Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining Hillslope Diffusion Rates in a Boreal Forest: Quaternary Fluvial Terraces in the Nenana River Valley, Central Alaska Range

s and Programs v.45, n.7, Ref: Abstract No: 227630 Bemis, S.P., Walker, L.A. , Burkett, C. , and DeVore, J.R. , 2013, Use of 3D models derived from handheld photography in paleoseismology, Digital Poster, GSA Abstracts with Program, v. 45, n.7, Ref: Abstract No: 233688 DeVore, J.R. , Bemis, S.P., and Walker, L.A. , 2012, Evidence for post‐26 ka displacement of the Northern Foothills thrust at the Nenana River, Alaska: Eos (Transactions of the American Geophysical Union), Abstract T11A‐2552. Walker, L.A. , 2009, The Eel Project, Dutchess Watershed Webpage, http://www.dutchesswatersheds. org/research/175‐the‐eel‐project Vojnovic, Igor, ed. 2011. Favelas, Urban Renewal, and Guanabara Bay: Environmental justice and Sustainability in Rio de Janeiro,” in Sustainability: A Global Urban Context. Michigan State University Press. (Maps made by Laurel Walker) Student Full Name: Laurel Anne Walker
Does Food Stamp Receipt Mediate the Relationship Between Food Insufficiency and Mental Health

Although the Food Stamp Program is the largest entitlement program remaining in the social safety net, comparatively little is known about the potential benefits that the program may confer on recipients. In this paper we examine an important dimension of well being, mental health, and the extent to which participation in the Food Stamp Program may attenuate the effect of food insufficiency on mental health status. Using data from a nationally representative sample of families in the 2001 Panel Study of Income Dynamics (PSID) we model the probability of being severely emotionally distressed as a function of food insufficiency and other known risk factors for poor mental health. We allow participation in the Food Stamp Program to have a direct impact on mental health, and then test whether food stamp participation mediates the effect of food insufficiency on emotional distress. Our model admits the possibility for simultaneity between food insufficiency, food stamp participation, and mental health status, and thus we employ an instrumental variables estimator in our analysis. We find that food insufficiency has a sizable deleterious effect on the chances of poor mental health, but that participation in the Food Stamp Program mitigates this negative effect between 20 and 50 percent depending on the ex ante risk of emotional distress. This research provides the first evidence that the Food Stamp Program has an important positive spill-over effect on mental health through its mediation of household food insufficiency.
THE HERMENEUTIC AND THE ATLAS.TI SOFTWARE: A PROMISING UNION

Objective: to describe a possible association of hermeneutic analysis based on Jürgen Habermas and Paul Ricoeur with the main functionalities of Atlas.ti software. Method: theoretical-methodological reflection that aims to describe a possible association of hermeneutic analysis based on Jürgen Habermas and Paul Ricoeur with the main functionalities of Atlas.ti software. Results: the software is an important tool which facilitates the storage and analysis of data, contributing to the challenge of providing quality and credibility in qualitative studies. The use of the software proved to be suitable for the use in approaches such as hermeneutics, it also saves time and facilitates the organization and analysis of data. Conclusion: Atlas.ti has significant potential when used with comprehensive approaches, such as hermeneutics, and requires the same attention as for other qualitative approaches. DESCRIPTORS: Qualitative research. Hermeneutics. Software. Data analysis. A HERMENÊUTICA E O SOFTWARE ATLAS.TI: UNIÃO PROMISSORA
Accuracy vs. Robustness in Grammar Engineering

Preface The conceptual origins of the English Resource Grammar go back to the days of GPSG grammar development in the Natural Language Project at Hewlett-Packard Laboratories beginning in the early 1980s, with Tom Wasow serving as one of the initiators and guiding forces of that research group, which this author joined starting as a summer intern in 1983. It was at HP Labs that we developed the methodology of building and using test suites exhibiting core linguistic phenomena, for regression testing and measurement of progress as we extended grammar coverage while maintaining a high level of linguistic accuracy.
Automated Calibration Of Greenhouse Energy Model Using Hybrid Evolutionary Programming (EP)-Energy Plus

