Design and analysis of sequential and parallel single-source shortest-paths algorithms

We study the performance of algorithms for the Single-Source Shortest-Paths (SSSP) problem on graphs with n nodes and m edges with nonnegative random weights. All previously known SSSP algorithms for directed graphs required superlinear time. Wie give the first SSSP algorithms that provably achieve linear O(n-m)average-case execution time on arbitrary directed graphs with random edge weights. For independent edge weights, the linear-time bound holds with high probability, too. Additionally, our result implies improved average-case bounds for the All-Pairs Shortest-Paths (APSP) problem on sparse graphs, and it yields the first theoretical average-case analysis for the "Approximate Bucket Implementation" of Dijkstra\u27s SSSP algorithm (ABI-Dijkstra). Futhermore, we give constructive proofs for the existence of graph classes with random edge weights on which ABI-Dijkstra and several other well-known SSSP algorithms require superlinear average-case time. Besides the classical sequential (single processor) model of computation we also consider parallel computing: we give the currently fastest average-case linear-work parallel SSSP algorithms for large graph classes with random edge weights, e.g., sparse rondom graphs and graphs modeling the WWW, telephone calls or social networks.In dieser Arbeit untersuchen wir die Laufzeiten von Algorithmen für das Kürzeste-Wege Problem (Single-Source Shortest-Paths, SSSP) auf Graphen mit n Knoten, M Kanten und nichtnegativen zufälligen Kantengewichten. Alle bisherigen SSSP Algorithmen benötigen auf gerichteten Graphen superlineare Zeit. Wir stellen den ersten SSSP Algorithmus vor, der auf beliebigen gerichteten Graphen mit zufälligen Kantengewichten eine beweisbar lineare average-case-Komplexität O(n+m)aufweist. Sind die Kantengewichte unabhängig, so wird die lineare Zeitschranke auch mit hoher Wahrscheinlichkeit eingehalten. Außerdem impliziert unser Ergebnis verbesserte average-case-Schranken für das All-Pairs Shortest-Paths (APSP) Problem auf dünnen Graphen und liefert die erste theoretische average-case-Analyse für die "Approximate Bucket Implementierung" von Dijkstras SSSP Algorithmus (ABI-Dijkstra). Weiterhin führen wir konstruktive Existenzbeweise für Graphklassen mit zufälligen Kantengewichten, auf denen ABI-Dijkstra und mehrere andere bekannte SSSP Algorithmen durchschnittlich superlineare Zeit benötigen. Neben dem klassischen seriellen (Ein-Prozessor) Berechnungsmodell betrachten wir auch Parallelverarbeitung; für umfangreiche Graphklassen mit zufälligen Kantengewichten wie z.B. dünne Zufallsgraphen oder Modelle für das WWW, Telefonanrufe oder soziale Netzwerke stellen wir die derzeit schnellsten parallelen SSSP Algorithmen mit durchschnittlich linearer Arbeit vor

Solar-powered aquaponics prototype as sustainable approach for food production

This paper presents the establishment of a solar-powered aquaponics prototype as a sustainable, cost effective and environmentally sound approach for food production. In this study, a prototype bench top aquaponics rig with an integrated 20 W solar panel were fabricated for the cultivation of red Hybrid Tilapia (Oreochromis spp.) and leaf mustard (Brassica juncea). The size of the fish tank is about 29.5L and serves as the base for the setup. Additionally, the hydroponic grower compartment (0.45 m (L) � 0.32 m (W) � 0.13 m (H)) was stacked on top of the fish tank and was filled with LECA media bed for the plant growth. Two important operating parameters were studied. First, the amount of energy produced by the solar panel and the energy consumption by the water pump used in the setup. Secondly, the resultant effects from fish cultivation and plants growth on the water qualities and nitrification effi�ciency of the aquaponics unit. The aquaponics unit was operated for a month and the values of pH, tem�perature, and ammonia level were measured to be within the range of 6.4–7.2, 27.1–31.7 �C, and 1 mg�L�1 , respectively. Survival rate for fish was about 75% with specific growth rate (SGR) of 3.75% per day and food conversion ratio of about 1.15. A slight nutrient deficiency was evident and plants showed a healthy growth with height gain as high as 5 cm was achieved. Despite raining season, our data shows that the energy produced via 20 W solar panel enabled the unit to run at night without depending on local electricity for nearly two hours. Clearly, a larger solar panel is needed for longer operation. Nevertheless, the study has proven the potential of operating a low cost aquaponics setup using renew�able energy for a sustainable food production method

