Miracle-dz/UniFAR-FTUs huggingface dataset:
AIMD-PQ: A path quality based TCP-friendly AIMD algorithm for multipath congestion control in heterogeneous wireless networks

Multipath congestion control algorithms are supposed to be friendly to traditional single-path TCP (SP-TCP). Existing multipath Additive Increase Multiplicative Decrease algorithms (MP-AIMD) for multipath TCP (MP-TCP) are confronted with the problems: 1) they are unfair to SP-TCP when the multiple available paths have heterogeneity, e.g. different RTT; 2) they all use packet losses as congestion signals and induce spurious backoffs on a wireless link with high error rate; 3) congestion window fluctuation reduces their potential to support smooth high-quality service such as multimedia applications. This paper proposes a path quality based multipath AIMD (AIMD-PQ) to tackle the above problems. We utilize the round trip time (RTT) on each sub-path to formulate the path quality estimation. AIMD-PQ balances the loads among its sub-paths, moves traffic off the most congested sub-path, and triggers Multiplicative Decrease by both packet loss and path quality signals. Simulation results show that AIMD-PQ improves both the TCP-friendliness and window fluctuation performance of MP-TCP in a heterogeneous wireless network environment.
A CCN-based Social Network application optimising network proximity

Online Social Networking (OSN) applications attracted millions of people in few years and are considered as the success story of current Internet applications. However, how they work is unclear for both end-users and researchers, since the developers keep the system architecture secret and use encryption mechanisms. In this paper, we present the main outcomes of our analysis of one of the most well known OSNs, Twitter, focusing on the networking behaviour, the involved entities, their location, etc. Detecting that the current network behaviour of those applications is not in line with current end-users behaviours, where locality is important, we propose to adapt the OSNs to a Content-Centric Networking (CCN) approach, which could improve the delivery and reduce the network load and server load. Indeed, CCN is a new networking paradigm focusing on interest based requests of content itself independently on location and so has features very close to OSNs. This paper then introduces our proposal for a CCN-based architecture for OSN applications, with a naming and routing proposal. We also present the demonstrator we have implemented as proof-of-concept and the testbed we set up for functional testing purposes.
The effect of minihaloes on cosmic reionization

One of the most debated issues in the theoretical modelling of cosmic reionization is the impact of small-mass gravitationally bound structures. We carry out the first numerical investigation of the role of such sterile 'minihaloes' (MHs), which serve as self-shielding screens of ionizing photons. MHs are too small to be properly resolved in current large-scale cosmological simulations, and thus we estimate their effects using a subgrid model, considering two cases that bracket their effect within this framework. In the 'extreme-suppression' case in which MH formation ceases once a region is partially ionized, their effect on cosmic reionization is modest, reducing the volume-averaged ionization fraction by an overall factor of less than 15 per cent. In the other extreme, in which MH formation is never suppressed, they delay complete reionization as much as Δz ∼ 2, in rough agreement with the results from a previous semi-analytical study by the authors. Thus, depending on the details of the MH formation process, their effect on the overall progress of reionization can range from modest to significant, but the MH photon consumption is by itself insufficient to force an extended reionization epoch.
CSE 255 Winter 2015 Assignment 1 : Eye Detection using Histogram of Oriented Gradients and Adaboost Classifier

An image of an eye is known to have a certain shape, roughly ellipse shaped. And so the Histogram of Oriented Gradient (HOG) feature is a good descriptor for this type of detection. In this paper, the eye detector is trained with HOG features using an Adaptive Boosting (AdaBoost) algorithm to train and learn a set of weak classifiers. It is shown to work fairly well although it underperforms when compared to the detectors included with openCV. However, as will be discussed in this paper, there is a lot of room for improving the eye detector. Note to the grader of this paper: The section titles have a “Task” label with numbers corresponding to the assignment1.pdf instructions to help grade each section. I have tried my best to keep everything in their corresponding sections.
On the conditions used to prove oracle results for the Lasso

Oracle inequalities and variable selection properties for the Lasso in linear models have been established under a variety of different assumptions on the design matrix. We show in this paper how the different conditions and concepts relate to each other. The restricted eigenvalue condition (Bickel et al., 2009) or the slightly weaker compatibility condition (van de Geer, 2007) are sufficient for oracle results. We argue that both these conditions allow for a fairly general class of design matrices. Hence, optimality of the Lasso for prediction and estimation holds for more general situations than what it appears from coherence (Bunea et al, 2007b,c) or restricted isometry (Candes and Tao, 2005) assumptions.
Data integration using similarity joins and a word-based information representation language

