Miracle-dz/UniFAR-FTUs huggingface dataset:
A low cost bidirectional Human-Computer Interface

There have been many advances in the development and application of human computer interfaces during the past decade. We were motivated by these successful applications of human computer interfaces to design a low cost device which may also provide the user with a faster training time. In this paper we discuss the design and implementation and testing of the proposed device, and show that it can be fabricated for less than 20 dollars.
Job attitudes and perceptions of exhausted IS/IT professionals: are we burning out valuable human resources?

The concept of work exhaustion (or job burnout) in the management and psychoIogy research literature is reviewed and its applicability to the IS/IT work environment is examined. Data collected from IS/IT professionals and managers in various industries across the U.S. are presented. The results of the study indicate that exhausted IS/IT professionals report significantly lower job satisfaction, lower organizational commitment, and higher intention to leave the job than non-exhausted IS/IT workers. Furthermore, the vast majority (81%) of the exhausted IS/IT workers perceived the cause of their exhaustion to be external and controllable by others in the organization.
Axon diameter and fluctuation in excitability.

A nerve fiber responds with an action potential in a fraction of all trials, if stimulated with identical electrical stimuli at threshold intensity and at a frequency such that the interval between the stimuli is larger than the recovery period (BLAIR and ERLANGER, 1932, 1933; PECHER, 1936). PECHER (1937, 1939) showed that this phenomenon is an inherent property of the nerve fiber. It is not due to variations in external circumstances, viz, stimulus intensity, hence the name, fluctuation in excitability. The sequence of these responses is a haphazard one; the probability of response has the same value each time and is independent of the preceding reactions (VERVEEN, 1960). The probability of response depends on stimulus intensity. PECHER (1939) suggested already the existence of a Gaussian relationship between response probability and stimulus intensity. In previous studies on nerve fibers of frog and of crag-fish (VERVEEN, 1960, 1961) it was shown that these relations approximate the Gaussian type of distribution function. The `threshold' (the mean of the distribution function) depends on stimulus duration : the classic strength-duration relation. It was found that the `spread' (the standard deviation of the distribution function) also depends on stimulus duration. However, the quotient of spread and threshold, the `relative spread' is independent of stimulus duration. It is a measure of the width of the threshold range, relative to the value of the threshold. The relative spread appeared smaller for the fastest conducting axons in the claw of crag-fish than for comparable fibers in the frog sciatic nerve. A difference in axon diameter exists between these two types of axons, apart from differences such as the myelin-sheath. This fact and the suggestion by FATT and KATZ (1952) that membrane noise might depend on axon diameter warranted a further investigation. Stellar nerves of the cuttle-fish (Sepia officinalis) were used for this purpose. These nerves contain axons of widely different diameters (one or two giant axons of about 250 u and a large number of fibers of a much smaller diameter) but all of the same structure (YOUNG, 1936). In this way differences in species and in structure are eliminated.
Towards Analog VLSI Arrays for Nonseparable 3D Spatiotemporal Filtering

We report the development of a new CNN based theoretical framework and its on-going analog VLSI implementation for continuous-time discrete-space spatiotemporal filtering. Our proposed formulation, which stems from the theory of linear cellular neural networks, is capable of realizing a wide range of linear spatiotemporal dynamics. Based on our proposed framework, 3D nonseparable spatiotemporal filters are synthesized. The filters are presented in the form of continuous-time/discrete-space mixed domain transfer functions with responses qualitatively resembling visual cortical bandpass spatiotemporal receptive fields. Analog VLSI building blocks suitable for the implementation of the required spatiotemporal dynamics are presented. Simulation results on AMS 0.35mum process parameters of a 5times5 array, with electrical parameters tuned to realize the spatiotemporal dynamics of one of our synthesized 3D bandpass filters, are presented
5.1 INTRODUCTION

