Miracle-dz/UniFAR-FTUs huggingface dataset:
Method Of Signal Processing In Passive InfraredDetectors For Security Systems

This article presents the construction and principle of operation of passive IR detectors (PIR detectors) of a large detection range. An important virtue of these detectors is highly efficient detection of slowly moving or crawling people. The PIR detector described here detects crawling people at a distance of 140 m. High signal-to-noise ratio was obtained by using a larger number of pyroelectric sensors, i.e., by using a larger number of detection zones (channels). The original electronic system for the PIR detector is presented in which DC signal amplifiers from pyroelectric signals are used. In order to ensure large detection ranges, a new method of signal analysis was used.
Social Simulation in the Social Sciences

This article provides an overview of the social simulation approach to the study of social phenomena. We focus especially on the relevance of heterogeneity of social behavior and dynamics and the complex interplay of agent behavior and social structure. The article identifies the peculiarities and the explanatory achievements of this approach and then discusses its prospects and challenges. Special attention is given to (i) how micro-level behavioral detail can be used to understand social patterns and dynamics; (ii) the importance of the meso level of social networks; and (iii) the two-way, process linkages between micro and macro aspects as a fundamental source of social uncertainty and unpredictability.
Performance and activated sludge characteristics at short solid retention time in a submerged MBR: effects of C/N ratio of wastewater

ABSTRACT This study investigated the effect of carbon to nitrogen (C/N) ratio of influent wastewater on performance and activated sludge properties at a sludge retention time of 5 d in a submerged membrane bioreactor. The chemical oxygen demand and ammonia–Nitrogen (NH3–N) removal efﬁciencies were found to be over 96.3% and 86.9% in the sMBRs having different C/N ratios. It was found that total extracellular polymeric substances and total soluble microbial products increased with an increase in C/N ratio. It was also observed that critical flux, relative hydrophobicity and zeta potential values decreased, and capillary suction time, particle size and viscosity of sludge increased as the C/N ratio increased.
A packet switching communication-based test access mechanism for system chips

In this paper, a Test Access Mechanism (TAM) architecture based on a packet switching communication network is presented. The basic goal is to develop a modular, generic, and configurable TAM.The proposed architecture provides a modular TAM that provides two levels of scalability, i.e., design-version scalability and multi-level scalability. Core access time and interconnect length models and simulation results for the proposed architecture are presented and compared to that of a bus- based TAM.
An efficient method for facial expression recognition

In this paper, an efficient method for human facial expression recognition is presented. Our method includes two major techniques: spatially maximum occurrence model (SMOM), which is used to describe the different facial expressions; and elastic shape-texture matching (ESTM), which is used to compute the similarity between two images. The combination of these two techniques, namely the SMOM-ESTM method, is used to classify the facial expressions. With our approach, the recognition rate based on the AR database is 94.5%.
Use of Reading Pen Assistive Technology to Accommodate Post-Secondary Students with Reading Disabilities

ABSTRACT Reading pens are a form of assistive technology that may be used to bypass weak word decoding and vocabulary skills of students with reading disabilities. Only two known studies have examined the effects of reading pens on the comprehension of school-aged students, and no known studies have been published regarding post-secondary students. The present study investigated the effects of reading pen assistive technology on the comprehension accuracy and rate of three post-secondary students with university-recognized reading disabilities. An alternating treatments design was implemented to compare the effects of (1) a reading pen decoding accommodation, (2) concurrent reading pen decoding and vocabulary accommodations, and (3) a no-accommodation control condition on the comprehension of the three participants when provided college level difficulty reading passages. Results indicate that use of a reading pen did not uniformly improve the comprehension of the post-secondary students. However, the student with the poorest reading skills benefitted the most. Discussion focuses on explanations for the results, practical implications for post-secondary students with reading disabilities, and future directions for study.
Graph-Based Resource Allocation for D2D Communications Underlying Cellular Networks in Multiuser Scenario

