Miracle-dz/UniFAR-FTUs huggingface dataset:
Miss distance analysis in a new guidance law

This paper presents an analysis of a guidance law that combines pursuit guidance with proportional navigation. The analysis accounts for the presence of measurement noise and autopilot dynamics. Under the assumptions that the measurement noise processes are Gaussian, white, with zero mean, and that the autopilot is ideal, we obtain an analytical expression for the mean square miss (i.e., the expected value of the square of the miss distance), explicitly in terms of the navigation constants. Generally, the mean square miss will then decrease as the navigation constants are increased. We also consider the effect of measurement noise in the presence of a first-order autopilot. Here, numerical simulations suggest that for relatively large values of the autopilot time-constant, increasing the navigation constants will be detrimental to the accuracy of the homing. This result corroborates the findings of previous studies on proportional navigation, where it was shown that increasing the navigation constant shortens the engagement, but degrades accuracy in the presence of autopilot dynamics.
Chemistry and Chemical Reactivity

Quality writing, seamless technology integration, and a rich ancillary package are hallmarks of John C. Kotz and Paul M. Treichel, Jr.'s CHEMISTRY AND CHEMICAL REACTIVITY. Now thoroughly revised and enhanced, the fifth edition of this best-selling text will bring students to a new level of understanding and appreciation for chemistry's vital role in their lives. By emphasizing the close interrelationship of the macroscopic, symbolic, and particulate levels of chemistry, Kotz and Treichel provide an important organizing principle that carries throughout the book. The text's significantly revised art program reveals these three levels in engaging detail. This new art program is fully integrated with CHEMISTRY AND CHEMICAL REACTIVITY'S unparalleled CD-ROM, GENERAL CHEMISTRY INTERACTIVE, VERSION 3.0. With hundreds of guided simulations, animations, and video clips, as well as new Intelligent Tutors that guide students step-by-step through problems, GENERAL CHEMISTRY INTERACTIVE is the benchmark learning tool by which all others are measured-and it is included with every new copy of the text.
Sociopragmatic Features of Learner-to-Learner Computer-Mediated Communication

The present study offers a holistic and rich description (as recommended by Ellis, 1999b) of the sociopragmatic features of exchanges among first-year learners of German. Specifically, it examines the use of opening and closing sequences, patterns of topic assignment, and maintenance by participants in computer-mediated interactions in order to gain insights into learners' sociopragmatic abilities in the foreign language. This is an important first step towards exploring the potential of computer-mediated communication (CMC) for fostering foreign language (L2) sociopragmatic competence, which--Kasper (1998) posited--may be developed only through practice and awareness raising. The results of the present study suggest that computer-mediated learner-to-learner interac-tion offers L2 learners unique opportunities for active control of topic selection and management and provides rich opportunities for learners to recognize and adapt to diverse interactional patterns through collaboration among the interactants. Thus, the study furthers the argument that through meaningful participation in different speech communities--here, CMC communities--L2 learners may develop the procedural knowledge (Wildner-Bassett, 1994) necessary for recognizing the interac-tional patterns of a microlevel speech community (e.g., an online discussion group) and for adapting their discourse effectively to function in these speech communities.
On performance evaluation methods and control strategies for semi-active suspension systems

The problem considered in this paper is the design and analysis of a control system for semi-active suspensions in road vehicles. Three control strategies are tested: the two-state skyhook damping, the linear skyhook damping, and a newly-proposed control strategy based on two-state switching dampers. In order to assess and to compare the closed-loop performance of these control strategies, an evaluation method based on the describing-function is proposed. This evaluation approach provides, in the frequency-domain, a clear picture of the closed-loop performance on the body acceleration (comfort objective) and on the vertical load at the road-tire contact surface (handling objective). This evaluation method inherently provides a quantitative estimate of the degree of input/output non-linearity of the closed-loop system.
When what you see is what you hear: Auditory-visual integration and presence in virtual environments

