De nos jours, il y a une demande croissante pour fournir de l'information temps réel à partir de l'environnement, e.g. état infectieux de maladies, force du signal, conditions de circulation, qualité de l'air. La prolifération des dispositifs de capteurs et la mobilité des personnes font de la Mobile Collaborative Sensing (MCS) un moyen efficace de détecter et collecter l'information à un faible coût. Dans MCS, au lieu de déployer des capteurs statiques dans une zone, les personnes disposant d'appareils mobiles jouent le rôle de capteurs mobiles. En général, une application MCS exige que l'appareil de chacun ait la capacité d'effectuer la détection et retourne les résultats à un serveur central, mais également de collaborer avec d'autres dispositifs. Pour que les résultats puissent représenter l'information physique d'une région cible et convenir, quel type de données peut être utilisé et quel type d'information doit être inclus dans les données collectées? Les données spatio-temporelles peuvent être utilisées par des applications pour bien représenter la région cible. Dans des applications différentes, l'information de localisation et de temps sont 2 types d'information communes, et en les utilisant la région cible d'une application est sous surveillance complète du temps et de l'espace. Différentes applications nécessitent de l'information différente pour atteindre des objectifs différents. E.g. dans cette thèse: i- MCS-Locating application: l'information de résistance du signal doit être incluse dans les données détectées par des dispositifs mobiles à partir d'émetteurs de signaux ; ii- MCS-Prédiction application : la relation entre les cas d'infection et les cas infectés doit être incluse dans les données par les dispositifs mobiles provenant des zones de flambée de la maladie ; iii- MCS-Routing application : l'information routière en temps réel provenant de différentes routes de circulation doit être incluse dans les données détectées par des dispositifs embarqués. Avec la détection de l'information physique d'une région cible, et la mise en interaction des dispositifs, 3 thèmes d'optimisation basés sur la détection sont étudiés et 4 travaux de recherche menés: -Mobile Collaboratif Détection Cadre : un cadre mobile de détection collaborative est conçu pour faciliter la coopérativité de la collecte, du partage et de l'analyse des données. Les données sont collectées à partir de sources et de points temporels différents. Pour le déploiement du cadre dans les applications, les défis clés pertinents et les problèmes ouverts sont discutés. -MCS-Locating : l'algorithme LiCS (Locating in Collaborative Sensing based Data Space) est proposé pour atteindre la localisation de la cible. LiCS utilise la puissance du signal reçu dans tous les périphériques sans fil comme empreintes digitales de localisation pour les différents emplacements. De sorte LiCS peut être directement pris en charge par l'infrastructure sans fil standard. Il utilise des données de trace d'appareils mobiles d'individus, et un modèle d'estimation d'emplacement. Il forme le modèle d'estimation de localisation en utilisant les données de trace pour atteindre la localisation de la cible collaborative. Cette collaboration entre périphériques est au niveau des données et est supportée par un modèle. -MCS-Prédiction: un modèle de reconnaissance est conçu pour acquérir dynamiquement la connaissance de structure de la RCN pertinente pendant la propagation de la maladie. Sur ce modèle, un algorithme de prédiction est proposé pour prédire le paramètre R. i.e. le nombre de reproduction qui est utilisé pour quantifier la dynamique de la maladie pendant sa propagation. -MCS-Routing : un algorithme de navigation écologique ‘eRouting’ est conçu en combinant l'information de trafic temps réel et un modèle d'énergie/émission basé sur des facteurs représentatifs. Sur la base de l'infrastructure standard d'un système de trafic intelligent, l'information sur le trafic est collectée / Nowadays, there is an increasing demand to provide real-time information from the environment, e.g., the infection status of infectious diseases, signal strength, traffic conditions, and air quality, to citizens in urban areas for various purposes. The proliferation of sensor-equipped devices and the mobility of people are making Mobile Collaborative Sensing (MCS) an effective way to sense and collect information at a low deployment cost. In MCS, instead of just deploying static sensors in an interested area, people with mobile devices play the role of mobile sensors to sense the information of their surroundings, and the communication network (3G, WiFi, etc.) is used to transfer data for MCS applications. Typically, a MCS application not only requires each participant's mobile device to possess