Reviewerly/exHarmony huggingface dataset:
Applications of representation theory in discrete mathematics

In this thesis we present two new applications of the representation theory of finite groups in discrete mathematics. The first application is in coding theory. We further develop the theory of upper bounds for error-correcting codes and mixed binary/ternary codes, thereby expanding upon the work of Gijswijt et al. and Brouwer et al. We consider semidefinite programs based on quadruples of codewords and apply a symmetry reduction to obtain an optimization problem of polynomial size. This enables us to solve the semidefinite program with the aid of the computer for several values of n (the length of the words), q (the size of the alphabet) and d (the distance). The second application of representation theory is concerned with the enumeration of local flows in embedded graphs. We extend the domain of the surface Tutte polynomial of Goodall et al. to include non-orientable embedded graphs and show that this invariant for embedded graphs contains for every finite group G the number of nowhere-identity local G-flows and the number of nowhere-identity local G-tensions as evaluations. We prove that for an embedded graph nowhere-identity local tensions correspond with proper colorings of a covering of the embedded graph, thereby generalizing coloring-flow duality for planar graphs. The surface Tutte polynomial also specializes to a trivariate polynomial for signed graphs. We show that this polynomial has a universal property, which we finally use to give combinatorial interpretations of several of its evaluations.
RETRACTED: Research on Transmission Functions of Foreign Language and Chinese Medicine Culture under the Background of “Big Data”

Abstract In order to solve the problem of learning resource description in big data environment, this paper proposes a learning resource description system based on metamodel, that is, to establish a set of metadata model that is not only in line with the standards of learning resource description, but also has extensibility. By referring or mapping to the element set of the common metamodel, the elements of the metadata model of various resources are obtained to achieve the compatibility between different metadata models. This paper combines the learning resource model in the context of big data, and analyses the transmission functions of foreign language and Chinese medicine culture, including communication of language, communication of Chinese medicine culture, communication of Chinese medicine trade and communication of Chinese medicine financing.
A fast and accurate moving target detection method

This paper proposes a significant moving target detection method combining time difference and optical flow field filter for scenes with complex backgrounds such as streets and traffic intersections. Firstly, the gradation change region of the sequence image is obtained by using the cumulative frame difference, then the Lucas-Kanade optical flow algorithm is introduced to obtain the optical flow field of the gray-scale change region. Finally, the optical flow time filter is used to filter the interference motion in the image background. The method can not only detect the motion area quickly and accurately, but also distinguish the spurious interference motion from the salient target (such as people, cars, etc.). So it detects the moving target in a complex background easily.
Development of Selective Control Algorithm of Production Logistics Flows

At present, the functioning of logistics flow management systems is based on the use of algorithms. However, such algorithms as "r, Q", EOQ," with a fixed order size", etc., are not fully universal means of management and distribution of logistics resources, adapted to different conditions of production activities. They are mainly used to solve specific problems of logistics and usually do not consider the logistics process as a component of a single dynamic complex. Existing processes and algorithms of management of specialized flows are aimed to work at specific values of characteristics of logistics flows. The results of preliminary studies have shown that the use of selective mechanism is possible to increase the percentage of processed applications by 20 - 35%, and with the expansion of the processed list of types of logistics resources by 10 times, the number of outstanding applications increases by only 10%.
Influence of Information Technology on Personnel Management in Nigeria

This study is to examine the influence of information technology on personnel management.To determine the extent of which application of information technology is significant on personnel management.The research method is descriptive.The study approach is based on the research questionnaire which has influenced the data generated and the pattern of the descriptive analysis presented.The researcher analyzed the data collected based on the response from the questionnaires distributed to the Staff and Management of the selected bank.Based on the findings, the following recommendations were made; Organizations should also develop effective security measures to protect their information system from deceptive aggressors.This could be done through the use of passwords, firewalls, encryption and decryption keys, digital signatures, anti-virus programs etc.The importance of information technology in organizations cannot be over highlighted because if the staffs get the right exercise, it will increase their output and customers will be satisfied.
SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity

In this paper we introduce a semi-analytic variational framework for approximating the posterior of a Gaussian processes coupled through non-linear emission models. While the semi-analytic method can be applied to a large class of models, the present paper is devoted to the analysis of causal connectivity between biological spiking neurons. Estimating causal connectivity between spiking neurons from measured spike sequences is one of the main challenges of systems neuroscience. This semi-analytic method exploits the tractability of GP regression when the membrane potential is observed. The resulting posterior is then marginalized analytically in order to obtain the posterior of the response functions given the spike sequences alone. We validate our methods on both simulated data and real neuronal recordings.
THE ANALYSIS OF GRAMMATICAL PROBLEMS AND GENERIC STRUCTURE OF NARRATIVE TEXT WRITTEN BY THE ELEVENTH GRADUATE STUDENTS OF LANGUAGE PROGRAM AT SMAK ST.KLAUS WERANG-WEST FLORES

