Miracle-dz/UniFAR-FTUs huggingface dataset:
Quarantine: Java Heap Protection in the Presence of Native Code

By using Java Native Interface (JNI), programmers can integrate Java programs with legacy systems or third-party libraries written in other languages (e.g., C, C++, and Pascal). However, the use of JNI may violate Java type safety feature because these native programs are not type-safe. As a result, such integration can cause memory errors that can be difficult to isolate. In this paper, we propose Quarantine, a runtime system that preserves memory safety of Java objects in spite of integration with native code. The goal of Quarantine is ensuring that no native threads can directly access objects in the Java heap. We provide a formal proof that our technique can achieve this goal. We then implement a prototype of Quarantine in the OpenJDK 1.7 running in interpreter mode. To evaluate the feasibility of our prototype, we conduct experiments to measure the runtime overhead of Quarantine. Because our current implementation is unoptimized, the overhead can be as high as 42%. We then discuss ways to reduce this overhead and perform a case study of using Quarantine to avoid heap corruption due to out-of-bound writes.
Socio-Economic Implications of Wireless Sensor Networks with Special Reference to its Application in Agriculture

Sensor Networks have been found to be one of the most important technologies for 21st century. Wireless sensor network are gaining greater attention from the research community. Sensor node which is the basic element of wireless node network is composed of sensing computation and wireless communication unit. These sensor nodes are hence capable of observing physical phenomenon, process the observed and received information and communicate the observed or processed information to the nearby sensor nodes to form a network of sensor nodes called Wireless Sensor Networks. The wireless networking capability of the sensor enabled nodes have resulted in various interesting applications ranging from surveillance, smart homes, precision agriculture, disaster detection, and traffic controlto vehicular andsupply chain management applications.
Translational and Scaling Formation Maneuver Control via a Bearing-Based Approach

This paper studies distributed maneuver control of multiagent formations in arbitrary dimensions. The objective is to control the translation and scale of the formation while maintaining the desired formation pattern. Unlike conventional approaches where the target formation is defined by relative positions or distances, we propose a novel bearing-based approach where the target formation is defined by inter-neighbor bearings. Since the bearings are invariant to the translation and scale of the formation, the bearing-based approach provides a simple solution to the problem of translational and scaling formation maneuver control. Linear formation control laws for double-integrator dynamics are proposed and the global formation stability is analyzed. This paper also studies bearing-based formation control in the presence of practical problems, including input disturbances, acceleration saturation, and collision avoidance. The theoretical results are illustrated with numerical simulations.
Defining the Genome Features of Escherichia albertii, an Emerging Enteropathogen Closely Related to Escherichia coli

Escherichia albertii is a recently recognized close relative of Escherichia coli. This emerging enteropathogen possesses a type III secretion system (T3SS) encoded by the locus of enterocyte effacement, similar to enteropathogenic and enterohemorrhagic E. coli (EPEC and EHEC). Shiga toxin-producing strains have also been identified. The genomic features of E. albertii, particularly differences from other Escherichia species, have not yet been well clarified. Here, we sequenced the genome of 29 E. albertii strains (3 complete and 26 draft sequences) isolated from multiple sources and performed intraspecies and intragenus genomic comparisons. The sizes of the E. albertii genomes range from 4.5 to 5.1 Mb, smaller than those of E. coli strains. Intraspecies genomic comparisons identified five phylogroups of E. albertii. Intragenus genomic comparison revealed that the possible core genome of E. albertii comprises 3,250 genes, whereas that of the genus Escherichia comprises 1,345 genes. Our analysis further revealed several unique or notable genetic features of E. albertii, including those responsible for known biochemical features and virulence factors and a possibly active second T3SS known as ETT2 (E. coli T3SS 2) that is inactivated in E. coli. Although this organism has been observed to be nonmotile in vitro, genes for flagellar biosynthesis are fully conserved; chemotaxis-related genes have been selectively deleted. Based on these results, we have developed a nested polymerase chain reaction system to directly detect E. albertii. Our data define the genomic features of E. albertii and provide a valuable basis for future studies of this important emerging enteropathogen.
Congestion Control with Adjustable Fairness in Opportunistic Networks

