Miracle-dz/UniFAR-FTUs huggingface dataset:
Bandwidth Enhancement of 4 GHz Probe Fed Rectangle Microstrip Patch Antenna with Diagonal DGS Technique for Wi-Fi Applications

Microstrip antenna is extensively used in Wireless communication and Wi-Fi communications above 1GHz. The demand of increased wireless Wi-Fi communication applications, needs increase in bandwidth, gain and efficiency of microstrip antenna. Microstrip antenna is a low profile antenna but has narrow bandwidth, low gain and efficiency. In this paper a micro strip antenna is designed with 1.6mm, 3.2mm and 4.8mm FR-4 thickness substrate material. The bandwidth was found to be 140MHz, 240MHz and 400MHz. The bandwidth requirement for 4GHz Antenna for Wi-Fi communication is 600MHz(3.6 to 4.2GHz). Hence only with increasing thickness of antenna is not sufficient for Wi-Fi application. Therefore diagonal DGS(DDGS) technique is applied on 3.2mm thickness and 4.8mm thickness FR-4 antennas. This resulted in enhancement bandwidth of 1850MHz (1.85GHz) from 140MHz (1222% ) and an radiation efficiency of 88.6% in 3.2mm thickness with DDGS and 1640MHz (1.64GHz) from 140MHZ (1071%) and an radiation efficiency of 78.6% in 4.8mm thickness with DDGS. Both meets the requirement of Wi-Fi application. But gain and S11 was found to be more in 3.2mm thickness with DDGS FR-4 antenna than 4.8mm thickness with DDGS FR-4 antenna. Hence 3.2mm thickness FR-4 with DDGS antenna provides low cost, simple solution for 4GHz Wi-Fi application.
Fe b 20 08 UWThPh-2008-4 The oblique parameters in multi-Higgs-doublet models

We present general expressions for the oblique parameters S, T , U , V , W , and X in the SU(2)×U(1) electroweak model with an arbitrary number of scalar SU(2) doublets, with hypercharge ±1/2, and an arbitrary number of scalar SU(2) singlets. E-mail: walter.grimus@univie.ac. at E-mail: balio@cftp.ist. utl.pt E-mail: omo@hib.no E-mail: per.osland@ift.uib. no 1
Spatial Concepts for Hydrography Ontology Alignment

The publication of multiple hydrography ontologies has demonstrated that such applied designs will inevitably result in differences based on varying project perspectives and objectives. The alignment of different models offers the opportunity to link databases for multiple purposes, though the way to do that has not been previously demonstrated. This paper describes an approach to geospatial ontology alignment based on relative spatial relations. Three hydrography ontologies were selected for the manual alignment with the objective to identify a general approach leading to harmonizing differences and expanding capabilities. Some aspects of ontologies were aligned with established approaches of matching annotation properties such as labels or synonyms. In other cases, subclass relations were aligned through the application of standard Resource Development Framework (RDF) vocabularies that support inference. The remaining challenges required deeper semantic analysis. The consistent concept that supported the semantic alignments of designs was spatial relations that are evident through the specification of triple subgraphs. Included are hydrographic features as landform slope enabling the collection and containment of surface water; the extension of a basic feature pattern to form a network enabled by inference on triple properties; and applied hydrography such as engineered features through an upper ontology pattern. The Cartesian product of an instance matrix is proposed as the approach for testing these spatial relations on ontology class sets.
The effect of adherence to statin therapy on cardiovascular mortality and falsification end-points in the Netherlands

Background: To determine the clinical effectiveness of statins on cardiovascular mortality in practice, observational studies are needed. Control for confounding is essential in any observational study. Falsification end-points may be useful to determine if bias is present after adjustment has taken place. Methods and results: We followed starters on statin therapy in the Netherlands aged 46 to 100 years over the period 1996 to 2012, from initiation of statin therapy until cardiovascular mortality or censoring. Within this group (n = 49,688, up to 16 years of follow-up), we estimated the effect of adherence to statin therapy (0 = completely non-adherent, 1 = fully adherent) on ischemic heart disease and cerebrovascular disease (ICD10-codes I20-I25 and I60-I69) as well as respiratory and endocrine disease mortality (ICD10-codes J00-J99 and E00-E90) as falsification end points, controlling for demographic factors, socio-economic factors, birth cohort, adherence to other cardiovascular medications, and diabetes using time-varying Cox regression models. Falsification end-points indicated that a simpler model was less biased than a model with more controls. Adherence to statins appeared to be protective against cardiovascular mortality (HR: 0.70, 95% CI 0.61 to 0.81). Conclusion: Falsification end-points helped detect overadjustment bias or bias due to competing risks, and thereby proved to be a useful technique in such a complex setting. Bijlsma MJ, Vansteelandt S, Janssen F, Hak E. Submitted.
Wrist-Worn Systems for Activity State Recognition: Evaluation of Challenges and Benefits