The study was intended to analyze grammatical problem and generic structures of narrative text written by the eleventh grade students of Language program at SMAK St. Klaus–West Flores in the academic year 2016/2017. The data were mainly collected through assigment on narrative written text and itervies and were analyzed descriptively using Dulay’lingistics taxonomy (1982) and  Fink’ category (2005). The result of  data analysis revealed that the students committed errors in  their narrrative writing, namely article, possessive case, omission of – ed, regularization by adding –ed, simple present tense used in place of simple past tense, omission of –be, pluralization, pronoun, preposition, omission of main verb, subject verb agreement, word order, diction, spelling, passive form, adverb, conjunction, double marking, and modals. The cause of error was interference, lack of vocabularies, and motivation, and teacher’ ability/qualification.
Scelsi, Sense, and the Musical Matter

Giacinto Scelsi’s first writing on music aesthetics, ‘Sens de la musique’ (1942/44) provides a comprehensive account of (the sense of) music as a complex equilibrium between the human elements (rhythm, emotion, cosmic, intellect, psychic) and those of music (rhythm, melody, harmony, construction). The complexity of that equilibrium indexes a highly intricate mode of relating to musical sound, hence Scelsi’s notion of klang—a complex sonic entity, more than just sound, chord, etc; klangis the material of music, the ‘sonorous matter’ on which listening projects ‘images’ created by the aforementioned elements. Music relates to language; however, its material does not necessitate discreet elements (such as words). Scelsi’s landmark Four Pieces on a single note (1959) is a perfect example of music’s materiality and its mode of existence in time/space. The notion of sonorous matter was developed decades later by philosopher Jean-Luc Nancy, who also focused on a notion of sense: listening (sensing) is in search of meaning, while at the same time touches on the materiality of sound. Sense is taken in its multiple meanings: sensibility, sensation, intelligibility, orientation, and is always in excess of meaning. Nancy's philosophy thus treats the relationship between matter, language, writing, and art, as one that operates on the limits; such thinking is enabled both by a materialist ontology and the excessive nature of sense (hence for Nancy the metonymy for all sense is touch). This paper will explore the links between the two approaches.
Experimental Sound Design for Wave Field Synthesis: Employing Low-Quality Voice Recordings into Spatial Audio for Art Installation

This paper explores the intersection between high-end technology for immersive media and conceptual sound installations using low-quality audios. It discusses the concept of fidelity in sound reproduction and traces how this concept relates to the subject of identity and self through the recorded voice. I analyse art projects that use low-quality audio to address issues of self and how these projects can help presenting an alternative understanding of experimental sound design for spatial audio. Finally, I explore the issue through my own artistic research called This Alienness and Me, where I investigate the feeling of “not belonging” through personal voice recordings made with a cellphone. In my project the audios were juxtaposed using Wave Field Synthesis to create an immersive environment.
DESIGNING AN INTERDISCIPLINARY CURRICULUM FOR DIGITAL TRANSFORMATION

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 7757-7763ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.1911Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
Higher-Order Masking Scheme against DPA Attack in Practice: McEliece Cryptosystem Based on QD-MDPC Code

A code-based cryptosystem can resist quantum-computing attacks.However, an original system based on the Goppa code has a large key size, which makes it unpractical in embedded devices with limited sources.Many special error-correcting codes have recently been developed to reduce the key size, and yet these systems are easily broken through side channel attacks, particularly differential power analysis (DPA) attacks, when they are applied to hardware devices.To address this problem, a higher-order masking scheme for a McEliece cryptosystem based on the quasi-dyadic moderate density parity check (QD-MDPC) code has been proposed.The proposed scheme has a small key size and is able to resist DPA attacks.In this paper, a novel McEliece cryptosystem based on the QD-MDPC code is demonstrated.The key size of this novel cryptosystem is reduced by 78 times, which meets the requirements of embedded devices.Further, based on the novel cryptosystem, a higher-order masking scheme was developed by constructing an extension Ishai-Sahai-Wagne (ISW) masking scheme.The authenticity and integrity analysis verify that the proposed scheme has higher security than conventional approaches.Finally, a side channel attack experiment was also conducted to verify that the novel masking system is able to defend against high-order DPA attacks on hardware devices.Based on the experimental validation, it can be concluded that the proposed higher-order masking scheme can be applied as an advanced protection solution for devices with limited resources.
Experimental Multi-Qubit Robustness by Local Encoding

