Miracle-dz/UniFAR-FTUs huggingface dataset:
Representation of Temporal Patternsin Recurrent Networks

In order to determine the manner in which temporal patterns are represented in recurrent neural networks, networks trained on a variety of sequence recognition tasks are examined. Analysis of the state space of unit activations allows a direct view of the means employed by the network to solve a given problem , and yields insight both into the class of solutions these networks can produce and how these will generalize to sequences outside the training set. This intuitive approach helps in assessing the potential of recurrent networks for a variety of modelling problems. This paper investigates the way temporal patterns are represented by recurrent networks. Small sequence discrimination tasks were devised with the speciic intention of requiring the network to base its discrimination on the temporal structure of the input sequences. The resulting solutions were then analyzed using elementary tools from dynamic systems theory. Our primary interest was to establish the relationship between the temporal characteristics of the training set and the representations developed by the network. The relationship between a representation and its counterpart in the physical world may be completely arbitrary, as between an instance of the written or spoken word`penguin' and any particular bird of that sort, or there may be a more direct relationship, e.g as between a tonotopic map and the frequencies it represents. Many of the issues involved in distinctions among representational systems have been discussed by van Gelder and Port (1993, van Gelder, 1992). If the relationship between a symbolic representation and its semantic properties is completely arbitrary, questions about the diiculty of symbol grounding arise. Questions of symbol grounding and semantic ar-bitrariness are not often addressed in developing computational systems with representational properties. It has been more usual to determine by at the nature of the representational primitives and to attempt to create meaningful relations between these units. An alternative is to induce the repre-sentational system from the properties of the input to the system. This is now quite common in the connectionist world, where one determines an architecture , a training algorithm, an input set, and possibly an output set and the network is then left to devise a suitable representation. In this manner, one is assured that whatever the nal representation , its relationship to the properties of the input which are relevant to the task at hand will be non-arbitrary. Distributed representations, as found in connec-tionist networks, possess many …
In What Ways Do Preservice Teachers Utilize an Online Learning Support System

This study explored how preservice teachers perceived and utilized the Online Learning Support System designed and developed to provide a platform for presenting utilities like content, news, and course assignments, and facilitating communication among students and instructor. In this research, a qualitative method was used. The data was obtained through focus group interviews. Of 43 prospective teacher students enrolled in the “Instructional Planning and Evaluation” course, offered by the Department of Educational Sciences at the Middle East Technical University, 15 students participated in this study. After utilization of the web site throughout the semester, students reported the advantages using online learning support system as: being independent concerning time and place, keeping contact with the instructor any time, accessing up-to-date announcements, and uploading the assignments in an electronic format. Introduction The swift development in computer technologies has increased higher expectations from educational institutions. Educational institutions are forced to prepare the next generation of citizens for the technologically oriented world. Teacher education institutions should educate prospective teachers who are able to create technologically enriched instructional settings and use advantages of technologies in instruction as well. It is universities’ responsibility to train prospective teachers with technology and how to apply technology to their instruction. In order for preservice teachers to achieve these intended outcomes, schools of education should provide appropriate training in using technology for instruction. According to The Office of Technology Assessment (OTA, 1995) report “ The most direct and cost-effective way to educate teachers about technology is through the preservice education they receive in colleges of education or other institutions” (pp. 166-167). Many faculty members have recognized the potential of using the Internet for instruction. The World Wide Web (Web) offers a great potential for education and provides variety of sources. The Web provides a user-friendly interface and easy access to text, graphics, audio, and video materials that may be used in a common and consistent format. Most educational web sites provide basic course information such as syllabus, schedule, announcements, and reading lists. Others go beyond static materials to include synchronous or asynchronous communication, online testing, discussion groups, conferences, whiteboards, streaming audio and video (Hazari & Schnorr, 1999). Exposing preservice teachers to using online supplementary material and after the course taking students’ perceptions on the utilization of the web site, factors affecting students web site usage rate and their suggestions on the web site could be helpful for the revised version of this tool. The findings of this study also could be beneficial while making decisions about alternative designs of the Web supported learning environments or tools for preservice
Application of Computational Redundancy in Dangling Pointers Detection