With the characteristics of considerable user equipment, massive traffic and numerous local services, but limited frequency resources, the mobile communications in the future require efficient use of frequency resources. Device-to-device (D2D) communications underlying cellular networks have been considered as a promising solution to improve the resources utilization in local scenario. In this paper, we investigated the resources allocation problem in multiuser scenario and proposed a graph-based resources allocation scheme which can achieve suboptimal performance but with low computational complexity and less feedback information.
Fast piecewise-constant approximation of images

In this work, we present a Least-Square-Error (LSE), recursive method for generating piecewise-constant approximations of images. The method is developed using an optimization approach to minimize a cost function. The cost function, proposed here, is based on segmenting the image, recursively, using Binary Space Partitionings (BSPs) of the image domain. We derive a LSE necessary condition for the optimum piecewise-constant approximation, and use this condition to develop an algorithm for generating the LSE, BSP- based approximation. The proposed algorithm provides a significant reduction in the computational expense when compared with a brute force method. As shown in the paper, the LSE algorithm generates efficient segmentations of simple as well as complex images. This shows the potential of the LSE approximation approach for image coding applications. Moreover, the BSP-based segmentation provides a very simple (yet flexible) description of the regions resulting from the partitioning. This makes the proposed approximation method useful for performing image affine transformations (e.g., rotation and scaling) which are common in computer graphics applications.
Recognition of a translational pulse in noise

One of the basic problems in pattern recognition is the detection of a pattern in noise. This problem becomes particularly difficult if the pattern varies in position and size. A system necessary to achieve this result can be modeled in a number of different ways. One currently popular approach is to use a neural network. (1,2) The advantage to using a neural network is that once the basic structure is assumed the characteristics of the network, described by it's weights, can then be learned. The learning or training process involves developing a training set of known inputs and outputs for the system and adapting the internal weights of the network so that the inputs will yield the desired outputs. The weights are adjusted to minimize the error, according to some criteria, between the actual outputs and the desired outputs. Most neural networks are composed of first order terms, that is, z = f{ w0 + wij xj } where xj are the inputs, z are the first level (or hidden) outputs, w are weight terms and the functional relationship is normally a sigmoid function for inputs between zero and one. Usually, there are at least two levels of this type. In other words, the output, yi, would be given by yk = f{ u0 + uik Zj } where y are the final outputs, u are the weights and the other terms are as before. This type of network is trained using a back-propagation technique. Neural networks offer hope in the possible solution of detecting an object in noise by proper training of the network to recognize the characteristics of the object and ignoring the noise. Unfortunately, most neural networks cannot be trained to detect an object that appears in different positions. In other words, most neural networks are not translationally invariant. However, some special higher order neural networks have been shown to posses translational invariance
Collaborative development of an online pharmacy experiential learning database

Academics preparing students for experiential placements within professional programs require considerable curriculum planning and pedagogical expertise. Communities of practice involving workshops and online processes provide opportunities for collaborative work in developing quality curriculum materials and also in supporting widespread dissemination. The aim of an Australian Learning and Teaching Council funded project was to collaboratively establish an online repository of tasks and other associated resources. These tasks were intended for potential inclusion in the suite of activities that could be required to be completed in a pharmacy experiential clinical placement. An educational template and website were initially created, with over 90 academics and other industry partners subsequently attending a series of workshops to share ideas and develop the online materials. Online surveys regarding the tasks, written feedback concerning workshop processes and interviews were conducted as part of the ongoing evaluation processes to ascertain the effectiveness of the tasks and processes and to inform future directions. Workshops and follow up processes resulted in publication of twenty eight tasks, positive responses to the materials and to the collaborative processes.
REDUCTION OF BALLISTOCARDIOGRAM ARTIFACT IN THE SIMULTANEOUS ACQUISITION AND FUNCTIONAL MAGNETIC RESONANCE IMAGES

