Miracle-dz/UniFAR-FTUs huggingface dataset:
Business Requirement Negotiation based on Generalized Requirement Approach (GRA)

Business software development is based on the specific business requirements that are collected during requirement negotiation process. Gathering business requirements, when final product requirements are dictated by known client, can be a difficult process. An idea about new business product can be obscure, and described by general terms that contributes very much common misunderstandings. Business requirement verification accomplished by using text and graphics, and manual review processes, can be slow, error prone and expensive. Misunderstandings and omitted requirements affect future software product. This research work proposes new approach to requirement negotiation, the Generalized Requirement Approach (GRA) and is focused on demonstration of business requirement during requirement negotiation process. The process of the business requirement negotiation is guided by the set of predefined objects that store requirement description in the common repository, in the structured text format. The objects attributes and properties are guidelines for specifying sufficient level of requirement details for generating source code that is used for requirement demonstration. The source code and executables are generated without manual programming.
Simulation-based autonomous systems in discrete and continuous domains

Highly dynamic, probabilistic and potentially only partially known domains render classical techniques for system development infeasible. Enabling autonomous adaptation by providing decision making and learning capabilities yields systems with the abilities that are necessary to deal with these challenges. The key to system autonomy is to drop exact specification of runtime behavior in favor of a whole space of solutions. This space can be explored by the system at runtime according to its current situation, and potential traces in this space can be evaluated w.r. t. the system's goals. Concrete behavior is then compiled based on the results of search and evaluation. This thesis studies the use of simulation-based Monte Carlo methods for decision making and learning that enable efficient and adequate system autonomy in discrete and continuous domains.
Response Time Analysis of Mobile Application DNUN in New Relic Monitoring Platform

In this paper we present a case study using New Relic as a monitoring platform to analyse the performance of mobile applications. DNUN (Danger Notification and User Navigation) is the application assumed to be evaluated. DNUN is associated with a geolocation system to navigate to the location of an object for immediate/later use from anywhere on the globe. We use the response time as the metric that Application Performance Management uses to measure the reliability of the DNUN application. We install DNUN app into the New Relic program using gem and configuration files. The dashboard proves that the overall rating of the app is excellent based on the response time performance.
Improved connectivity-based layout segmentation method

Layout segmentation is an important part of layout analysis.An improved page segmentation algorithm based on connective region which can effectively and quickly split the more complex images is presented,which is effective in reducing segmentation errors in the threshold of the original algorithm.The regions of the single text font have been expanded in the text image,so that the follow-up statistics in the distance between the connected regions is more accurate and convenient.The larger connected regions are formed by smearing the image through the statistic in the distance between the connected regions,and the regions of the text image are segmented.Experimental results show that the method is accurate,efficient and applicable,and it is superior for the more complex layouts segmentation.
Architectural Support for Power Reduction in High Performance Microprocessors

Prompted by demands in portability and low cost packaging, the microprocessor industry has started viewing power, along with area and performance, as a decisive design factor in todays microprocessors. Most of the research in recent years has focused on the circuit, gate and RT-levels of the design. In this paper, we focus on the software running on a microprocessor and we view the program as a power consumer. Our work concentrates on the role of the compiler in the construction of “power-efficient” code, and especially its interaction with the hardware so that unnecessary activity is saved. We propose a technique that effectively shuts-down the Instruction Fetch Unit (IF) of a processor when the execution thread is caught within a loop. This mechanism can have very substantial power savings, since the IF unit is the main power consumer in most of todays high-performance microprocessors. *This work was supported by Intel Corp.
Developing Students Workbook for English Profession

This study is aimed at developing English Profession material. In this case, the product isÂ English Profession material in teaching English. To support the study, the appropriate design that the researcher applied was research and development (R & D). To support the study, the appropriate design that the researcher applied was Research and Development . Â The result of need assessment,Â consists of 1) the College Need English Profession material, 2) the Students need toward English Profession material, 3) The Economics Graduates about English at Economics Department, 4) theÂ Curriculum maker interview. Â After that the material mapping to develops the first draft of the material, then gave the product to the expert validation, after revised the result of the try out of the material, the researcher revised of the product and got the final. The final product consists of the good cover, the material by using communicative approach which full activitiesÂ ofÂ reading andÂ speaking also the essential phrases for use in real-life situation. Key word : Developing, English Profession Material, studentsâ€™ workbook
Sustainable Urban Community Construction Based on Affordance Theory

