Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Computing Lecture 8 Unsupervised Learning

In the course of our lives, much of what we learn is acquired from others, either formally, from a teacher, or informally, from friends and acquaintances. Either way, this kind of learning is supervised because some form of instruction is involved. But we also learn things without any instruction at all, for instance by simply observing the way the world is. Backpropagation learning is a form of supervised learning-when it is used for pattern recognition the neural network is provided with the correct class label for each input pattern. This has a parallel in our daily lives where we have learnt (by being told) the names of a vast number of things. For instance, we know there is a class of creature called animals and within that class there are many subclasses – cats, dogs, cows, etc. We learn to classify them in terms of their labels, ie their names. But before language ever developed, human beings (or their predecessors) learnt to classify animals without the use of labels. And in particular some of them learnt, in a totally unsupervised fashion, which animals to run away from. Sometimes it was the last thing they learnt. In this lecture we will examine some forms of unsupervised learning that have been developed for artificial neural networks. We will commence with a system that is essentially supervised, but which involves some operations that are employed in unsupervised systems. These two nets work cooperatively to identify the class to which a given input pattern belongs. The pattern is identified by means of a set of stored prototype patterns (one for each class). The input pattern is assigned to the class of the prototype that is closest in terms of Hamming distance. The basic structure is shown in Fig. 8.1. If we want the classifier to identify examples from p different classes, both the Hamming net and Maxnet should have p outputs. The Hamming net gives the largest output for the prototype that is closest (has smallest Hamming distance) to the input vector. The role of Maxnet is simply to suppress all other outputs so that the right-hand vector in Fig 8.1 finishes with just one non-zero output, which corresponds to the pattern class identified by the Hamming net. Basic notation and structure are shown in Fig 8.2. Note that the neurons have the characteristics shown in Fig 8.2(b).
HCI using hand gesture recognition for Digital Sand Model

The Digital Sand Model is a tactical exercise without troops, which gives a bird's view of the terrain and allows the users to work on the battle planning and management. Interaction plays a substantial role in such training setups. In this paper we designed and developed an intuitive and "hands-free" human computer interaction for the DSM. The captured image is pre-processed for enhancing the hand object in the image. Specific features need to be extracted for fast and accurate recognition of the hand gesture. Two sets of feature vectors are explored in this paper, namely, Hu moments and hand contour. These features are classified using two different classifiers, namely, SVM and HMM and their performances are compared and analyzed.
Hypophyseal Influence on Function and Composition of Cardiac Muscle

The effects of hypophysectomy and of growth hormone (GH) on the properties and composition of rat myocardium were studied. GH, in dosage sufficient to maintain a normal rate of growth, did not correct the microcardia of hypophysectomy. Tension production of surviving left ventricular muscle columns was not modified by hypophysectomy or GH administration. Ventricular actomyosin concentration was slightly but significantly elevated in hypophysectomized animals, with or without GH. However, “ATP sensitivity” of the extracted actomyosin was markedly depressed by hypophysectomy and partially restored by GH. Differential hormonal regulation of cardiac actin and myosin is suggested.
The Realities of New Principals: Challenges, Joys, and Sorrows

This empirical qualitative study of 62 new principals was conducted over several years to determine what challenges they face, how the principalship compares with their expectations, and what their long-term career aspirations are. The findings indicate that the challenges experienced by new principals pertain to instructional leadership; managerial issues such as budgeting and human resources; and community issues involving climate, politics, and differing expectations from parents. New principals’ job expectations depended on the experiences they had as assistant or vice principals. Finally, few new principals anticipated long-term careers as principals. Most new principals desired district-level positions within 10 years. Implications for preparation and professional development are provided.
Adaptive Neural Networks Control for a Class of Pure-feedback Systems in Discrete-time

