Correct Location Research Articles

The first microwave and submillimetre closure study using particle models of oriented ice hydrometeors to simulate polarimetric measurements of ice clouds

Abstract. The first closure study involving passive microwave and submillimetre measurements of ice clouds with the consideration of oriented particles is presented, using a unique combination of polarised observations from the ISMAR spectral-like radiometer, two radars with frequencies of 35 and 95 GHz, and a variety of in situ instruments. Of particular interest to this study are the large V–H polarised brightness temperature differences measured from ISMAR above a thick frontal ice cloud. Previous studies combining radar and passive submillimetre measurements have not considered polarisation differences. Moreover, they have assumed particle habits a priori. We aim to test whether the large V–H measurements can be simulated successfully by using an atmospheric model consistent with in situ microphysics. An atmospheric model is constructed using information from the in situ measurements, such as the ice water content, the particle size distribution, and the mass and shape of particles, as well as background information obtained from dropsonde profiles. Columnar and dendritic aggregate particle models are generated specifically for this case, and their scattering properties are calculated using the independent monomer approximation under the assumption of horizontal orientation. The scattering properties are used to perform polarised radiative transfer simulations using ARTS to test whether we can successfully simulate the measured large V–H differences. Radar measurements are used to extrapolate the 1-D microphysical profile to derive a time series of particle size distributions which are used to simulate ISMAR brightness temperatures. These simulations are compared to the observations. It is found that particle models that are consistent with in situ microphysics observations are capable of reproducing the brightness temperature depression and polarisation signature measured from ISMAR at the dual-polarised channel of 243 GHz. However, it was required that a proportion of the particles were changed in order to increase the V–H polarised brightness temperature differences. Thus, we incorporated millimetre-sized dendritic crystals, as these particles were observed in the probe imagery. At the second dual-polarised channel of 664 GHz, the brightness temperature depressions were generally simulated at the correct locations; however, the simulated V–H was too large. This work shows that multi-frequency polarisation information could be used to infer realistic particle shapes, orientations, and representations of the split between single crystals and aggregates within the cloud.

Formalising the role of behaviour in neuroscience.

We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processing strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.

The role of prediction and visual tracking strategies during manual interception: An exploration of individual differences.

The interception (or avoidance) of moving objects is a common component of various daily living tasks; however, it remains unclear whether precise alignment of foveal vision with a target is important for motor performance. Furthermore, there has also been little examination of individual differences in visual tracking strategy and the use of anticipatory gaze adjustments. We examined the importance of in-flight tracking and predictive visual behaviors using a virtual reality environment that required participants (n = 41) to intercept tennis balls projected from one of two possible locations. Here, we explored whether different tracking strategies spontaneously arose during the task, and which were most effective. Although indices of closer in-flight tracking (pursuit gain, tracking coherence, tracking lag, and saccades) were predictive of better interception performance, these relationships were rather weak. Anticipatory gaze shifts toward the correct release location of the ball provided no benefit for subsequent interception. Nonetheless, two interceptive strategies were evident: 1) early anticipation of the ball's onset location followed by attempts to closely track the ball in flight (i.e., predictive strategy); or 2) positioning gaze between possible onset locations and then using peripheral vision to locate the moving ball (i.e., a visual pivot strategy). Despite showing much poorer in-flight foveal tracking of the ball, participants adopting a visual pivot strategy performed slightly better in the task. Overall, these results indicate that precise alignment of the fovea with the target may not be critical for interception tasks, but that observers can adopt quite varied visual guidance approaches.

Технологическое обеспечение эксплуатационных свойств сопрягаемых поверхностей элементов сборной формообразующей оснастки с учетом установленной долговечности пресс-форм

