Miracle-dz/UniFAR-FTUs huggingface dataset:
Analytic search methods in online social networks

This thesis presents and evaluates methods for searching and analyzing social media data in order to improve situational awareness. We begin by proposing a method for network vertex search that looks for the target vertex by sequentially examining the neighbors of a set of “known” vertices. Using a dynamic programming approach, we show that there is always an optimal “block” search policy, in which all of the neighbors of a known vertex are examined before moving on to another vertex. We provide a precise characterization of the optimal policy in two specific cases: (1) when the connections between the known vertices and the target vertex are independent, and (2) when the target vertex is connected to at most one known vertex. We then apply this result to the problem of finding new accounts belonging to Twitter users whose previous accounts had been suspended for extremist activity, quantifying the performance of our optimal search policy in this application against other policies. In this application we use thousands of Twitter accounts related to the Islamic State in Iraq and Syria (ISIS) to develop a behavioral models for these extremist users. These models are used to identify new extremist accounts, identify pairs of accounts belonging to the same user, and predict to whom a user will connect when opening an account. We use this final model to inform our network search application. Finally, we develop a more general application of network search and classification that obtains a set of social media users from a specified location or group. We propose an expand—classify methodology which recursively collects users that have social network connections to users inside the target location, and then classifies all of the users by maximizing the probability over a factor graph model. This factor graph model accounts for the implications of both observed user profile features and social network connections in inferring location. Using geo-located data to evaluate our method, we find that our classification method typically outperforms Twitter’s native search methods in building a dataset of Twitter users in a specific location. Thesis Supervisor: John Irvine Title: Draper, Inc. Thesis Supervisor: Tauhid Zaman Title: KDD Professor
Chapter INTELLIGENT TUTORING SYSTEMS THAT ADAPT TO LEARNER MOTIVATION

This chapter provides an introduction to the topic of motivation from the point of view of those interested in the design or use of intelligent tutoring systems. To that end it introduces some of the complexities of motivational states and processes together with a range of motivational theories and their application in intelligent tutoring systems. The theories include learner beliefs about learning, including their goal orientation, their selfefficacy and their attributions of causality, as well as their academic emotions. It also introduces Keller’s work on the design of tutoring systems that puts motivation at the heart of that design process. The chapter describes six tutoring systems that have been designed to deal with the learner’s motivation, either as a one-off adaptation or dynamically. These six were chosen to cover a reasonably broad range of motivational theories and to cover the history of the field of motivationally adaptive intelligent tutoring systems from its start to the present day.
Improving American Sign Language Recognition with Synthetic Data

There is a need for real-time communication between the deaf and hearing without the aid of an interpreter. Developing a machine translation (MT) system be-tween sign and spoken languages is a multimodal task since sign language is a visual language, which involves the automatic recognition and translation of video images. In this paper, we present the research we have been carrying out to build an automated sign language recognizer (ASLR), which is the core component of a machine translation (MT) system between American Sign Language (ASL) and English. Developing an ASLR is a challenging task due to the lack of sufﬁcient quantities of annotated ASL-English parallel corpora for training, testing and developing an ASLR. This paper describes the research we have been conducting to explore a range of different techniques for automatically generating synthetic data from existing datasets to improve the accuracy of ASLR. This work involved experimentation with several algorithms with varying amounts of synthetic data and evaluations of their effectiveness. It was demonstrated that automatically creating valid synthetic training data through simple image manipulation of ASL video recordings improves the performance of the ASLR task.
C O ] 2 7 Ju l 2 01 9 Coloring rings

A ring is a graph R whose vertex set can be partitioned into k ≥ 4 nonempty sets, X1, . , Xk, such that for all i ∈ {1, . , k} the set Xi can be ordered as Xi = {u1i , . , u |Xi| i } so that Xi ⊆ NR[u |Xi| i ] ⊆ · · · ⊆ NR[u 1 i ] = Xi−1 ∪ Xi ∪ Xi+1. A hyperhole is a ring R such that for all i ∈ {1, . , k}, Xi is complete to Xi−1 ∪ Xi+1. In this paper, we prove that the chromatic number of a ring R is equal to the chromatic number of a maximum hyperhole in R. Using this result, we give a polynomial-time coloring algorithm for rings. Rings appeared as one of the basic classes in a decomposition theorem for a class of graphs studied by Boncompagni, Penev, and Vušković in [Journal of Graph Theory 91 (2019), 192–246]. Using our coloring algorithm for rings, we show that graphs in this larger class can also be colored in polynomial time. Furthermore, we obtain an optimal χ-bounding function for this larger class of graphs, and we also verify Hadwiger’s conjecture for it.
Construction of a Spatio-Temporal Face Atlas : Experiments Using Down Syndrome Samples

