Miracle-dz/UniFAR-FTUs huggingface dataset:
Models of soil organic matter decomposition: the SoilR package, version 1.0

Soil organic matter decomposition is a very impor- tant process within the Earth system because it controls the rates of mineralization of carbon and other biogeochemical elements, determining their flux to the atmosphere and the hydrosphere. SOILR is a modeling framework that contains a library of functions and tools for modeling soil organic mat- ter decomposition under the R environment for computing. It implements a variety of model structures and tools to rep- resent carbon storage and release from soil organic matter. In SOILR, organic matter decomposition is represented as a linear system of ordinary differential equations that gener- alizes the structure of most compartment-based decomposi- tion models. A variety of functions is also available to repre- sent environmental effects on decomposition rates. This doc- ument presents the conceptual basis for the functions imple- mented in the package. It is complementary to the help pages released with the software.
An adaptive medium access control for energy efficiency in wireless sensor networks

Wireless sensor networks are usually a collection of sensor nodes deployed remotely with limited energy resources. Therefore, conservation of energy is one of the highest priorities in a wireless sensor network design. In this paper we present enhancements at medium access control (MAC) layer to improve energy efficiency. The MAC employs a variable frame size instead of using a fixed frame size, which improves energy conservation. A new approach called extended Kalman Filter is used to predict the optimal frame size. The variable frame size keeps the system degradation caused by a time varying wireless channel to minimum. These enhancements are designed to optimize the MAC layer without losing its fairness while increasing throughput. Simulations have been conducted with different network scenarios and the results suggest that our approach improves energy efficiency by 5 to 15%.
Audio Feedback – Better Feedback?

Abstract National Student Survey (NSS) results show that many students are dissatisfied with the amount and quality of feedback they get for their work. This study reports on two case studies in which we tried to address these issues by introducing audio feedback to one undergraduate (UG) and one postgraduate (PG) class, respectively. In case study one audio feedback was given to half of the UG class whereas the other half received written feedback for a low stake (10%) exam style essay. In case study two audio feedback only was given to the PG class for a purely formative assignment which formed the basis for a final, summative piece of work. In both studies, audio feedback was received favourably as students found it clear, detailed and personal. A comparison between audio and written feedback (case study one) indicated that audio feedback left students more satisfied and provided more explanatory as well as motivational comments than written feedback. Generating audio feedback proved to be significantly more time consuming (by five minutes per script) than written feedback, but was more efficient in the sense that it produced nearly 10 times as much and higher quality feedback per unit of time. However, neither form of feedback led to an increase in students' subsequent performance in a final, summative exam essay. We conclude that audio feedback is better feedback in terms of student experience but it is still unclear if audio feedback can lead to higher attainment than other forms of feedback.
On the Definition of Terms in a Requirements Expression

The purpose of a requirement expression is to communicate clearly the needs of various entities into a formal language such that the intent is clearly understood by all involved: those whose job it is to implement the requirement, those responsible for proving the built system meets the requirement, and those responsible for proving the resulting system meets the needs of the relevant entity. Although many sources provide definitions of the terms associated with a requirement expression, there are only occasional agreements on common definitions, and the defined terms are too narrowly focused to be useful across the full requirements engineering domain. This paper proposes a cohesive set of definitions of the terms associated with a requirement expression. First, a framework for the transformation of needs into requirements is briefly discussed and existing definitions are presented from major relevant sources. These definitions are then analyzed and a cohesive set of definitions is offered for the key terms associated with a requirements expression: entity; need; requirement statement; and the requirement attributes that, along with the requirement statement itself, comprise the requirement expressions in a requirement set.
Application of high-resolution satellite imagery to transportation: accessibility index extraction approach

This study focuses on transportation application using remotely sensed imagery, in GIS-based environment; GIS is regarded as one of the important and effective methodologies in the transportation problem solving. Generally, transportation application is the complicated task, containing GIS-T (GIS for Transportation) database building and specialized analytical processes; therefore, this study aims at accessibility index extraction using high-resolution imagery, applicable to transportation planning considering an urban environment among transportation. Accessibility, defined as measuring the easiness of reaching from one place to other place, is an element in analyzing the efficiency of a transportation system in its planning process. As for attractive factors in transportation accessibility, many variables such as travel cost, travel time, job opportunity, and the number of facilities or population can be applied. Among them, some parts are associated with visually recognizable features revealed on remotely sensed imagery, and accessibility indices can be utilized to road network or by-pass design problem, and public transit planning. In this study, the gravity-typed accessibility measures are implemented in ArcView-GIS environment with Image Analysis extension. Some ortho-rectified KOMPSAT imageries and IKONOS imageries in local area nearby Seoul-city are used in this study, with digital GIS road layers of the National Geographic Institute in Korea. Conclusively, it is thought that thematic information extraction from high-resolution imagery with GIS databases contributes to expand application fields in remote sensing.
Improving support for e-puck robot in Webots mobile robots simulation software