Design and technological concepts are viewed at the stages of designing, manufacturing and joining process providing for the required reliability (durability) of mold elements. Recommendations are given for rationing and achieving the parameters of accuracy and quality of mating surfaces, taking into account the formation of the necessary operational properties at the main stages of the product life cycle. The factors that have the greatest impact on ensuring the correct and accurate location of forming tool elements have been elicited. The concept of determining the actual contact area and calculating the scale parameter, which provides a contact interface degree specification for conjugated surfaces, is presented. The hypothesis of the formation of reliability indicators is found, taking into account the manufacturing capability and technical capacity of production with the introduction of correction of the upper and lower dimensional deviations included in the dimension chains and ensuring the pre-set accuracy parameters of the master link. The analysis of the operating conditions of the studied type of pressmold elements is carried out. The main operational properties that provide the required operating time for shaping part failures are identified and analyzed. Special attention is paid to the study of the structural features of such parts, a comparison of the integral and prefabricated structures is made, and also, contact stresses under the joining operation for the most promising of the latter are calculated for contact interface degree simulation. This will allow developing practical recommendations for any type of compound forming tool for the benefit of basic mechanical properties rate making, accuracy indicators, including deviation allowances in the correct geometric shape, including quality parameters of the surface layer at the designing stage,processing methods dispatch and modes setting at the manufacturing and testing stages and also suggesting the amount of static loading when assembling.

Dylematy interpretacyjne stosowania sygnałów drogowych ze szczególnym uwzględnieniem sygnalizatora S-2 w „bezpiecznym” zarządzaniu ruchem drogowym. Część III/III

This is the last of a three-part article devoted to the correctness of signal-controlled road traffic management. This part contains a presentation and commentary on the results of research on the use of signals transmitted by S-2 traffic light devices. In addition, the problem of correct location in the approach (situational plan on the road) of the signals transmitting the green arrow signal is characterized. The conflict resulting from the definition of the “intersection area” in the context of road traffic control and the possibility of using traffic lights at intersections where one of the approaches is the inlet to a private road is also commented on. The summary is the authors' conclusions considering all the parts of the article, along with recommendations for amendments to the Act on Road Traffic and implementing executive acts resulting thereof.

Weather Report Provider And Location Provider Using Google Map

The purpose of this research title is to present a weather forecast report on various factors and attributes so we can learn more about them such as temperature, wind speed, clouds, sunrise and sunset times, etc. In addition to displaying the correct location, Google Maps makes it easier for people who don't know a particular place and are new to it to understand it more easily, which makes it a great deal easier for them to make any type of decision like traveling to that place. This type of information can be extremely helpful. Using our app, the map can be accessed directly to give you directions to a location by using the map feature on Google directly. One of the biggest benefits of our application is its effectiveness, ease of use, and ability to collect so much information on one page. Keywords—Weather Forecast, Weather Report, Google Maps, Machine Learning, Data Preprocessing.

A strain gage technique for measuring the mode II stress intensity factors

In this paper, we propose a strain gage technique that allows an accurate measurement of the mode II stress intensity factors (SIFs). In order to ensure a good KII measurement, the size of the correct radial location of the strain gages is identified by using a methodology based on finite element analysis (FEA) and consolidated by solid theoretical foundations. The extent r1,max and r2,max of the validity of the five- and six-term representation of generalized Westergaard stress functions, which requires the use of two and three strain gages, respectively, is determined using the proposed method, and its dependence on the crack length to width ratio is also investigated. Numerical results obtained are in good agreement with the theoretical predictions, and confirm that the present method makes it possible to determine the KII with high precision when two (or three) strain gages are well placed within r1,max (or r2,max). Also, the numerical experiments show that the use of three strain gages is necessary when the size of the linear behavior region r1,max is very small. In addition, the effect of friction between the crack lips was checked and shown to have no effect on KII in pure mode II.

Shape completion in the dark: completing vertebrae morphology from 3D ultrasound

PurposeUltrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information. While performing US-based diagnosis or investigation, medical professionals therefore create a mental map of the 3D anatomy. In this work, we aim to replicate this process and enhance the visual representation of anatomical structures.MethodsWe introduce a point cloud-based probabilistic deep learning (DL) method to complete occluded anatomical structures through 3D shape completion and choose US-based spine examinations as our application. To enable training, we generate synthetic 3D representations of partially occluded spinal views by mimicking US physics and accounting for inherent artifacts.ResultsThe proposed model performs consistently on synthetic and patient data, with mean and median differences of 2.02 and 0.03 in Chamfer Distance (CD), respectively. Our ablation study demonstrates the importance of US physics-based data generation, reflected in the large mean and median difference of 11.8 CD and 9.55 CD, respectively. Additionally, we demonstrate that anatomical landmarks, such as the spinous process (with reconstruction CD of 4.73) and the facet joints (mean distance to ground truth (GT) of 4.96 mm), are preserved in the 3D completion.ConclusionOur work establishes the feasibility of 3D shape completion for lumbar vertebrae, ensuring the preservation of level-wise characteristics and successful generalization from synthetic to real data. The incorporation of US physics contributes to more accurate patient data completions. Notably, our method preserves essential anatomical landmarks and reconstructs crucial injections sites at their correct locations.

