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This paper talks about Hexabot, an Internet of Things (IoT) enabled surveillance robot. Hexabot has a height of 50 cm and a width of 40*40. Its goal is to integrate sensing, communication and computing capabilities to enable it to perform surveillance tasks in both indoors and outdoors environments. Hexabot leverages the capabilities of sensors, wireless communication, and embedded systems to provide an affordable, reliable, and versatile surveillance solution. Hexabot is designed to detect, recognize and track objects, measure environmental parameters, and navigate autonomously. This paper presents the design and implementation of Hexabot and its components. Additionally, an experimental evaluation of the robot's performance is presented. The results demonstrate that Hexabot is a reliable and cost-effective surveillance robot with the potential to become an invaluable asset for various surveillance applications. [ABSTRACT FROM AUTHOR]

As per the United Nations World Water Development Report of 2018, approximately 6 billion people will be impacted by clean water scarcity by 2050. Due to the rise in population, several parts of the world experience water crises as their groundwater table levels are decreased. In addition to this, wasting water through unwanted usage has become one of the habitual activities of the human population. To resolve this issue, an intelligent solution is proposed using water metering in this paper. A novel approach to performing automated water-metering by providing the water inlet and outlet information from the locality to the Water Distribution Board (WDB) is proposed in this paper. This smart metering method is distinct from currently available commercial models with a simple hardware setup for water inlet and outlet measurement and a mobile application. The proposed scheme significantly decreases overhead expenses on the water distribution board in handling water meter readings and billing water consumption. This scheme aims to make the consumers conserve water and become active participants in the water management system. This also helps in minimizing the unwanted use of water either from the corporation or from borewells at their localities and thus gives a great lead to water conservation and saving the lives of the future generation. [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]

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]

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 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]

This paper explores the application of a hybrid compression approach using the Tap97-Wavelet transform, Short Discrete Cosine Transform (DCT), and an advanced entropy encoder, specifically the BZIP2 algorithm, to compress speech audio signals. The study aims to investigate the effectiveness and performance of this compression technique in achieving high compression ratios while maintaining acceptable audio quality. This Paper focuses on the control parameters: parameters of quantization step, Sampling rate, the number of passes of the wavelet transform, and the number of blocks in the pre-Discrete Cosine Transform (DCT) stage. These parameters play a crucial role in audio signal processing and compression techniques. Performance evaluation metrics, including compression ratio, peak signal-to-noise ratio (PSNR), Mean Squared Error (MSE) and Mean Absolute Error (MAE) assess the effectiveness and efficiency of this approach, moreover the time of compression was also studied to evaluate the speed of performance in terms of time. The findings of this Paper contribute to the understanding of utilizing hybrid compression approaches for speech audio signals, providing insights into their effectiveness and potential applications in speech processing and transmission systems. [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]

Cybercrime has been on a massive increase for several years. As more individuals conduct business and live their lives online, more criminals are turning to the internet to steal. With the developments in cybersecurity, adoption of best practices, cybersecurity awareness initiatives, and increased regulations and partnerships between businesses and governments to resolve the problems, cybercriminals may be feeling the pressure. In this paper, we are going to predict operating system vulnerabilities using machine learning algorithms. And evaluate their accuracies through training them. The aim of the paper is to use Machine Learning algorithms to predict with accuracy operating systems vulnerabilities. Different ML algorithms have been analyzed, such as Logistic Regression, Support Vector Machine and Random Forest. And, out of all of these algorithms, Random Forest had the highest accuracy of 99.33%. [ABSTRACT FROM AUTHOR]

The paper considers issues related to the theoretical study of electromagnetic phenomena in a certain stationary coordinate system in various variations. The use of electromagnetic force, controlled, easy to handle, which is applicable in a wide variety of sites and devices. The main attention is directed to the analysis of a number of phenomena from the simplest electrical moments, and also in a more complex understanding are presented as the forces of the most powerful attraction, expressed as a very topical issue. It is these aspects that are considered in this study. Of course, the image of such a performance is precisely the electromagnetic design, the physics of which is built from the initial ideas about electromagnetism. The developed theoretical framework is also used to analyze a large number of phenomena, each of which requires its own analysis in all parameters. The description of the algorithm created at the moment is given in this paper. [ABSTRACT FROM AUTHOR]