Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconstruction of a 3-D surface from its normal vectors

A well-known problem in pattern recognition is to deteromine the shape of a 3-D object from its 2-D image. This paper de~cribes a new, general algorithm to reconstruct a surface from its normal vectors relative to an arbitrary reference point. The depth values of the surface are calculated recursively, having smoothed the defect due to path dependency homogeneously. The theoretical background is worked out to prove the correctness of the program. The time complexity of the algorithm is given. Two applications of the general method are discussed with a detailed error analysis. The comparison of experimental results of this new approach and a previous one is presented. Theoretical analysis and experiments show that our method is both powerful and simple to implement. Acknowledgement I would like to thank Kees van Overveld for the valuable suggestions and Agoston Eiben for his useful comments on a draft version of this paper. Photos made by Huub van de Wetering and implementation of the algorithm by Servaas van der Ploeg were much appreciated.
Bold Hearts Team Description RoboCup 2017 Kid Size

In this paper we describe the structure and the software of the RoboCup Humanoid Kid Size division team Bold Hearts. We discuss the construction and the aspects of our software architecture, enlightening our solutions to important problems such as the action selection, vision, stability, and sensorimotor modeling. Finally, we provide an overview of the relevant experience and achievements of our team.
Bold Hearts Team Description RoboCup 2014 Kid Size

In this paper we describe the RoboCup Humanoid Kid Size division of team Bold Hearts, the RoboCup team of the University of Hertfordshire, in Hatfield UK. We discuss construction and aspects of our software architecture, as well as some of our solutions to important problems such as vision, localisation, action selection, and communication. Finally, we provide an overview of the relevant experience and achievements of our team.
Bold Hearts Team Description RoboCup 2015 Kid Size

In this paper we describe the RoboCup Humanoid Kid Size division of team Bold Hearts, the RoboCup team of the University of Hertfordshire, in Hatfield UK. We discuss construction and aspects of our software architecture, as well as some of our solutions to important problems such as vision, localisation, action selection, and communication. Finally, we provide an overview of the relevant experience and achievements of our team.
UltraSPARC-III: designing third-generation 64-bit performance

The UltraSPARC-III is the third generation of Sun Microsystems' most powerful microprocessors, which are at the heart of Sun's computer systems. These systems, ranging from desktop workstations to large, mission critical servers, require the highest performance that the UltraSPARC line has to offer. The newest design permits vendors the scalability to build systems consisting of 1,000+ UltraSPARC processors. Furthermore, the design ensures compatibility with all existing SPARC applications and the Solaris operating system. The UltraSPARC-III design extends Sun's SPARC Version 9 architecture, a 64-bit extension to the original 32-bit SPARC architecture that traces its roots to the Berkeley RISC-I processor. The UltraSPARC-III design target is a 600-MHz, 70-watt, 13-mm die to be built in 0.25-micron CMOS with six metal layers for signals, clocks, and power.
Simulating quantum circuits by adiabatic computation: improved spectral gap estimates via eigenstate ansatz

Adiabatic quantum computing is a framework for quantum computing that is superficially very different to the standard circuit model. However, it can be shown that the two models are computationally equivalent. The key to the proof is a mapping of a quantum circuit to an an adiabatic evolution, and then showing that the minimum spectral gap of the adiabatic Hamiltonian is at least inverse polynomial in the number of computational steps L. In this paper we provide a simplified proof that the gap is inverse polynomial, showing that for L 1 the minimum gap is bounded by mins ∆ & π/[8(L+ 1)], an improvement over previous estimates. Our derivation is reminiscent of the Bethe ansatz, and suggests that it may be possible to use those well-developed methods to find bounds for spectral gaps of Hamiltonians in other scenarios.
Automatic Reliability Testing For Cluster Management Controllers

Modern cluster managers like Borg, Omega and Kubernetes rely on the state-reconciliation principle to be highly resilient and extensible. In these systems, all cluster-management logic is embedded in a loosely coupled collection of microservices called controllers . Each controller independently observes the current cluster state and issues corrective actions to converge the cluster to a desired state. However, the complex distributed nature of the overall system makes it hard to build reliable and correct controllers – we ﬁnd that controllers face myriad reliability issues that lead to severe consequences like data loss, security vulnerabilities, and resource leaks. We present Sieve, the ﬁrst automatic reliability-testing tool for cluster-management controllers. Sieve drives controllers to their potentially buggy corners by systematically and extensively perturbing the controller’s view of the current cluster state in ways it is expected to tolerate. It then compares the cluster state’s evolution with and without perturbations to detect safety and liveness issues. Sieve’s design is powered by a fundamental opportunity in state-reconciliation systems – these systems are based on state-centric interfaces between the controllers and the cluster state; such interfaces are highly transparent and thereby enable fully-automated reliability testing. To date, Sieve has efﬁciently found 46 serious safety and liveness bugs (35 conﬁrmed and 22 ﬁxed) in ten popular controllers with a low false-positive rate of 3.5%.
Computer Vision and Image Understanding