The integration of distributed, heterogeneous databases, such as those available on the World Wide Web, poses many problems. Herer we consider the problem of integrating data from sources that lack common object identifiers. A solution to this problem is proposed for databases that contain informal, natural-language “names” for objects; most Web-based databases satisfy this requirement, since they usually present their information to the end-user through a veneer of text. We describe WHIRL, a “soft” database management system which supports “similarity joins,” based on certain robust, general-purpose similarity metrics for text. This enables fragments of text (e.g., informal names of objects) to be used as keys. WHIRL includes textual objects as a built-in type, similarity reasoning as a built-in predicate, and answers every query with a list of answer substitutions that are ranked according to an overall score. Experiments show that WHIRL is much faster than naive inference methods, even for short queries, and efficient on typical queries to real-world databases with tens of thousands of tuples. Inferences made by WHIRL are also surprisingly accurate, equaling the accuracy of hand-coded normalization routines on one benchmark problem, and outerperforming exact matching with a plausible global domain on a second.
Social Big Data and Privacy Awareness

Based on the rapid development of Big Data, the data from the online social network becomea major part of it. Big data make the social networks became data-oriented rather than social-oriented. Taking this into account, this dissertation presents a qualitative study to research howdoes the data-oriented social network aﬀect its users’ privacy management for nowadays.Within this dissertation, an overview of Big Data and privacy issues on the social network waspresented as a background study. We adapted the communication privacy theory as a frameworkfor further analysis how individuals manage their privacy on social networks. We study socialnetworks as an entirety in this dissertation. We selected Facebook as a case study to present theconnection between social network, Big Data and privacy issues.The data that supported the result of this dissertation collected by the face-to-face and in-depthinterview study. As consequence, we found that the people divided the social networks intodiﬀerent level of openness in order to avoid the privacy invasions and violations, according totheir privacy concern. They reduced and transferred their sharing from an open social networkto a more close one. However, the risk of privacy problems actually raised because peopleneglected to understand the data process on social networks. They focused on managed theeveryday sharing but too easily allowed other application accessed their personal data on thesocial network (such like the Facebook proﬁle).
Evaluation of a Queue Management Method for TCP Communications over Multi-hop Wireless Links

In this paper we propose a queue management method for improving TCP performance over multihop wireless links. With our proposed control method, packet loss in the wireless link is completely eliminated and all packets are delivered in the correct order. No change is required to TCP itself or to the servers. Our proposed method is implemented between the media access control layer (MAC) and logical link layer in each node, and is designed to help the local retransmission control in the MAC layer. Computer simulation experiments show that our proposed method can communicate in high error wireless link conditions even when conventional methods cannot maintain communication. The fairness problem of TCP communication, between connections with different round trip times, is also improved.
Research of Edge-Collapse-Based 3-D Model Simplification

Highly detailed geometric models are rapidly becoming common-place in computer graphics. But sometimes it is often desirable to use approximations in place of excessively detailed models to control processing time. This paper introduces a surface simplification algorithm that based on edge-collapse. The algorithm uses quadric error metrics to confirm the position of new vertex in order to control the error, and gives a new cost function of the edge cost. This algorithm can preserve the important feature of original 3D model efficiently and control the error effectively. The results show that this algorithm is memory efficient, allowing the simplification of very large polygonal models, and can rapidly produce high quality approximations of polygonal models.
First LIGO search for gravitational wave bursts from cosmic (super)strings

We report on a matched-filter search for gravitational wave bursts from cosmic string cusps using LIGO data from the fourth science run (S4) which took place in February and March 2005. No gravitational waves were detected in 14.9 days of data from times when all three LIGO detectors were operating. We interpret the result in terms of a frequentist upper limit on the rate of gravitational wave bursts and use the limits on the rate to constrain the parameter space (string tension, reconnection probability, and loop sizes) of cosmic string models.
' s personal copy What ’ s magic about magic numbers ? Chunking and data compression in short-term memory

Short term memory is famously limited in capacity to Miller’s (1956) magic number 7 ± 2— or, in many more recent studies, about 4 ± 1 ‘‘chunks’’ of information. But the definition of ‘‘chunk’’ in this context has never been clear, referring only to a set of items that are treated collectively as a single unit. We propose a new more quantitatively precise conception of chunk derived from the notion of Kolmogorov complexity and compressibility: a chunk is a unit in a maximally compressed code. We present a series of experiments in which we manipulated the compressibility of stimulus sequences by introducing sequential patterns of variable length. Our subjects’ measured digit span (raw short term memory capacity) consistently depended on the length of the pattern after compression, that is, the number of distinct sequences it contained. The true limit appears to be about 3 or 4 distinct chunks, consistent with many modern studies, but also equivalent to about 7 uncompressed items of typical compressibility, consistent with Miller’s famous magical number. 2011 Elsevier B.V. All rights reserved.
Continuous similarity-based queries on streaming time series