This chapter describes the application of a grammatically-based Genetic Programming system to discover rainfall-runoff relationships for two vastly different catchments. A context-free grammar is used to define the search space for the mathematical language used to express the evolving programs. A daily time series of rainfall-runoff is used to train the evolving population. A deterministic lumped parameter model, based on the unit hydrograph, is compared with the results of the evolved models on an independent data set. The favourable results of the Genetic Programming approach show that machine learning techniques are potentially a useful tool for developing hydrological models, especially when the relationship between rainfall and runoff is poor.
Virtual Reality–Assisted Heart Rate Variability Biofeedback as a Strategy to Improve Golf Performance: A Case Study

Growing evidence suggests that Heart Rate Variability (HRV) biofeedback (BFB) may improve sport performance by helping athletes cope with the stress of competition. This study sought to identify whether HRV BFB procedure impacted psychological, physiological, and sport performance of a collegiate golfer. This individual volunteered to participate in 10 weeks of HRV BFB training according to the protocol developed by Leher, Vaschillo, and Vaschillo (2000). During the first, fourth, seventh, and tenth weeks of the study, the golfer and lead author met at a virtual reality golf center to practice skills for breathing at resonance frequency during golf performance. Golf performance and HR were recorded during nine holes of virtual reality golf before and after 10 weeks of HRV BFB training. Self-report questionnaires were administered also before and after HRV BFB training to measure symptoms of anxiety, stress, and sensation seeking. Physiological measures, including HRV and respiration rate, were recorded in.
Long-term auto-correlation statistics based voice activity detection for strong noisy speech

This paper proposes a voice activity detection (VAD) algorithm based on a novel long-term metric. By assuming that the most significant difference between noisy speech and non-speech is the harmonicity of the noisy speech spectrum caused by human nature, the long-term auto-correlation statistics (LTACS) measure is designed to be shown as a powerful metric used in VAD. The LTACS measure is calculated among several successive frames around the concerned frame and it represents the significance of harmonics of the signal spectrum over a long term rather than a short term. A novel LTACS-based VAD algorithm is derived by jointly making use of the minimum operator to reduce non-speech variability and of then calculating variance to detect speech. Simulative comparisons with four standardized VAD algorithms (ETSI adaptive multi-rate option 1 and 2, ETSI advanced front-end and G.729 Annex B) as well as three former proposed VAD algorithms show that the proposed LTACS-based VAD algorithm achieves the best performance under all SNR conditions, especially in strong noisy environments (e.g., SNR is -5dB or -10dB).
Watson-Aided Non-Linear Problem-Oriented Clinical Visit Preparation on Tablet Computer

Tablet computers have been growing in popularity and finding their way to workspace. Their ubiquity is attributable to their ease of use and portability, also applicable to hospital work environment. We have designed an Electronic Medical Record (EMR) application for clinical visit preparation task on tablet computers. There are many design challenges due to the limited form factor for both input and output. According to our interviews with physicians, our solution utilizes IBM Watson’s machine learning ability to analyze unstructured clinical notes and create a relation graph of medical entities. With the medical knowledge graph, the system enables easy relation retrieval to show only relevant information as needed in simple and easy-to-understand displays. We informally evaluated our system by walking through sample visit preparation steps from a physician.
Optimization of forming load and variables in deep drawing process for automotive cup using Genetic Algorithm

1 Abstract Sheet metal forming is a significant manufacturing process for producing a large variety of automotive parts and aerospace parts as well as consumer products. Deep drawing is a compression-tension forming process involving wide spectrum of operations and flow conditions. The result of the process depends on the large number of parameters and their interdependence. With the developments in the technology the design of deep drawing is an art than science still today . It depends on the knowledge and experience of the design engineer only. The selection of various parameters is still based on trial and error methods. In this paper the authors presents a new approach to optimize the geometry parameters of circular components, process parameters such as blank holder pressure and coefficient of friction etc. The optimization problem has been formulated with the objective of optimizing the maximum forming load required in deep drawing. Genetic algorithm is used for the optimization purpose to minimize the drawing load and to optimize the process parameters. A finite element analysis simulation software fast form advanced is used for the validations of the results after optimization. The results obtained for the automotive cup shows the potential interest of the proposed approach.
Pooling SAX-BoP Approaches with Boosting to Classify Multivariate Synchronous Physiological Time Series Data