In this paper, adaptive neural networks (NNs) control is investigated for a class of nonlinear pure-feedback discrete-time systems by prediction. To overcome the difficulty of nonafflne appearance of control input, the pure-feedback system is transformed into an n-step ahead predictor, and then, implicit function theorem is exploited. NN is employed to approximate the unknown function in the control and the resultant control completely avoids controller singularity problem and achieves semi-global-uniformly-ultimately-boundedness (SGUUB) stability of the closed-loop system. The output tracking error is made within a small neighborhood around zero. The effectiveness of the proposed control approach is demonstrated in the simulation results.
Induction of Cytotoxic T Lymphocyte Antigen 4 (Ctla-4) Restricts Clonal Expansion of Helper T Cells

Cytotoxic T lymphocyte antigen (CTLA)-4 plays an essential role in immunologic homeostasis. How this negative regulator of T cell activation executes its functions has remained controversial. We now provide evidence that CTLA-4 mediates a cell-intrinsic counterbalance to restrict the clonal expansion of proliferating CD4+ T cells. The regulation of CTLA-4 expression and function ensures that, after ∼3 cell divisions of expansion, most progeny will succumb to either proliferative arrest or death over the ensuing three cell divisions. The quantitative precision of the counterbalance hinges on the graded, time-independent induction of CTLA-4 expression during the first three cell divisions. In contrast to the limits imposed on unpolarized cells, T helper type 1 (Th1) and Th2 effector progeny may be rescued from proliferative arrest by interleukin (IL)-12 and IL-4 signaling, respectively, allowing appropriately stimulated progeny to proceed to the stage of tissue homing. These results suggest that the cell-autonomous regulation of CTLA-4 induction may be a central checkpoint of clonal expansion of CD4+ T cells, allowing temporally and spatially restricted growth of progeny to be dictated by the nature of the threat posed to the host.
Personal identification using footstep detection

Footsteps, with different shoes of heels, sneakers, leathers or even bare footed, will appear in different grounds of concrete, wood, etc. To recognize human footsteps is not only the need of surveillance but the home service center also can use this information to understand the motion of people with techniques of sound localization, etc. Thus, if a footstep is discriminable, the application to various fields can be considered. In this paper, the feature extraction of a footstep is investigated. We focused on the mel-cepstrum analysis, walking interval, and the degree of similarity of spectrum envelope. It is shown for personal identification that the performance of the proposed method is effective.
How Much Training Is Needed in One-Bit Massive MIMO Systems at Low SNR?

This paper considers training-based transmissions in massive multi-input multi-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). We assume that each coherent transmission block consists of a pilot training stage and a data transmission stage. The base station (BS) first employs the linear minimum mean-square-error (LMMSE) method to estimate the channel and then uses the maximum-ratio combining (MRC) receiver to detect the data symbols. We first obtain an approximate closed-form expression for the uplink achievable rate in the low SNR region. Then based on the result, we investigate the optimal training length that maximizes the sum spectral efficiency for two cases: i) The training power and the data transmission power are both optimized; ii) The training power and the data transmission power are equal. Numerical results show that, in contrast to conventional massive MIMO systems, the optimal training length in one-bit massive MIMO systems is greater than the number of users and depends on various parameters such as the coherence interval and the average transmit power. Also, unlike conventional systems, it is observed that in terms of sum spectral efficiency, there is relatively little benefit to separately optimizing the training and data power.
A Success-Guided Selection of Expanded Systems for Result-Verifying Nonlinear Solvers

Most result-verifying solvers for nonlinear systems include a branchand-bound algorithmic backbone, complemented with accelerating methods such as constraint propagation, interval Newton, and many others. Often the effectiveness of the accelerators can be improved if one works not only with the given system but also with expanded systems, which are obtained by introducing additional variables for suitable subterms. While reducing the overall number of boxes that must be considered during the solution, applying the accelerators to the (often much larger) expanded systems can increase significantly the time spent on a single box. Therefore a good strategy for deciding which methods to apply to which expanded system is essential for the performance and robustness of the whole solver. We propose a heuristic that selects expanded systems based on performance information gathered during the computations. Numerical experiments show that this new dynamical strategy tends to be superior to a fixed small-to-large traversal (with restarts) of the expanded systems, which has been the default strategy in our nonlinear solver and optimizer SONIC.
Photometric catalog of nearby globular clusters. II. A large homogeneous (V,I) color-magnitude diagram data-base

