and maximizing the use of renewable energy sources. These algorithms are able to estimate which is the best utilization of what resources are accessible and reduce consumption by describing the energy system as a collection of linear equations. The optimization system makes assumptions about the various energy costs when it will be high or low and modifies energy use accordingly. We applied different scenarios to assess the resiliency of the system. The simulation took into account a number of variables, including the weather, energy usage, and pricing fluctuations. MATLAB R2023a and Simulink provide an integrated platform with data analytics to build the proposed system and optimization model to minimize cost in MATLAB. Compared to other methods using various optimization algorithms as the binary orientation search algorithm (BOSA), cockroach swarm optimization (CSO), and the sparrow search algorithm (SSA) were applied to DSM methodology for a residential community with a primary focus on decreasing peak energy consumption results as in previous study was, BOSA has a lower standard deviation (0.8) compared to the other algorithms (1.7 for SSA and 1.3 for CSOA), making it more robust and superior, in addition to minimizing cost (5438.98 cents of USD (mean value) and 16.3% savings), the suggested approach is used for lowering electrical energy costs in a micro-grid system while maintaining their regular load and operating hours. [ABSTRACT FROM AUTHOR]

This paper investigates the Nelder-Mead, Powell, and Differential Evolution algorithms in the optimization of a multidimensional optimization problem. Actually, this type of the problem is difficult to solve since the objective function mixes quadratic terms and trigonometric functions. Optimization techniques were use; the ideal values for the design variables that minimize the objective function i discovered. Using 3D surface plots, contour plots, convergence rate plots, and fitness landscape plots, the optimization process made visible. The outcomes show how each algorithm works and behaves in terms of convergence, giving information about both how well it performs and how the objective function is distributed. The results add to our understanding of optimization strategies and offer suggestions for choosing the best algorithms for situations with similar complexity in optimization. Finally, the numerical optimization approach has been implemented by Python language. [ABSTRACT FROM AUTHOR]

At present, detection and recognition of animals remain a complicated task and no distinctive technique can solve all situations strongly and effectively. Animal detection in images is challenging because of the complexity of wild environments. Including several different things: The large differences in shapes and color appearances of variations of objects which belong to the same class, and Lighting/Illumination Conditions. This paper presents an effective and efficient animal detection system for Birds detection in images. MobileNet SSD model is a Single Shot Multibox Detection (SSD) suggested in this work, which is capable of handling different shapes and view angles of the objects. This approach allows extracting features of image regions and using deep learning techniques for classifying regions into two categories: (bird and non-animal). The experimental results demonstrated the efficiency of classification and detection of single and multi-animals even in difficult environmental conditions. The accuracy of detection and classification is up to 98.8%. This methodology is more accurate than other similar approaches. This paper exhibits a method for training a convolutional neural network (CNN) based on object detection classifiers. [ABSTRACT FROM AUTHOR]

Abstract. In this paper, a prey, predator and apex predator food 4chain model4 is proposed and analyzed. The model includes the impact of fear on solution dynamics. All feeding processes in this ecological model are formulated in terms of Crowley-Martin-like functional responses. The primary goal of this work is to find the existence condition, uniqueness and boundedness of the solution. The second goal is to study the local and global stability of these solutions. Finally, the analysis results are verified by numerical simulation. [ABSTRACT FROM AUTHOR]

The convoluted and dynamic nature of cancer growth makes it difficult to predict long-term cancer survival. Evolutionary deep learning techniques have been growing in popularity as efficient and accurate prediction techniques in recent years. Long-term cancer survival prediction has been developed to utilize evolutionary deep-learning techniques. This research combines the power of evolutionary algorithms using Particle Swarm Optimization (PSO) with some deep learning techniques to improve the performance and accuracy of the deep learning models by optimizing its parameters and minimizing the error between the predicted and actual outputs. Overall, combining evolutionary algorithms with deep learning models for cancer survival analysis prediction demonstrates the potential to significantly improve the accuracy and efficiency of cancer survival predictions, leading to better treatment decisions and improved patient outcomes. This paper uses the gbsg2 survival analysis dataset, a well-known dataset commonly used in survival analysis studies. [ABSTRACT FROM AUTHOR]

The primary goal of this paper is to introduce and investigate a novel subclass of analytic functions in the open unit disk by generalizing the Srivastava-Attiya operator. So by using the generalization we have introduced a subclass of analytic function with negative coefficients in the unit disk. We have referred to the previous studies that used the Sirvastava-Attiya operator and generalized it, explained the functions of the class 퓐 and the basic definitions that included this paper. We used some important lemmas from previous studies to prove our results, and we obtained some important geometric properties of the analytical functions. We proved the theorem of growth and destortion, and we showed the cofficient bound, extreme points of the functions in this class, in addition to the radii of the starlike, convex and close-to-convex functions of order 휑. Finally, we defined the 훼 −neighborhood and showed the relationship between the functions that belong to the class S ⌣ λ p , μ q , t s , a , λ (γ , ρ , l , σ) and the functions that belong to the class S ⌣ λ p , μ q , t s , a , λ , ω (γ , ρ , l , σ). [ABSTRACT FROM AUTHOR]