Miracle-dz/UniFAR-FTUs huggingface dataset:
A Progress Report on the Discourse and Reference Components of PAL

Abstract : This paper reports on research being conducted on a computer assistant, called PAL. PAL is being designed to arrange various kinds of events with concern for the who, what, when, where and why of that event. The goal for PAL is to permit a speaker to interact with it in English and to use extended discourse to state the speaker's requirements. The portion of the language system discussed in this report disambiguates references from discourse and interprets the purpose of sentences of the discourse. PAL uses the focus of discourse to direct its attention to a portion of the discourse and to the database to which the discourse refers. The focus makes it possible to disambiguate references with minimal search. Focus and a frames representation of the discourse make it possible to interpret discourse purposes. The focus and representation of the discourse are explained, and the computational components of PAL which implement reference disambiguation and discourse interpretation are presented in detail. (Author)
KOMUNIKASI PEMBELAJARAN BERBASIS AL-QUR’AN

Komunikasi merupakan dasar eksistensi suatu masyarakat dan menentukan pola struktur masyarakat. Hubungan antar manusia dibangun atas dasar komunikasi. Dalam komunikasi manusia saling mempengaruhi, sehingga dengan demikian terbentuklah pengetahuan tentang pengalaman masing-masing orang. Komunikasi dapat membentuk manusia saling pengertian, menimbulkan persahabatan, memelihara kasih sayang, mempengaruhi sikap yang akhirnya dapat menimbulkan tindakan nyata riil. Dalam kegiatan pendidikan pada umumnya dan dalam proses kegiatan belajar pada khususnya, komunikasi merupakan salah satu faktor utama yang turut serta dalam penentuan pencapaian tujuan pendidikan, atau kata lain dapat dikatakan bahwa komunikasi merupakan sarana atau media dalam rangka pencapaian tujuan pendidikan. Maka untuk mencapai interaksi belajar mengajar perlu adanya komunikasi yang jelas antara guru (komunikator) dengan siswa (komunikan). Sehingga terpadu dua kegiatan yang berdaya guna dalam mencapai tujuan pengajaran dan pendidikan dimana siswa dapat sukses dalam tugas belajarnya, begitu pula guru dapat berhasil mengajar dan mendidik sesuai dengan tujuan yang hendak dicapai. Pada dasarnya motivasi belajar siswa sangat dipengaruhi adanya komunikasi guru atau pengajar. Seorang pengajar yang tidak piawai atau jarang melakukan komunikasi dengan muridnya akan atau dapat mengalami kegagalan dalam proses belajar mengajar. Pengajar adalah pihak yang paling bertanggungjawab terhadap berlangsungnya komunikasi yang efektif dalam pembelajaran, sehingga pengajar dituntut memiliki kemampuan berkomunikasi yang baik agar menghasilkan proses pembelajaran yang efektif.Dalam berbagai kasus masih banyak ditemukan aktifitas belajar mengajar yang belum efektif dikarenakan faktor buruknya komunikasi di dalam dan di luar kelas. Diantaranya masih ditemukan siswa yang rendah motivasinya. Bila tengah berlangsung proses belajar mengajar banyak siswa yang mengantuk dan mengobrol dengan teman sebangkunya. Apabila diberikan pertanyaan oleh guru hanya sebagian siswa saja yang dapat menjawab, apabila diberikan kesempatan untuk bertanya hanya satu dua orang saja yang berani untuk bertanya. Menurut Luna Cahya seorang pemerhati pendidikan, bahwa disadari atau tidak, kita harus mengakui bahwa para siswa seringkali punya pandangan yang terpolarisasi terhadap cara mengajar guru-gurunya. Sederhananya, ada guru yang dipandang oleh para siswa sebagai guru yang cara ngajarnya asik, seru, mudah dipahami. Guru-guru seperti ini seringkali menjadi idola murid-murid bahkan jam pelajarannya ditunggu-tunggu oleh para siswa. Sementara itu, di sisi lain ada juga guru yang dipandang siswa sebagai guru yang cara mengajarnya membosankan, bikin ngantuk, materinya tidak menarik, dll. Dua bentuk polarisasi dari cara pandang siswa terhadap gurunya ini memang seringkali ada, bahkan bersifat kolektif. Kalau ada beberapa anak yang menganggap gurunya ini membosankan, masa satu kelas akan kompak menganggap guru tersebut membosankan.
Survey On Novel Techniques for Effective Image Search Based On Users Intention

