Miracle-dz/UniFAR-FTUs huggingface dataset:
e-Review Program: An alternative online interaction for a first-year unit of Engineering Mechanics using a virtual classroom

For large first-year units such as Engineering Mechanics 100, a lack of close interactive consultations between individual students and lecturers, and opportunities for weekly topic reviews precludes the enhancement of effective learning outcomes. Such drawbacks can lead to students’ disengagement that ultimately results in their academic underperformance. This e-Review project investigated the effective use of an alternative flexible learning method in which the interactive online teaching tool Elluminate Live was combined with a visual-aid graphics tablet to conduct the weekly e-Review sessions and revisions of past-semester examination questions. As opposed to the conventional in-class review in unit teaching, the difference of the eReview program lies in its convenient electronic access to unit revision activities through the monitoring of lecturers (as moderators) in a virtual classroom. It is shown that the use of Elluminate Live offers supplementary academic support that is beneficial to students through more direct feedback than can be achieved in a real class. Students also recognise the higher utility of e-Review materials that allow for subsequent viewing of recorded e-Review sessions.
Local feature selection for heterogeneous problems

Current electronic data repositories contain enormous amount of data including also unknown and potentially interesting patterns and relations. One approach commonly used is supervised machine learning, in which a set of training instances is used to train one or more classifiers that map the space formed by different features of the instances into the set of class values. The classifiers are later used to classify new instances with unknown class values. The multidimensional data is sometimes feature-space heterogeneous so that different features have different importance in different subareas of the whole space. In this paper we describe a technique that searches for a division of the feature space identifying the best subsets of features for each instance. Our technique is based on the wrapper approach where a classification algorithm is used as the evaluation function to differentiate between several feature subsets. On the other hand, to make the feature selection dynamic or local, we apply the recently developed technique for dynamic integration of classifiers to determine what classifier and with what feature subset is applied for each new instance. Our technique can be applied in the case of implicit heterogeneity when the regions of heterogeneity cannot be easily defined by a simple dependency. We make experiments with well-known datasets of the UCI machine learning repository using ensembles of simple base classifiers. The base classifiers discussed in the experiments are developed by C4.5 based on only one feature each but the combining method itself is allowed to take into account unlimited amount of present features. The results achieved are promising and show that the local data mining in comparison with mining the whole space can be advantageous. In many cases, the mining accuracy is better as well as the time of processing is shorter, because only a small set of features is used to classify each new instance.
Advisor Networks and Referrals for Improved Trust Modelling in Multi-Agent Systems

This thesis relates to the usage of trust modelling in multi-agent systems – environments in which there are interacting software agents representing various users (for example, buyers and sellers exchanging products and services in an electronic marketplace). In such applications, trust modelling may be crucial to allow one group of agents (in the e-commerce scenario, buyers) to make effective decisions about which other agents (i.e., sellers) are the most appropriate partners. A number of existing multi-agent trust models have been proposed in the literature to help buyers accurately select the most trustworthy sellers. Our contribution is to propose several modifications that can be applied to existing probabilistic multi-agent trust models. First, we examine how the accuracy of the model can be improved by limiting the network to a portion of the population consisting of the most trustworthy agents, such that the less trustworthy contributions of the remaining agents can be ignored. In particular, we explore how this can be accomplished by either setting a maximum size for a buyer’s advisor network or setting a minimum trustworthiness threshold for agents to be accepted into that advisor network, and develop methods for appropriately selecting the values to limit the network size. We demonstrate that for two models, both the Personalized Trust Model (PTM) developed by Zhang as well as TRAVOS, these approaches will yield significant improvements to the accuracy of the trust model, as opposed to using an unrestricted advisor network. Our final proposed modification is to use an advisor referral system in combination with one of the network-limiting approaches. This would ensure that if a particular agent within the advisor network had not met a specified level of experience with the seller under consideration, it could be replaced by another agent that had greater experience with that seller, which should in turn allow for a more accurate modelling of the seller’s trustworthiness. We present a particular approach for replacing advisors, and show that this will yield additional improvements in trust-modelling accuracy with both PTM and TRAVOS, especially if the limiting step were such that it would yield a very small advisor network.
Achieve Fuzzing Based on Symbolic Execution Platform

The traditional software development does not consider the concerns, which is can addressing security problem effectively. So how to find the problem is the standard consideration for security researchers. In the field of software security testing, there are four ways, Fuzzing, Dynamic Taint Analysis, Model Checking and Symbolic Execution. This paper we use symbolic execution to achieve functional of fuzzing. Introduction With the development of computer technology, there are more and more software applied in every walk of life, so the security of software have been known by developer. However, we cannot avoid the exception in developing software, the method of software vulnerability analysis is an important way to protect the security of information system. There are four ways in this field. Dynamic taint analysis [1] is belongs to data-path analysis. It sign the data with untrusted source to the taint, and tracking the data. Model checking [2] will model a system and uses formal method to judge the system whether it is a satisfied system properties. Fuzzing [3,4] can provide random input data to find the software vulnerability. Symbolic execution [5] is also belongs to data-path analysis, it use symbolic input instead of actual input, so it can generate more targeted test cases automatically.
A system for VEP detection and stimulus phase discrimination