This work describes a method for constructing a spatio-temporal face atlas based on pairwise non-rigid registration and kernel regression in order to explicitly consider the craniofacial differences that could exist across the time due to the subjects growth. The whole pipeline includes the following steps: (a) Facial Landmarks Positioning; (b) Sample Group Equalization and Kernel Interpolation; (c) Registration; (d) Atlas Construction. Our experiments on Down Syndrome face images show that the method generates realistic and unbiased face atlases from toddlers to teens.
Similarity using Dense Vector Representation In cooperation with : XING AG Data Science

The purpose of this thesis is to analyze different document representation models for identifying similar job advertisements to improve the quality of job recommendations on XING, a social network for professionals. We test our algorithms both in an offline experiment as well as in an online evaluation. For offline experimentation, we present a method for automatically creating a training dataset based on user interactions. We experiment with different pre-processing techniques like lowercasing the input text and stemming which shows significant increase in performance. Moreover, we test four different word embedding techniques: average and weighted average of vectors using Word2Vec, Word2VecF using arbitrary context and Doc2VecC. Results show performance boost when a weighted average is used and both global and local context is included in the model training. We also analyze the performance of LDA and discover that it does not perform well on the dataset. The best results in the offline evaluation are achieved when exploiting more information like the job title along with the full job posting description. Titles are used for weighing the word vectors more accurately when building the vector representing the entire document. Finally, we implement and integrate the best performing model also in XING’s job recommendation system and conduct an online A/B test evaluation with Millions of XING users. The results from that online evaluation confirm our findings from the offline experimentation and lead to an +8.0% increase of the click-through rate on job recommendations.
An Exploration of Placeholding in Neural Machine Translation

Phrase-based machine translation provides the system developer with controls that enable ﬁne-grained control over machine translation output. One approach to provide similar control in neural machine translation is placeholding (herein called masking ), which replaces input tokens with masks which are replaced with the original input text in post-processing. But is this a good idea? We undertake an exploration of masking in French–English and Japanese–English using Transformer architectures. We attempt to quantify whether (and where) masking is necessary with analysis of a baseline system, and then explore numerous parameterization of masking, including post-processing techniques for re-placing the masks. Our analysis shows this to be a thorny matter; masks solve some problems but are not perfectly translated themselves.
A3-108 Machine Translation System for LoResMT 2019

In this paper, we describe our machine translation systems submitted to LoResMT 2019 Shared Task. Systems were developed for Bhojpuri, Magahi, Sindhi, Lat-vian ⇐⇒ (English). This paper outlines preprocessing , conﬁguration of the submitted systems and the results produced using the same.
Career-Decision Self-Efficacy among College Students with Symptoms of Attention Deficit Disorder

Compared to the general college population, students with attention deficit disorder (ADD) are less academically prepared with the skills to maintain college course requirements. This inadequacy is due to the change in academic structure, time management, and the skills required for higher education. I measured career-decision self-efficacy to assess college students’ abilities to accomplish tasks necessary to making career decisions, and a relationship emerged between students that self-reported increased symptoms of ADD and a decrease in career decision selfefficacy. Providing academic institutions with knowledge of how symptoms of ADD affects college students and their future career planning may assist advisors in providing students with services and treatment options to increase retention and career commitment.
Efficient Motion Planning for Intuitive Task Execution in Modular Manipulation Systems (Effiziente Bahnplanung und intuitive Aufgabenbeschreibung zur Erzeugung erwartungstreuen Verhaltens von Mehrrobotersystemen)

The design of complex systems in robotics requires modern engineering approaches and intuitive task descriptions. This work introduces an instruction paradigm that goes beyond typical programming interfaces and toward a more intuitive interaction style with a robot system. A newly developed motion planning algorithm avoids exhaustive exploration of configuration spaces and actively balances the exploitation of available information in order to achieve significant performance improvements compared to other state-of-the-art sampling-based planners. Accessible descriptions are realized by a combination of task-based control algorithms with multimodal interfaces and cognitive reasoning modules. Abstraction of kinematics, dynamics, geometry, and hardware aspects result in flexible systems with replaceable components. Reengineering between systems is reduced due to the development of an open source framework with common robotics algorithms.
Automated Conversion of Text Instructions to Human Motion Animation