Perfusion image processing

Cílem této diplomové práce bylo vytvořit skript pro program MATLAB, který je schopen načíst obrázky DICOM standardu, přečíst informace v jejich hlavičce a zvolit správnou sérii snímků pro perfuzní analýzu. Tato analýza je založena na detekci kontrastní látky v lidském těle a správné interpretaci změn kontrastu této látky v čase. Celá práce se snaží popsat cestu ke tvorbě systému schopného automatické analýzy a kvalifikace nádoru. Nakonec je vytvořeným skriptem provedena analýza poskytnutých DICOM snímků.The goal of this diploma thesis was to create a script in MATLAB, which is capable to load DICOM pictures, read the data in their headers and then select the right series for perfusion analysis. This analysis is based on detection of contrast fluid in bloodstream and tissue and right interpretation of concentration changes of this fluid in time. This work is trying to describe a way of building an ultimate system capable of autonomous tumor analysis and classification. In the end, there is an analysis of DICOM sample performed by created script.

Privaatsust säilitavad paralleelarvutused graafiülesannete jaoks

Turvalisel mitmeosalisel arvutusel põhinevate reaalsete privaatsusrakenduste loomine on SMC-protokolli arvutusosaliste ümmarguse keerukuse tõttu keeruline. Privaatsust säilitavate tehnoloogiate uudsuse ja nende probleemidega kaasnevate suurte arvutuskulude tõttu ei ole paralleelseid privaatsust säilitavaid graafikualgoritme veel uuritud. Graafikalgoritmid on paljude arvutiteaduse rakenduste selgroog, nagu navigatsioonisüsteemid, kogukonna tuvastamine, tarneahela võrk, hüperspektraalne kujutis ja hõredad lineaarsed lahendajad. Graafikalgoritmide suurte privaatsete andmekogumite töötlemise kiirendamiseks ja kõrgetasemeliste arvutusnõuete täitmiseks on vaja privaatsust säilitavaid paralleelseid algoritme. Seetõttu esitleb käesolev lõputöö tipptasemel protokolle privaatsuse säilitamise paralleelarvutustes erinevate graafikuprobleemide jaoks, ühe allika lühima tee, kõigi paaride lühima tee, minimaalse ulatuva puu ja metsa ning algebralise tee arvutamise. Need uued protokollid on üles ehitatud kombinatoorsete ja algebraliste graafikualgoritmide põhjal lisaks SMC protokollidele. Nende protokollide koostamiseks kasutatakse ka ühe käsuga mitut andmeoperatsiooni, et vooru keerukust tõhusalt vähendada. Oleme väljapakutud protokollid juurutanud Sharemind SMC platvormil, kasutades erinevaid graafikuid ja võrgukeskkondi. Selles lõputöös kirjeldatakse uudseid paralleelprotokolle koos nendega seotud algoritmide, tulemuste, kiirendamise, hindamiste ja ulatusliku võrdlusuuringuga. Privaatsust säilitavate ühe allika lühimate teede ja minimaalse ulatusega puuprotokollide tegelike juurutuste tulemused näitavad tõhusat meetodit, mis vähendas tööaega võrreldes varasemate töödega sadu kordi. Lisaks ei ole privaatsust säilitavate kõigi paaride lühima tee protokollide hindamine ja ulatuslik võrdlusuuringud sarnased ühegi varasema tööga. Lisaks pole kunagi varem käsitletud privaatsust säilitavaid metsa ja algebralise tee arvutamise protokolle.Constructing real-world privacy applications based on secure multiparty computation is challenging due to the round complexity of the computation parties of SMC protocol. Due to the novelty of privacy-preserving technologies and the high computational costs associated with these problems, parallel privacy-preserving graph algorithms have not yet been studied. Graph algorithms are the backbone of many applications in computer science, such as navigation systems, community detection, supply chain network, hyperspectral image, and sparse linear solvers. In order to expedite the processing of large private data sets for graphs algorithms and meet high-end computational demands, privacy-preserving parallel algorithms are needed. Therefore, this Thesis presents the state-of-the-art protocols in privacy-preserving parallel computations for different graphs problems, single-source shortest path (SSSP), All-pairs shortest path (APSP), minimum spanning tree (MST) and forest (MSF), and algebraic path computation. These new protocols have been constructed based on combinatorial and algebraic graph algorithms on top of the SMC protocols. Single-instruction-multiple-data (SIMD) operations are also used to build those protocols to reduce the round complexities efficiently. We have implemented the proposed protocols on the Sharemind SMC platform using various graphs and network environments. This Thesis outlines novel parallel protocols with their related algorithms, the results, speed-up, evaluations, and extensive benchmarking. The results of the real implementations of the privacy-preserving single-source shortest paths and minimum spanning tree protocols show an efficient method that reduced the running time hundreds of times compared with previous works. Furthermore, the evaluation and extensive benchmarking of privacy-preserving All-pairs shortest path protocols are not similar to any previous work. Moreover, the privacy-preserving minimum spanning forest and algebraic path computation protocols have never been addressed before.https://www.ester.ee/record=b555865