the capability of performing sensing and returning sensed results to a central server, but also requires to collaborate with other mobile and static devices. In order to make sensed results well represent the physical information of a target region, and well be suitable to a certain application, what kind of data can be used for different applications, and what kind of information needs to be included into the collected sensing data? Spatio-temporal data can be used by different applications to well represent the target region. In different applications, location and time information is two kinds of common information, and by using such information, the target region of an application is under comprehensive monitoring from the view of time and space. Different applications require different information to achieve different sensing purposes. E.g. in this thesis: i- MCS-Locating application: signal strength information needs to be included into the sensed data by mobile devices from signal transmitters; ii- MCS-Prediction application: the relationship between infecting and infected cases needs to be included into the sensed data by mobile devices from disease outbreak areas; iii- MCS-Routing application: real-time traffic and road information from different traffic roads, e.g., traffic velocity and road gradient, needs to be included into the sensed data by road-embedded and vehicle-mounted devices. With sensing the physical information of a target region, and making mobile and static devices collaborate with each other in mind, in this thesis three sensing based optimization applications are studied, and following four research works are conducted: - a MCS Framework is designed to facilitate the cooperativity of data collection, sharing, and analysis among different devices. Data is collected from different sources and time points. For deploying the framework into applications, relevant key challenges and open issues are discussed. - MCS-Locating: an algorithm LiCS (Locating in Collaborative Sensing based Data Space) is proposed to achieve target locating. It uses Received Signal Strength that exists in any wireless devices as location fingerprints to differentiate different locations, so it can be directly supported by off-the-shelf wireless infrastructure. LiCS uses trace data from individuals' mobile devices, and a location estimation model. It trains the location estimation model by using the trace data to achieve collaborative target locating. Such collaboration between different devices is data-level, and model-supported. - MCS-Prediction: a recognition model is designed to dynamically acquire the structure knowledge of the relevant RCN during disease spread. On the basis of this model, a prediction algorithm is proposed to predict the parameter R. R is the reproductive number which is used to quantify the disease dynamics during disease spread. - MCS-Routing: an eco-friendly navigation algorithm, eRouting, is designed by combining real-time traffic information and a representative factor based energy/emission model. Based on the off-the-shelf infrastructure of an intelligent traffic system, the traffic information is collected

Computer hardware and algorithm design have seen significant progress over the years. It is also seen that there are several domains in which humans are more efficient than computers. For example in image recognition, image tagging, natural language understanding and processing, humans often find complicated algorithms quite easy to grasp. This thesis presents the different case studies to learn human mapping strategy to solve the mapping problem in the area of coarse-grained reconfigurable architectures (CGRAs). To achieve optimum level performance and consume less energy in CGRAs, place and route problem has always been a major concern. Making use of human characteristics can be helpful in problems as such, through pattern recognition and experience. Therefore to conduct the case studies a computer mapping game called UNTANGLED was analyzed as a medium to convey insights of human mapping strategies in a variety of architectures. The purpose of this research was to learn from humans so that we can come up with better algorithms to outperform the existing algorithms. We observed how human strategies vary as we present them with different architectures, different architectures with constraints, different visualization as well as how the quality of solution changes with experience. In this work all the case studies obtained from exploiting human strategies provide useful feedback that can improve upon existing algorithms. These insights can be adapted to find the best architectural solution for a particular domain and for future research directions for mapping onto mesh-and- stripe based CGRAs.

