A STUDY OF CRIMINAL BEHAVIOUR (CAUSALITY & PREVENTION OF CRIME)

This research is set out to carefully analyze the psyche of the criminals and to identify commonality in their behaviour irrespective of the demographic aspect. The research aims at analyzing criminal law theories and their practical usage in the modern scenario. Crime is defined as an act of deviance from socially accepted norms translated as criminal code. Countries all around the world have a definite set of criminal code compromising principles of morality and ethics as per their unique culture and society. But in practicality, these principles have failed to culminate the desired result of prevention of crime upon implementation by the traditional methods of enforcement. Deviance relates to the subjectivity of society. Considering morality as a subjective aspect would propagate deviance among individuals formed out of different circumstances than the majority. Hence, crime is often committed by the minority upon the majority in a society. The ultimate aim of the research is to identify the principle of causality in relation to crime and eventually portraying an effective approach for the prevention of crime

Facile synthesis of mesoporous N doped zirconium titanium mixed oxide nanomaterial with enhanced photocatalytic activity under visible light

The present paper deals with a hydrazine mediated synthesis of high surface area and thermally stable N-doped zirconium titanium mixed oxide with enhanced photocatalytic activity towards reduction of selenium (VI) to metallic Se0 under visible light. Materials were synthesized at pH ¼ 2 by varying the hydrazine concentration and characterized by XRD, TEM, BET method, XPS, Raman spectroscopy and UV-vis solid state spectra. Presence of low amount of zirconium oxide (10 wt%) helps in phase stabilization and maintains the porous structure even at higher calcinations temperature in comparison to that of pure titania. XPS spectrum justifies the presence of nitrogen and Ti3+ in the material due to the decomposition reaction of hydrazine. Hydrazine controls the nitrogen content, surface area and the formation of oxygen vacancy in the material. Investigation of metal oxide to hydrazine ratio on the overall surface properties and photocatalytic activity indicates that the 1 : 6 ratio is the optimum composition for the best result. Surface area and pore volume increases to 298 m2/g and 0.323 cm3/g. The obtained material (TiZr-6N-400) is found to reduce selenium (VI) to selenium (0) under visible light within only 45 min of reaction. Increased photocatalytic activity under visible light is mostly due to the synergistic effect of substantial nitrogen doping, high surface area and presence of oxygen vacancy

Machine Learning Methods for detection of bystanders: A Survey

The number of users on social media networks is increasing day by day as their popularity increases. The users are sharing their photos, videos, daily life, experiences, views, and status updates on different social networking sites. Social networking sites give great possibilities for young people to interact with others, but they also make them more subject to unpleasant phenomena such as online harassment and abusive language, which leads to cyberbullying. Cyberbullying is a prevalent social problem that inflicts detrimental consequences to the health and safety of victims such as psychological distress, anti-social behavior, and suicide. To minimize the impact of Cyberbullying, the Bystander role is very important. In this paper, a review of the cyberbullying content on the Internet, the classification of cyberbullying categories, classifying author roles (harasser, victim, bystander-defender, bystander-assistant), data sources containing cyberbullying data for research, and machine learning techniques for cyberbullying detection are overviewed.&nbsp

Analysis of a Compact Squeeze Film Damper with Magneto Rheological Fluid

Rotor systems play vital role in many modern day machinery such as turbines, pumps, aeroengines, gyroscopes, to name a few. Due to unavoidable unbalance in the rotor systems, there are lateral and torsional vibrations. Ignoring these effects may cause the system serious damages, which sometimes lead to catastrophic failures. Vibration level in rotor systems is acceptable within a range. Focus in this work is to minimize the vibration level to the acceptable range. One of the ways vibration level can be minimised is by means of providing damping. To accomplish this task in this work a new concept squeeze film damper is made by electro discharge machining which is compact in configuration, is filled with magneto-rheological (MR) fluid and tested out on one support of a Jeffcott rotor. This compact squeeze film damper (SFD) produces damping in a compact volume of the device compared to a conventional SFD. MR fluid is a smart fluid, for which apparent viscosity changes with the application of external magnetic field. This compact damper with MR fluid provides the variable damping force, controlled by an external magnetic field. In this work, proportional controller has been used for providing the control feedback. This MR damper is seen to reduce vibrations in steady state and transient input to the Jeffcott rotor. Parametric study for important design parameters has been done with the help of the simulation model. These controlled dampers can be used for reducing vibrations under different operating conditions and also crossing critical speed

Named Entity Recognition in Indian court judgments

Identification of named entities from legal texts is an essential building block for developing other legal Artificial Intelligence applications. Named Entities in legal texts are slightly different and more fine-grained than commonly used named entities like Person, Organization, Location etc. In this paper, we introduce a new corpus of 46545 annotated legal named entities mapped to 14 legal entity types. The Baseline model for extracting legal named entities from judgment text is also developed.Comment: to be published in NLLP 2022 Workshop at EMNL

