Miracle-dz/UniFAR-FTUs huggingface dataset:
Part of Speech Tagging for Arabic Long Sentence

Part Of Speech (POS) tagging of Arabic words is a difficult and non-travail task it was studied in details for the last twenty years and its performance affects many applications and tasks in area of natural language processing (NLP). The sentence in Arabic language is very long compared with English sentence. This affect tagging process for any approach deals with complete sentence at once as in Hidden Markov Model HMM tagger. In this paper, new approach is suggested for using HMM and n-grams taggers for tagging Arabic words in a long sentence. The suggested approach is very simple and easy to implement. It is implemented on data set of 1000 documents of 526321 tokens annotated manually (containing punctuations). The results shows that the suggested approach has higher accuracy than HMM and n-gram taggers. The F-measures were 0.888, 0.925 and 0.957 for n-grams, HMM and the suggested approach respectively.
Disjunctive Aspects in Generalized Semi-infinite Programming

In this thesis the close relationship between generalized semi-infinite problems (GSIP) and disjunctive problems (DP) is considered. We start with the description of some optimization problems from timber industry and illustrate how GSIPs and DPs arise naturally in that field. Three different applications are reviewed. Next, theory and solution methods for both types of problems are examined. We describe a new possibility to model disjunctive optimization problems as generalized semi-infinite programs. Applying existing lower level reformulations for the obtained semi-infinite program we derive conjunctive nonlinear problems without any logical expressions, which can be locally solved by standard nonlinear solvers. In addition to this local solution procedure we propose a new branch-and-bound framework for global optimization of disjunctive programs. In contrast to the widely used reformulation as a mixed-integer program, we compute the lower bounds and evaluate the logical expression in one step. Thus, we reduce the size of the problem and work exclusively with continuous variables, which is computationally advantageous. In contrast to existing methods in disjunctive programming, none of our approaches expects any special formulation of the underlying logical expression. Where applicable, under slightly stronger assumptions, even the use of negations and implications is allowed. Our preliminary numerical results show that both procedures, the reformulation technique as well as the branch-and-bound algorithm, are reasonable methods to solve disjunctive optimization problems locally and globally, respectively. In the last part of this thesis we propose a new branch-and-bound algorithm for global minimization of box-constrained generalized semi-infinite programs. It treats the inherent disjunctive structure of these problems by tailored lower bounding procedures. Three different possibilities are examined. The first one relies on standard lower bounding procedures from conjunctive global optimization. The second and the third alternative are based on linearization techniques by which we derive linear disjunctive relaxations of the considered sub-problems. Solving these by either mixed-integer linear reformulations or, alternatively, by disjunctive linear programming techniques yields two additional possibilities. Our numerical results on standard test problems with these three lower bounding procedures show the merits of our approach.
Designing Energy-Efficient MPSoC with Untrustworthy 3PIP Cores

The adoption of large-scale MPSoCs and the globalization of the IC design flow give rise to two major concerns: high power density due to continuous technology scaling and security due to the untrustworthiness of the third-party intellectual property (3PIP) cores. However, little work has been undertaken to consider these two critical issues jointly during the design stage. In this paper, we propose a design methodology that minimizes the energy consumption while simultaneously protecting the MPSoC against the effects of hardware trojans. The proposed methodology consists of three main stages: 1) Task scheduling to introduce core diversity in the MPSoC in order to detect the presence of malicious modifications in the cores, or mute their effects at runtime, 2) Vendor assignment to the cores using a novel heuristic that chooses vendor-specific cores with operating speed that minimizes the total energy consumption of the MPSoC, and 3) Explore optimization opportunities for further energy savings by minimizing idle periods on the cores, which are caused by the inter-task data dependencies. Experimental results show that our solutions consume only 1/3 energy of existing solutions without increasing schedule length while satisfying the security constraints.
DEM BASED REGISTRATION OF MULTI-SENSOR AIRBORNE POINT CLOUDS EXEMPLARY SHOWN ON A RIVER SIDE IN NON URBAN AREA

