Reviewerly/exHarmony huggingface dataset:
Eccentricities via Parallel Set Cover (Brief Announcement)

The eccentricity of a node in a graph G(V,E) is its maximal shortest-path distance to any other node. Shun (KDD 2015) suggested a simple heuristic for computing all eccentricities in an input graph, based on two-phase parallel BFS from a small sample of nodes. It was shown to outperform state-of-the-art algorithms by up to orders of magnitude. This empirical success stands in apparent contrast to recent theoretical hardness results on approximating all eccentricities (Backurs et al., STOC 2018). This note aims to formally explain the performance of this heuristic, by drawing a connection to the streaming Set Cover algorithm of Demaine et al. (DISC 2014). We use it to suggest a variant with similar work and depth bounds, which is guaranteed to compute almost all eccentricities exactly, if the graph satisfies a condition we call small eccentric periphery. The condition can be ascertained for all real-world graph used in Shun (KDD 2015) and in our experiments. Experimental results demonstrate the validity of the analysis and the empirical advantage of our proposed variant.
Publishing with Open Journal Systems(OJS): Sensitization Workshop

A presentation at KLISC Pre-AGM workshop held at MasindeMuliroUniversity of Science and Technology (MMUST) on 30thMay 2019
Isolation Kernel: The X Factor in Efficient and Effective Large Scale Online Kernel Learning

Large scale online kernel learning aims to build an efficient and scalable kernel-based predictive model incrementally from a sequence of potentially infinite data points. A current key approach focuses on ways to produce an approximate finite-dimensional feature map, assuming that the kernel used has a feature map with intractable dimensionality---an assumption traditionally held in kernel-based methods. While this approach can deal with large scale datasets efficiently, this outcome is achieved by compromising predictive accuracy because of the approximation. We offer an alternative approach which overrides the assumption and puts the kernel used at the heart of the approach. It focuses on creating an exact, sparse and finite-dimensional feature map of a kernel called Isolation Kernel. Using this new approach, to achieve the above aim of large scale online kernel learning becomes extremely simple---simply use Isolation Kernel instead of a kernel having a feature map with intractable dimensionality. We show that, using Isolation Kernel, large scale online kernel learning can be achieved efficiently without sacrificing accuracy.
Towards Interpretable Deep Extreme Multi-label Learning

Many Machine Learning algorithms, such as deep neural networks, have long been criticized for being "black-boxes"-a kind of models unable to provide how it arrive at a decision without further efforts to interpret. This problem has raised concerns on model applications' trust, safety, nondiscrimination, and other ethical issues. In this paper, we discuss the machine learning interpretability of a real-world application, eXtreme Multi-label Learning (XML), which involves learning models from annotated data with many pre-defined labels. We propose a two-step XML approach that combines deep non-negative autoencoder with other multi-label classifiers to tackle different data applications with a large number of labels. Our experimental result shows that the proposed approach is able to cope with many-label problems as well as to provide interpretable label hierarchies and dependencies that helps us understand how the model recognizes the existences of objects in an image.
ANALYSIS OF THE ENGLISH-LANGUAGE SLOGANS USED BY HIGHER EDUCATION INSTITUTIONS IN WEST JAVA

This study analyzes the English-language slogan used by higher education institutions in West Java. The purpose of this study is to describe the linguistic patterns and to describe the substance contained in the slogans. This research used descriptive method in analyzing data since it was aimed to get a picture of the use of slogans in higher education institutions. The data were 63 English-language slogans of higher education institutions in West Java with the official web pages and electronic brochures on the Internet as data resources. This study shows that the English-language slogans used by higher education institutions in West Java consist of phrases and sentences. These phrases are noun phrase (41 or 64% slogans), gerund phrase (6 or 9.2 % slogans), verb phrase (4 or 6.3% slogans), prepositional phrase (3 or 4.7% slogans), and infinitive phrase (1 or 1.5% slogan). Meanwhile, the types of the sentence are declarative sentence (8 or 12.5 % slogans) and imperative sentences (1 or 1.5% slogans). This study also shows that there are 13 slogans (20.9%) which contain goal, 49 (77.8%) slogans which contain ideology, and 1 (1.6%) slogan which contains both goal and ideology.
Configuration-Space Flipper Planning for Rescue Robots

For rescue robots, flipper endows the robot with additional ability to pass through various terrain. Autonomous motion becomes more important. In recent work autonomy is done by either planning with several special states or based on collected data. We are considering if it is possible to find a way to build continues states without collecting old trail data. In this paper, we first model the possible states as a global planning path with parameter configuration of the scene. Then, we follows the path to achieve the autonomous run. We plot the morphology of each path points to show the correctness of the path and implement a simple path following on real robot to demonstrate the performance of our algorithm.
A Semantic Ontology of Danish Adjectives