E-puck is a mobile robot which has various sensors (camera, infra red sensors, microphones etc.) and actuators (motors, speaker, LEDs). It is useful for a broad range of applications, especially teaching and is supported in the Webots mobile robots simulation software. An extension for e-puck, making it a full computer on wheels was recently developed. Supporting the new extension in Webots was the goal of this project. This was done by developing a software library called E-GO which provides access to all of the features of the extended robot, such as sampling sensors, updating actuators, communication between e-puck and the extension, wireless communication between the extended robot and other devices. The goal was also to do this in a simple and standardized manner, providing compatibility with the Webots API and with a clean and user friendly interface. Library supports both autonomous execution of a controller on the robot as well as remote control of the robot. This approach masks the complexity of the system while still providing its functionalities to the user. Combination of the extension and the software library allows for image acquisitions with up to 10fps in maximum camera resolution (640x480) compared to a maximum of 4fps with 40x40 pixels resolution of the basic e-puck version. From the two formats in which the camera can supply the image (RGB565 and YUV422) tests showed RGB565 to be faster by about 2.5x compared to YUV422. Communication between the basic e-puck robot and the extension is via serial connection. Average transfer rate achieved is about 85μs/byte, which when adjusted with the overhead of control bits gives a throughput of about 120000b/s (programmed data rate of the serial connection is 230400b/s). Average amount of time necessary to transmit maximum possible amount of data (update all actuators and sample all sensors) through the serial bus is about 50ms and to acquire one image in full resolution is about 100ms. keywords: e-puck, autonomous, mobile, robot, Webots, E-GO, Gumstix. Chapter
A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications

Computing devices and applications are now used beyond the desktop, in diverse environments, and this trend toward ubiquitous computing is accelerating. One challenge that remains in this emerging research field is the ability to enhance the behavior of any application by informing it of the context of its use. By context, we refer to any information that characterizes a situation related to the interaction between humans, applications, and the surrounding environment. Context-aware applications promise richer and easier interaction, but the current state of research in this field is still far removed from that vision. This is due to 3 main problems: (a) the notion of context is still ill defined, (b) there is a lack of conceptual models and methods to help drive the design of context-aware applications, and (c) no tools are available to jump-start the development of context-aware applications. In this anchor article, we address these 3 problems in turn. We first define context, identify categories of contextual information, and characterize context-aware application behavior. Though the full impact of context-aware computing requires understanding very subtle and high-level notions of context, we are focusing our efforts on the pieces of context that can be inferred automatically from sensors in a physical environment. We then present a conceptual framework that separates the acquisition and representation of context from the delivery and reaction to context by a context-aware application. We have built a toolkit, the Context Toolkit, that instantiates this conceptual framework and supports the rapid development of a rich space of context-aware applications. We illustrate the usefulness of the conceptual framework by describing a number of context-aware applications that have been prototyped using the Context Toolkit. We also demonstrate how such a framework can support the investigation of important research challenges in the area of context-aware computing.
Multi-polarization SAR data for operational ice monitoring

The launch of Envisat-ASAR, RADARSAT-2 and ALOS-PALSAR will offer operational polarization-diverse SAR data for the first time. A series of example data sets from aircraft and SIR-C are examined to evaluate the operational potential of these future systems. The primary operational advantage of multi-polarization data will be improved ice-water discrimination at low incidence angles, although the expected noise-floor of the satellite systems may limit their utility for discrimination of new ice types.
From Abstraction to Realization: Canonical Abstract Prototypes for User Interface Design REVISED

¶ Abstract. Canonical abstract prototypes are an innovative means for specifying and exploring visual and interaction design ideas. Intermediate between abstract task models and realistic or representational prototypes, canonical abstract prototypes provide designers with a standardized vocabulary for expre ssing visual and interaction designs independent of details of appearance and behavior. This common abstract design vocabulary facilitates comparison of designs as well as recognition and description of common design patterns. This paper introduces the basic concepts of abstract prototypes and covers recent refinements in the modeling notation and the set of canonical abstract components. Learn more about usage-centered design, including training in canonical abstract prototypes, at http://www.forUse. com. Abstract Prototypes
A regression sequences based method for high dimensional outlier detection