Abstract. This paper presents a method to register photogrammetric point clouds generated from optical images acquired by UAV and aerial LIDAR point clouds. Normally, the registration of two airborne scans of the same scene is solved by the use of control points and the direct registration using GNSS and INS information. However, the registration of multi-sensor point clouds without control points is more complicated and challenging. For the scene of non urban areas, the registration task gets even more complicated, because it is hard to extract sufficient geometric primitives from the building structures. For our proposed method, an outdoor scene is tested providing almost no man-made objects. Therefore, it is nearly impossible to search for planar objects and use them for registration. With no geometric primitives extracted, the proposed method utilizes the structure of the 2.5D DEM created from the ground points of the point cloud. Besides, instead of using control points or key points, the method automatic detect key planes from the 2.5D DEM as correspondences. These key planes are detected on a regular grid by the use of a predefined mask. To mark a DEM grid cell as key plane the histogram of sums of the angles between the center cell is used. Afterwards, similarity values between two key planes are calculated based on the histogram differences and a RANSAC based strategy is adopted to find corresponding key planes and estimate the transformation parameters. Experiments conducted in this paper indicate that it is feasible to register multi sensor point clouds with a big difference in their ground sampling distances with respect to the used cell size of the 2.5D DEM.
Gradual evaluation in argumentation frameworks: methods, properties and applications

Gradual evaluation methods in argumentation frameworks provide semantics for assessing the gradual acceptance of arguments, differing from the qualitative semantics that have been used in argument evaluation since argumentation’s conception. These methods and their semantics are wideranging; they comprise those for group acceptance, probabilistic measures and game-theoretical strength, amongst many others. This affords numerous application areas and so the requisite behaviour for each needs to be justified by theoretical proofs of useful properties for a specific application. Our contributions to this field span three interweaving sub-categories, namely methods, properties and applications. For gradual evaluation methods, we develop a number of novel and useful methods themselves. For each method we detail the semantics’ and the frameworks’ definitions then undertake theoretical evaluations based on their properties, before applications targeting real-world problems are suggested for each method. As for gradual evaluation properties, we undertake a systematic analysis for this research landscape by first identifying groups of conceptually related properties in the literature and provide a simplifying and unifying perspective for these properties by showing that all the considered literature properties are implied by four, novel parametric principles. We then validate these principles by showing that they are satisfied by several quantitative argumentation formalisms in the literature. We also instantiate the extensive number of implied properties of these principles which are not present in the literature. These properties are also used to extract argumentation explanations for recommendations in recommender systems, a novel concept and application.
The Compact Radio Sources in the Nucleus of NGC 1068

We report VLBA images of the nucleus of the Seyfert galaxy NGC 1068 at 1.7, 5, and 15 GHz, with resolutions between 3 and 10 mas (0.2-0.7 pc) and a sensitivity of ~106 K at all three frequencies. Our goals are to study the morphology of the radio emission at subparsec resolution and to investigate thermal gas in the putative obscuring disk or torus and in the narrow-line region clouds through free-free absorption of the radio emission. All four known radio components in the central arcsecond (S2, S1, C, and NE, from south to north) have been detected at either 1.7 or 5 GHz, or both. No radio emission was detected at 15 GHz. Component S1 is probably associated with the active nucleus, with radio emission originating from the inner edge of the obscuring torus according to Gallimore et al. Our observed flux densities at 1.7 and 5 GHz are in agreement with their thermal bremsstrahlung emission model, and we find that the nuclear radiation may be strong enough to heat the gas in S1 to the required temperature of ~4 × 106 K. The bremsstrahlung power would be 0.15(frefl/0.01) times the bolometric luminosity of the nucleus between 1014.6 and 1018.4 Hz (where frefl is the fraction of radiation reflected into our line of sight by the electron-scattering mirror) and so the model is energetically reasonable. We also discuss two other models for S1 that also match the observed radio spectrum: electron scattering by the torus of radio emission from a compact synchrotron self-absorbed source and synchrotron radiation from the torus itself. Components NE and S2 have spectra consistent with optically thin synchrotron emission, without significant absorption. Both of these components are elongated roughly perpendicular to the larger scale radio jet, suggesting that their synchrotron emission is related to transverse shocks in the jet or to bow shocks in the external medium. Component C has a nonthermal spectrum absorbed at low frequency. This absorption is consistent with free-free absorption by plasma with conditions typical of narrow-line region clouds.
Network design system recommending similar configurations characterized by manual knowledges

Recently, the number of skilled network design engineers is not enough, and the improvement of non-expert's working efficiency and design quality by the design support system becomes an important issue. Therefore, we developed the network design support system that recommended similar configuration files when the engineer made new design. Our system converts the dependent part of each design matter in existing configuration files into the representation that showed design characteristics by use of the dictionary extracted from the manual of network device. It performs clustering (unsupervised learning) of the converted configuration files, and finds similar ones. We report the concept and implementation of the developed system.
Generation and Uses of Distributed Entanglement in Quantum Information

