Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraint-Based Type-Directed Program Synthesis Extended Report

We explore an approach to type-directed program synthesis rooted in constraint-based type inference techniques. By doing this, we aim to more efficiently synthesize polymorphic code while also tackling advanced typing features such as GADTs that build upon polymorphism. Along the way, we also present an implementation of these techniques in Scythe, a prototype live, type-directed programming tool for the Haskell programming language and reflect on our initial experience with the tool.
Protection in the Spatial and Transform Domain

In spite of the existence of watermarking technique for all kinds of digital data, most of the literature addresses the watermarking of still images for copyright protection and only some work is extended to video watermarking. Video watermarking is distinct from image watermarking, because there is more data available to both the attacker as well as to the watermarker. This additional data volume allows the payload to be more redundantly and reliably embedded.
Terminal Sliding Mode Control with Evolutionary Algorithms for Finite-Time Robust Tracking of Nonholonomic Systems ITC 1 / 47

This paper deals with utilizing a recursive fast terminal sliding mode control method for finite-time robust tracking in a class of nonholonomic systems described by an extended chained form of differential equations. To enhance the performance of the proposed method, the constrained parameters of the controller are exactly tuned using evolutionary algorithms such that the tracking error reaches zero in a short time while chattering is significantly reduced. A comparative study is also presented among the applied evolutionary algorithms, namely, differential evolution, bat optimization, cuckoo optimization and bacterial foraging optimization. Applying the proposed design method leads to a considerable reduction in convergence time of the states as well as the chattering phenomenon. It is shown that the method is robust against disturbance in the input of the system. Numerical simulations for a well-known nonholonomic system, i.e., wheeled mobile robot demonstrate effective improvement in the results compared with conventional terminal sliding mode control method.
Changes in Systemic Hemodynamics in Orthostasis in Patients With Long-Term Impairment of Consciousness

The purpose of the study: to study hemodynamic parameters and the degree of its orthostatic stability during verticalization in patients with long-term impairment of consciousness in post-comatose period of brain damage.Materials and methods. This study included 30 patients with long-term impairment of consciousness caused by severe brain damage (Group 1), 10 of whom were in a vegetative state (VS) and 20 patients had a minimally conscious state (MCS). A severe traumatic brain injury was the most frequent cause of long-term disorders of consciousness (53.3%), other causes were associated with severe disorders of cerebral circulation (13.4%) and following consequences: rupture of cerebral aneurysms (10%), or post-hypoxic brain damage (10%), or removal of brain tumors (13.3%). The second group was comprised of 24 patients with local neurological symptoms after cerebral circulation disorders. The third group included 40 healthy volunteers. Systemic hemodynamic parameters were monitored using a multifunctional monitor TFM 3040i (CNSystem Austria) . Blood pressure (BP), heart rate (HR), stroke volume (SV), cardiac output (CO), and total peripheral resistance (TPR) were measured in real time. The statistical analysis was carried out using the Statistica-10 software package.Results. 26 patients of the first group (86%) demonstrated satisfactory hemodynamic stability in the tilt test at 30° and 60°; 3 patients of this group presented signs of orthostatic hypotension and 1 patient developed postural orthostatic tachycardia syndrome (SPOT) when tilted by 30°. A comparative analysis of hemodynamic parameters in patients of the first and second groups did not demonstrate significant differences, except for significantly higher HR values and lower SV values in the first group. Parameters of systemic hemodynamics in the horizontal position were significantly different in healthy volunteers, and were characterized by higher SV and CO values and lower BP, HR and TPR values as compared to patients of groups 1 and 2.Conclusion. This study demonstrated a hypokinetic type of blood circulation in all patients with brain lesions; it was more severe in patients with long-term impaired consciousness after severe brain damage. The majority of patients in this group presented satisfactory orthostatic hemodynamic stability; different types of orthostatic disorders were found in 14% of cases. A passive orthostatic test (0—30—60°) applied in this study allowed to diagnose orthostatic disorders at a slight tilt up to the onset of clinical symptoms of brain hypoperfusion. This indicates the need for hemodynamic monitoring in the early stages of patients' verticalization.
Risk Assessment System for Anti-Phishing

Phishing attacks steal a user’s identity data and financial account credentials using social engineering and technical spoofing techniques. Many counter measures have been developed to protect user’s sensitive information from phishing attacks. Although most approaches use both website black lists (WBLs) and website white lists (WWLs), these approaches have several weakneksses. This paper presents a novel anti-phishing Website Risk Assessment System (WRAS). WRAS computes a security risk index of website and generates warnings as to the website trustworthiness. Therefore, it can protect inexperienced users against spoofed website-based phishing attacks and exploit-based phishing attempts that may occur from legitimate web pages.
UvA-DARE ( Digital Academic Repository ) Pitching Emotions The Interpersonal Effects of Emotions in Baseball