Author(s): Nematihosseinabadi, Ebrahim | Advisor(s): Sarrafzadeh, Majid | Abstract: This dissertation investigates the limitation and challenges of wrist-worn sensing in activity state recognition including posture and gait quality inference. In spite of all the benefits that come with wrist-worn sensing systems, there are many challenges in inferring activities using them. The most important challenge is the high rate of false positive due to unwanted hand motion when the system is worn on the wrist. Another important challenge is the limitation on the power budget and processing capabilities of a wrist-worn device. Being far from the Center of Mass (COM), inferring posture and gait seem to be a very challenging problem using wrist data. This dissertation tries to provide a deep investigation on these challenges and propose ways to mitigate them. Different time series analysis methods are employed to serve for improvement in both accuracy and power consumption of activity state recognition. Along the way, we introduce some of the systems and algorithms that were built around these ideas and how they can be helpful in tackling the challenges of wrist-worn sensing systems, when it comes to activity state recognition.
Lubricious Thin-Film Coatings for Forging Applications : A Literature Review

One of the industry-wide objectives identified by the Forging Industry Association (FIA) is the reduction of lubricant use during forging. Toward that goal, FIERF funded a research effort at the Colorado School of Mines (CSM) to test permanent PVD coatings that may minimize lubricant use during forging. The initial focus of the project is to develop a laboratory test to quantitatively measure the impact of permanent PVD coatings on the coefficient of friction between aluminum or steel workpieces and steel tooling. The first stage of the project has been to perform a literature review to understand the state-of-the-art in lubricous PVD coatings. Table 1 gives an overview of the findings of this literature review, and lists the various types of liquid and solid lubricants available for forging dies, including lubricating mechanisms and temperature limits of various types of lubricants. Table 1: Summary of current lubricants and potential coatings for forging dies. Lubricants and Mechanisms Material Examples Temperature Range Traditional liquid lubricants Oils and greases <250 oC Atomic structures that can easily shear MoS2, graphite <300 oC PVD hard coatings (can contain softer lubricating phases) CrN, AlCrN, TiAlN, TiCN, diamond-like-carbon, i-Kote <500-800oC depending upon coating Soft metals within hard coatings that diffuse to contact surfaces Ag, Au or Cu encapsulated in hard coatings such as TiN, CrN, VN, YSZ, CrAlN 300 500oC Lubricious oxides V2O5, MoO3 500 1000oC
Entrepreneurial Intention Among College Students : An Empirical Study

IT (Information Technology) entrepreneurs have been contributing greatly to economic growth and job creation. Despite its importance, IT entrepreneurship remains understudied in business research. Particularly, the study of IT entrepreneurial behavior has been ignored in both Information Systems (IS) and entrepreneurship disciplines. Utilizing the social cognitive career theory (SCCT), this study, for the first, time investigates empirically IT entrepreneurial behavior among college students. The results indicate that students’ IT entrepreneurial intention is determined directly by their expected outcomes, social influence, and self-efficacy. The study concludes with recommendations for IS education in business schools.
Exploring aspects of cognitive development andmental health awareness as part of healthpromotional goal in snooker

The aim of the present study is to ascertain whether playing snooker sustains development of mental cognition from acquiring and developing knowledge of the game of snooker for the ‘everyday snooker player’ that plays snooker as a hobby or pastime. A total of 1,352 participants has taken part in the Snooker Insight Survey and responded to a variety of questions that covered different aspects of snooker. This study investigated some of the theoretical concepts of cognitive development, mental concentration and other underpinning aspects of mental health in sport, with a view of looking specifically through the lens of ‘everyday snooker player’. Outcomes suggest that the game can be considered as a positive health promotional activity, which can also help to develop an individual knowledge, concentration and focus as an activity of living, as well as proposing that the game of snooker is being used as an encouraging and supportive activity that can potentially benefit an individual’s mental health and well-being. This work poses an opportunity for further research relating to health and snooker in the future, especially to explore a variety of dimensions associated with snooker from an array of topics that centre on a very broad and holistic scope around issues in health and social care needs of individuals and communities.
Application of Optimal Tolerance Parameters for Variogram Calculation