—Aiming at the discordance between human behavior and community environment existing in the urban community construction under the current paradigm of computational psychology, and the disorderly development of the community under the functional analysis method, this paper analyzes the ecological connotation of the affordance theory, and puts forward the development modes of sustainable urban community construction based on affordance theory by using the research method of ecology. These modes are constructing the ecological communities with embodiment fitness, constructing urban community environment with the integral open interactivity, and constructing a self-organizing urban community. It concludes that the affordance theory can provide the realization path and ecological method for sustainable community construction. The innovation of this paper is to introduce the ecological connotation of affordance theory into sustainable urban community construction, and propose ecological development ideas and methodological mechanisms.
Synchronizing Robot Motions in Cooperative Tasks

This paper discusses the problem of synchronizing multiple robots in cooperative tasks. The problem is divided in two parts: first the problem of synchronizing robots which are handling large objects that cannot be manipulated only by one robot (hard connected robots) is discussed; the problem is approached from the point of view of path planning, kinematics, and movement synchronization. An alternative of control using the force control and dynamics which solved by using a decentralized control structure is also presented. The second problem concerns robot synchronization in a shared workspace; here is presented a method of control for collision avoidance and time optimization for the robot tasks (assembly/disassembly). In the conclusion section the results from the experiments conducted on two SCARA type robots (Adept Cobra s600) are presented.
The Adequacies and Inadequacies of Three Current Strategies to Recruit, Prepare, and Retain the Best Teachers for All Students

This paper analyzes the strengths and weaknesses of three of the major approaches to teacher education reform in the United States: the professionalization agenda, the deregulation agenda, and the social justice agenda. Although each of these approaches to reform has contributed in positive ways to improving teacher education in a manner that would lessen the achievement gap in U.S. public schools, they each have certain weaknesses that undermine this goal. There are also important issues of inequality in U.S. society that are not addressed by any of the reform agendas. In this article I discuss the research base on recruiting, preparing, and retaining good teachers for all of our children in relation to the different reform agendas that are currently being implemented in U.S. teacher education. Currently, there are three major agendas for the reform of teacher education being played out in teacher education programs across the country: the well-publicized professionalization agenda, propelled by the NCTAF Report, NCATE, TEAC, the National Board for Professional Teaching Standards, and other groups; the deregulation agenda, supported by the work of the Fordham Foundation and other conservative think tanks and foundations like the Abell Foundation, the Pacific Research Institute, and the Progressive Policy Institute; and the less-visible but widespread social justice agenda being implemented by individual teacher education practitioners in their teacher education classrooms and supported by groups like the National Association for Multicultural Education, policy
Research on User Adoption of Information Systems

the information system is built up in a modern way, integrated with people, data and information technology. The successful implementation of information systems is very important to the effectively usage of information system. This paper focused on the adoption of information systems, firstly explained the usage behavior of information system, and then mainly discussed the information technology adoption theory. And the development of information technology adoption theory was further discussed.
PENGARUH MANAJEMEN LABA DAN RASIO LIKUIDITAS TERHADAP AGRESIVITAS PAJAK

ABSTRAKPenelitian ini memiliki tujuan meneliti antara pengaruh Manajemen Laba dan Rasio Likuiditas terhadap Agresivitas Pajak. Sifat penelitian kuantitatif menggunakan sumber data sekunder. Populasinya perusahaan manufaktur pada yang terdaftar di BEI tahun 2012-2016. Sampel menggunakan purposive sampling dengan total sampel sebanyak 45 data dan Penelitian ini menggunakan SPSS 22. Hasil penelitian ini, bahwa Manajemen Laba berpengaruh negatif terhadap Agresivitas Pajak. Rasio Likuiditas berpengaruh terhadap Agresivitas Pajak. Secara simultan (Bersama-sama) Rasio Manajemen Laba dan Rasio Likuiditas berpengaruh signifikan terhadap Agresivitas Pajak.
Fairness and the Willingness to Pay for Renewable Energy

Overview For a long time fairness has been disregarded in both economic theory and empirical work. At least since Rabin's (1993) incorporation of fairness into game theory, experimental evidence suggests that fairness affects a plethora of economic outcomes. We build upon Fehr and Schmidt (1999), modeling fairness as self-centered inequality aversion with respect to individual contributions to a public good. Furthermore, we take into account Thaler’s (1985) concept of transaction utility according to which it is not only the value of a good but also the value of getting a good deal that influences individual well-being.
Pushing Archetypal Representational Systems Further

