Miracle-dz/UniFAR-FTUs huggingface dataset:
CS-2006-27-11 : A Performance Analysis of MANTIS and TinyOS

The capabilities of a sensor network are strongly influenced by the operating system used on the sensor nodes. In general, two different sensor network operating system types are currently considered: event driven and multi-threaded. It is commonly assumed that event driven operating systems are more suited to sensor networks as they use less memory and processing resources. Hence, the de-facto standard operating system used for sensor networks today is the event driven operating system TinyOS. However, if factors other than resource usage are considered important, a multi-threaded system might be preferred. This paper investigates the resource overhead that is incurred by running a multi-threaded operating system on a sensor node. The resources considered are memory usage and power consumption. Additionally, the event handling capabilities of event driven and multi-threaded operating systems are analyzed and compared. For comparison, the event-based system TinyOS and the multi-threaded system MANTIS executing the same sensor network applications on the DSYS25 sensor platform are used. The results presented in this paper show that for a number of application areas a thread-based sensor network operating system is feasible and preferable.
Methods of Teaching the Bible-A Study on the Learning Experience of the Millennium ’ s Pupils from High Schools

Through qualitative research, data were collected using semi-structured interviews of 76 pupils ages 12-18, born between 1997-2003. The research study attempts to answer the question: what are the expectations of millennial (Generation Z) youths from Bible study classes in public schools. Results show that Israeli pupils in nonreligious public schools prefer and expect Bible studies to be conducted utilizing three teaching and learning methods: 1. Literary criticism and high-order thinking 2. Experiential manner of teaching 3. Discourse forming moral identity The expectation of many of the participants in the research is for instruction that invites expression of opinions and critical thought through dialogue and class discussion. The pupils’ expectations are contrary to traditional teaching that is focused on the content per se, which according to the research participants causes them to disassociate themselves from the subject matter. As befitting millennials in the Digital Age, the participants did not express interest in amassing content knowledge, but rather in the stimuli of experiential teaching that includes media, technology, drama, stories and games, all in contrast to the prevailing conservative teaching approaches that they claim causes them to be disinterested. The pupils’ perceptions and expectations calls for the planning and execution of teaching based on critical and high order thinking, with emotional and cognitive processing of cultural humanistic content that is relevant for molding young adults’ cultural identity.
THE EFFECTS OF TECHNOSTRESS ON INFORMATION TECHNOLOGY ACCEPTANCE

Recent information technology is developing rapidly enough to provide new insights beyond human intuition. However, due to incidents such as job loss and privacy invasion, individuals are exposed to stress such as fear and pressure. The stress caused by such information technology may have a negative impact on the acceptance of new technology or productivity, and understanding this in practice is a critical task in modern society. The purpose of this research is to investigate the direct and indirect effects of technostress on the level of the individual in accepting new information technology. We developed a research model with innovation resistance as a mediating variable and conducted empirical analysis through 190 questionnaire responses. As a result, there were influences of the pace of change, reliability, connectivity, and complexity on the characteristics of information technology that induces individual technostress. Also, technostress has been proven to influence the acceptance of information technology only indirectly through innovation resistance. This study will provide meaningful insights and implications for the technostresses and consequences raised in the information system field through innovation resistance.
User modeling for spoken dialogue system evaluation

Automatic speech dialogue systems are becoming common. In order to assess their performance, a large sample of real dialogues has to be collected and evaluated. This process is expensive, labor intensive, and prone to errors. To alleviate this situation we propose a user simulation to conduct dialogues with the system under investigation. Using stochastic modeling of real users we can both debug and evaluate a speech dialogue system while it is still in the lab, thus substantially reducing the amount of field testing with real users.
Title Statistical Transformation of Language and PronunciationModels for Spontaneous Speech Recognition

We propose a novel approach based on a statistical transformation framework for language and pronunciation modeling of spontaneous speech. Since it is not practical to train a spoken-style model using numerous spoken transcripts, the proposed approach generates a spoken-style model by transforming an orthographic model trained with document archives such as the minutes of meetings and the proceedings of lectures. The transformation is based on a statistical model estimated using a small amount of a parallel corpus, which consists of faithful transcripts aligned with their orthographic documents. Patterns of transformation, such as substitution, deletion, and insertion of words, are extracted with their word and part-of-speech (POS) contexts, and transformation probabilities are estimated based on occurrence statistics in a parallel aligned corpus. For pronunciation modeling, subword-based mapping between baseforms and surface forms is extracted with their occurrence counts, then a set of rewrite rules with their probabilities are derived as a transformation model. Spoken-style language and pronunciation (surface forms) models can be predicted by applying these transformation patterns to a document-style language model and baseforms in a lexicon, respectively. The transformed models significantly reduced perplexity and word error rates (WERs) in a task of transcribing congressional meetings, even though the domains and topics were different from the parallel corpus. This result demonstrates the generality and portability of the proposed framework.
Profile of renal biopsies in a tertiary care hospital