x Chapter 1: Introduction . 1 1.1 Problem Statement . 1 1.2 Objectives . 1 Chapter 2: Literature Review . 2 2.1 Related Systems . 2 2.1.1 WordsEye . 2 2.1.2 Web2Animation. 2 2.1. 3 Xtranormal . 3 2.1. 4 CarSim . 3 2.1. 5 Real-Time Automatic 3D Scene Generator . 4 2.1. 6 Animated Storytelling System via Text. 4 2.1. 7 Constraint-Based Conversion of Text to Time-based Graphical Representation . 4 2.1. 8 Text Description to Animation Sequences . 4 2.1. 9 Text Generated TV . 5 2.1.10 Prototype Natural Language Interface for Animation Systems . 5 2.2 Animation Techniques . 6 2.2.1 Key-Frame . 6 2.2.2 Motion Capture . 6 2.2. 3 Procedural . 7 Chapter 3: Methodology . 8 3.1 Data Collection & Preprocessing . 8 3.2 Animation Graph . 13 3.3 Animation Collection . 14 3.3.1 3D Models . 14 3.3.2 Animations & Animation Clips . 15 3.4 Text-to-Animation Conversion System . 16 3.4. 1 Semantic Analysis . 16 3.4. 2 MatchScore . 16 3.4. 3 Animation Graph Search . 18
Prevalence of Double Burden of Malnutrition among Indian Pre-School Children : an Analysis of Cross-Sectional DLHS-4 Data from 23 States

Background: Double burden of malnutrition means co-existence of underand overnutrition in a community, household or an individual. It is observed in countries undergoing nutrition transition. Research on double burden among Indian children aged under five has been scarce. I therefore aim to study the prevalence of double burden of malnutrition in this age group. Methods: Cross-sectional population-based data from District Level Household and Facility Survey 4 conducted in 2012-2013 in 23 Indian States and Union Territories were used for the analysis. Prevalence of overweight, stunting and anaemia were examined as main outcomes at the community level. Simultaneous overweight and stunting or anaemia in same child were the main outcomes for individual level prevalence. Households with stunted child and overweight adult were also examined. Results: In this sample, 40.1 % of children were stunted, 74.2 % anaemic and 8.2 % overweight. Simultaneous overweight and stunting as well as overweight and anaemia both affected about 5.5 % of children. Stunted children had a higher prevalence of overweight than non-stunted children. No such association was seen for anaemia. At household level, 26.5 % of households had an overweight adult and a stunted child. Discussion: Double burden of malnutrition is emerging among Indian children aged under five and should be included in national nutrition policy. Undernutrition is still bigger concern than overnutrition, but overweight is spreading also to lower wealth quintiles. Further studies should be done to examine this phenomenon at the national level. UPPSALA UNIVERSITET 3 (58)
Suspicious Call Detection Using Bayesian Network Approach

The rapid advancements in the fast and rapidly growing field of information and communication technologies (ICT’s) has lead us to new thinking paradigm and it is being implemented in all walks of life including business, finance, health, management, engineering, basic sciences, sports, social sciences and many other domains. There are many advantages of speedy growth of internet and mobile phones in the society and people are taking full advantage of them. However this technology is widely used by the criminals for the execution of criminal or terrorist activities. The state of Pakistan is going through a period where they are crushing criminal and terrorist networks throughout the country. There are number of terrorist and criminal activities in the last few years. This study focuses on the use of related equipment like mobile phone, SIM’s etc. in criminal or terrorist activities. We have analyzed call detail records (CDR) collected from tower data of five mobile companies by using geo-fencing approach. The classification of suspicious call detection and identification is done by using Bayesian classifier approach. In the research document, the researcher exhibits approaches for establishing Bayesian systems from previous information and review Bayesian techniques for improvisation of these models. We encapsulate approaches for structuring and learning parameters in Bayesian system, including various methods to learn from Bayesian database
RQ 1 : Does the implementation of CSR rules lead to a reorganization of supply chain relationships ?

Corporate social responsibility has become a strategic asset for food firms to demonstrate their good environmental conduct. The aim of this paper is to investigate the role of the implementation of corporate social responsibility activities on the reorganization of vertical relationships within food supply chains. Applying content analysis techniques to the Global Reporting Initiative reports, we collected qualitative data on investments in environmentally friendly options, the adoption of standards, stakeholder engagement, information searches, impact monitoring activities and chain coordination to transform it into quali-quantitative data. We find that the variables affecting chain coordination relate to the presence of sourcing standards, effort in discussing with chain partners ways to prevent and manage chain environmental impacts, and costs related to stakeholder feedback collection. The results of the analysis confirm corporate social responsibility as a strategic tool to improve supply chain relationships through an augmented vertical coordination and to integrate environmental policy.
A Mixed Methods Analysis of the Adoption and Diffusion of Chatbot Technology in the German Insurance Sector Completed Research