Many programmers manipulate dynamic data improperly, which may produce dynamic memory problems, such as dangling pointer. Dangling pointers can occur when a function returns a pointer to an automatic variable, or when trying to access a deleted object. The existence of dangling pointers causes the programs to behave incorrectly. Dangling pointers are common defect that are easy to commit, but are difficult to discover. In this paper we propose a dynamic approach that detects dangling pointers in computer programs. Redundant computation is an execution of a program statement(s) that does not contribute to the program output. The notion of redundant computation is introduced as a potential indicator of defects in programs. We investigate the application of redundant computation in dangling pointers detection. The results of the initial experiment show that, the redundant computation detection can help the debuggers to localize the source(s) of the dangling pointers. During the experiment, we find that, our approach may be capable of detecting other types of dynamic memory problems such as memory leaks and inaccessible objects, which we plan to investigate in our future research.
A meta-model for operational support

Process mining techniques can be used to extract information from event logs helping organizations to gain insights into the operation of their business processes. It is now possible to provide such analysis information for ongoing executions in an on-line setting, yielding predictions about the current execution or recommendations of actions to take, commonly referred to as operational support. This paper defines a meta-model for operational support making it possible for users or tools to receive operational support without detailed knowledge of the algorithm providing answers. The meta-model defines four types of queries: A simple query asks diagnostic information about the current execution and a compare query compares the current execution with other similar executions. A predict query considers the future of previous executions similar to the current one to make a prediction about its future. A recommend query recommends the best next action to take based on predictions. We formally define our meta-model and take care to provide implementation suggestions for each defined concept. We present our implementation of the meta-model in the work flow system Declare and the process mining framework ProM.
The successful integration of smallholders in vertical coordination arrangements : experiences of the KASCOL model in Zambia : a thesis presented in partial fulfilment of the requirements for the degree of Master of AgriCommerce at Massey University, Manawatu, New Zealand

i Dedication . iii Acknowledgements . iv Table of contents . v List of tables . x List of figures . xi List of acronyms . xii Chapter One : Introduction. 1 1.1. Background . 1 1.2. Problem statement . 4 1.3. Research questions . 5 1.4. Objectives . 6 1.5. Thesis outline . 6 Chapter Two : Literature review . 7 2.
HybridCast: Joint multicast-unicast design for multiuser MIMO networks

Multi-user MIMO (MU-MIMO) has recently been specified in wireless standards, e.g., LTE-Advance and 802.11ac, to allow an access point (AP) to transmit multiple unicast streams simultaneously to different clients. These protocols however have no specific mechanism for multicasting. Existing systems hence simply allow a single multicast transmission, as a result underutilizing the AP's multiple antennas. Even worse, in most of systems, multicast is by default sent at the base rate, wasting a considerable link margin available for delivering extra information. To address this inefficiency, we present the design and implementation of HybridCast, a MU-MIMO system that enables joint unicast and multicast. HybridCast efficiently leverages the unused MIMO capability and link margin to send unicast streams concurrently with a multicast session, while ensuring not to harm the achievable rate of multicasting. We evaluate the performance of HybridCast via both testbed experiments and simulations. The results show that HybridCast always outperforms single multicast transmission. The average throughput gain for 4-antenna AP scenarios is 6.22× and 1.54× when multicast is sent at the base rate and the best rate of the bottleneck receiver, respectively.
Mining Top-K Graph Patterns that Jointly Maximize Some Significance Measure

Most of graph pattern mining algorithms focus on finding frequent subgraphs and its compact representations, such as closed frequent subgraphs and maximal frequent subgraphs. However, little attention has been paid to mining graph patterns with user-specified significance measure. In this paper, we study a new problem of mining top-k graph patterns that jointly maximize some significance measure from graph databases. Exploiting entropy and information gain, we give two problem formulation s , E M and IG M. We first prove them to be NP-hard and then propose two efficient algorithms, PP-TopK and DM-TopK, to solve them . PP-TopK greedily selects top-k graph patterns among frequent sub graph s. DM-TopK integrates the pruning techniques into the mining framework, and directly mines top-k graph patterns from graph databases. Empirical results demonstrate the quality of our top-k graph patterns, and validate the efficiency and scalability of our algorithms.
Solid‐to‐solid isostructural transition in the hard sphere/attractive Yukawa system

A thermodynamically consistent density functional‐perturbation theory is used to study the isostructural solid‐to‐solid transition which takes place in the hard sphere/attractive Yukawa system when the Yukawa tail is sufficiently short ranged. A comparison with results for the square well potential allows us to study the effect of the attractive potential form on the solid–solid transition. Reasonable agreement with simulations is found for the main transition properties as well as for the phase diagram evolution with the range of the attractive potential.
DUF283 domain of Dicer proteins has a double-stranded RNA-binding fold