Background: Renal biopsy is an invaluable method used in evaluation of patient with renal disease. Light microscopy and immunofluorescence findings make it possible to establish accurate diagnosis, get information on evaluation and prognosis of disease process and develop approach in treatment of renal disorders.We in this study tried to evaluate the profile of renal biopsies received in a year and correlated the findings of routine microscopy to immunofluorescence (IF) staining. Material and method: We retrospectively studied 75 consecutive kidney biopsies received from January 2012 to December 2012 at Pt. BD Sharma, PGIMS, Rohtak. H&E and special stained sections were examined and findings were correlated with immunofluorescence staining. Results: The study included 75 cases. Male : female1.3:1 ranging from age group 1576 years with maximum number of cases belonging to second to third decade. The cases were categorized into 5 groups: [1]. Primary Glomerulonephritis61.3% (46/75). [2]. Secondary Glomerulonephritis16% (12/75). [3]. Vascular and tubulointerstitial disease1.3% (1/75). [4]. End stage renal disease-4% (3/75). [5]. Inadequate-17.4% (13/75). The largest group comprises of primary glomerulonephritis with membranous glomerulonephritis being the most common (32.6% 15/46). This was followed by secondary glomerulonephritis group with lupus nephritis (58.4% 7/12) being the most common cause. Conclusion: Renal biopsy and IF appears to be an important tool for diagnosing glomerular diseases. Immunofluorescence helped in making diagnosis where light microscopy findings were equivocal and it also helps in understanding immunological mechanisms involved in various renal lesions. Hence it is less time consuming and effective method in diagnosing glomerular diseases on renal biopsies.
Hybrid-genetic-algorithm-based resource allocation for slow adaptive OFDMA system under channel uncertainty

A resource allocation algorithm for the slow adaptive orthogonal frequency division multiple access system under channel uncertainty is considered. The optimisation objective maximises the long-term system throughput over subcarrier assignment and the constraint condition satisfies the short-term data rate requirements of individual users, except occasional outage. Such an objective has a natural chance-constrained programming formulation. To solve the chance-constrained optimisation, the neural network and the genetic algorithm (GA) are integrated to develop a hybrid GA (HGA) which could satisfy the user data rate requirement with the target outage probability. The simulation tests verify that the HGA yields a higher long-term system throughput than the Li algorithm with the Bernstein approximation.
A clock power model to evaluate impact of architectural and technology optimizations - a summary

The clock distribution and generation circuitry forms a critical component of current synchronous digital systems and is known to consume around a quarter of the power budget of existing microprocessors. We propose and validate a high level model for evaluating the energy dissipation of the clock generation and distribution circuitry, including both the dynamic and leakage power components. The validation results show that the model is reasonably accurate, with the average deviation being within 10% of SPICE simulations. Access to this model can enable further research at high-level design stages in optimizing the system clock power. To illustrate this, a few architectural modifications are considered and their effect on the clock sub-system and the total system power budget is assessed.
ESTIMATION, CLASSIFICATION, AND ANALYSIS OF LOSSES IN OPTICAL BURST SWITCHING NETWORKS

Optical burst switching (OBS) is considered a popular switching paradigm for the realization of core optical networks due to the balance it offers between coarse-grained optical circuit switching (OCS) and fine-grained optical packet switching (OPS). OBS avoids the use of optical buffering and optical processing logic unlike in OPS but still achieves switching in optical domain. It improves the utilization of the fiber compared to OCS because of statistical multiplexing of bursts on different wavelengths. Generally it is assumed that buffering of the data bursts is allowed only at the edge nodes since the technology for optical buffers is immature. Due to the bufferless nature of the core nodes and the use of one-way reservation protocols, bursts are dropped whenever more than one burst requests the same wavelength at the same time. These losses, termed as contention losses which are characteristic of the OBS networks, occur quite frequently in a random fashion. However, at a core node the presence of contention losses cannot be treated as a sign of congestion which is typically associated with a high link utilization. Research in the OBS networks mainly focuses on the techniques to resolve contention and provide quality of service guarantees at the higher layers in spite of contention losses. In this thesis, we focus on the estimation, classification, and analysis of losses in OBS networks. Estimation of loss rate at the core nodes can identify potential bottleneck links in the network and helps the design of congestion control mechanisms. The main challenge in estimation of losses in OBS networks is that the core nodes have limited capability in providing feedback. We propose a method to estimate the loss rate at the core nodes using only the total loss rate measured at the ingress nodes. The proposed approach is passive and non-invasive so that it is scalable even for large networks with a high data rate. The accuracy of the method is validated with the loss rate measured from the simulations. In OBS networks, losses may either occur temporarily due to contention or might occur due to congestion along the path which is associated with high link utilization. We address the problem of identifying a situation of congestion from the contention losses. We propose a method of classifying the observed losses into contention and congestion losses using the machine learning techniques. We use both a supervised machine learning technique that uses manual labels to differentiate between the losses and an unsupervised learning technique that does not require any labels. The proposed technique for loss classification is purely end-
Riding tandem: an organic and collaborative approach to research in vocational education and training