Corpus for Automatic Structuring of Legal Documents

In populous countries, pending legal cases have been growing exponentially. There is a need for developing techniques for processing and organizing legal documents. In this paper, we introduce a new corpus for structuring legal documents. In particular, we introduce a corpus of legal judgment documents in English that are segmented into topical and coherent parts. Each of these parts is annotated with a label coming from a list of pre-defined Rhetorical Roles. We develop baseline models for automatically predicting rhetorical roles in a legal document based on the annotated corpus. Further, we show the application of rhetorical roles to improve performance on the tasks of summarization and legal judgment prediction. We release the corpus and baseline model code along with the paper.Comment: Accepted at LREC 2022, 10 Pages (8 page main paper + 2 page references

SemEval 2023 Task 6: LegalEval -- Understanding Legal Texts

In populous countries, pending legal cases have been growing exponentially. There is a need for developing NLP-based techniques for processing and automatically understanding legal documents. To promote research in the area of Legal NLP we organized the shared task LegalEval - Understanding Legal Texts at SemEval 2023. LegalEval task has three sub-tasks: Task-A (Rhetorical Roles Labeling) is about automatically structuring legal documents into semantically coherent units, Task-B (Legal Named Entity Recognition) deals with identifying relevant entities in a legal document and Task-C (Court Judgement Prediction with Explanation) explores the possibility of automatically predicting the outcome of a legal case along with providing an explanation for the prediction. In total 26 teams (approx. 100 participants spread across the world) submitted systems paper. In each of the sub-tasks, the proposed systems outperformed the baselines; however, there is a lot of scope for improvement. This paper describes the tasks, and analyzes techniques proposed by various teams.Comment: 13 Pages (9 Pages + References), Accepted at SemEval 202

Thermodynamic Geometry: Evolution, Correlation and Phase Transition

Under the fluctuation of the electric charge and atomic mass, this paper considers the theory of the thin film depletion layer formation of an ensemble of finitely excited, non-empty $d/f$-orbital heavy materials, from the thermodynamic geometric perspective. At each state of the local adiabatic evolutions, we examine the nature of the thermodynamic parameters, \textit{viz.}, electric charge and mass, changing at each respective embeddings. The definition of the intrinsic Riemannian geometry and differential topology offers the properties of (i) local heat capacities, (ii) global stability criterion and (iv) global correlation length. Under the Gaussian fluctuations, such an intrinsic geometric consideration is anticipated to be useful in the statistical coating of the thin film layer of a desired quality-fine high cost material on a low cost durable coatant. From the perspective of the daily-life applications, the thermodynamic geometry is thus intrinsically self-consistent with the theory of the local and global economic optimizations. Following the above procedure, the quality of the thin layer depletion could self-consistently be examined to produce an economic, quality products at a desired economic value.Comment: 22 pages, 5 figures, Keywords: Thermodynamic Geometry, Metal Depletion, Nano-science, Thin Film Technology, Quality Economic Characterization; added 1 figure and 1 section (n.10), and edited bibliograph

An Exact Fluctuating 1/2-BPS Configuration

This work explores the role of thermodynamic fluctuations in the two parameter giant and superstar configurations characterized by an ensemble of arbitrary liquid droplets or irregular shaped fuzzballs. Our analysis illustrates that the chemical and state-space geometric descriptions exhibit an intriguing set of exact pair correction functions and the global correlation lengths. The first principle of statistical mechanics shows that the possible canonical fluctuations may precisely be ascertained without any approximation. Interestingly, our intrinsic geometric study exemplifies that there exist exact fluctuating 1/2-BPS statistical configurations which involve an ensemble of microstates describing the liquid droplets or fuzzballs. The Gaussian fluctuations over an equilibrium chemical and state-space configurations accomplish a well-defined, non-degenerate, curved and regular intrinsic Riemannian manifolds for all physically admissible domains of black hole parameters. An explicit computation demonstrates that the underlying chemical correlations involve ordinary summations, whilst the state-space correlations may simply be depicted by standard polygamma functions. Our construction ascribes definite stability character to the canonical energy fluctuations and to the counting entropy associated with an arbitrary choice of excited boxes from an ensemble of ample boxes constituting a variety of Young tableaux.Comment: Minor changes, added references, 30 pages, 4 figures, PACS numbers: 04.70.-s: Physics of black holes; 04.70.-Bw: Classical black holes; 04.50.Gh Higher-dimensional black holes, black strings, and related objects; 04.60.Cf Gravitational aspects of string theory, accepted for publication in JHE