This study investigates how people's perceived sense of safety affects their use of and feeling of safety when they are in a park. The chosen location for the case study research is Karlstad City Garden. Currently, Karlstad City Garden is underutilized and was described as unsafe in a survey conducted by the municipality of Karlstad in 2018 (Karlstad kommun 2019). The purpose of this study is to examine visitors' perceived feelings of safety when they are in Karlstad City Garden. The study will focus on four factors; lighting, lack of people, maintenance, and visibility to provide what effect they have on people when they visit a public place. Previous research, including the municipality's safety survey, identified these four factors as significant contributors to visitors' feelings of safety. This study aims to gain a better understanding of why visitors perceive themselves as safe or unsafe in the park and how these four factors influence their perceived sense of safety. To investigate visitors' experiences of the park, a questionnaire was distributed through social media, and QR codes were distributed in the park to reach a diverse range of respondents. Additionally, observations were conducted as part of the study, primarily to complement the questionnaire and strengthen the findings. The study findings revealed that the time of day and the four factors mentioned above influenced visitors' perceived sense of safety in the park. During the day, more people were present, which made visitors feel safer. In the evening, the park was largely empty, and there were few visitors. The feelings of safety during this time could be attributed to the low population in the park, inadequate lighting in most areas, and reduced visibility during the evening. The poor visibility and lighting could be a result of insufficient maintenance, particularly in the densely vegetated southern part of the park. As a result, many people may have avoided visiting the park in the evening due to feeling unsafe.

No description available.

Text in English / The study investigated the policing of service delivery protests in South Africa with specific reference to Free State province. Failure by local governments to provide basic services to the previously disadvantaged South Africans has led to a number of service delivery protests taking place. The manner in which these protests are managed by the police in South Africa more especially the Public Order Police who are specialists in this field, raises concerns. One would perceive that the police are losing the battle in dealing with protest action for they are criticised for their brutal tactics in quelling the violence. This brutal handling of protesters dates back to the apartheid era and not much has changed contrary to the expectations of a newly formed democratic country. This therefore led to the investigation as to why the police in South Africa fail to contain such protest actions. The South African Police Services (SAPS) as it is known in a democratic South Africa employed tactics from international countries in order to introduce more professionalism in the SAPS. Although better tactics have been introduced, this did not seem to improve the situation because not only are properties destroyed but many lives are also lost through police action. The researcher conducted his investigation in the central part of South Africa in the Free State Province concentrating in the three main areas; namely Bloemfontein, Welkom and Bethlehem where the Public Order Police units are based. The investigation resulted in the researcher arriving at the conclusion that there are a number of challenges that are experienced by the SAPS when dealing with protests and the main problem identified was that of a shortage of manpower. This problem create challenges when it came to managing the number of protests taking place and exacerbated by not allowing the police to use the tactics that they were trained in. As much as we acknowledge these challenges, there are best practices that can be learnt from international countries. The crowd psychology strategies applied by the Swedish police as well as the high tolerance level of the British police, are the good practices that can be recommended in dealing with protests in South Africa. / Police Practice / M.Tech. (Policing)