This study set out to explore the use of the Internet in peer-to-peer learning environments within vocational education and training and to investigate whether this approach could replace traditional teaching and learning. A mixed methods design, including classroom observations, design experiments, interviews and questionnaires was adopted. Although this study represents a mid-term report on work in progress only, a number of observations can nevertheless be made about the process of conducting research within Further Education (FE) colleges. Whilst, traditionally, the pursuit of research is not a priority within FE colleges, this study has encouraged lecturers in Highbury College, Portsmouth, United Kingdom to trial a research-based approach to curriculum development. They have worked as co-researchers in the study from the conceptual phase to implementation. This paper outlines the process of conducting research in partnership with Business lecturers at Highbury College. It presents preliminary findings based on the researcher and lecturers’ reflections on the research methodology and process followed over a period of 9 months. Keywords: Emergent learning; FE Colleges; SOLE; vocational education and training (Published: 28 August 2014) Citation: Research in Learning Technology 2014, 22 : 24614 - http://dx.doi. org/10.3402/rlt.v22. 24614
Fuzzy pre-extracting method for support vector machine

The support vector machine (SVM) learning algorithm is a method for small samples learning, but the selected support vectors (SVs) must be obtained by an optimal algorithm. To counter the low speed of the SVM learning, a new fast method combining SVM and a fuzzy method is proposed. The SVs are pre-extracted by an iterative algorithm and a fuzzy method is used instead of solving the complex quadratic program problem. The method greatly reduces the training samples and improves the speed of SVM learning, while the ability of the SVM is not degraded. Better results are obtained over other SVM methods, which makes this new fuzzy pre-extracting SVM method useful in practice.
Contributions to Meta-Modeling Tools and Methods

Highly integrated domain-specific environments are essential for the efficient design of complex physical products. However, developing such design environments is today a resource-consuming error-prone process that is largely manual. Meta-modeling and meta-programming are the key to the efficient development of such environments. The ultimate goal of our research is the development of a meta-modeling approach and its associated meta-programming methods for the synthesis of model-driven product design environments that support modeling and simulation. Such environments include model-editors, compilers, debuggers and simulators. This thesis presents several contributions towards this vision, in the context of the Modelica framework. Thus, we have first designed a meta-model for the object-oriented declarative modeling language Modelica, which facilitates the development of tools for analysis, checking, querying, documentation, transformation and management of Modelica models. We have used XML Schema for the representation of the meta-model, namely, ModelicaXML. Next, we have focused on the automatic composition, refactoring and transformation of Modelica models. We have extended the invasive composition environment COMPOST to handle Modelica models described using ModelicaXML. The Modelica language semantics has already been specified in the Relational Meta-Language (RML), which is an executable meta-programming system based on the Natural Semantics formalism. Using such a meta-programming approach to manipulate ModelicaXML, it is possible to automatically synthesize a Modelica compiler. However, such a task is difficult without the support for debugging. To address this issue we have developed a debugging framework for RML, based on abstract syntax tree instrumentation in the RML compiler and support of efficient tools for complex data structures and proof-trees visualization. Our contributions have been implemented within OpenModelica, an open-source Modelica framework. The evaluations performed using several case studies show the efficiency of our metamodeling tools and methods.
An Improvement Password-Based Authentication Protocol Using Smart Card

To access resources from a remote system, the user authentication is a very important security mechanism. Among remote authentication protocol, password-based authenticated key exchange protocol is most popular since the two communication entities only shared a human-memorable password can establish a session key which is used to protected their later communication over an insecure networks. Recently, Xu Zhu proposed improved password-based protocol using smart card based on previous research. He claims that his protocol is secure against various attacks. However, Song points out that the Xu Zhu’s protocol suffers from attacks. In addition, Song gives an improved version of Xu Zhu. In this paper, we first found Song’s protocol also is vulnerable to off-line dictionary attack. Later, we extend Song’s protocol so that the extended protocol can resist to off-line dictionary attack even if an adversary captures the smart card.
NDA Based Hierarchical Classification Scheme for Identifying the Contributors to a Multivariate Control Chart

