HLS-based dataflow hardware architecture for Support Vector Machine in FPGA

Implementing fast and accurate Support Vector Machine (SVM) classifiers in embedded systems with limited compute and memory capacity and in applications with real-time constraints, such as continuous medical monitoring for anomaly detection, can be challenging and calls for low cost, low power and resource efficient hardware accelerators. In this paper, we propose a flexible FPGA-based SVM accelerator highly optimized through a dataflow architecture. Thanks to High Level Synthesis (HLS) and the dataflow method, our design is scalable and can be used for large data dimensions when there is limited on-chip memory. The hardware parallelism is adjustable and can be specified according to the available FPGA resources. The performance of different SVM kernels are evaluated in hardware. In addition, an efficient fixed-point implementation is proposed to improve the speed. We compared our design with recent SVM accelerators and achieved a minimum of 10x speed-up compared to other HLS-based and 4.4x compared to HDL-based designs

Study Of Wave-Induced Scour Depth Around Group Of Piles Using Support Vector Machines

Various arrangements of pile groups are widely being used as supports of marine structures. As piles are located on erodible beds of the sea, scouring is a threat to such structures and the scour depth amounts should be considered well in their designs. Though most of these supports are constructed in form of groups of piles, majority of studies were concentrated on predictions of scouring around single piles whereas the arrangement of the piles and the spaces between them in arrangements as well as their geometry, sediment and wave characteristics should also be studied. Despite the importance of the scour hole depths, the existing prediction formulas are not capable of accurate estimations around pile groups with different arrangements. Hence, developing a robust model for the estimation of scour depth seems necessary. One of the most common approaches as an alternative to empirical ones is the soft computing methods. Artificial Neural Network as the most famous data-mining method has been successfully applied in scour studies. But there are still needs of more assessments in their applications on pile group case studies. In addition, Support Vector Machines as one of the recently applied soft computing models in scouring has scarcely been studied so far. In this study, series of large scale scouring experiments were done for various arrangements of pile groups with different pile and arrangement characteristics exposed to waves of shallow water and equilibrium scour depth around them were measured in wave basin of Ujigwa Open Laboratory of Kyoto University. Finally, by applying the provided experimental data, the applicability of data mining models were assessed in predictions of pile group scour properties. Results indicate that, data mining approaches can provide more reliable predictions of scouring properties due to waves compared to current available empirical formulae

Layers of intervention for revitalization of historical districts

The historical context of a city is part of its physical body, the existence of which has begun in the far past and is now challenging and opposing modern urban developments. Today, in the process of making optimum use of urban lands, treating the historical contexts has turned into a dilemma, for with such blocks being of vast areas, it is impossible for them to be frozen and turn into museums; on the other hand, it’s impossible to halt the process of developing new buildings, the visual and historical properties of which do not match the ones of the old context. Now the question, in studies regarding the revitalization of ancient, historical contexts is: how can the paradox of modern life and its needs be combined with the old urban context? ‘Oudlaajaan, a neighborhood in the west of Tehran, was built during Safavid Dynasty and is now, due to wrong policies applied by urban management authorities during different eras, worn in many aspects. With the inhabitants not feeling to belong in the place and the presence of functions which do not match the physical body, the area has completely lost its visual values. In case we want to perform a more realistic and effective revitalization, it’s better to view the historical context, not as a combination of building blocks, but as a system. In this article, we tend to present four layers of action to revitalize ancient contexts. It’s necessary for planners of urban policies to legislate and make their decisions in each one of these layers, and through the hierarchy mentioned that will be mentioned

Identfying effective elements in the landscape of historical districts (Typical sample: Oudlaajaan neighborhood-Tehran)

The historical context of a city is part of its cultural property, reflecting its identity and visual values through forming the inhabitants’ collective memory and showing the lifestyle of their ancestors. One of the most important questions has always been: what are the factors that guarantee the permanence of the landscape of a historical context? Finding these factors and classifying them into a hierarchy, depending on their amount of effectiveness, will clarify how much change needs to be applied to each one of them; it will also make way for urban management authorities to start planning the changes. For this purpose, ‘Oudlaajaan - one of Tehran’s residential neighborhoods built in Safavid Dynasty - was chosen. This district has been registered by Tehran’s Cultural Heritage Organization for its historical value. But unfortunately, due to the wrong policies applied by the urban management during different eras, it has lost all its physical values. Our interpretation of a city’s landscape is in the first place visual, and is formed by moving inside the structure of the city and an association of ideas. There, we can experience the environment in the form of a series of visual intakes. The mind, then, establishes a connection between the past experiences and the new environment. On this basis, we divided the district into several survey blocks and chose some people of each block randomly to fill out our questionnaires, asking them about their visual experience of the district. Based on the results of both theoretical studies and the surveys, we could identify the dimension and shape of the pathways, signs and turning points, activities, architectural characteristics of the buildings and vegetation, serving as the most important landmarks of the district, a comprehensive understanding of which can lead to an explicit plan for applying changes to the context