The combination of Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) is now being used to analyze brain function. However, Ballistocardiogram Artifact (BA), which is caused hy the pulsatile motion related to the heart beat, dominates the EEG signal in the MR environment. The objective of this research is to reduce these MR-induced artifacts in order to extract useful information from the EEG recordings, specifically auditory Event-Related Potentials (ERPs). The BA was reduced through the use of an algorithm which creates an adaptive BA template by median-filtering the previous 10 artifacts in the EEG signal. The continuously updated template is then subtracted from each BA in the EEG signal. Results are reported for five subjects, and it was found that the results for the MisMatch Negativities (MMNs) were comparable to those that have previously heen reported for studies using auditory frequency deviants. The methods used to reduce the BA in this study demonstrate that the acquisition nf auditory ERPs along with the sobsequent MMN component can validly he obtained in the MR-environment.
A probe into the citation patterns of high-quality and high-impact publications

Li, J., & Ye, F. Y. (2014). A probe into the citation patterns of high-quality and high-impact publications. Malaysian Journal of Library & Information Science, Vol.19, no. 2: 17-33. Enlightened by Avramescu’s studies, we classified the citation patterns of high-quality and highimpact publicationsinto five mathematical types: lognormal type, exponential-type, polynomialtype, wave-type and sleeping-beauty. Based on practical datasets of high-quality and high-impact publications, the five types of citation patterns are fitted well at statistical level. The results reveal that high-quality publications usually appear irregular citation curves (wave-type and sleepingbeauty) and high-impact publications tend to show regular ones (lognormal-type, exponential-type and polynomial-type).
The framework of axiomatics fuzzy sets based fuzzy classifiers

In this paper we will propose a new classifier design based on the AFS fuzzy theory. First, we will briefly review the current researches in data classification based on fuzzy and rough set theories and then present the AFS framework. Second, we will present new membership functions for fuzzy sets with their logic operations in the AFS framework and then tackle some theoretical and computational problems related to classifier design. Third, we will develop a new approach for fuzzy classifier design based on the proposed membership functions and their logic operations. Finally, a well-known example is used to illustrate its effectiveness. The advantage of this classifier is in two-folds. One is that it can mimic the human reasoning comprehensively and offers a far more flexible and effective way for the study of large-scale intelligent systems. The other is its simplicity in methodology and mathematical beauty in fuzzy theory.
Heaps and Hops

This dissertation is about the specification and verification of copyless message-passing programs, a particular kind of concurrent programs that communicate by message passing. Instead of copying messages over channels, processes exchange pointers into a shared memory where the actual contents of messages are stored. Channels are themselves objects in the heap that can be communicated, thus achieving full mobility. This flexible and efficient programming paradigm must be used carefully: every pointer that is communicated becomes shared between its sender and its recipient, which may introduce races. To err on the side of caution, the sender process should not attempt to access the area of storage circumscribed by a message once it has been sent. Indeed, this right is now reserved to the recipient, who may already have modified it or even disposed of it. In other words, the ownership of pieces of heap hops from process to process following the flow of messages. Copyless message passing combines two features of programs that make formal verification challenging: explicit memory management and concurrency. To tackle these difficulties, we base our approach on two recent developments. On the one hand, concurrent separation logic produces concise proofs of pointer-manipulating programs by keeping track only of those portions of storage owned by the program. We use such local reasoning techniques to analyse the fluxes of ownership in programs, and ensure in particular that no dangling pointer will be dereferenced or freed at runtime. On the other hand, channel contracts, a form of session types introduced by the S♯ programming language, provide an abstraction of the exchanges of messages that can be used to statically verify that programs never face unexpected message receptions and that all messages are delivered before a channel is closed. The contributions contained in this dissertation fall into three categories. First, we give a semantics to copyless message-passing programs, the ownership transfers they induce and contracts, and link the three together. In doing so, we provide the first formal model of a theoretically significant subset of the S♯ programming language. In particular, we show that some properties of their contracts rub off on programs, which justifies their use as protocol specifications. Second, we introduce the first proof system for copyless message passing, based on separation logic and contracts. The proof system discharges parts of the verification of programs on the verification of their contracts. The marriage of these two techniques allows one to prove that programs are free from memory faults, race conditions and message-passing errors such as unspecified receptions and undelivered messages. Moreover, we show how the logic and contracts cooperate to prove the absence of memory leaks. Third, we give an implementation of our analysis, Heap-Hop, that takes annotated
Flame image segmentation algorithm based on background subtraction