This paper presents a semantic annotation scheme for Danish adjectives, focusing both on prototypical semantic content and semantic collocational restrictions on an adjective's head noun.The core type set comprises about 110 categories ordered in a shallow hierarchy with 14 primary and 25 secondary umbrella categories.In addition, domain information and binary sentiment tags are provided, as well as VerbNet-derived frames and semantic roles for those adjectives governing arguments.The scheme has been almost fully implemented on the lexicon of the Danish VISL parser, DanGram, containing 14,000 adjectives.We discuss the annotation scheme and its applicational perspectives, and present a statistical breakdown and coverage evaluation for three Danish reference corpora.
New Code-Based Privacy-Preserving Cryptographic Constructions.

Code-based cryptography has a long history but did suffer from periods of slow development. The field has recently attracted a lot of attention as one of the major branches of post-quantum cryptography. However, its subfield of privacy-preserving cryptographic constructions is still rather underdeveloped, e.g., important building blocks such as zero-knowledge range proofs and set membership proofs, and even proofs of knowledge of a hash preimage, have not been known under code-based assumptions. Moreover, almost no substantial technical development has been introduced in the last several years.
Faktor-Faktor Yang Mempengaruhi Kesediaan Petani Dalam Membayar Jasa Lingkungan Air Padi Sawah

The Air Sarap Sub-watershed is a sub-watershed located in Samadua Subdistrict, South Aceh Regency, where water from the Air Sarap Sub-watershed has been used for domestic household needs and rice field water supply needs. The impact of forest encroachment and land conversion on upstream sub-watersheds causes droughts in the dry season and floods in the rainy season, where floods that come in the rainy season destroyed most community infrastructure, such as houses, roads, bridges and agricultural irrigation which provide supply community wetland water. This research aims to analyze and determine factors that influence rice field farmers in paying for environmental services in the Air Sarap Sub-watershed which has been functioning as a water supplier in lowland rice farming
Method of continuous improvement of multidisciplinary programs and outreach activities

The growth of the global photonics market and technology investment creates a need for skilled professionals with multidisciplinary knowledge. The development of a successful multidisciplinary training for these professionals requires special attention to the implemented educational approaches. Current methods of multidisciplinary teaching and learning include tutoring by a team of experts of different backgrounds and development of projects among multidisciplinary teams of students. In these cases, a detailed feedback is needed from students and teachers in order to improve the course and keep a consistent alignment among the learning outcomes, teaching strategy, and evaluation methods. In this study, we describe the implementation of a method based on continuous improvement of multidisciplinary outreach activities and undergraduate programs. We illustrate the results of this implementation by showing samples of the feedback we received from students and teachers. The overall quality of the teaching and the content of the subject matter was perceived as good by students. Teachers’ evaluation showed students’ knowledge and behavior was satisfactory and the learning outcomes were achieved. Based on this, we believe our educational approach could improve the development and implementation of multidisciplinary activities.
Ways of Formation of Professional Competences of Students of Pedagogical Higher Education Institutions

Today, in various branches of psychological and pedagogical knowledge, competences are characterized as constituent units of educational programs that define the requirements for the development of knowledge and skills of graduates of higher educational institutions. In this regard, higher education institutions are faced with the task of forming key competencies that lead to the concept of “professional competence”. The purpose of this article is to describe the components of its competence and to determine the didactic conditions for their formation in relation to the training of future teachers in the university. The urgent need to clarify the key competencies included in the concept of “professional competence” led to a search for its components: the authors of the proposed article determine their characteristics based on the decisions of the Council of Europe symposium on the topic “Key competencies for Europe” in which this list is marked. Today, the modeling of a teacher’s professional characteristics is perceived as a didactic condition for his university development, designed to reflect the epistemological, perceptual, constructive, organizational, communicative, informational, adaptive levels of the teacher. It seems quite reasonable that the study of the correlation of these competencies in the model being developed with the activity of a particular teacher will allow determining the degree of his professional competence. The authors of the article prepared for publication and tested in the conditions of the university teaching aids, in which the competence approach is clearly expressed. The leading idea of the study is to use the potential of integrated approaches to the formation of key competencies of a future teacher in terms of credit technology as an instrument that stimulates students' interest and desire to understand the ways of forming professional competence of a future specialist who has constructive thinking and has a level of training that meets the requirements .
Improving Action Localization by Progressive Cross-stream Cooperation