The development of a system for detecting the presence and estimating the phase of the visual evoked potential in the electroencephalogram (EEG) of a human subject is presented. The stimulus set consists of several light emitting diodes (LEDs), all flashing at a rate of 10 Hz but with differing phases. The system employs a combination of wavelet prefiltering, harmonic preprocessing, neural network detection and phase discrimination and postprocessing of the neural network outputs. After an initial training period, the system is able to determine from the EEG at which of the LEDs the subject is looking with a rate of error of less than 20% within an interval of 0.8 seconds.
Graphical User Interface in MATLAB for Lithography in MICROSCALE Devices

Micro-photolithography consists of patterning the substrate using a source of light for micro and nano scale devices. Process parameters play a vital role in the designing of any process for Microlithography. Process engineers pre-calculate these parameters in order to refine and make the process more accurate. Graphical user interface created in Matlab – memspro – enables its users to simulate the process flow for Lithography operations and calculate process parameters for their designed process. It acts as a supporting tool for better understanding of the process with photomask and device visualization. The interface consists of options for generating plots and saving reports for the processes simulated. The entire code can be executed as an application and run on any system with an installed MATLAB runtime engine.
THE EFFECTIVENESS OF ONE STAY/THREE STRAY METHODTO TEACH READING VIEWED FROM STUDENTS’ SELF–ACTUALIZATION

The objectives of the research are: (1) to identify whether One Stay/Three Stray Method (OSTS) is more effective than Grammar-Translation Method (GTM) to teach reading to the eleventh graders of SMA Negeri 01 Daik Lingga ; (2) to identify whether the students having high self–actualization have better reading skill than those having low self-actualization to the eleventh graders of SMA Negeri 01 Daik Lingga; and (3) to identify w hether there is an interaction between the teaching methods and students’ self-actualization to teach reading . The research methodology was the experimental research . The research was conducted at SMA Negeri 01 Daik Lingga from October to November 2012. The population of this research was eleventh graders of SMA Negeri 01 Daik Lingga. The data analysis shows the following findings : (1) OSTS is more effective than GTM to teach reading to the eleventh graders of SMA Negeri 01 Daik Lingga ; (2) The students having high self–actualization have better reading skill than those having low–one; and (3) There is an interaction between the teaching methods and students’ self-actualization for teaching reading. It means that the effectiveness of the teaching methods depends on the degree of the students’ self-actualization to the eleventh graders of SMA Negeri 01 Daik Lingga . Keywords: Teaching methods, reading Comprehension, Self–actualization
Text-dependent Speaker Verification and RSR2015 Speech Corpus

RSR2015 (Robust Speaker Recognition 2015) is the largest publicly available speech corpus for text-dependent robust speaker recognition. The current release includes 151 hours of short duration utterances spoken by 300 speakers. RSR2015 is developed by the Human Language Technology (HLT) department at Institute for Infocomm Research (I2R) in Singapore. This newsletter describes RSR2015 corpus that addresses the reviving interest of text-dependent speaker recognition.
A fresh Two-party Authentication Key Exchange Protocol for Mobile Environment

Mobile environment has been used in large area range of network. In order to communicate securely, a number of schemes also have been proposed. The typical protocol which is two-party authentication key exchange (2PAKE) protocol is based on elliptic curve cryptosystem (ECC) in public networks. In this paper, we propose a two-party authentication key exchange protocol. Our protocol is indeed safer and meets the needs. It achieves efficiency in computational cost. Hence, the proposed protocol has a great contribution to the area of mobile environment. KEYWORD: Mobile environment; 2PAKE; Elliptic curve cryptosystem; Mutual authentication. International Conference on Industrial Technology and Management Science (ITMS 2015) © 2015. The authors Published by Atlantis Press 933
Disciplinary knowledge and gesturing in communicative events: a comparative study between lessons using interactive whiteboards and traditional whiteboards in Mexican schools