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32 15 v 3 [ cs . C L ] 1 4 D ec 2 01 4 Sequence to Sequence Learning with Neural Networks

Deep Neural Networks (DNNs) are powerful models that have ac hieved excellent performance on difficult learning tasks. Although DNNs work well whenever large labeled training sets are available, they cannot be us ed to map sequences to sequences. In this paper, we present a general end-to-end ap proach to sequence learning that makes minimal assumptions on the sequence str ucture. Our method uses a multilayered Long Short-Term Memory (LSTM) to map the input sequence to a vector of a fixed dimensionality, and then another deep LS TM to decode the target sequence from the vector. Our main result is that on an English to French translation task from the WMT’14 dataset, the translations produced by the LSTM achieve a BLEU score of 34.8 on the entire test set, where the L STM’s BLEU score was penalized on out-of-vocabulary words. Additiona lly, the LSTM did not have difficulty on long sentences. For comparison, a phraseb d SMT system achieves a BLEU score of 33.3 on the same dataset. When we used the LSTM to rerank the 1000 hypotheses produced by the aforementione d SMT system, its BLEU score increases to 36.5, which is close to the previous b est result on this task. The LSTM also learned sensible phrase and sentence rep resentations that are sensitive to word order and are relatively invariant to t he active and the passive voice. Finally, we found that reversing the order of the words in all source sentences (but not target sentences) improved the LSTM’s pe rformance markedly, because doing so introduced many short term dependencies be tween the source and the target sentence which made the optimization problem easier.
A Survey Paper on Different Steganography Technique

With the rapid advance in digital network, information technology, digital libraries, and particularly World Wide Web services, many kinds of information could be retrieved any time. So in this digital scenario invisible communication between two parties is the prime concern. Steganography is the technique of hidden communication. It not only hides the message contents, instead it hides the existence of the message. In this paper, a new image steganography method based on spatial domain is proposed secret data hided in image segments using least significant bit (LSB) steganography is proposed. The color image is divided into four equal parts and the secret data is also divided into four equal parts and those divided data is hided in the image segments using least significant bit steganography. In this paper we have critically analyzed various steganographic techniques and also have covered steganography overview its major types, classification, applications.
Design and Evaluation of Mobile Interfaces for an Aging Population

The design and evaluation of mobile interfaces for older adults are becoming more important as the population ages and their use of technology increases. Current design strategies, which are used to guide the design of mobile interfaces, are either not primarily developed for mobile platforms or are not focused on the aging population with diverse limitations. Adaptation and integration of the existing strategies were necessary to create an inclusive and comprehensive set of guidelines for interactive mobile interfaces for older adults. The paper presents an overview of the Universal Design Mobile Interface Guidelines (UDMIG) and the related evaluation checklist. UDMIG v.2. 1 and the evaluation checklist were developed to ensure usability of future mobile technologies by older adults through a universal design strategy that accommodates all users to the greatest extent possible. This paper contributes to human-computer interaction research by including this population of users and advancing the technology uses for the mobile touchscreen interfaces for aging population. Keywords-aging; design; evaluation; mobile interfaces.
Abstract An Error Correction Neural Network for Stock Market Prediction

An Error Correction Neural Network for Stock Market Prediction Mhlasakululeka Mvubu Department of Mathematical Sciences, University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa. Thesis: MSc April 2019 Predicting stock market has long been an intriguing topic for research in different fields. Numerous techniques have been conducted to forecast stock market movement. This study begins with a review of the theoretical background of neural networks. Subsequently an Error Correction Neural Network (ECNN), Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) are defined and implemented for an empirical study. This research offers evidence on the predictive accuracy and profitability performance of returns of the proposed forecasting models on futures contracts of Hong Kong’s Hang Seng futures, Japan’s NIKKEI 225 futures, and the United State of America S&P 500 and DJIA futures from 2010 to 2016. Technical as well as fundamental data are used as input to the network. Results show that the ECNN model outperforms other proposed models in both predictive accuracy and profitability performance. These results indicate that ECNN shows promise as a reliable deep learning method to predict stock price. ii Stellenbosch University https://scholar.sun.ac.za
An algorithm for computing the minimum pure-strategy payoffs in repeated games

