Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomedical Text Mining Based on Machine Learning: from Information Extraction to Coordination Identification

We focus on the information extraction from clinical trial MEDLINE abstracts. This is strongly connected with Evidence-based medicine (EBM), which has arisen from daily demands from patients for valid information about diagnosis, prognosis, therapy, and prevention, as well as from clinical doctors for up-to-date, correct, and effective sources of that information. At present, there are several practices that support EBM; one example is to manage systems that provide the summary of clinical studies for specified disorders. However, they mostly depend on human labor. Our future goal is to create a system that automatically summarizes original articles (such as clinical trial MEDLINE abstracts). As the necessary pre-processing, in this thesis, we concentrate on to develop the systems for information extraction and coordination disambiguation. In information extraction we shall extract compared treatments and patient population from phase III clinical trial MEDLINE abstracts. There we shall see that to mark terms of treatments and patients is not so difficult, however, not all the marked terms are valid for our purposes: extraction targets should be the treatments and patients that directly connect with the focusing clinical trial. So we shall attempt to select terms by employing a sentence classification filter that can make use of grammatical structures of sentences. There we encounter with the difficulties when we analyze sentences containing coordinated phrases using the state-of-the-art parser. From a viewpoint that coordinated phrases are likely to include important information for EBM, this problem is also significant. Then we propose a method for detecting and disambiguating coordinate phrases. Nearly all the previous methods focus on the construction of heuristic rules. Unlike ∗Doctoral Dissertation, Department of Information Processing, Graduate School of Information Science, Nara Institute of Science and Technology, NAIST-IS-DD461029, March 17, 2008.
Software Fault Tolerance: A Tutorial

Because of our present inability to produce error-free software, software fault tolerance is and will continue to be an important consideration in software systems. The root cause of software design errors is the complexity of the systems. Compounding the problems in building correct software is the difficulty in assessing the correctness of software for highly complex systems. After a brief overview of the software development processes, we note how hard-to-detect design faults are likely to be introduced during development and how software faults tend to be state-dependent and activated by particular input sequences. Although component reliability is an important quality measure for system level analysis, software reliability is hard to characterize and the use of post-verification reliability estimates remains a controversial issue. For some applications software safety is more important than reliability, and fault tolerance techniques used in those applications are aimed at preventing catastrophes. Single version software fault tolerance techniques discussed include system structuring and closure, atomic actions, inline fault detection, exception handling, and others. Multiversion techniques are based on the assumption that software built differently should fail differently and thus, if one of the redundant versions fails, it is expected that at least one of the other versions will provide an acceptable output. Recovery blocks, N-version programming, and other multiversion techniques are reviewed.
Readability level of reading texts in Bahasa Inggris for Senior High School Grade X published by Kemendikbud

Reading is one of the four language skills that should be acquired by the students in learning a language. To be able to read, reader needs materials that support her/him in reading. The material can be in form of reading texts in the textbook. However, not all reading text graded with the grade level of the students using the textbook. Therefore, choosing the right reading texts is important. Nuttall (2005:170) states, one of the criteria for evaluating text for reading development is readability. The study that the researcher conducted uses descriptive quantitative content analysis design and Fry Readability Graph. The aim of the study is to know the readability level of 16 reading texts from Bahasa Inggris for Grade X published by Kemendikbud. The researcher’s study showed that from 16 reading texts which were analyzed, there were 13 reading texts’ readability levels that can be analyzed while there are 3 reading texts of which the levels cannot be analyzed because the meeting point fell on the black area which considered that the grade level is not valid. The average number of the sentences and number of the syllables from the 16 reading texts fell in the area of grade level 9. This means that this textbook has the readability level of grade level 9. As the result, the researcher concluded that it is better for the writer of the textbook to give more concern about the readability level of the reading texts in the textbook beside focus on the Kompetensi Dasar (KD) and Kompetensi Inti (KI) of English subject of curriculum 2013 for Grade X.
A Mobile Application for Quick Classification of Plant Leaf Based on Color and Shape

— This paper presents an effective way to develop an android application that gives user the ability to identify plant species based on photographs of the plant’s leaf taken with mobile phone. The algorithm acquires a color image of the leaf using mobile phone’s camera and perform the classification by comparing the acquired image with the stored database image. The method proposed in the paper performs preprocessing to obtain the binary contour of the leaf, then morphological features of the leaf are obtained to generate feature vector of the leaf, then classifies the species based on the combination of computed feature vector. The system is first trained against several known species and then used to classify unknown species. The paper also presents a way to improve current system by providing classification based on shape and color of the plant’s leaf. To classify the leaf based on shape, the binary contour of the plant’s leaf is obtained using Otsu’s method and sobel operator. The classification based on color is achieved using the dominant color method. To compare the morphological features, Euclidean distance method is used.
The use and development of habere + infinitive in Latin

