Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Algorithms for Multiobjective Optimization with Applications in Portfolio Optimization

RADHAKRISHNAN, ALAMELU. Evolutionary Algorithms for Multiobjective Optimization with Applications in Portfolio Optimization. (Under the supervision of Dr. Negash Medhin.) Multiobjective optimization (MO) is the problem of maximizing/minimizing a set of nonlinear objective functions (modeling several performance criteria) subject to a set of nonlinear constraints (modeling availability of resources). The MO problem has several applications in science, engineering, finance, etc. It is normally not possible to find an optimal solution in MO, since the various objective functions in the problem are usually in conflict with each other. Therefore, the objective in MO is to find the Pareto front of efficient solutions that provide a tradeoff between the various objectives. Classical techniques assign weights to the various objectives in the MO problem, and solve the resulting single objective problem using standard algorithms for nonlinear optimization. Moreover, these techniques only compute a single solution to the problem forcing the decision maker to miss out on other desirable solutions in the MO problem. We investigate the use of evolutionary algorithms to solve MO problems in this thesis. Unlike classical methods, evolutionary strategies directly solve the MO problem to find the Pareto front. These algorithms use probabilistic rules to search for solutions and are very efficient in solving medium sized MO problems. We use evolutionary algorithms to compute the efficient frontier in the classical Markowitz mean-variance optimization problem in finance, and illustrate our results on an example. EVOLUTIONARY ALGORITHMS FOR MULTIOBJECTIVE OPTIMIZATION WITH APPLICATIONS IN PORTFOLIO OPTIMIZATION by ALAMELU RADHAKRISHNAN A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Master of Science OPERATIONS RESEARCH Raleigh, North Carolina March 27, 2007 APPROVED BY Dr. Jeffrey Scroggs Dr. Salah Elmaghraby Dr. Negash Medhin (Chair of Advisory Committee) BIOGRAPHY Alamelu Radhakrishnan is from India. She is currently pursuing a Master’s in Operations Research at North Carolina State University and will graduate in Spring 2007. She received her undergraduate degree in Electrical Engineering from University of Madras, Chennai, India and a M.S. in Electrical Engineering from Polytechnic University, Brooklyn, New York.
A Grammar of Maonan

Maonan is a Kam-Tai (Tai-Kadai) language spoken by 75,000 people in the border area of Guangxi and Guizhou provinces of China. This grammar book is the first volume to account for the phonology, word-formation, syntax, grammaticalization and lexicalization patterns of Maonan from a typological and ethno-linguistic perspective. It renders a comprehensive description of Maonan with analysis of the neutralization of semantic macroroles and the dialectic interrelations between subject and topic. Particular attention is paid to the interplay between syntactic and semantic valencies.The detailed analysis of the Maonan aspects is also unprecedented. It examines Maonan tone sandhi from a totally new approach. The book also gives a full description of the clause final particles of Maonan.
On Lippmann's Photography

Abstract. This paper revisits the problem of recording of photographs using ultra-fine grain recording materials backed by a reflecting surface. A discussion is given of the underlying theoretical concepts and practical recording limitations and an explanation is given of the ability of the method to work with relatively narrow band (0.03 p) natural light. A simple practical experiment helps to clarify the underlying physical difficulties and provides an evaluatory method for the recording emulsion. An important necessary criterion associated with the recording optics is verified. A discussion of the use of Lippmann's technique to produce holograms in natural light emphasizes the difficulty of the exercise.
Synthesis of Trifluoromethylated Isoxazoles and Their Elaboration Through Inter‐ and Intra‐Molecular C—H Arylation.

We report conditions for the preparation of a range of trifluoromethylated isoxazole building blocks through the cycloaddition reaction of trifluoromethyl nitrile oxide. It was found that controlling the rate (and therefore concentration) of the formation of the trifluoromethyl nitrile oxide was Critical for the preferential formation of the desired isoxazole products versus the furoxan dimer. Different conditions were optimised for both aryland alkyl-substituted alkynes. In addition, the reactivity at the isoxazole 4-position has been briefly explored for these building blocks. Conditions for intermolecular C–H arylation, lithiation and electrophile quench, and alkoxylation were all identified with brief substrate scoping that signifies useful tolerance to a range of functionalities. Finally, complementary processes for structural diversification through either intramolecular cyclisation or intermolecular cross-coupling were developed.
Enantioselective Synthesis of 2,3‐Disubstituted Piperidines from (S)‐Methylpyroglutamate.