This paper presents an optimization approach of calibrating a tomato greenhouse energy model using hybrid Evolutionary Programming (EP)-EnergyPlus. The proposed methodology applies automated simulation-based approach by coupling Matlab and EnergyPlus to perform building energy simulation and obtain the best variables configuration with minimal error between the simulated and measured energy of the greenhouse. The proposed method is tested using a tomato greenhouse system located in Universiti Putra Malaysia (UPM). The greenhouse envelope is built using 0.15mm thick Transparency Plastic Film. Meanwhile, the electrical loads in the greenhouse consists of 6 exhaust fans, 2 axial fans, 5 fluorescent lamps and 1 irrigation pump. An Evolutionary Programming (EP) algorithm is chosen and programmed in Matlab to find the best configurations for optimum calibration of the greenhouse energy model. Three variables were chosen to find the best configuration which are the operating hours of Exhaust Fan, Axial Fan and Water Pump. The EP optimization algorithm in Matlab is coupled with building energy simulator, EnergyPlus using BCVTB as the coupling tool. Result shows that the EnergyPlus-EP model can provide NMBE and CV(RMSE) within the range recommended by the IPMVP protocol. The proposed method is not only requiring less computation time but also effective in searching for the best variables configuration with minimal error.
Helix : A Scalable and Fair Consensus Algorithm

We present Helix, a Byzantine fault tolerant and scalable consensus algorithm for fair ordering of transactions among nodes in a distributed network. In Helix, one among the network nodes proposes a potential set of successive transactions (block). The known PBFT protocol is then run within a boundedsize committee in order to achieve agreement and commit the block to the blockchain indefinitely. In Helix, transactions are encrypted via a threshold encryption scheme in order to hide information from the ordering nodes. The encryption is further used to realize a verifiable source of randomness, which in turn is used to elect the committees in an unpredictable way, as well as to introduce a correlated sampling scheme of transactions included in a proposed block. The correlated sampling scheme restricts nodes from prioritizing their own transactions over those of others. Nodes are elected to participate in committees in proportion to their relative reputation. Reputation, attributed to each node, serves as a measure of obedience to the protocol’s instructions. Committees are thus chosen in a way that is beneficial to the protocol.
Active DOP: an Active Learning Constituency Treebank Annotation Tool

We present a language-independent treebank annotation tool supporting rich annotations with discontinuous constituents and function tags. Candidate analyses are generated by an exemplar-based parsing model that immediately learns from each new annotated sentence during annotation. This makes it suitable for situations in which only a limited seed treebank is available, or a radically different domain is being annotated. The tool offers the possibility to experiment with and evaluate active learning methods to speed up annotation in a naturalistic setting, i.e., measuring actual annotation costs and tracking specific user interactions. The code is made available under the GNU GPL license at https://github.com/andreasvc/activedop.
COCONUT BAGASSE TREATED BY THIOUREA/AMONIUM SOLUTION FOR CADMIUM REMOVAL: KINETIC AND ADSORPTION EQUILIBRIUM

Coconut bagasse, an agricultural solid waste was used as biosorbent for the removal of cadmium after modification with thiourea. The adsorption of Cd2+ was studied at pH 5.5. Langmuir, Freundlich, and Temkin isotherms were used to model the adsorption equilibrium data, and it was found that the system followed the Langmuir and Temkin isotherms. The adsorption capacity of the biosorbent was found to be 35.97 mg g-1, which is higher or comparable to the adsorption capacity of various adsorbents reported in literature. Kinetic studies showed that the adsorption followed a pseudo-second-order rate model.
Shapaval Raman Security Risk Management for the IoT systems