We experimentally demonstrate on photonic four-qubit graph states, robust noise protection without requiring any additional physical qubits. Our method is tested in a realistic scenario as phase estimation in highly noisy environment.
Research on Energy Blockchain Platform Based on Private Key Storage Algorithm of Image Information Hiding

With the adjustment of the world's energy structure, the proportion of clean energy represented by renewable energy is increasing. In response to the shortcomings of renewable energy instability, researchers have proposed the concept of the microgrid. However, with the expansion of the scale of the promotion of the microgrid, the traditional energy distribution system with the sales company as the core exposes the shortcomings of being inflexible. Based on this researcher's continuous exploration of new energy trading models, the energy blockchain has developed rapidly in recent years. Reliable private key storage is a necessary guarantee for the security of energy blockchain services. At present, blockchain private key storage technology still has many security risks in the new energy transaction mode. This paper first builds an energy blockchain platform inside the microgrid, so that all participants can complete energy transactions more safely and conveniently. At the same time, the energy blockchain private key storage technology based on image information hiding is proposed. The blockchain private key is hidden in the watermark information and embedded in the carrier image. A watermarking algorithm based on discrete wavelet transform and quantization index modulation is used to accurately extract the blockchain private key. Finally, the feasibility and security of the algorithm are proved by an example test analysis.
Exploration Of Vocal Repertoire In Performance

This project consists of a 25-minute vocal recital accompanied by a written component. The vocal recital includes repertoire from each of the four main periods of music history (Baroque, Classical, Romantic, and Contemporary) and works in English, Italian, French, and German. The written component consists of biographical information on each composer, character and musical analysis, exploration of technical aspects of the pieces, musical characteristics of composers and time periods, and translations of texts. Pieces that are part of a larger work of music, such as an oratorio or opera, include historical information and a synopsis of the larger work. When the author of the text of a piece can be identified, that information will be included alongside the composer. A condensed version of this thesis will be available to audience members as program notes as the time of the recital.
A Methodology for Defining Working Healthcare Ontologies

Retrieving the information needed for right clinical decision and searching through a large amount of data are important challenges that health information systems encountered despite the advances in the information systems.In order to reuse these distributed data, the health information standards are developed to enable interoperable health information systems.As the standards are far from the necessary semantics, the data defined according to these standards are not been efficiently used by machines.Semantic Web technologies provide a common framework to access and process the information by machines with the support of ontologies.The heterogeneous and distributed nature of health data makes it a very suitable candidate to define health domain specific ontologies.In this work, a methodology for defining health ontologies, which should work as information base of a health information system as the next stage, is proposed to ensure interoperability and reuse between health information systems with the support of health information standards.Clinical Biochemistry Laboratory Ontology (CBLO) is given as a use case to model information of laboratory tests realized in clinical biochemistry laboratory that are a sub-domain of medical laboratory tests.In addition, a weighted evaluation for the proposed methodology is presented.
Upper bounds on secure key against non-signaling adversary via non-signaling squashed secrecy monotones

We initiate a systematic study to provide upper bounds on device-independent key, secure against a non-signaling adversary (NSDI), distilled by a wide class of operations, currently used in both quantum and non-signaling device-independent protocols. These operations consist of a direct measurements on the devices followed by Local Operations and Public Communication (MDLOPC). We employ the idea of squashing on the secrecy monotones, which provide upper bounds on the key rate in secret key agreement (SKA) scenario, and show that secrecy monotones are the upper bounds on NSDI key. As an important instance, an upper bound on NSDI key rate called squashed non-locality, has been constructed. It exhibits several important properties, including convexity, monotonicity, additivity on tensor products, and asymptotic continuity. Using this bound, we identify numerically a domain of two binary inputs and two binary outputs non-local devices for which the non-locality is zero, and therefore one can not distil key from them via MDLOPC operations. These are mixtures of Popescu-Rohrlich (PR) and anti-PR box with the weight of PR box less than $80\%$. This example confirms the intuition that non-locality need not imply secrecy in the non-signaling scenario. The approach is general, describing how to construct other tighter yet possibly less computable upper bounds. Our technique for obtaining upper bounds is based on the non-signaling analog of quantum purification: the complete extension, which yields equivalent security conditions as previously known in the literature.
A Simple Algorithm for Identifying the Direction of Arrows

During the development of intelligent drive,the pursue for real-time and precise process of image has been the key point of research. This article introduces a simple way to identify the direction of arrows by means of their length and width.This method has been proven by Matlab.The Terasic's DE1-SoC development board and D5M camera are used to realize the algorithm. The result shows that this method has high performance on both timeliness and robustness.
Impact of Self Management Behavior and Sportsmanship of Ssireum Athletes on Organizational Effectiveness and Performance

