Miracle-dz/UniFAR-FTUs huggingface dataset:
Bound states with complex frequencies near the continuum on lossy periodic structures

On a lossless periodic dielectric structure sandwiched between two homogeneous media, bound states in the continuum (BICs) with real frequencies and real Bloch wavevectors may exist, and they decay exponentially in the surrounding homogeneous media and do not couple with propagating plane waves with the same frequencies and wavevectors. The BICs are of significant current interest, because they give rise to high-$Q$ resonances when the structure or the Bloch wavevector is slightly perturbed. In this paper, the effect of a small material loss on the BICs is analyzed by a perturbation method and illustrated by numerical results. It is shown that bound states with complex frequencies near the continuum appear, but they behave differently depending on whether the BIC is symmetry-protected or not. The Bloch wavevector of a bound state with a complex frequency can be real if the original BIC is symmetry-protected, and it is usually complex if the original BIC is not symmetry-protected. Our study improves the theoretical understanding on BICs and provides useful insight for their practical applications.
Transfer operator approach to ray-tracing in circular domains

The computation of wave-energy distributions in the mid-to-high frequency regime can be reduced to ray-tracing calculations. Solving the ray-tracing problem in terms of an operator equation for the energy density leads to an inhomogeneous equation which involves a Perron–Frobenius operator defined on a suitable Sobolev space. Even for fairly simple geometries, let alone realistic scenarios such as typical boundary value problems in room acoustics or for mechanical vibrations, numerical approximations are necessary. Here we study the convergence of approximation schemes by rigorous methods. For circular billiards we prove that convergence of finite-rank approximations using a Fourier basis follows a power law where the power depends on the smoothness of the source distribution driving the system. The relevance of our studies for more general geometries is illustrated by numerical examples.
J ul 2 01 5 Quantum Hall effect with small numbers of vortices in Bose-Einstein condensates

Tim Byrnes 2, 3 and Jonathan P. Dowling New York University, 1555 Century Ave, Pudong, Shanghai 200122, China NYU-ECNU Institute of Physics at NYU Shanghai, 3663 Zhongshan Road North, Shanghai 200062, China National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan Hearne Institute for Theoretical Physics, Department of Physics & Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803-4001, USA (Dated: September 30, 2018)
Managing DSRC and WAVE Standards Operations in a V2V Scenario

The Dedicated Short-Range Communications (DSRC) standards suite is based on multiple cooperating standards mainly developed by the IEEE. In particular, we focus this paper on the core design aspects of DSRC which is called Wireless Access in Vehicular Environment (WAVE). WAVE is highlighted in IEEE 1609.1/. 2/. 3/. 4. The DSRC and WAVE standards have been the center of major attention in both research and industrial communities. In 2008, WAVE standard was the third best seller standards in the history of the IEEE. This attention reflects the potential of WAVE to facilitate much of the vehicular safety applications. In this paper we present a fairly detailed tutorial of the WAVE standards. We extend the paper by describing some of the lessons learned from particular design approaches. We direct the reader to the landmark research papers in relevant topics. We alert the reader about major open research issues that might lead to future contribution to the WAVE design.
A Survey of Practices and Problems Associated with Incomplete User Requirements Documents

Incompleteness is one of the inherent problems of system requirements represented through informal notations (natural language. diagrams. pictures . etc) and captured in the User Requirement Document (URD). These early requirements need further analysis and refinement to produce a structured document that can then be formally specified. A survey was conducted to investigate the problems encountered and the common practices applied during requirement analysis. The main purpose of the qualitative survey was to use practitioners' responses to develop an approach to the problem of incompleteness within the context of existing literature. This paper presents the main findings of the interviews conducted witl: eight individuals employed by six different companies ill Australia and in the U.S.A. during a six-month period.
ENZYMATICALLY AND PHYSICALLY INDUCED INHERITANCE CHANGES IN BACILLUS SUBTILIS

When a culture of Bacillus subtilis strain 168 is treated with a solution of crystalline lysozyme, the bacteria pass through an osmotically sensitive bacillary phase to the protoplast stage. All of the protoplasts can be recovered as L-colony-forming elements on complex or chemically defined osmotically stabilized agar media. Protoplasts or L-bodies can be propagated in the L-state indefinitely or can be mass-reverted to the bacillary state by altering medium ingredients. In particular, several D-amin acids and soft agar inhibit reversion to the bacillary state, while hard agar and 30 per cent gelatin media induce reversion. Reversion in 30 per cent gelatin is often 100 per cent efficient and begins within five hours after plating. Penicillin-induced L-forms of B. subtilis differ from the bacillary form in their resistance to penicillin and seem to be identical to the lysozyme-induced L-forms. Their induction and resistance behavior constitutes an instance of Lamarckian inheritance. The conversion of bacteria to the L-state is attributed to the loss of a primer for cell-wall formation and cell division, while reversion is thought to be due to reinitiation of this primer. The primer is probably associated with the cell membrane. Its possible nature and parallels between the present inheritance system and previously described systems are discussed.
Extraction of glycerol from biodiesel into a eutectic based ionic liquid