The Effects of an Obesogenic Diet on Liver Oxysterol Metabolism in C57BL/6J Mice

Oxysterols are key regulators of lipid metabolism and play a role in the etiology of atherosclerosis; however, our current understanding of tissue levels of oxysterols during different disease states such as obesity is limited. The purpose of this study was to quantify the effects of obesity induced by a high fat-cholesterol (HFC) diet on liver oxysterol metabolism. Male C57BL/6J mice were fed either a standard control diet (5.0% w/w fat, 0.03% w/w chol) or a HFC (21.0% w/w fat, 0.15% w/w chol) diet for 24 weeks. Comparisons between dietary groups were made with independent sample t-tests. Total body mass and liver tissue mass of the HFC group was greater (33.2±5.2 vs. 49.0±3.6 g and 1.4±0.3 vs. 3.9±0.8 g, respectively; P\u3c0.05) than the control group. In the HFC group, a 3.3 fold increase in lipid mass of the liver tissue was due to increased levels of cholesterol (0.10±0.01 vs. 0.33±0.06 mg/mg protein; P\u3c0.05) and triglyceride (0.37±0.05 vs. 1.49±0.12 mg/mg protein; P\u3c0.05). In the HFC diet, 4β-OH, 5,6β-epoxy, and 27-OH were greater and 7-keto was lower when compared to the control diet. Post-dietary liver 4β-OH, 5,6β-epoxy, and 27-OH were increased in the HFC diet group. Interestingly, despite increased oxysterol levels no significant changes in mRNA levels were observed for oxysterol-related enzymes CYP3A11, CYP27A1 or CYP7A1. The 24-week HFC diet was effective at promoting obesity and hepatic steatosis in mice. Due to the low concentration of oxysterols in the diet, it is unlikely that the oxysterols in the diet had a significant impact on liver oxysterols. Furthermore, our results suggest that the increased hepatic oxysterol levels observed in mice on the obesogenic diet were not due to increased rates of oxysterol synthesis

Serum HDL cholesterol uptake capacity in subjects from the MASHAD cohort study: its value in determining the risk of cardiovascular endpoints

Background: The efficiency of high-density lipoprotein (HDL) to efflux cholesterol contributes to the reverse cholesterol transport (RCT) pathway as one of HDL’s proposed functions and depends on the ability of HDL to uptake cholesterol. We aimed to investigate cholesterol uptake capacity (CUC) by a newly developed assay in samples from the MASHAD (Mashhad Stroke and Heart Atherosclerotic Disorders) cohort study. Method: The study population comprised 153 individuals developed CVD diagnosed by a specialist cardiologist, over 6 years of follow-up, and 350 subjects without CVD. We used a modified CUC method to evaluate the functionality of HDL in serum samples. Result: The CUC assay was highly reproducible with values for inter- and intra-assay variation of 13.07 and 6.65, respectively. The mean serum CUC was significantly lower in the CVD group compared to control (p = 0.01). Although, there were no significant differences in serum HDL-C between the groups and there was no significantly association with risk of progressive CVD. Multivariate logistic regression analysis showed that there was a significantly negative association between CUC and risk of CVD after adjustment for confounding parameters (OR = 0.57, 95% CI = 0.38–0.87, p = 0.009). The CUC was also inversely and independently associated with the risk of CVD event using Cox proportional hazards models analysis (HR = 0.62; 95% CI = 0.41–0.94, p = 0.02). We determined the optimum cutoff value of 1.7 a.u for CUC in the population. Furthermore, the CUC value was important in determining the CVD risk stratification derived from data mining analysis. Conclusions: Reduced HDL functionality, as measured by CUC, appears to predict CVD in population sample from north-eastern Iran

異なる頭部形状を有する連続した水制工周辺の流れと土砂輸送に関する研究

京都大学0048新制・課程博士博士(工学)甲第18560号工博第3921号新制||工||1602(附属図書館)31460京都大学大学院工学研究科社会基盤工学専攻(主査)教授 中川 一, 教授 藤田 正治, 准教授 川池 健司学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDFA

Hardware Acceleration of Microwave Imaging Algorithms

Microwave Imaging (MWI) is a technique that allows to reconstruct an image of the internal structure of an object by irradiating the object with a known incident field and by acquiring and processing the scattered field. As such, MWI can be used as a diagnostic technique for various medical issues, such as brain stroke or breast cancer. However, the image reconstruction process entails a sequence of compute-intensive algorithms, which we call “kernels.” The kernels execution time might become an issue when the time to diagnosis is a key factor. To speed up the kernels execution, we can use hardware acceleration techniques. In this chapter, we will identify the complex computational kernels that are recurrent in MWI. Then, we present the methodologies to design specific hardware accelerators in Field-Programmable Gate Arrays (FPGAs) for these kernels by means of an efficient design method called High Level Synthesis (HLS) and by several HLS-based hardware optimization techniques. In addition, we will present new methodologies for design automation in HLS-based hardware designs. The results show that the presented HLS optimizations and design automation techniques can significantly improve the efficiency of the hardware accelerator designs for MWI

Efficient Training and Hardware Co-design of Machine Learning Models

To implement a Machine Learning (ML) model in hardware (Hw), usually a first Design Space Exploration (DSE) optimizes the model hyper-parameters in search of the best ML performance, while a second DSE finds the configuration with the best Hw performance. Multiple iterations of these steps might be needed as the optimal ML model may not necessarily be implementable. To reduce the design-time and provide the designer with a single exploration environment, we propose a general framework based on Bayesian Optimization (BO) and High-Level Synthesis (HLS), which performs at once both DSEs generating efficient Pareto curves in the space of ML and Hw performance

Histological study of the annular ligament in the rabbitfish eye (Siganus sp.)

Rabbitfish is economically valuable teleost species which lives in shallow coastalwaters. Two species of rabbit fish have been recognized in southern sea of Iran (Persiangulf) as namely Siganus sutor and Siganus javus. In the current study, in order toinvestigate the histology of the annular ligament of the S. javus’ eye, the prepared sectionsof the eyes of twelve healthy specimens were studied under light microscope. The resultsrevealed that annular ligament is a crescent shape structure which is situated between thescleral stroma anteriorly and the iris posteriorly. It contains a vascularized, amorphousand granular matrix with fibers of dense connective tissue; high glycogen content andmelanin pigments