Abstract In recent years, high dimensional space outlier detection has attracted wide attention. High dimensional space outlier detection plays a very important role in many fields such as network intrusion detection, credit card fraud, electronic commerce crime, medical diagnosis and anti-terrorism. The purpose of high-dimensional outlier detection is to find a small number of objects in a high-dimensional dataset, which has a special behavior or abnormal behavior compared with most of the rest of the objects in the high-dimensional dataset. The existing high dimensional space outlier detection method cannot effectively deal with the problem of uncertain and incomplete data. In this paper, the concept of rough set boundary and the high dimensional space outlier detection method based on regression distance proposed by Knorr et al are combined together. We propose a new method for the definition and detection of high dimensional space outliers based on the regression sequence in the framework of rough set. For this method, we design a corresponding high dimensional space outlier detection algorithm (HDSOD) and verify the validity of the algorithm HDSOD by experiments on high dimensional data set. The experimental results show that the proposed method provides a new method to deal with the uncertain and incomplete data in high dimensional space outlier detection.
Manual resolution of viscosity and mass

Psychophysical experiments measuring human resolution in manually discriminating viscosity and mass were performed while the associated force and displacement variations over time generated by the subjects were simultaneously recorded. The experiments were performed on a computer controlled electromechanical device called the Linear Grasper. For viscosity the Just Noticeable Difference (JND), a measure of human sensory resolution, was found to be 13.6% for a reference viscosity of 120 Ns/m. For mass, the JND was approximately 21% for a reference mass of 12 Kg. Motor performance data indicated that subjects applied average mean grasping forces ranging from 3.5 to 9.5 N with squeeze velocities of 35 mm/sec to 80 mm/sec in viscosity discrimination experiments and accelerations of 350 to 700 mm/sec2 in mass discrimination experiments. Analysis of the motor performance data indicated that in both discrimination experiments, the subjects' average mean applied force increased with stimulus intensity, while the average mean grasping velocity decreased with stimulus intensity in the viscosity discrimination experiments and the average mean grasping acceleration decreased with stimulus intensity in the mass discrimination experiments. This study is part of an ongoing research program to better understand human haptic perception of physical properties of objects and to provide human factors data for the improved design of haptic interfaces for virtual environments and teleoperation.
Framing Effects in Success of Social Networks Based on Information System

Current study tries to describe outcomes of the framing effects (in domains of gain and loss). In this paper, first, some fundamental framing elements are discussed, then they are employed in the municipality idea bank, and in the third step the results of framing's implementation are identified. The effects of framing are tested among experts by questionnaire and interview. Based on our findings, all framing effects can be used by different degrees. The results of examining the effects of framing in the idea bank as a social network indicate that framing can be utilized as an incentive method for long term cooperation between the expert and the idea bank. The results shows, there is a positive relationship between the expert’s aversive experience in their past professional and private life. Also experts highly expect the idea bank to compensate their contributions by providing their expected awards. And that, at the time of decision making, more than half of the people who are analytic thinkers do not become affected by framing.
The Effect of Task Complexity on Functional Adequacy, Fluency and Lexical Diversity in Speaking Performances of Native and Non-Native Speakers.

This study investigated how task complexity affected native and non-native speakers’ speaking performance in terms of a measure of communicative success (functional adequacy), three types of fluency (breakdown fluency, speed fluency, and repair fluency), and lexical diversity. Participants (208 non-native and 59 native speakers of Dutch) carried out four simple and four complex speaking tasks. Task complexity was found to affect the three types of fluency in different ways, and differently for native and non-native speakers. With respect to lexical complexity, both native and non-native speakers produced a wider range of words in complex tasks compared to simple tasks. Results for functional adequacy revealed that non-native speakers scored higher on simple tasks, whereas native speakers scored higher on complex tasks. We recommend that, in future research examining effects of task types on task performance, the notion of functional adequacy be included.
Neurodesign: Optimal Experimental Designs for Task fMRI