In this paper, it is hypothesized that consistency across modalities in terms of matching the visual space to the auditory space is important for the sense of presence. An experiment was carried out where thirty participants were exposed to four conditions having different degrees of auditory-visual consistency (one purely visual and three auditory-visual). A presence questionnaire was used after exposure to measure participants’ sensations. Although participants rated the auditory-visual conditions as inducing significantly higher presence than the condition with only visual information, no differences in presence ratings between the three auditory-visual conditions were found. However, participants’ rankings of their sensed presence in all conditions revealed that there might be such differences. Moreover, the results show that sound in general has a significant effect on VE users’ sense of presence.
Managing change: The use of mixed delivery modes to increase learning opportunities

Science teaching in the new millennium will need to suit the students' needs and understanding, and employers' expectations. Choosing to learn will help form the learning opportunities presented. This paper looks at the way the delivery of teaching and learning materials for large first year biology units of study has changed over a period of time during which there have been reductions in staff resources and increases in student numbers. The strategies currently used to manage student learning and improve the learning experience will be detailed. These include a mix of on campus and online opportunities such as the management of laboratory classes in a peer mode model and the recent re-purposing of existing online resources to provide a Virtual Learning Environment (VLE). The VLE offers a safe, student centred learning environment with access to synchronous and asynchronous communications, and access to learning and assessment materials. Reasons for the development of the VLE are discussed, with ideas on the management of campus based teaching in the experimental sciences.
A secure communication architecture for GSM networks

With the advance of wireless communications technology, mobile communications has become more convenient than ever. However, because of the openness of wireless communications, how to protect the privacy between communication parties is becoming a very important issue. In this paper, we focus on the security of the Global System for Mobile communication (GSM) networks. A secure communication architecture for the GSM network is proposed. In the proposed architecture, we use public-key cryptography for user authentication and a stream cipher for message encryption and decryption. This architecture significantly improves the security of today's GSM networks.
AN AUTONOMOUS ACCELERATED COORDINATION OF STOCHASTICMOVING MULTI-AGENTS UNDER VARIATIONS AND RESOURCE UTILIZATION

This paper presents a new behavior of autonomous moving multi-agents, whose agents stochastically move over a resource consisting of cells in accordance with transition probabilities, depending on other agents. We suppose interactions or coordination among agents such that an agent can not move to a destination cell occupied by agents more than the agents of a current cell. The first we show that a moving multiagent with an appropriate average moving speed is more stable than a moving multi-agent without average moving speed. Then the stability can be accelerated by giving appropriate moving speed for agents. The second result is that the resource utilization of a moving multi-agent with an appropriate average moving speed becomes higher than the resource utilization of a moving multiagent without average moving speed. Then the resource utilization can be accelerated by giving moving speed. The above results are based on both theory and experiments, and we present the optimal moving speed of the system-specific for the acceleration.
Data Mining Analysis of the Effect of Educational, Demographic, and Economic Factors on Time from Doctoral Program Entry to Degree Completion in Education

The duration of doctoral studies has been linked to low persistence rates and can therefore be viewed as an indirect measure of risk for non-completion. In 2004, the median time between master’s and doctorate in Education was 12.7 years, which was 4 years longer than the median for all fields. The purpose of this study was to identify demographic, educational, and economic factors associated with atypically long time (i.e., the highest 33%) between doctoral program admission and degree completion. The population included all doctoral recipients in Education from Florida public universities between 1998 and 2004 (n=773). Data mining was used to generate six models which were compared on the basis of variable importance and predictive accuracy. Tree and classification models were compared to models developed through the traditional statistical methods of discriminant analysis and logistic regression. Assessment of model predictive accuracy was based on four criteria as follows: cumulative misclassification rate, weighted misclassification rate, misclassification of the dependent variable, and model consistency. The models’ predictive accuracy differed but there was general consensus on variable importance with educational and institutional variables superseding all demographic variables. The highest predictive accuracy was observed in the three tree models which validated the analytic merit of data mining in this study.
Performance analysis of MIMO eigenmode transmission system under realistic channel and system conditions

The performance of the MIMO eigenmode transmission system (EMTS) is very sensitive to the accuracy of channel state information and thus it is of practical importance to analyzing its performance when channel state information is corrupted under realistic system and propagation conditions. We lower bound the mutual information of MIMO EMTS with imperfect channel estimation and delayed quantized feedback in a spatially correlated continuous fading channel. Our results show that this lower bound is tight and can serve as a comprehensive guide to the actual performance of MIMO EMTS under practical operating conditions.
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1] . The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3] , DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac. uk/projects/segnet/.
Segmentation of breast tumors in mammograms by fuzzy region growing