As the current standard practice of manually recorded vital signs through a few hours is giving way to continuous, automated measurement of high resolution vital signs, it brings a tremendous opportunity to predict patient outcomes and help to improve the early care. However, making predictions in an effective way is fairly challenging, because high resolution vital signs data are multivariate, massive and noisy. Inspired by the max-pooling approaches in Convolutional Neural Networks (CNN), we propose extensions of vanilla SAX-BoP approach, called Pooling SAX-BoP to successfully predict patient outcomes from multivariate synchronous vital signs data. Our experiments on two standard datasets demonstrate the Pooling SAX-BoP approaches are competitive with the current state-of-the-arts on multivariate time series classification problems. We also integrate Boosting algorithm as one of the most powerful ensemble learning approaches on the BoP representations to further improve the performance. Our experimental results on the clinical data demonstrate that our methods are accurate and stable for classifying multivariate synchronous vital signs time series data
Nerve growth factor-induced hyperalgesia in the neonatal and adult rat

Recently, we have shown that the interaction between NGF and sensory neurons in early postnatal periods is restricted to nociceptive afferents (Ritter et al., 1991; Lewin et al., 1992a; Ritter and Mendell, 1992). Here we show that administration of excess NGF to neonatal or mature animals can lead to a profound behavioral hyperalgesia. Neonatal NGF treatment (postnatal day 0–14) resulted in a profound mechanical hyperalgesia that persisted until the animals had reached maturity (6 weeks of age). This hyperalgesia could be explained by an NGF-mediated sensitization of A delta nociceptive afferents to mechanical stimuli. This peripheral sensitization wore off with a time course similar to that of the behavior hyperalgesia. Treatment of animals from the second postnatal week until 5 weeks of age (juveniles) led to a very similar behavioral hyperalgesia; however, there was no corresponding sensitization of A delta nociceptors to mechanical stimuli. Finally, one group of adult animals (5 weeks old) was treated daily with single injections of NGF for between 1 and 4 d. Within 24 hr after the first NGF injection these animals developed a mechanical hyperalgesia of the same magnitude seen after neonatal and juvenile NGF treatments. No sensitization of A delta nociceptive afferents was observed in these animals. In addition to the mechanical hyperalgesia, the animals also developed a heat hyperalgesia after one injection of NGF. The heat hyperalgesia was apparent within 15 min after the injection; however, signs of mechanical hyperalgesia were not seen until 6 hr after the injection. In conclusion, it appears that the NGF- induced mechanical hyperalgesia is brought about by different mechanisms in neonatal and adult rats. Furthermore, in adult animals the NGF-induced mechanical and heat hyperalgesia also appear to be attributable to two different mechanisms. The mechanical hyperalgesia may be due to central changes (see Lewin et al., 1992b), whereas the heat hyperalgesia is likely to result at least in part from the sensitization of peripheral receptors to heat.
Social Spam Discovery Using Bayesian Network Classifiers Based on Feature Extractions

People always communicate with each other through social networking services (SNSs). However they often receive various kinds of unwelcomed messages that can be requests from uncomfortable friends or may be advertisements. In this paper, we defined these messages as "social spams", and suggested new classification method to detect them. By characterizing the problem of discovering social spams which frequently occurs in current popular SNSs, we extracted and exploited novel features that had not shown in the existing E-mail or web spamming prevention techniques. Our proposal for collecting various features such as behavior, celebrity, trust, common interest, etc. could incrementally been updated for SNS users. We modified the existing well-known classification techniques such as Bayesian network classifiers (BNCs) to customize for SNS features. To make decision efficiently, we computed Katz or trust scores with only part of updated network topologies.
The overview of Horticultural growth the role of horticulture in Tamenglong District : a survey account of ten villages in the Tamenglong District , Manipur State

