Performance Analysis of Cloud-Based Stream Processing Pipelines for Real-Time Vehicle Data

The recent advancements in stream processing systems enabled applications to exploit fast-changing data and provide real-time services to companies and users. This kind of application requires high throughput and low latency to provide the most value. This thesis work, in collaboration with Scania, provides fundamental blocks for the efficient development of latency-optimized, cloud-based, real-time processing pipelines. With investigation and analysis of the real-time Scania pipeline, this thesis delivers three contributions, that can be employed to speed up the process of developing, testing and optimizing low-latency streaming pipelines in many different contexts. The first contribution is the design and implementation of a generic framework for testing and benchmarking AWS based streaming pipelines. This framework allows collecting latency statistics from every step of the pipeline. The insights it produces can be used to quickly identify bottlenecks of the pipeline. Employing this framework, the study then proceeds to analyze the behaviour of Scania serverless streaming pipeline, which is AWS Kinesis and AWS Lambda services. The results show the importance of optimizing configuration parameters such as memory size and batch size. Several suggestions of best configurations and optimization of the pipeline are discussed. Finally, the thesis offers a survey of the main alternatives to Scania pipeline, including Apache Spark Streaming and Apache Flink. With an analysis of the benefits and drawbacks of each framework, We choose Flink as an alternative solution. Scania pipeline is adapted to Flink with new design and implementation. Benefits of Flink pipeline and performance comparison are discussed in detail. Overall, this work can be used as an extensive guide to the design and implementation of efficient, low-latency pipelines to be deployed on the cloud

Hierarchical Adaptive Loco-manipulation Control for Quadruped Robots

Legged robots have shown remarkable advantages in navigating uneven terrain. However, realizing effective locomotion and manipulation tasks on quadruped robots is still challenging. In addition, object and terrain parameters are generally unknown to the robot in these problems. Therefore, this paper proposes a hierarchical adaptive control framework that enables legged robots to perform loco-manipulation tasks without any given assumption on the object's mass, the friction coefficient, or the slope of the terrain. In our approach, we first present an adaptive manipulation control to regulate the contact force to manipulate an unknown object on unknown terrain. We then introduce a unified model predictive control (MPC) for loco-manipulation that takes into account the manipulation force in our robot dynamics. The proposed MPC framework thus can effectively regulate the interaction force between the robot and the object while keeping the robot balance. Experimental validation of our proposed approach is successfully conducted on a Unitree A1 robot, allowing it to manipulate an unknown time-varying load up to $7$ $kg$ ($60\%$ of the robot's weight). Moreover, our framework enables fast adaptation to unknown slopes (up to $20^\circ$) or different surfaces with different friction coefficients.Comment: Accepted to appear at IEEE International Conference on Robotics and Automation (ICRA), 202

Understanding kidney care needs and implementation strategies in low- and middle-income countries: conclusions from a "Kidney Disease: Improving Global Outcomes" (KDIGO) Controversies Conference

Evidence-based cinical practice guidelines improve delivery of uniform care to patients with and at risk of developing kidney disease, thereby reducing disease burden and improving outcomes. These guidelines are not well-integrated into care delivery systems in most low- and middle-income countries (LMICs). The KDIGO Controversies Conference on Implementation Strategies in LMIC reviewed the current state of knowledge in order to define a road map to improve the implementation of guideline-based kidney care in LMICs. An international group of multidisciplinary experts in nephrology, epidemiology, health economics, implementation science, health systems, policy, and research identified key issues related to guideline implementation. The issues examined included the current kidney disease burden in the context of health systems in LMIC, arguments for developing policies to implement guideline-based care, innovations to improve kidney care, and the process of guideline adaptation to suit local needs. This executive summary serves as a resource to guide future work, including a pathway for adapting existing guidelines in different geographical regions