Since 2012 the number of units in global infrastructure for the information society (The Internet of Things) has grown twice. With this number also has grown the number of possible threats and risks, which influence security on all levels of the system. As a result, a huge amount of users’ data was stolen or damaged. According to Third Quarter, 2016 State of the Internet / Security Report based on data gathered from the Akamai Intelligent Platform the total number of DDoS attacks in Q3 2016 increased in 71% compared to Q3 2015. With 623 Gbps data transfer attack it was largest DDoS ever and this fact will only increase the number of future attack events. All these facts reveal a problem that a lot of IoT systems are still unsecured and users’ data or personal information stay vulnerable to threats. The thesis combines knowledge of Security Risk Management with existing practice in securing in IoT into a framework, which aim is to cover vulnerabilities in IoT systems in order to protect users’ data. We propose an initial comprehensive reference model to management security risks to the information and data assets managed and controlled in the IoT systems. Based on the domain model for the information systems security risk management, we explore how the vulnerabilities and their countermeasures defined in the open Web application security project could be considered in the IoT context. To illustrate the applicability of the reference model we test the framework on self-developed IoT system represented by Raspberry Pi 3 interconnected with sensors and remote data storage.
Mikheil Kenchoshvili Tool for Identifying Working Style Based on Event Logs

Working style is a relatively new topic in Business Informatics. It is strictly related to concepts existing in other areas of the research such as Organizational Mining, Visual analytics, Pattern recognition. While there are several tools to tackle the task of organizational mining, they are general purpose stand-alone desktop applications, and none of them concentrate solely and deeply on working style identification. To this end, this thesis introduces a domain-specific web-based tool that aids the user with working style identification. The tool allows end users to import event logs. They can explore and query patterns to answer the questions related to the working style of the human actors involved in that event logs. The thesis presents, functional and technical requirements as well as the implementation details of the tool. Also, discusses the difficulties faced during the development and the gaps that have been identified in the current state of practice of the technologies that were used for implementation. Moreover, several possible extensions of the tool are suggested that could be addressed in the future works. Finally, the thesis demonstrates the usage of the tool by importing the sample data and exploring different capabilities and aspects of the application.
Wound healing potential of Biophytum sensitivum (L.) DC.: An ayurvedic drug

Non curative wounds is one of the major problems of ten encountered in health care system. The resumpti on of interest to use of Traditional System of Medicine e specially plant based medicines is rapidly growing. Herbs are more potent healers and promote the repair mechanis ms in a scientific way without causing any side eff cts. Plants used in Ayurveda are known to play significant rol e in the management of wound healing. But scientifi c evaluation of these herbal drugs to assess their safety and ef ficacy as well their standardization are required f or their international recognition and acceptance. Hence in the present study attempts were made to scientifica lly evaluate the wound healing potentials of an ayurvedic plant, ‘LAJJALU’ botanically equated as Biophytum sens itivum (L.) DC. (BS). In this study wistar strain albino rats a re used as animal model. The wound healing efficac y of the methanolic extracts of source taxon in 1g and 2g do se level was evaluated in excision wound models. Th e wound treated selected plant showed higher rate of wound contraction, increased level of Hydroxy proline, Hexosamine content, Super Dismutase, Ascorbic acid and decrea sed Lipid peroxidation. Histopathological studies r evealed the presence of newly formed blood vessels amidst the well laid collagen fibres. Significant wound healin g activity was observed in both the groups which were administered 1g and 2g of the test drug. But the animals treat ed with 2g revealed complete healing effect on 15 th day.
Posterior CramrRao Bound for Tracking Target Bearing

The posterior Craḿer-Rao bound on the mean square error in tracking the bearing, bearing rate, and power level of a narrowband source is developed. The formulation uses a linear process model with additive noise and a general nonlinear measurement model, where the measurements are the sensor array data. The joint Bayesian Cram ér-Rao bound on the state variables over the entire observation interval is formulated and a recursive bound on the state variables as a function of time is derived based on the nonlinear filtering bound developed by Tichavsky et al (1998) and analyzed by Ristic et al (2004). The bound is shown to have the same form as when the measurements are bearing and power estimates with variance equal to the deterministic Cram ér-Rao bound for a single data snapshot. The bound is compared against simulated performance of the maximum a posteriori penalty function (MAP-PF) tracking algorithm developed in Zarnich et al (2001).
Late Proterozoic – Paleozoic Geology of the Golan Heights and Its Relation to the Surrounding Arabian Platform