Spatio-temporal action localization consists of three levels of tasks: spatial localization, action classification, and temporal segmentation. In this work, we propose a new Progressive Cross-stream Cooperation (PCSC) framework to use both region proposals and features from one stream (i.e. Flow/RGB) to help another stream (i.e. RGB/Flow) to iteratively improve action localization results and generate better bounding boxes in an iterative fashion. Specifically, we first generate a larger set of region proposals by combining the latest region proposals from both streams, from which we can readily obtain a larger set of labelled training samples to help learn better action detection models. Second, we also propose a new message passing approach to pass information from one stream to another stream in order to learn better representations, which also leads to better action detection models. As a result, our iterative framework progressively improves action localization results at the frame level. To improve action localization results at the video level, we additionally propose a new strategy to train class-specific actionness detectors for better temporal segmentation, which can be readily learnt by focusing on "confusing" samples from the same action class. Comprehensive experiments on two benchmark datasets UCF-101-24 and J-HMDB demonstrate the effectiveness of our newly proposed approaches for spatio-temporal action localization in realistic scenarios.
Can Unconditional Language Models Recover Arbitrary Sentences?

Neural network-based generative language models like ELMo and BERT can work effectively as general purpose sentence encoders in text classification without further fine-tuning. Is it possible to adapt them in a similar way for use as general-purpose decoders? For this to be possible, it would need to be the case that for any target sentence of interest, there is some continuous representation that can be passed to the language model to cause it to reproduce that sentence. We set aside the difficult problem of designing an encoder that can produce such representations and, instead, ask directly whether such representations exist at all. To do this, we introduce a pair of effective, complementary methods for feeding representations into pretrained unconditional language models and a corresponding set of methods to map sentences into and out of this representation space, the reparametrized sentence space. We then investigate the conditions under which a language model can be made to generate a sentence through the identification of a point in such a space and find that it is possible to recover arbitrary sentences nearly perfectly with language models and representations of moderate size without modifying any model parameters.
A Quantum-inspired Similarity Measure for the Analysis of Complete Weighted Graphs

We develop a novel method for measuring the similarity between complete weighted graphs, which are probed by means of discrete-time quantum walks. Directly probing complete graphs using discrete-time quantum walks is intractable due to the cost of simulating the quantum walk. We overcome this problem by extracting a commute-time minimum spanning tree from the complete weighted graph. The spanning tree is probed by a discrete time quantum walk which is initialised using a weighted version of the Perron-Frobenius operator. This naturally encapsulates the edge weight information for the spanning tree extracted from the original graph. For each pair of complete weighted graphs to be compared, we simulate a discrete-time quantum walk on each of the corresponding commute time minimum spanning trees, and then compute the associated density matrices for the quantum walks. The probability of the walk visiting each edge of the spanning tree is given by the diagonal elements of the density matrices. The similarity between each pair of graphs is then computed using either a) the inner product or b) the negative exponential of the Jensen-Shannon divergence between the probability distributions. We show that in both cases the resulting similarity measure is positive definite and therefore corresponds to a kernel on the graphs. We perform a series of experiments on publicly available graph datasets from a variety of different domains, together with time-varying financial networks extracted from data for the New York Stock Exchange. Our experiments demonstrate the effectiveness of the proposed similarity measures.
An Embedding Framework for Consistent Polyhedral Surrogates

We formalize and study the natural approach of designing convex surrogate loss functions via embeddings, for problems such as classification, ranking, or structured prediction. In this approach, one embeds each of the finitely many predictions (e.g.\ rankings) as a point in $\mathbb{R}^d$, assigns the original loss values to these points, and "convexifies" the loss in some way to obtain a surrogate. We establish a strong connection between this approach and polyhedral (piecewise-linear convex) surrogate losses. Given any polyhedral loss $L$, we give a construction of a link function through which $L$ is a consistent surrogate for the loss it embeds. Conversely, we show how to construct a consistent polyhedral surrogate for any given discrete loss. Our framework yields succinct proofs of consistency or inconsistency of various polyhedral surrogates in the literature, and for inconsistent surrogates, it further reveals the discrete losses for which these surrogates are consistent. We show some additional structure of embeddings, such as the equivalence of embedding and matching Bayes risks, and the equivalence of various notions of non-redudancy. Using these results, we establish that indirect elicitation, a necessary condition for consistency, is also sufficient when working with polyhedral surrogates.
Combining Sequential Gaussian Simulation and Fractal Analysis for Mapping of Cu Concentration in Haftcheshmeh Porphyry Copper Deposit