Hierarchical knowledge graph relationship prediction leverage of axiomatic fuzzy set graph structure

Knowledge graph embedding has found widespread application across various fields due to its inherent structured data. However, some non-graph-based models necessitate improvement in accurately describing complex hierarchical structures and connecting intricate relational paths. Graph neural networks embedding methods provide a promising direction for exploring complex hierarchical modeling, facilitating the flow of information from nodes along relational paths. Nevertheless, the deficient interpretable characterization by the saliency estimation in entities, which contributes to the efficient performance of the model, is difficult to comprehend. This paper proposes a novel model to mitigate the described phenomenon by intensifying the original structure of knowledge graphs. Specifically, it integrates the Axiomatic Fuzzy Set entity semantic extraction framework with a heterogeneous relationship self-attention mechanism to bolster node representation. Next, this framework incorporates a convolutional neural network model to increase the interaction capabilities of entities and relations. This interpretable entity-level attention mechanism complements the structural information of the knowledge graphs, enabling more comprehensive neighbor information capture and improving the ability to identify the correct entity location. Experimental validation on two relationally complex datasets demonstrates superior performance compared to current methods, obtaining a new Hit@1 value of 45.6% on WN18RR.

New Trends in Emerging Novel Nanosponges Drug Delivery

Medical professionals have long had trouble delivering medications to the correct location in the body and controlling their release to prevent overdose. Nano-sponges are novel and complicated molecules, which have the ability to alleviate these challenges. Utilizing nano-sponges allows for precise drug delivery to the desired location. Nano-sponge technology gets better patient compliance by delivering drugs to strategic locations while also extending dosing intervals. Various drug delivery techniques, such as parenteral, transdermal, oral, and immunosuppressive drugs, involve Nano-sponges. In today's world, nanosponges are used in gastro-retentive drug delivery systems.

Potential of Augmented Reality in the Library

Augmented reality (AR) applications are getting popular since they integrate the real world and the virtual world. This paper focusses on AR applications for public and scientific libraries. There exist some projects and sample implementations of AR apps specially designed for libraries, but they are seldom found in practice. To identify whether there is potential for AR apps to be applied in libraries, the results of a qualitative study that has been performed among librarians working in public and scientific libraries in Austria and experts in augmented reality are presented. Searching for media, navigating to the correct location and displaying ancillary information, like ratings, reviews, secondary media, links, etc., has the highest potential for users according to the experts. AR apps for maintaining the bookshelfs of a library provide real benefit for librarians and are awarded high potential as well. Guided tours through libraries using AR-based apps lightens the load of the librarians to introduce new users to the library. The feasibility of an AR app for a library is demonstrated by introducing a prototype that supports library users with additional information on media and the library itself.

Exploring Localized Geomagnetic Disturbances in Global MHD: Physics and Numerics

AbstractOne of the prominent effects of space weather is the formation of rapid geomagnetic field variations on Earth's surface driven by the magnetosphere‐ionosphere system. These geomagnetic disturbances (GMDs) cause geomagnetically induced currents to run through ground conducting systems. In particular, localized GMDs (LGMDs) can be high amplitude and can have an effect on scale sizes less than 100 km, making them hazardous to power grids and difficult to predict. In this study, we examine the ability of the Space Weather Modeling Framework (SWMF) to reproduce LGMDs in the 7 September 2017 event using both existing and new metrics to quantify the success of the model against observation. We show that the high‐resolution SWMF can reproduce LGMDs driven by ionospheric sources, but struggles to reproduce LGMDs driven by substorm effects. We calculate the global maxima of the magnetic fluctuations to show instances when the SWMF captures LGMDs at the correct times but not the correct locations. To remedy these shortcomings we suggest model developments that will directly impact the ability of the SWMF to reproduce LGMDs, most importantly updating the ionospheric conductance calculation from empirical to physics‐based.