Image search is a specialized data search used to find images. To search for images, a user may provide query terms such as keyword, image file/link, or click on some image, and the system will return images "similar" to the query. The similarity used for search criteria could be meta tags, color distribution in images, region/shape attributes, etc. Many commercial Internet scale image search engines use only keywords as queries. Users type query keywords in the hope of finding a certain type of images. The search engine returns thousands of images ranked by the keywords extracted from the surrounding text. It is well known that text-based image search suffers from the ambiguity of query keywords. The keywords provided by users tend to be short. They cannot describe the content of images accurately. The search results are noisy and consist of images with quite different semantic meanings. For example, if a user wants to search for an “apple” image, he/she may request a query search using the keyword “apple” to the corresponding image search engine. The meanings of the word “apple” include apple fruit, apple computer, and apple ipod. The search results will contain different categories, such as “green apple,” “red apple,” “apple logo,” and “iphone” because of the ambiguity of the word “apple”. This leads to ambiguous & noisy search results which are not satisfactory to fulfill the user query request. In order to solve the ambiguity, additional information has to be used to capture users’ search intention. A comprehensive survey and study of various techniques for effective image retrieval based on users’ search intention has been presented in this paper.
Medical Image Fusion Technique Using Singlelevel and Multilevel DWT

In the field of medicine to evaluate or to examine the inner body parts different radiometric scanning techniques can be used. Some most commonly used scanning techniques include the computerized tomography scan (CT scan) and magnetic resonance imaging scan (MRI scan) but the images of various body parts taken by using these scanning techniques are having their own merits and demerits. MRI scans can show the images of soft tissues very clearly but it cannot show the images of bones and hard tissues clearly. the idea of combining images from different modalities become very important and medical image fusion has emerged as a new promising research field. Image fusion involves merging two or more images in such a way as to retain the most desirable characteristics of input image in resultant output Image. By observing medical fusion image, doctor could easily conform the position of illness. In this paper dwt and three level dwt techniques have been studied and the simulation carried out using matlab and the results from a number of image quality metrics schemes are to be compared. Keywords-image fusion ;discrete wavelet transform; computerized tomography scan; magnetic resonance imaging scan; image quality metrics
MVTOBIT: Stata module to calculate multivariate tobit models by simulated maximum likelihood (SML)

mvtobit estimates M-equation tobit models (including bivariate tobit models). To evaluate the multidimensional integrals, mvtobit relies on Cappellari & Jenkins' mdraws and egen mvnp commands to implement the Geweke-Hajivassiliou-Keane (GHK) simulator. The estimator is implemented with the lf method and supports all the usual maximum likelihood features. Computation time is an issue with many equations. Users of Stata 9 and higher should have a look at the user command cmp.
Improving functional density through run-time circuit reconfiguration

The dense array of programmable logic and rich interconnect of modern FPGAs make them ideal for solving many application-specific computing challenges. By specializing all aspects of a computing structure, these FPGA based architectures achieve unusual levels of efficiency and performance. The benefits of gate-level specialization can be extended by reconfiguring an application-specific computing structure at run-time. This technique, termed run-time reconfiguration (RTR), allows dynamic conditions to dictate the optimal computing architecture within the programmable logic resources. The use of this technique, however, requires additional time for circuit reconfiguration. A functional density metric is introduced that balances the advantages of RTR against this reconfiguration cost. This metric is used to justify RTR within a special-purpose computing architecture and identify the effects of reconfiguration time within a run-time reconfigured application. Several run-time reconfigured applications are presented and shown to provide greater functional density than a conventional, statically configured alternative. Since the functional density of such run-time reconfigured systems is so sensitive to reconfiguration time, configuration improvement methods have been suggested. Several configuration improvement techniques are reviewed and analyzed using the functional density metric. Techniques that reduce device configuration time increase the functional density of RTR applications and extend the benefits of RTR to additional configurable computing applications.
METACOGNITIVE PROMPT AS A MEANS TO IMPROVE STUDENTS’ TASK COMPREHENSION

One of the most dominant errors made by (Indonesian) students when solving context-based PISA mathematics tasks is error in comprehending the task. This paper reports a study on improving students’ comprehension of context-based tasks. A total of 299 eight graders from six junior high schools in the Province of Yogyakarta participated in this study. The study employed a field experiment with a pretest-posttest control-group design for which we used an intervention program comprising a set of context-based tasks which were supplemented with metacognitive prompts. The result of the study shows a significant difference between the experimental group and the control group on the decrease in the total number of errors (² (1, n = 4127) = 4.149, p = . 042). In comparison to their counterparts in the control group, the students in the experimental group had a better improvement regarding two aspects of task comprehension: understanding the instruction of the task and selecting relevant information. Key words: context-based tasks; metacognitive prompts; task comprehension
Applied optimal control & estimation : digital design & implementation