Weissbrod, T. , 2005. The Paleozoic in Israel and Environs, in J. K. Hall, V. A. Krasheninnikov, F. Hirsch, H. Benjamini, and A. Flexer, eds., Geological Framework of the Levant, 2: Jerusalem, p. 283-316. Weissbrod, T. and Sneh, A. , 2002. Sedimentology and paleogeography of the late Precambrian early Cambrian arkosic and conglomeratic facies in the northern margins of the Arabo-Nubian Shield. Isr. Geol. Surv. Bull., 87. Wolfart, R. , 1967. Geologie von Syrien und dem Lebanon, 326 p. Gebruder Borntrager, Berlin.
Meta-analysis of social-personality psychological research

Follow this and additional works at: http://digitalcommons.uconn. edu/chip_docs Part of the Applied Statistics Commons, Behavior and Behavior Mechanisms Commons, Biostatistics Commons, Human Geography Commons, Other Statistics and Probability Commons, Personality and Social Contexts Commons, Probability Commons, Psychological Phenomena and Processes Commons, Social Psychology Commons, Spatial Science Commons, Statistical Methodology Commons, Statistical Models Commons, and the Statistical Theory Commons
N 95-23757 Telescope Loading : A Problem Reduction Approach

This paper presents a problem reduction approach to telescope loading. To study time-varying celestial behavior, astronomers submit periodic observation campaigns which involve a sequence of observations at a given sampling frequency over months or years. The loader's task is to generate an assignment of observation tasks to each night in the time window such that resource demand does not exceed resource capacity and such that the observations usefully contribute to the campaigns' scientific purposes, in a manner that is fair to all participating astronomers.
Enforcing Regulation Under Illicit Adaptation

Attempts to curb illegal activity by enforcing regulations gets complicated when agents react to the new regulatory regime in unanticipated ways to circumvent enforcement. We present a research strategy that uncovers such reactions, and permits program evaluation net of such adaptive behaviors. Our interventions were designed to reduce over-fishing of the critically endangered Pacific hake by either (a) monitoring and penalizing vendors that sell illegal fish or (b) discouraging consumers from purchasing using an information campaign. Vendors attempt to circumvent the ban through hidden sales and other means, which we track using mystery shoppers. Instituting random monitoring visits are much more effective in reducing true hake availability by limiting such cheating, compared to visits that occur on a predictable schedule. Monitoring at higher frequency (designed to limit temporal displacement of illegal sales) backfires, because targeted agents learn faster, and cheat more effectively. Sophisticated policy design is therefore crucial for determining the sustained, longer-term effects of enforcement. Data collected from fishermen, vendors, and consumers allow us to document the upstream, downstream, spillover, and equilibrium effects of enforcement on the entire supply chain. The consumer information campaign generates two-thirds of the gains compared to random monitoring, but is simpler for the government to implement and almost as cost-effective.
ENHANCEMENTS OF LEACH ALGORITHM FOR WIRELESS NETWORKS: A REVIEW

Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is the first hierarchical cluster based routing protocol successfully used in the Wireless Sensor Networks (WSN). In this paper, various enhancements used in the original LEACH protocol are examined. The basic operations, advantages and limitations of the modified LEACH algorithms are compared to identify the research issues to be solved and to give the suggestions for the future proposed routing algorithms of wireless networks based on LEACH routing algorithm.
Body Conformation and Internal Organs Characteristics of Different Commercial Broiler Lines

I Professor, Department of Poultry Breeding, Faculty of Animal Breeding and Biology UTP University of Science and Technology, Bydgoszcz, Poland II Master of Science, Sohag University, Faculty of Agriculture, Department of Poultry and Animal Breeding, Sohag, Egypt III Master of Science, Department of Poultry Breeding, Faculty of Animal Breeding and Biology UTP University of Science and Technology, Bydgoszcz, Poland
Extensible type-directed editing

