Expert Systems and Advanced Algorithms in Mobile Robots Path Planning

Metody plánování pohybu jsou významnou součástí robotiky, resp. mobilních robotických platforem. Technicky je realizace plánování pohybu z globální úrovně převedena do posloupnosti akcí na úrovni specifické robotické platformy a definovaného prostředí, včetně omezení. V rámci této práce byla provedena recenze mnoha metod určených pro plánování cest, přičemž hlavním těžištěm byly metody založené na tzv. rychle rostoucích stromech (RRT), prostorovém rozkladu (CD) a využití fuzzy expertních systémů (FES). Dosažené výsledky, resp. prezentované algoritmy, využívají dostupné informace z pracovního prostoru mobilního robotu a jsou aplikovatelné na řešení globální pohybové trajektorie mobilních robotů, resp. k řešení specifických problémů plánování cest s omezením typu úzké koridory či překážky s proměnnou polohou v čase. V práci jsou představeny nové plánovací postupy využívající výhod algoritmů RRT a CD. Navržené metody jsou navíc efektivně rozšířeny s využitím fuzzy expertního systému, který zlepšuje jejich chování. Práce rovněž prezentuje řešení pro plánovací problémy typu identifikace úzkých koridorů, či významných oblastí prostoru řešení s využitím přístupů na bázi dekompozice prostoru. V řešeních jsou částečně zahrnuty sub-optimalizace nalezených cest založené na zkracování nalezené cesty a vyhlazování cesty, resp. nahrazení trajektorie hladkou křivkou, respektující lépe předpokládanou dynamiku mobilního zařízení. Všechny prezentované metody byly implementovány v prostředí Matlab, které sloužilo k simulačnímu ověření efektivnosti vlastních i převzatých metod a k návrhu prostoru řešení včetně omezení (překážky). Získané výsledky byly vyhodnoceny s využitím statistických přístupů v prostředí Minitab a Matlab.Motion planning is an active field in robotics domain, it is responsible for translating high-level specifications of a motion task into low-level sequences of motion commands, which respect the robot and the environments constraints. In this work many path-planning approaches have been reviewed, mainly, the rapidly exploring random tree algorithm (RRT), the cell decomposition approaches (CD), and the application of fuzzy expert system (FES) in motion planning. These approaches have been adapted to solve some of mobile robots motion-planning problems efficiently, i.e. motion planning in small and narrow areas, the global path planning in dynamic workspace, and the improvement of planning efficiency using available information about the working environments. New planning approaches have been introduced based on exploiting and combining the advantages of cell-decomposition, and RRT, in addition to use other tools i.e. fuzzy expert system, to increase the efficiency and completeness of finding a solution. This thesis also proposed solutions for other motion-planning problems, for example the identification of narrow area and the important regions when using sampling-based algorithms, the path shortening for RRT, and the problem of planning a safe path. All proposed methods were implemented and simulated in Matlab to compare them with other methods, in different workspaces and under different conditions. Moreover, the results are evaluated by statistical methods using Matlab and Minitab environments.

Safe Path Planning Using Cell Decomposition Approximation

Motion planning is an essential part in robotics domain; it is responsible for guiding the robot motion toward the goal. It generates a path from one location to another one, while avoiding the obstacles in the way. The planning modules could be configured to check the optimality, completeness, power saving, shortness of path, minimal number of turn, or the turn sharpness, etc., in addition to path safety. In this paper the cell decomposition approximation planar is used to find a safe path; the quad-tree approximation algorithm divides the workspace into manageable free areas, and builds a graph of adjacency between them. New methods are proposed to keep the robot far away from the obstacles boundaries by a minimum safe distance. These methods manipulate the weights of adjacency graph's edges. They utilize and reflect the size of free cells when planning a path. These approaches give a lower weight to the connection between big free cells, and a higher weight to the connections between the smaller cells. The planner after that searches for the lowest cost path based on these weights. The safe path in this work is the path which keeps the robot far away from obstacles by specified minimum safety distance and it bias the robot's motion to follow the bigger areas in the workspace. The shortest path is not considered. However a tradeoff between the real path cost and the safe path cost is considered when choosing the weight values.Plánování trasy pohybu robota je jednou ze základních úloh robotiky. Představuje úlohu bezpečného dovedení robota k cíli. Spočívá v návrhu trasy jednoho místa do druhého místa, přeičemž obchází překážky. Plánovací modul by může být nakonfigurován tak, že respektuje různá kritéria optimalizace - úplnost, minimalizace spotřeby energie, minimalizace délky trasy, minimální počet zatáček nebo maximálně povelý úhel zatáček aj. Jedním z kritérií je také bezpečnosti cesty. V tomto článku je popsána metoda rokladu terénu na elementy používáné pro nalezení bezpečné cesty. Algoritmus čtyřcestného stromu rozděluje pracovní plochu na elementární akceptovatelné plochy a generuje graf jejich vzájemné "přilehlosti". Jsou zde diskutovány metody umožňující pohyb robota v minimální bezpečné vzdálenosti od překážek. Diskutovaná metoda je založena na manipulaci s vahami hran "přilehlosti" hran oblastí. Algoritmus respektuje váhy jednotlivých oblastí pro plánování trasy. Tento přístup využívá nižší váhy propojení mezi velkými volnými buňkami na jedné straně a vyšší váhy na propojení mezi menšími buňkami. Plánovač trasy hledá trasu na základě minimalizace vah všech použitých oblastí. Bezpečná trasa je ta, která udržuje robota v bezpečné minimální vzdálenosti od překážek a umožňuje sledovat větší prostor prostoru v němž se robot pohybuje. Nehledá se nejkratší cesta. Kompromis mezi náklady na použití trasy a bezpečností trasy představují hodnotu vahy.Motion planning is an essential part in robotics domain; it is responsible for guiding the robot motion toward the goal. It generates a path from one location to another one, while avoiding the obstacles in the way. The planning modules could be configured to check the optimality, completeness, power saving, shortness of path, minimal number of turn, or the turn sharpness, etc., in addition to path safety. In this paper the cell decomposition approximation planar is used to find a safe path; the quad-tree approximation algorithm divides the workspace into manageable free areas, and builds a graph of adjacency between them. New methods are proposed to keep the robot far away from the obstacles boundaries by a minimum safe distance. These methods manipulate the weights of adjacency graph's edges. They utilize and reflect the size of free cells when planning a path. These approaches give a lower weight to the connection between big free cells, and a higher weight to the connections between the smaller cells. The planner after that searches for the lowest cost path based on these weights. The safe path in this work is the path which keeps the robot far away from obstacles by specified minimum safety distance and it bias the robot's motion to follow the bigger areas in the workspace. The shortest path is not considered. However a tradeoff between the real path cost and the safe path cost is considered when choosing the weight values