打造一個好的產品是所有早期新創公司的核心，然而如何將產品從構想到販售並取顧客喜愛，則是一個需要理論與實務結合、不斷實驗的過程。在本論文中，作者將過去三年實際帶領產品-Voltset從出生到成長的經驗紀錄下來並與理論相呼應，探討一個新產品如何透過不斷循環的迭代過程 (iteration process)增加其新產品完整度 (product readiness) 。這三年當中，作者歸納了 Voltset從初期抽象構想的形成，獲得第一位付費的客戶，到後期在全球最大的群眾募資平台上進行全球市場驗證的過程。本論文主要會針對兩大部分做深度討論: 第一部分著重於探討如何在各種實際市場驗證測試中增加產品就緒度，並點出在目前現有理論框架，如: 精實創業 (the Lean startup) 下可能與實際執行面不同之處。根據本產品的經驗，新產品第一次的迭代過程循環應該經由以下幾個步驟：產品目標市場願景、產品本身定義、最小可行性產品構築、意見領袖背書、市場驗證、市場測試與學習。第二部分則是討論當在定義一個新產品的功能與特徵時，如何正確地選擇性聽取以及以什麼方式來聽取目標客戶的需求。根據打造 Voltset產品的經驗，作者發現當潛在客戶聲音太廣泛時，應只聽取”已付費”客戶的意見，因為該族群的產生是藉由深入了解產品價值，並經歷認同與付費過程而形成，因此會在產品的功能與特徵上的需求較聚焦。 本論文藉由親身實務經驗與理論的對話提供深度的產品迭代過程探討，作者期許這樣的研究能對於縮小理論與實務的鴻溝做出貢獻。 / Product building is a core activity for any early-stage startup. However, there are still many gaps between literature to real world practice for successfully developing a product that is accepted by the market. In this thesis, the building experience of Voltset -- a one of the kind hardware and software integrated multimeter, is studied for its journey of product iteration process to increase product readiness. The cofounder of the startup as well as the author of this thesis, has reflected his firsthand experience with literature such as the Commercializing New Technologies and the Lean Startup to seek steps necessary to move the project from shaping an abstract concept, acquiring the first paying customer, and then campaigning a successful crowd funding project. The thesis focuses on answering two questions: First, what are the steps required to enhance product readiness through validation testing from the first business idea to receiving its first group of paying customers. Based on the experience of Voltset and the Lean startup framework, it suggests the first product iteration process should loop through the following stages: Product market vision, product definition, minimum viable product building, key opinion leader endorsement, validation sell, measure, and learn. Second, when a product specification needs to be pinpointed, who and how to listen to the voice of targeted customers (VOC) is the state-of-art question for early-stage startups. Within the scope of this experience, it indicates to focus only on paying customers since they understand the potential value of the new product and have similar needs compare to the wide range of feature request from the rest of potential buyers. This thesis provides the insights of product iteration from first-hand experience, enriching the knowledge gap between real product building and theoretic framework point of view.

Problems involving optimal sequential making in uncertain dynamic systems arise in domains such as engineering, science and economics. Such problems can often be cast in the framework of Markov Decision Process (MDP). Solving an MDP requires computing the optimal value function and the optimal policy. The idea of dynamic programming (DP) and the Bellman equation (BE) are at the heart of solution methods. The three important exact DP methods are value iteration, policy iteration and linear programming. The exact DP methods compute the optimal value function and the optimal policy. However, the exact DP methods are inadequate in practice because the state space is often large and in practice, one might have to resort to approximate methods that compute sub-optimal policies. Further, in certain cases, the system observations are known only in the form of noisy samples and we need to design algorithms that learn from these samples. In this thesis we study interesting theoretical questions pertaining to approximate and learning algorithms, and also present an interesting application of MDPs in the domain of crowd sourcing. Approximate Dynamic Programming (ADP) methods handle the issue of large state space by computing an approximate value function and/or a sub-optimal policy. In this thesis, we are concerned with conditions that result in provably good policies. Motivated by the limitations of the PBE in the conventional linear algebra, we study the PBE in the (min, +) linear algebra. It is a well known fact that deterministic optimal control problems with cost/reward criterion are (min, +)/(max, +) linear and ADP methods have been developed for such systems in literature. However, it is straightforward to show that infinite horizon discounted reward/cost MDPs are neither (min, +) nor (max, +) linear. We develop novel ADP schemes namely the Approximate Q Iteration (AQI) and Variational Approximate Q Iteration (VAQI), where the approximate solution is a (min, +) linear combination of a set of basis functions whose span constitutes a subsemimodule. We show that the new ADP methods are convergent and we present a bound on the performance of the sub-optimal policy. The Approximate Linear Program (ALP) makes use of linear function approximation (LFA) and offers theoretical performance guarantees. Nevertheless, the ALP is difficult to solve due to the presence of a large number of constraints and in practice, a reduced linear program (RLP) is solved instead. The RLP has a tractable number of constraints sampled from the original constraints of the ALP. Though the RLP is known to perform well in experiments, theoretical guarantees are available only for a specific RLP obtained under idealized assumptions. In this thesis, we generalize the RLP to define a generalized reduced linear program (GRLP) which has a tractable number of constraints that are obtained as positive linear combinations of the original constraints of the ALP. The main contribution here is the novel theoretical framework developed to obtain error bounds for any given GRLP. Reinforcement Learning (RL) algorithms can be viewed as sample trajectory based solution methods for solving MDPs. Typically, RL algorithms that make use of stochastic approximation (SA) are iterative schemes taking small steps towards the desired value at each iteration. Actor-Critic algorithms form an important sub-class of RL algorithms, wherein, the critic is responsible for policy evaluation and the actor is responsible for policy improvement. The actor and critic iterations have deferent step-size schedules, in particular, the step-sizes used by the actor updates have to be generally much smaller than those used by the critic updates. Such SA schemes that use deferent step-size schedules for deferent sets of iterates are known as multitimescale stochastic approximation schemes. One of the most important conditions required to ensure the convergence of the iterates of a multi-timescale SA scheme is that the iterates need to be stable, i.e., they should be uniformly bounded almost surely. However, the conditions that imply the stability of the iterates in a multi-timescale SA scheme have not been well established. In this thesis, we provide veritable conditions that imply stability of two timescale stochastic approximation schemes. As an example, we also demonstrate that the stability of a widely used actor-critic RL algorithm follows from our analysis. Crowd sourcing (crowd) is a new mode of organizing work in multiple groups of smaller chunks of tasks and outsourcing them to a distributed and large group of people in the form of an open call. Recently, crowd sourcing has become a major pool for human intelligence tasks (HITs) such as image labeling, form digitization, natural language processing, machine translation evaluation and user surveys. Large organizations/requesters are increasingly interested in crowd sourcing the HITs generated out of their internal requirements. Task starvation leads to huge variation in the completion times of the tasks posted on to the crowd. This is an issue for frequent requesters desiring predictability in the completion times of tasks specified in terms of percentage of tasks completed within a stipulated amount of time. An important task attribute that affects the completion time of a task is its price. However, a pricing policy that does not take the dynamics of the crowd into account might fail to achieve the desired predictability in completion times. Here, we make use of the MDP framework to compute a pricing policy that achieves predictable completion times in simulations as well as real world experiments.

Alone in a Crowd: Charles Baudelaire and 20th-Century and Contemporary Art The dissertation called Alone in a Crowd explores the influence of the poet Charles Baudelaire's personality and work on 20th-century and contemporary art. Due to the field of study, the main focus is on the visual arts, but literature, music, philosophy, and film are also included to a large extent. This dissertation is divided into four substantive chapters. The first chapter, The Inner Message, introduces the poet's life, his family and acquaintances, as well as Baudelaire's poetry collection The Flowers of Evil. Themes of evil, ugliness, fear, death, and even a relationship to their mother, father and women are common for 20th-century and contemporary artists. This chapter presents Félicien Rops, James Ensor, Edvard Munch, Hans Bellmer, Francis Bacon, Joel-Peter Witkin, Kurt Cobain, members of the Young British Artists group, Lars von Trier, and others. The second chapter pursues the correspondence theory. The character of the Swedish philosopher Emanuel Swedenborg and his successor, William Blake, is followed by Baudelaire's understanding of sensual and spiritual correspondences, as his principles are adopted by modern artists in a distinct manner. The third chapter called "On the Edge of Society" covers the curse...