Many approaches that address the analysis of crowded scenes rely on using short trajectory fragments, also known as tracklets , of moving objects to identify motion pathways. Typically, such approaches aim at defining meaningful relationships among tracklets. However, defining these relationships and incorporating them in a crowded scene analysis framework is a challenge. In this article
Using Free Software Doesn ’ t Mean It Won ’ t Cost Anything

Policy Note to Readers The Air Force has established a policy to revitalize the software aspects of systems engineering. Wondering if open source software is right for your project? This well-rounded article discusses the origins of open source, its strengths and security issues, and some ways open source can be utilized in projects. This article describes the factors that led the Army to use open source development for its next-generation simulation system, including the key processes and tools supporting its development. To break the user interface language barrier, this author proposes a single language capable of describing user interfaces for virtually any computing device, and describes how it is being applied in defense applications. Read how certifiable software reuse can be an alternative to developing software from scratch for next-generation systems, and how it provides significant return on investment and time-to-market advantages. Opening Up Open Source Without welcoming arms and attitudes, Free/Libre/Open Source Software will not become a more viable programming alternative for technical and non-technical users despite its increasing popularity. D e p a r D e p a r t m e n t s t m e n t s
Eecient Recursive Subtyping

Subtyping in the presence of recursive types for the-calculus was studied by Amadio and Cardelli in 1991 1]. In that paper they showed that the problem of deciding whether one recursive type is a subtype of another is decidable in exponential time. In this paper we give an O(n 2) algorithm. Our algorithm is based on a simpliication of the deenition of the subtype relation, which allows us to reduce the problem to the emptiness problem for a certain nite automaton with quadratically many states. It is known that equality of recursive types and the covariant BB ohm order can be decided eeciently by means of nite automata, since they are just language equality and language inclusion, respectively. Our results extend the automata-theoretic approach to handle orderings based on contravariance.
Rotation Invariant Texture Characterization and Retrieval using Steerable Wavelet-domain Hidden Markov Models

We present a new statistical model for characterizing texture images based on wavelet-domain hidden Markov models. With a small number of parameters, the new model captures both the subband marginal distributions and the dependencies across scales and orientations of the wavelet descriptors. Applying to the steerable pyramid, once it is trained for an input texture image, the model can be easily steered to characterize that texture at any other orientation. Furthermore, after a diagonalization operation, we obtain a rotation-invariant model of the texture image. We also propose a fast algorithm to approximate the Kullback-Leibler distance between two wavelet-domain hidden Markov models. We demonstrate the effectiveness of the new texture models in retrieval experiments with large image databases, where significant improvements are shown. Keywords—texture characterization, image retrieval, rotation invariance, wavelets, hidden Markov models, steerable pyramids, Kullback-Leibler distance.
Analysis of Physical Habitat Change for Target Fish Induced by Extended Floodplain

ABSTRACT Hong, I. ; Kim, J.S. ; Kim, K.H. ; Shin, H.S. , and Jeon, H.S. 2018. Analysis of physical habitat change for target fish induced by extended floodplain. In: Shim, J.-S. ; Chun, I. , and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 86–90. Coconut Creek (Florida), ISSN 0749-0208. Flood protection structures such as levees and dams are being built continuously to prevent floods and they cause many rivers to lose inundated river areas. These losses slow down the natural development process and also reduce the weighted usable area of fish. In particular, fish requiring periodic floods and floodplains are seriously affected by flow regulation and floodplain reduction. Therefore many species of fish have gone extinct due to environmental changes and instability of river ecosystems. In order to protect and maintain the habitat environment of fish in aquatic ecosystem, proper habitat of fish must be guaranteed. One of the ways to ensure the proper habitat of fish is to restore the floodplain area. Restoration of floodplain offers many benefits to several species. The River2D model was used to simulate habitat of Pseudopungtungia nigra with life stage before and after restoration on the Mankyung River. As a result of WUA calculation which is an important index when estimating the optimum flow rate, it is found that after three kinds of restoration scenarios are more effective than before restoration. In case of old bypass channel restoration, the WUA value shows that the largest restoration effect at 20.0% in spawning and 39.5% in juvenile stage. Unlike the previous result, restoration effect of backswamp restoration was largest at 85.3% in adult stage. Based on these results, it is necessary to secure proper habitat to protect and maintain the fish habitat environment, and it is also considered that the effect on the physical habitat with life stage should be fully examined.
Cloud Computing Security: An Issue of Concern