Narrow passage identification using cell decomposition approximation and minimum spanning tree

Narrow passage problem is a problematic issue facing the sampling-based motion planner. In this paper, a new approach for narrow areas identification is proposed. The quad-tree cell-decomposition approximation is used to divide the free workspace into smaller cells, and build a graph of adjacency for these. The proposed method follows the graph edges and finds a sequence of cells, which have the same size, preceded and followed by a bigger cell size. The sequence, which has the pattern bigger-smaller-bigger cells size, is more likely to be located in a narrow area. The minimum spanning tree algorithm is used, to linearize adjacency graph. Many methods have been proposed to manipulate the edges cost in the graph, in order to make the generated spanning tree traverse through narrow passages in detectable ways. Five methods have been proposed, some of them give bad results, and the others give better on in simulationsNarrow passage problem is a problematic issue facing the sampling-based motion planner. In this paper, a new approach for narrow areas identification is proposed. The quad-tree cell-decomposition approximation is used to divide the free workspace into smaller cells, and build a graph of adjacency for these. The proposed method follows the graph edges and finds a sequence of cells, which have the same size, preceded and followed by a bigger cell size. The sequence, which has the pattern bigger-smaller-bigger cells size, is more likely to be located in a narrow area. The minimum spanning tree algorithm is used, to linearize adjacency graph. Many methods have been proposed to manipulate the edges cost in the graph, in order to make the generated spanning tree traverse through narrow passages in detectable ways. Five methods have been proposed, some of them give bad results, and the others give better on in simulation

Pantheon: Private Retrieval from Public Key-Value Store

Consider a cloud server that owns a key-value store and provides a private query service to its clients. Preserving client privacy in this setting is difficult because the key-value store is public, and a client cannot encrypt or modify it. Therefore, privacy in this context implies hiding the access pattern of a client. Pantheon is a system that cryptographically allows a client to retrieve the value corresponding to a key from a public key-value store without allowing the server or any adversary to know any information about the key or value accessed. Pantheon devises a single-round retrieval protocol which reduces server-side latency by refining its cryptographic machinery and massively parallelizing the query execution workload. Using these novel techniques, Pantheon achieves a $93\times$ improvement for server-side latency over a state-of-the-art solution

Patterns of multimorbidity in primary care electronic health records: A systematic review

Multimorbidity; Electronic health records; Primary careMultimorbilidad; Registros médicos electrónicos; Atención primariaMultimorbiditat; Registres mèdics electrònics; Atenció primàriaBackground Multimorbidity, the coexistence of multiple chronic conditions in an individual, is a complex phenomenon that is highly prevalent in primary care settings, particularly in older individuals. This systematic review summarises the current evidence on multimorbidity patterns identified in primary care electronic health record (EHR) data. Methods Three databases were searched from inception to April 2022 to identify studies that derived original multimorbidity patterns from primary care EHR data. The quality of the included studies was assessed using a modified version of the Newcastle-Ottawa Quality Assessment Scale. Results Sixteen studies were included in this systematic review, none of which was of low quality. Most studies were conducted in Spain, and only one study was conducted outside of Europe. The prevalence of multimorbidity (i.e. two or more conditions) ranged from 14.0% to 93.9%. The most common stratification variable in disease clustering models was sex, followed by age and calendar year. Despite significant heterogeneity in clustering methods and disease classification tools, consistent patterns of multimorbidity emerged. Mental health and cardiovascular patterns were identified in all studies, often in combination with diseases of other organ systems (e.g. neurological, endocrine). Discussion These findings emphasise the frequent coexistence of physical and mental health conditions in primary care, and provide useful information for the development of targeted preventive and management strategies. Future research should explore mechanisms underlying multimorbidity patterns, prioritise methodological harmonisation to facilitate the comparability of findings, and promote the use of EHR data globally to enhance our understanding of multimorbidity in more diverse populations