A Lewis basic mixture of quaternary ammonium salts with glycerol has been used to extract excess glycerol from biodiesel formed from the reaction of triglycerides with ethanol in the presence of KOH. The effect of the cation on the partition coefficient of glycerol was determined, together with the time taken for the systems to reach equilibrium. Protocols were also investigated for the separation of glycerol from the quaternary ammonium salt mixtures.
Coordination of AtHKT 1 ; 1 and AtSOS 1 Facilitates Na + and K + Homeostasis in Arabidopsis thaliana under Salt Stress

Reducing Na accumulation and maintaining K stability in plant is one of the key strategies for improving salt tolerance. AtHKT1;1 and AtSOS1 are not only the salt tolerance determinants themselves, but also mediate K uptake and transport indirectly. To assess the contribution of AtHKT1;1 and AtSOS1 to Na homeostasis and K nutrition in plant, net Na and K uptake rate, Na and K distributions in Arabidopsis thaliana wild type (WT), hkt1;1 mutant (athkt1;1) and sos1 mutant (atsos1) were investigated. Results showed that under 2.5 mM K plus 25 or 100 mM NaCl, athkt1;1 shoot concurrently accumulated more Na and less K than did WT shoot, suggesting that AtHKT1;1 was critical for controlling Na and K distribution in plant; while atsos1 root accumulated more Na and absorbed lower K than did WT root, implying that AtSOS1 was determiner of Na excretion and K acquisition. Under 0.01 mM K, athkt1;1 absorbed lower Na than did WT with 100 mM NaCl, suggesting that AtHKT1;1 is involved in Na uptake in roots; while atsos1 shoot accumulated less Na than did WT shoot no matter with 25 or 100 mM NaCl, implying that AtSOS1 played a key role in controlling long-distance Na transport from root to shoot. We present a model in which coordination of AtHKT1;1 and AtSOS1 facilitates Na and K homeostasis in A. thaliana under salt stress: under the normal K, the major function of AtHKT1;1 is Na unloading and AtSOS1 is mainly involved in Na exclusion, whereas under the low K, AtHKT1;1 may play a dominant role in Na uptake and AtSOS1 may be mainly involved in Na loading into the xylem.
Object Detection in Video Based on Transfer Learning Using Convolution Neural Network

Object Detection has been an active area of research and development since the past few years and due to its diverse applications it continues to be a challenging research topic. It is indeed an evident fact that convolution neural network have shown a remarkable progress for various vision related tasks such as image classification object detection etc. In this thesis, we introduce a complete framework of object detection in a real time video using the concept of transfer learning. In this thesis the model used to train the system is a Deep Neural Net. The whole concept of how deep neural net learns to recognize the pattern in the data is termed as Deep Learning. It originates from Machine Learning which is basically a sub-branch of Artificial Intelligence (AI). Deep Learning is mainly based on Artificial Neural Network with a concept to mimic the human brain i.e. Artificial Neural Networks are computational models which work similar to the functioning of human brain. Here, we use convolution neural networks to train our system on ImageNet CIFAR-10 dataset and use this trained system to detect objects in YTO dataset. We have applied various image processing techniques so as to achieve a better accuracy in comparison to the state-of-the-art methods for object detection. Basically, in this thesis, the technique that we have incorporated is transfer learning. Transfer
Pengaruh Pembelajaran Matematika Diskrit dengan Blended Learning terhadap Hasil Belajar

Matematika Diskrit adalah mata kuliah wajib yang ditempuh oleh mahasiswa Teknik Informatika STIKI pada semester pertama. Namun, pembelajaran Matematika Diskrit yang sudah pernah dilakukan, kurang maksimal dalam penggunaan LMS. Penggunaan model pembelajaran yang tepat pada mata kuliah Matematika Diskrit dapat meningkatkan hasil belajar mahasiswa. Selain itu, selalu ada mahasiswa yang hadir tidak konsisten di setiap pertemuan. Akibatnya hasil belajar mahasiswa tidak baik. Artinya bahwa nilai akhir mahasiswa banyak yang mendapatkan nilai C atau kurang dari C. Oleh karena itu, dibutuhkan model sistem pembelajaran blended pada mata kuliah Matematika Diskrit yang dapat meningkatkan hasil belajar mahasiswa. Tujuan dari penelitian ini adalah untuk melihat pengaruh pembelajaran blended terhadap hasil belajar mahasiswa. Penelitian ini adalah penelitian eksperimen One-Group Pre-Test Post-Test Design. Setelah dilakukan uji coba terhadap model sistem pembelajaran blended Matematika Diskrit, terjadi perbedaan terhadap hasil belajar setelah dilakukan pembelajaran blended. Dengan kata lain, pembelajaran blended berpengaruh signifikan terhadap hasil belajar pada tingkat kepercayaan 95%. Model sistem pembelajaran blended matematika diskrit dikatakan valid dengan nilai 3,58. Model sistem pembelajaran blended matematika diskrit dikatakan praktis dengan nilai 3. Model sistem pembelajaran blended matematika diskrit dikatakan hampir efektif bagi mahasiswa dengan nilai rata-rata 2.9 dari seluruh indikator.
Evaluation of Machine Learning Models for Patient Data De-identification in Clinical Records

