Unauthorized Areas Research Articles

ORION: Verification of drone trajectories via remote identification messages

With the widespread adoption of drones in daily life, next-generation smart cities need to establish highways, i.e., trajectories where drones can fly and operate safely. However, due to the untrusted nature of their ecosystem, drones might misbehave and take disallowed trajectories, e.g., to reduce the time to fly to a destination, reduce energy consumption, visit unauthorized areas, or disrupt operations of sensitive sites. In this paper, we address the cited problem by proposing ORION, a new framework for online drone trajectory verification. ORION requires one or more receivers distributed in a given area capable of receiving and analyzing standard Remote Identification (RID) messages emitted by operational drones. ORION compares the locations reported in such messages with the closest set of coordinates in the allowed trajectory. It raises an alarm if the distance between such locations exceeds a threshold calibrated offline. We validate the performance of ORION through data collected from both a real drone flight in Amsterdam (Netherlands) and taxi trajectories in Porto (Portugal), achieving a True Positive Ratio (correct detection of disallowed trajectories) up to 0.95 and a False Positive Ratio (incorrect detection of disallowed trajectories) up to 0.04. Our solution significantly outperforms existing approaches used for drone detection or time-series analysis. Finally, we also release the gathered data as open-source to foster future research.

Nature-Based Solutions (NBS) in spatial planning for urban flood mitigation: The perspective of flood management experts in Accra

The rapid rate of urban expansion with its associated physical development in recent years conflicts with the urban ecosystem and the services it provides. In most Sub-Saharan African cities, rapid urban expansion often does not conform to existing spatial plans. Physical developments are sometimes carried out in unauthorized areas, contributing to urban floods. The Sub-Saharan African regions' flood management strategies mainly focus on engineering solutions but have not been fully functional in mitigating urban floods. There is a scarcity of knowledge on how urban flood-related NBS measures can be part of the spatial development in Sub-Saharan African cities for effective flood management. In order to address this gap, this study employed content and text analysis of policy documents and interviews to understand how current spatial and flood mitigation schemes in Accra, Ghana reflect possible NBS applicability and identify possible approaches to integrating NBS into existing planning schemes to prevent urban floods. The study found that Accra’s spatial plans and flood mitigation schemes reflect a possibility of NBS integration. Additionally, the study unveiled techniques for integrating NBS measures and possible implementation barriers and facilitation in the Ghanaian context, which can be linked to combating the challenges that the Ghanaian spatial planning and flood management authorities face. The research, therefore, contributes to knowledge of how NBS can be integrated into spatial planning systems and flood mitigation schemes in Sub-Saharan African regions.

A New Surveillance and Security Alert System Based on Real-Time Motion Detection

Due to the frequent and widespread instances of burglary, effective and accurate intrusion detection with an alarm system is now necessary. In this study, the proposed system is used for secret and vital places that need a good monitoring system based on human motion detection. The system can protect museums that contain critical historical objects and libraries with old historical books. The security alert system is also essential to the protection of banks. The system uses a two-frame difference algorithm and a simple background modeling algorithm for motion detection with the help of AForge.NET. Whenever the system detects motion, it interprets the frames of motion to determine humans by using YOLO. The security alert system activates the alerts whenever it detects human motion, like sending an email to an authorized person, triggering the LED alert and sound alert, recording a video of that place, taking a motion picture, and saving it within the databases. The system has the advantages of low cost, a user-friendly interface, and high security. The system was thoroughly tested to detect human movement in unauthorized areas. The system successfully detected human activity indoors and outdoors and activated the alarms. Also, the system could detect human movement in all four directions and alert observers directly at the time of the incident. In low light or minimum illumination, the system can determine human motion. The evaluation results showed that the system's accuracy in detecting human movement was 95%, which shows that the system is able to protect vital and secret places and can successfully monitor areas.