This book covers optimal design for multi-input/multi-output (MIMO) systems, providing not only the theoretical background, but also practical implementation techniques for control and estimation algorithms. Real-time implementation methods for a wide range of industries and control problems are detailed, including control of computer disk drives, chemical process control, and aircraft control. The book puts modern control design tools - based on solving matrix equation - well within the reach of the individual design engineer. You'll see how to design control systems using software programs, simulate these controllers on digital controllers, and then implement digital controllers on actual processors using digital signal processors (DSPs). Appropriate
Naked Eye Pseudo 3D Display Technology Outside the Screen

The 3D display technology based on motion parallax has the advantages of no need to wear glasses and has no limitation on the viewing angle. However, the current problems of this method include 3D scenes and models can only be displayed within the screen; the system is sensitive to light. For the first problem, we proposed the concept of virtual bezel, which makes out system could produce a strong illusion that objects displayed outside the screen, and greatly increases the visual impact of 3D display. For the problem of light sensitivity, unlike other system using RGB camera, we use RGB-D images to detect and track the viewer’s face, which makes our system work properly even at night.
Prototype Selection for Composite Nearest Neighbor Classifiers

Combining the predictions of a set of classifiers has been shown to be an effective way to create composite classifiers that are more accurate than any of the component classifiers. Increased accuracy has been shown in a variety of real-world applications, ranging from protein sequence identification to determining the fat content of ground meat. Despite such individual successes, the answers are not known to fundamental questions about classifier combination, such as "Can classifiers from any given model class be combined to create a composite classifier with higher accuracy? " or "Is it possible to increase the accuracy of a given classifier by combining its predictions with those of only a small number of other classifiers? ". The goal of this dissertation is to provide answers to these and closely related questions with respect to a particular model class, the class of nearest neighbor classifiers. We undertake the first study that investigates in depth the combination of nearest neighbor classifiers. Although previous research has questioned the utility of combining nearest neighbor classifiers, we introduce algorithms that combine a small number of component nearest neighbor classifiers, where each of the components stores a small number of prototypical instances. In a variety of domains, we show that these algorithms yield composite classifiers that are more accurate than a nearest neighbor classifier that stores all training instances as prototypes. The research presented in this dissertation also extends previous work on prototype selection for an independent nearest neighbor classifier. We show that in many domains, storing a very small number of prototypes can provide classification accuracy greater than or equal to that of a nearest neighbor classifier that stores all training instances. We extend previous work by demonstrating that algorithms that rely primarily on random sampling can effectively choose a small number of prototypes.
Computational intelligence in robotics and automation

Robots have been used in many fields of industry. Robots are important for automation in the factory, laboratory and office, as well as in space. These robots must have the capability for intelligence such as adaptation, learning and evolution. Computational intelligence including neural networks, fuzzy systems and genetic algorithms have been discussed for realizing human intelligence. In order to realize human intelligence functions such as perception, inference, decision making and learning should be integrated. This paper deals with this kind of intelligent robot systems. The intelligence of a robotic system depends on the architecture of hardware and software as a whole system. This paper introduces a robotic system with structured intelligence.
Exploratory Methodology for Acquiring Architectural Plans Based on Spatial Graph Similarity

In architectural planning, previous cases of similar spatial program provide important data for architectural design. Case-based reasoning (CBR) paradigm in the field of architectural design is closely related to the designing behavior of a planner who makes use of similar architectural designs and spatial programs in the past. In CBR, spatial graph can be constituted with most fundamental data, which can provide a method of searching spatial program by using visual graphs. This study developed a system for CBR that can analyze the similarity through graph comparison and search for buildings. This is an integrated system that is able to compare space similarity of different buildings and analyze their types, in addition to the analysis on a space within a single structure.
Global illumination models for volume rendering

The increasing demand for realistic images has led to the development of several global illumination models and rendering techniques. Great effort has been taken to extend these illumination models and optimize the rendering techniques to produce more realistic images in less time. Despite this effort, most of these methods are designed for scenes consisting of geometric surface descriptions, and cannot directly render volumetric data. Volumetric data sets can be rendered using volume rendering techniques that, in order to decrease rendering times and therefore increase interactivity, typically employ only a local illumination model. The development of global illumination models and rendering techniques for volumetric data is the focus of this work. These illumination methods can be used to generate realistic images of scenes containing volumetric as well as geometric data. The volumetric global illumination methods can be employed by a visualization system in order to add intuitive cues to an image for a greater three-dimensional understanding of a scene. Also, these methods allow for amorphous effects that can not be captured using geometric illumination models, including clouds, fog, and smoke. A volumetric ray tracing method is presented that encompasses classical ray tracing while allowing for volume rendering effects. The definition of an intersection is extended to include intersection points for surface contributions to the intensity equation, and intersection segments for volumetric contributions. A method for accelerating primary and shadow rays is developed. A volumetric radiosity method is presented that encompasses classical radiosity while also including isotropic and diffuse volumetric interactions. Geometric surfaces and volumetric isosurfaces are approximated using standard surface patches, and voxels are used to approximate participating volumes. Diffuse volumetric interactions make it possible to give the appearance of shaded surfaces to scenes consisting of only volumetric data. Hierarchical techniques are applied to decrease the number of interactions required for a solution. Multipass methods are developed to increase realism by combining illumination methods. A multipass method that combines volumetric ray tracing and volumetric radiosity is presented. Also, a multipass method that extends volumetric ray tracing to account for indirect specular lighting is presented.
Evolution Versus Design: Controlling Autonomous Robots