The purpose of this study investigates the cause-effect relationship of the impact of self management behavior and sportsmanship of ssireum athletes on organizational effectiveness and performance. Using 475 valid specimens comprised of ssireum athletes in semi-professional and college teams, the Window SPSS Ver. 20.0 statistics program was utilized and the following conclusions were acquired using the frequency analysis, descriptive analysis, factor analysis and multiple regression analysis. First, self management behavior (willpower control, life management, unique behavior management, interpersonal relationship management, body management) had positive correlation with sportsmanship(respecting and considerate of others, concentration in best performance, respect of rulings, teamwork), organizational effectiveness (organizational concentration and satisfaction), and performance.
Use of Blockchain Technology in the Financing of DEASH

Technological developments that accelerated in the 21st century, while providing great positive contributions to societies, bring with them some problems. Especially the using of technological opportunities in the crime world is a new threat to public security. DEASH (ad-Dawlah al-Islamiyah fil-â€˜Iraq wa ash-Sham) terrorist organization is actively using financial and visual tools of the Internet for the financing of terrorism in cyberspace. In this study, it is explained how the blockchain technology and Bitcoin used by DEASH terrorist organization have been used in recent years with sample cases.
LibGuides: Scholarly Writing and Publishing: Home

This guide is designed to help you find materials from the Houston Cole Library or online for scholarly writing and publication.
Obstructions for partitioning into forests

For a class $\mathcal C$ of graphs, we define $\mathcal C$-edge-brittleness of a graph $G$ as the minimum $\ell$ such that the vertex set of $G$ can be partitioned into sets inducing a subgraph in $\mathcal C$ and there are $\ell$ edges having ends in distinct parts. We characterize classes of graphs having bounded $\mathcal C$-edge-brittleness for a class $\mathcal C$ of forests or a class $\mathcal C$ of graphs with no $K_4\setminus e$ topological minors in terms of forbidden obstructions. We also define $\mathcal C$-vertex-brittleness of a graph $G$ as the minimum $\ell$ such that the edge set of $G$ can be partitioned into sets inducing a subgraph in $\mathcal C$ and there are $\ell$ vertices incident with edges in distinct parts. We characterize classes of graphs having bounded $\mathcal C$-vertex-brittleness for a class $\mathcal C$ of forests or a class $\mathcal C$ of outerplanar graphs in terms of forbidden obstructions. We also investigate the relations between the new parameters and the edit distance.
Semi-Greedy Construction of Oblique-Split Decision Trees

Classication and Regression Trees (CART) are a method of structured prediction widely used in machine learning. Favored for their robustness to non-linear relationships and interpretability (James, Witten, Hastie, & Tibshirani, 2013), they have seen continued application since their broad introduction in 1984 (Breiman, Friedman, Olshen, & Stone, 1984). The shortcomings of a single-tree model, especially overfitting and lack of competitiveness compared to other machine learning methods, have been overcome through advances in bagging, pruning, and boosting (James et al., 2013). Decision trees are fitted in a top-down, greedy fashion because non-greedy fitting is computationally intractable. While this leads to efficient computation, using top-down, greedy estimates can produce suboptimal models. To overcome this suboptimality I propose a semi-greedy method of decision tree construction. First, I reformulate the problem based on the work of Norouzi et. al. (2015)(Norouzi, Collins, Johnson, Fleet, & Kohli, 2015), and use an algorithm which optimizes the split functions at all levels of the tree jointly, based on a global objective. This algorithm is parameterized by a single scalar for which I propose a bound. Second, I propose a dimensionality reduction step for cases when the semi-greedy algorithm becomes intractable. In the five datasets tested (Breast Cancer Wisconsin, Banknotes Authentication, Haberman Survival Data, Blood Transfusion Data, Fertility Data), the algorithm produces higher accuracy than two existing greedy tree packages in R (rpart, tree). And, it is computationally tractable for low-width datasets (approximately 8 features or fewer). For higher order problems, I propose a preprocessing step which reduces the higher-width data to a more tractable subset. I show that a dimensionally reduced space, processed using the semi-greedy algorithm, outperforms the greedy methods (rpart, trees) trained with both full and reduced data sets.
Hotspots for Enhancing Quranic Speech Recognition

This paper discusses hotspots where minor changes in these spots can lead to significant changes in results. Speech recognition is a process with multiple stages and in each stage; there are spots to be enhanced. Recording principles and avoiding issues are essential steps. Collecting the relevant data or designing the data in such form or structure can enhance the training model. In addition, extracting phonemes using a smart acoustic model or using a robust language model tool are another important spots for improvement. Finally, using Deep Neural Network (DNN) as a speech recognition model has been proved to achieve very good results.
Refining Your Idea

A great idea with poor execution is a poor app, but a poor idea with excellent execution is a great app. This means that it matters far less what your app idea is, and far more that it's a well made app.