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While we are already used to see more than 1,000 cores within a single machine, the next processing platforms for database engines will be heterogeneous with built-in GPU-style processors as well as specialized FPGAs or chips with domain-specific instruction sets. Moreover, the traditional volatile as well as the upcoming non-volatile RAM with capacities in the 100s of TBytes per machine will provide great opportunities for storage engines but also call for radical changes on the architecture of such systems. Finally, the emergence of economically affordable, high-speed/low-latency interconnects as a basis for rack-scale computing is questioning long-standing folklore algorithmic assumptions but will certainly play an important role in the big picture of building modern data management platforms. In this talk, we will try to classify and review existing approaches from a performance, robustness, as well as energy efficiency perspective and pinpoint interesting starting points for further research activities.

GMAW (Gas Metal Arc Welding) is one of the most important arc welding processes being adopted in modern manufacturing industry due to its advantages in productivity, energy efficiency and automation. By monitoring and improving some of the important properties of GMAW such as production rate, metal transfer and base metal heat input, researchers could bring the process efficiency and stability to a new level. In recent years, some innovative modifications of GMAW such as Twins, Tandem and laser-MIG hybrid welding have been adopted into many industrial applications for better productivity. In this dissertation, a novel GMAW called DB-GMAW (Dual Bypass Gas Metal Arc Welding) using two GTAW torches and one GMAW torch to construct a welding system, is proposed and developed. In DB-GMAW, two GTAW torches perform the bypass system which decouples the total welding current into base metal current and bypass current after the melt down of filler wire. Compared to conventional GMAW, DB-GMAW has many advantages in droplet formation, base metal heat input and penetration achievement due to its unique characteristics in welding arc and current flow. In the first place of the research, experimental system of DB-GMAW is constructed. Then, sufficient experiments under different parameters are performed to provide us a good understanding of the behaviors and characteristics of this novel GMAW process. Observation about metal transfer formation and base metal heat input is studied to verify its theoretical analysis. Full penetration of work piece via DB-GMAW is achieved based on a series of parameter testing experiments. Moreover, image processing techniques are applied to DB-GMAW to monitor the welding process and construct a feedback system for control. Considering the importance of maintaining stable full penetration during many welding applications, a nonlinear model of DB-GMAW full penetration is developed in this dissertation. To do that, we use machine vision techniques to monitor the welding profile of the work piece. A control algorithm based on the nonlinear model using adaptive control technique is also designed. The achievement of this dissertation provides a fundamental knowledge of a novel welding process: DB-GMAW, and a good guidance for further studies about DBGMAW.

This thesis investigates the reception and treatment of the refugees from Hungary and Egypt who arrived in France and in Britain after the Hungarian revolution and the Suez crisis. The thesis argues that the reception of the refugees from Hungary and from Egypt was primarily linked to the French and British immigration policies and influenced by the Cold War context. The first part deals with the creation of the Hungarian refugees and their reception in France and Britain. Chapter two gives a brief account on the Hungarian revolution and what led 200,000 Hungarians to leave their country. Chapter three deals with the reception and treatment of the Hungarian refugees in France, and sets out to demonstrate how the revolution and the refugee situation were first exploited for propagandistic purposes and national political interests. It also examines immigration policy in France and how the Hungarians were to serve France's economic and demographic interests as candidates for immigration. French-Jewish responses to the refugee situation are also explored. Finally, it discusses the effects of the Cold War in the resettlement process. Chapter four explores similar questions about the Hungarians with respect to Britain. The second part of the thesis studies the expulsion of the French, British and stateless Jews from Egypt and their resettlement in France and Britain. Chapter five deals with who the refugees from Egypt were, and the unusual nature of their nationality and cultural background. Chapter six deals with the reception and treatment of refugees from Egypt in France, and focuses on how the French government and administration oscillated between obligation and desire to provide relief to the French Jews of Egypt, as they were not considered to be suitable candidates for resettlement in France according to immigration policies and practices. As most of the refugees from Egypt were Jewish, the chapter also looks at the Jewish specificity of the resettlement policy and how their resettlement made the refugees question their French identity. Chapter seven discusses the reception of the refugees from Egypt in Britain. It analyses the different domestic context regarding the Suez crisis and its impact on the refugees. The question of identity and cultural background is also explored.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

abstract: Facial Expressions Recognition using the Convolution Neural Network has been actively researched upon in the last decade due to its high number of applications in the human-computer interaction domain. As Convolution Neural Networks have the exceptional ability to learn, they outperform the methods using handcrafted features. Though the state-of-the-art models achieve high accuracy on the lab-controlled images, they still struggle for the wild expressions. Wild expressions are captured in a real-world setting and have natural expressions. Wild databases have many challenges such as occlusion, variations in lighting conditions and head poses. In this work, I address these challenges and propose a new model containing a Hybrid Convolutional Neural Network with a Fusion Layer. The Fusion Layer utilizes a combination of the knowledge obtained from two different domains for enhanced feature extraction from the in-the-wild images. I tested my network on two publicly available in-the-wild datasets namely RAF-DB and AffectNet. Next, I tested my trained model on CK+ dataset for the cross-database evaluation study. I prove that my model achieves comparable results with state-of-the-art methods. I argue that it can perform well on such datasets because it learns the features from two different domains rather than a single domain. Last, I present a real-time facial expression recognition system as a part of this work where the images are captured in real-time using laptop camera and passed to the model for obtaining a facial expression label for it. It indicates that the proposed model has low processing time and can produce output almost instantly. / Dissertation/Thesis / Masters Thesis Computer Science 2019

Zugl.: Köln, Universiẗat, Diss., 2007.

This thesis proposes a dB-linear programmable variable gain amplifier (VGA) and a voltage peak detector with digital calibration for FPW-based antibody sensing system. In the first topic, a dB-linear programmable variable gain amplifier is proposed. By using two source followers as the input terminals, input signals with very low DC offset could be received. The linear local-feedback transconductors are employed to be trans-condurctor-stage and load-stage. Besides, a reconfiguration method is used to reduce the layout area and improve the linearity of the gain to attain gain error less than 0.86 dB measured on silicon. In the second topic, a voltage peak detector with digital calibration is proposed. The voltage peak of the input sine-wave signal is sampled and held by using an integra-tor, a digital-to-analog converter, and a voltage comparator to generate a square-wave signal. Besides, the voltage error caused by the propagation delay could be calibrated by the proposed digital calibration method. The frequency of input signal is up to 20 MHz and the voltage error is justified to be less than 0.81 % by simulations.

<p>Both artificial intelligence (AI) and database (DB) communities have advantages in incorporating features from each other's areas. From a DB view, handling of complexity in today's information systems can be aided by incorporating AI features, and database environments could gain in flexibility by entrusting some of their functionality to agent systems. Contemplated from the AI view, agent systems could gain in robustness by being based on DB-systems.</p><p>By applying the semantics of database-transaction to interactions between agents in a multiagent-system, and analysing the consequences, this project endeavours to cross borders of the two research areas. In the project, states where drop-out of some agent is severe to the task fulfilment, of the system, have been identified, and examined after applying transaction semantics to the agent interactions. An existing system for multiagent applications, JADE, has been examined in order to investigate how problem situations are handled in practice. The result from this work shows the feasibility to contemplate both type of systems as very similar, but modelled and viewed in different ways.</p>