This paper sets out and justifies a methodology for the development of the control systems, or ‘cognitive architectures)) of autonomous mobile robots. It will be argued that the design b y hand of such control systems becomes prohibitively dificult as complexity increases. The alternative approach of artificial evolution is presented. It is argued that the most useful basic building blocks for an evolved cognitive archite(*t ? ure are adaptive noise tolerant neural networks raiher than programs. These networks may be recurrent, and should operate in real time. Evolution should be incremental, using an extended and modified version of genetic algorithms. Time constraints mean that architecture evaluations must be largely done an simulation. Results from a simulation are presented. The pitfalls of simulations compared with reality is discussed, together with the importance of incorporating noise.
Security Enhanced Linux

Apart from the complex concept, the origin of SELinux may be a further reason for critics not to have a closer look at it. Considering the events that unraveled after May 2013 and the NSA leaks, some people wont like to hear that the kernel module written to enhance security on their systems originated in a National Security Agency (NSA) research project. Together with the Secure Computing Corporation (SCC), the NSA conducted research into the usage of a type enforcement based access control.
Detection And 3d Reconstruction Of Brain Tumor From Brain Mri Images

In the last 20 years we have a number of useful algorithms developed for segmentation of medical image. Each method comes with its own set of features. Daily growth of medical data volume leads to raise human mistakes in their manual analysis and increase the requests to analyze automatically. Therefore applying some tools to collect, classify, and analyze the medical data automatically is necessary to decrease the human mistakes. The analysis and study of the brain is of great interest due to its potential for studying early growth patterns and morphologic changes in the tumour process. Segmentation of anatomical regions of the brain is the fundamental problem in medical image analysis. In this paper brain tumor segmentation method has been developed and validated segmentation on 2D MRI Data. Also detected tumors are represented in 3-Dimensional (3D) view. 3D visualization of tumor yields actual shape and size of the tumors along with their positions. Finally, work was carried over to calculate the area of the tumor of single slice of MRI data set and then it was extended to calculate the volume of the tumor from multiple image MRI data sets. Experimental results for a single MRI slice have been reported. Key WordsTumor Segmentation, Morphological operations, MRI Image Slices, 3D visualization.
Multi-subspace pursuit algorithm based on body area network

Wireless body area networks (WBANs) provide a tremendous opportunity for remote health monitoring. However, the design of WBAN health monitoring system encounters a number of challenges including the process of the biomedical information. In this paper, we give an overview of the results of a special joint sparse model (JSM), JSM-2, in body area networks. We present JSM-2 for the signal groups that each signal has a common K-sparse characteristic although the biomedical signal groups are not all sparse signals. The reconstruction algorithm, multi-subspace pursuit algorithm, is proposed based on JSM-2. The algorithm combines the advantages of the previous study of the one-step greedy algorithm (OSGA) and simultaneous orthogonal matching pursuit (SOMP). Furthermore, the proposed algorithm not only performs better in sparse reconstruction performance than OSGA, but also needs less calculation than SOMP. The performance is evaluated through numerical simulations.
Embracing Insanity: Open Source Software Development

From the Publisher: In this book, you will learn where the Open Source movement comes from and what motivates its adherents. You will be introduced to the culture that fuels the movement, as well as the personalities and organizations that promote its growth. You will also understand the strengths of the Open Source movement and how it changes the way in which software is written. In addition, people and organizations wishing to participate in the Open Source world will be given a guide regarding what to do - and what not to do - and why. You do not need to be a technical wizard to read this book. It does not matter if you are an IT manager, a programmer, or just someone who is interested in new trends in technology. This book will peel away the mystery and misunderstandings surrounding the Open Source movement.
The New Digital Engineering Design and Graphics Process

With current computer-aided design technology, the traditional tasks of a designer, drafter, analyst, and prototype maker are all performed by a single engineer using modern digital engineering design tools. These digital tools include computer systems with 3-D solid modeling software, seamless links to engineering analysis and manufacturing simulations, and digital interfaces to rapid prototyping machines. While these new technology tools have been developed and are commercially available, they have not yet been integrated into mainstream engineering graphics education as the contemporary curriculum. This paper will summarize the digital engineering design process using current software that is widely available for the educational setting.