Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

     The healthcare sector has traditionally been an early adopter of technological progress, gaining significant advantages, particularly in machine learning applications such as disease prediction. One of the most important diseases is stroke. Early detection of a brain stroke is exceptionally critical to saving human lives. A brain stroke is a condition that happens when the blood flow to the brain is disturbed or reduced, leading brain cells to die and resulting in impairment or death. Furthermore, the World Health Organization (WHO) classifies brain stroke as the world's second-deadliest disease. Brain stroke is still an essential factor in the healthcare sector. Controlling the risk of a brain stroke is important for the surviv

A flexible pavement structure usually comprises more than one asphalt layer, with varying thicknesses and properties, in order to carry the traffic smoothly and safely. It is easy to characterize each asphalt layer with different tests to give a full description of that layer; however, the performance of the whole; asphalt structure needs to be properly understood. Typically, pavement analysis is carried out using multi-layer linear elastic assumptions, via equations and computer programs such as KENPAVE, BISAR, etc. These types of analysis give the response parameters including stress, strain, and deflection at any point under the wheel load. This paper aims to estimate the equivalent Resilient Modulus (MR) of the asphalt concrete

In this paper a new technique based on dynamic stream cipher algorithm is introduced. The mathematical model of dynamic stream cipher algorithm is based on the idea of changing the structure of the combined Linear Feedback Shift Registers (LFSR's) with each change in basic and message keys to get more complicated encryption algorithm, and this is done by use a bank of LFSR's stored in protected file and we select a collection of LFSR's randomly that are used in algorithm to generate the encryption (decryption) key.

We implement Basic Efficient Criteria on the suggested Key Generator (KG) to test the output key results. The results of applying BEC prove the robustness and efficiency of the proposed stream cipher cryptosystem.

The ground state densities of unstable proton-rich 9C, 12N and 23Al exotic nuclei are studied via the framework of the two-frequency shell model (TFSM) and the binary cluster model (BCM). In TFSM, the single particle harmonic oscillator wave functions are used with two different oscillator size parameters βc and βv, where the former is for the core (inner) orbits and the latter is for the valence (halo) orbits. In BCM, the internal densities of the clusters are described by single particle Gaussian wave functions. The long tail performance is clearly noticed in the calculated proton and matter density distributions of these nuclei. The structure of the valence proton in 9C and 12N is a pure (1p1/2) configuration while that for 23Al is

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

In this paper, we obtain a complete characterization for the norm and the minimum norm attainment sets of bounded linear operators on a real Banach spaces at a vector in the unit sphere, using approximate 𝜖-Birkhoff-James orthogonality techniques. As an application of the results, we obtained a useful characterization of
bounded linear operators on a real Banach spaces. Also, using approximate 𝜖-Birkhoff -James orthogonality proved that a Banach space is a reflexive if and only if for any closed hyperspace of , there exists a rank one linear operator such that , for some vectors in and such that 𝜖 .Mathematics subject classification (2010): 46B20, 46B04, 47L05.

Highly plastic soils exhibit unfavorited properties upon saturation, which produce different defects in engineering structures. Attempts were made by researchers to proffer solutions to these defects by experimenting in practical ways. This included various materials that could possibly improve the soil engineering properties and reduce environmental hazards. This paper investigates the strength behavior of highly plastic clay stabilized with brick dust. The brick dust contents were 10%, 20%, and 30% by dry weight of soil. A series of linear shrinkage and unconfined compression tests were carried out to study the effect of brick dust on the quantitative amount of shrinkage experienced by highly plastic clay and the undra

Recently there has been an urgent need to identify the ages from their personal pictures and to be used in the field of security of personal and biometric, interaction between human and computer, security of information, law enforcement. However, in spite of advances in age estimation, it stills a difficult problem. This is because the face old age process is determined not only by radical factors, e.g. genetic factors, but also by external factors, e.g. lifestyle, expression, and environment. This paper utilized machine learning technique to intelligent age estimation from facial images using support vector machine (SVM) on FG_NET dataset. The proposed work consists of three phases: the first phase is image preprocessing include four st

Background: Chronic obstructive pulmonary disease causes permanent morbidity, premature mortality and great burden to the healthcare system. Smoking is it's most common risk factor and Spirometry is for diagnosing COPD and monitoring its progression.

Objectives: Early detection of chronic obstructive pulmonary disease in symptomatic smokers’ ≥ 40years by spirometry.

Methods: A cross sectional study on all symptomatic smokers aged ≥ 40 years attending ten PHCCs in Baghdad Alkarkh and Alrisafa. Those whose FEV1/FVC was <70% on spirometry; after giving bronchodilator, were considered COPD +ve.

Results:  Overall, airway obstruction was seen in