Ce mémoire propose une étude des poésies de Michel Houellebecq menée dans le respect des visées et du cadre théorique de la sociocritique (Duchet, Robin, Popovic). Chacun de ses trois chapitres explore un thème de recherche qui s’est imposé par sa prégnance dans l’œuvre étudiée : la vie urbaine, la vie sociale, les altérités de la ville. L’hypothèse principale est que l’écriture houellebecquienne capte des signes, des actes de langage, des représentations qui circulent dans la société française contemporaine, et qu’elle le fait de manière dynamique, c’est-à-dire en les soumettant à un travail scriptural qui critique leur usage et qui en modifie le sens. La « mise en texte » (Duchet) de la vie urbaine (premier chapitre) met à jour une domination de la ville et de ses habitants par les seules lois économiques. Elle décrit ainsi un monde qui n’est plus que marchand. Celle de la vie sociale et des liens interpersonnels (deuxième chapitre) démontre leur étonnante facticité et atteste que leur organisation restreint de plus en plus les libertés individuelles. Ce qui était un acquis de la modernité sociale : pouvoir bénéficier de « temps libre » pour prendre soin de soi et des proches, devient de plus en plus impossible. Enfin, celle des altérités de la ville (banlieue, province, nature – troisième chapitre), prouve que ces dernières n’offrent aucune alternative à l’hostilité du monde urbain et à la règle du chacun pour soi. Malgré ce diagnostic désolant, la poésie cherche à déceler ici ou là des traces d’espoir et de solidarité. / This master’s dissertation is a study of Michel Houellebecq’s poetry according to the theoretical framework of sociocritic (Duchet, Robin, Popovic). Urban life, social life and alterities of the city are the most present themes in the poetical work of the author. The main hypothesis is that the writing mobilizes and take over signs, linguistic acts and representations which float around in the French contemporary society, but in a dynamic way: the scriptural act of writing modifies their meaning and criticizes their common use. In the first chapter, we will discuss the “putting into text” (literal translation of the « mise en texte » concept by Duchet, which is the action of putting something into the form of a literary text) of urban life, which shines a light on how much the economic laws rule the city and its inhabitants. It describes a market world where money reigns. In the second chapter, the “putting into text” of social life and people-to-people ties shows how surprisingly artificial they are and certifies that their organization shrinks individual liberties more and more. Having free time to spend with your loved ones was once a given of social modernity but is now becoming difficult to manage. In the third and last chapter, the putting into text of the othernesses of the city (suburbs, province, nature) reveals that they offer no alternative to the hostility of the urban world and the fact that it is, and it will always be, every man for himself. Despite this distressing diagnosis, poetry tries to detect here and there hints of hope and solidarity.

Uppsala's student life largely consists of the student nations. The student nations are required to count the number of guests due to fire safety and to meet the regulations from the Public Health Agency of Sweden concerning the current pandemic. This report presents how a mobile application that shows if the student nations are calm, active, crowded, or full was created. The students in Uppsala can use the application to aid the decision of where they want to go, and the nations can use it to count the number of guests. By using this application, the nations are encouraged to keep track of the number of guests continuously and therefore contribute to a more safe environment in the student life of Uppsala. The vision for the application is to be reliable, user friendly, and have a quick response time. This was evaluated through several user experience metrics. During the performed user tests it came to our attention that the application was overall easy to use, had good functionality and that the user interface was minimalistic as well as appealing. However, some of the initial specifications of requirements were not fulfilled, and it appeared that some aspects of the application called for improvements to fulfill these requirements. / Uppsalas studentliv består till stor del av studentnationer. Nationer är skyldiga att veta hur många gäster som befinner sig i deras lokaler på grund av brandsäkerhet och för att följa Folkhälsomyndighetens föreskrifter angående den nuvarande pandemin. Den här rapporten presenterar hur en mobilapplikation skapades som visar om det är lugnt, aktivt, trångt eller fullt på studentnationerna. Uppsalas studenter kan använda applikationen för att underlätta i beslutet om var de vill gå, och nationerna kan använda den för att räkna antalet gäster. När nationerna använder applikationen uppmanas de att hålla koll på antalet besökare kontinuerligt och på så sätt bidra till en säkrare tillvaro för studenter i Uppsala. Visionen är att applikationen ska upplevas som pålitlig, användarvänlig och ha snabb responstid. Detta utvärderades genom användbarhetstester. Under dessa uppmärksammades det att applikationen totalt sett var enkel att använda, hade god funktionalitet och att användargränssnittet var minimalistiskt samt tilltalande. En del av de ursprungliga krav som sattes upp uppfylldes däremot inte, och vissa aspekter av applikationen kräver förbättringar för att uppfylla dessa krav.