Segmentation of tumor regions in mammograms is not easy due to the low contrast and the fuzzy nature of the boundaries of malignant tumors. General image segmentation procedures do not consider the uncertainty present around the boundaries of a tumor region. In this paper we present a segmentation method based on fuzzy region growing. The procedure starts with a seed pixel, and uses a fuzzy membership function based upon statistical measures of the region being grown. Results of testing with several mammograms indicate that the method can provide boundaries of tumors close to those drawn by an expert radiologist. The regions obtained preserve the transition information present around tumor boundaries. Statistical measures computed from the resulting regions have shown the potential to classify masses and tumors as benign or malignant.
Study of Prefrontal Blood Flow in Dementia Patients Using Near‐Infrared

SUMMARY The category frequency task has become one of the most important tools for measuring brain function. In this investigation, we used near-infrared spectroscopy to examine the prefrontal blood flow in the brain, using a category fluency task function test to determine if this method can be used to diagnose dementia in the early stages. We examined 21 healthy volunteer students (age 21.0±1.4; 11 males and 10 females) and 50 patients with dementia (age 83.3±6.7; 12 males and 38 females; mini mental status: 0–22). The category fluency task required the subjects to produce nouns belonging to the category of vegetables. Our results showed that the healthy volunteer students had an increase in the blood flow while performing this task. On the other hand, the dementia patients did not show any relevant increase in blood flow while performing this task. The results suggest that the combination of the category fluency task and near-infrared spectroscopy could be used as one more tool for the diagnosis of dementia.
Biased Monte Carlo methods for efficient simulation of communication systems

This thesis investigates biased Monte Carlo (MC) methods for e cient simulation of orthogonal frequency division multiplexing (OFDM), multiple-input multipleoutput (MIMO) and coded communication systems. Analytical complexity of exact performance evaluation of modern communication systems demands MC simulations, which estimate the performance metrics by statistical sample averaging. Even though MC is generally applicable for arbitrarily complex systems, it requires large sample sizes and extensive computational time to estimate low probabilities with a high degree of accuracy. This motivates the development of e cient simulation techniques. Statistical e ciency of simulations can be improved by properly biasing the MC simulations to encourage the occurrence of important events. This thesis investigates such biasing strategies for communication system simulation. First, optimal importance sampling (IS) methods are proposed for e cient simulation of OFDM and MIMO-OFDM systems operating over frequency selective fading channels. Optimum IS parameters that minimise the statistical variance of the estimator are derived. The proposed methods provide increased sample size reductions with decreasing probability. Next, at histogram Monte Carlo (FHMC) techniques, developed for statistical physics systems, are investigated in a communication engineering context. The potential of FHMC techniques to accelerate communication system simulations is explored. Simulation results show that sample size reductions in the order of 10 can be achieved in estimating probabilities in the order of 10 with a relative error of ±10%. Moreover, improved MC estimators are derived and these estimators are used to enhance the e ciency of FHMC algorithms. The improved FHMC algorithms are successfully applied to capacity estimation of MIMO systems whose analytical solutions are intractable. Of these derived estimators, the improved combination of Wang-Landau (WL) and transition matrix Monte Carlo (TMMC) methods shows
Identification and Inference for Econometric Models

This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.
Teaching English Language Learners through Technology