In this paper a hybrid approach of Sequential Gaussian Simulation (SGSIM) and Concentration-Volume (C-V) fractal method was applied to boreholes data for classification of major geochemical parameters and associated features with alteration zones of the Haftcheshmeh Cu deposit in NW of Iran. Thereupon, Cu parameters were detected with higher efficiency and lower uncertainty. The purpose is also extended to delineate the alteration zones pertinent to Cu mineralization. Firstly, the most straightforward simulation (SGSIM) was utilized for projecting different lithogeochemical parameters of Cu. Then the C-V fractal model was used to discriminate these parameters by thresholds, obtained from the C-V Log-Log plot. The Fractal based resulting maps of 10 realizations and their E-type indicate their association with potassic alteration that has imposed on porphyry granodiorite. Moreover, these maps illustrate that the boreholes (1, 9, 23, and 31) at about longitudes of 643400 to 643800 are more promising than others. This fact explicitly had been correlated with reality of the studied area and denoted in its primary surface map. The results based on SGSIM, C-V confirmed enhanced mineralization in three-dimensional maps of the Haftcheshmeh deposit as a powerful combined method that can be used to detect the similar ore zones in continuation of the ore roots in adjacent areas.
Topological quantum walks in cavity-based quantum networks

We present a protocol to implement discrete-time quantum walks and simulate topological insulator phases in cavity-based quantum networks, where the single photon is the quantum walker and the cavity input-output process is employed to realize the state-dependent translation operation. Different topological phases can be simulated through tuning the single-photon polarization rotation angles. We show that both the topological boundary states and topological phase transitions can be directly observed via measuring the final photonic density distribution. Moreover, we also demonstrate that these topological signatures are quite robust to practical imperfections. Our work opens a new prospect using cavity-based quantum networks as quantum simulators to study discrete-time quantum walks and mimic condensed matter physics.
MODEL OF THE PROCESS OF FUNCTIONING OF THE INFORMATION PROTECTION SYSTEM FROM UNAUTHORIZED ACCESS CREATED IN THE SOFTWARE ENVIRONMENT OF IMITATION MODELING "CPN TOOLS"

Objectives . At present, conducting a computational experiment on a system for protecting information from unauthorized access operated in an automated system is a time consuming process. The greatest difficulty in this area of research is the determination of probabilistic-temporal characteristics and the formation of reports during the operation of the information protection system. In order to analyze, obtain and study the probabilistic-time characteristics of this system, it is necessary to develop a mathematical model of its operation using an imitational modeling tool. Method. One of the methods for solving this problem is a computational experiment, which is based on the construction of a simulation model. The CPN Tools environment was chosen as a software simulation product, the main advantages of which are: a high level of visualization, the ability to generate various reports on the system operation, fast modifiability of models for solving a different class of problems, as well as integration with other software means for the formation of graphical dependencies. Result. A simulation model of the system for protecting information from unauthorized access in the “CPN Tools” software environment was developed. protected performance. Conclusion. The presented im-model model of protecting information from unauthorized access in the software environment “CPN Tools” can be used as a tool in assessing the security of special bodies for the attestation of informatization objects and structural divisions of authorized departments. It can also be used in the design of such systems in order to prevent logical errors, determine their temporal characteristics and compare with the existing ones in accordance with the technical specifications for the system being developed to protect information from unauthorized access.
Discovery Education Transformative Professional Development Model in Egypt: A phenomenological study

I would like to extend my sincere gratitude to Dr. Heba El Deghaidy, the research supervisor, for her dedicated assistance, advice, inspiration, encouragement and continuous support. Her guidance and feedback have been invaluable instructional moments for me to research more and acquire consolidated knowledge at its best. Her belief in the strength of my thesis, keenness to produce high-quality work, and her recognition of my abilities to work out the study challenges have been highlights of a great instructional and inspirational leader. I would like to express my deepest appreciation to my esteemed research readers Dr. Thomas Wolsey and Dr. Teklu Abate whose depth of knowledge, profound feedback, insightful suggestions and constructive comments have been ingenious and helpful contributions.I also take pride in acknowledging and appreciating the privilege of learning at the hands of prolific professors like Dr. Malak Zaalouk, Dr. Russanne Hozayin, Dr. Nagawa Megahed, Dr. Gehan Osman, Dr. Mustafa Toprak, Dr. Nasser Mansour, Dr. Heba Kotb , Dr. Jennifer Skaggs, along with Dr. Heba El Deghaidy and Dr. Teklu Abate. My special words of thanks should also go to Ms. Dena Riad for her usual assistance and continuous support. Special thanks go to Ashraf Magdd, Emily Waters and Andrew Tideswell for their understanding and encouragement.This thesis would not have been possible without my family’s unwavering and unselfish love and support at all times. Loads of thanks to my wife and my two kids for bearing with me in difficult moments, and for their sacrifices.
Correction to: User Behaviour-Based Mobile Authentication System

In the original version of the book, the following belated corrections are to be incorporated.