his paper is devoted to an overview of literatures so far review related to role of horticulture in relation to historical background, international, national, regional and state issues with special reference to Tamenglong district. Distinguished scholars, thinkers, horticultural scientists, government and nongovernmental organization have mentioned on the importance of horticulture and its allied activities. Intensive and comprehensive overviewed is done concerning to hilly and mountainous regions along with rural development issues. This chapter tries to see the gap in the literature and also throw some light on the already existed literature on the topic of my research areas and an attempt is made to assess what is left undone, so that new things and current research issues can be connected with the present times. It also includes the survey account of ten villages in Tamenglong District, Manipur.
General aspects of Trefftz method and relations to error estimation of finite element approximations

In this paper a guaranteed upper bound of the global discretization error in linear elastic finite element approximations is presented, based on a generalized Trefftz functional. Therefore, the general concept of complementary energy functionals and the corresponding approximation methods of Ritz, Trefftz, the method of orthogonal projection and the hypercircle method are briefly outlined. Furthermore, it is shown how to use a generalized Trefftz functional to solve a Neumann problem in linear elasticity. Based on an implicit a posteriori error estimator within the finite element method, using equilibrated local Neumann problems, the generalized Trefftz functional yields a computable guaranteed upper bound of the discretization error without multiplicative constants.
INTELLIGENT OPPONENTS FOR VIRTUAL REALITY TRAINERS

Offensive urban combat is one of the most difficult tasks soldiers are called upon to perform (USMC 1998). Urban combat is characterized by building-to-building and room-to-room fighting, and even a vastly outnumbered defensive force can inflict significant casualties on attacking forces. Effective, frequent training is an essential element in reducing casualties in urban combat. However, training in urban environments is costly and resource constrained (due, in part, to the terrain needed for training).
Nano-Objects and Ions in Liquid Crystals: Ion Trapping Effect and Related Phenomena

The presence of ions in liquid crystals is one of the grand challenges that hinder the application of liquid crystals in various devices, which include advanced 3-D and flexible displays, tunable lenses, etc. Not only do they compromise the overall performance of liquid crystal devices, ions are also responsible for slow response, image sticking, and image flickering, as well as many other negative effects. Even highly purified liquid crystal materials can get contaminated during the manufacturing process. Moreover, liquid crystals can degrade over time and generate ions. All of these factors raise the bar for their quality control, and increase the manufacturing cost of liquid crystal products. A decade of dedicated research has paved the way to the solution of the issues mentioned above through merging liquid crystals and nanotechnology. Nano-objects (guests) that are embedded in the liquid crystals (hosts) can trap ions, which decreases the ion concentration and electrical conductivity, and improves the electro-optical response of the host. In this paper, we (i) review recently published works reporting the effects of nanoscale dopants on the electrical properties of liquid crystals; and (ii) identify the most promising inorganic and organic nanomaterials suitable to capture ions in liquid crystals.
A Hidden Markov Model based efficient next best viewpoint planning for autonomous exploration

A next best viewpoint planning algorithm based on Hidden Markov Model (HMM) was presented for autonomous exploration. The grid map and probabilistic assessment model based on HMM was established to evaluate the next best exploration perspective. Leveraging the relative information entropy, the maximum information gain of candidate viewpoints were assessed. After the establishment of the actual scene graph rule, the state transfer matrix and observation occupied state transition matrix were derived. Used Bayesian filtering to update the probabilistic grid diagram, the path planning was selected from starting point to the maximum information return point. By simulation experiment scene of different complexity, the efficiency and its good robustness was confirmed.
ezDI's Semantics-Enhanced Linguistic, NLP, and ML Approach for Health Informatics