Job Satisfaction of Public Secondary School Teachers in Second Zarqa District Directorate of Education

This study aims at identifying the correlation of teachers’ satisfaction about their jobs, and their job performance from their perspectives. In analyzing the data, the researcher used the descriptive research methodology. Achieve the objective of the study the questionnaire was used as a study tool, and the validity and reliability of the tool were verified the study used person coefficient and Cronbach alpha coefficient This study is based on a (229) teachers in the academic year 2017\2018 chosen randomly. Findings of the study revealed that: There were statistically significant differences at the level (α ≥ 0.05) between the teachers’ job-satisfaction with and their job performance in all dimensions. The degree of the job satisfaction among public secondary teachers’ in the Second Directorate of Education in Zarqa medium. The degree of the job performance among the public secondary teachers in public schools from their own perspectives was high. Based on the findings of the study, the researcher suggested some recommendation. The current study concluded with a number of recommendations, including work on increasing salaries and incentives for secondary public school teachers to suit thei

Paracetamol biodegradation by activated sludge and photo-catalysis and its removal by a micelleclay complex, activated charcoal and reverse osmosis membranes

Kinetic studies on the stability of the pain killer paracetamol in Al-Quds activated sludge demonstrated that paracetamol underwent biodegradation within less than one month to furnish p-aminophenol in high yields. Characterizations of bacteria contained in Al-Quds sludge were accomplished. It was found that Pseudomonas aeruginosa is the bacterium most responsible for the biodegradation of paracetamol to p-aminophenol and hydroquinone. Batch adsorptions of paracetamol and its biodegradation product (p-aminophenol) by activated charcoal and a composite micelle (octadecyltrimethylammonium)-clay (montmorillonite) were determined at 25°C. Adsorption was adequately described by a Langmuir isotherm, and indicated better efficiency of removal by the micelle-clay complex. The ability of bench top reverse osmosis (RO) plant as well as advanced membrane pilot plant to remove paracetamol was also studied at different water matrixes to test the effect of organic matter composition. The results showed that at least 90% rejection was obtained by both plants. In addition, removal of paracetamol from RO brine was investigated by using photocatalytic processes; optimal conditions were found to be acidic or basic pH, in which paracetamol degraded in less than 5 min. Toxicity studies indicated that the effluent and brine were not toxic except for using extra low energy membrane which displayed a half maximal inhibitory concentration (IC-50) value of 80%

Coeus: A System for Oblivious Document Ranking and Retrieval

Given a private string q and a remote server that holds a set of public documents D, how can one of the K most relevant documents to q in D be selected and viewed without anyone (not even the server) learning anything about q or the document? This is the oblivious document ranking and retrieval problem. In this paper, we describe Coeus, a system that solves this problem. At a high level, Coeus composes two cryptographic primitives: secure matrix-vector product for scoring document relevance using the widely-used term frequency-inverse document frequency (tf-idf) method, and private information retrieval (PIR) for obliviously retrieving documents. However, Coeus reduces the time to run these protocols, thereby improving the user-perceived latency, which is a key performance metric. Coeus first reduces the PIR overhead by separating out private metadata retrieval from document retrieval, and it then scales secure matrix-vector product to tf-idf matrices with several hundred billion elements through a series of novel cryptographic refinements. For a corpus of English Wikipedia containing 5 million documents, a keyword dictionary with 64K keywords, and on a cluster of 143 machines on AWS, Coeus enables a user to obliviously rank and retrieve a document in 3.9 seconds---a 24x improvement over a baseline system

Addra: Metadata-private voice communication over fully untrusted infrastructure

Metadata from voice calls, such as the knowledge of who is communicating with whom, contains rich information about people’s lives. Indeed, it is a prime target for powerful adversaries such as nation states. Existing systems that hide voice call metadata either require trusted intermediaries in the network or scale to only tens of users. This paper describes the design, implementation, and evaluation of Addra, the first system for voice communication that hides metadata over fully untrusted infrastructure and scales to tens of thousands of users. At a high level, Addra follows a template in which callers and callees deposit and retrieve messages from private mailboxes hosted at an untrusted server. However, Addra improves message latency in this architecture, which is a key performance metric for voice calls. First, it enables a caller to push a message to a callee in two hops, using a new way of assigning mailboxes to users that resembles how a post office assigns PO boxes to its customers. Second, it innovates on the underlying cryptographic machinery and constructs a new private information retrieval scheme, FastPIR, that reduces the time to process oblivious access requests for mailboxes. An evaluation of Addra on a cluster of 80 machines on AWS demonstrates that it can serve 32K users with a 99-th percentile message latency of 726 ms—a 7× improvement over a prior system for text messaging in the same threat model