Considering the defect and imperfection of flame pixel point extraction and the bad environmental adaptability in the field of the present fire flame image segmentation algorithm, we put forward a kind of new algorithm based on the background difference method and fire flame color criterion. The adaptive background differencing method can detect and find objects which are moving or changing in the view field. The color criterion of fire flame can judge the color of flame of the moving objects, and then extract the flame image. Finally, the experimental results show that this algorithm has better adapt to the changing environment, and the flame extracting more accurately, perfect and stable.
New metrics for clutter affecting human target acquisition

Clutter plays a very important role in the area of human-in-the-loop target acquisition. A great deal of interest has recently been shown in defining clutter for electro-optical images. In spite of so many definitions available, no single clutter definition has been agreed on by the electro-optical community as being the best. We modify the structure similarity index, which is extensively used for image quality assessment, to be clutter metrics and call them target structure similarity measures (TSSIMs). Two different methods for calculating the TSSIM metrics are suggested. The TSSIMs of many images in Search/spl I.bar/2 dataset have been analyzed. Experimental results show the proposed metrics correlate very well to the detection probability of the observers.
Intrinsic Plagiarism Detection with kohonen Self Organizing Maps

Summary form only given. In this invited talk, the millimetre-wave (mmW) antenna arrays which are fully integrated into low-temperature co-fired ceramic (LTCC) with substrate integrated concept are reviewed. We start with addressing the important challenges in designing mmW antennas such as losses, fabrication, and measurement. After that, three typical designs are introduced as examples. A 60-GHz antenna array with greatly reduced loss caused by surface waves is first introduced. With the proposed cavity technique, the gain of the array increases by up to 2 dB. Second, a broadband high-gain 60-GHz LTCC array is shown. The multiple layered LTCC substrate provides more freedom to integrate the array and feeding network in substrate with much low insertion loss and consistent radiation patterns using parallel feeding structures. Finally, the design and measurement of a 140GHz LTCC antenna array is reported. The challenges related to fabrication and measurement is highlighted.
An algorithm for estimation of frequencies of biological signals using adaptive IIR line enhancers

An estimator using an adaptive IIR filter form was used to estimate the frequencies of a biological signal. This signal was the instantaneous ventricular diameter of a dog's heart. This method was found to be more accurate in determining frequency than traditional FFT and periodogram methods. Its high speed of estimation makes it useful as a real time process. <<ETX>>
Chaos communications-principles, schemes, and system analysis

This paper provides a comprehensive overview of chaotic communication methods and schemes with emphasis on digital schemes. Starting from general demands for communications, the general communication system structure is introduced. From this basic viewpoint, different classical and chaotic modulation and demodulation methods are treated and classified. For the performance analysis and comparison, a discrete-time statistical calculus is developed and applied to chaotic signal processing schemes. Discrete-time baseband models are developed, which are suitable for a statistical performance analysis. Analysis results for various example systems are provided and compared. New decoder structures are proposed and included in the comparative studies.
Software Engineering with Obj: Algebraic Specification In Action