Many multivariate control charts have been proposed for monitoring several related quality characteristics simultaneously. However, even when an out-of-control signal is detected, the employed multivariate control charts generally do not provide any interpretable information associated with that signal. That is, the contributors of the out-of-control event can not be identified by the charts. Hence, how to tackle this interpretation problem effectively is an important issue in multivariate process control. One rarely addressed but very crucial property of this interpretation problem is that the number of possible outcomes can be very large. According to this key property, a nonparametric discriminant analysis (NDA)-based hierarchical classification scheme is proposed in this paper. A simulation experiment including several popular classification methods was conducted for evaluating the performance of the proposed method. The result shows that our proposed scheme is very competitive when measured against these popular methods.
Interconnection & Handover between IEEE 802.16e & UMTS

Currently, the interruptions of service during the vertical handover between different technologies, especially when the service is sensitive to delay, pose a real problem to the end users. In order to reduce the latency during the vertical handover; we propose in this paper to combine two mechanisms proposed recently for the handover. The both mechanisms that we will combine in the case of vertical handover are: the IEEE 802.21 architecture, that allows obtaining information on networks before the Handover; and the MSCTP protocol that uses during the handover the multihoming technique to open several IP sessions at the same time between the mobile station and the networks. To test our proposition, we will design an interconnection and mobility model between two WMAN radio technologies, which one belongs to the networks family based on IP protocol: IEEE Mobile WiMAX, and the second belongs to the telecommunication networks family: UMTS. For evaluate the performance of the proposition, we will apply first each mechanism only on the model; then our proposed solution; and we will compare the three results obtained The simulations will drive under NS2 simulator; based on the tracking of a mobile station movement between the Mobile WiMAX and the UMTS networks, and using the VoIP traffic for the communication with other correspondent node localized in an external network.
Indexing and dependency logic for answering english questions

This paper describes a computer system which uses a combination of coordinate indexing and structure matching techniques to extract from English questions many criteria which can be used for selecting and recognizing answers. A complete index of all content words in text is first searched to find information-rich statements which may be answers to the question. Each of these statements is then dependency analyzed to determine if the words (or synonyms) which correspond to question words maintain the dependency relations holding in the question. A simple semantic evaluation of structurally acceptable answers follows. A human editor working with the computer system helps to resolve syntactic ambiguities which are otherwise a major stumbling block in question-answering systems.
DATA COLLECTION METHOD FOR PEDESTRIAN MOVEMENT VARIABLES

The need of tools for design and evaluation of pedestrian areas, subways stations, entrance hall, shopping mall, escape routes, stadium etc lead to the necessity of a pedestrian model. One approach pedestrian model is Microscopic Pedestrian Simulation Model. To be able to develop and calibrate a microscopic pedestrian simulation model, a number of variables need to be considered. As the first step of model development, some data was collected using video and the coordinate of the head path through image processing were also taken. Several numbers of variables can be gathered to describe the behavior of pedestrian from a different point of view. This paper describes how to obtain variables from video taking and simple image processing that can represent the movement of pedestrians and its variables
A Method of Creating 3D Haptic Sensation Using Interactive Evolutionary Computation

本論文では, 3次元物体の触知を可能にする触力覚装置の最適化を, 対話型進化計算 (IEC) で支援する手法を提案する. 提案手法は, 利用する装置に関する知識やプログラミング技能を要せず, 触力覚技術に不慣れな利用者でも, 自身がイメージする触感を直観的に作成することを可能にする. 利用者は, 計算機が提示する複数の触感つき3次元モデルに触 (さわ) りながら, 自身の好みで適合度を与える. それに対して, システムが遺伝的アルゴリズムを用いて, 利用者から与えられた適合度を基にモデルの触感を進化させる. この「利用者評価とモデルの進化」を利用者が満足する触感が得られるまで繰返す. さらに, IECによる触感生成法と従来型の手動式パラメータ設定法を実装し, 比較実験をとおして提案手法の有効性を検証した.
A comparison of knowledge‐based and statistically‐based techniques for reference retrieval

This paper reports on a comparative evaluation of two computerised reference retrieval systems, INSTRUCT and PLEXUS. Instruct is a statistically‐based system based on best match searching and automatic index term weighting while Plexus uses expert systems techniques to improve access to a conventional Boolean search system. After an introduction to the retrieval techniques used by the two systems, their retrieval effectiveness is compared using a set of nineteen queries and 512 documents on the subject of gardening. The best results were obtained by using the terms suggested by the Plexus system as the basis for an Instruct search.