A wideband linear tunable CDTA and its application in field programmable analogue array

This document is the Accepted Manuscript version of the following article: Hu, Z., Wang, C., Sun, J. et al. ‘A wideband linear tunable CDTA and its application in field programmable analogue array’, Analog Integrated Circuits and Signal Processing, Vol. 88 (3): 465-483, September 2016. Under embargo. Embargo end date: 6 June 2017. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs10470-016-0772-7 © Springer Science+Business Media New York 2016In this paper, a NMOS-based wideband low power and linear tunable transconductance current differencing transconductance amplifier (CDTA) is presented. Based on the NMOS CDTA, a novel simple and easily reconfigurable configurable analogue block (CAB) is designed. Moreover, using the novel CAB, a simple and versatile butterfly-shaped FPAA structure is introduced. The FPAA consists of six identical CABs, and it could realize six order current-mode low pass filter, second order current-mode universal filter, current-mode quadrature oscillator, current-mode multi-phase oscillator and current-mode multiplier for analog signal processing. The Cadence IC Design Tools 5.1.41 post-layout simulation and measurement results are included to confirm the theory.Peer reviewedFinal Accepted Versio

KUALITAS PELAYANAN PERPUSTAKAAN BERDASARKAN PENGELOLAAN KOLEKSI, TATA RUANG, KOMPETENSI PENGELOLA, DAN FASILITAS

Library is one of many place to get knowledge. A management library success can be seen from service quality that give to library customer. Research includes quantitative research. Population this research is all customer Wonosobo Library. Incidental sampling is the sampling technique used, by using iteration formula obtained by respondent with amount 116 costumer library. Data method using, questionnaire, interview, and documentation. Methods of data analysis are multiple linear regression  and descriptive percentage. Results showed the multiple linear regression equation is: Y ꞊ -3,489 + 0,242PK + 0,514TR + 0,519KP + 0,475FP + e. The results showed that collection processing , library layout, library management competence, and library facilities had a direct positive effect on the quality of Wonosobo library with total effect is 79,2%. Library layout give the biggest influence with 22,27%, collection processing with 13,76% total effect, management competence give influence 13,39%, and library facilities give less effect with 11,15% total effec

Target Localization Accuracy Gain in MIMO Radar Based Systems

This paper presents an analysis of target localization accuracy, attainable by the use of MIMO (Multiple-Input Multiple-Output) radar systems, configured with multiple transmit and receive sensors, widely distributed over a given area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and non-coherent processing. Coherent processing requires a common phase reference for all transmit and receive sensors. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the non-coherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. We further prove that optimization over the sensors' positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE's utility is in providing a closed form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area.Comment: 36 pages, 5 figures, submitted to IEEE Transaction on Information Theor

Evaluating the layout quality of UML class diagrams using machine learning

UML is the de facto standard notation for graphically representing software. UML diagrams are used in the analysis, construction, and maintenance of software systems. Mostly, UML diagrams capture an abstract view of a (piece of a) software system. A key purpose of UML diagrams is to share knowledge about the system among developers. The quality of the layout of UML diagrams plays a crucial role in their comprehension. In this paper, we present an automated method for evaluating the layout quality of UML class diagrams. We use machine learning based on features extracted from the class diagram images using image processing. Such an automated evaluator has several uses: (1) From an industrial perspective, this tool could be used for automated quality assurance for class diagrams (e.g., as part of a quality monitor integrated into a DevOps toolchain). For example, automated feedback can be generated once a UML diagram is checked in the project repository. (2) In an educational setting, the evaluator can grade the layout aspect of student assignments in courses on software modeling, analysis, and design. (3) In the field of algorithm design for graph layouts, our evaluator can assess the layouts generated by such algorithms. In this way, this evaluator opens up the road for using machine learning to learn good layouting algorithms. Approach.: We use machine learning techniques to build (linear) regression models based on features extracted from the class diagram images using image processing. As ground truth, we use a dataset of 600+ UML Class Diagrams for which experts manually label the quality of the layout. Contributions.: This paper makes the following contributions: (1) We show the feasibility of the automatic evaluation of the layout quality of UML class diagrams. (2) We analyze which features of UML class diagrams are most strongly related to the quality of their layout. (3) We evaluate the performance of our layout evaluator. (4) We offer a dataset of labeled UML class diagrams. In this dataset, we supply for every diagram the following information: (a) a manually established ground truth of the quality of the layout, (b) an automatically established value for the layout-quality of the diagram (produced by our classifier), and (c) the values of key features of the layout of the diagram (obtained by image processing). This dataset can be used for replication of our study and others to build on and improve on this work. Editor\u27s note: Open Science material was validated by the Journal of Systems and Software Open Science Board

Speeding up SOR Solvers for Constraint-based GUIs with a Warm-Start Strategy

Many computer programs have graphical user interfaces (GUIs), which need good layout to make efficient use of the available screen real estate. Most GUIs do not have a fixed layout, but are resizable and able to adapt themselves. Constraints are a powerful tool for specifying adaptable GUI layouts: they are used to specify a layout in a general form, and a constraint solver is used to find a satisfying concrete layout, e.g.\ for a specific GUI size. The constraint solver has to calculate a new layout every time a GUI is resized or changed, so it needs to be efficient to ensure a good user experience. One approach for constraint solvers is based on the Gauss-Seidel algorithm and successive over-relaxation (SOR). Our observation is that a solution after resizing or changing is similar in structure to a previous solution. Thus, our hypothesis is that we can increase the computational performance of an SOR-based constraint solver if we reuse the solution of a previous layout to warm-start the solving of a new layout. In this paper we report on experiments to test this hypothesis experimentally for three common use cases: big-step resizing, small-step resizing and constraint change. In our experiments, we measured the solving time for randomly generated GUI layout specifications of various sizes. For all three cases we found that the performance is improved if an existing solution is used as a starting solution for a new layout