This paper presents a method for computing the minimum purestrategy subgame-perfect equilibrium payoffs in repeated games. These optimal punishments play an important role as they provide the players’ credible threats and the required incentives to stay on the equilibrium path of play. The algorithm is based on the idea of branch-and-bound, and it produces lower and upper bounds for the minimum payoffs. The optimal punishment paths may be long in general and finding them is a difficult computational problem. It is also shown that approximations of bounded length can be obtained by relaxing either feasibility or optimality.
Independent Offset Wheel Steering: An Improved Approach to Wheeled Mobile Robot Locomotion

In this paper, a new wheel configuration for mobile robot locomotion called IWOS (Independent Wheel Offset Steering) is presented. This approach offers quasiomnidirectionality, collision detection and mitigation, expressive navigation capabilities with a simple mechanical design. First, an overall study of popular wheel designs and configurations is provided and then a detailed explanation of IWOS as well as it’s distinct advantages are given. A proof of concept is shown using the physics simulation (GazeboSim) simulating various scenarios.
745 ) Details Type : Bug Status : CLOSED Priority : Major Resolution : Complete Affects

Many automated tasks in software maintenance rely on information retrieval (IR) techniques to identify specific information within unstructured data. Bug localization is such a typical task, where text in a bug report is analyzed to identify file locations in the source code that can be associated to the reported bug. Unfortunately, despite the promising results reported in the literature, the performance offered by IR-based bug localization tools is still not significant for large adoption. We argue that one reason could be the attempt by the community to build a “one-size-fits-all” approach for bug localization, without fully addressing the differences of available information that may exist among the bug reports and across the project source code files. In this paper, we first extensively study the performance of state-of-the-art bug localization tools, specifically focusing on investigating the query formulation (i.e., which bug report features should be compared against which features of source code files) and its importance with respect to the localization performance. Building on insights from this study, we propose a new learning approach where multiple classifier models are trained on clear-cut sets of bug-location pairs. Concretely, we apply a gradient boosting supervised learning approach to various sets of bug reports whose localizations appear to be successful with specific types of features. The training scenario builds on our findings that the various state-of-the-art localization tools (hence the associated similarity features that they leverage) can be highly performant for specific sets of bug reports. We implement D&C, a multi-classifier approach, which computes appropriate weights that should be assigned to the similarity measurements between pairs of information token types (the bug report and source code). Experimental results on large and up-to-date datasets reveal that D&C outperforms state-of-the-art tools. On average, the validation experiments yield an MAP score of 0.52, and an MRR score of 0.63 with a curated dataset. Comparison against the state-of-the-art shows that D&C provides a substantial performance improvement of MAP and MRR over all tools: MAP is improved by between 4 and up to 10 percentage points, while MRR is improved by between 1 and up to 12. Finally, we note that D&C is stable in its localization performance: around 50% of bugs can be located at Top1, 77% at Top5 and 85% at Top10.
Stratified ( L , M )-semiuniform convergence tower spaces

The notion of stratified (L,M)-semiuniform convergence tower spaces is introduced, which extends the notions of probabilistic semiuniform convergence spaces and lattice-valued semiuniform convergence spaces. The resulting category is shown to be a strong topological universe. Besides, the relations between our category and that of stratified (L,M)filter tower spaces are studied.
Taking Competition to the System Level: Entry Incentives, Market Convergence, and Sticky Prices

Firms in many industries increasingly compete by offering systems of complementary product components. We develop a formal model to examine under what conditions incumbent companies benefit from becoming a system integrator instead of only offering complementary product components. By expanding product scope and taking competition to the system level, an incumbent firm may strengthen its own competitive position, even though this results in reduced overall industry profit. We also analyze under what conditions system competition creates entry opportunities for newcomers. We find that weak competition facilitates the entry of new firms, while fierce competition provides strong incentives for incumbents to move first in offering integrated products. Finally, we also show how sticky prices for component products reduce incumbents’ incentives to compete on the system level, while making entry for newcomers more attractive. Our results provide new insights on the ’attacker’s advantage’ in technological competition. JEL Codes: L11, L13, O33
Multi-Data Correlation in Papillary Thyroid Cancer THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By

ii Dedication . iii Acknowledgments. iv Vita . v List of Tables . vii List of Figures . viii Chapter 1: Introduction . 1 Part A: Thyroid Cancer . 1 Part B: Feature Extraction . 3 Chapter 2: Materials and Methods . 5 Chapter 3: Results . 16 Chapter 4: Conclusions . 22 References . 25 Appendix A: Last Twenty Years of Published Results. 29
The Dynamics of Entrepreneurial, Strategic and Network Based Factors in the Formation of R&D Intensive Entrepreneurial Born Global Firms