Abstract N -methoxy- N -methylamide derived from ( S )-methylpyroglutamate was prepared in good yield and allowed the addition of Grignard reagents. Erythro ( 2S )-1-benzyl-2-hydroxybenzyl pyrrolidine obtained by this way was converted into ( 2S,3R )-1-benzyl-3-hydroxy-2-phenylpiperidine and its chloro analog.
EEG Signal Analysis Based on the LabVIEW Station

This paper introduces the basic theory of wavelet analysis and its application in the EEG(Electroencephalogram) signal processing.Based on the virtual instrument development platform LabVIEW,a wavelet analysis system of EEG is designed to realize the function of filtering and rhythm detecting of the EEG signal.The power spectrum analysis method is also discussed.
Improving Information Extraction by Discourse-Guided and Multifaceted Event Recognition

Events are one important type of information throughout text. Event extraction is an information extraction (IE) task that involves identifying entities and objects (mainly noun phrases) that represent important roles in events of a particular type. However, the extraction performance of current event extraction systems is limited because they mainly consider local context (mostly isolated sentences) when making each extraction decision. My research aims to improve both coverage and accuracy of event extraction performance by explicitly identifying event contexts before extracting individual facts. First, I introduce new event extraction architectures that incorporate discourse information across a document to seek out and validate pieces of event descriptions within the document. TIER is a multilayered event extraction architecture that performs text analysis at multiple granularities to progressively “zoom in” on relevant event information. LINKER is a unified discourse-guided approach that includes a structured sentence classifier to sequentially read a story and determine which sentences contain event information based on both the local and preceding contexts. Experimental results on two distinct event domains show that compared to previous event extraction systems, TIER can find more event information while maintaining a good extraction accuracy, and LINKER can further improve extraction accuracy. Finding documents that describe a specific type of event is also highly challenging because of the wide variety and ambiguity of event expressions. In this dissertation, I present the multifaceted event recognition approach that uses event defining characteristics (facets), in addition to event expressions, to effectively resolve the complexity of event descriptions. I also present a novel bootstrapping algorithm to automatically learn event expressions as well as facets of events, which requires minimal human supervision. Experimental results show that the multifaceted event recognition approach can effectively identify documents that describe a particular type of event and make event extraction systems more precise.
Componentized Software Service and Its Application in Artemis-ARC

This paper proposed a method of componentized software service in both conception and technology which explicitly described the dependency among services and guarantees uniformity of functional abstraction.In addition,it particularly discussed some key techniques about description,composition and searching of componentized services.At last,it implemented a prototype system and applied in a system named Artemis-ARC to support developing,deploying,managing and using componentized services.
A Lightweight Digital Signature Cryptographic Protocol for Authentication and Integrity Based on Location

The shipping of digital documents, from a sender to a receiver, must keep certain properties, including the authenticity of the source and message integrity. These properties can be achieved through cryptographic protocols, which define the way in which a cryptographic primitive should be used during a communication process. As an additional function to the mentioned properties, GeoLock is a function that is used to add the coordinates of a receiver to the digital signature primitive or to other cryptographic primitives, which helps to prove that such entity is located in the right place and is able to verify a generated signature avoiding antispoof receivers. However, the use of public key cryptographic primitives with the GeoLock function on mobile devices, involves considering the performance of all cryptographic operations together. Considering the aforementioned, in this study a lightweight cryptographic protocol based on the digital signature primitive and GeoLock is presented in order to meet authentication and integrity based on location. The obtained results show that the proposed protocol is more efficient if compared to related works, as less cryptographic operations are required.
The role of the 'self' and 'awareness' in language teaching and learning : a case study of the 'silent way'

Currently there are many methods used in the teaching of foreign languages. One method that is different to the traditional as well as the modern approaches is the Silent Way. The Silent Way is the direct application of Gattegno's theories in the area of foreign language teaching. The current study investigated how four Silent Way teachers in Besançon, France, constructed their teaching practice based on Gattegno's theories. The study explored how these teachers translated Gattegno's ideas into teaching strategies and how their students experienced learning English the Silent Way. Data were collected using participant observation, interviews and videos of lessons employed as stimuli for interviews after these lessons. The data were gathered within phenomenological and ethnomethodological research frameworks. For the data analysis a grounded theory approach was taken. Findings from the research suggested that the Silent Way teachers involved in the study base their teaching on Gattegno's theory of learning. Further, the teachers attempted to make their students aware of what was taking place within themselves as they were learning the language. The teachers subordinated their teaching to the students' learning by furnishing informational feedback on the sentences on which the students worked. The twelve students who participated in the study generally responded positively to learning a language the Silent Way. The findings suggest that the students experienced at times essential states of being in which focussed concentration was coupled with high levels of intrinsic motivation. Their learning experiences would probably be considered by proponents of the "flow" theory to be a good example of this theory. Findings from the study demonstrate that the processes involved in teaching and learning a language the Silent Way do not develop in a linear but a cyclic fashion. Several phenomena are characterised by subtle shifts in energy that are difficult to observe within each person. The Silent Way seems to be based on energy movements of each person and the group and these need to be explored with further research.
Formal Derivation of the Minimum Spanning Tree Algorithm with PAR Method