The paper discusses Latin constructions consisting of habere + infinitive. Habere + infinitive is used to express several different meanings, both ability/capacity and various kinds of deontic modalities as well as future tense. Within the framework of Lexical-Functional Grammar, I provide a syntactic analysis (f-structure) of habere + infinitive in each of its uses. Finally, a possible historical pathway of development is established, based on the Latin data combined with theoretical/cross-linguistic considerations.
Credit scoring model based on neural network

The research develops a neural network credit-scoring model by using the principle of multilayer perceptron. 106 selected listed companies are divided into two groups: "good" ones and "bad" ones. All the data come from China. The simulation results show that the neural network credit-scoring model has a high rate of classification accuracy and strong suitability. We construct the structure of the neural network credit scoring and present its learning algorithm.
Studio life : The construction of digital design competence

This paper analyses how interaction designers act and think in two different studio settings in order to understand what potential each setting presents for the development of digital design competence. We first observed interaction design students working in a design studio and then in a computer augmented interactive space. In the studio, the students oscillated continuously between individual and cooperative work, while in the interactive space, the work was focused on shared displays. The results describe how students collaborate to develop digital design competence, which not only includes competence in using digital media, but also competence in envisioning and articulating someone else’s future use of digital media.
Specification-based regression test suite generation and reduction

During maintenance of evolving software systems, regression testing is crucial for confirming that the unchanged parts of the system have not been adversely affected by the modifications on the system specification and implementation. It is timeand resource-consuming, especially for large software systems. Much attention has been paid to the regression testing area in recent years. Most regression testing techniques are code-based. There exists limited research on requirement-based regression testing techniques. In our research, we are interested in model-based regression testing techniques. Model-based testing involves, among other activities, test generation, execution, and evaluation using software models [Binder 00]. Some such models are given in formal description languages, e.g., Extended Finite State Machine (EFSM) models. In this thesis, we present two regression testing techniques, a regression test suite (RTS) generation method (RTSG method), and a regression test suite reduction method (RTSR method). Both methods are based on EFSM dependence analysis. The RTSG method generates regression test cases to construct a regression test suite instead of selecting test cases from an existing test suite. The RTSR method is an extension to an existing requirement-based regression test suite reduction approach presented in [Korel+02] and [Xie 05]. In this thesis, based on [Korel+02] and [Xie 05], twelve types of dependencies are identified related to three types of elementary modifications (EMs), i.e., adding, deleting, and changing transitions in an EFSM model representing an SUT. These dependencies capture the effects of the model on the EMs, the effects of the EMs on the model, and the side-effects of the EMs. The proposed RTSG method constructs an RTS by covering all occurrences of these dependencies caused in a given EFSM model by a given set of EMs. Given an EFSM representing the requirements of a system under test (SUT) and a set of EMs on the EFSM, interaction patterns are identified related to each type of EMs, i.e., adding, deleting, and changing transitions in the EFSM. These interaction patterns capture the effects of the model on the EMs, the effects of the EMs on the model, and the
A Text Mining Classification Framework and Its Experiments Using Aviation Datasets

This paper presents our text mining classification framework, that we implemented and evaluated using aviation datasets. Our contribution through the proposed framework and the algorithms is to create predictive models to predict the category labels for a given text input with high classification accuracy based on the experiments and by improving our algorithms and framework integrating with Natural Language Process (NLP) tools. Our preliminary experimental results indicate that the classification and prediction accuracy of the predictive models created from the framework improved from 40% to 90%. Our future work will be focused on expanding the prototyped analytics framework with big data analytics technologies for developing data-driven predictive analytics for related applications in other industries.
Sensitivity to Doppler shift and carrier frequency errors in OFDM systems-the consequences and solutions

Due to the intercarrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) mobile radio communication systems, the bit error rate (BER) of the received signals are extremely sensitive to Doppler frequency shifts and carrier synchronization errors. This paper studies the mechanism of the ICI signals, and then proposes a new method to overcome such problems without any equalization procedures. The results show that by using the self ICI cancellation scheme proposed, the ICI can be reduced significantly. Therefore this OFDM system suffers much less from performance degradation caused by frequency errors than the normal OFDM systems.
Theoretical analysis and experimental verification of a manipulator/sensor/environment model for force control