High-quality, high-throughput measurement of protein-DNA binding using HiTS-FLIP

In order to understand in more depth and on a genome wide scale the behavior of transcription factors (TFs), novel quantitative experiments with high-throughput are needed. Recently, HiTS-FLIP (High-Throughput Sequencing-Fluorescent Ligand Interaction Profiling) was invented by the Burge lab at the MIT (Nutiu et al. (2011)). Based on an Illumina GA-IIx machine for next-generation sequencing, HiTS-FLIP allows to measure the affinity of fluorescent labeled proteins to millions of DNA clusters at equilibrium in an unbiased and untargeted way examining the entire sequence space by Determination of dissociation constants (Kds) for all 12-mer DNA motifs. During my PhD I helped to improve the experimental design of this method to allow measuring the protein-DNA binding events at equilibrium omitting any washing step by utilizing the TIRF (Total Internal Reflection Fluorescence) based optics of the GA-IIx. In addition, I developed the first versions of XML based controlling software that automates the measurement procedure. Meeting the needs for processing the vast amount of data produced by each run, I developed a sophisticated, high performance software pipeline that locates DNA clusters, normalizes and extracts the fluorescent signals. Moreover, cluster contained k-mer motifs are ranked and their DNA binding affinities are quantified with high accuracy. My approach of applying phase-correlation to estimate the relative translative Offset between the observed tile images and the template images omits resequencing and thus allows to reuse the flow cell for several HiTS-FLIP experiments, which greatly reduces cost and time. Instead of using information from the sequencing images like Nutiu et al. (2011) for normalizing the cluster intensities which introduces a nucleotide specific bias, I estimate the cluster related normalization factors directly from the protein Images which captures the non-even illumination bias more accurately and leads to an improved correction for each tile image. My analysis of the ranking algorithm by Nutiu et al. (2011) has revealed that it is unable to rank all measured k-mers. Discarding all the clusters related to previously ranked k-mers has the side effect of eliminating any clusters on which k-mers could be ranked that share submotifs with previously ranked k-mers. This shortcoming affects even strong binding k-mers with only one mutation away from the top ranked k-mer. My findings show that omitting the cluster deletion step in the ranking process overcomes this limitation and allows to rank the full spectrum of all possible k-mers. In addition, the performance of the ranking algorithm is drastically reduced by my insight from a quadratic to a linear run time. The experimental improvements combined with the sophisticated processing of the data has led to a very high accuracy of the HiTS-FLIP dissociation constants (Kds) comparable to the Kds measured by the very sensitive HiP-FA assay (Jung et al. (2015)). However, experimentally HiTS-FLIP is a very challenging assay. In total, eight HiTS-FLIP experiments were performed but only one showed saturation, the others exhibited Protein aggregation occurring at the amplified DNA clusters. This biochemical issue could not be remedied. As example TF for studying the details of HiTS-FLIP, GCN4 was chosen which is a dimeric, basic leucine zipper TF and which acts as the master regulator of the amino acid starvation Response in Saccharomyces cerevisiae (Natarajan et al. (2001)). The fluorescent dye was mOrange. The HiTS-FLIP Kds for the TF GCN4 were validated by the HiP-FA assay and a Pearson correlation coefficient of R=0.99 and a relative error of delta=30.91% was achieved. Thus, a unique and comprehensive data set of utmost quantitative precision was obtained that allowed to study the complex binding behavior of GCN4 in a new way. My Downstream analyses reveal that the known 7-mer consensus motif of GCN4, which is TGACTCA, is modulated by its 2-mer neighboring flanking regions spanning an affinity range over two orders of magnitude from a Kd=1.56 nM to Kd=552.51 nM. These results suggest that the common 9-mer PWM (Position Weight Matrix) for GCN4 is insufficient to describe the binding behavior of GCN4. Rather, an additional left and right flanking nucleotide is required to extend the 9-mer to an 11-mer. My analyses regarding mutations and related delta delta G values suggest long-range interdependencies between nucleotides of the two dimeric half-sites of GCN4. Consequently, models assuming positional independence, such as a PWM, are insufficient to explain these interdependencies. Instead, the full spectrum of affinity values for all k-mers of appropriate size should be measured and applied in further analyses as proposed by Nutiu et al. (2011). Another discovery were new binding motifs of GCN4, which can only be detected with a method like HiTS-FLIP that examines the entire sequence space and allows for unbiased, de-novo motif discovery. All These new motifs contain GTGT as a submotif and the data collected suggests that GCN4 binds as monomer to these new motifs. Therefore, it might be even possible to detect different binding modes with HiTS-FLIP. My results emphasize the binding complexity of GCN4 and demonstrate the advantage of HiTS-FLIP for investigating the complexity of regulative processes