In recent years, gradual improvements in information, computing, communication and connectivity technologies have enabled new technical possibilities for the adoption of Chatbots across diverse sectors. In the case of the insurance sector, the implementation of service innovations based on Chatbot technology can contribute, among other benefits, to improve the efficiency across the insurance value chain, reduce costs and generate customer loyalty and trust (Barrett et al., 2015; Ross et al., 2016). However, despite the advantages, the adoption success of Chatbot Technology depends on the understanding of the ambivalent perceptions, attitudes, and beliefs of the main social actors (i.e. practitioners and potential users) towards the customer interface. Using a mixed methods design based on an interpretive paradigm and within the frameworks of acceptance and diffusion research, we identified the “relative advantages” and “IS infrastructure” as the most critical ambivalent socio-technical factors for the adoption and diffusion of Chatbot technology in Germany.
The Term Structure of Interest Rates as a Random Field . Applications to Credit Risk

The principal aim of this paper is the modeling of the term structure of interest rates as a positive-valued random field. Special emphasis is given to chi-squared fields which can be generated from a finite number of Gaussian fields. In particular, we introduce a short rate model which is based on the square of an Ornstein-Uhlenbeck process. It is shown that bond prices can be expressed as an exponential-affine function of the short rate. We extend our approach to the credit risk area and model the default intensities of a class of obligors as a two-parameter positive-valued random field. Finally, random fields will be applied to the modeling of firm values in a structural credit risk framework.
Motion Frame Omission for Cartoon-like Effects

In this paper, we propose a simple method for automatically converting motion capture data to imitate the unique expressions of limited animation. Especially, we focus on the following two features related to motion timing; one is that limited animation does not show subtle motion because it omits almost-static inbetween frames. The other is that it exaggerates motion speeds by omitting inbetweens, which is called “nakanashi” in Japanese [2]. Given motion capture data, our method holds each pose up to three frames to reduce subtle motion while it also omits poses in fast motion to exaggerate the speed. The accompanying movie with animating cartoon characters demonstrates that our method can imitate the expressions of limited animation.
SLR 2000 C : AN AUTONOMOUS SATELLITE LASER RANGING AND SPACE-TO-GROUND OPTICAL COMMUNICATIONS FACILITY

The adaptation of NASA’s SLR2000 satellite laser ranging station to a dual mode ranging and optical communications terminal for space-to-ground links is discussed. The SLR2000C concept assumes multiple communications channels near 1550 nm, which allows the use of commercially available fiberoptic communications components. Preliminary link calculations suggest that the 40 cm aperture of SLR2000 would permit several Gbps downloads per channel from geosynchronous or lower Earth orbits and several tens of Mbps per channel from lunar orbit with nominal spaceborne transmitter powers on the order of a few watts. A ground network of approximately 25 SLR2000C stations coupled into a ground-based fiberoptic network would meet most of the foreseeable needs of “instantaneous” high data rate space-to-ground communications, including Earth-orbiting satellites and Deep Space missions. A simple space architecture based on four interlinked geosynchronous satellites (plus up to four additional satellites for polar coverage), would provide greater than 99% link availability and permit instantaneous transfer of data between an airborne or spaceborne remote sensing terminal and any point on the ground that is connected to the fiberoptic network. A single 10 cm diameter cube on each of the GEO satellites would provide adequate cross-section for the ranging link.
Monitoring Technology Acceptance for Banking Consumers in India

: August 15 th 1995 marked a new dawn in India’s communications history, when Videsh Sanchar Nigam Ltd (VSNL) then a state owned Telecom Company introduced commercial Internet services. Till then Internet connectivity was available to only select few researchers and government officials through the ERNET or NICNET networks. The research approach employed in this study is qualitative which is in line with our purpose of our study. The purpose of this study is to explore the relationship between technology enabled banking processes and its acceptance among Indian Consumers. This is due to the fact that, there is not much information since internet banking is still at its increasing stage. This descriptive as well as empirical research study would therefore provide us with much information and insight so as to get deeper understanding of the issue at stake. It would help us to explore the underlying facts relevant to online banking.
Smartphone as a Portable Detector, Analytical Device, or Instrument Interface

The Encyclopedia Britannia defines a smartphone as a mobile telephone with a display screen, at the same time serves as a pocket watch, calendar, addresses book and calcula tor and uses its own operating system (OS). A smartphone is considered as a mobile tele - phone integrated to a handheld computer. As the market matured, solid-state computer memory and integrated circuits became less expensive over the following decade, smart - phone became more computer-like, and more more-advanced services, and became ubiq uitous with the introduction of mobile phone networks. The communication takes place for sending and receiving photographs, music, video clips, e-mails and more. The grow ing capabilities of handheld devices and transmission protocols have enabled a growing number of applications. The integration of camera, access Wi-Fi, payments, augmented reality or the global position system (GPS) are features that have been used for science because the users of smartphone have risen all over the world. This chapter deals with the importance of one of the most common communication channels, the smartphone and how it impregnates in the science. The technological characteristics of this device make it a useful tool in social sciences, medicine, chemistry, detections of contaminants, pesticides, drugs or others, like so detection of signals or image.