Miracle-dz/UniFAR-FTUs huggingface dataset:
Does innovation need reanalysis

Syntactic reanalysis has been claimed to be the only mechanism capable of explaining syntactic change. However, the concept of syntactic reanalysis is flawed. It insufficiently accommodates gradience in synchronic grammar and in language change, and depends too heavily on ambiguity as a cause of change. Alternative mechanisms exist to account for innovation that do not suffer from these problems. At the same time, the problem of explaining syntactic innovations is partly tied to models of language that overstate the role of syntax. Part of the problem therefore disappears under different theoretical starting assumptions.
Can the Essential Lexicon of Geology be Appropriately Represented in an Intuitively Written EAP Module

This study aimed to find out to what extent an intuitively developed ESP module for Science majors, taught at Sultan Qaboos University is appropriately written in terms of lexicon when compared to a core Geology textbook. The module was developed based on key topics which appeared in the Geology textbook. This study will only be evaluating vocabulary and will not be looking at other aspects of material evaluation. The digitized pages of the Module (LANC 2050) and the Essentials of Geology Textbook were loaded into the Software of WordSmith 5.0 for analysis. The results revealed low percentage word coverage in the module as compared with the limited pedagogical word list that was developed for Geology. In addition, the high density and low consistency ratios for the module as compared to the textbook indicated the compactness of the module for teaching purposes. A very low percentage of the technical words that were related to Geology was discovered in the Module (LANC 2050).
Coding performance on generalized fading channels

The author presents the uncoded and coded performance results of MFSK (M-ary frequency-shift keying) and DPSK (differentially coherent binary phase-shift keying) on a generalized fading-channel model, the slow nonselective Nakagami-m fading channel. Simple expressions are given for asymptotic slopes of probability of bit error for a large signal-to-noise ratio, and it is shown that the effective diversity of the system is in the product of two parameters, one for the code and one for the channel. It is concluded that the results obtained are potentially useful in the performance assessment of several current MFSK and DPSK systems that are required to operate on channels with a wide variety of fading or scintillation conditions. <<ETX>>
Somatosensory Information in Lifting Objects While Applying Contralateral Finger Touch to the Target Arm

We have observed that the magnitude of grip force used to lift and transport a hand-held object could be reduced if a light finger touch is provided by the contralateral arm to the target arm. In the current study, we investigate if different types of somatosensory information formulate parallel modulation of grip force when perform similar functional experimental task. Nine healthy individuals performed the same task of lifting and transporting an insrumented cup with contrlalateral index finger touch to the wrist, elbow and shoulder, in addition to no touch condition. Movement of the contralateral arm was produced when touch to the wrist and elbow; while touching the shoulder involve no movement of contralateral arm. But a relative movement between finger tip and the touch location can be found with application of finger touch to the shoulder. Grip force was reduced approximately the same amount in all touch conditions (wrist, elbow, shoulder) as compared to no touch condition. This outcome suggest that proprioceptive information from the muscle and joint receptors of the contralateral arm is used in control of grip force when a finger touch applied to wrist and elbow and cutaneous information is utilized when touch became available to the shoulder. It needs to be highlighted that different neural mechanisms are employed while lifting a hand-held object with a self contralateral finger touch. The results of the study also provided additional evidence to support the use of a second arm in the performance of activities of daily living and stress the importance of future studies investigating contralateral arm sensory input in grip force control.
Distributed Information Retrieval: Developments and Strategies

Opposed to centralized search where Websites are crawled and indexed, Distributed Information Retrieval (DIR), also known as Federated Search, is a powerful way to comprehensively search multiple databases in real-time simultaneously. DIR is preferred to centralized search environments in a number of ways, characteristically among them are: 1. the diversity of resources that are made available; 2. improving scalability and reducing server load and network traffic; 3. the leverage of accessing the hidden or deep Web.There are three major phases/tasks of a DIR (i) resource description or collection representation (ii) resource selection and (iii) result merging. This paper aims at providing a comprehensive review on the various phases of DIR and also some current strategies being recommended in enhancing and improving the smooth implementation of a DIR system.
The Attitudes of Preschool Teacher Candidates Studying through Distance Education Approach towards Teaching Profession and Their Perception Levels of Teaching Competency.