This paper uses PAR method to derivate the readable and efficient recursive minimum spanning tree algorithm formally by transforming function specification.This method simplifies the process of algorithmic program’s design and correctness testifying,and effectively improves the automatization,standardization and correctness of algorithmic program’s design.It gives the implementation of the algorithm in automatic program transformation system of PAR platform.
Dynamic trajectory planning for unmanned aerial vehicle based on sparse A* search and improved artificial potential field

Based on the sparse A* search algorithm for path planning and the improved artificial potential field, we propose a method of dynamic trajectory planning for unmanned aerial vehicle(UAV) in the threat model composed of obstacles with different attributes. This method first builds a grid model of the threat distribution; and then, it makes the global path planning by sparse A* search algorithm according to the static obstacles; Finally, combining the pre-determined route and the dynamic obstacles, UAV can accomplish the dynamic trajectory planning by using the improved artificial potential field. Simulation results indicate that the proposed method can find a global optimal path with the given risk index and achieve a good performance of dynamic obstacle avoidance.
Secure service discovery in building automation and control systems

Building Automation and Control Systems (BACS) are intelligent networks of distributed sensors and actuators, which enable monitoring and control of heating, ventilation, and air conditioning (HVAC), lighting, and safety systems deployed in commercial buildings. These sensors and actuators can be seen as resources of the corresponding nodes interacting with each other, and with users providing various device services. For easy commissioning and cost-effective operation of BACS, service discovery operations are essential. BACS is very critical part of a building infrastructure requiring that device and services are accessed and controlled in a secure way. Consequently, security and access control must be incorporated as integral part of the methods for service discovery in BACS. Furthermore, any security solution needs to take into account the domain specific requirements such as constraints on computation power, limited memory of nodes, and communication bandwidth, among others. The objective of this thesis is to identify design requirements of a secure service discovery protocol in BACS. Further based on these requirements, a design solution is presented and analyzed based on the constraints of the system. Functionality of the proposed design is implemented as a proof-ofconcept and the system is evaluated.
Organocatalytic Synthesis ofTerminal Propargylamine Derivatives by Tandem Amination-Alkynylation

The first organocatalytic synthesis of terminal propargylic amines from aldehydes via tandem amination/Seyferth― Gilbert alkynylation has been developed. The described protocol provides the formal addition products of acetylene (HC≡CH) to aliphatic imines, which are not easily obtained directly.
Universal Annotation of Slavic Verb Forms

Abstract This article proposes application of a subset of the Universal Dependencies (UD) standard to the group of Slavic languages. The subset in question comprises morphosyntactic features of various verb forms. We systematically document the inventory of features observable with Slavic verbs, giving numerous examples from 10 languages. We demonstrate that terminology in literature may differ, yet the substance remains the same. Our goal is practical. We definitely do not intend to overturn the many decades of research in Slavic comparative linguistics. Instead, we want to put the properties of Slavic verbs in the context of UD, and to propose a unified (Slavic-wide) application of UD features and values to them. We believe that our proposal is a compromise that could be accepted by corpus linguists working on all Slavic languages.
Syntax-based Statistical Machine Translation Models and Approaches

This paper gives an overview of our research work on syntax-based statistical machine translation in recent year.Our work especially focused on a series of syntax-based statistical machine translation models and approaches,which includes: the translation model based on maximum entropy bracketing transduction grammar,source phrase structure based tree-to-string translation model and the translation approaches based on it—tree-based approach,forest-based approach,and joint parsing and decoding approach,and the source dependency based translation model.
Switching Thresholds for Rate Adaptation with MRC under Feedback Delay

The design of spectrally efficient and robust schemes is vital to overcome the harsh wireless environment when delivering high data rate services. In the present paper, the performance of a constant power-discrete rate adaptation scheme is evaluated in a multiple antenna scenario. Such technique has low complexity, and needs a low rate feedback channel to adapt transmission rate. However, the feedback can become outdated when the channel is changing rapidly. To compensate the error in feedback, we propose a new switching thresholds for the rate adaptive system coupled with a multi-antenna MRC receiver. Closed form expressions are obtained for the Bit-ErrorRate (BER) performance of a rate adaptive system with an instantaneous BER constraint. On the basis of the analytical study, two types of switching thresholds are obtained, generic and updated. The latter takes into account the feedback error due to delay. We analyze the impact of feedback delay on the BER performance, when employing both generic and updated thresholds. Simulation results show that the proposed thresholds maintain the performance of the system when in presence of time-delayed feedback.
Collaborative defending scheme against malicious Web pages based on social trust