Dimitrios-Georgios Akestoridis. Bachelor of Science, Department of Computer Science and Engineering, University of Ioannina, October 2013. Congestion Control with Adjustable Fairness in Opportunistic Networks. Advisor: Assistant Professor Evangelos Papapetrou. In Opportunistic Networks, where the topology is stochastic and unknown, the nodes have to seize the opportunities of forwarding data to other nodes, in order to deliver them to their destinations successfully. For this reason, the routing protocols that have been proposed for these networks use various techniques to determine the suitable data carriers. However, it has been observed that the performance of these networks depends heavily on a small subset of important nodes, which results in an unbalanced traffic load distribution. These nodes are usually under congestion, which leads to packet drops due to the storage constraints. In this thesis we study the problem of congestion control in Opportunistic Networks and we propose a new congestion control mechanism with adjustable fairness, which provides a trade-off between efficiency and overhead. The proposed mechanism achieves high delivery ratio and low delay, without excessive use of the most important nodes, by taking into account the destination of each message and the saturation state of each node. Finally, we show that we can significantly improve the performance of the network with a slight distortion of fairness.
A PARALLEL IMPLEMENTATION OF A PARSIMONY-BASED METHOD FOR PHYLOGENETIC INFERENCE by

iv ACKNOWLEDGMENTS I wish to thank Dr. Jugal Kalita for his guidance throughout the course of the project. I would also like to thank Dr. Charles Shub and Dr. Robert Melamede for their valuable input during the presentation of my proposal for the project. Several people helped me in making parallel programming hardware and software accessible for running my tests. I would like to thank Dave Lohmann of the Computer Science Department for help with my initial testing and debugging sessions on the June cluster, and later on SBC. I would like to thank Dr. James Mattoon of the Biology Department for giving me access to the SBC cluster in the Biology Department.
Data Science, Predictive Analytics, and Big Data: A Revolution that Will Transform Supply Chain Design and Management

We illuminate the myriad of opportunities for research where supply chain management intersects with data science, predictive analytics, and big data, collectively referred to as DPB. We show that these terms are not only becoming popular but are also relevant to supply chain research and education. Data science requires both domain knowledge and a broad set of quantitative skills, but there is a dearth of literature on the topic and many questions. We call for research on skills that are needed by SCM data scientists and discuss how such skills and domain knowledge affect the effectiveness of a SCM data scientist. Such knowledge is crucial to developing future supply chain leaders. We propose definitions of data science and predictive analytics as applied to supply chain management. We examine possible applications of DPB in practice and provide examples of research questions from these applications, as well as examples of research questions employing DPB that stem from management theories. Finally, we propose specific steps interested researchers can take to respond to our call for research on the intersection of supply chain management and DPB.
Leveraging Social Network APIs for Enhancing Smartphone Apps: An Example of VoIP App

With the rapid advancement of communication technology and mobile devices, many software companies and individual developers have started to develop a variety of mobile applications. However, since the resources individual developers can get are far less than a software company, it is important for individual developers to utilize the free API resources available on the Internet to harvest the benefit of the cloud computing. This research explores the benefits that individual developers can acquire from free APIs and service-oriented computing (SOC) in building desired smartphone applications (apps). Using a VoIP application (app) as an example, the design and implementation of a smartphone app using the proposed approach is described in this article. In addition, by comparing this VoIP app with some other smartphone apps which also provide VoIP services, the advantages and potential value of our approach to integrating social network APIs and SOC concept will be discussed.
Full orientation invariance and improved feature selectivity of 3D SIFT with application to medical image analysis

This paper presents a comprehensive extension of the Scale Invariant Feature Transform (SIFT), originally introduced in 2D, to volumetric images. While tackling the significant computational efforts required by such multiscale processing of large data volumes, our implementation addresses two important mathematical issues related to the 2D-to-3D extension. It includes efficient steps to filter out extracted point candidates that have low contrast or are poorly localized along edges or ridges. In addition, it achieves, for the first time, full 3D orientation invariance of the descriptors, which is essential for 3D feature matching. An application of this technique is demonstrated to the feature-based automated registration and segmentation of clinical datasets in the context of radiation therapy.
A Global Scheduling Algorithm Based on Dynamic Critical Path

Task scheduling algorithm, with which the tasks with precedence constraints are assigned to the proper processor, is vital for obtaining high performance in multiprocessors system. In this paper, we firstly analyzed three typical table-based algorithms, i.e. MCP algorithm, ETF algorithm and BDCP algorithm. It is showed these algorithms cannot guarantee that the critical tasks have the priority to schedule firstly. To solve this problem, we proposed a new global scheduling algorithm that based on dynamic critical path (GDCP). In GDCP algorithm, tasks on the critical path have the priority to be scheduled firstly in each scheduling step, and a global search strategy will be applied to select a suitable processor to execute each task, thus reduces the schedule length. The result of experiments shows that the proposed algorithm is better than other algorithms.
Scalable annotation mechanisms for digital content aggregation and context-aware authoring