xi List of Abbreviations Used . xii Acknowledgements . xiii Chapter
Reducing GPU Address Translation Overhead with Virtual Caching

Heterogeneous computing on tightly-integrated CPU-GPU systems is ubiquitous, and to increase programmability, many of these systems support virtual address accesses from GPU hardware. However, there is no free lunch. Supporting virtual memory entails address translations on every memory access, which greatly impacts performance (about 77% performance degradation on average). To mitigate this overhead, we propose a software-transparent, practical GPU virtual cache hierarchy. We show that a virtual cache hierarchy is an effective GPU address translation bandwidth filter. We make several empirical observations advocating for GPU virtual caches: (1) mirroring CPUstyle memory management unit in GPUs is not effective, because GPU workloads show very high Translation Lookaside Buffer (TLB) miss ratio and high miss bandwidth. (2) many requests that miss in TLBs find corresponding valid data in the GPU cache hierarchy. (3) The GPU’s accelerator nature simplifies implementing a deep virtual cache hierarchy (i.e., fewer virtual address synonyms and homonyms). We evaluate both L1-only virtual cache designs and an entire virtual cache hierarchy (private L1s and a shared L2 caches). We find that virtual caching on GPUs considerably improves performance. Our experimental evaluation shows that the proposed entire GPU virtual cache design significantly reduces the overheads of virtual address translation providing an average speedup of 1.77× over a baseline physically cached system. L1-only virtual cache designs show modest performance benefits (1.35× speedup). By using a whole GPU virtual cache hierarchy, we can obtain additional performance benefits.
Transformation and Visualization of BPMN Models to Petri Nets

The Business Process Modeling Notation (BPMN) is a language for capturing business processes. It is able to model the complex concepts of systems such as: choice, parallel, and synchronization. However it suffers from the lack of an unambiguous definition, so we may produces models with semantic errors. On the other hand, Petri nets are a formal tool with solid mathematical principles [4]. Moreover, it offers a number of analytical techniques. So Petri nets and BPMN have complementary abilities: BPMN can handle the modeling and Petri nets can handle the analysis. In this paper, we propose an approach for transforming BPMN models to Petri nets models, then assign coordinates of Petri nets elements and control the path of every arc. Finally, we get a valid and neat Petri net model which is both convenient and practical for human analysts and other Petri nets analysis techniques.
Honor among thieves : a zooarchaeological study of Neandertal ecology

This study uses ecological niche theory to analyze and interpret several Middle Palaeolithic archaeological and palaeontological sites in southern Europe. The hunting, scavenging and foraging behaviour of Neandertals is compared and contrasted with the subsistence behaviour of other large predators living in the region at the time - lions, hyenas and wolves, for example - and with how Neandertal subsistence behaviour related to the behaviour of the anatomically modern humans who subsequently came to dominate the area in the Upper Paleolithic. Her conclusion, broadly stated, is that Neandertals entered the Middle Palaeolithic in direct and successful competition with lions, hyenas and wolves, but ended the period in unsuccessful struggle for the ecological niche that modern humans came to occupy with more advanced technology and slightly more sophisticated ambush hunting strategies and techniques.
Stereo Vision Based Balancing System Results

Keeping a system in stable state is one of the important issues of control theory. The main goal of our basic research is stability of unmanned aerial vehicle (quadrotor) . This type of system uses a variety of sensors to stabilize. In control theory and automatic control system to stabilize any system it is need to apply feedback control based on information from sensors. Our aim is to provide balance based on the 3D spatial information in real time. We used PID control method for stabilization of a seesaw balancing system and the article presents our experimental results. This paper presents the possibility of balancing of seesaw system based on feedback information from stereo vision system only.
Interference Management in D2D-Enabled Heterogeneous Cellular Networks Using Matching Theory