Abstract We revived Jung’s Archetypes to characterize what we see as an emerging confluence of evolutionary, embodied, and ecological responses to traditional cognitive models of mental representation. We propose that all humans possess archetypal representational systems that are (a) computationally grounded in perception and action, (b) shaped by learning and culture, and (c) biologically prepared by our ancestral past. Because these functionally modular systems arose in tandem with—and in response to—our increasingly complex social world, one implication is that even the most abstract issues studied in cognitive science may be, at least in part, scaffolded on more ancient social and emotional calculi.
SÜRDÜRÜLEBİLİRLİK RAPORLARININ KURUMSAL MARKA BAKIŞ AÇISI İLE ANALİZİ: ARÇELİK ÖRNEĞİ

Calismada, bir surdurulebilirlik raporu ornegi kullanilarak, kurumsal marka kavramlarinin surdurulebilirlik unsurlariyla nasil iliskilendirildigi tartisilmistir. Arastirmanin kurumsal surdurulebilirlige iliskin degiskenleri, BIST Surdurulebilirlik Endeksi’ne dâhil olma kriterlerini temel alan 54 adet unsurdan olusmaktadir. Kurumsal markaya iliskin degiskenler ise, Hatch ve Schultz’un (2003) vizyon, kultur ve imaj modelini temel alan 51 adet unsurdan olusmaktadir. Buna gore, Arcelik firmasinin 2015 yilina ait kurumsal surdurulebilirlik raporu, ilk adimda toplam 105 unsura gore kodlanarak tematik icerik analizi yapilmis, bu analiz sonunda ortaya cikan kavramlar arasi yakinlik iliskileri Semantik Ag Analizi kullanilarak gorsellestirilmis ve kumeleme analizine tabii tutulmustur. Analiz sonucunda 3 adet bulgu ortaya cikmistir. Ilki; Arcelik’in surdurulebilirlik raporunda, surdurulebilirligin ekonomik-sosyal boyutu ile calisanlari odak noktaya aldigi, surdurulebilirligin uygulamasini oncelikle onlar uzerinde gerceklestirdigi ve calisanlar vasitasiyla diger coklu paydaslara ulasmakta oldugudur. Ikincisi, surdurulebilirligin cevresel ve ekonomik boyutlari ile musteriler ve tedarikcilerin yakin iliskide kullanilmasidir. Sonuncusu, calisanlar ve tedarikciler arasinda etik algi, musterilere karsi ise cevreye duyarli imaj olusturmanin amaclandigidir. Bu calismanin alan yazina iki katkisi bulunmaktadir. Birincisi, surdurulebilirlik raporlarinin onceden belirlenen bir perspektiften (kurumsal marka) incelenmesi ve ikincisi kavram frekanslari yerine analizde kavramlar arasi iliskilerin kullanilmasidir.
Mastering Python Data Visualization

About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop your existing Python knowledge, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives, author-driven narratives, and the principles of perception Understand why Python is an effective tool for numerical computation much like MATLAB, and explore some interesting data structures that come with it Use various visualization techniques to explore how Python can be very useful for financial and statistical computations Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL, such as Hive, to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations that involve optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, the book covers the complete visualization process, using the most popular Python libraries with working examples. You will learn how to use NumPy, SciPy,
The complement of binary linear codes for error detection

For a binary code C of length n, let C~ = V/sub n//spl bsol/C, be the complementary code. The main result of this paper is to determine K(n), the largest integer such that C~ is good for error detection for all linear [n, k] codes C with k/spl les/K(n).
Analysis of variability in speech with applications to speech and speaker recognition

The speech signal has variability due to language, speakers, and communication channels. In this work, variability due to language is referred to as variability due to different phones in the language. It is also referred to as (inter-phone or) phone variability. Variability due to speakers is referred to as speaker variability, and variability due to different communication channels is referred as channel variability. The remaining variability in the signal is referred to as residual variability. The total variability in speech is decomposed using multivariate analysis of variance (MANOVA). Here variability in speech refers to variability in the set of features extracted from speech signal, and variability refers to covariance of features due to different phones, different speakers, and different channels. In this work, MANOVA is performed using three databases—HTIMIT, OGI Stories and OGI Numbers. Variability in the commonly used features is measured in spectral and temporal domains. The results are shown to be consistent across different databases and datasets. The results are also shown to be consistent with the previous studies. The results of MANOVA are applied in two ways. First, we show that contribution of the variabilities in features is related to their performance on speech and speaker recognition tasks. Second, we show that results of MANOVA can be used for deriving discriminant features for a given task. Relationship between results of MANOVA and speech and speaker recognition results is illustrated using several examples. We show that the change in the contribution of phone variability is related to change in the performance of the features on speech recognition task. Using MANOVA, we had observed that the variability due to phones spreads for approximately 250 ms around the current frame. We include this variability in the design of features using Linear discriminant analysis (LDA). The results show that features from joint analysis perform worse than combined analysis because joint analysis over-fits the training data and does not generalize on the test data. Specifically, we show that combination of spectral and temporal discriminants yields to the best joint time-frequency discriminants. (Abstract shortened by UMI.)
Group Data Verification for Enhancing the Storage Security in Cloud Computing