For experimental variogram calculation in the case of irregular data set (in terms of spatial configurations of the data), some tolerance parameters are defined in order to get a reliable variogram with enough number of pairs. These tolerance parameters can be optimized by using the methodology presented in paper 121 of this annual report. In this paper the application of optimized tolerance parameters for experimental variogram calculation is presented. Two different example will be presented the first one is a synthetic data set and the second one is Amoco data (2D and 3D).
Adventitious Root Production of Centella asiatica in Response to Plant Growth Regulators and Sucrose Concentrations

Centella asiatica is an important medicinal plant commonly used for wound healing purposes and as a brain tonic. A study was undertaken to investigate the effects of different plant growth regulators at various concentrations on adventitious root induction from the leaf and petiole explants. Full strength Murashige and Skoog (MS) medium supplemented with indole-3-acetic acid (IAA), indole-3butyric acid (IBA), and -naphthaleneacetic acid (NAA) at 0, 1, 3, 5, and 7 mg/L were used in this study. All treatments were kept in the dark and data collection was performed after 8 weeks of culture. No adventitious roots formed in the control medium devoid of any plant growth regulators (PGRs). Among the PGRs used, IBA showed the best adventitious root formation for both explants, followed by NAA, and IAA. The highest percentage of explants forming roots, number of roots per explant and longest roots formed from leaf explants was observed in 7 mg/L IBA. Meanwhile, IBA at 5 mg/L showed better rooting efficiency for petiole explants. Petiole explants were better than leaf explant for inducing adventitious roots. The effects of sucrose at 0, 1, 2, 3, 4, 5, 6, and 7% (w/v) on adventitious root induction from petiole explants were also assessed. No adventitious roots formed in MS media without sucrose. Sucrose at 4% and 5 mg/L of IBA showed the highest number of roots per explant and the longest roots. _____________________________________________________________________________________________________________
On the General Solution for the Two-Dimensional Electrical Impedance Equation in Terms of Taylor Series in Formal Powers

We study the general solution of the twodimensional Electrical Impedance Equation in terms of Taylor series in formal powers, for the case when the electrical conductivity is a separable-variables function. We use the elements of Quaternionic Analysis in order to rewrite the Electrical Impedance Equation into a Vekua equation, for which it is possible to express the general solution using the elements of Bers Pseudoanalytic Function Theory. We nally discuss the contribution of thess results for approaching solutions of the Electrical Impedance Tomography problem. Index TermsElectrical impedance, pseudoanalytic functions, quaternions, tomography.
Error-DependentDataScheduling inResource-Aware Multi-LoopNetworkedControl Systems ⋆

In this work we address the problem of event-based data scheduling for multiple heterogeneous LTI control loops over a shared resource-constrained communication network. We introduce a novel bi-character scheduling scheme, which dynamically prioritizes the channel access at each time-step according to an error-dependent priority measure. Given local error thresholds for each control loop, the scheduling policy deterministically blocks the transmission from sub-systems with lower error values. The scheduler then allocates the limited communication resource probabilistically among the eligible sub-systems based on a prioritized measure. We prove stochastic stability of the networked control system under the proposed scheduler in terms of f ergodicity of the overall network-induced error. Uniform analytical performance bounds are further derived for an average cost function comprised of a quadratic error term and transmission penalty. The simulation results show that our approach results in a significant reduction of the aggregate network-induced error variance compared to the conventional scheduling protocols.
Protein Query Language : A Novel Approach

This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner, utilizing the work of Patel [1] and introducing constructs in principal similar to those in RoldanGarcia [2]. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein characteristics such as methyl donated hydrogen bond interactions, minimum and maximum phi and psi angles, repulsive forces, CH/Pi calculations, and other pertinent factors. In addition, front end applications can be developed to support retrieving, transforming, and preprocessing of information from the Research Collaboratory for Structural Bioinformatics (RCSB) [3] into the backend data repository.
Routine Test Analysis in Power Transformers by Using Created Firefly Algorithm and Computer Program

Faults that occur during the transmission and distribution of energy usually occur in power transformers. The interruptions in the transformers, the voltage drops, the sudden interventions in the over currents cause important problems. For this reason, power transmission and distribution companies should perform routine tests and transformers more effectively. In this study, transformer routine tests have been analyzed by using the generated firefly algorithm. Data from sensor and measuring instruments in the transformer units obtained. A data collection system consisting of hardware and software has been created to collect the data and transfer it to the computer center. Electronic hardware has been utilized for transferring data from sensors connected to different units of transformer to computer. The data received from the transformer has been synchronized with the PIC microcontrollers in the designed circuit and transferred quickly and safely to the computer by means of the USB port. An interface written in Visual Studio programming language has been created in order to present the analog signals in digital format to the user in a visual way. The voltage values obtained from the sensors have been displayed on the Transformer Routine Test Analysis Program screen created on the computer. The measurement accuracy and success of the designed software and hardware have been tested on real system. The data obtained showed that the system is successful. Thus, remote monitoring, control and routine testing of transformers with the software and hardware created have been realized. INDEX TERMS Transformers, power transformers, animal behavior, test.
Downscaling dense rain gauge networks with short historical records using Bayesian networks