To deal with the threat of malicious Web pages,a distributed defending scheme against malicious Web pages based on social trust was proposed.Besides the malicious URL list from third-party professional organizations,the direct and indirect trust relations between friends in social network were used to obtain evaluations of Web pages.The experiences about Web surfing from a user’s friends were collected to result in synthetical evaluations on his computer.Each user cooperated with his friends,so that a defending system was formed on the overall perspective,which can improve the defending ability of the social network against malicious Web pages.The experiment results indicate that the visits of malicious Web pages under the scheme decrease obviously than the methods without social trust.
Geospatial Named Entities Recognition Using Combination of CRF and Rules

A GeoSpatial Named Entities Recognition(GSNER) method based on combination of Conditional Random Fields(CRF) and rules is proposed.This method takes extensive knowledge as trigger conditions.Triggered text fragments are put into CRF Named Entity Recognition(NER) module,and recognized NEs are deconstructed to several components,CRF and knowledge are also employed for classification of GSNE.Experimental results show that,this combination method and the NE deconstruction strategy effectively promotes the performance of GSNER: the overall Precision,Recall,F1 achieves 92.86%,90.91%,91.87%.
Indium Triflate as a Recyclable Catalyst for the Nitration of Aromatic Compounds without a Halogenated Solvent

Indium triflate [In(OTf)3] was found to be excellent catalyst (0.5 or 2.0 mol%) for the mononitration of aromatic compounds using a single equivalent of nitric acid (60 or 90%, 1.0 equiv.) without using a halogenated solvent. The side product is water and the indium triflate catalyst can be readily recovered from the aqueous phase and reused.
A Survey of Reservation-Based Scheduling

A survey of reservation-based CPU scheduling, developed as a part of the VINNOVA project FISS2 and of the EU project ACTORS The field of Reservation-based scheduling is presented. A brief history is given together with an in-depth look at the main classes of reservation-based scheduling algorithms. An overview of important publicly available implementations of reservation-based schedulers is provided as well.
A Lesk-inspired Unsupervised Algorithm for Lexical Choice

The generation of text from abstract meaning representations involves, among other tasks, the production of lexical items for the concepts to realize. Using WordNet as a foundational ontology, we exploit its internal network structure to predict the best lemmas for a given synset without the need for annotated data. Experiments based on re-generation and automatic evaluation show that our novel algorithm is more effective than a straightforward frequency-based approach.
A Novel Approach to Position Senseorless Vector Control of PMSM Based on Active-disturbance Rejection Controller

A novel approach to position sensorless vector control system of permanent magnet synchronous motor (PMSM) based on active disturbance rejection controller (ADRC) is presented in this paper.The speed regulator is an ADRC regulator,in which the effect of load in speed loop is regarded as an external disturbance.The disturbance is observed and compensated by ADRC,which lead to good dynamic and static performance and robust to load.The speed is also estimated by ADRC.The effect of speed and d-axis current in torque loop are regarded as a disturbance,which is observed by ADRC.The PMSM speed is then estimated based on the exactly observe value of torque loop disturbance. Simulation and experiment results show that the speed can be accurately estimated from Or/min to 1500r/min with load or not. A good dynamic and static performance of PMSM speed regulation is achieved by this method.
Design, modeling, and evaluation of efficient caching mechanisms for content dissemination networks

Imai Satoshi, Leibnitz Kenji, Murata Masayuki, Energy efficient data caching for content dissemination networks, Journal of High Speed Networks, vol. 19, no. 3, pp. 215-235, 2013.The final publication is available at IOS Press through http://dx.doi. org/10.3233/JHS-130474 .
APPLICATION OF FOURIER TRANSFORM ON SEGMENTATION OF CONNECTED CHARACTER

For the research of handwritten character recognition, which has a higher recognition rate for the practical application, segmentation becomes very important point and influences the performance of the system directly. This paper focuses on the analysis of Fourier transform of an image pattern and apply it to distinguish single/multiple character image. And an algorithm of estimating connected character is proposed, which overcome the influence of the width of stroke. The experiential results show that this algorithm, whose accuracy is over 96%, could become a good method for segmentation of connected handwritten character.
Analyzing and Verifying SOFL Workflows for Web Service Composition

While the different aspects of flexible workflow in the management are still under discussion, number of domain-specific languages for workflow description have been proposed with consensus being formed around a process-oriented language known as WS-BPEL. However, detecting logic errors and conducting the validation of the business process is quite hard due to BPEL does not have formal semantics. This paper aims at validating the feasibility of using SOFL for static analysis of business process. SOFL can be used as a design language for the specification of complex workflows, and SOFL theory provides for powerful analysis techniques which can be used to verify the correctness of workflow procedures. In particular, we focus on how to apply SOFL modeling approach to validate and analyze workflow which is an extension of WfMC's process definition meta-model.