Title of dissertation: GENERATION AND USES OF DISTRIBUTED ENTANGLEMENT IN QUANTUM INFORMATION Zachary Eldredge Doctor of Philosophy, 2019 Dissertation directed by: Professor Alexey Gorshkov Department of Physics In this thesis, we focus on the questions of how quantum entanglement can be generated between two or more spatially separated systems and, once generated, how it can be applied in quantum technology. First we will discuss a protocol, which we conjecture to be optimal in some regimes, that quickly creates entangled states across long distances in systems with power-law interactions. We will discuss how this protocol compares with currently known bounds on entangled state generation and how it might be implemented in a three-dimensional lattice of Rydberg atoms. Next, we will turn our attention to more general questions of how the LiebRobinson bound and other limitations on entanglement can be used to inform the design of quantum computers. Quantum computers will be required to create entanglement if they are to realize significant advantages over classical computers, meaning that the generation of entanglement is an important question. First, we will discuss the implications of the Lieb-Robinson bound on graph descriptions of quantum computer architectures, and how the relevant graph parameter (diameter) compares to likely cost functions for architectures, such as maximum graph degree and total number of necessary connections. We will present a proposed graph architecture, the hierarchical product, which we believe provides excellent balance between these considerations. We will then introduce new methods of evaluating graphs that allow us to include quantum architectures capable of measurement and feedback operations. After doing so, we will show that the generation of entanglement entropy becomes a limit on computation. We will show that, for several possible physical models of computation, the generation of entanglement can be bounded by simple graph properties. We demonstrate a connection between worst-case scenarios for entanglement generation and a graph quantity called the Cheeger constant or isoperimetric number, which we evaluate for several proposed quantum computing architectures. Finally, we will look at the scenario of quantum sensing. In particular, we will examine protocols for quantum function estimation, where quantum sensors are available to measure all of the inputs to the function. We will demonstrate that entangled sensors are more capable than non-entangled ones by first deriving a new lower bound on measurement error and then presenting protocols that saturate these bounds. We will first do so for linear functions of the measured quantities and then extend this to general functions using a two-step linearizing protocol. GENERATION AND USES OF DISTRIBUTED ENTANGLEMENT IN QUANTUM INFORMATION
Research on the Realizability of Microservice Interaction Contract Based on CSP#

Microservice Architecture is a new development paradigm that transforms the traditional business-oriented information management system into the collaborative work of microservices. Microservices are usually distributed in a loosely coupled manner in the network. In order to coordinate tasks, microservices must coordinate their executions through message interactions with each other. Therefore, modeling and analyzing the interaction between microservices becomes a key issue. The choreography defines the interaction contract between services, and the realizability analysis is the key task to ensure the correct implementation of the microservices interaction contract. The choreography is realizable if interaction contract satisfies choreography specification. This paper use CSP# to analyze the realizability of microservice choreography under synchronous communication and bounded asynchronous communication, and a solution is proposed to repair the unrealizable microservice choreography and made it realizable.
Leveraging Software-Defined Networking for QoS in home networks

Home networks refer to devices at the edge of the internet. These networks face unique provisioning challenges. As the home network is growing and more complex devices are added, the Internet Service Provider (ISP) may struggle to fulfil the specific requirements of each home user. This study investigates the advantages of Software-Defined Networking (SDN) and proposes a way the ISP can leverage it to improve the Quality of Service (QoS) and monitor the traffic in home networks. The SDN controller offers the ISP a centralised point of control that can potentially manage multiple home networks via SDN-enabled devices. A comprehensive survey is conducted on existing work related to SDN implementations for home networks. It is found that most implementations require the home gateway router to be replaced with an SDN-enabled device. Scalability considerations are also rarely investigated. Based on these current shortcomings, an experimental setup that resembles a typical South African home network is designed and tested in the Mininet emulation environment. The Analytical Hierarchy Process (AHP) is used to identify the Ryu controller as the most suitable for the design, compared to six other open-source SDN controllers. Experiments with different network traffic types are quantitatively compared using four QoS parameters, namely throughput, jitter, packet loss and round-trip time. Two different use cases are compared with each other, first where QoS is not implemented and second where specified traffic is prioritised by the SDN controller. The SDN switch (Open vSwitch) is configured using Ryu's REST Application Programming Interface (API) and the OpenFlow protocol. A Graphical User Interface (GUI) application is developed (using the tkinter package in Python) to offer a simple and easy way for the ISP to configure their clients' networks. By using the statistics of queues installed on the SDN switch, the controller can monitor the network traffic of a home network. The scalability of this design is tested by emulating an increasing number of queues installed on OVS and measuring the amount of
Control and data-acquisition of a heater/temperature sensor

