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Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery
No full textSmart governance is an area, that is increasingly becoming important, not only in advanced countries, but all across the globe. Thanks to global scale network connectivity, permeance of smart-devices of various form-factors, and overall improvement in digital literary, we are now seeing smartness everywhere, or if not, the general public is expecting the same. Ultimately, the goal of smart governance is to facilitate state-of-the-art technologies to improve citizens’ lives. With the ubiquity of smart phone technologies today, citizens more readily participate in collaboration with public officials for improved quality of life and their communities. By utilizing optimal tools, public officials can maximize the benefits from citizen participation and leverage their insights to make informed decisions. With more responsive systems, public officials can increase citizen satisfaction and engagement encouraging greater participation. This will lead to more effective and collaborative governance. Also, adoption of new technologies can demonstrate a commitment to innovation and continual improvement, demonstrating to citizens that their local government is proactive and forward-thinking.
311 service is popular in the US, and is available to many cities for reporting non-emergent civic related issues around their communities. 311 based systems are widely used for reporting things like overflowing garbage, illegal dumping, evidence of drug activity on streets, medical waste and graffiti. Previously, the 311 service was primarily available through phone calls. However, the 311 service has expanded to include various channels as technology has advanced. Citizens can now contact the 311 service using a variety of channels such as a mobile app, a website, and Twitter. With the popularity of 311 mobile app, more and more citizens take photos and report issues with just a few clicks using the mobile app. The overall goal of this dissertation is the design, deployment and validation of computer vision technologies to solve problems of critical importance in smart governance. Specifically, our focus is to automate the detection and classification of garbage on streets, and detecting drug use. Both problems are of not only national importance, but global too.
For this dissertation, we have collected photos on San Francisco 311 which were taken and uploaded by citizens of San Francisco. Using the image data from San Francisco 311, we present the computer vision techniques to detect and localize objects of interests automatically. These images are citizen-generated, so they vary in resolutions and angles containing objects of different sizes. Also, they contain backgrounds from various locations in San Francisco. Utilizing a diverse range of images contributes to building a more stable and robust object detection model. we were able to compare and evaluate different convolutional neural network object detection models to identify different objects related to 311 service categories.
We first observed and compared 311 datasets from three major cities in the US, namely Los Angeles, San Francisco and Boston because they are major cities known for their successful 311 services. we found out that garbage issue was one of the major issues across all three cities. Also, we discovered that San Francisco 311 publicly shares its image data. Then, we conducted statistical analysis on the San Francisco 311 dataset. we plotted 311 requests on the San Francisco map. we observed that Street and Sidewalk Cleaning was the most reported 311 request service which took up 36% of all 311 requests. The Street and Sidewalk Cleaning service was comprised of the following service detail categories: Other Loose Garbage accounting for the highest at 12% followed by Furniture at 5% as the second highest. Then, we performed garbage object detection on the San Francisco 311 image data using two pre-trained models, namely Faster R-CNN and RetinaNet. The models detected the following four classes: garbage, cardboard box, garbage can and garbage can overflow. RetinaNet outperformed Faster R-CNN with mAP = 0.87.
Next, we tackled another important worldwide social problem, which is detecting illegal drug use. For centuries, illegal drug use has been a major problem in society globally despite a lot of effort and resources invested to combat the issue. In the United States, drug overdose is the leading cause of injury-related deaths which caused CDC to declare drug overdose over America as an epidemic. One of the critical challenges in the war against drugs is that people who inject drugs discard syringes and drug-related objects in public leading to many civic problems not only due to increased drug use but also threat to public safety and health. Additionally, the primary cause of blood-borne infectious diseases such as hepatitis C, hepatitis B and HIV is sharing contaminated injecting instruments such as syringes. We explored the possibility of using crowd support to combat illegal drug use by performing drug-related object detection using three pre-trained models, Faster R-CNN, EfficientDet and YOLO v5. The models detected the following nine classes: biohazard box , cooker , orange cap , plunger , syringe , syringe packaging , tourniquet , vial and white cap . YOLO v5 performed the best with mAP = 0.64 on the test dataset.