In this paper we present the second and nal part of a large and photometrically homogeneous CCD color-magnitude diagram (CMD) data base, comprising 52 nearby Galactic globular clusters (GGC) imaged in the V and I bands. The catalog has been collected using only two tele- scopes (one for each hemisphere). The observed clus- ters represent 75% of the known Galactic globulars with (m M)V 16:15 mag, cover most of the globular clus- ter metallicity range ( 2:2 (Fe=H) 0:4), and span Galactocentric distances from 1: 2t o 18: 5k pc. In particular, here we present the CMDs for the 13 GGCs observed in the Northern hemisphere. The remaining 39 Southern hemisphere clusters of the catalog have been presented in a companion paper (Rosenberg et al. 2000). We present the rst CCD color magnitude diagram for NGC 6779 (M 56). All the CMDs extend from at least 2 magnitudes below the turn-o (i.e. Vlim 22) to the tip of the red giant branch. The calibration has been done using a large number of standard stars, and the absolute calibration is reliable to a 0:02 mag level in both lters. This catalog, because of its homogeneity, is expected to represent a useful data base for the measurement of the main absolute and relative parameters characterizing the CMD of GGCs.
Blood pressure responses in healthy older people to 50 g carbohydrate drinks with differing glycaemic effects

The aim of the present study was to determine the effects on blood pressure response of 50 g carbohydrate drinks with differing glycaemic effects in ten healthy elderly subjects (age >65 years; randomized crossover design). Systolic (SBP), diastolic (DBP) and mean arterial (MAP) blood pressure, heart rate and plasma glucose levels were determined following ingestion of equal volumes (379 ml) of water and 50 g carbohydrate drinks with differing reported glycaemic indices (GI) (surrogate marker for glycaemic effect): (1) low-GI: Apple & Cherry Juice; (2) intermediate-GI: Fanta Orange; (3) high-glucose. Glucose (SBP and DBP P<0·001; MAP P=0·005) and Fanta Orange (SBP P=0·005; DBP and MAP P<0·001) ingestion caused a significant decrease in BP whilst blood pressure increased (SBP P=0·008; MAP P=0·005) from baseline following Apple & Cherry Juice ingestion. Water had no significant effect on postprandial blood pressure. Fanta Orange and Apple & Cherry Juice caused similar (P=0·679) glycaemic effects, which were significantly greater than water, but lower than glucose (P<0·001). There was no significant correlation between the glycaemic effect of the carbohydrate drinks and there was no change in blood pressure from baseline (SBP r −0·123, P=0·509; DBP r −0·051, P=0·784; MAP r −0·069, P=0·712). Apple & Cherry Juice and Fanta Orange had similar glycaemic effects, but differing effects on blood pressure. Therefore, it is unlikely that the glycaemic effect of a drink can be used to predict the subsequent cardiovascular response.
CompUXLSA: A computational model in predicting user experience from reviews using Latent Semantic Analysis

In this paper, we proposed a novel method (CompUXLSA) to predict user experience from reviews sentences using Latent Semantic Analysis (LSA). Human uses words to represent or express thoughts. The “word of mouth” could influence others especially through web and social media, which are the common communication tools today. We believe that reviews can be categorized according to user experiences since reviews are the thoughts and opinions from users after they have used certain products. In our works, we intend to mine and predict the user experience of expressed through reviews according to the five behavioral variables: Perceived Ease of Use, Perceived Usefulness, Affects towards Technology, Social Influence and Trust. We apply the state of the art method: Latent Semantic Analysis to build a semantic space and map review sentences to the most similar variable measurement items that adapted from Human Behavior Project to predict their experiences. Besides that, we also proposed a rule based template, SubEx to extract features of subject-experience from reviews to enhance the performance. Based on the results obtained, CompUXLSA had achieved average F-measure of 0.24.
My hands or my mouse: Comparing a tangible and graphical user interface using eye-tracking data