Statistical downscaling is a mature field with many applications in different socioeconomic sectors —such as hydrology— which require local weather data. Standard downscaling methods rely on long historical records (tens of years) typically associated with sparse networks of low spatial resolution (e.g. the SYNOP network). Thus, these methods are not suitable for modern station networks with shorter temporal coverage (years) and, typically, higher spatial resolution. In this paper, we present a new technique to combine both sources of information into a single downscaling model, connecting the modern to the historical stations in a hierarchical way, thus avoiding overfiting. To this aim we use Bayesian networks to graphically represent the variables and their dependencies defining an underlying joint probabilistic model; we introduce a new automatic learning algorithm method to infer the model with an appropriate hierarchy from data. The resulting model is shown to improve the results of other state of the art methods, such as the Näıve model or a simple nearest neighbors method. In particular we consider precipitation occurrence and focus on probabilistic weather-typing downscaling techniques.
T HE INTERACTION BETWEEN AFFIXES AND BASES : THE CASE OF THE G REEK VERB SUFFIXES

In the first part of this study the semantics of the Greek verb-deriving suffixes -íz(o), -én(o), -év(o), -ón(o), -(i)áz(o), and -ín(o) are presented. The description is based on an empirical analysis of data extracted from 28 interviews conducted with native speakers of Greek, in Athens, Greece. In the analysis Rochelle's Lieber's (2004) theoretical framework is used. In the second part are presented the properties of an interfering socio-expressive level of meaning, i.e. the 'socio-expressive tier', on the example of -(i)áz(o) verbs. The analysis suggests the coordination of Lieber's denotational structures with the author's socio-expressive structures so that a base can be selected by a particular suffix.
A State Transition Model for Policy Specification

The model of policies used in a variety of computer systems management and security domains has typically followed the paradigm of if-then-else statements. While the use of such statements has resulted in significant progress in the field of policy based systems, their use has also entailed significant effort in defining the policy rules and system models needed for employing policy based technologies. Better models of policy specification can ease some of the difficulties associated with building policy based systems. In this paper, we introduce a new model for specifying policies, based on a user defined state transition diagram describing system behavior, and demonstrate how this model can be employed advantageously in managing policies.
Children and adolescents : Excessive consumption of energy drinks Increases health risk for cardiovascular system

In addition to other ingredients, energy drinks contain caffeine, usually in quantities of 80 milligrams (mg) per 250 millilitre (ml) can. In moderate quantities, caffeine can have a positive effect, such as enhancing attention levels. High doses, on the other hand, can have undesired effects, such as nervousness, insomnia, gastrointestinal complaints, palpitations and increased blood pressure.
M ay 2 01 9 Classification with imperfect training labels

We study the effect of imperfect training data labels on the performance of classification methods. In a general setting, where the probability that an observation in the training dataset is mislabelled may depend on both the feature vector and the true label, we bound the excess risk of an arbitrary classifier trained with imperfect labels in terms of its excess risk for predicting a noisy label. This reveals conditions under which a classifier trained with imperfect labels remains consistent for classifying uncorrupted test data points. Furthermore, under stronger conditions, we derive detailed asymptotic properties for the popular k-nearest neighbour (knn), support vector machine (SVM) and linear discriminant analysis (LDA) classifiers. One consequence of these results is that the knn and SVM classifiers are robust to imperfect training labels, in the sense that the rate of convergence of the excess risks of these classifiers remains unchanged; in fact, our theoretical and empirical results even show that in some cases, imperfect labels may improve the performance of these methods. On the other hand, the LDA classifier is shown to be typically inconsistent in the presence of label noise unless the prior probabilities of each class are equal. Our theoretical results are supported by a simulation study.
Dynamic convolutional neural network for eliminating item sparse data on recommender system

Several efforts have been conducted to handle sparse product rating in e-commerce recommender system. One of them is the inclusion of texts such as product review, abstract, product description, and synopsis. Later, it converted to become rating value. Previous researches have tried to extract these texts based on bag of word and word order. However, this approach was given misunderstanding of text description of products. This research proposes a novel Dynamic Convolutional Neural Network (DCNN) to improve meaning accuracy of product review on a collaborative filtering recommender system. DCNN was used to eliminate item sparse data on text product review while the accuracy level was measured by Root Mean Squared Error (RMSE). The result shows that DCNN has outperformed the other previous methods.