Cloud computing is an emerging technology exemplar that migrate current technological and computing concepts into utility-like solutions. Cloud computing as a ubiquitous on-demand model for accessing common resources over a network. The main idea of cloud computing is to deliver both software and hardware as services. Clouds bring out a wide range of benefits including configurable computing resources, economic savings, and service flexibility. However, security and privacy concerns are shown to be the issues of great concern to a wide adoption of clouds. The new concepts that clouds introduce, such as multi-tenancy, resource sharing and outsourcing, create new challenges to the security community. Addressing these challenges requires, in addition to the ability to grow and tune the security measures developed for traditional computing systems, proposing new security policies, models, and protocols to address the unique cloud security challenges. In this paper, we provide a comprehensive study of cloud computing security and privacy concerns. We identify cloud vulnerabilities, classify known security threats and attacks, and present the state-of-the-art practices to control the vulnerabilities, neutralize the threats, and calibrate the attacks. Additionally, we investigate and identify the limitations of the current solutions and provide insights of the future security perspectives.
Characterizing Sources of Ineffectual Computations in Deep Learning Networks

Recent hardware accelerators for inference on the ImageNet dataset with Deep Convolutional Neural Networks eliminate ineffectual work and traffic resulting from value properties, such as precision variability and sparsity at the value-or bit-level. This work analyzes to what extent these properties persist in a broader set of neural network models and data sets. We analyzed: a) image classification networks, b) other image application models (non-classification), and c) Long-Short-Term-Memory (LSTM) models for non-image applications. We show that these properties persist, albeit to a different degree, and identify opportunities for future accelerator design efforts.
A New Approach Using Unequal Power Allocation for Image Transmission with Chaotic Communication

: The advance of wireless communication in the last few decades has led to the development of multiple transmit and receive (MIMO) systems enabling proficient real-time image and video communication. The discovery of the multiple-input multiple-output (MIMO) wireless systems shows tremendous potential to relieve the bottleneck of wireless data transmission. MIMO offers an increase in traffic capacity for future cellular systems, to face the challenge of internet-intensive applications. These advantages of multiple antenna systems along with efficient transmission and coding schemes can be explored to achieve very high data rates along with improved data reliability. This paper presents a novel approach for transmitting images over a noisy channel. The proposed method employs OFDM and chaotic encoder schemes to achieve distortion less and secure image transmission over the noisy channel.
Deriving parallel numerical algorithms using data distribution algebras: Wang's algorithm

Parallel and distributed programming are much more difficult than the development of sequential algorithms because of data distribution issues and communication requirements. The paper presents a methodology that enables an abstract description of the distribution of data structures by means of overlapping covers that form data distribution algebras. Algorithms are formulated and derived by transformation in a functional environment using skeletons, i.e. higher order functions with specific parallel implementations. Communication is specified implicitly through the access to overlapping parts of covers. Such specifications enable the derivation of explicit lower level communication statements. We illustrate the concepts by a complete derivation of H.H. Wang's (1981) partition algorithm for the solution of tridiagonal systems of linear equations.
The influence of microclimate on the development of foot pad dermatitis in broilers

Footpad dermatitis and lameness are a major welfare concern in broiler chicken farming. In general, footpad lesions are linked to poor environmental conditions. Ulcers that arise from advanced lesions can negatively affect the gait of the birds, with effects on the animal welfare, including, in the worst cases, inability to reach the feed or water. In this study, the degree of footpad dermatitis and lameness was manually scored on four broiler farms across Europe, as part of an EU-wide welfare assessment programme (Welfare Quality® protocol). Assessment of animal welfare is typically based on manual scoring, which requires a lot of trained manpower/labour. Precision Livestock Farming (PLF) can combine information technologies into on-line automated tools that can be used to control, monitor and model the behavior of animals and their biological response without stressing, disturbing or handling the animals. The association between the PLF and the Welfare Quality® protocol was investigated to assess whether animal welfare could be better ensured if they were closely monitored with state of the art technology that gives rapid feedback to the farmer. Thus, the aim of this study was to find the association between environmental predisposing factors, measured continuously (such as the indoor temperature and humidity) and leg problems, scored manually during the welfare assessment procedure, in order to find an automated prediction system to detect those lesions. Even if genetics is a heavy predisposing factor for leg disorders, environmental condition could trigger the presence of lesions. Indeed, immobility on litter of poor quality might cause footpad dermatitis affecting the gait of birds. The association between automated control of the environmental conditions and the welfare assessments could be the basis for the development of models and algorithms capable to automatically detect thresholds above which lesions are mostly probable.
Security middleware infrastructure for medical imaging system integration and monitoring