Fluid Mechanics in Innovative Food Processing Technology

Generally, food industries employ traditional technologies and bulk devices for mixing, aeration, oxidation, emulsification and encapsulation. These processes are characterized by high energy consumption and result in high cost product, with limited diversity and usually with non-competitive quality. Moreover, the byproduct is also high. In recent years immense efforts have been dedicated to overcome these issues and major advances in food engineering have come from transfer and adaptation of knowledge from related fields such as chemical and mechanical engineering. It is well known that the majority of elements contribute to transport properties, physical and rheological behavior, texture and sensorial traits of foods are in micro-level. In this context invention at microscopic level is of critical importance to improve the existing foods quality while targeting also the development of new products. Therefore, microfluidics has a significant role in future design, preparation and characterization of food micro-structure. The diminutive scale of the flow channels in microfluidic systems increases the surface to volume ratio and is therefore advantageous for many applications. Furthermore, high quality food products can be manufactured by means of innovative microfluidic technology characterized by less energy consumption and a continuous process in substitution to the problematic batch one. To meet these challenges, this work is focused on main two tasks: (i) efficient micromixing, and (ii) production of microbubbles and microdroplets. Firstly, two novel 3D split and recombine (SAR) micromixers are designed on an extensive collection of established knowledge. Mixing characteristics of two species were elucidated via experimental and numerical studies associated with microchannels at various inlet flow-rate ratios for a wide range of Reynolds numbers (1-100); at the same time, results are compared with two well-known micromixers. It was found that performances of the mixers are significantly affected by their design, inlet flow-rate ratios and Reynolds numbers. The proposed micromixers show better efficiency (more than 90%) in all examined range of Reynolds numbers than the well-known basic mixers at each desired region; the required pressure-drop is also significantly less than that of the previous mixers. Furthermore, numerical residence time distribution (RTD) was also explored, which successfully predicts the experimental results. In a word, the presented new micromixers have advantages of high efficiency, low pressure-drop, simple fabrication, easy integration and ease for mass production. Secondly, four micro-devices are designed for the mono-dispersed droplets and bubbles generation. Two different experimental setups were used to create water droplet in silicone oil (W/O) and air bubble in silicone oil (A/O) for continuous flow rate from 10 ml/h to 230 ml/h. The mean size of droplet and bubble as well as frequency of generation can be controlled by dispersed and continuous flow rate. Besides, squeezing and dripping flow regimes are observed inside the four devices over a broad range of Capillary numbers: 0.01~0.18. Among the examined four devices, T-1 and T-2 provide smaller droplet (100 µm) and higher production rate. Furthermore, negative pressure setup provides more robust bubble generation but positive pressure yields better production rate. In addition, droplet and bubble diameter is about four times less than the microchannel dimension, therefore small droplet and bubble can be generated spending less energy. In summary, the investigation in this dissertation reflects that both SAR micromixers and micro-devices are very efficient and can be applied to meet the growing demands of food industries. The first part of the thesis, chapters 1 to 5, addresses state of art, design, experimental technique and results of micromixers. The second part, chapters 6 to 9, presents background, construction of devices, tests and results related to the production of microdroplets and microbubbles. Finally, chapter 10 summaries the whole presented work

A technology and policy analysis for global E-business

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2002.Includes bibliographical references (p. 49-51).We introduce an e-business analytical framework that focuses on transaction flows, including information, physical goods, and services. Within this framework, global e-business involves transaction flows that cross both organizational and national boundaries. Many challenging technology and policy issues arise from this trans-boundary characteristic of global e-business. These issues are analyzed using web aggregation as an example global e-business application. We start the analysis by introducing web aggregation services and their enabling technologies. Our survey of current status of web aggregation indicates that most services are still operated regionally despite their global presence. Although benefits of web aggregation have been realized in regions with extensive use of information aggregation, little is done at the global level. Our case study on worldwide price distribution of a nearly homogeneous consumer electronics product indicates great potential for global aggregation to bring information and efficiency to the global market. In addition to lack of global integration, we identified other deficiencies of web aggregation. Technological challenges and possible solutions to overcoming these deficiencies are discussed. However, having technological capability for trans-boundary information flow does not solve all problems in global aggregation. National policies often prohibit such flow into nations that have different policies, especially in database and privacy protection areas. We analyze these policy issues and propose future research on international policy harmonization.by Hongwei Zhu.S.M

Analysis and modeling a distributed co-operative multi agent system for scaling-up business intelligence

Modeling A Distributed Co-Operative Multi Agent System in the area of Business Intelligence is the newer topic. During the work carried out a software Integrated Intelligent Advisory Model (IIAM) has been develop, which is a personal finance portfolio ma