The purpose of this study is to determine the attitudes of preschool teacher candidates studying through distance education approach towards teaching profession and to determine their perception levels of teaching competency. The population and sampling of the study were the senior students of Anadolu University, Open Education Faculty, Preschool Teacher Training Undergraduate Program. The study was conducted through 957 teacher candidates. A survey was used in order to measure the attitudes of teacher candidates towards teaching profession and to determine their perception levels of teaching competency as a data collection instrument for this study. The study revealed that the attitudes of teacher candidates towards teaching profession are quite positive, and their perception levels of teaching competency are very good. Moreover, the teacher candidates consider the program they enrolled in so beneficial for them to gain teaching competencies.
A decision fusion method using an algorithm for fusion of correlated probabilities

ABSTRACT This paper proposes a new decision fusion method accounting for conditional dependence (correlation) between land-cover classifications from multi-sensor data. The dependence structure between different classification results is calculated and used as weighting parameters for the subsequent fusion scheme. An algorithm for fusion of correlated probabilities (FCP) is adopted to fuse the prior probability, conditional probability, and obtained weighting parameters to generate a posterior probability for each class. A maximum posterior probability rule is then used to combine the posterior probabilities generated for each class to produce the final fusion result. The proposed FCP-based decision fusion method is assessed in land-cover classification over two study areas. The experimental results demonstrate that the proposed decision fusion method outperformed the existing decision fusion methods that do not take into account the correlation or dependence. The proposed decision fusion method can also be applied to other applications with different sensor data.
A differential current-conveyor based buffer for high-bandwidth, low-signal applications

This paper describes a novel differential buffer designed for high-bandwidth, low-power current transducers. This buffer uses modified class II current-conveyor cells, interconnected in such a way as to provide controlled impedance-matched differential inputs. This buffer is shown to provide a small current gain. Circuit simulations are presented and the circuit behaviour is analysed as a function of both input transducer characteristics and output loads. Noise considerations are also presented. This buffer is then applied to a wireless optical system. It increases overall system performance in both terms of gain and frequency response.
Optimal Encounter-Based Routing of Queries for Mobile Objects

—Mobile objects can be equipped with sensors enabling them to collect data, as well as answer queries remotely and in real-time. For that, one needs to be able to effectively route queries from a base station to the queried object in an efﬁcient way, i.e., with minimum energy-cost and/or minimum delay. Complicating factors in many domains are that the objects in the network are mobile and that they may not form a single connected component at all times. In this paper we take advantage of periodically repeated encounters, where an encounter is deﬁned as a time-period long enough so that sensors can communicate with each other. Possessing such encounter patterns we show how to model routing as an optimization problem in a graph with domain-oriented constraints. Further, we propose polynomial time algorithms to ﬁnd the optimal and near-optimal routes to deliver the query from a source to one or more query object(s). We also show that the proposed model is ﬂexible enough to support different assumptions about the nature of the encounters. Experimental results, using both real and synthetic datasets, show that our proposed approaches always ﬁnd better routes with regard to delivery delay and energy cost comparing to other state-of-art protocols.
Morphosyntactic Processing, Cue Interaction, and the Effects of Instruction: An Investigation of Processing Instruction and the Acquisition of Case Markings in L2 German

Sentence comprehension is among the most fundamental elements of second language (L2) acquisition, but it is also incredibly complex because L2 learners have to develop the ability to detect multiple types of cues in the input and interpret them in context. This is particularly difficult given that L2 learners have limited knowledge of these cues and have limited resources to process them. As a result, L2 learners employ a variety of strategies to help them make sense of complicated input. These strategies include attending to simpler or more salient cues in the input, such as lexical items, semantic cues (e.g., animacy, plausibility), or word order (VanPatten, 2004a). Consequently, other cues, such as morphosyntax (e.g., tense or case information) are not processed readily, and learners have difficulty acquiring these forms. Thus the presence of more salient forms that encode the same semantic information, may present a significant barrier to acquisition. On the other hand, there may be situations where certain cues support each other and promote acquisition. For example, current research (e.g., Grünloh, Lieven, & Tomasello, 2011) suggests that prosody (e.g., stress, pitch) may support the processing of morphosyntactic forms. The goal of this dissertation is to explore the psychological principles that underlie learners’ interactions with lexical-semantic, morphosyntactic, and prosodic cues in an input stream and to investigate how these processes impact the acquisition of morphosyntactic forms. Furthermore, this dissertation seeks to examine whether instructional interventions such as Processing Instruction can take advantage of these psychological principles in order to change processing behaviors and promote the acquisition of morphosyntactic cues. In order to address these issues, the present research tests the offline and online (i.e., real-time) effects of Processing
External Memory Algorithms for Factoring Sparse Matrices

