14 research outputs found
The impact of police-monitored CCTV cameras on crime patterns: a quasi-experimental study in the metropolitan city of Bursa, Turkey
No full textRapid adoption and expansion of the CCTV systems in Turkey as well as all over the world have produced a fair amount of "technological determinism" among many law enforcement officials, which Norris and Armstrong (1999, p. 9) define as "an unquestioning belief in the power of technology". As a matter of technological determinism, politicians and the public continue to myopically expect that the exclusive responsibility of preventing crime rest on the police-monitored CCTV cameras. Conversely, policy makers may be better informed if they consider why the law enforcement agencies should invest in the installation of the CCTV cameras in public areas based on the research. In fact, a well-designed evidence based paradigm in the CCTV literature is likely to reveal the truth about the question of "does it work?" In addition to all previous methodological efforts, empirical evaluations in the CCTV literature are still needed to account for alternative perspectives to measure their effectiveness in the deterrence of crimes. Therefore, the present study focused on the concepts of environmental criminology, namely "crime risk at place". This research also considered the environmental risk values that might identify "environmental conditions under which cameras would be most effective" (Caplan et al., 2011, p.271). Thus, the concept of "Environmental risk value" provided a unique methodological approach to the police-monitored CCTV literature. This study examined the impact of the metropolitan city of Bursa‘s city-wide system and certain individual police-monitored CCTV camera‘s views used to scan the landscape, respectively on street level, including aggravated assault, auto theft, thefts from autos, and larceny theft crime incident numbers in a spatial distribution of locations; and analyzed whether the environmental risk value effects on the deterrent effect of police-monitored CCTV cameras on aforementioned crime types. To accomplish that statistical analyses (paired t test, location quotient, and regression models) and risk terrain modeling (RTM) were conducted in this dissertation. Three important findings were found in this study. Firstly, city-wide system effect indicated that larceny thefts and thefts from auto experienced significant reduction. However, aggravated assaults and auto thefts were not. Secondly, the results from assessing the deterrent effect of certain individual police-monitored CCTV cameras on aggravated assaults, larceny thefts, thefts from autos and auto thefts were mixed. Finally, each individual CCTV camera has a unique environment – environmental risk value that influences its deterrent effect on – aggravated assaults, larceny thefts, thefts from autos and autos theft. Further, the affect was discernable and in positive direction for each crime type. Environmental risk value assessments can advance our understanding of the deterrent effect of CCTV cameras at their viewshed areas. So environmental risk sites must be taken into account when the decision process concerning CCTV cameras is made by local and national level policy makers, police agencies and politicians who try to establish where the most appropriate location to install police-monitored CCTV cameras is. In this respect RTM can be considered as a pre intervention tool so that police agencies can measure the deterrent effect of CCTV before installation. Such a pre-evaluation process increases the capacity for effective police management and crime prevention strategies in police agencies.Ph. D.Includes bibliographical referencesIncludes vitaby Emirhan Darca
A comparative study on iterative algorithms of almost contractions in the context of convergence, stability and data dependency
No full textIn this paper, we propose a new iterative algorithm and analyze it in detail inasmuch as convergence, stability, and data dependency for the class of almost contraction mappings. We also consider another iterative algorithm called F* iterative algorithm proposed by Ali et al. (Comp. Appl. Math. 39, 267 (2020)) and derive some new algorithms from this with the aim of giving an affirmative answer to an open question raised by the same authors. Our results considerably improve the corresponding results in Ali et al. (Comp. Appl. Math. 39, 267 (2020)). We submit some non-trivial numerical examples to illustrate the robustness, feasibility, and effectiveness of our findings
Existence and convergence for a new multivalued hybrid mapping in CAT(kappa) spaces
No full textMost of the studies about hybrid mappings are carried out for single-valued mappings in Hilbert spaces. We define a new class of multivalued mappings in CAT (kappa) spaces which contains the multivalued generalization of (alpha, beta) - hybrid mappings defined on Hilbert spaces. In this paper, we prove existence and convergence results for a new class of multivalued hybrid mappings on CAT(kappa) spaces which are more general than Hilbert spaces and CAT(0) spaces
Monotone Generalized ?-Nonexpansive Mappings on CATp(0) Spaces
No full textWe examine the existence of fixed points of generalized alpha-nonexpansive mappings on CAT(p)(0) spaces. We establish various convergence results for a newly defined algorithm associated with alpha-nonexpansive mappings and present some illustrative examples to show the efficiency of the proposed algorithm and to support the above-mentioned results. We also define monotone generalized alpha-nonexpansive mappings and prove some existence and convergence results for these mappings
Evaluating Souper: A Synthesizing Superoptimizer