In addition, we have investigated hyperparameters for these convolutional neural network object detection models, namely Faster R-CNN, RetinaNet, EfficientDet and YOLO v5. Hyperparameters are settings to run the object detection models effectively during training. Thus, setting hyperparameters appropriately for different tasks is imperative to develop efficient and high performing inference models. We have found that there are common hyperparameters among models, such as the learning rate, the batch size and the number of epochs. Also, we have found each object detection model can accept a set of different configurations. For example, the Faster R-CNN model allows to pick an optimizer among RMSProp optimizer, Momentum optimizer, and Adam optimizer. The RetinaNet model can be configured with the anchor config file, which accepts the anchor sizes, strides, ratios and scales in each line. YOLO v5 utilizes a YAML file to set hyperparameters. A YAML file is a text-based file often used for configuration.
Our evaluation results show that our system can be an effective tool for next generation smart governance systems for identifying garbage and drug-related objects in the public domain. Moreover, our work may have global impact as many parts of the world suffer many of similar social issues. We are currently a web-based demonstration of our work, and in the future, hope to engage civic officials in deploying our technologies for real use
Development of Antiviral Peptidomimetics
No full textProtein-protein interactions (PPIs) are essential for biological processes and are associated with a number of diseases, including cancer, infectious diseases, and neurodegenerative diseases. As a result, modulation of PPIs has been recognized as one of the most promising strategies to develop the novel drugs. Peptide modulators always exhibit higher specificity and affinities with targets than small compounds or monoclonal antibodies, but their broad medicinal effectiveness is constrained by their poor bioavailability and biostability. Peptidomimetics, which have been developed to mimic the structure as well as function of bioactive peptides and proteins, have shown excellent potential in protein surface mimicry and recognition, modulation of PPIs, catalysis, and other fields. In comparison to conventional α-helixes, these peptidomimetics with unique and unnatural monomers showed enhanced bioavailability and chemodiversity as well as higher resistance to proteolytic degradation. Inspired by this concept, our group had developed a new peptidomimetics-γ-AApeptide, which could fold into well-defined protein-like secondary and tertiary structures, and they display remarkable biological potential for the recognition of protein and nucleic acids. As a result, γ-AApeptides could be developed into useful tools and drug candidates that probe or modulate medicinally relevant cellular processes.In this study, we describe the development of bioactive antiviral peptidomimetics based on γ-AApeptides. First, we identified a new pan-coronavirus fusion inhibitor to SARS-CoV-2 using the one-bead-two-compound macrocyclic γ-AApeptides combinatorial library. According to this study, combinatorial libraries provide an excellent platform for the development of antiviral inhibitors and other protein-protein interactions’ inhibitors. Second, using the rational design strategy, we developed a series of helical mimetic sulfonyl-γ-AApeptides to prevent the fusion process of diverse viruses. These two investigations suggested that it is an extremely promising strategy to the development of new drugs by using of L-sulfonyl-AApeptides or D-sulfonyl-AApeptides to modulate a range of protein-protein interactions. A number of applications of γ-AApeptides in the biological field were further supported by all of these investigations
Restrictions are lifted: The effect of risk perception of COVID-19 on future travel intentions of Dutch travellers
No full textThis study aims to understand better the psychological impact of COVID-19, the risk perception, travel and destination risks of Dutch travellers and their intention to travel when travel restrictions due to COVID-19 are lifted. This study takes a step toward closing the gap in the literature as it provides new insights into the risk perceptions regarding COVID-19 and the travel intentions of Dutch travellers now that travel restrictions are lifted. This study employed a quantitative approach to market research. Questionnaire research was applied. The questionnaire is created with the web-based survey tool Qualtrics. 343 respondents filled in the questionnaire. The results indicate that the psychological impact of COVID-19 was high on Dutch people. The majority feels that COVID-19 changed their everyday life, and it changed hygiene standards. Overall, this study\u27s psychological impact is greater on women than on men. Based on the findings of this study, it can be concluded that Dutch travellers perceive the risk of contracting COVID-19 while travelling to be high
The impact of globalization on domestic growth in Africa
No full textResearch into the impacts of globalization on domestic growth in Africa has been scarce and the results of the research that does exist have been mixed. This research addresses this gap in the literature by using the newly revised KOF Globalization Index to determine the impact of social, political, and financial globalization on African economies. The KOF Index was revised substantially in 2019. Our full data set includes 40 years of data, from 1980-2019. Findings indicate that the relationship between globalization and GDP is best represented by a non-linear cubic model. With that model, social globalization has become Africa’s most important predictor of GDP, particularly in the most recent ten-year period. Economic globalization was also a small, but significant, predictor. Implications for policymaking are also discussed