With the increasing demand for electronic medical records sharing, it is a challenge for medical imaging service providers to protect the patient privacy and IT infrastructure security in an integrated environment. In this paper, we present a novel security middleware infrastructure for seamlessly and securely linking legacy medical imaging systems, diagnostic imaging web applications as well as mobile applications. In this infrastructure, software agents such as user agent and security agent have been integrated into medical imaging domains that can be trained to perform their tasks. The proposed security middleware utilizes both online security technologies such as authentication, authorization and accounting, as well as post security operations to discover system security vulnerability. By integrating with the proposed security middleware, both legacy system users and Internet users can be uniformly identified and authenticated; access to patient diagnostic images can be controlled based on patient's consent directives and other access control polices defined at a central point; relevant user access activities can be audited at a central repository; user access behavior patterns are studied by utilizing data mining techniques; the explored behavior patterns provide system administrators valuable knowledge to refine existing security policies; behavior-based access control is enforced by capturing user's dynamic behavior and determining their access rights through comparing with the discovered knowledge of common behaviors. A case study is presented based on the proposed infrastructure.
Health-e-Child: An Integrated Biomedical Platform for Grid-Based Pediatrics

There is a compelling demand for the integration and exploitation of heterogeneous biomedical information for improved clinical practice, medical research, and personalised healthcare across the EU. The Health-e-Child project aims at developing an integrated healthcare platform for European Paediatrics, providing seamless integration of traditional and emerging sources of biomedical information. The long-term goal of the project is to provide uninhibited access to universal biomedical knowledge repositories for personalised and preventive healthcare, large-scale information-based biomedical research and training, and informed policy making. The project focus will be on individualised disease prevention, screening, early diagnosis, therapy and follow-up of paediatric heart diseases, inflammatory diseases, and brain tumours. The project will build a Gridenabled European network of leading clinical centres that will share and annotate biomedical data, validate systems clinically, and diffuse clinical excellence across Europe by setting up new technologies, clinical workflows, and standards. This paper outlines the design approach being adopted in Health-e-Child to enable the delivery of an integrated biomedical information platform.
Governance and Public Service Delivery in Nigeria : The Role of Information and Communication technologies CUCEN 2017

The task of assigning papers to reviewers is crucial to the realization of a peer-to-peer review process of academic conferences. The manual process of ensuring submissions assigned to reviewers is related to their knowledge domain can be very cumbersome. Besides, poor quality reviews results from an ineffective assignment of papers. From extant literature, automated reviewer assignment systems based on distributional semantic models have been used to capture semantics with the shortcoming of limited in the bag of words models. Neural Network Language models have been used to eliminate the limitations of bag of words of models in expertise finding and product recommendation. Thus this paper proposes a framework based on neural network language models to derive suitability scores based on the semantic relatedness between a paper meant for review and a reviewer’s representation papers. The present performance of the neural network language model compared to distributional semantic models used in solving reviewer-assignment. This ensures the semantic relatedness of paper and reviewer knowledge representation in allocating a paper, which improves the overall success of the peer-to-peer review process.
Large‐Scale Forces Under Surface Gravity Waves at a Wavy Bottom: A Mechanism for the Generation of Primary Microseisms

Primary microseisms are background seismic oscillations recorded everywhere on Earth with typical frequencies 0.05 < f < 0.1 Hz. They appear to be generated by ocean waves of the same frequency f, propagating over shallow bottom topography. Previous quantitative models for the generation of primary microseisms considered wave propagation over topographic features with either large scales, equivalent to a vertical point force, or small scales matching ocean wave wavelengths, equivalent to a horizontal force. While the first requires unrealistic bottom slopes to explain measured Rayleigh wave amplitudes, the second produced Love waves and not enough Rayleigh waves. Here we show how the small scales actually produce comparable horizontal and vertical forces. For example, a realistic rough bottom over an area of 100 km2 with depths around 15 m is enough to explain the vertical ground motion observed at a seismic station located 150 km away. Ocean waves propagating over small‐scale topography is thus a plausible explanation for the observed microseisms at frequencies around 0.07 Hz.