Two RNases, Dicer and Argonaute, are at the heart of the RNA interference (RNAi) molecular machinery responsible for gene silencing. Both RNases contain multiple domains, most of which have been characterized or have functions that can be predicted based on sequence comparisons. However, Dicers of higher eukaryotes contain the domain known as DUF283 which at present has no assigned role. Using sensitive profile-profile comparisons, we detected a divergent double-stranded RNA-binding domain coinciding with the DUF283 of Dicer. This finding has potential implications regarding the mechanistic role of Dicer in RNAi.
Automatic landmark identification in 3D image volumes by topography conserving approximation of contour data

If organs are represented by a compact and non-ambiguous mathematical function, many actually interactive diagnostics on tomographic images can be performed automated. Such a representation is constructed from the organ's surface by mapping characteristic topographic structures (landmarks) onto identical function variables. Organs scanned by tomographic images series--periacetabular region of 14 hip joints imaged by X-ray CT--may be segmented. Their surface's contour points are approximated by tensor-product-B-splines (TPBSs). In a reference TPBS surface model landmarks are denoted interactively to define a mapping `variable-pair of the TPBS vs. landmark'. The patient TPBS models are mapped onto the reference model by fitting the model function values. The fit, and so the landmark identification, is performed by a homology function, which is applied to the patient model's variable plane. For simply shaped organs, the transformation of the tomographic to the topographic representation was possible using only the values and first order derivatives of the TPBSs. The presented landmark identification method avoids unnecessary assumptions of model deformation mechanism and has low computational costs.
Rab11a-dependent exocytosis of discoidal/fusiform vesicles in bladder umbrella cells

The discoidal/fusiform vesicles (DFV) of bladder umbrella cells undergo regulated exocytosis in response to stretch, but little is known about their biogenesis or the molecular machinery that modulates this process. We observed that Rab11a was expressed in umbrella cells (but not Rab11b or Rab25) and was associated with DFV. Using adenovirus-mediated delivery we transduced umbrella cells in situ with either dominant active (DA) or dominant negative (DN) mutants of Rab11a. DA-Rab11a stimulated an increase in apical surface area in the absence of stretch, whereas DN-Rab11a inhibited stretch-induced changes. Endocytosed fluid and membrane markers had little access to Rab11a-positive DFV, but virally expressed human growth hormone (hGH), a secretory protein, was packaged into DFV. Whereas expression of DA-Rab11a stimulated release of hGH into the bladder lumen, expression of DN-Rab11a had the opposite effect. Our results indicate that DFV may be biosynthetic in nature and that their exocytosis depends on the activity of the Rab11a GTPase.
Data Narratives: Uncovering tensions in personal data management

We present an interview study of 34 participants in the US and Korea who described how they manage their personal data, from work files to family photos. Through their 'data narratives' - accounts of their data management practices, including device usage patterns and negotiations with system and brand ecosystems' we explore how individuals negotiate a complex, multi-service, and morally-charged sociotechnical landscape, balancing demands to share and to safeguard their data in appropriate ways against a shifting background of changing technologies, relationships, individuals, and corporations. We describe the guiding framework that people use to make decisions as a 'moral economy' of data management, contributing to our understanding of context-specific system choices.
A Review of Personalised E-Learning: Towards Supporting Learner Diversity

The realisation of personalised e-learning to suit an individual learner's diverse learning needs is a concept which has been explored for decades, at great expense, but is still not achievable by non-technical authors. This research reviews the area of personalised e-learning and notes some of the technological challenges which developers may encounter in creating authoring tools for personalised e-learning and some of the pedagogical challenges which authors may encounter when creating personalised e-learning activities to enhance the learning experience of their students. At present educators who wish to create personalised e-learning activities require the assistance of technical experts who are knowledgeable in the area. Even with the help of an expert the creation of personalised e-learning activities still remains a complex process to authors who are new to the concept of tailoring e-learning to suit learner diversity. Before the successful utilisation of adaptive authoring tools can be realised, academic authors need to learn how to effectively use these tools. All learners come to education with a diverse set of characteristics; educators need to decide which learner characteristic(s) they wish to focus on addressing through the use of personalised e-learning activities. Further investigation, evaluation and analyses of authoring tools is required before personalised e-learning to support learner diversity can be achieved by many academics. Research members of the AMAS (2013) project team are currently involved in developing an authoring tool for adaptive activities for e-learning.
Robust Portfolio Selection

In this paper, we discuss one of the reasons leading practitionners to the rejection of the Markowitz model and propose a new stastistical method to avoid this problem. To be more precise, we discuss the problem of statistical robustness of the Markowitz optimizer and show that the latter is not robust, meaning that a few extreme assets prices or returns can lead to irrelevant 'optimal' portfolios. We then propose a robust Markowitz optimizer and show that it is far more stable than the classical version.
Assessing the Performance of a Computer-Based Policy Model of HIV and AIDS