@contents:PART ONE: YOUR ENGLISH LANGUAGE LEARNER 1.1 Orientation 1.2 The Process of English Language Learning and What to Expect 1.3 Deciding on the Best ESOL Program 1.4 Teaching for English Language Development 1.5 Not All ELLs are the Same 1.6 Culturally Responsive Pedagogy 1.7 Not All Parents are the Same: Home/School Communication 1.8 English language Learners with Special Needs PART TWO: WHAT WE KNOW FROM RESEARCH 2.1 Taking the Lead from Vygotsky 2.2 Differentiated Instruction, Project-based Learning, Constructivist Pedagogy Principles 2.3 Making Accommodations for ELLs and Infusing Technology into a Lesson 2.4 Principles of Technology Use in Educational Settings 2.5 Computer-Assisted Language Learning (CALL) Research PART THREE: TEACHING ELLs THROUGH TECHNOLOGY 3.1 Orientation 3.2 E-Creation Tools & Self-made Computer-based Resources: getting ELLs to play & be creative with language 3.3 Communicative Facilitating E-Tools: getting ELLs to produce language 3.4 Writing/Reading Facilitative E-tools: getting ELLs to improve & focus on their literacy skills 3.5 Listening Facilitative E-tools: Improving ELLs comprehension skills 3.6 E-Assessments: Portfolios, Quizzes & Rubrics 3.7 Managing Teaching through Virtual Learning Environments PART FOUR: ANNOTATED RESOURCES 4.1 WWW Resources 4.2 Print Materials for Teachers 4.3 Resources for Students 4.4 GLOSSARY
Blended learning: Investigating its potential in an English language teacher training program

Although the benefits of blended learning have been well documented in educational research, relatively few studies have examined blended learning in language teacher education. This study discusses a blended learning approach for a teacher training program designed for in-service English language teachers, and investigates its effectiveness by comparing with a face to face MA Program in English Language teaching. The research involved 39 in-service English language teachers, with 12 studying in a blended course (i.e., they received face to face instruction in the classroom and used web-based materials) and 27 in a traditional classroom. Results indicated that there was no difference in content knowledge acquisition between teachers receiving blended instruction and teachers receiving face to face instruction.
The acquisition of the DP in modern Greek

This book offers new data on the acquisition of functional categories in early child speech. Based on longitudinal corpora of five children acquiring Modern Greek as their first language, it describes the development of single DPs consisting of definite and indefinite articles, complex DPs that require the use of multiple definite articles — possessive constructions, appositive constructions and Determiner Spreading, a form of adjectival modification — and number and case marking in nouns and definite articles. Detailed quantitative and qualitative analyses show an incremental development of the DP. The findings address the debate concerning maturation versus continuity . Incremental acquisition of the DP argues in favour of a weak continuity approach to language acquisition. Whilst gradual acquisition of the DP remains unexplained within the Principles and Parameters Theory , it is fully compatible within Minimalism , as it is argued to result from the gradual acquisition of the features associated with the Greek DP.
Investigation of Seismograms of North Korean Nuclear Explosion of September 3, 2017 Recorded by the Sakarya University and Kandilli Observatory Seismic Stations

A nuclear test was done on September 3, 2017 in North Korea. This activity is regarded as a nuclear test based on both CTBTO analysis and the statement of the official North Korean news agency. The type of explosion was announced as a fusion based thermonuclear hydrogen bomb. Preliminary solution of CTBTO International Data Center (IDC) reported the origin time, epicenter coordinates and magnitude as 03:30:01 UTC, 41.3°N 129.1°E, and mb 6.1. U.S. Geological Survey (USGS) determined these parameters as 41.343°N, 129.036 °E and body wave magnitude, mb 6.3. In this study the seismograms of September 3, 2017 North Korean nuclear test recorded by the Sakarya University and Kandilli Observatory seismic stations were investigated. As we observed the first motion polarity is upwards for the explosion records but the first motion polarity is downwards for the April 14, 2014 Japan earthquake records. Also we statistically analyzed the North Korean nuclear explosions and some teleseismic earthquakes near Japan by using mb/Ms values. Linear discriminant function (LDF) was used to discriminate teleseismic events and nuclear explosions. The discrimination success percentage is 100 % in this study.
An improved analytical yield evaluation method for redundant RAM's

A new stochastic method is introduced for calculating the manufacturing field of fault-tolerant VLSI/WSI systems. This method is an improvement on a previous method based on a Markov chain. This new method gives a higher lower bound value of the field with respect to other methods based on the same assumptions. This improvement is obtained by the consideration of reconfiguration strategies based on the knowledge of the fault patterns and the redundancy levels. The proposed method is easy to use in parametric studies of the field of a chip versus redundancy level and very versatile for inclusion in CAM/CAD programming environments.