This paper discusses the role of context information in building the next generation of human-centered information systems, and classifies the various aspects of contextualization with a special emphasis on the production and consumption of digital content. The real-time annotation of resources is a crucial element when moving from content aggregators (which process third-party digital content) to context-aware visual authoring environments (which allow users to create and edit their own documents). We present a publicly available prototype of such an environment, which required a major redesign of an existing Web intelligence and media monitoring framework to provide real-time data services and synchronize the text editor with the frontend's visual components. The paper concludes with a summary of achieved results and an outlook on possible future research avenues including multi-user support and the visualization of document evolution.
A Hierarchical Bayesian Approach for Residential Property Valuation:Application to Hong Kong Housing Market

We have developed a statistical method for the valuation of residential properties using a hierarchical Bayesian approach, which takes into consideration the unique structure of the Hong Kong property market. Our model is calibrated on a dataset that covers all residential real estate transactions in ten major Hong Kong residential complexes from February 2008 to February 2009. Although parsimonious, our model outperforms other valuation methods that are based on average price-per-square-feet or expert assessments. By providing our model-based valuations online without charge, we hope to improve transparency in the Hong Kong housing market, thus enabling consumers to make better investment decisions.
Continuous Time and Consistent Histories

We discuss the use of histories labelled by a continuous time in the approach to consistent-histories quantum theory in which propositions about the history of the system are represented by projection operators on a Hilbert space. This extends earlier work by two of us [C. J. Isham and N. Linden, J. Math. Phys. 36, 5392–5408 (1995)] where we showed how a continuous time parameter leads to a history algebra that is isomorphic to the canonical algebra of a quantum field theory. We describe how the appropriate representation of the history algebra may be chosen by requiring the existence of projection operators that represent propositions about the time average of the energy. We also show that the history description of quantum mechanics contains an operator corresponding to velocity that is quite distinct from the momentum operator. Finally, the discussion is extended to give a preliminary account of quantum field theory in this approach to the consistent histories formalism.
Performance analysis of detection schemes in MIMO spatially correlated channels

The promise of substantial capacity increase by exploiting spatial diversity has made MIMO systems a new frontier in wireless communication research, but this performance gain is theoretical and does not take real world impairments like channel correlation into account. A lot of work has been done on MIMO detectors. However performance analysis in spatially correlated channels in real world scenarios is lacking. In this paper, we investigate the effects of channel correlation on the performance of existing MIMO detectors like linear detectors (ZF), non-linear detectors (V-BLAST) and exact decoders (Sphere Decoders).
Dynamic Route Guidance Method Based on Particle Swarm Optimization Algorithm

Dynamic route guidance is an important part of the intelligent transportation system(ITS), first of all the characteristic of dynamic route guidance was analyzed. For the requirement of real-time guidance, a kind of natural algorithm - Particle Swarm Optimization (PSO) algorithm was introduced into dynamic route guidance. Firstly the basic principle and characteristic of Particle Swarm Optimization algorithm was analyzed, then based on this the application method of Particle Swarm Optimization algorithm in path searching of dynamic route guidance was proposed. Finally a simulation example showed that Particle Swarm Optimization algorithm has a very fast speed, high efficiency and an adequate accuracy when used in search of the shortest path of the road network and so can be used in dynamic route guidance.
A Method of Traffic Flow Forecast and Management

As an important aspect in transportation research, the forecast of traffic state serves as the basis for reasonable traffic control and management. Original prediction models in actual appliance donpsilat consider influencing factors comprehensively when dealing with complex and changeable traffic state. Based on the observation of daily similarity of expressway traffic flow series, the paper recognizes weather and date attribute as classification vectors and designs a new time series clustering algorithm through calculating representatives in all kinds of clusters and building correlative relations between observing time series and representatives. In the end traffic flow under different time scales on both weekday and weekend are forecasted. The experiment result shows that the time series clustering algorithm and forecast model make good use of historical data and the accuracy is quite satisfied under 30-minute time scale with the mean-absolute-relative-error 3.34 percent.
Refined Topological Vertex and Instanton Counting

It has been proposed recently that topological A-model string amplitudes for toric Calabi-Yau 3-folds in non self-dual graviphoton background can be caluculated by a diagrammatic method that is called the ``refined topological vertex''. We compute the extended A-model amplitudes for SU(N)-geometries using the proposed vertex. If the refined topological vertex is valid, these computations should give rise to the Nekrasov's partition functions of = 2 SU(N) gauge theories via the geometric engineering. In this article, we verify the proposal by confirming the equivalence between the refined A-model amplitude and the K-theoretic version of the Nekrasov's partition function by explicit computation.
Analysis of asymmetric hidden node problem in IEEE 802.11ax heterogeneous WLANs