Tangible User Interfaces (TUIs) have drawn the interest of HCI and learning communities because of their potential positive impact on the learning experience. In this paper, we describe a preliminary study of a TUI application for training spatial skills of carpenter apprentices. We designed a tangible interface to perform a CAD modelling activity in a way that resembles what apprentices do in the workspace: shaping a wooden brick through sequential cuts by using a saw. The core of the study is to compare the effects of TUI and GUI on the user experience, by taking advantage of eye-tracking data. We report two main findings: first, the successful employment of eye-gaze tool in TUI research which represents a novelty per-se. Second, a significant impact of the TUI on the user experience which gives some insights about the cognitive benefit of tangibles.
Towards a More Effective Operational Response Arsenic Contamination of Groundwater in South and East Asian Countries Volume Ii Technical Report the World Bank Environment and Social Unit -south Asia Region Water and Sanitation Program (wsp) -south and East Asia

This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank and of the Water and Sanitation Program. The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgement on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.
Preventing complications of central venous catheterization.

Central venous catheters permit the measurement of hemodynamic variables that cannot be measured accurately by noninvasive means. They also allow delivery of medications and nutritional support. More than 15 percent of patients, however, have a serious mechanical, infectious, or thrombotic complication related to the use of a central venous catheter. This review explains strategies for minimizing the frequency of such complications. An accompanying video shows techniques for catheter insertion by the internal jugular and subclavian routes.
Dynamic QoS-aware event sampling for community-based participatory sensing systems

Over the recent years, the proliferation of mobile networking and the increasing capabilities of smartphone devices have led to the development of the "Community-based Participatory Sensing" approach, where users participate in data collection and sharing in a wide range of application areas such as entertainment, transportation and environmental monitoring. This paper develops a participatory sensing system that uses a sampling mechanism that aims to stimulate user participation in dynamic groups that provide services and get compensated for the services they provide. Users participate in the community by sensing and sharing streams of events. The system then uses a sampling mechanism to define a subset of events that preserves the characteristics of the stream data and provides the highest "information gain" to the system, given the budget and resource constraints. Our experimental results illustrate that our approach is practical, efficient and depicts good performance.
Conctruct Validity Assessment of Dundee Ready Educational Environment Measurement (Dreem) in a School of Dentistry

Introduction : Learning environment in educational institutions of medicine and health is an important thing to be evaluated, so it takes a valid and reliable instrument. Dundee ready Educational Environment Measurement (DREEM) is one of the most frequently used instruments to evaluate the learning environment in various countries, including Indonesia. However, some psychometric study cannot prove the construct validity of DREEM. This study aims to assess the construct validity of Indonesian version of the DREEM in Study Program of Dentistry, Faculty of Medicine, University of Sam Ratulangi. Method : A total of 352 medical students were divided into three groups asked to complete the DREEM. Evaluation of the construct validity of DREEM was assessed by calculating the score of internal consistency, testing the validity of the items by Pearson Product Moment Correlation test, and confirmatory factor analysis. Results : 50 items of DREEM proven to have good reliability score (Cronbach alpha 0.883), but the two subscales have lower internal consistency score (alpha Conbach 0.6). Conclusion : Indonesian translation of DREEM proved to be reliable, but the construct validity of this instrument cannot be proven in this study. It is hoped that this DREEM psychometric research continues in various countries as a basis for improving these instruments.
ScaNS : Using Actors for Massive Simulation of Distributed Routing Algorithms