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We study the performance of algorithms for the Single-Source Shortest-Paths (SSSP) problem on graphs with n nodes and m edges with nonnegative random weights. All previously known SSSP algorithms for directed graphs required superlinear time. Wie give the first SSSP algorithms that provably achieve linear O(n-m)average-case execution time on arbitrary directed graphs with random edge weights. For independent edge weights, the linear-time bound holds with high probability, too. Additionally, our result implies improved average-case bounds for the All-Pairs Shortest-Paths (APSP) problem on sparse graphs, and it yields the first theoretical average-case analysis for the "Approximate Bucket Implementation" of Dijkstra's SSSP algorithm (ABI-Dijkstra). Futhermore, we give constructive proofs for the existence of graph classes with random edge weights on which ABI-Dijkstra and several other well-known SSSP algorithms require superlinear average-case time. Besides the classical sequential (single processor) model of computation we also consider parallel computing: we give the currently fastest average-case linear-work parallel SSSP algorithms for large graph classes with random edge weights, e.g., sparse rondom graphs and graphs modeling the WWW, telephone calls or social networks.In dieser Arbeit untersuchen wir die Laufzeiten von Algorithmen für das Kürzeste-Wege Problem (Single-Source Shortest-Paths, SSSP) auf Graphen mit n Knoten, M Kanten und nichtnegativen zufälligen Kantengewichten. Alle bisherigen SSSP Algorithmen benötigen auf gerichteten Graphen superlineare Zeit. Wir stellen den ersten SSSP Algorithmus vor, der auf beliebigen gerichteten Graphen mit zufälligen Kantengewichten eine beweisbar lineare average-case-Komplexität O(n+m)aufweist. Sind die Kantengewichte unabhängig, so wird die lineare Zeitschranke auch mit hoher Wahrscheinlichkeit eingehalten. Außerdem impliziert unser Ergebnis verbesserte average-case-Schranken für das All-Pairs Shortest-Paths (APSP) Problem auf dünnen Graphen und liefert die erste theoretische average-case-Analyse für die "Approximate Bucket Implementierung" von Dijkstras SSSP Algorithmus (ABI-Dijkstra). Weiterhin führen wir konstruktive Existenzbeweise für Graphklassen mit zufälligen Kantengewichten, auf denen ABI-Dijkstra und mehrere andere bekannte SSSP Algorithmen durchschnittlich superlineare Zeit benötigen. Neben dem klassischen seriellen (Ein-Prozessor) Berechnungsmodell betrachten wir auch Parallelverarbeitung; für umfangreiche Graphklassen mit zufälligen Kantengewichten wie z.B. dünne Zufallsgraphen oder Modelle für das WWW, Telefonanrufe oder soziale Netzwerke stellen wir die derzeit schnellsten parallelen SSSP Algorithmen mit durchschnittlich linearer Arbeit vor