Objectives: A privacy-preserving mechanism for public auditing of shared data in cloud storage has been proposed. This boosts up the effectiveness of the verification task which is meant for auditing multiple tasks. It also reduces the response time and auditing time and thereby improves data integrity. Methods/Analysis: A privacy preserving methodology has been proposed which sustains the social interaction and examination on the data which is being mutually shared across the cloud. In scrupulous, ring signatures have been utilized to enhance the verifiability of the computed metadata and to improve the accuracy of the group data analysis. The proposed system maintains the secrecy of the mutual data. The confidentiality of the specific user in the group is ensured by data filtering mechanism. This mechanism masks the user’s private data from being accessed publicly across the cloud. The proposed system also supports multi-group audits simultaneously. Findings: A distinct privacy preserving mechanism is rarely available in the cloud storage especially for shared data. Also the personal information should not be disturbed by public verifiers. The ring mechanism shares only the verified information instead of sharing the entire file. This improves the integrity of the confidential data. The mechanism boosts the potency of substantive multi-group analysis to support the entire data cluster. This improvises the real time cloud data distribution. The identity of the signer is traceable by the group owner. Novelty/Improvement: Only registered users can login to the cloud. This prevents the unauthorized access to the cloud. Data is secured during cloud upload. Other users in the group have no permission to modify the data. Except the signer other users have got read-only permission.
Automatic generation of hardware FIR filters from a frequency domain specification

This article presents an open-source tool for the automatic design of reliable finite impulse response (FIR) filters, targeting FPGAs. It shows that user intervention can be limited to a very small number of relevant input parameters: a high-level frequency-domain specification, and input/output formats. All the other design parameters are computed automatically, using novel approaches to filter coefficient quantization and direct-form architecture implementation. Our tool guarantees a priori that the resulting architecture respects the specification while attempting to minimize its cost. Our approach is evaluated on a range of examples and shown to produce designs that are very competitive with the state of the art, with very little design effort.
An Effective Verification Method for Varying the Quality of Fingerprint Images

An Effective Verification Method for Varying the Quality of Fingerprint Images Taizo Umezaki, Member (Faculty of Engineering, Chubu University, Kasugai-shi, 487-8501 Ja pan.), Shozo Sato, Non-member (Research Center for Business & Engineering, Nihon Fukushi University, Nagoya-shi, 460-0011 Japan.), Akihito Kimura, Non-member (Hitachi Information Systems, Ltd., Tokyo, 140-0013 Japan.), Noriyuki Matsumoto, Non-member (Chuo Spring Co., Ltd., Nishikamo-gun, 470-0225 Japan.)
HDR video synthesis for vision systems in dynamic scenes

High dynamic range (HDR) image generation from a number of differently exposed low dynamic range (LDR) images has been extensively explored in the past few decades, and as a result of these efforts a large number of HDR synthesis methods have been proposed. Since HDR images are synthesized by combining well-exposed regions of the input images, one of the main challenges is dealing with camera or object motion. In this paper we propose a method for the synthesis of HDR video from a single camera using multiple, differently exposed video frames, with circularly alternating exposure times. One of the potential applications of the system is in driver assistance systems and autonomous vehicles, involving significant camera and object movement, non- uniform and temporally varying illumination, and the requirement of real-time performance. To achieve these goals simultaneously, we propose a HDR synthesis approach based on weighted averaging of aligned radiance maps. The computational complexity of high-quality optical flow methods for motion compensation is still pro- hibitively high for real-time applications. Instead, we rely on more efficient global projective transformations to solve camera movement, while moving objects are detected by thresholding the differences between the trans- formed and brightness adapted images in the set. To attain temporal consistency of the camera motion in the consecutive HDR frames, the parameters of the perspective transformation are stabilized over time by means of computationally efficient temporal filtering. We evaluated our results on several reference HDR videos, on synthetic scenes, and using 14-bit raw images taken with a standard camera.