A recent stream of alarmist publications has questioned the validity of published neuroimaging findings. As a consequence, fMRI teams worldwide have been encouraged to increase their sample sizes to reach higher power and thus increase the positive predictive value of their findings. However, an often-overlooked factor influencing power is the experimental design: by choosing the appropriate experimental design, the statistical power of a study can be increased within subjects. By optimizing the order and timing of the stimuli, power can be gained at no extra cost. To facilitate design optimization, we created a python package and web-based tool called Neurodesign to maximize the detection power or estimation efficiency within subjects, while controlling for psychological factors such as the predictability of the design. We implemented both a simulation-based optimisation, as well as an optimisation using the genetic algorithm, introduced by Wager and Nichols (2003) and further improved by Kao et al. (2009), to optimize the experimental design. The toolbox Neurodesign allows more complex experimental setups than existing toolboxes, while the GUI provides a more user-friendly experience. The toolbox is accessible online at www.neuropowertools. org.
Performance Analysis of Gender Clustering and Classification Algorithms

— In speech processing, gender clustering and classification plays a major role. In both gender clustering and classification, selecting the feature is an important process and the often utilized feature for gender clustering and classification in speech processing is pitch. The pitch value of a male speech differs much from that of a female speech. Normally, there is a considerable frequency value difference between the male and female speech. But, in some cases the frequency of male is almost equal to female or frequency of female is equal to male. In such situation, it is difficult to identify the exact gender. By considering this drawback, here three features namely; energy entropy, zero crossing rate and short time energy are used for identifying the gender. Gender clustering and classification of speech signal are estimated using the aforementioned three features. Here, the gender clustering is computed using Euclidean distance, Mahalanobis distance, Manhattan distance & Bhattacharyya distance method and the gender classification method is computed using combined fuzzy logic and neural network, neuro fuzzy and support vector machine and its performance are analyzed.
Multipurpose 4+4 Channel Array Setup for Parallel Imaging in 3D

Introduction: Array-coil imaging is an advanced method for acquiring high resolution images with high SNR in a comparatively short time. Several coils are used to cover a defined volume simultaneously. In a second step, the data for the array is combined to form the final image. Since the sensitivity of each single array-coil in its detection area is better than that of one single volume coil, increased SNR can be expected [1]. This concept has become more and more popular for many applications using various specialized array-coils. The objective of this work was to develop a pair of coil arrays for multipurpose applications feasible for many different small regions of the human body.
Designing the optimal structure of a neural filter

In this paper, we propose a new method for designing the optimal structure of a neural filter (NF), and evaluate its performance. In order to verify the validity of the proposed method, we apply the proposed method to the NF that has been trained to achieve the function of a linear filter with kernel of known shape, and verify that the optimal kernel is achieved. The experimental results demonstrate that the optimized NF by the proposed method achieves the optimal generalization ability, and the performance of the optimized NF by the proposed method is superior to that of the original NF. By the comparative evaluation with the NF that has been trained to reduce noise in medical images, we show that the proposed method is superior to the ability of the conventional method quantitatively in terms of the performance of optimization, the filter performance of the optimized NF, and the generalization ability of the optimized NF.
Custom Processor Using An Fpga For Undergraduate Computer Architecture Courses

The field programmable gate array (FPGA) and modern computer aided design tools provide new opportunities in teaching computer architecture. This paper presents a simple yet nontrivial Von Neumann style computer architecture and corresponding implementation suitable for an undergraduate course in computer architecture. The processor architecture itself is worthy of study, including such features as subroutines, stack relative addressing, interrupts, and conditional branching. The processor is able to pre-fetch with some instructions and provides performance comparable to traditional small microprocessors such as the Motorola/Freescale 68HC11. The architecture and implementation documents are written so that several options are possible for introducing nod4 into the classroom curriculum. In particular, students may investigate the nod4 processor or implement the processor themselves. It is also possible to present the processor architecture entirely without the implementation.
Research on cost-sensitive ensemble classification for mining imbalanced massive data streams

The existing classifiers for massive data streams do not consider the imbalance distribution and cost factors, so this paper proposes the approach of the cost-sensitive ensemble classification for imbalanced massive data streams (CECIDS). Firstly, this paper gives the construction method for cost-sensitive ensemble SVM Classification, which is integrated by the classifiers with oversampling, sub-sampling and reconstituted sample space. Secondly, we propose a classifier method BL_KNNModel, which is based on KNNModel algorithm for imbalanced massive data streams. BL_KNNModel can detect the concept drift streams by using the variable windows size, which has lower time complexity. At last, the cost-sensitive ensemble classifier for imbalanced massive data streams is given, which has the virtue of high classification and lower time complexity. In addition, the cost-sensitive ensemble SVM algorithm is used to handle the confused instances. The experiments using both synthetic and real datasets show that compared to the other classification algorithms for imbalanced data streams, CECIDS has higher evaluating indicator and more excellence integrated learning curve.