In this study the authors have looked at the use of interactive whiteboards (IWBs) in Mexico from a linguistic anthropological perspective. Twenty lessons were video recorded to compare the use of IWBs and traditional boards in different areas of the curriculum in primary schools. Data were analysed as a set of sequenced communicative events in which participants construct knowledge together in a multimodal environment. The authors found, firstly, that teachers ask students – through the use of language and gestures – to show in sequence their understanding of the use of multimodal objects according to the goals set for the lesson and the knowledge privileged by an academic discipline. Secondly, pedagogic ideologies are an important aspect of students’ socialisation into disciplinary knowledge that is embodied in communicative practices. Implications from the research include recognising the communicative competence of participants for achieving joint collective goals, as well as suggesting the design of new participation frameworks with pertinent and creative problem‐solving activities for promoting knowledge construction through talk in interaction.
New Planar CPW Fed Antenna for UWBApplications with Excellent Performance

The design analysis andfabrication of an antenna with improved gain and operational beyond the conventional ultra wideband frequency range is presented. The proposed antenna provides extremely wide operating frequency bandwidth, from 2.9 GHz till more than 18 GHz, with a maximum gain of 6.8dB, which is appropriate for ultra wideband wireless applications. The patch is printed on FR4 substrate with permittivity ofo£r=4.3 and the antenna is simple in design and easy in fabrication. The simulation results and the experimental measurements show that the antenna gain is excellent during the operating frequency.
Evaluación del índice de adiposidad corporal en la predicción del porcentaje de grasa en adultos de Bogotá, Colombia

Objective: the body adiposity index (BAI) is a new simplistic method for predicting body fat percentage (BF%) via a simple equation of hip circumference to height. Up to now, few studies have evaluated the performance of BAI in determining excess fat in Colombians. The aim of this study was to evaluate the usefulness of BAI as a predictor of body fat in among Colombian adults. Methods: cross-sectional study carried out in a sample of 204 male belonging to the education sector from Bogota, Colombia. BAI was calculated based on the equation reported in the Bergman et al. %BF determined by tetrapolar bioimpedance analysis (BIA) was used as the reference measure of adiposity. Bland-Altman analysis was used to assess the agreement between the two methods: BAI and BIA. Associations between anthropometric measures of adiposity were investigated by Pearson correlation analysis. Results: in general pupulation, the BAI overestimates %BF (mean difference: 12.5 % [95%CI = -4.04 % to -21.02 %]), mainly at lower levels of adiposity (mean difference: 10.2 ± 3.3). Significant correlations were found between BAI and all measurements, being the strongest-moderate correlation with %BF (r = 0.777, p < 0.001), waist to height ratio (r = 0.557, p < 0.001) and BMI (r = 0.480, p < 0.001). Conclusion: the results of this investigation indicate that BAI results in large individual errors when predicting BF% among Colombian adults and has a tendency to provide overestimated values as BF% decreases. Therefore, this method can be a useful tool to predict %BF in Colombian adults, although it has some limitations.
Performance evaluation of TCP over radio link protocol in TIA/EIA/IS-99 environment

This paper presents the work done to study the effects of the radio link protocol (RLP) layer on the performance of TCP over wireless links. In particular we consider RLP as described in TIA/EIA/IS-99 with variations in some of its parameters. We concentrate on the sensitivity study of TCP throughput and delay, when the parameters of RLP such as segmentation depth and maximum number of retrials varied. Also we consider the effect of maximum TCP advertised window size on the abovementioned TCP performance parameters. Previous work in this area have provided some upper bounds for the performance measures. The results presented are on the basis of detailed simulation of the RLP retransmission mechanism. Network Simulator has been used as the simulation platform for our study. We use a two-state Markov model to capture the mobility characteristics of the channel. Some results for high-speed links are also presented.
Orthogonal simple component analysis: A new, exploratory approach

Combining principles with pragmatism, a new approach and accompanying algorithm are presented to a longstanding problem in applied statistics: the interpretation of principal components. Following Rousson and Gasser [53 (2004) 539–555] 'the ultimate goal is not to propose a method that leads automatically to a unique solution, but rather to develop tools for assisting the user in his or her choice of an interpretable solution'. Accordingly, our approach is essentially exploratory. Calling a vector ‘simple’ if it has small integer elements, it poses the open question: 'What sets of simply interpretable orthogonal axes—if any—are angle close' to the principal components of interest? its answer being presented in summary form as an automated visual display of the solutions found, ordered in terms of overall measures of simplicity, accuracy and star quality, from which the user may choose. Here, ‘star quality’ refers to striking overall patterns in the sets of axes found, deserving to be especially drawn to the user’s attention precisely because they have emerged from the data, rather than being imposed on it by (implicitly) adopting a model. Indeed, other things being equal, explicit models can be checked by seeing if their fits occur in our exploratory analysis, as we illustrate. Requiring orthogonality, attractive visualization and dimension reduction features of principal component analysis are retained. Exact implementation of this principled approach is shown to provide an exhaustive set of solutions, but is combinatorially hard. Pragmatically, we provide an efficient, approximate algorithm. Throughout, worked examples show how this new tool adds to the applied statistician’s armoury, effectively combining simplicity, retention of optimality and computational efficiency, while complementing existing methods. Examples are also given where simple structure in the population principal components is recovered using only information from the sample. Further developments are briefly indicated.
Simultaneous untangling and smoothing of hexahedral meshnes