ezDI uses large and extensive knowledge graph to enhance linguistics, NLP and ML techniques to improve structured data extraction from millions of EMR records. It then normalizes it, and maps it with various computer-processable nomenclature such as SNOMED-CT, RxNorm, ICD9, ICD-10, CPT, and LOINC. Furthermore, it applies advanced reasoning that exploited domainspecific and hierarchical relationships among entities in the knowledge graph to make the data actionable. These capabilities are part of its highly scalable AWS deployed heath intelligence platform that support healthcare informatics applications, including Computer Assisted Coding (CAC), Computerized Document Improvement (CDI), compliance and audit, and core measures and utilization, as well as support improved decision making that involve identification of patients at risk, patterns in diseases, outcome prediction, etc. This paper focuses on the key role of its semantic approach and techniques.
TERMINOLOGY CHOICE IN GENERATIVE ACQUISITION RESEARCH

Abstract Pascual y Cabo and Rothman (2012) and Kupisch and Rothman (2018) argue against the use of term incomplete to characterize the grammars of heritage speakers, claiming that it reflects a negative evaluation of the linguistic knowledge of these bilingual speakers. We examine the reasons for and against the use of “incomplete” across acquisition contexts and argue that its use is legitimate on both theoretical and empirical grounds. Our goal is to present arguments for using the term, not to evaluate the scientific validity of incomplete acquisition over other possible accounts. Although our conclusion is that the term should not be abandoned, we advocate a position whereby researchers consider the possible negative impact of the terminology they use and how they use it. This position aims to resolve the tension between the need to prioritize scientific effectiveness and the need to avoid terminology that can be negatively misconstrued by the general public.
Vocal Fold Vibration and Voice Quality

There have been various methods proposed for diagnosing laryngeal pathology by analyzing the pathological voice. However, even if two diagnoses are the same, the voice quality might not be the same. In other words, it is difficult to diagnose laryngeal pathology only by acoustic parameters. In this study, we analyze the vibration patterns seen in various pathological cases to explain pathological voice quality.
Aliso: A Journal of Systematic and Floristic Botany Aliso: A Journal of Systematic and Floristic Botany Tracheid Dimorphism: A New Pathway in Evolution of Imperforate Tracheid Dimorphism: A New Pathway in Evolution of Imperforate Tracheary Elements Tracheary Elements

Certain dicotyledon families characteristically have tracheids as their imperforate tracheary element type. Of these, six families are anomalous by having septate (or nonseptate but living) fiber-tracheids or libriform fibers coexisting with the tracheids in some species or genera (Austrobaileyaceae, Celas traceae, Convolvulaceae, Ericaceae, and Grossulariaceae, and Rosaceae). Data from the literature and original data on wood anatomy of these families are presented. A theory of tracheid dimorphism is developed to account for these instances oftracheids combined with fiber-tracheids or libriform fibers. According to this theory, septate or living fiber-tracheids or libriform fibers are produced in addition to tracheids, starting with ancestors that contain tracheids as the only imperforate tracheary element type, in response to selection for a rapidly increased photosynthate storage capacity, while maintaining the advantage oftracheids in providing conductive safety. Borders are phyletically lost rapidly on the septate (or nonseptate but living) imperforate tracheary elements because they are not water-conducting cells. Genera cited in this study can be ranged into a phyletic series with respect to differentiation from the hypothetical monomorphic-tracheid ancestors with respect to (I) loss of borders on pits of the septate or living elements; (2) distribution of tracheids with respect to vessels; and (3) retention of axial parenchyma. Austrobaileya is the most primitive genus in these respects, while genera such as Holodiscus and Spiraea are specialized . Tracheid dimorphism is compared to vessel dimorphism, fiber-tracheid dimorphism, fiber dimorphism, and the dimorphism related to origin of vessels. All these pathways except the last named one are confined to small numbers offamilies, and are considered minor trends superimposed on the major trends described by I. W. Bailey and coworkers. Basic to all of the dimorphic behaviors described is selection for two divergent cell types as a way ofperforming two distinctive wood functions.