Tyrol: Evolution Of A 10-Axis Biped Robot
No full textThis paper presents work demonstrating the evolution of a biped robot named Tyrol from a simulation environment to physical realization. For the past few years, humanoid robot development has been receiving increasing interest by several research groups. The design of this class of robots is quite challenging because of a variety of reasons such as the high number of degrees of freedom involved, balancing issues, power to weight ratio, and complexity of their control. By studying the development of a biped robot, this work addresses humanoid robot design and control in a bottom-up approach. For this purpose, a ten-degree-of-freedom biped robot concept was developed, modeled and constructed. Different gait algorithms have been developed for the biped robot to navigate on flat and inclined surfaces
Position Tracking Performance of a Redundant Teleoperation System
No full textTeleoperation has captured the interest of robotics researchers for more than two decades. Many focused on the stability problem when the system experiences time delays. Most of the time, guaranteeing stability has overshadowed the tracking performance. This work differentiates teleoperation systems into two groups as limited and unlimited-workspace teleoperation depending on their position tracking priorities. Specifically, this paper examines limited-workspace teleoperation on a redundant system. The slave is modeled to be the virtual representation of a Fanuc LR Mate 100iB, a five degree-of-freedom (DOF) serial industrial manipulator. The master is selected as a two-DOF force-reflecting joystick. Hence, the teleoperation system is redundant since the degree-of-freedom of the slave is greater than the master. Teleoperation experiments have been conducted for this system under constant time delays and communication losses. The results are presented when the customary and modified wave variable techniques are utilized
Determination of Impact Force and Crush Energy Using Abductive Networks
No full textSensory based methods as well as approximation methods are currently being used to determine the impact force and the crush energy pertained to vehicles’ collision. This paper describes a method, based on Abductive Networks that can be used to develop explicit models by which the above quantities can be estimated. Similar to Neural Networks Abductive Networks are “trained”, using experimental data and upon convergence, a model is established. Comparisons between the results, obtained by the different methods, indicate that the models obtained with this method provide more accurate results
Virtual Urban Siege: Modern Urban Siege and Swarming in Culiacán 2019 & 2023
No full textModern urban siege is a metaphor for evolved urban campaigns. The template for such attacks draws from the tactics seen in the 26/11 Mumbai attack in 2008, and continued with the 2013 Westgate Mall attack in Kenya, the January 2015 Charlie Hebdo and Hyper Cacher attacks in Paris and the November 2015 attacks against the Stade de France and Bataclan. These virtual sieges employ swarming tactics, techniques, and procedures (TTPs) to provide a template for urban strife and insecurity. This article provides an overview of terrorist swarming tactics, expanding the aperture to review the use of similar TTPs by criminal gangs in Brazil in the Novo Cagngaço style high intensity robberies and raids. The article will then review the October 2019 Battle of Culiacán or Culiacanazo, where elements of the Cártel de Sinaloa (CDS) employed urban siege TTPs to counter the arrest of cartel leaders by state security forces. The second incident occurred in January 2023 when the CDS again employed swarming TTPs in an unsuccessful attempt to thwart the arrest of Ovidio Guzmán
Urban Warfare: The Recent Israeli Experience
No full textThis article analyzes the evolution of urban warfare tactics, technologies, and approaches in Israel. The article briefly addresses the nature and constraints of modern urban warfare, examines Israel’s early experience with urban warfare during the 1982 Lebanon War, and then describes and assesses the development of Israeli urban warfare in a range of wars and operations starting with Defensive Shield in the West Bank, then moving to the Second Lebanon War and then addressing a number of conflicts between Israel and Hamas in the Gaza Strip between 2007 and 2021. This article will also identify a few overarching trends in the evolution of Israeli urban warfare
The Political Trajectory of Urban Violence: Organized Crime in Michoacán’s Apatzingán
No full textContrary to the “narco-centric” explanation of homicidal violence in Mexico, this article proposes “the political trajectory of urban violence” (PTUV) as an additional analytical category to nuance the developmental process of today´s large-scale violence in Mexican urban enclaves. Building on previous research, this article argues that organized crime-related violence in Mexican cities today has unveiled –and exacerbated– intricate power tensions among private actors –both illegal and, perhaps more importantly, legal ones– which need to be explored by considering the historical evolution of these political processes within a given urban context. The PTUV, then, regards recent organized crime-related violence as part of a continuum of the socio-political complex in urban environments, and not only due to criminal conduct or activity per se. Because a concrete case study is central to advance on this research agenda, the article posits that repeated outbreaks of homicidal violence in the city of Apatzingán, Michoacán, Mexico, have been the result of a rooted local conflict over land access, economic hegemony, political dominance and increased urbanization