Existing simulators designed for the evaluation of distributed graph algorithms tend to be based on a threaded model of concurrency. This leads to scaling issues when simulating particularly large graphs such as Internet-like graphs or poor utilisation of resources when using large multiprocessor machines. Here, I present a simulator that uses actor-model concurrency to directly model the interactions between nodes in a graph during the simulation of a distributed algorithm. While more closely modelling the behaviour of an abstract network, the actor model brings performance advantages.
DESIGN OF A FUNCTIONAL SIZE MEASUREMENT FOR REAL-TIME SOFTWARE

A requirement for software productivity analysis and estimation is the ability to measure the size of a software product from the user’s viewpoint, that is, from a functional perspective rather than from a technical perspective. One example of such a measurement method is Function Point Analysis (FPA). FPA is now widely used in the Management Information Systems (MIS) domain, where it has become a “de facto” standard. However, FPA has not achieved the same degree of acceptance in other domains of software engineering, such as real-time software. The general opinion is that when FPA is applied to such software the results do not constitute an adequate size measurement of this type of software. This paper reports on a research project carried out to adapt FPA to the specific functional characteristics of real-time software. The proposed extension, called Full Function Points (FFP), is described and the results of field-testing are discussed. This research was conducted using an adaptation of Basili’s framework for empirical research in software engineering and it is described accordingly.
Antiinflammatory effects of salmeterol after inhalation of lipopolysaccharide by healthy volunteers.

RATIONALE Salmeterol is a beta2-adrenoreceptor agonist used in the treatment of obstructive pulmonary disease. Salmeterol inhibits inflammatory responses by neutrophils and mononuclear cells in vitro and in mouse models of lung inflammation in vivo. OBJECTIVE To determine the effect of salmeterol on LPS-induced lung inflammation in humans. METHODS Thirty-two healthy subjects were enrolled in a single-blinded, placebo-controlled study. Subjects inhaled 100 microg salmeterol or placebo (t=-0.5 h) followed by 100 microg LPS or normal saline (t=0 h; n=8/group). Measurements were performed in bronchoalveolar lavage fluid and purified alveolar macrophages obtained 6 h post-challenge. MEASUREMENTS AND MAIN RESULTS Inhalation of LPS was associated with neutrophil influx, neutrophil degranulation (myeloperoxidase, bactericidal/permeability-increasing protein and elastase), release of cytokines (tumor necrosis factor alpha and interleukin 6) and chemokines (interleukin 8, epithelial cell-derived neutrophil attractant 78, macrophage inflammatory proteins 1alpha and 1beta), activation of alveolar macrophages (upregulation of HLA-DR and CD71; enhanced expression of mRNAs for 13 different mediators of inflammation), and protein leakage (all p<0.05 vs. placebo/saline). Pretreatment with salmeterol inhibited LPS-induced neutrophil influx, neutrophil degranulation (myeloperoxidase), tumor necrosis factor alpha release, and HLA-DR expression (all p<0.05 vs. placebo/LPS), while not significantly influencing other responses. CONCLUSION Salmeterol exerts antiinflammatory effects in the pulmonary compartment of humans exposed to LPS.
Hybrid-state driver/vehicle modelling, estimation and prediction

The first part of this study develops a general architecture for estimation and prediction of hybrid-state systems. The proposed system utilizes the hybrid characteristics of decision-behaviour coupling of many systems such as the driver and the vehicle; uses estimates of observable parameters to track instantaneous discrete state and predicts the most likely outcome, depending on the discrete model and the observed behaviour of the continuous subsystem. The proposed method is suitable for the scenarios that involve unknown decisions of other individuals, such as lane changes or intersection precedence/access. In the second part, this paper specifically deals with the implementation of the proposed methodology on an intersection safety system, predicting the vehicle behaviours and potential outcomes through traffic intersection scenarios. Driver intentions are tracked and predicted through vehicle behaviour, and possible combinations of intention predictions for different vehicles are interpreted for the safety of the situation.