Recreating Observed Convection‐Generated Gravity Waves From Weather Radar Observations via a Neural Network and a Dynamical Atmospheric Model

AbstractConvection‐generated gravity waves (CGWs) transport momentum and energy, and this momentum is a dominant driver of global features of Earth's atmosphere's general circulation (e.g., the quasi‐biennial oscillation, the pole‐to‐pole mesospheric circulation). As CGWs are not generally resolved by global weather and climate models, their effects on the circulation need to be parameterized. However, quality observations of GWs are spatiotemporally sparse, limiting understanding and preventing constraints on parameterizations. Convection‐permitting or ‐resolving simulations do generate CGWs, but validation is not possible as these simulations cannot reproduce the CGW‐forcing convection at correct times, locations, and intensities. Here, realistic convective diabatic heating, learned from full‐physics convection‐permitting Weather Research and Forecasting simulations, is predicted from weather radar observations using neural networks and a previously developed look‐up table. These heating rates are then used to force an idealized GW‐resolving dynamical model. Simulated CGWs forced in this way closely resembled those observed by the Atmospheric InfraRed Sounder in the upper stratosphere. CGW drag in these validated simulations extends 100s of kilometers away from the convective sources, highlighting errors in current gravity wave drag parameterizations due to the use of the ubiquitous single‐column approximation. Such validatable simulations have significant potential to be used to further basic understanding of CGWs, improve their parameterizations physically, and provide more restrictive constraints on tuning with confidence.

481 Spinal Cord Stimulator Promotes Neuroplasticity in Patients With Severe Spinal Cord Injury

INTRODUCTION: Traumatic spinal cord injury (SCI) is one of the leading causes of morbidity and mortality worldwide. Recently, epidural electrical stimulation (EES) has been shown to restore voluntary motor control in patients with severe SCI. METHODS: To this date, three patients with SCI have been implanted with 5-6-5-Specify-Medtronic electrodes and Medtronic-Intellis pulse generator. All procedures were approved by the local Ethics Committee. The age of the patients ranged from 38-69 y, and the levels of the SCI were C6-D5. Clinically, they were classified ASIA A (2) or B (1). The time frame after injury was 2-7 y. Intraoperative electrophysiological mapping was performed to ensure correct location of the lead at the levels involved in the control of L3-S2 nerve roots. Clinical assessments were performed every 3 m. Additionally, we measured superficial EMG each month, through sensors equipped with accelerometers and gyroscopes. RESULTS: One patient completed 12 m of intense rehabilitation program. The other two patients are currently on training and to this date they completed respectively 6 and 3 months of the program. All 3 patients were able to perform walking activities on a treadmill and stationary bicycle with stimulation turned on. There was an important improvement in the scales related to motor skills and balance, at expense of worsening in pain scores. After 8 months the first patient started to present voluntary movements even with stimulation turned off. CONCLUSIONS: EES allows restoration of voluntary motor control of the legs after severe traumatic SCI. Moreover, after 8 months, a plastic effect could be observed, and a patient was able to control movements even with off stimulation. The observed improvement in overall patient’s performance occurred at expense of more pain, which need to be addressed carefully.

Laparoscopic Large Hiatal Hernia Repair With RefluxStop: Outcomes of Six Months Follow-up in Thirty Patients.

The antireflux surgical technique with the RefluxStop device is one of the latest approaches to treating patients with gastroesophageal reflux disease (GERD). The aim of this study was to assess the safety and feasibility of laparoscopic hiatal hernia (HH) repair with the RefluxStop device in patients with GERD and concurrent large HH (≥4 cm). A retrospective chart review was performed for the first 30 patients with a large HH who consented and underwent HH surgery with the RefluxStop device. The operative technique and outcomes were evaluated to assess safety and feasibility, HH recurrence, dysphagia, and patient satisfaction. Between May 2020 and April 2022, 30 patients underwent laparoscopic HH repair with the RefluxStop device. All patients had typical symptoms of GERD, such as heartburn and regurgitation, and 15 patients (50%) had preoperative dysphagia. Median HH size was 5 cm (interquartile range, 4 to 5). Median operating time was 56 minutes (interquartile range, 52 to 63), with no intra and postoperative complications related to the device. One patient required laparotomy due to adhesions and associated bleeding when accessing the abdomen. All patients had postoperative imaging (video fluoroscopy) on postoperative day 1 and at 3 months, confirming the correct location of the RefluxStop device. One patient (3.3%) needed postoperative balloon dilatation due to severe dysphagia. Reflux symptoms (heartburn and acid regurgitation) resolved significantly in all patients ( P < 0.001) at 6 months. One episode of recurrence of HH (3.3%) occurred during the follow-up period of 6 months. This study demonstrates the short-term safety and feasibility of laparoscopic HH repair with the RefluxStop device in patients with large HH, with a low rate of postoperative dysphagia and subsequent improvement or resolution of reflux symptoms in all patients.

The left digit effect in an unbounded number line task.

The left digit effect in number line estimation refers to the phenomenon where numerals with similar magnitudes but different leftmost digits (e.g., 19 and 22) are estimated to be farther apart on a number line than is warranted. The effect has been studied using a bounded number line task, a task in which a line is bounded by two endpoints (e.g., 0 and 100), and where one must indicate the correct location of a target numeral on the line. The goal of the present work is to investigate the left digit effect in an unbounded number line task, a task that involves using the size of one unit to determine a target numeral's location, and that elicits strategies different from those used in the bounded number line task. In a preregistered study, participants (N = 58 college students) completed four blocks of 38 trials each of an unbounded number line task, with target numerals ranging between 0 and 100. We found a medium and statistically reliable left digit effect (d = 0.70). The study offers further evidence that the effect is not driven by response strategies specific to the bounded number line task. We discuss other possible sources of the effect including conversion of symbols to magnitudes in these and other contexts.

Intelligent gold nanocluster for effective treatment of malignant tumor via tumor-specific photothermal-chemodynamic therapy with AIE guidance.

Precise and efficient therapy of malignant tumors is always a challenge. Herein, gold nanoclusters co-modified by aggregation-induced-emission (AIE) molecules, copper ion chelator (acylthiourea) and tumor-targeting agent (folic acid) were fabricated to perform AIE-guided and tumor-specific synergistic therapy with great spatio-temporal controllability for the targeted elimination and metastasis inhibition of malignant tumors. During therapy, the functional gold nanoclusters (AuNTF) would rapidly accumulate in the tumor tissue due to the enhanced permeability and retention effect as well as folic acid-mediated tumor targeting, which was followed by endocytosis by tumor cells. After that, the overexpressed copper ions in the tumor cells would trigger the aggregation of these intracellular AuNTF via a chelation process that not only generated the photothermal agent in situ to perform the tumor-specific photothermal therapy damaging the primary tumor, but also led to the copper deficiency of tumor cells to inhibit its metastasis. Moreover, the copper ions were reduced to cuprous ions along with the chelation, which further catalysed the excess H2O2 in the tumor cells to produce cytotoxic reactive oxygen species, resulting in additional chemodynamic therapy for enhanced antitumor efficiency. The aggregation of AuNTF also activated the AIE molecules to present fluorescence, which not only imaged the therapeutic area for real-time monitoring of this tumor-specific synergistic therapy, but also allowed us to perform near-infrared radiation at the correct time point and location to achieve optimal photothermal therapy. Both in vitro and in vivo results revealed the strong tumor elimination, effective metastasis inhibition and high survival rate of tumor-bearing mice after treatment using the AuNTF nanoclusters, indicating that this AIE-guided and tumor-specific synergistic strategy could offer a promising approach for tumor therapy.

The impact of aerosols and model grid spacing on a supercell storm from Swabian MOSES 2021

AbstractThe supercell storm that occurred in southwestern Germany on June 23, 2021, had an exceptionally long lifetime of 7.5 hr, travelled a distance of nearly 190 km, and produced large amounts of hail. During that summer, the Swabian MOSES field campaign was held in that area, and several hydro‐meteorological measurements are available, as the storm passed directly over the main observation site. We present hindcasts of this event with the Icosahedral Non‐hydrostatic model using two horizontal grid spacings (i.e., 2 km, 1 km) with a single‐moment and an advanced double‐moment microphysics scheme. Numerical results show that all 2 km model realizations do not simulate convective precipitation at the correct location and time. For the 1 km grid spacing, changes in aerosol concentration resulted in large changes in convective precipitation. Only the 1 km run assuming a low cloud condensation nuclei (CCNs) concentration is able to realistically capture the storm, whereas no supercell is simulated in the more polluted scenarios. Observed aerosol particle concentrations indicate that CCNs values were the lowest of the month, which suggests that the low aerosol concentration is a reasonable assumption. The thermodynamic structure of the pre‐convective environment, as well as other observations, showed the best agreement to this model run as well, indicating that the good representation of the supercell was obtained for the right reason. The automatic tracking of individual clouds revealed that more convective cells with longer lifetimes are simulated at finer resolution. We also find a negative aerosol–precipitation effect that is not only due to a reduced collision–coalescence process, but also to weaker cold‐rain processes. These findings demonstrate the benefits of using an aerosol‐aware double‐moment microphysics scheme for convective‐scale predictability and that the use of different CCNs concentrations can determine whether a supercell is successfully simulated or not.

JDECMC: Improving JDE based multi-object tracking with Camera Motion Compensation

Jointly Detection and Embedding (JDE) based approaches estimate bounding boxes and embedding features of objects with a single network in multi-object tracking. Due to the crowded scenarios or non-rigid camera motion, the bounding box location in the image can shift dramatically, which affects the performance of the trackers. In addition, JDE-based approaches fuse the target appearance information and location information by applying the same rule, which could fail to associate when the target is lost or occluded. To address these issues, we propose a simple yet effective architecture based on JDE, called JDECMC. Our approach incorporates the embedding and location distance of the object, which combines embedding cosine distance and location distance of objects, as well as Camera Motion Compensation (CMC) to predict the correct location of the bounding box. This is especially useful in scenarios where dynamic camera motion can cause the bounding box to shift significantly. By enhancing the accuracy of the tracking system, JDECMC achieves a MOTA of 74.2%, 72.0%, and 90.5% on the MOT17, MOT20 and DanceTrack benchmark datasets, respectively, while also scoring an IDF1 of 72.5%, 72.4%, and 79.8% on those benchmarks. The experimental results demonstrate our effectiveness and advantages over the other one-shot trackers. The code is available at https://github.com/Melikamuliyih/JDECMC.

Crime Prevention Through Environmental Design: Numerical investigation of environmental factors affecting security in sports facilities

Sports are one of the most essential categories of developed and developing societies, among which football, as the most popular sport in the world, receives special attention from governments. Therefore, to increase the attendance of people in stadiums, it is necessary for the managers to identify the factors influencing the attendance of spectators, both psychological and internal factors, as well as external and environmental factors, and to design and implement a written and specific strategy and plan. Having a sense of security is one of the influential factors in creating satisfaction in the audience. Due to the high cost of building sports facilities and spaces, care should be taken about many factors and variables, especially the correct location of such spaces, to enable easier access, fairer distribution, and greater security. Therefore, this research aims to analyze the environmental factors that affect security in sports facilities with the approach of crime prevention through environmental design in stadiums. The instrument in this research is a questionnaire on security in sports facilities with the effectiveness of crime prevention through environmental design. Finally, the artificial neural network system method was used in MATLAB (A 2018) and SPSS (V24) software to analyze the data and answer the research questions. Environmental factors of access, light and illumination, readability, visibility and natural surveillance, repair and maintenance, dynamics, functional disorders, and guide signs respectively had a positive effect on security and crime prevention through environmental design in sports facilities. Therefore, sports directors and architects must pay attention to these indicators in the design of sports stadiums. Keywords: Stadiums, Sport Management, Sports Events, CPTED Approach, Neural Networks.