Models of increasing complexity are briefly discussed, and a fourth-order dynamic model composed of the manipulator, force sensor, and environment is analyzed. Study of the undamped and underdamped cases yields insight into the mode of oscillation of the system and provides the ability to extract system parameter values from the measured force values. The effect of hysteresis is considered. Experimental data for the arm and environment system under small oscillations are reported. Simulation results based on the extracted parameters closely match the experimental data, further confirming the validity of the model. <<ETX>>
Eating Our Own Cooking: Toward a Design Science of Research Methods

This paper argues that Design Science is an appropriate paradigm for research into Research Methods. Research Methods are designed and created by people to achieve a specific purpose – creating new knowledge. Research methods vary in utility depending on how well they their purpose in the particular contexts and contingencies for which they were developed. Applying a DSR perspective to research methods should yield increased utility in the application of research methods, better guidance in applying them and greater confidence in achieving the desired outcomes of applying them. Based on these premises, this paper analyses the logical consequences of taking a Design Science perspective on research methods. First, it analyses the various purposes of research methods to clarify the alternative and competing design goals of research methods. Second, it analyses and characterises the types of design artefacts that comprise research methods. Third, it considers issues of the evaluation of research methods. Fourth and finally, it considered the development of design theories of research methods.
A 25-ns 1-Mbit CMOS SRAM with loading-free bit lines

A 128 K/spl times/8-b CMOS SRAM is described which achieves a 25-ns access time, less than 40-mA active current at 10 MHz, and 2-/spl mu/A standby current. The novel bit-line circuitry (loading-free bit line), using two kinds of NMOSFETs with different threshold voltages, improves bit-line signal speed and integrity. The two-stage local amplification technique minimizes the data-line delay. The dynamic double-word-line scheme (DDWL) allows the cell array to be divided into 32 sections along the word-line direction without a huge increase in chip area. This allows the DDWL scheme to reduce the core-area delay time and operating power to about half that of other conventional structures. A double-metal 0.8-/spl mu/m twin-tub CMOS technology has been developed to realize the 5.6/spl times/9.5-/spl mu//SUP 2/ cell size and the 6.86/spl times/15.37-mm/SUP 2/ chip size.
THE USE OF COMPUTER INTELLIGENT PROCESSING TECHNOLOGIES AMONG ENVIRONMENTAL SCIENTISTS IN NIGERIAN UNIVERSITIES

This paper assesses the awareness and usage of a novel approach to data and information processing among scientists, researchers and students in the field of environmental sciences. In depth and structured interview was conducted, targeting a population who are working in a variety of environmental issues. The data generated were analysed using simple descriptive statistics. The results indicate that the level of awareness and responsiveness to this approach is very low (26.5%), and computer proficiency is also very low (30.8%). This suggests the need for a vigorous academic reorientation of all stakeholders through conferences, workshops and seminars. Key words: computer intelligent processing technologies, environmental scientists
An Improved Mesh Network for Massively Parallel Computers

Mesh is one of the well-known interconnection networks among the parallel architectures in massively parallel computers. Simple and efficient parallel algorithm has been devised for efficient execution on it. We propose a new class of parallel architectures that can reduce the cost of the network without affecting the complete connectivity of the existing network. Accordingly existing parallel algorithm can be extended to this proposed new architecture.
Classification Techniques in Machine Learning: Applications and Issues

Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic classification techniques. Later we discuss some major types of classification method including Bayesian networks, decision tree induction, k-nearest neighbor classifier and Support Vector Machines (SVM) with their strengths, weaknesses, potential applications and issues with their available solution. The goal of this study is to provide a comprehensive review of different classification techniques in machine learning. This work will be helpful for both academia and new comers in the field of machine learning to further strengthen the basis of classification methods.
Assessment of Technological Processes in the Metallurgy of Non-Ferrous Metals Based on Information Theory

The work suggests a formula for estimating complex indeterminancy of a group of technological operations undergoing analyses before and after their improvement, as well as technological schemes as a whole in the information units. The formula allows to estimate the complex indeterminancy of a group of technological operations undergoing analyses, as well as technological schemes as a whole, which will result in determining predictability and technological reliability of these operations.
UTILIZATION OF F-AHP METHOD IN BRI FOR GIVING SELECTION OF KUR