In many applications, local or remote sensors send in streams of data, and the system needs to monitor the streams to discover relevant events/patterns and deliver instant reaction correspondingly. An important scenario is that the incoming stream is a continually appended time series, and the patterns are time series in a database. At each time when a new value arrives (called a time position), the system needs to find, from the database, the nearest or near neighbors of the incoming time series up to the time position. This paper attacks the problem by using fast Fourier transform (FFT) to efficiently find the cross correlations of time series, which yields, in a batch mode, the nearest and near neighbors of the incoming time series at many time positions. To take advantage of this batch processing in achieving fast response time, this paper uses prediction methods to predict future values. When the prediction length is long, FFT is used to compute the cross correlations of the predicted series (with the values that have already arrived) and the database patterns, and to obtain predicted distances between the incoming time series at many future time positions and the database patterns. If the prediction length is short, the direct computation method is used to obtain these predicted distances to avoid the overhead of using FFT. When the actual data value arrives, the prediction error together with the predicted distances is used to filter out patterns that are not possible to be the nearest or near neighbors, which provides fast responses. Experiments show that with reasonable prediction errors, the performance gain is significant. Especially, when the long term predictions are available, the proposed method can handle incoming data at a very fast streaming rate.
Efficiency Analysis and Ranking of Major Container Ports in Northeast Asia: An Application of Data Envelopment Analysis

The Northeast Asia is emerging as the third hub of world economy next to EU and NAFTA. Neighboring countries in the region enter into keen competition to take the lead in global supply chain network. This competition is accelerated by the fast growing Chinese economy. Under these circumstances, it is necessary for container ports not only to extend the facilities but also to improve the operational efficiency for gaining competitive advantage over their rivals. By applying DEA models, we attempt to measure the operational efficiency of the 19 major container ports in the Northeast Asia. This analysis of operational efficiency reveals the causes of inefficient operation and also suggests how to overcome the drawbacks. An additional analysis for ranking the container ports was conducted using the super-efficiency model. According to the results of this study, eight container ports are operated efficiently among which Hongkong is ranked top as the most efficient port in the Northeast Asia. Two Korean container ports, both Busan and Gwangyang show relatively low operational efficiency compared to their rival ports. To become efficient, they need to improve either cut their labor and capital (inputs) or increase their TEU (output) of the two ports.
Continuous reactive-based position-attitude control of quadrotors

A new control scheme for position-orientation tracking of underactuated quadrotor robotic vehicle is proposed. A quaternion-based sliding surface parametrizes the open-loop error equation of orientation dynamics, then a second order sliding mode (SOSM) is synthesized for global exponential stabilization of attitude coordinates along an orientation equilibrium manifold. This SOSM for any initial condition leads to a simplified design of a torque PD controller for position dynamics, for globally uniformly ultimately bounded of position trajectories. The SOSM reacts to the effect of the PD as if it were an endogenous persistent disturbance, which vanishes until it reaches its equilibrium position manifold. In contrast to other results that consider the full model without linearization nor further simplifications, our proposal yields a controller which is smooth and does not require the dynamic model. Since the parametrization of attitude representation is global, aggressive maneuvering capabilities are exhibited. Simulations are presented for a variety of flight regimes, including carry out helixes and loops at high angular velocities. Real-time experiments provide a glimpse of the closed-loop performance for a custom made quadrotor.
Do Fertilizer Subsidies Affect the Demand for Commercial Fertilizer? An Example from Malawi

Fertilizer subsidies are again becoming a popular policy tool in sub-Saharan Africa. Despite their potential, little empirical research has been undertaken on how subsidies affect a farmer’s decision to purchase commercial fertilizer. Because of this, there is a dearth of information on how fertilizer subsidy programs affect total fertilizer and commercial fertilizer use. This paper uses a double hurdle model with panel data from Malawi to answer these questions. It also uses a control function approach to deal with endogeneity of subsidized fertilizer in a commercial fertilizer demand equation. Our results indicate that subsidized fertilizer negatively impacts participation in commercial markets. Once the participation decision has been made however, demand for commercial fertilizer is driven by farm size, assets and fertilizer price and maize price rather than by whether a farmer received subsidized fertilizer. We calculate the average partial effects of subsidized fertilizer and find that on average, receiving one additional kilogram of subsidized fertilizer causes a farmer to purchase 0.20 fewer kilograms of commercial fertilizer. This indicates that fertilizer subsidies may adversely affect the demand for commercial fertilizer and also raise total fertilizer use by a somewhat smaller quantity than the quantity of fertilizer distributed through the subsidy program.
Genomic Survey of the Non-Cultivatable Opportunistic Human Pathogen, Enterocytozoon bieneusi