The goal of this bachelor thesis is to develop a control system that controls the temperature of a microthruster. This system also needs to acquire data for research. The microthruster contains a resistor that is used both as a heater and as a sensor. To facilitate the acquisition of data and the testing of the control system, a lab setup with a Keithley 2450 SourceMeter power supply was used. LabVIEW was used to control the power supply and to execute the control algorithms. The final system consists of a microcontroller that runs the control algorithms based on proportional-integral-derivative (PID) control developed in this thesis. The PID values can be adapted with use of the graphical user interface (GUI). A read-out circuit and current supply will be part of the integrated system. These circuits will be developed by other groups that are part of this bachelor project.
Deep Learning Tasks Processing in Fog-RAN

Recently, the demand on performing intelligent tasks for mobile devices with low-latency is ever- increasing, while the requirements of intensive computation and large storage size impedes the deployment of deep learning models directly on devices. Fog radio access network (Fog-RAN) offers a promising solution by integrating the computing power and storage of edge processing nodes (e.g., base stations). In this paper, we propose a joint deep learning task selection and downlink transmit beamforming approach to improve the communication efficiency while achieving green computing, i.e., minimizing the sum of computation power consumption for deep learning tasks and downlink transmit power consumption. For efficient algorithm design, we exploit the group sparsity structure of the aggregated beamforming vector and propose a log-sum based group sparse beamforming framework. An iteratively reweighted l1 algorithm is developed to solve the nonconvex and nonsmooth log-sum minimization problem. Furthermore, we derive the global convergence result of the iteratively reweighted l1 algorithm, which shows that it converges to the first-order stationary point from any feasible starting point. Simulation results demonstrate that our log-sum based group sparse beamforming approach for deep learning tasks processing is more efficient than state- of-the-art approaches in terms of power consumption.
A novel control strategy for power conditioning unit to enhance power quality during FRT

This paper proposes a novel control strategy for power conditioning unit (PCU) to enhance power quality during fault ride through (FRT) operation. During unsymmetrical fault condition, PCU injects sinusoidal currents by adopting control method suggested. By using effective current limitation technique suggested here, injected currents can be limited to their rated value during a fault. To avoid triggering of overcurrent protection, FRT operation is ensured. In case of failure of dc-dc unit to handle the maximum PV power, a non-maximum power point tracking (Non-MPPT) operation mode is proposed to get it operated under severe fault condition.
Optimization design of the online learning environment for ethnic college students: the perspective of the emotional participation

ABSTRACT The emotional participation of online learning is a process-oriented emotional indicator that measures learners’ learning effects. Existing studies have shown there is little research on online-learning emotional participation, and even fewer have studied the online learning participation of ethnic college students. In order to study the online learning participation of ethnic college students, this paper tried to build the online-learning emotional participation theory model, which included four dimensions: learning interest, self-efficacy, self-worth and the sense of belonging. Based on the survey of 723 students from Yunnan Minzu University in China, we analysed the structural and quantitative relationships among the four dimensions of online-learning emotional participation of ethnic and Han college students respectively. The results show that there are significant differences in the online-learning emotional participation between ethnic and Han college students, especially their sense of belonging. Furthermore, in order to build a better online learning environment for ethnic college students and enhance their sense of belonging, an online learning community model is proposed.
Group Event Recommendation in Event-Based Social Networks Considering Unexperienced Events

As users in event-based social networks (EBSNs) usually participate in events together with friends, classmates, colleagues, or family members, recommending events to a group of users is attracting increasing attention in EBSNs recent years. However, existing studies are lack of attention to the fact that groups in EBSNs may have potential desires for participating in the unexperienced events. In order to deal with the challenges, including mining implicit friendships between users, simulating the consulting process between users and their friends outside the groups, and simulating the negotiating process among members inside the groups, we propose a two-phase group event recommendation (2PGER) model for EBSNs. First, we leverage information, such as online social behaviors, users’ event participation records, and topological structures of EBSNs to establish a global trust network among users and establish egotrust networks of all users. Then, we perform random walks on the pre-built egotrust network for each user to acquire the user’s predicted preferences on the unexperienced events. Third, we adopt a random walk with restarts (RWR) method to aggregate users’ preferences and recommend top N events to groups. In the end, we compare 2PGER with several baseline approaches on real datasets from Meetup. The results show that 2PGER outperforms baselines.