No full textModern compilers exploit syntax \& semantics to optimize input programs.Often such optimization rules are arduous to get right and the output is not guaranteed to be globally optimal.Superoptimizers take a different approach to this problem by traversing the program space.This study focuses on Souper, a synthesizing superoptimizer which makes use of an enhanced counter-example-guided inductive synthesis loop to find optimizations.We first detail the working mechanism of the superoptimizer and its components, then we explain our attempts at reproducing the results mentioned by Souper's authors.Finally, we give three program classes each exercising different aspects of the superoptimizer and how these are useful in gaining insight into Souper's optimization capabilities and use cases.CSE3000 Research ProjectComputer Science and Engineerin
An Efficient Inertial Type Iterative Algorithm to Approximate the Solutions of Quasi Variational Inequalities in Real Hilbert Spaces
No full textIn this article, we design a projection type iterative algorithm with two inertial steps for solving quasi-variational inequalities with Lipschitz continuous and strongly monotone mappings in real Hilbert spaces. We establish different strong convergence results through this algorithm. We give a non-trivial example to validate one of our results and to illustrate the efficiency of the proposed algorithm compared with an already existing one. We also present some numerical experiments to demonstrate the potential applicability and computing performance of our algorithm compared with some other algorithms existing in the literature. The results obtained herein are generalizations and substantial improvements of some earlier results
Iterative approximation of fixed points and applications to two-point second-order boundary value problems and to machine learning
No full text*Maldar, Samet ( Aksaray, Yazar )
*Atalan, Yunus ( Aksaray, Yazar )In this paper, we revisit two recently published papers on the iterative approximation of fixed points by Kumam et al. (2019) [17] and Maniu (2020) [19] and reproduce convergence, stability, and data dependency results presented in these papers by removing some strong restrictions imposed on parametric control sequences. We confirm the validity and applicability of our results through various non-trivial numerical examples. We suggest a new method based on the iteration algorithm given by Thakur et al. (2014) [28] to solve the two-point second-order boundary value problems. Furthermore, based on the above mentioned iteration algorithm and S-iteration algorithm, we propose two new gradient type projection algorithms and applied them to supervised learning. In both applications, we present some numerical examples to demonstrate the superiority of the newly introduced methods in terms of convergence, accuracy, and computational time against some earlier methods
A gradient projection algorithm based on the normal-S iterative algorithm: convergence analysis and machine learning application
No full textUsing the normal-S iterative method [D.R. Sahu, Fixed Point Theory12 (2011), 187-204], a gradient projection algorithm for solving convex minimization problems in Hilbert spaces is designed. A rigorous analysis of the convergence properties of the proposed algorithm is given, establishing strong convergence results through systematic refinement. The theoretical advancements are supported by non-trivial examples and comprehensive numerical experiments on benchmark datasets, demonstrating a superior computational efficiency of our algorithms, as well as their accuracy and convergence. Our findings significantly improve upon the outcomes of earlier studies.Serbian Academy of Sciences and Arts [Phi-96]Research of G.V.M. was partly supported by the Serbian Academy of Sciences and Arts (Project Phi-96
Flexible and Efficient Iterative Solutions for General Variational Inequalities in Real Hilbert Spaces
No full textThis paper introduces a novel Picard-type iterative algorithm for solving general variational inequalities in real Hilbert spaces. The proposed algorithm enhances both the theoretical framework and practical applicability of iterative algorithms by relaxing restrictive conditions on parametric sequences, thereby expanding their scope of use. We establish convergence results, including a convergence equivalence with a previous algorithm, highlighting the theoretical relationship while demonstrating the increased flexibility and efficiency of the new approach. The paper also addresses gaps in the existing literature by offering new theoretical insights into the transformations associated with variational inequalities and the continuity of their solutions, thus paving the way for future research. The theoretical advancements are complemented by practical applications, such as the adaptation of the algorithm to convex optimization problems and its use in real-world contexts like machine learning. Numerical experiments confirm the proposed algorithm's versatility and efficiency, showing superior performance and faster convergence compared to an existing method.Adiyaman University Scientific Research Projects Unit; Serbian Academy of Sciences and Arts [Phi-96]; [FEFMAP/2025-0001]The authors (E.H., M.E., and F.G.) acknowledge that their contribution to this work was partially supported by the Adiyaman University Scientific Research Projects Unit under Project No. FEFMAP/2025-0001, titled A New Preconditional Forward-Backward Algorithm for Monotone Operators: Convergence Analysis and Applications. The work of G.V.M. was supported in part by the Serbian Academy of Sciences and Arts (Phi-96)
New insights on a pair of quasi-contractive operators in Banach spaces: Results on Jungck type iteration algorithms and proposed open problems
No full textIn this paper, we explore relationships among the pairs of various well-known contractive type operators in Banach spaces. We also present a novel Jungck type iteration algorithm for a pair of quasi-contractive operators, which is thoroughly investigated in terms of strong convergence, stability, and data dependency. To demonstrate the efficacy of the proposed algorithm and reliability of each of the mentioned results, we furnish illustrative academic examples including both linear and nonlinear DEs. Furthermore, we present several open problems that warrant further study. Our results complement recent findings in the literature and contribute to further development in this area. (c) 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved
