Crowded Streets Research Articles

Towards One health for All; Maintaining Human health in a town through Integration of an integrated scientific projects into a healthy landscaped site.

Chronic diseases in big town as a result of over crowded streets, waste pollutants and factories lead us to work suriously and regourously in order to provide a healthy environment suitable for traitment in ecological town with a suitable density of population for healthy living. In this research through landscape architecture and the concept of ONE HEALTH as well as the fabric space, we promote health for all through a modern healthy structure in Ouzera town with a salutogenic architecture. The research in the medical fields is also being developed by establishing an integrated scientific space in Ouzera town according to the local schema for mangement of Médéa territories for the 2030 horizons. This space is designated with landscape Architecture and one of its research structures proposed for design is a reserch center on animal medicine and productivity that implements the one health initiative.

Sistem Keamanan Kendaraan Jarak Jauh Menggunakan GPS Berbasis NODEMCU ESP8266

The use of motorcycles as a means of personal transportation is a practical and easy-to-use transportation option in various crowded road conditions. In general, vehicle security systems are still very weak, and additional security systems are needed to prevent theft, especially in older vehicles. To increase security on motorbikes, researchers developed a security system that can monitor the location of motorbikes that can be monitored and controlled via an Android application. In making this prototype, the NodeMCU ESP8266 microcontroller as the Internet of Things (IoT), Ublox Neo-6M GPS module, and relays to control motorcycle electricity. The GPS module is used to determine the location based on the latitude and longitude of the motorcycle directly and will be sent to the server and then displayed through the Android application. In addition to displaying location coordinates, this application can also control motorcycle electricity with NodeMCU ESP8266 to activate relays connected to motorcycle electricity to function as turning on or off the motorcycle engine and there is a location history menu obtained from the GPS module.

The relationship between toxic air pollution, health expenditure, and economic growth in the European Union: fresh evidence from the PMG-ARDL model.

Air pollution is a danger to economies throughout the European Union. Industry, population expansion, a building boom owing to housing and infrastructure development, increasing vehicle traffic, crowded streets, a lack of availability of clean fuel, and ineffective control programs are the primary causes. Toxic air is a double-edged sword for a country's health since it affects just a tiny fraction of Europe's population. The financial burden and healthcare expenses for people rise when health expenditures rise. The present research looks at how dangerous air levels, healthcare costs, and the expansion of the European Union's economy are all connected. The findings are based on data collected over 29years and account for the abovementioned variables. The results of the unit root test have the significant probability values of all variables: health expenditures (HE), gross domestic product (GDP), nitrous oxides (NOX), and carbon dioxides (CO2) emissions at both level and first difference. We used the Johansen, Kao, and Pedroni cointegration tests to test the null hypothesis of no cointegration to see that sample variables had a long-term association. The PMG-ARDL test was used to get these findings. The results confirmed the significant probability values of dependent variables in long- and short-run results that GDP has a positive and significant effect on health expenditure, while NOX and CO2 emissions have a negative and significant impact on (HE), in the European Union. To verify the results, we applied the robustness test, fully modified OLS (FMOLD), and dynamic OLS (DOLS); the robustness test results validated the PMG-ARDL test results. Environmental pollution (CO2, NOX) has a significant and negative impact on healthcare expenditures and a significant effect on GDP (HE) in the EU region. The findings of this research have implications for a wide range of parties, including those who would examine the link between factors in a study meant to improve air quality, distribute health resources, or develop strategies for economic development.

Multi-scale feature fusion with attention mechanism for crowded road object detection

Multi-scale feature fusion with attention mechanism for crowded road object detection

Multi-object detection for crowded road scene based on ML-AFP of YOLOv5

Aiming at the problem of multi-object detection such as target occlusion and tiny targets in road scenes, this paper proposes an improved YOLOv5 multi-object detection model based on ML-AFP (multi-level aggregation feature perception) mechanism. Since tiny targets such as non-motor vehicle and pedestrians are not easily detected, this paper adds a micro target detection layer and a double head mechanism to improve the detection ability of tiny targets. Varifocal loss is used to achieve a more accurate ranking in the process of non-maximum suppression to solve the problem of target occlusion, and this paper also proposes a ML-AFP mechanism. The adaptive fusion of spatial feature information at different scales improves the expression ability of network model features, and improves the detection accuracy of the model as a whole. Our experimental results on multiple challenging datasets such as KITTI, BDD100K, and show that the accuracy, recall rate and mAP value of the proposed model are greatly improved, which solves the problem of multi-object detection in crowded road scenes.

Anatomical Study of Nerium oleander L. Leaves Found in Places Contaminated with H2S

The research study the effect of H2S on Nerium oleander leaves, the leaves were collected from the pollution places in the crowded streets with cars and factory areas from five different regions of Basrah city, The results showed that the average of highest concentration of hydrogen sulfide gas was 4. ppm in the Al-Amin Aldakhli area, while the lowest value of gas was recorded in Karmat Ali, it was 0.4 ppm of date palm plants and 0.8 ppm. Anatomy study of N. oleanderleaves showed that the different changes in plant internal tissues with H2S pollution which presented by difference in the thickness of epidermal cell walls of N. oleander leaves in the areas of Al-Dair, Manawi Pasha and Andal’s, while the thickness of the cells was less in the area of Karmat Ali. Highest average length of cells of the upper epidermis was recorded in the Al-Dier and Karmat Ali region was 40 μm and 37.5 μm respectively, while the lower epidermis was 35.82 μmin Al-Dier. Stomata dimension found the lowest average was recorded in the Al-Amin Aldakhli area was 24 μm while in the upper epidermis have highest value, it was in Karmat ali was 30 μm. The number of stomata different between the stations, it was found that the highest average of stomata was found in the lower epidermis in Al-Amin Aldakhli station was 215.98, while the lowest average in Karmat Ali was 98. The upper epidermis had the highest average number of stomata in the Minawi Pasha station was 183.96 on lower epidermis and the lowest average in Andal’s area was 66. Also, the highest average number of cells was in the Lower epidermis in Andal’s region was 3159.96, and the lowest average was 919.98 in the Al-Dair.

CONSERVING AND PREVENTIVE CONSERVATION PLAN OF PHOTOGRAPHIC ARCHIVE BELONG TO KHEDIVE ISMAIL PASHA BACK TO 19TH CENTURY STORAGE IN VEHICLES MUSEUM

Abstract. The Royal Vehicles Museum contains five albums of Albumin photographs dating from the 19th century. These photographs are poorly preserved in the basement of the Royal Vehicle Museum which is located on one of the most crowded streets, July 26 St., near the Nile River in Cairo. Due to the poor storage conditions of wooden boxes without treatment, it is unsafe against insects and microbiological damage, so they are vulnerable to rapid because the albumin photographs are composed of organic and inorganic materials, which makes them vulnerable to rapid damage. This paper presents documentation, preservation, and conservation of albumen photographic print-outs. Temperature, humidity, and UV were measured in the storage area by Data Luger. The deterioration aspect of the Royal Album and the albumen photographs has been identified. A condition report has been planned to record all the archaeological and historical information belonging to the album. SEM_EDX was used to identify the surface morphology and determine the type of silver salts used. The microbiological test was performed to identify fungi and bacteria. Growth requirements are determine. A portable scanner has digitized albumen photographs. USB Digital Microscope strongly enlarge 300× has been used to identify cracks, crevices, dirt, and other damages on the album and photographs. A stereo microscope 500× shows the structure of albumin photo prints.

Optimal Scheduling of Rainwater Collection Vehicles: Mixed Integer Programming and Genetic Algorithms

Due to climate change, some areas in the world witnessed higher levels of heavy rain than the capacity of the wastewater system of the streets. Therefore, water tankers are used for the dewatering process to take the extra rainwater from the streets to keep a smooth flow of vehicles and to use the water in agriculture and industry. Water is taken to a water treatment plant. Performing the dewatering process as fast as possible, especially in crowded streets, was ignored by researchers. In this study, at first, the problem was solved using two mixed integer programming (MIP) models. A new variant of identical parallel machine scheduling with job splitting is proposed for the first time, where one or at most two tankers can work at the same flood location at the same time. This is performed in the second model. However, the first model considers dividing the dewatering processes into two phases, where the first one, which is more urgent, is to reduce the amount of floodwater. The second one is for dewatering the rest of the water. Then two genetic algorithms (GAs) were used to solve faster the two MIP models, which are NP-hard problems. At first, the MIP and GA models were applied to small-sized problems. Then GA was used for large practical data sets. Results showed that for small problems, MIP and GA gave optimal solutions in a reasonable number of iterations, while for larger problems, good solutions were obtained in a reasonable number of iterations.

Smart Parking System

Abstract: In recent days, Parking allocation has become a major problem in modern cities for which numerous smart parking systems have been developed. This paper aims to provide comprehensive study, comparison and extensive analysis of Smart Parking Systems in terms of technological approach, user interface, computational approaches, and service provided. Moreover, the paper fills up the research gap by providing a clear insight into the suitability of SPSs in various environmental conditions and highlights their advantages/disadvantages. The extensive comparison among multiple aspects of SPSs would enable researchers, designers, and policymakers to identify the best suited Smart Parking System and understand the current trends in this sector. In order to overcome difficulties such as waiting in long queue and circling around the blocks to find a vacant parking space, in this paper we are proposing a unique system wherein people living in the vicinity of crowded streets can rent their unused parking space. Using this approach, especially malls can productively manage the parking problem effectively during rush hours. This system also provides convenience to customers by reducing the amount of time spent to find a vacant parking slot by allowing them to reserve a vacant slot through pre-book.

Important Factors for Inclusive Pedestrian Ways Development in Pecinan Semarang City

Urban Planning is strongly related to public spaces. Open public spaces are an essential element in sustaining community activity spaces. Social, economic, and other activities regularly happen in this area. Pecinan (Chinatown) is one of the heritage areas in Semarang that still has high community activity. Narrow and crowded street in this area becomes one the issues for pedestrian. The unsafe feeling occurs when people cross the street. The store’s activity on the side of the street also creates a fuzzy condition for pedestrians. The study aims to the sustainability and inclusivity of pedestrian ways in Pecinan. Data Collection is done by observing the actual condition of 1380 samples in the field through interviews and questionnaires for the pedestrian. The method of this study uses quantitative methods and use behavioral mapping for the analysis methods. The result of the study shows that pedestrians tend to rank accessibility as the most important factor, followed by transit points, infrastructure, and parking areas. The result also shows that continuous arcade shade and vegetation coverage as other factors that affect pedestrian comfort in Southeast Asian Country climates condition. The result also reveals that an active frontage of a store creates a more lively atmosphere. The recommendation based on the study is to relocate the street vendors’ activity alongside the narrow road. The relocation also should still be near the area of the Pecinan.

Fast Obstacle Avoidance Based on Real-Time Sensing

Humans excel at navigating and moving through dynamic and complex spaces, such as crowded streets. For robots to do the same, it is crucial that they are endowed with highly reactive obstacle avoidance which is adept at partial and poor sensing. We address the issue of enabling obstacle avoidance based on sparse and asynchronous perception. The proposed control scheme combines a high-level input command provided by either a planner or a human operator with fast reactive obstacle avoidance (FOA). The sampling-based sensor data can be combined with an analytical reconstruction of the obstacles for real-time collision avoidance. Thus, we can ensure that the agent does not become stuck when a feasible path exists between obstacles. Our algorithm was evaluated experimentally on static laser data from cluttered, indoor office environments. Additionally, it was used in shared-control mode in a dynamic and complex outdoor environment in the center of Lausanne. The proposed control scheme successfully avoided collisions in both scenarios. During the experiments, the controller took 1 ms to evaluate over 30000 data points.

A Secure Traffic Police Remote Sensing Approach via a Deep Learning-Based Low-Altitude Vehicle Speed Detector through UAVs in Smart Cites: Algorithm, Implementation and Evaluation

Nowadays, the unmanned aerial vehicle (UAV) has a wide application in transportation. For instance, by leveraging it, we are able to perform accurate and real-time vehicle speed detection in an IoT-based smart city. Although numerous vehicle speed estimation methods exist, most of them lack real-time detection in different situations and scenarios. To fill the gap, this paper introduces a novel low-altitude vehicle speed detector system using UAVs for remote sensing applications of smart cities, forging to increase traffic safety and security. To this aim, (1) we have found the best possible Raspberry PI’s field of view (FOV) camera in indoor and outdoor scenarios by changing its height and degree. Then, (2) Mobile Net-SSD deep learning model parameters have been embedded in the PI4B processor of a physical car at different speeds. Finally, we implemented it in a real environment at the JXUST university intersection by changing the height (0.7 to 3 m) and the camera angle on the UAV. Specifically, this paper proposed an intelligent speed control system without the presence of real police that has been implemented on the edge node with the configuration of a PI4B and an Intel Neural Computing 2, along with the PI camera, which is armed with a Mobile Net-SSD deep learning model for the smart detection of vehicles and their speeds. The main purpose of this article is to propose the use of drones as a tool to detect the speeds of vehicles, especially in areas where it is not easy to access or install a fixed camera, in the context of future smart city traffic management and control. The experimental results have proven the superior performance of the proposed low-altitude UAV system rather than current studies for detecting and estimating the vehicles’ speeds in highly dynamic situations and different speeds. As the results showed, our solution is highly effective on crowded roads, such as junctions near schools, hospitals, and with unsteady vehicles from the speed level point of view.

Renewable energy generation using electromechanical speed bump

AbstractThe design of pollution-free energy recovery systems has become an important goal by researchers as renewable energy is an alternative to traditional energy that depends on fossil fuels. In this work, a multifunctional electromechanical speed bump was invented to be used on the streets to generate clean, sustainable energy by utilizing and investing the kinetic energy of vehicles passing on the roads. The current model was designed to perform three functions simultaneously.To measure the performance of the innovative speed bump system, a (simplified) prototype was made that simulates the work of the multifunctional bump. The results showed that the proposed initial speed bump model is a promising technology that can be applied as a clean, renewable energy source that can be easily applied in crowded streets.

Conventroad.com: a fashion curation experiment

Learning outcomes The case is an example of the dilemma and constraints an entrepreneur faces as they go forward in implementing ideas while setting up an enterprise. Through the eyes of John, the case helps the participants to understand and analyse two distinct business models, the bricks and clicks model and an online aggregator model and evaluate them using a visual business tool like the business model canvas (BMC). Thus, the case helps the participants to:▪ Analyse the customer segments and demand.▪ Apply frameworks for analysing a new venture’s prospects.▪ Understand two distinct business models and learn how to sketch a business model using the BMC.▪ Compare various business model designs using the BMC template. Case overview/synopsis Set against the backdrop of high consumerism and haute couture, conventroad.com is an example of fashion aggregation and curation in the online platform. Once known as the fashion hub of Kerala with its crowded streets, cramped with boutiques on each corner, Convent Road lost its following as big and major stores left the miniscule space for better facilities in the name of development. This case follows Rijin John, founder and developer, through the course of his idea conceptualisation. In an attempt to regain its popularity through the internet, John set out to rope all the popular Convent Road boutiques into one platform. But, as more options became available, John was in a dilemma about whether he should continue to try to convince the indifferent boutique owners to be a part of his enterprise or explore an alternative model and create a platform for weavers while sacrificing the brand value of Convent Road. Complexity academic level The case is designed for use in an undergraduate or graduate-level course on entrepreneurship, marketing, business policy and managing growing ventures. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

More Human Than Human: The Exile in Blade Runner

More Human Than Human: The Exile in <i>Blade Runner</i>

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Artificial Intelligence (AI) is changing every technology we are used to deal with. Autonomy has long been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Big auto manufacturers as well are investing billions of dollars to produce Autonomous Vehicles (AVs). This new technology has the potential to provide more safety for passengers, less crowded roads, congestion alleviation, optimized traffic, fuel-saving, less pollution as well as enhanced travel experience among other benefits. But this new paradigm shift comes with newly introduced privacy issues and security concerns. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected. They collect huge troves of information, which needs to be protected from breaches. In this work, we investigate security challenges and privacy concerns in AVs. We examine different attacks launched in a layer-based approach. We conceptualize the architecture of AVs in a four-layered model. Then, we survey security and privacy attacks and some of the most promising countermeasures to tackle them. Our goal is to shed light on the open research challenges in the area of AVs as well as offer directions for future research.

SPATIOTEMPORAL FEATURES OF MOSUL CITY ROAD NETWORK

Mosul is the second-largest city in Iraq, the movements of people within the city have become more restricted by the crowded streets during rush hours. This issue has also become critical since it impacts most of the life aspects of the city (e.g., going to work, schools, etc.). Therefore, there is a need to mitigate this issue using low-cost strategies and solutions due to the current economic issues in the country. In this work, a network-based model is generated that represents the road network of both sides of the city (east and west coasts). The generated network is analysed based on its spatial and temporal features. Then, the elite intersections (crossroads) are extracted, which represent the most effective factors in the road network of the city. After that, low-cost sensor technologies are suggested and can contribute to mitigating the traffic jam issue in the city. Finally, the proposed solutions and suggestions can be generalized to any city that is close in the nature to the considered city in this study.

Noise prediction for urban air taxi operation

Solutions to escape crowded streets are increasingly taking up new forms of mobility. This also includes air taxis or VTOLs. In addition to passenger traffic, suggestions, such as parcel delivery by drones, are also regularly part of future visions. Air taxis pose additional safety requirements due to the transport of people and they also represent a major potential source of noise. A challenge that urban planners, pollution control officers and decision-makers have to face. Using the concrete example of an urban landing place for air taxis at the main train station in the city of Ingolstadt, possible problems, issues related to noise protection and their legal basis were examined. This presentation is a summary of the projects results. The examinations include the creation of noise mapping in order to simulate the impact to the already existing noise situation. Those were based on current flight noise regulations with necessary alterations regarding VTOLs. Because air taxi noise is expected to be more annoying than regular traffic noise, the possible application of flight noise indexes such as the "Frankfurt flight noise index FFI 2.0" shall be reviewed. Based on the results of the previous examinations, possible noise protection measures shall be developed.

GaitWear: a smartwatch application for in-the-wild gait normalisation based on a virtual field study assessing the effects of visual and haptic cueing

ABSTRACT We explore the use of Virtual Reality as a way to simulate field studies via what is known as Virtual Field Studies. This is particularly relevant when inviting participants to the lab is not feasible, or in the case of our work to simulate locomotion in crowded streets from the safety of the lab. We rely on this to assess the effects of four different cues in normalising gait performance in a simulated environment: two baselines from literature (visual and haptic) that have been traditionally explored in the context of a controlled lab environment, and two novel haptic cues that combine temporal and spatial feedback. We compare these in a holistic manner for the first time, capturing not only gait and gaze performance, but usability, perceived workload, and participant preference. Our haptic baseline performed according to the results described in the literature, and together with participants' gaze behaviour and sense of embodiment we start to validate Virtual Field Studies in this domain. We further report that the haptic baseline was the preferred cue by participants, and led to an overall better performance. We conclude with our implementation of GaitWear, a smart watch application that produces this haptic baseline on the fly.

The Impact of the COVID-19 Movement Restrictions on the Road Traffic in the Czech Republic during the State of Emergency

The COVID-19 pandemic crisis has impacted numerous areas of people’s work and free-time activities. This article aims to present the main impacts of the COVID-19 movement restrictions on the road traffic in the Czech Republic, measured during the first epidemic wave, i.e., from 12 March to 17 May 2020. The state of emergency was imposed by the Czech government as a de jure measure for coping with the perceived crisis, although the measure eventually resulted only in a quite liberal de facto form of stay-at-home instruction. Unique country-scale traffic data of the first six months of 2020 from 37,002 km of roads, constituting 66% of all roads in the Czech Republic, were collected and analyzed. For the prediction of the prepandemic traffic conditions and their comparison with the measured values in the period of the state of emergency, a long-term traffic speed prediction ensemble model consisting of case-based reasoning, linear regression, and fallback submodels was used. The authors found out that the COVID-19 movement restrictions had a significant impact on the country-wide traffic. Traffic density was reduced considerably in the first three weeks, and the weekly average traffic speed in all road types increased by up to 21%, expectedly due to less crowded roads. The exception was motorways, where a different trend in traffic was found. In sum, during the first three weeks of the state of emergency, people followed government regulations and restrictions and changed their travel behavior accordingly. However, following this period, the traffic gradually returned to the prepandemic state. This occurred three weeks before the state of emergency was terminated. From a behavioral perspective, this article briefly discusses the possible causes of such discrepancies between de jure and de facto pandemic measures, i.e., the governmental communication strategy related to loosening of movement restrictions, media reality, and certain culture-related traits.