Dependently typed programming languages, such as Idris and Agda, feature rich interactive environments that use informative types to assist users with the construction of programs. However, these environments have been provided by the authors of the language, and users have not had an easy way to extend and customize them. We address this problem by extending Idris's metaprogramming facilities with primitives for describing new type-directed editing features, making Idris's editors as extensible as its elaborator.
Smart And Autonomous Systems For Repair And Improvisation

This integrative project addresses a longer-term vision and intellectual challenge of developing a library approach to robot behavior generation and learning. The researchers will build a large-scale long-term multidomain intelligent physical system that can repair and improvise desired processes and devices. The system will learn from instruction in the form of educational kits and books, and from a curriculum of training tasks, watching humans do tasks, coaching, practice, less directed play, and reflection. Evaluation of the proposed work will focus on how well robots can perform suggested activities from the instructional material, repair broken processes and devices, and create processes and devices that achieve new task specifications. The following hypotheses will be tested: 1) appropriate libraries can be built in practice and grown over time, 2) relevant experience can be accessed from a large multi-domain library and combined to exhibit rich behavior comparable to humans, and 3) such a library can support life-long learning for thousands of tasks in multiple domains, rather than a one-shot demo of one task in one domain. Can they overcome the curse of knowledge for AI systems: The more the system knows, the slower and stupider it gets?
Robust 6D Object Pose Estimation in Cluttered Scenes Using Semantic Segmentation and Pose Regression Networks

Object pose estimation is a crucial prerequisite for robots to perform autonomous manipulation in clutter. Real-world bin-picking settings such as warehouses present additional challenges, e.g., new objects are added constantly. Most of the existing object pose estimation methods assume that 3D models of the objects is available beforehand. We present a pipeline that requires minimal human intervention and circumvents the reliance on the availability of 3D models by a fast data acquisition method and a synthetic data generation procedure. This work builds on previous work on semantic segmentation of cluttered bin-picking scenes to isolate individual objects in clutter. An additional network is trained on synthetic scenes to estimate object poses from a cropped object-centered encoding extracted from the segmentation results. The proposed method is evaluated on a synthetic validation dataset and cluttered realworld scenes.
A Universal Background Subtraction System

OF THESIS A UNIVERSAL BACKGROUND SUBTRACTION SYSTEM Background Subtraction is one of the fundamental pre-processing steps in video processing. It helps to distinguish between foreground and background for any given image and thus has numerous applications including security, privacy, surveillance and traffic monitoring to name a few. Unfortunately, no single algorithm exists that can handle various challenges associated with background subtraction such as illumination changes, dynamic background, camera jitter etc. In this work, we propose a Multiple Background Model based Background Subtraction (MB 2 S) system, which is universal in nature and is robust against real life challenges associated with background subtraction. It creates multiple background models of the scene followed by both pixel and frame based binary classification on both RGB and YCbCr color spaces. The masks generated after processing these input images are then combined in a framework to classify background and foreground pixels. Comprehensive evaluation of proposed approach on publicly available test sequences show superiority of our system over other state-of-the-art algorithms.
Relationship between Module Size , Alternative Cost and Bugs

The aim of this thesis is to find out if Alternative Cost (AC) and size of modules lead to more bugs in a software project. Using the historical churn extracted from revisions data and bug reports data retrieved from four software projects namely, JQuery, Font-Awesome, ReactJS, and Atom, we calculate their AC. After which we use Kendall correlation to investigate the strength of association between AC and bugs, and module size (measured in Lines of Code) and bugs. We find a strong association between size of modules in all four software projects and bugs existing in them, while that of AC and bugs remain inconclusive. From our investigation, we conclude that when quality assurance activities are performed on a software project, modules with larger size should be given more attention. On the other hand, using our result, Alternative Cost is not relevant for bugs localization.