We consider the factorization of sparse symmetric matrices in the context of a two-layer storage system: disk/core. When the core is sufficiently large the factorization can be performed in-core. In this case we must read the input, compute, and write the output, in this sequence. On the other hand, when the core is not large enough, the factorization becomes out-of-core, which means that data movement and computation must be interleaved. We identify two major out-of-core factorization scenarios: read-once/write-once (R1/W1) and read-many/write-many (RM/WM). The former requires minimum traffic, exactly as much as the in-core factorization: reading the input and writing the output. More traffic is required for the latter. We investigate three issues: the size of the core that determines the boundary between the two out-of-core scenarios, the in-core data structure reorganizations required by the R1/W1 factorization and the traffic required by the RM/WM factorization. We use three common factorization algorithms: left-looking, right-looking and multifrontal. In the R1/W1 scenario, our results indicate that for problems with good separators, such as those coming from the discretization of partial differential equations, ordered with nested dissection, right-looking and multifrontal factorization perform slightly better than left-looking factorization. There are, however, applications for which multifrontal is a bad choice, requiring too much temporary storage. On the other hand, right-looking factorization should be avoided in the RM/WM scenario. Left-looking is a good choice, but only if data is blocked along one dimension. Multifrontal performs well for both one and two dimensional blocks as long as not too much storage is required. We also explore a framework for a software implementation. We have implemented an in-core solver that relies on some object-oriented constructs. Most of the code is written in C++, except for some kernels written in Fortran 77. We intend to add out-of-core functionality to the code and data movement is a major concern. Implicit data movement represents the easy way, but, as some of our experiments show, good performance can be achieved only with explicit data movement. This complicates the code and we expect a substantial effort in order to implement an efficient out-of-core solver.
Hierarchical probabilistic model of language acquisition

In this thesis, I propose an unsupervised computational model of language acquisition through visual grounding. I especially focus on a case where the language input is in a form of variable length sentences. The state-of-the-art cognitive architectures with the focus on grounding language in vision are explored. I take an advantage of probabilistic Bayesian models which are besides neural networks one of the main tools used in a computational cognitive modeling. The probabilistic (Bayesian) models have been used in the tasks such as language processing, decision making or causality learning. In the first part of the thesis newly proposed method for estimating a number of clusters in data is described. In the second part of the thesis I focus on the description of the cognitive architecture itself. The developed hierarchical cognitive architecture processes separately visual (static) and language (time-sequence) data and combines them in a multimodal layer. The important feature is a compositionality of the system ability to derive meaning of previously unheard sentences and unseen objects and its ability to learn all features describing the object from sentences of variable length. The proposed architecture was implemented into the humanoid robot iCub and tested on both artificially generated data and on the realworld data.
YodaQA: A Modular Question Answering System Pipeline

This is a preprint, submitted on 2015-03-22. Question Answering as a sub-field of information retrieval and information extraction is recently enjoying renewed pop- ularity, triggered by the publicized success of IBM Watson in the Jeopardy! competition. But Question Answering re- search is now proceeding in several semi-independent tiers depending on the precise task formulation and constraints on the knowledge base, and new researchers entering the field can focus only on various restricted sub-tasks as no modern full-scale software system for QA has been openly available until recently. By our YodaQA system that we introduce here, we seek to re- unite and boost research efforts in Question Answering, pro- viding a modular, open source pipeline for this task — allow- ing integration of various knowledge base paradigms, an- swer production and analysis strategies and using a machine learned models to rank the answers. Within this pipeline, we also supply a baseline QA system inspired by DeepQA with solid performance and propose a reference experimen- tal setup for easy future performance comparisons. In this paper, we review the available open QA platforms, present the architecture of our pipeline, the components of the baseline QA system, and also analyze the system perfor- mance on the reference dataset.
An empirical analysis of factors influencing continuance intention of mobile instant messaging in China