Smart Surveillance System for Illegal Garbage Dumping

Effective garbage management is a key challenge faced by urban areas across the world Garbage dumping in unauthorized places is a common problem in most cities, and it poses a serious threat to public health and the environment. To address this issue, we propose a real-world surveillance platform that detects and reports instances of garbage dumping in unauthorized areas using vision-based action recognition techniques. Our approach involves training a deep neural network on a dataset of garbage dumping actions to recognize and classify instances of this behaviour in real-time video footage. The system operates in three stages detection, tracking, and classification. In the detection phase, we use object detection techniques to locate potential dumping events in video frames. In the tracking phase, we track the detected object across subsequent frames to obtain a trajectory that helps in understanding the context of the action. In the classification phase, we classify the action as garbage dumping or non-dumping using a convolutional neural network. Our system achieves an accuracy of 96.2% on a test dataset, demonstrating its effectiveness in detecting garbage dumping events in real-world surveillance scenarios. The proposed system can be integrated into existing surveillance infrastructure to improve the efficiency of garbage management systems and enhance public health and environmental protection.

Web Attack Prediction using Stepwise Conditional Parameter Tuning in Machine Learning Algorithms with Usage Data

There is a rapid growth in internet and website usage. A wide variety of devices are used to access websites, such as mobile phones, tablets, laptops, and personal computers. Attackers are finding more and more vulnerabilities on websites that they can exploit for malicious purposes. A web application attack occurs when cyber criminals gain access to unauthorized areas. Typically, attackers look for vulnerabilities in web applications at the application layer. SQL injection attacks and Cross Site script attacks is used to access web applications to obtain sensitive data. A key objective of this work is to develop new features and investigate how automatic tuning of machine learning techniques can improve the performance of Web Attack detections that use HTTP CSIC datasets to block and detect attacks. The Stepwise Conditional parameter tuning in machine learning algorithms is a proposed model. This model is a dynamic and automated parameter choosing and tuning based on the better outcome. This work also compares two datasets for performance of the proposed model.

Emotional support animals supporting college students’ mental health and well-being: A qualitative analysis exploring practices, policies, and perceptions

Objectives: Describe the emotional support animal (ESA) experience of college students detailing the process of obtaining an ESA, as well as the benefits and obstacles. Participants: Nine students who had an ESA at college provided preliminary information while an additional four offered insights into their COVID experience with their ESA. Archived records from the Accessibility Resource Center added detail on the ESA process. Methods: This mixed-method study included qualitative interviews (9 students prior to COVID and 4 during COVID) as well as a quantitative analysis of archived data. Thematic analysis was used to extract themes from the interviews. Archived data were analyzed for frequency of select topics. Results: Four positive themes (presence of animal, empowerment, symptom alleviation, and social catalyst) and three negative themes (housing accommodations, lack of ESA education on campus, and social consequences) were extracted from initial interview responses. Analysis of COVID interviews also revealed positive and negative themes with many similar to the pre-COVID responses but also included unique themes reflective of the restrictions imposed by the pandemic. Archived data revealed a substantial increase in the number of ESAs on campus, a wide range of species, and an array of complaints such as safety concerns, ESA behavior, ESA cleanliness, and ESA in unauthorized areas. Conclusions: Overall, the college ESA experience appears beneficial, facilitating the adjustment to college for students with mental health concerns. However, there are drawbacks. Knowledge of obstacles and concerns will help ease the ESA process for all constituents.

Impacts of tax refund on enterprise’s decisions on recycled materials production: A cross-regional perspective

Recently along with the development of waste recycling markets, a distinct management scenario which extends the traditional municipality-level management scenario to a cross-regional management scenario emerges. Under the cross-regional management scenario, on the one hand, disparities in value-added tax refund policy aggravate imbalanced development of construction and demolition waste recycling markets between regions. On the other hand, how preferential taxation policies would influence decisions of waste recycling enterprises are unclear. To fill the research gap, this paper investigates impacts of value-added tax refund policies on enterprise’s cross-regional recycling decisions by establishing game models that involve two recycling enterprises and two transportation enterprises. Through developing and analyzing game theory based models, the optimal decisions of involved enterprises are obtained. The findings reveal that (i) when the disparities in transportation costs and market capacities between two regions are moderate, recycling enterprises should choose cross-regional production rather than local production; (ii) enlarging market capacities after cross-regional recycling could simultaneously increase recycling quantities of waste in original region. But moderate market capacities and high value-added tax refund rate promote both recycling enterprises being better off in cross-regional production scenario; and (iii) raising value-added tax refund rate is not always necessary under certain conditions, where higher value-added tax refund rate reversely decrease recycling enterprise profits in current region. To enhance the effectiveness of value-added tax refund policy, reducing cross-regional transportation costs and balancing regional market capacities should be applied by the local government. The findings are valuable in expanding the research scope of traditional construction and demolition waste recycling markets and increasing the efficiency of applying tax policies in promoting waste recycling. There are two research limitations; one is that we did not consider the illegal waste dumping (i.e., dumping waste into unauthorized areas) frequently occurring in the process of waste transportation, and the other is that we considered unified preferential taxation for both of the recycling enterprises.

Blockchain-Powered Policy Enforcement for Ensuring Flight Compliance in Drone-Based Service Systems

Drones, or unmanned aerial vehicles, can be used for commercial services such as short-dis-tance delivery. In order to ensure quality services, multiple drone-based delivery service providers can be employed in delivery service systems. In this article, we address two very important and unexplored challenges of employing drones in delivery services. First, involving multiple drones from different service providers elevates the chance of collision during flights. Second, drones may hamper the privacy of citizens by unauthorized access to private and restricted areas. In order to solve the aforementioned issues, we propose a blockchain-based policy enforcement mechanism in the drone-based delivery service systems. At first, the mechanism will set policies to establish pre-allocated flight paths for different drones at different times to avoid collisions, and ensure the privacy of citizens by restricting their access to unauthorized areas. Later, the blockchain will enforce the policies to monitor compliance of the drone flights and identify non-compliant drone services to penalize corresponding service providers. We simulate a virtual drone-based delivery system with the Ethereum blockchain platform and examine the performance and feasibility of our proposed mechanism.

A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems.

Improving performance and safety conditions in industrial sites remains a key objective for most companies. Currently, the main goal is to be able to dynamically locate both people and goods on the site. Security and access regulation to restricted areas are often ensured by doors or badge barriers and those have several issues when faced with people being in places they are not supposed to be in or even tools of objects being used incorrectly. In addition to this, a growing use of new devices requires precise information about their location in the environment such as mobile robots or drones. Therefore, it is becoming essential to have the tools to dynamically manage these flows of people and goods. Ultra-wide-band and motion capture solutions will be used to quickly identify people who may be in unauthorized areas or performing tasks which they have been uninstructed to do. In addition to the dynamic tracking of people, this also overcomes some issues associated with moving objects or tools around the production floor. We offer a new set of data that provides precise information on worker movement. This dataset can be used to develop new metrics regarding worker efficiency and safety.

An Overview of Hazelnut Markets and Policy in Turkey

Turkey is the biggest actor in the world hazelnut market with its production potential and policies. The aim of this paper was to assess the recent developments in the Turkish hazelnut market and policy. The time series data of hazelnut markets was taken from the internet databases of Food and Agriculture Organization (FAO), Turkish Statistical Institute (TSI), Black Sea Hazelnut Exporter Union (BSHEU), Ministry of Agriculture and Forestry (MoAF), Giresun Commodity Exchange (GCE) and Official Journal and Turkish Republic (OJoTR). Under the New Hazelnut Strategy, an area based payment has been provided to the hazelnut farmers in the authorized areas and a compensatory payment had been provided to the farmers in the unauthorized areas. Since 2001, while hazelnut areas and the export of Turkey had increased, hazelnut yield and production had decreased. Despite increases in hazelnut prices, Turkey could increase hazelnut export both in terms of quantity and value. While there is no need to limit hazelnut areas in high crop years, the government should establish a hazelnut buffer stock mechanism. The Turkish government should also create fair competition conditions for the actors in the hazelnut market with a more effective hazelnut policy.

Solid Waste Management Practices and Challenges: The Case of Halaba Town in Southern Ethiopia

Solid waste, which is a consequence of day-to-day activity of human kind, needs to be managed properly. Due to rapid increase in urbanization and population, the generation rate of municipal solid waste in Halaba town is also increasing due to which the town is facing several difficulties in providing proper solid waste management services to its population. Accordingly, the objective of this particular study was to assess the existing solid waste management practices and challenges in Halaba town in southern Ethiopia. Questionnaire, interview, field measurement and field observation were the instrument employed to collect valid data. Data was gathered from 150 randomly selected sampled households using open ended and close ended questionnaire and from purposely selected key informants using semi structured interview. Based on the findings of this study, the households’ solid waste generation rate is 0.271kg/person/day. The result showed that waste composition in the study area was dominated by a high organic content; food waste and vegetable peelings (43.18%) followed by ash and dust (35.81%) leaves, wood scarp, paper and cardboard (11.88%) and metal, glass, ceramics, plastics and textiles (8.52%). The study revealed that only 18% of the household’s solid waste was collected by municipality. As a result of this, huge amounts of uncollected solid wastes are indiscriminately disposed in unauthorized areas. Finally, the study indicated the weak financial status of the municipality to provide adequate solid waste management services along with low awareness of the community were the series problem that challenges the practice of solid waste management system in Halaba town. Therefore, adoption of sustainable solid waste management systems (reuse, recycle and composting) through awareness creation campaign to enable the people aware of the importance of safe solid waste disposal for their environment and health should be encouraged. Keywords: Household, Key informants, Solid waste generation rate, Solid waste management DOI : 10.7176/JEES/9-9-03 Publication date :September 30 th 2019

Big data analytics to identify illegal construction waste dumping: A Hong Kong study

Illegal dumping, referring to the intentional and criminal abandonment of waste in unauthorized areas, has long plagued governments and environmental agencies worldwide. Despite the tremendous resources spent to combat it, the surreptitious nature of illegal dumping indicates the extreme difficulty in its identification. In 2006, the Construction Waste Disposal Charging Scheme (CWDCS) was implemented, regulating that all construction waste must be disposed of at government waste facilities if not otherwise properly reused or recycled. While the CWDCS has significantly improved construction waste management in Hong Kong, it has also triggered illegal dumping problems. Inspired by the success of big data in combating urban crime, this paper aims to identify illegal dumping cases by mining a publicly available data set containing more than 9 million waste disposal records from 2011 to 2017. Using behavioral indicators and up-to-date big data analytics, possible drivers for illegal dumping (e.g., long queuing times) were identified. The analytical results also produced a list of 546 waste hauling trucks suspected of involvement in illegal dumping. This paper contributes to the understanding of illegal dumping behavior and joins the global research community in exploring the value of big data, particularly for combating urban crime. It also presents a three-step big data-enabled urban crime identification methodology comprising ‘Behavior characterization’, ‘Big data analytical model development’, and ‘Model training, calibration, and evaluation’.

Truck Parking Utilization Analysis Using GPS Data

Unavailability of sufficient parking spaces during various periods at rest areas results in illegal and unsafe parking at on/off-ramps and other unauthorized areas, which may lead to traffic safety hazards. In this research, the authors attempt to understand truck parking utilization by developing econometric models by using truck global positioning system (GPS) data to predict truck parking utilization at rest areas to improve truck parking management and ensure proper use of parking spaces. Count models, including Poisson and negative binomial models, were developed in addition to generalized ordered-response probit (GORP) models to understand the factors that affect truck parking utilization. The GORP model that subsumes the Poisson model as a special case was found to provide the best data fit. The model results suggest that several factors positively contribute to truck parking utilization (e.g., truck volume on the adjacent roadway, number of lanes) at rest areas, whereas factors such as on/off-ramp violations decrease truck parking utilization. In addition, parking utilization was found to vary considerably throughout the day.

Application and Comparison of Analytical Hierarchy Process (AHP) and Network Methods in Path Finding of Pipeline Water Transmission System, from Taleghan’s Dam to Hashtgerd New City, Tehran, Iran

These instructions give you guidelines for preparing determination of optimum path by considering technical and engineering, environment and cost management visions. In this point of view from Taleghan’s dam to Hashtgerd New City case study, we need to distinguish and apply the essential parameters such as topographic and morphologic conditions, environmental issues by consideration on sustainable development, population distribution patterns, roads and etc. by using base map and extraction of expected points geometrical location from Google Earth, position land surveying done. Then the mentioned co-parameters data layer loaded in GIS environment and after allocation the special coefficient and value for weighting parameters and combine them based on MCE method and the cost map made based on AHP method which Lead to determination of optimum path by using LCPA method. Paths include of ABFA path and two evaluated optimum path compared and indicated that two optimum paths overlapped mostly. Cost comparison between optimum path and ABFA path imply 14% decrease in expenditure Which the main extra expense of ABFA path due to more intersection with rivers, roads and necessity construct of structures to keep water natural regimes, passing unauthorized areas and personal parcels need to pay, path finding only by personal experience underestimating academic science, data analyzing software’s which Cause to increasing the length of water supply pipeline.

