"Field Manager" Application Package

One of the important problems in the development of Decision Support Systems regards the issue of designing and implementation of man-machine interface. Importance of this component of the DSS follows from the fact that the end-user is usually not a computer specialist and, therefore, even the most useful decision-theoretic framework will be rejected if communication with the computer is too difficult for him. From the other side, design and implementation of user interface requires a lot of experience from the system designer, big resources for programming and a long time for for debugging and coding. Therefore, every attempt to simplify this aspect of DSS design and development is important. In this paper the software package Field Manager is presented. This package allows easy and quick development of user interfaces. The design is based on two novel ideas in the field of software management -- the abstract data type approach and object-oriented software specification. The package has been applied in several practical applications and the collected experience has shown its effectiveness and simplicity

A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method

<p>Abstract</p> <p>Background</p> <p>The Molecular Interaction Map (MIM) notation offers a standard set of symbols and rules on their usage for the depiction of cellular signaling network diagrams. Such diagrams are essential for disseminating biological information in a concise manner. A lack of software tools for the notation restricts wider usage of the notation. Development of software is facilitated by a more detailed specification regarding software requirements than has previously existed for the MIM notation.</p> <p>Results</p> <p>A formal implementation of the MIM notation was developed based on a core set of previously defined glyphs. This implementation provides a detailed specification of the properties of the elements of the MIM notation. Building upon this specification, a machine-readable format is provided as a standardized mechanism for the storage and exchange of MIM diagrams. This new format is accompanied by a Java-based application programming interface to help software developers to integrate MIM support into software projects. A validation mechanism is also provided to determine whether MIM datasets are in accordance with syntax rules provided by the new specification.</p> <p>Conclusions</p> <p>The work presented here provides key foundational components to promote software development for the MIM notation. These components will speed up the development of interoperable tools supporting the MIM notation and will aid in the translation of data stored in MIM diagrams to other standardized formats. Several projects utilizing this implementation of the notation are outlined herein. The MIM specification is available as an additional file to this publication. Source code, libraries, documentation, and examples are available at <url>http://discover.nci.nih.gov/mim</url>.</p

A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems

abstract: Text Classification is a rapidly evolving area of Data Mining while Requirements Engineering is a less-explored area of Software Engineering which deals the process of defining, documenting and maintaining a software system's requirements. When researchers decided to blend these two streams in, there was research on automating the process of classification of software requirements statements into categories easily comprehensible for developers for faster development and delivery, which till now was mostly done manually by software engineers - indeed a tedious job. However, most of the research was focused on classification of Non-functional requirements pertaining to intangible features such as security, reliability, quality and so on. It is indeed a challenging task to automatically classify functional requirements, those pertaining to how the system will function, especially those belonging to different and large enterprise systems. This requires exploitation of text mining capabilities. This thesis aims to investigate results of text classification applied on functional software requirements by creating a framework in R and making use of algorithms and techniques like k-nearest neighbors, support vector machine, and many others like boosting, bagging, maximum entropy, neural networks and random forests in an ensemble approach. The study was conducted by collecting and visualizing relevant enterprise data manually classified previously and subsequently used for training the model. Key components for training included frequency of terms in the documents and the level of cleanliness of data. The model was applied on test data and validated for analysis, by studying and comparing parameters like precision, recall and accuracy.Dissertation/ThesisMasters Thesis Engineering 201

Simulasi Dan Analisis Pengklasifikasian Tipe Modulasi Digital Menggunakan Support Vector Machine (SVM) pada Software Defined Radio (SDR)