In this paper, we investigate issues of fairness and spatial reuse in heterogeneous wireless local area networks (WLANs) based on IEEE 802.11ax. According to discussions in the evolving IEEE 802.11ax standardization, the value of carrier sensing threshold (CSTH) needs to be increased, in order to improve spectral efficiency of WLANs by means of spatial reuse. We reveal a serious problem of unfairness, referred to as asymmetric hidden node problem, arising when legacy devices that have smaller CSTH coexist and compete for channel access with new devices that have larger CSTH; legacy devices hardly access the wireless channel and the channel is mostly occupied by new devices. The reasons of this problem are analyzed from two viewpoints of asymmetry of carrier sensing and unintended operation of binary exponential backoff. We also show that this problem is not effectively resolved by the ready-to-send/clear-to-send (RTS/CTS) mechanism, which is a well-known solution to the hidden node problem. Via simulation study, we validate this problem and evaluate the trade-off between spatial reuse and fairness with respect to the value of CSTH.
Conduction mechanisms in biphenyl dithiol single-molecule junctions

Based on density-functional theory calculations, we report a detailed study of the single-molecule charge-transport properties for a series of recently synthesized biphenyl-dithiol molecules. The torsion angle ϕ between the two phenyl rings, and hence the degree of π conjugation, is controlled by alkyl chains and methyl side groups. We consider three different coordination geometries, namely, top-top, bridge-bridge, and hollow-hollow, with the terminal sulfur atoms bound to one, two, and three gold surface atoms, respectively. Our calculations show that different coordination geometries give rise to conductances that vary by one order of magnitude for the same molecule. Irrespective of the coordination geometries, the charge transport calculations predict a cos2ϕ dependence of the conductance, which is confirmed by our experimental measurements. We demonstrate that the calculated transmission through biphenyl dithiols is typically dominated by a single transmission eigenchannel formed from π electrons. For perpendicular orientation of the rings a residual conductance arises from σ-π couplings. But only for a single molecule with a completely broken conjugation we find a nearly perfect degeneracy of the σ-π eigenchannels for the hollow-hollow-type contact in our theory.
60-GHz Millimeter-Wave Identification Reader on 90-nm CMOS and LTCC

A reader module at 60 GHz for high data-rate short-range backscattering-based communications is presented. The reader consists of a CMOS-based oscillator, amplifiers, and a mixer on a low-temperature co-fired ceramic (LTCC) substrate. The filter, power splitter, and antennas are directly patterned on the LTCC. All millimeter-wave components are contained within the module and the only interfaces to the module are the IF and bias lines. Transmit power of the module is +11.6-dBm effective isotropic radiated power with an IF bandwidth of 400 MHz. The LTCC module measures 13×24 mm2 and has a dc power consumption of 130 mW. Reception of a 20-MHz square wave from a tag 5 cm apart from the reader is demonstrated; the suggested millimeter-wave identification concept enables a 102- 103-fold data-rate increase in comparison to the present near-field communication technique, with similar size, range, and power consumption of the reader.
A Strategy for Low Power FSM-Design by Reducing Switching Activity

Power dissipation is growing to be one of the most crucial parameter in the design of VLSI systems. Focusing the low power design of synchronous finite state machines (FSM) our paper presents a novel approach to reduce switching events by a profiling-based strategy. The idea of this strategy is to combine the deactivation of special self-loops with an appropriate state assignment. Analyzing the given sequence of input pattern and being sensitive to the FSM structure, our approach is capable to utilize environment conditions in a application-oriented manner.
Handling uncertainties of models inputs in inverse problem: the U-discrete PSO approach

The inverse problem of unconstrained physical systems consists in finding the set of continuous inputs for its model that minimize fitness function measuring the distance between a target and the result of the model. However either the characterization of the sensitivity of model to each input or a preliminary knowledge on the uncertainties on parameters can reveal different required precision on each input. Therefore a blind search of the best set of parameters could be unnecessarily costing in terms of computational effort on the determination of non significative digits. To overcome this problem a solution consists in searching the best parameter sets within a predefined discrete space of search that is designed from the significative number of digits. The strategy consists in transforming the continuous problem into a discrete one that falls within combinatorial optimization eventually before ending the search of the best continuous inputs if required. The performance of continuous and discrete PSO are compared by their application to the inverse problem of the purple color of the Lycurgus cup. The structure of this ancient glass is recovered from photograph by using a direct model of color generation. The discussion of results is also an opportunity to convince that the heuristic approaches provide solutions to the inverse problem unlike nested loops, from a pedagogical point of view.
Switched current filter design with the use of integrators composed of equal size transistors

This paper presents an approach to the design of low power SI filters. The filters use a new type of integrator which is built with equal size transistors. The design parameter is the channel length. Thanks to the proposed design, power consumption falls below 1mW, and the integrator is less sensitive with respect to variations of production parameters. The design method is illustrated by an example of a third-order elliptic filter. The layout in 0.35/spl mu/m CMOS technology of the filter is also presented. Simulation results show that the presented approach can be used to realize low-power high-precision SI filters.