Background Model-based analyses, conducted within a decision analytic framework, provide a systematic way to combine information about the natural history of disease and effectiveness of clinical management strategies with demographic and epidemiological characteristics of the population. Among the challenges with disease-specific modeling include the need to identify influential assumptions and to assess the face validity and internal consistency of the model. Methods and Findings We describe a series of exercises involved in adapting a computer-based simulation model of HIV disease to the Women's Interagency HIV Study (WIHS) cohort and assess model performance as we re-parameterized the model to address policy questions in the U.S. relevant to HIV-infected women using data from the WIHS. Empiric calibration targets included 24-month survival curves stratified by treatment status and CD4 cell count. The most influential assumptions in untreated women included chronic HIV-associated mortality following an opportunistic infection, and in treated women, the ‘clinical effectiveness’ of HAART and the ability of HAART to prevent HIV complications independent of virologic suppression. Good-fitting parameter sets required reductions in the clinical effectiveness of 1st and 2nd line HAART and improvements in 3rd and 4th line regimens. Projected rates of treatment regimen switching using the calibrated cohort-specific model closely approximated independent analyses published using data from the WIHS. Conclusions The model demonstrated good internal consistency and face validity, and supported cohort heterogeneities that have been reported in the literature. Iterative assessment of model performance can provide information about the relative influence of uncertain assumptions and provide insight into heterogeneities within and between cohorts. Description of calibration exercises can enhance the transparency of disease-specific models.
A new variable step-size algorithm on acoustic feedback suppression for digital hearing aids

Acoustic feedback suppression is a key task of digital hearing aid which commonly uses least mean square (LMS) or normalized LMS(NLMS) adaptive algorithm to cancel acoustic feedback signal, however the characteristic of acoustic feedback signal is not considered in these algorithms. In order to improve the listening recognition of hearing-impaired patients, this paper proposes a new variable step-size improved proportionate NLMS(IPNLMS) algorithm which bases on the sparseness of echo impulse. According to the nonlinear relationship between step size and error signal, this paper proposes a variable step-size IPNLMS adaptive algorithm which adds a step smooth process. The simulation results show that the proposed algorithm has more excellent performance for noise-canceling acoustic feedback of digital hearing aids, comparing with others variable step-size IPNLMS adaptive algorithms.
Comparison of Different Antidepressants and Psychotherapy in the Short-term Treatment of Depression

This paper reports the result of an analysis of data of brief therapy for patients with depression referred by physicians in a busy specialist hospital in Kuala Lumpur. The patients were divided into three groups at random using one of three antidepressants i.e. escitalopram, sertraline, or fluoxetine. All patients received cognitive behavior therapy. The therapy was aimed for a maximum of twelve sessions after which the patients will be discharged. However there were patients on escitalopram and sertraline that went on follow-up sessions monthly till six months and these patients were analized separately. There were 32 patients in the escitalopram group, 33 patients in the sertraline group, and 31 patients in the fluoxetine group. The result shows that all the groups were similar in the severity and scores pre-treatment but post-treatment there were a significant difference among them. All groups showed significant improvements in all modalities of measurements. However the escitalopram group showed better improvement compared to the two other groups.
The Impact of Mobile Channel Adoption on Purchase Time Dispersion in e-Commerce

The portability of a mobile device and the ubiquity of mobile Internet provide e-market users with more opportunities of access to e-commerce sites throughout a day. In this paper, we examine the access affordance of mobile technologies by analyzing the changes in purchase time dispersion of e-marketplace users after their adoption of mobile channel. By analyzing a large archival dataset including transactions in the mobile and online channels, we find that (1) a user's purchase time becomes more dispersed throughout a day after the mobile channel adoption, and (2) the impact of the mobile channel adoption on the purchase time dispersion is significantly different across different user groups. These findings present strong empirical evidences of access affordance of the mobile channel and how the affordance is realized across e-market users.
A SIMPLE WAY OF EXTRACTING THE FACIAL FEATURE : BETWEEN-THE-EYES

Stable and clear visible facial features are crucial for the tasks in human face perception, such as face detection and tracking. Among other features, the center point between the eyes, or the “Between-the-Eyes” (BTE) has been found to be one of the good choices. In this paper, we propose a simple and fast way of extracting this facial feature from a facial image. By using down-sampling strategy, a rotationally invariant filter is used for detecting the BTE feature. Primary experiments show the feasibility of this scheme and its usage in face tracking.