Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions

Predicting crime using machine learning and deep learning techniques has gained considerable attention from researchers in recent years, focusing on identifying patterns and trends in crime occurrences. This review paper examines over 150 articles to explore the various machine learning and deep learning algorithms applied to predict crime. The study provides access to the datasets used for crime prediction by researchers and analyzes prominent approaches applied in machine learning and deep learning algorithms to predict crime, offering insights into different trends and factors related to criminal activities. Additionally, the paper highlights potential gaps and future directions that can enhance the accuracy of crime prediction. Finally, the comprehensive overview of research discussed in this paper on crime prediction using machine learning and deep learning approaches serves as a valuable reference for researchers in this field. By gaining a deeper understanding of crime prediction techniques, law enforcement agencies can develop strategies to prevent and respond to criminal activities more effectively.Comment: 35 Pages, 6 tables and 11 figures. Consists of Dataset links used for crime prediction. Review Pape

Advances in Cybercrime Prediction: A Survey of Machine, Deep, Transfer, and Adaptive Learning Techniques

Cybercrime is a growing threat to organizations and individuals worldwide, with criminals using increasingly sophisticated techniques to breach security systems and steal sensitive data. In recent years, machine learning, deep learning, and transfer learning techniques have emerged as promising tools for predicting cybercrime and preventing it before it occurs. This paper aims to provide a comprehensive survey of the latest advancements in cybercrime prediction using above mentioned techniques, highlighting the latest research related to each approach. For this purpose, we reviewed more than 150 research articles and discussed around 50 most recent and relevant research articles. We start the review by discussing some common methods used by cyber criminals and then focus on the latest machine learning techniques and deep learning techniques, such as recurrent and convolutional neural networks, which were effective in detecting anomalous behavior and identifying potential threats. We also discuss transfer learning, which allows models trained on one dataset to be adapted for use on another dataset, and then focus on active and reinforcement Learning as part of early-stage algorithmic research in cybercrime prediction. Finally, we discuss critical innovations, research gaps, and future research opportunities in Cybercrime prediction. Overall, this paper presents a holistic view of cutting-edge developments in cybercrime prediction, shedding light on the strengths and limitations of each method and equipping researchers and practitioners with essential insights, publicly available datasets, and resources necessary to develop efficient cybercrime prediction systems.Comment: 27 Pages, 6 Figures, 4 Table

Micro-Acoustic-Trap (µAT) for microparticle assembly in 3D

Acoustic tweezers facilitate the manipulation of objects using sound waves. With the current state of the technology one can only control mobility for a single or few microparticles. This article presents a state of the art system where an Acoustic Lens was used for developing a Micro-Acoustic Trap for microparticle assembly in 3D. The model particles, 2 µm diameter polystyrene beads in suspension, were driven via acoustic pressure to form a monolayer at wavelength-defined distances above the substrate defined by the focal point of an Acoustic Lens The transducer was driven at 89 MHz, mixed with 100 ms pulses at a repetition rate of 2 Hz. Beyond a threshold drive amplitude sufficient to overcome Brownian motion, this led to 2D assembly of the microparticles into close-packed rafts >80 µm across (∼5 wavelengths of the carrier wave and >40 particles across). This methodology was further extended to manipulation of live Dictyostelium discoideum amoebae. This approach therefore offers maneuverability in controlling or assembling micrometer-scale objects using continuous or pulsed focused acoustic radiation pressure

Development and Characterization of Core Shell Nanoparticle for Enhanced Drug Delivery to Treat Solid Tumor: Preparation and In-Vitro Assessment

Mortalities from cancer in the world are projected to continue rising, with an estimated 9 million and 11.4 million people dying from cancer in 2015 and 2030, respectively. Rates are rising as more people live to an old age and as mass lifestyle changes occur in the developing world. With present treating regimen for cancer, dose-limited toxicity is a big reason that reduces the efficacy of cancer treatments. In search for more effective cancer treatments, nanosized drug delivery systems, those are capable of delivering their drug payload selectively to cancer cells such as nanoparticles, solid lipid nanoparticles, liposomes are among the most promising approaches. Core shell nanoparticles are one of the investigated moieties in recent years that are seeking much attention nowadays for biomedical applications including the field of oncology.The present work aims at developing a core shell nanoparticle comprising Poly (D, L –lactide –co –glycolide) (PLGA) core and polyethyleneimine (PEI) shell loaded with anticancer bioactive docetaxel (DTX) for passive targeting of the tumor tissue. It is expected that incorporation of PEI will improve the uptake and subsequent release of the drug in the cytosol due to endosomal escape phenomenon. Keywords: Solid tumor; nanotechnology; nanoparticle; PLG

Assessing Systematic Blade Production in the Indian Subcontinent with Special Reference to Eastern Gujarat

Blades as a component of lithic assemblages hold significant importance to understanding the more recent part of human evolution, particularly with regard to the emergence and adaptations of Homo sapiens. The systematic production of elongated stone blanks provides several advantages, including a longer cutting edge and high efficiency in raw material utility. However, the reasons behind the development of these technological forms and the chronological patterns of systematic blade production remain poorly understood in many regions, despite a clear overall intensification in the Late Pleistocene. The South Asian Paleolithic archive is full of blade-bearing assemblages, most of which are defined as Upper Paleolithic or Late Paleolithic. However, many of these previously assumed ‘Upper Paleolithic’ tool components prominently appear in Middle Paleolithic contexts. Here, we discuss some of the most recent case studies of blade-bearing assemblages from Eastern Gujarat that show an in situ emergence of blade technology from advanced Middle Paleolithic technology, suggesting localized origins of blade technology

Schematic representation of the interaction geometry of a colloidal probe with a nano-rough surface.

<p>Red upper line: plane of first-contact, defined by the protruding asperities; orange bottom line: mid-plane, or average plane of charges. The distance between the two planes is approximately equal to R_q.</p