The nature of the knowledge based entrepreneurship relates to its essential reliance on R&D, deployment and maximization of R&D returns via technology solution development, and its commercialization via venturing. From the small country perspective, R&D globalization, speed of new technology development, the need to deal with extremely complex conditions in searching and exploiting market, institutional and technological opportunities, the need to exploit R&D resources and their return globally leads to the formation of born global R&D driven entrepreneurial firms. The paper aims to provide the empirically grounded framework for analysing the key internal determinants leading to the formation of R&D intensive entrepreneurial born global firm with a special focus on entrepreneurial firm and network theories rather than only on early internationalisation of the firm. The paper argues that born global firm as a specific form of entrepreneurial firm occur via linking entrepreneurial, strategy and network factors, and are strategically designed to be global from scratch. Qualitative data analysis allowed to extract essential factors and specific combinations that lead to the drivers patterns of R&D intensive entrepreneurial born global development. The multi-case study disclosed that entrepreneurial factors act as a starting and independent variable impacting strategy, while network is formed as a strategically intended resource for the firm. Moreover, distinctive behavioural patterns were observed revealing the ways network is used as a critical resource for exploitation of knowledge in the global market place.
Donau-Auen National Park , Lower Austria

Xylobiontic beetles represent a substantial fraction of the biodiversity of forest ecosystems and are useful bioindicators for evaluating effects of forest management measures. This study was conducted in the Donau-Auen National Park in Lower Austria, one of the largest remaining semi-natural floodplain forests in Central Europe. There, for five months in summer 2012, beetles were sampled using flight interception traps, a widely used method for inventorying the fauna of wood inhabiting beetles. The aims of the study were to investigate the differences of xylobiontic beetle assemblages between two forest strata (understory and canopy) and the possible effects of an abruptly increased volume of fresh dead wood on them. The dead wood originated from the neophytic Box Elder (Acer negundo), that is becoming more and more widespread in riparian landscapes, and was girdled or felled at several locations in the national park to prevent a further dispersal. At five sites where such control measures had been applied beetles were sampled with one flight interception trap in the understorey and one in the canopy, the same was done at five reference sites without management. In total, 267 species of xylobiontic beetles (of 49 families) were recorded. Species richness, total abundance and also the composition of beetle assemblages differed significantly between forest strata. Total abundance was higher in the understorey, whereas species richness was higher in the canopy. There is no evidence however for an effect of the control measures on box elder on either total abundance, species richness or the composition of assemblages. The distribution of the functional groups of xylobiontic beetles seems to correlate neither with stratum nor with site type. The complete lack of an influence of the newly available dead wood material on xylobiontic beetle assemblages can be accounted for by the following factors: for one thing the time lag between implementation of control measures and sampling (less than one year) may have been too short for beetles to react, or the neophytic origin of the dead wood made it unsuitable for autochthonous beetle species.
Equivalence classes of permutations modulo excedances 455

Let Sn be the set of permutations of length n, i.e., all one-to-one correspondences from [n] = {1, 2, . , n} into itself. The one-line notation of a permutation π ∈ Sn is π1π2 · · ·πn where πi = π(i) for i ∈ [n]. A cycle in Sn is a n-length permutation π such that there exist some indices i1, i2, . , in with π(i1) = i2, π(i2) = i3, . , π(in−1) = in and π(in) = i1. According to the context, a cycle will be also denoted by its cyclic notation π = 〈i1, i2, . , in〉. Let Cn ⊂ Sn be the set of all cycles of length n. Let π be a permutation in Sn. An excedance of π is a position i, 1 ≤ i ≤ n, such that π(i) > i. The set of excedances of π will be denoted E(π). For instance, if π = 4 1 6 3 5 7 2 then E(π) = {1, 3, 6}. The graphical representation of π is the set of points in the plane at coordinates (i, πi) for i ∈ [n]. We define its associated rook placement R(π) on the triangular board consisting of the cells located atop the diagonal y = x in the graphical representation of the permutation. For short, R(π) will be called excedance board of π. Obviously, a point (i, πi) appears in the excedance board of π if and only if i is an excedance of π. See Figure 1 for the graphical representation of a permutation with its associated excedance board. We consider the equivalence relation ∼ on Sn in which two permutations π and σ are considered to be equivalent if they coincide on their excedance sets, i.e., E(π) = E(σ) and π(i) = σ(i) for i ∈ E(π), or again π and σ have the same excedance board. Let Eq(π, Sn) denote the set of permuta-
Adomain Sumudu Transform Method for the Blasius Equation

This paper presents a new method namely, Adomain Sumudu Transform Method, a coupling of the Sumudu transform and Adomain decomposition method, for handling a differential equation of mixing layer that arises in viscous incompressible fluid. In order to apply the condition at infinity, we converted the obtained series solution into rational function by using Padé approximant.