The purpose of this research is to investigate factors affecting users’ continuance intention in the context of mobile instant messaging (IM). Drawing upon the social cognitive perspective, the study builds a theoretical model to illustrate the relationships between perceived user base, habit, resistance to change and continuance intention. An empirical study is conducted to test the research model by surveying Chinese mobile IM users. The results show that habit and resistance to change both play important roles in intention to continue use of mobile IM. More specifically, resistance to change is found to have the largest effect on continuance intention. The results also show that habit directly and indirectly affects continuance intention through resistance to change. In addition, perceived user base has a significant effect on continuance intention. Extant information system (IS) continuance research has mainly focused on contexts other than mobile IM. Furthermore, prior IM-related studies have tended to focus more on investigation of factors affecting IM usage behavior and have paid less attention to user continuance of mobile IM services. This current study attempts to address this research gap. Specifically, the study proposes a model that integrates factors such as resistance to change, habit, perceived user base, and continuance intention in the context of mobile IM services. In addition, the study empirically demonstrates the effects of resistance to change and habit on continuance intention, as well as the influence of habit on resistance to change.
Assessing the quality of OpenStreetMap building data and searching for a proxy variable to estimate OSM building data completeness

OpenStreetMap (OSM) is an open data, geospatial information (GI) project that relies on contributions from volunteers to create a digital, on-line, map of the world. The use of OSM is also free and available under the Open Database License (Hecht, et al., 2013). As the amount of information available in the OSM database continues to grow, interest has grown regarding the application of OSM in industry and according to scientific standards (Haklay, 2010; Hecht, et al., 2013; Koukoletsos, et al., 2012). However the quality of OSM building data is largely unknown and thus the practical applications for OSM building data remain limited.
Image watermarking and data hiding techniques

Gradually people are motivated to embed information such as owner info, date, time, camera settings, event/occasion of the image, image title, or even secret message in the digital images for value-added functionalities and possibly secret communication. A novel sample-based methods are proposed to embed some information bits in the JPEG compressed domain. The proposed method called J-Mark embeds the information bits in the DCT coefficients with significant energy in the selected blocks significant masking properties. Spread spectrum technique (SST) is widely adopted for vector-based image and video watermarking in the past few years. Four novel techniques are proposed to embed watermarks for different purposes. The first one call Single Watermark Embedding (SWE) is use to embed a watermark bit sequence in digital images using two secret keys. The second technique called Multiple Watermark Embedding (MWE) extends SWE to embed multiple watermarks simultaneously in the same watermark space while minimizing the watermark energy. The third technique called Iterative Watermark Embedding (IWE) embeds watermarks in JPEG-compressed images. The proposed iterative approach can prevent largely the potential removal of watermarks in the JPEG recompression process. The fourth technique called Direct JPEG Watermark Embedding (DJWE) is an extension of the IWE. DJWE embeds the watermarks with lower computation complexity
GPF : a framework for general packet classification on GPU co-processors

This thesis explores the design and experimental implementation of GPF, a novel protocol-independent, multi-match packet classification framework. This framework is targeted and optimised for flexible, efficient execution on NVIDIA GPU platforms through the CUDA API, but should not be difficult to port to other platforms, such as OpenCL, in the future. GPF was conceived and developed in order to accelerate classification of large packet capture files, such as those collected by Network Telescopes. It uses a multiphase SIMD classification process which exploits both the parallelism of packet sets and the redundancy in filter programs, in order to classify packet captures against multiple filters at extremely high rates. The resultant framework comprised of classification, compilation and buffering components efficiently leverages GPU resources to classify arbitrary protocols, and return multiple filter results for each packet. The classification functions described were verified and evaluated by testing an experimental prototype implementation against several filter programs, of varying complexity, on devices from three GPU platform generations. In addition to the significant speedup achieved in processing results, analysis indicates that the prototype classification functions perform predictably, and scale linearly with respect to both packet count and filter complexity. Furthermore, classification throughput (packets/s) remained essentially constant regardless of the underlying packet data, and thus the effective data rate when classifying a particular filter was heavily influenced by the average size of packets in the processed capture. For example: in the trivial case of classifying all IPv4 packets ranging in size from 70 bytes to 1KB, the observed data rate achieved by the GPU classification kernels ranged from 60Gbps to 900Gbps on a GTX 275, and from 220Gbps to 3.3Tbps on a GTX 480. In the less trivial case of identifying all ARP, TCP, UDP and ICMP packets for both IPv4 and IPv6 protocols, the effective data rates ranged from 15Gbps to 220Gbps (GTX 275), and from 50Gbps to 740Gbps (GTX 480), for 70B and 1KB packets respectively.