Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.The PhD Symposium was a very good opportunity for the young researchers to share information and knowledge, to present their current research, and to discuss topics with other students in order to look for synergies and common research topics. The idea was very successful and the assessment made by the PhD Student was very good. It also helped to achieve one of the major goals of the NESUS Action: to establish an open European research network targeting sustainable solutions for ultrascale computing aiming at cross fertilization among HPC, large scale distributed systems, and big data management, training, contributing to glue disparate researchers working across different areas and provide a meeting ground for researchers in these separate areas to exchange ideas, to identify synergies, and to pursue common activities in research topics such as sustainable software solutions (applications and system software stack), data management, energy efficiency, and resilience.European Cooperation in Science and Technology. COS

Mobile-based application for discovering family relationship using rule based system in Tanzania

A Project Report Submitted in Partial Fulfillment of the Requirements of the Award the Degree of Master of Science in Embedded and Mobile Systems of The Nelson Mandela African Institution of Science and TechnologyFamily is a basic unit in society where traditionally, parents raise their children and family bonds survive longer and provide a primary sense of belonging. It has been observed that it become difficult when extended family become complex to find distant relatives using traditional approaches this is due to rural-urban migration and residential mobility, which has been weakened family relationship. Several researchers have developed systems to help relatives in discovering their family relationships using genealogical data, nevertheless, these systems may provide false-positive findings when there is lack of information. In Tanzania the genealogical sites have insufficient individual’s family information for family discovery. The purpose of this paper is to present a developed mobile based application for discovering family relationships with no use of genealogical data and use of rule-based system to identify the type of relationship with a person. Both primary and secondary data collection methods were used to collect data and analyzed using R-studio. The research revealed that rule-based system can easily discover family relationships, and families grow when people interact with the mobile application (MyFam). The system was validated with users, where results emphasized its efficiency as a discovery tool with performance of 40% in user experience, 40% in system functionalities and 55% in system interface. The contribution of this study is to provide a mobile application that can be used in many countries for discovering family members relationships. In addition, due to efficacy of the rule-based system, any relationship can be inferred simply and reliably based on how family relationships are named

PENGEMBANGAN DAN ANALISIS KUALITAS APLIKASI SISTEM PAKAR DIAGNOSIS KERUSAKAN KOMPUTER

PENGEMBANGAN DAN ANALISIS KUALITAS APLIKASI SISTEM PAKAR DIAGNOSIS KERUSAKAN KOMPUTER Oleh : Kifni Taufik Darmawan 08520241008 ABSTRAK Penelitian ini bertujuan untuk mengembangkan Aplikasi Sistem Pakar Diagnosis Kerusakan Komputer menggunakan bahasa pemrograman Java dan database SQLite dan melakukan analisis kualitas pada aplikasi yang dikembangkan, khususnya pada faktor kualitas correctness, functionality, portability, dan usability. Pengembangan Aplikasi Sistem Pakar Diagnosis Kerusakan Komputer dilakukan dengan kaidah rekayasa perangkat lunak (software engineering) yaitu dimulai dari proses perencanaan (planning), modeling (perancangan), konstruksi (construction), dan penyebaran (deployment). Analisis faktor kualitas correctness dilakukan dengan perhitungan jumlah error / KLOC. Analisis faktor kualitas functionality dilakukan dengan pengujian setiap fungsi aplikasi. Analisis faktor kualitas portability dilakukan dengan percobaan penjalanan aplikasi pada beberapa sistem operasi yang berbeda. Analisis faktor kualitas usability dilakukan dengan metode kuesioner dengan responden Siswa Kelas XI TKJ SMK Muhammadiyah 2 Yogyakarta. Hasil pengembangan aplikasi yaitu Aplikasi Sistem Pakar Diagnosis Kerusakan Komputer dalam bentuk file runnable. Hasil analisis kualitas menunjukan bahwa aplikasi yang dikembangkan memenuhi semua standar faktor kualitas yang diujikan yaitu correctness, functionality, portability, dan usability. Kata kunci : sistem pakar, java, sqlite, software quality, correctness, functionality, portability, usability

Demonstrating Autonomous Mission Operations Onboard the International Space Station

The NASA Autonomous Mission Operations (AMO) project conducted an experiment to turn over operation and management of selected International Space Station (ISS) sys- tems to the on-board crew. ISS crews managed two different spacecraft systems: the Total Organic Carbon Analyzer (TOCA), a water quality analyzer, and Station Support Com- puters (SSC) laptops, which are non-critical crew computer systems. These systems were selected because they are representative of systems a future crew may need to operate au- tonomously during a deep space mission. The crew autonomously operated these systems, taking on mission operations functions traditionally performed by support teams on the ground, using new software tools that provide decision support algorithms for planning, monitoring and fault management, hardware schematics, system briefs, and data displays that are normally unavailable to the crew. The experiment lasted seven months, during which ISS crews managed TOCA and SSCs on 22 occasions. The AMO software processed data from TOCA and SSCs continuously during this seven month period. The combined performance of the software and crew achieved a 88 success rate on managing TOCA activity, the system for which ground-truth was available