Preface. Introduction J. Goguen, G. Malcolm. Part I: An Introduction to OBJ. 1. Introducing OBJ J.A. Goguen, et al. Part II: OBJ Specifications. 2. Specifying in OBJ, Verifying in REVE and Some Ideas About Time V. Stavridou. 3. Constructing a Graphics System with OBJ2: A Practical Guide A.T. Nakagawa, K. Futatsugi. 4. Applications of OBJ to the Specification of Standards for Computer Graphics D.A. Duce. Part III: Semantics in OBJ. 5. Semantic Specifications for the Rewrite Rule Machine J.A. Goguen. 6. OBJ for OBJ C. Kirchner, et al. 7. OBJSA Nets: OBJ and Petri Nets for Specifying Concurrent Systems E. Battiston, et al. Part IV: Parameterized Programming. 8. A LOTOS Simulator in OBJ K. Ohmaki, et al. 9. More Higher Order Programming in OBJ J.A. Goguen, G. Malcolm. References. Index.
Juggling Points and Polygons: GIS Researchers’ Metadata and Search Needs

This article discusses the results of a focus group analyzing advanced and intermediate Geographic Information System (GIS) researchers’ metadata needs and information-finding behavior while using the online GIS Lookup at North Carolina State University (NCSU) Libraries, as well as a metadata normalization project that resulted from study findings. Information was gathered on what metadata is important to GIS researchers for resource discovery, how researchers want to be able to search for data sets, and the importance of controlled vocabulary for GIS keywords.
FATİH PROJESİ ÜZERİNE YAPILAN AKADEMİK ÇALIŞMALARIN İÇERİK ANALİZİ

Bu calismanin amaci, 2011 yilindan gunumuze kadar Firsatlari Arttirma ve Teknolojiyi Iyilestirme Hareketi (FATIH) Projesi ile ilgili olarak yapilan calismalari detayli bir sekilde incelemek ve egilimlerini ortaya cikarmaktir. Bu amacla 2011-2014 yillari arasinda yapilan uluslararasi ve ulusal FATIH projesi ile ilgili 120 makale, bildiri, lisansustu tez ve rapor icerik analizi yontemiyle incelenmistir. FATIH Projesi Yayin Siniflama Formu kullanilarak toplanan veriler betimleyici istatistikler ve grafiklerle sunulmustur. Cogunlugu BOTE’de gorev yapan akademisyenler tarafindan gerceklestirilen calismalarin daha cok nicel yontemlerle paydas tutumlarinin ele alindigi ve degerlendirme turunde calismalar oldugu tespit edilmistir. SSCI kapsamindaki dergilerde digerlerine gore cok daha az yayinladigi gozlenmistir. Elde edilen sonuclarin FATIH projesi ile ilgili calismalarin egilimini ortaya koyacagi gibi ayni zamanda var olan calismalardaki eksikliklerin saptanip bundan sonraki calismalar icin de yol gosterici olmasi dusunulmektedir.
Unscented Kalman Filter for SINS/GPS Integrated Navigation System

In this research work, we study on the Unscented Kalman Filter (UKF) to estimate GPS/SINS integrated navigation system. The heart of the UKF is the Unscented Transformation (UT). UKF is presented for simulation. Simulation results show the superior performance of this approach when compared with classical suboptimal techniques such as Extended Kalman Filter (EKF) in cases of large initial misalignment. The UKF has good performance in case of small initial misalignment. The research provides theoretical support for engineering design and modication.
An X‐Band Carbon‐Doped InGaP/GaAs Heterojunction Bipolar Transistor MMIC Oscillator

This paper addresses a fully‐integrated low phase noise X‐band oscillator fabricated using a carbon‐doped InGaP heterojunction bipolar transistor (HBT) GaAs process with a cutoff frequency of 53.2 GHz and maximum oscillation frequency of 70 GHz. The oscillator circuit consists of a negative resistance generating circuit with a base inductor, a resonating emitter circuit with a microstrip line, and a buffering resistive collector circuit with a tuning diode. The oscillator exhibits 4.33 dBm output power and achieves −127.8 dBc/Hz phase noise at 100 kHz away from a 10.39 GHz oscillating frequency, which benchmarks the lowest reported phase noise achieved for a monolithic X‐band oscillator. The oscillator draws a 36 mA current from a 6.19 V supply with 47.1 MHz of frequency tuning range using a 4 V change. It occupies a 0.8 mm × 0.8 mm die area.