Currently, there is not a general method such that any given geometry can generate a mesh with elements of hexahedral type. However, there are several methods used to create the numerical discretization for certain types of geometries. Unfortunately, these methods could generate meshes with highly distorted elements and in some cases the mesh obtained may include tangled elements. Therefore, it is of most importance to develop a procedure that could smooth and untangle hexahedral meshes. This work will provide a method that improves the quality of unstructured meshes and, if required, untangle the inverted elements by the minimization of a smoothed objective function. This objective function is based on the shape quality index of the elements or in the conditioning number of the shape matrix. To illustrate the applica- tion of the proposed smoother, several example of tangled meshes are presented, show-ing how the smoother untangles and smoothes quadrilateral and hexahedral meshes. A comparison of the performance between several minimization methods is presented. Finally, the robustness of smoother is compared to one of the most used smoothing methods.
A problem in data variability on speaker identification system using Hidden Markov Model

Thepaperaddresses a problem on speaker identification system using Hidden Markov Model (HMM) caused by the training data selected far from its distribution centre. Four scenarios for unguided data have been conr'ucted to partition the data into training data andtesting data. The data were recorded from ten speakers. Each speaker uttered 80 times with the same physical (health) condition. The data colIected then pre-processed using Mel-Frequence Cepstrum Coefficients (MFCC) feature extraction method. The four scenarios are based on the distance of each speech to its distribution centre, which is computed using Self Organizing Map (SOM) algorithm. HMM with many number of states (from 3 up to 7) showed that speaker with multi-modals distribution will drop the system accuracy up to 9% from its highest recognition rate, i.e. 100%.
Just Enough Synchrony for Message Passing k-Set Agreement

kset agreement problem in message passing systems. To this end, we introduce two weak communication predicates Psrcs(k) and Pmov-dom(k) for round-based message passing systems using the Heard-Of (HO) Model by Charron-Bost and Schiper, and present and prove correct a novel algorithm that solves k-set agreement in a system wherePsrcs(k) holds. The algorithm works by approximating a synchrony graph, which is defined by the timely links between processes. In addition, we show thatPsrcs(k) is tight, in the sense that there is no algorithm for (k 1)-set agreement withPsrcs(k). Furthermore, we prove that any HO predicate that allows to solve k-set agreement is at least as strong asPmov-dom(k), which itself is sucient for solving k-set agreement. Finally, we show that Psrcs(k) naturally corresponds to a new class of partially synchronous modelsM 2-source (k) with weak timely link assumptions.
A Random Forest Approach to Model-based Recommendation ⋆

Model-based recommender systems are popular since models with demographic/item information can highlight the correlation of data and provide an intuitive recommendation. Some algorithms, such as Bayesian classifiers, decision trees, have been used to generate respective models. In this paper, we propose a random forest approach to create model-based recommendations. First, two types of datasets are extracted from the original one for the purposes of demographic-based and content-based recommendation, respectively. Second, average ratings are added into the new datasets as an attribute. Third, a forest is built for each user/item, where each leaf is assigned as a discrete score. Fourth, 6 predicting approaches adopting standard voting, weighted average, etc., are applied to compute evaluation values from the forest. Experimental results on the well-known MovieLens dataset show that some approaches are more reliable than others in terms of mean absolute error.
Pruning Method of Belief Decision Trees

—The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interpretation of the belief function theory. The uncertainty can appear either in the actual class of training objects or attribute values of objects to classify. In this paper, we develop a post-pruning method of belief decision trees in order to reduce size and improve classiﬁcation accuracy on unseen cases. The pruning of decision tree has a considerable intention in the areas of machine learning.
Insights on Cognizant Computing: Concepts, Technologies and Trends

One of the emerging trends that have gained increasing prominence and is fast becoming a household name in the global IT industry is the concept of cognizant computing. Research has repeatedly suggested that this technology may hold the key to satisfying nearly all the computing needs of humanity even down to the preferences of the unique individual, by harnessing and then enhancing the capabilities of the cloud services and the internet of things like nothing ever before experienced, in the next decade . This research provides new insights on a more wholesome approach to viewing cognizant computing – the continuum approach; it also illuminates this emerging technology by studying its basic concepts, technologies as well as emerging trends; and highlights specifically how the technologies of the Internet of Things (IoT) and Cloud Computing (CC) would help to drive the goals of Cognizant Computing.