To support the increasing data traffic demand in wireless communications networks, a multi-tier architecture that consists of multiple small cells is adopted in traditional (macro) cellular networks. Nevertheless, due to the expansion of various wireless devices and services, there is still a need to increase the network capacity in new generation networks such as 5G. Hence, the integration of Device-to-Device (D2D) communication as a promising technology with heterogeneous networks has been proposed. This integration not only increases network capacity but also improves spectral efficiency and alleviates the traffic load of base stations. However, the co/cross-tier interferences between D2D and cellular communications caused by resource sharing is a significant challenge. In this paper, we propose a distributed resource allocation algorithm based on matching theory to minimize these interferences and optimize the network performance. It is shown in this paper that the proposed algorithm converges to a stable matching and terminates after finite iterations. Simulation results show that the proposed algorithm is able to achieve more than 90 percent of the optimum network performance with much lower overhead and complexity.
An Open and Data-driven Taxonomy of Skills Extracted from Online Job Adverts

In this work we offer an open and data-driven skills taxonomy, which is independent of ESCO and O*NET, two popular available taxonomies that are expert-derived. Since the taxonomy is created in an algorithmic way without expert elicitation, it can be quickly updated to reflect changes in labour demand and provide timely insights to support labour market decision-making. Our proposed taxonomy also captures links between skills, aggregated job titles, and the salaries mentioned in the millions of UK job adverts used in this analysis. To generate the taxonomy, we employ machine learning methods, such as word embeddings, network community detection algorithms and consensus clustering. We model skills as a graph with individual skills as vertices and their co-occurrences in job adverts as edges. The strength of the relationships between the skills is measured using both the frequency of actual co-occurrences of skills in the same advert as well as their shared context, based on a trained word embeddings model. Once skills are represented as a network, we hierarchically group them into clusters. To ensure the stability of the resulting clusters, we introduce bootstrapping and consensus clustering stages into the methodology. While we share initial results and describe the skill clusters, the main purpose of this paper is to outline the methodology for building the taxonomy.
Design and Simulation of an Embedded Controller for the iRobot Create robot by Integrating ROS in Gazebo

In this thesis, we design and implement a controller for the iRobot Create robot by integrating Robot Operating System (ROS) in the robot simulator Gazebo. The thesis consists of two main parts. The first part describes the implementation of the robot and the controller in ROS and Gazebo. By choosing the proper Gazebo sensors and adding ROS plugins to them, we show how we can accurately simulate the robot and control it using ROS. In the second part, we present an algorithm that is used by our controller to make iRobot Create find a hill in an unknown environment, climb the hill, and drive back down. We conclude that the algorithm does what it is supposed to do and we find out which configuration of the algorithm makes the robot find the hill as fast and efficient as possible. Afterwards, we present an addition to the algorithm to try and improve its performance. Although the controller works, there is much room for improvement and further development which we discuss as well.
Effects of Switchable DOF for Mid-Air Manipulation in Immersive Virtual Environments

ABSTRACT In the context of mid-air manipulation, this paper presents the effects of allowing the user to dynamically switch between 1DOF, 2DOF, and 3DOF operations. Such “manipulation with switchable DOF” has been widely used in commercial graphics packages and is increasingly being adopted for virtual reality editing, where the 3D scene is constructed through mid-air interaction in immersive virtual environments. However, its effectiveness and advantages/disadvantages have not been investigated. This paper compares “manipulation with switchable DOF” with “manipulations with DOF separation,” which allows only 1DOF operations, and “manipulation without DOF separation,” which provides 3DOF operations. Using translation, rotation, and scaling, three methods were evaluated in terms of completion time and precision. The experiment results showed that “manipulation with switchable DOF” outperformed “manipulation with DOF separation” in terms of completion time whereas three methods were comparable in terms of precision. “Manipulation with switchable DOF” was further analyzed, and the results showed that the more 3DOF operations led to the shorter completion time and the more 1DOF operations led to the higher precision.
Exploiting Background Knowledge in Compact Answer Generation for Why-Questions

This paper proposes a novel method for generating compact answers to open-domain why-questions, such as the following answer, “Because deep learning technologies were introduced,” to the question, “Why did Google’s machine translation service improve so drastically? ” Although many works have dealt with why-question answering, most have focused on retrieving as answers relatively long text passages that consist of several sentences. Because of their length, such passages are not appropriate to be read aloud by spoken dialog systems and smart speakers; hence, we need to create a method that generates compact answers. We developed a novel neural summarizer for this compact answer generation task. It combines a recurrent neural network-based encoderdecoder model with stacked convolutional neural networks and was designed to effectively exploit background knowledge, in this case a set of causal relations (e.g., “[Microsoft’s machine translation has made great progress over the last few years]effect since [it started to use deep learning.]cause”) that was extracted from a large web data archive (4 billion web pages). Our experimental results show that our method achieved significantly better ROUGE F-scores than existing encoder-decoder models and their variations that were augmented with query-attention and memory networks, which are used to exploit the background knowledge.