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Using the Nudge Theory in Improving Security Policies and Crime Prevention: Integrative Review
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The "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of  Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.

The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.

The study is based on the literature of behavioral economics, with a focus on three basic and recent theories: nudges, fast and slow thinking, and chaos bias. All of them confirm that the ordinary person acts spontaneously, and makes his daily decisions according to what is available, without thinking and contemplation. Thus, they bear characteristics that the security researcher can employ in preventing crime and designing security policies.

Many of the results of studies using poke and behavioral economics theories in crime prevention emphasized the reduction of crime rates, and yielded positive results in preventing crime, rather than combating it, especially in the field of urban planning, shop design, afforestation, lighting, and paving of streets, which encourages the turnout of individuals to it and causes a natural social interaction that prevents the criminal from being motivated to commit his crime.

The study recommends giving more attention to studies about uses of the nudge theory, developing the design of security policies in crime prevention, and supporting modern security studies and security policy studies.

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Publication Date
Tue Jul 30 2024
Journal Name
Iraqi Journal Of Science
Frame-Based Change Detection Using Histogram and Threshold to Separate Moving Objects from Dynamic Background
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      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Sun Jun 01 2025
Journal Name
Cleaner Waste Systems
Performance enhancement of natural asphalt using waste-derived modifiers: Sugarcane molasses and waste engine oil
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The growing demand for sustainable and high-performance asphalt binders has prompted the exploration of waste-derived modifiers. This study investigates the performance enhancement of Natural Asphalt (NA) using Sugarcane Molasses (SM) and Waste Engine Oil (WEO). The modified blends were prepared by partially replacing 50 % NA with varying proportions of SM and WEO ranging from 10 % to 40 % of the total weight of NA. Comprehensive testing was conducted, including penetration, softening point, ductility, viscosity, Bending Beam Rheometer (BBR), Multiple Stress Creep Recovery (MSCR), Energy Dispersive X-ray Spectroscopy (EDX), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy (SEM). The results demonstrated that

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Publication Date
Sat Dec 01 2018
Journal Name
Sustainable Materials And Technologies
A sustainable pavement concrete using warm mix asphalt and hydrated lime treated recycled concrete aggregates
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Recently, increasing material prices coupled with more acute environmental awareness and the implementation of regulation has driven a strong movement toward the adoption of sustainable construction technology. In the pavement industry, using low temperature asphalt mixes and recycled concrete aggregate are viewed as effective engineering solutions to address the challenges posed by climate change and sustainable development. However, to date, no research has investigated these two factors simultaneously for pavement material. This paper reports on initial work which attempts to address this shortcoming. At first, a novel treatment method is used to improve the quality of recycled concrete coarse aggregates. Thereafter, the treated recycled

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Publication Date
Thu Jul 31 2025
Journal Name
Computers, Materials & Continua
A Secure Audio Encryption Method Using Tent-Controlled Permutation and Logistic Map-Based Key Generation
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The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Peak to Average Power Ratio Reduction of OFDM Signals Using Clipping and Iterative Processing Methods
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One of the serious problems in any wireless communication system using multi carrier modulation technique like Orthogonal Frequency Division Multiplexing (OFDM) is its Peak to Average Power Ratio (PAPR).It limits the transmission power due to the limitation of dynamic range of Analog to Digital Converter and Digital to Analog Converter (ADC/DAC) and power amplifiers at the transmitter, which in turn sets the limit over maximum achievable rate.

        This issue is especially important for mobile terminals to sustain longer battery life time. Therefore reducing PAPR can be regarded as an important issue to realize efficient and affordable mobile communication services.

   

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Optimization of Voltammetric Determination of Dysprosium (III) Using Plackett-Burman and RSM-CCD Experimental Designs
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This study was aimed to develop an optimized Dy determination method using differential pulse voltammetry (DPV). The Plackett-Burman (PB) experimental design was used to select significant factors that affect the electrical current response, which were further optimized using the response surface method-central composite design (RSM-CCD). The type of electrolyte solution and amplitude modulation were found as two most significant factors, among the nine factors tested, which enhance the current response based on PB design. Further optimization using RSM-CCD shows that the optimum values for the tw

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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Synthesis and Characterization of Multishapes of Fe3O4 Nanoparticle by Solve-Hydrothermal Method Using Microwave Radiation
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Iron oxide(Fe3O4) nanoparticles of different sizes and shapes were synthesized by solve-hydrothermal reaction assisted by microwave irradiation using ferrous ammonium sulfate as a metal precursor, oleic acid as dispersing agent, ethanol as reducing agent and NaOH as precipitating agent at pH=12. The synthesized Fe3O4 nano particles were characterized by X-ray diffraction (XRD), FTIR and thermal analysis TG-DTG. Sizes and shapes of Fe3O4 nanoparticles were characterized by Scanning Electron Microscopy (SEM), and atomic force microscopy (AFM).

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