Bank Rakyat Indonesia (BRI) is a business entity which collects funds from the public in the form of deposits and distribute to the public in the form of the People 's Business Credit (KUR) or loan. Along with over time after KUR realized, there is no doubt BRI will be faced with the problems of risk, namely the risk of KUR problematic. There are several methods that can be used in making a decision to be able to solve the problem include the Analytical Hierarchy Process (AHP). AHP is used when the decision involves many factors, where the decision had difficulty in making the weight of each factor. Despite this problem the use of AHP in Multiple Criteria Decision Making (MCDM) approach has less to cope with uncertainties taken by decision-makers, when it should give a definite value in the pairwise comparison matrix therefore, to overcome the weaknesses of the existing AHP then developed a method namely Fuzzy Analytic Hierarchy Process (F-AHP). F-AHP method is the combination between fuzzy AHP approach. The results of research conducted using the Fuzzy Analytic Hierarchy Process (F-AHP) has a 100 % accuracy this is evidenced by the results obtained together with the calculation of banking. Calculation banking mention of 20 customers, acquired 14 accepted and rejected 6.
EXTENSIONS OF JADE AND JXTA FOR IMPLEMENTING A DISTRIBUTED SYSTEM

Distributed systems offer a useful approach for resolving critical networking limitations that result from the use of centralized topologies. Currently available distributed software platforms, however, have limitations that can limit their usefulness. This thesis examines the architectures of two distributed software platforms, JADE and JXTA, and compares their strengths and weaknesses. It is shown that JADE is a superior platform in terms of efficiency and latency, mainly due to the partially centralized approach of its Agent Management System. On the other hand, the decentralized management system and unrestricted scalability of JXTA has the advantage that it is not critically dependent on any node.
A recommendation algorithm of we-media articles

Since the explosive growth1 of we-medias today, personalized recommendation is playing an increasingly important role. How to help users to find their target articles in vast amounts of data, has become a very challenging job. Deep learning, on the other hand, have been shown good results in the image processing, computer vision, natural language processing and other fields. But it's a relatively blank in the application of we-media articles recommendation. Combining with the new features of we-media articles, this paper puts forward a recommendation algorithm of we-media articles based on topic model, Latent Dirichlet Allocation (LDA), and deep learning algorithm, Recurrent Neural Networks (RNNs).
Pengaruh Panjang Segmen Video pada Dynamic Adaptive Streaming over HTTP (DASH) terhadap Kualitas Pengiriman Video H.265

Saat ini sudah muncul video coding terbaru yaitu H.265 atau dikenal dengan nama High Efficiency Video Coding (HEVC). Dalam penerapan layanan video streaming menggunakan MPEG-DASH, representasi tingkat kualitas video yang terdapat pada Media Presentation Description (MPD) disusun oleh beberapa segmen video. Permasalahan yang muncul saat pengaturan panjang segmen video tersebut adalah pengaruh kualitas video yang diterima pada klien pada saat segmen video tersebut dikirimkan menggunakan MPEG-DASH. Penelitian ini menggunakan video H.265 untuk dikirimkan menggunakan MPEG-DASH yang dicampur dengan trafik background dari server FTP pada jaringan WLAN. Hasil penilitian ini menunjukkan video H.265 dapat digunakan untuk pengiriman secara adaptif menggunakan MPEG-DASH. Panjang segmen video yang semakin kecil akan menghasilkan nilai PSNR yang semakin besar. Segmen video yang semakin besar berdampak positif terhadap processor usage karenamenghasilkan nilai yang semakin kecil. Kata kunci: HEVC, MPEG-DASH, H.265, PSNR, segmen
Editorial: Internet rights, Internet wrongs

One of the most enduring and interesting aspects of the information revolution has been the way that the information and Internet environments have developed, in turn highlighting the role of these ‘new’ environments both in facilitating the development of harmful activity and also challenging the understanding of rights. The new and complex nature of the Internet environment has widely been highlighted; Giddens (1990) argued that the detachment of time and space in the context of the Internet had led to the creation of new types of criminal (and indeed other, non-criminal) endeavour (such as the theft of and alteration to pictures, music or software), as well as providing new and fruitful chances for existing criminal and harmful enterprise, such as forms of fraudulent activity, child abuse and theft, and providing a new medium for the communication of extreme sentiment, such as race-hate and homophobic speech or the support of terrorist and other activities (Wall, 2002). This special issue of Information & Communications Technology Law, consisting of five articles derived from the presentations of participants in the Information Law and Cyberspace Stream of the Socio-Legal Studies Association Annual Conference, highlights a number of important contemporary developments in the spheres of information technology law and the information society in relation to the evolution of rights in this context as well as some activities viewed potentially as harmful.