ABSTRAKSI: Software Defined Radio (SDR) akan menghadirkan teknologi komunikasi radio generasi berikutnya yang sangat berperan penting dalam kesuksesan teknologi BWA (Broadband Wireless Access). Dengan lebih menerapkan fungsi-fungsi yang ada di dalam software dibandingkan dengan pendekatan hardware secara tradisional, sistem radio akan menawarkan solusi potensial untuk interoperabilitas, jaringan yang fleksibel dan dinamis serta pengurangan biaya operasi. SDR (Software Defined Radio) juga diharapkan dapat mendukung terhadap perbedaan frekuensi, perbedaan tipe modulasi dan perbedaan bandwidth. Deteksi skema modulasi adalah salah satu fungsi awal yang harus ada pada Software Defined Radio (SDR), karena nantinya penerima yang digunakan pada sistem ini harus mampu memilih skema demodulasi yang tepat untuk bermacam-macam sinyal dengan skema modulasi yang tidak diketahui. Algoritma pendeteksian skema modulasi digital yang digunakan pada penelitian ini merupakan gabungan antara metode Transformasi Wavelet dan metode Support Vector Machine (SVM) yang kemampuannya dalam berbagai aplikasi menempatkannya sebagai state of the art dalam pattern recognition dan domain ini merupakan salah satu metoda pengenalan pola yang berkembang pesat. Sinyal termodulasi digital yang akan dideteksi adalah QPSK, 16QAM dan 64QAM. Hasil penelitian menunjukkan nilai ƒc = 3.8 Hz dan ƒb = 2.4 Hz pada metode Transformasi Complex Shannon Wavelet menunjukkan hasil complex envelope terbaik dan kinerja theoritic decision menggunakan Supoort Vector Machine (SVM). Dan hasil yang ditampilkan berupa klasifikasi tipe modulasi digital yang terbagi dalam kelasnya masing-masing. Sistem yang dirancang ini dapat mencapai tingkat keakurasian 89,227 % dalam melakukan pengidentifikasian tipe modulasi digital dengan menggunakan One Against All metode yang terdapat pada Support Vector Machine (SVM).Kata Kunci : Deteksi Skema Modulasi, Software Defined Radio, Transformasi Wavelet, Support Vector Machine (SVM).ABSTRACT: Software Defined Radio (SDR) brings the next communication radio technology and plays some important roles in BWA (Broadband Wireless Access) system development. By applying software function better than traditional hardware which is formerly used, radio technology offers potential solution for interoperability, reducing operational cost, flexibility and dynamically network. SDR also support system with different frequencies, modulation types and bandwidths. Modulation schemes detection are preliminary function on Software Defined Radio (SDR). Next, receiver on Software Defined Radio (SDR) system is able to choose the best demodulation schemes for various signals with unknown modulation schemes. The algorithm of digital modulations scheme’s detection used in this project is combined between Complex Shannon Wavelet Transformation and Statistical Method of feature extraction. Uses Support Vector Machine (SVM), that in many application become as state of the art in pattern recognition. QPSK, 16QAM and 64QAM are modulated digital signal which going to be detected. The research show that ƒc = 3.8 Hz and ƒb = 2.4 Hz as Complex Shannon Wavelet Transformation Method’s inputs produce the best complex envelope and theoretic decision’s performance using Support Vector Machine (SVM). The result is classification type of digital modulation that divided each class. This system has precision 89,227 % using One Against All in SVM.Keyword: Modulation Scheme detection, Software Defined Radio, Complex Shannon Wavelet Transformation, Statistical Method, Theoritic Decision (Tree Diagram), Optimum Threshold

Representation and validation of domain and range restrictions in a relational database driven ontology maintenance system

An ontology can be used to represent and organize the objects, properties, events, processes, and relations that embody an area of reality [1]. These knowledge bases may be created manually (by individuals or groups), and/or automatically using software tools, such as those developed for information retrieval and data mining. Recently, the National Science Foundation funded a large collaborative development project for the semi-automated construction of an ontology of amphibian anatomy (AmphibAnat [2]). To satisfy the extensive community curation requirements of that project, a generic, Web-based, multi-user, relational database ontology management system (RDBOM [3]) was constructed, based upon a novel theoretical ontology model called an Ontology Abstract Machine (OAM [4]). The need to support concurrent data entry by multiple users with different levels of access privileges (as determined and assigned by the administrators), made it critical to ensure that the entered data were semantically correct. In particular, the ability to define and enforce restrictions on property characteristics such as the domain and range of a relation provide several advantages. It helps to identify inconsistencies in the ontology, maintain a higher level of overall integrity, and avoid erroneous conclusions that could be made by automated reasoners. In this thesis a modified OAM model is presented that includes definitions for property characteristics and the associated validation algorithms. As proof of concept, it is shown how this modified abstract model has been implemented for domain and range restrictions in RDBOM --Abstract, page iii

Towards Python-based Domain-specific Languages for Self-reconfigurable Modular Robotics Research

This paper explores the role of operating system and high-level languages in the development of software and domain-specific languages (DSLs) for self-reconfigurable robotics. We review some of the current trends in self-reconfigurable robotics and describe the development of a software system for ATRON II which utilizes Linux and Python to significantly improve software abstraction and portability while providing some basic features which could prove useful when using Python, either stand-alone or via a DSL, on a self-reconfigurable robot system. These features include transparent socket communication, module identification, easy software transfer and reliable module-to-module communication. The end result is a software platform for modular robots that where appropriate builds on existing work in operating systems, virtual machines, middleware and high-level languages.Comment: Presented at DSLRob 2011 (arXiv:1212.3308