Enterocytozoon bieneusi is the most common microsporidian associated with human disease, particularly in the immunocompromised population. In the setting of HIV infection, it is associated with diarrhea and wasting syndrome. Like all microsporidia, E. bieneusi is an obligate, intracellular parasite, but unlike others, it is in direct contact with the host cell cytoplasm. Studies of E. bieneusi have been greatly limited due to the absence of genomic data and lack of a robust cultivation system. Here, we present the first large-scale genomic dataset for E. bieneusi. Approximately 3.86 Mb of unique sequence was generated by paired end Sanger sequencing, representing about 64% of the estimated 6 Mb genome. A total of 3,804 genes were identified in E. bieneusi, of which 1,702 encode proteins with assigned functions. Of these, 653 are homologs of Encephalitozoon cuniculi proteins. Only one E. bieneusi protein with assigned function had no E. cuniculi homolog. The shared proteins were, in general, evenly distributed among the functional categories, with the exception of a dearth of genes encoding proteins associated with pathways for fatty acid and core carbon metabolism. Short intergenic regions, high gene density, and shortened protein-coding sequences were observed in the E. bieneusi genome, all traits consistent with genomic compaction. Our findings suggest that E. bieneusi is a likely model for extreme genome reduction and host dependence.
Improved OpenMM algorithms for CUDA and OpenCL using new stochastic dynamics and the Berendsen thermostat

The simulations done in molecular dynamics (MD) are used to learn about the behavior of macromolecular systems. While analyzing large macromolecular systems, the computation can last long, many times for days, weeks and months, due to which the need of parallelization occurs for shortening the time. The graphics processing unit (GPU) yields to multithread computational capacity by the use of CUDA high-level language which suits the molecular dynamics algorithms. The OpenCL platform allows its reckoning kernels to run without difficulty on GPUs, as well as on multicore computers. We developed a new thermostat that combines Langevin dynamics with the global Berendsen thermostat which is parallelized in CUDA, as well as in OpenCL. The GPU parallelization is presented in this paper by applying stochastic dynamics, respectively the Langevin integrator, together with the Berendsen thermostat. A system of atoms is tested by taking into consideration the friction coefficient and the coupling parameter.
Fractal-generated wakes

This thesis aims at getting a better understanding of the properties, scalings and similarities of turbulent axisymmetric wakes, as well as possible applications that arise from the information learnt. Over the last 60 years, axisymmetric wakes have been generated using axisymmetric bodies, such as disks, spheres and bodies of revolution, and key parameters such as the drag coefficient, shedding frequency and similarity and scaling of the wake width and velocity deficit have been documented and verified by numerous experimental and numerical studies. However, in this thesis the aim is to use asymmetric wake generators to generate the axisymmetric wakes and see if this has any effect on the results. These asymmetric wake generators are made up of a square plate and a number of fractal plates, where the perimeter of the plates can be increased by as much as 16 times that of the square. As well as increasing the perimeter, the irregularity, or fractal dimension, is also increased. It is found that the drag coefficient of the fractal plates is increased to beyond the values observed for regular polygons and a theory is presented that could explain this possible change in the drag coefficient, whereby the drag coefficient is the product of the volume of the wake and the dissipation of the turbulent kinetic energy within the wake. Wake profiles were taken over a moderate downstream distance of up to 50`, where ` is the characteristic length of the plates, defined as the square root of the frontal area. Using the measured integral width of the wake directly, it was found that the volume of the wake decreased with increasing fractal dimension and iteration. Using these values, the similarity and scaling of the wake was carried out and a new high local Reynolds number scaling for turbulent axisymmetric wakes was discovered and for which the data from the fractal plates fit very well. The intensity of the vortex shedding is also shown to decrease with increasing perimeter and fractal dimension and it is found that the rate at which these vortices are shed is the same for all plates if the characteristic length is used to normalise the frequency. It is also discussed how the decrease in the energy of the vortex shedding is linked to the volume of the wake. Finally, the use of fractal geometries to manipulate the wake to reduce noise is also investigated, with emphasis placed on various aspects of an aircrafts wing.
A unified optimization based learning method for image retrieval

In this paper, an optimization based learning method is proposed for image retrieval from graph model point of view. Firstly, image retrieval is formulated as a regularized optimization problem, which simultaneously considers the constraints from low-level feature, online relevance feedback and offline semantic information. Then, the global optimal solution is developed in both closed form and iterative form, providing that the latter converges to the former. The proposed method is unified in the senses that 1) it makes use of the information from various aspects in a global optimization manner so that the retrieval performance might be maximally improved; 2) it provides a natural way to support two typical query scenarios in image retrieval. The proposed method has a solid mathematical ground. Systematic experimental results on a general-purpose image database demonstrate that it achieves significant improvements over existing methods.