Offine/online Optimum Routing of a UAV using Auxiliary Points

<p>This paper presents a method to determine the route of a three-dimensional UAV. Three criteria; the height, the length of flight path and the unauthorized areas are used as the constraints and combined in a fuzzy function as the evaluation function. The article aimed to discover a minimum cost route from source to destination considering the constrains. In this paper a new searching method is proposed, with use of auxiliary points. The auxiliary point method iteratively divides a straight line to two shorter lines with less cost of evaluation function. Implementation results show that the proposed method dramatically decreases the calculations; meanwhile the ight route is sub-optimum.</p>

Logging concessions enable illegal logging crisis in the Peruvian Amazon.

The Peruvian Amazon is an important arena in global efforts to promote sustainable logging in the tropics. Despite recent efforts to achieve sustainability, such as provisions in the US–Peru Trade Promotion Agreement, illegal logging continues to plague the region. We present evidence that Peru's legal logging concession system is enabling the widespread illegal logging via the regulatory documents designed to ensure sustainable logging. Analyzing official government data, we found that 68.3% of all concessions supervised by authorities were suspected of major violations. Of the 609 total concessions, nearly 30% have been cancelled for violations and we expect this percentage to increase as investigations continue. Moreover, the nature of the violations indicate that the permits associated with legal concessions are used to harvest trees in unauthorized areas, thus threatening all forested areas. Many of the violations pertain to the illegal extraction of CITES-listed timber species outside authorized areas. These findings highlight the need for additional reforms.

Public Health Implication Of Household Solid Waste Management In Awka South East Nigeria.

Background: Solid waste management remains one of the major challenges of urbanization faced by developing countries. The sanitary state of an area is largely influenced by the waste handling practices of the residents and the measures in place for safe waste evacuation and disposal. Objective: This study was aimed at examining the waste handling practices among households in Awka, an urban area in south eastern Nigeria. Methodology: We conducted a cross-sectional, descriptive study. A total of 200 households were selected using a multi-staged random sampling technique and information was obtained from them using an interview-administered questionnaire. The data obtained was analyzed and relevant proportions calculated. Results: The bulk of the solid waste generated consisted of putrescible matter and cellophane bags. 170 (85%) of the households stored their waste in a closed container outside the house. 73% of the respondents disposed their waste through the inefficient government waste management agency, 27% dumped theirs in unauthorized areas and the remainder patronized private mobile cart pushers. Majority of the respondents (87.5%) did not sort their waste prior to disposal. Despite very good knowledge of waste recycling (95%), only 35 households (17.5%) practiced it. More than half of the respondents expressed dissatisfaction with the level of government involvement in waste management and wished it could do more. Conclusion: There is a need for greater government involvement, community participation and orientation with private sector involvement in waste management in Awka with a view to building capacity for effective delivery of waste management services and ultimately improve the sanitary state of the city thereby reducing preventable disease burden on the populace.

A “smoke-free” hospital in Israel—a possible mission

Background. A revised antismoking law in Israel (August 2001) called for a complete ban of smoking in hospitals. An evaluation of a hospital process and short-term outcome of implementing such policy may guideline its sustainability. Methods. Two cross-sectional, random-sample surveys of employees 3 months before policy implementation, and 6–9 months post-implementation. The pre-implementation survey included 368 employees (90.4% response rate) and the post-implementation survey, 364 (92.8% response rate). Results. The ‘smoke-free’ policy significantly reduced smoking in the unauthorized areas. Before implementation, 63% of staff reported frequently observing smoking in the hospital, compared to 40% 6 months post-policy implementation ( P < 0.001). Significantly more smokers reported leaving their workplace to smoke (17% pre- vs. 62% post-implementation, P < 0.0001). Sixty-five percent of smokers, in both surveys, agreed that “a smoke-free policy is unfair to smokers”. Fewer nonsmokers subscribed to this belief: 42% pre- and 34% post-implementation. Smoker prevalence remained unchanged (19%). Conclusions. Implementation of a “smoke-free” policy is an effective way to reduce smoking in the hospital environment. More effort is required, however, to help staff quit smoking altogether.