IoT system for the validation of conditions in shipping couriers

The growth in online activity these days has caused an increase in the number of online shopping businesses. As the shopping experience becomes less personal, some people try to abuse online businesses with return fraud. The number of IoT devices has also experienced growth due to the fourth industrial revolution, or Industry 4.0, which consists of process automation and data exchange in the industry through IoT and machine learning. This dissertation includes research questions, hypotheses, objectives, and a methodology for the development of a system that integrates IoT to solve the problem of fraudulent returns. The prototype developed monitors when packages leave the facilities and when they are delivered, in addition to allowing to check upon the packages’ integrity at these same moments. This is achieved by using a Raspberry Pi with a camera attached and an ESP32 with a motion sensor, connected via the MQTT and Node-RED protocol. To evaluate the system, several tests were created to simulate a scenario of real-world application. With the results obtained, it is possible to conclude that the development was a success and that the prototype can be used in logistics business to prevent return fraud.O aumento da atividade online nos dias de hoje tem causado um aumento no número de lojas de comércio online. À medida que a experiência de compra se torna menos pessoal, algumas pessoas tentam abusar negócios online com fraudes de devolução. O número de dispositivos IoT também tem crescido devido à quarta revolução industrial, ou Indústria 4.0, que consiste na automação de processos e troca de dados na indústria através de IoT e machine learning. Esta dissertação inclui questões de investigação, hipóteses, objetivos e uma metodologia para o desenvolvimento de um sistema que integra IoT para resolver o problema de devoluções fraudulentas. O protótipo desenvolvido monitoriza quando encomendas saem das instalações e quando são entregues, para além de permitir a verificação da integridade física das encomendas nestes mesmos momentos. Isto é alcançado com o uso de um Raspberry Pi com uma câmara associada e um ESP32 com um sensor de movimento, conectados entre si através do protocolo MQTT e Node-RED. Para avaliar o sistema, vários testes foram criados de forma a simular um cenário de aplicação no mundo real. Os resultados obtidos permitem concluir que o desenvolvimento foi um sucesso e que o protótipo pode ser usado em empresas de logística, distribuição e transporte para evitar fraudes de devolução

InSight2: An Interactive Web Based Platform for Modeling and Analysis of Large Scale Argus Network Flow Data

Monitoring systems are paramount to the proactive detection and mitigation of problems in computer networks related to performance and security. Degraded performance and compromised end-nodes can cost computer networks downtime, data loss and reputation. InSight2 is a platform that models, analyzes and visualizes large scale Argus network flow data using up-to-date geographical data, organizational information, and emerging threats. It is engineered to meet the needs of network administrators with flexibility and modularity in mind. Scalability is ensured by devising multi-core processing by implementing robust software architecture. Extendibility is achieved by enabling the end user to enrich flow records using additional user provided databases. Deployment is streamlined by providing an automated installation script. State-of-the-art visualizations are devised and presented in a secure, user friendly web interface giving greater insight about the network to the end user

EVALUATION OF BUSINESS EFFECTS OF MACHINE-TO-MACHINE SYSTEM

The tightening competition and pressure in the project schedules often leave no time or space for the assessment of business impacts of different investments and projects. In addition, in many cases the assessment may be challenging and there is no experience available to undertake it. Therefore, companies often commit to different projects and investments without careful planning and vision of the costs it may cause. The goal in this thesis is to present and clarify the possible applications for the designed platform. The different benefits and its scope of use are also evaluated. Its potential market size is also assessed and its payback period calculated. Moreover, the investment eligibility from customer point of view is evaluated using several investment decision methods. In order to enable the practical business impact assessment, the designed platform is applied to fleet management business. In order to facilitate and increase the assessment of business impacts, a decision support system is also created. It is built on the understanding gained from the cost-benefit analysis conducted in the fleet management case and three other cases from the machine-to-machine business. As a background for the thesis, an overview of the existing solutions is presented and few well-known service models are described. Also an introduction to three sales forecasting methods is given. In order to build a basis for the decision support system, few investment decision methods are presented. As a result, a good understanding of different applications of the platform was gained. It was found to be suitable for any business in which vehicles are involved as they share several common properties such as location information, fuel consumption, speed, and status information. Its potential market size was assessed very promising despite low market share assumption. The payback period was found as very appealing and the investment strongly eligible. The created decision support system was found to be successful. It can be seen as a reliable tool as it consists of several investment decision methods. However, experience from the business area is still needed because any system cannot provide thorough means to identify all the crucial cost factors involved in an investment.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Techniques for Detection, Root Cause Diagnosis, and Classification of In-Production Concurrency Bugs

Concurrency bugs are at the heart of some of the worst bugs that plague software. Concurrency bugs slow down software development because it can take weeks or even months before developers can identify and fix them. In-production detection, root cause diagnosis, and classification of concurrency bugs is challenging. This is because these activities require heavyweight analyses such as exploring program paths and determining failing program inputs and schedules, all of which are not suited for software running in production. This dissertation develops practical techniques for the detection, root cause diagnosis, and classification of concurrency bugs for inproduction software. Furthermore, we develop ways for developers to better reason about concurrent programs. This dissertation builds upon the following principles: — The approach in this dissertation spans multiple layers of the system stack, because concurrency spans many layers of the system stack. — It performs most of the heavyweight analyses in-house and resorts to minimal in-production analysis in order to move the heavy lifting to where it is least disruptive. — It eschews custom hardware solutions that may be infeasible to implement in the real world. Relying on the aforementioned principles, this dissertation introduces: 1. Techniques to automatically detect concurrency bugs (data races and atomicity violations) in-production by combining in-house static analysis and in-production dynamic analysis. 2. A technique to automatically identify the root causes of in-production failures, with a particular emphasis on failures caused by concurrency bugs. 3. A technique that given a data race, automatically classifies it based on its potential consequence, allowing developers to answer questions such as “can the data race cause a crash or a hang?”, or “does the data race have any observable effect?”. We build a toolchain that implements all the aforementioned techniques. We show that the tools we develop in this dissertation are effective, incur low runtime performance overhead, and have high accuracy and precision