Development of mobile indoor positioning system application using android and bluetooth low energy with trilateration method

This proceedings volume contains papers presented at the fifth International Conference on Soft Computing, Intelligent System and Information Technology (the 5th ICSIIT) held in Bali, Indonesia, 26-29 September 2017. Main theme of this international conference is �Building Intelligence through IoT and Big Data�, and it was organized and hosted by Informatics Engineering Department, Petra Christian University, Surabaya, Indonesia. The Program Committee received 106 submissions for the conference from across Indonesia and around the world. After peer-review process by at least two reviewers per paper, 64 papers were accepted and included in the proceedings. The papers were divided into ten groups: Classification and Correlation Techniques, Feature Extraction and Image Recognition Methods, Algorithms for Intelligent Computation, Distributed Systems and Computer Networks, Mobile and Pervasive IoT Applications, Assessments of Integrated IS/IT, Simulation and Virtual Reality Applications, Smart Assistive Technologies, Smart Mobile Applications, Case Studies of Knowledge Discovery and Management

Development of Interactive Learning Media for Simulating Human Blood Circulatory System

This proceedings volume contains papers presented at the fifth International Conference on Soft Computing, Intelligent System and Information Technology (the 5th ICSIIT) held in Bali, Indonesia, 26-29 September 2017. Main theme of this international conference is “Building Intelligence through IoT and Big Data”, and it was organized and hosted by Informatics Engineering Department, Petra Christian University, Surabaya, Indonesia. The Program Committee received 106 submissions for the conference from across Indonesia and around the world. After peer-review process by at least two reviewers per paper, 64 papers were accepted and included in the proceedings. The papers were divided into ten groups: Classification and Correlation Techniques, Feature Extraction and Image Recognition Methods, Algorithms for Intelligent Computation, Distributed Systems and Computer Networks, Mobile and Pervasive IoT Applications, Assessments of Integrated IS/IT, Simulation and Virtual Reality Applications, Smart Assistive Technologies, Smart Mobile Applications, Case Studies of Knowledge Discovery and Management

Development of Interactive Learning Media for Simulating Human Digestive System

This proceedings volume contains papers presented at the fifth International Conference on Soft Computing, Intelligent System and Information Technology (the 5th ICSIIT) held in Bali, Indonesia, 26-29 September 2017. Main theme of this international conference is “Building Intelligence through IoT and Big Data”, and it was organized and hosted by Informatics Engineering Department, Petra Christian University, Surabaya, Indonesia. The Program Committee received 106 submissions for the conference from across Indonesia and around the world. After peer-review process by at least two reviewers per paper, 64 papers were accepted and included in the proceedings. The papers were divided into ten groups: Classification and Correlation Techniques, Feature Extraction and Image Recognition Methods, Algorithms for Intelligent Computation, Distributed Systems and Computer Networks, Mobile and Pervasive IoT Applications, Assessments of Integrated IS/IT, Simulation and Virtual Reality Applications, Smart Assistive Technologies, Smart Mobile Applications, Case Studies of Knowledge Discovery and Management

A multi-agent based medical image multi-display visualization system

The evolution of equipments used in the medical imaging practice, from 3-tesla Magnetic Resonance (MR) units and 64-slice Computer Tomography (CT) systems to the latest generation of hybrid Positron Emission Tomography (PET)/CT technologies is fast producing a volume of images that threatens to overload the capacity of the interpreting radiologists. On the other hand multi-agents systems are being used in a wide variety of research and application fields. Our work concerns the development of a multi-agent system that enables a multi-display medical image diagnostic system. The multi-agent system architecture permits the system to grow (scalable) i.e., the number of displays according to the user’s available resources. There are two immediate benefits of this scalable feature: the possibility to use inexpensive hardware to build a cluster system and the real benefit for physicians is that the visualization area increases allowing for easier and faster navigation. In this way an increase in the display area can help a physician analyse and interpret more information in less tim

Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis

A software method has been developed that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography (CT). This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2D sheets (or flattened onion skins ) in addition to a series of top view slices and 3D volume rendering. The advantages of viewing the data in this fashion are as follows: (1) the use of standard and specialized image processing and analysis methods is facilitated having 2D array data versus a volume rendering; (2) accurate lateral dimensional analysis of flaws is possible in the unwrapped sheets versus volume rendering; (3) flaws in the part jump out at the inspector with the proper contrast expansion settings in the unwrapped sheets; and (4) it is much easier for the inspector to locate flaws in the unwrapped sheets versus top view slices for very thin cylinders. The method is fully automated and requires no input from the user except proper voxel dimension from the CT experiment and wall thickness of the part. The software is available in 32-bit and 64-bit versions, and can be used with binary data (8- and 16-bit) and BMP type CT image sets. The software has memory (RAM) and hard-drive based modes. The advantage of the (64-bit) RAM-based mode is speed (and is very practical for users of 64-bit Windows operating systems and computers having 16 GB or more RAM). The advantage of the hard-drive based analysis is one can work with essentially unlimited-sized data sets. Separate windows are spawned for the unwrapped/re-sliced data view and any image processing interactive capability. Individual unwrapped images and un -wrapped image series can be saved in common image formats. More information is available at http://www.grc.nasa.gov/WWW/OptInstr/ NDE_CT_CylinderUnwrapper.html

A multigrid accelerated eigensolver for the Hermitian Wilson-Dirac operator in lattice QCD

Eigenvalues of the Hermitian Wilson-Dirac operator are of special interest in several lattice QCD simulations, e.g., for noise reduction when evaluating all-to-all propagators. In this paper we present a Davidson-type eigensolver that utilizes the structural properties of the Hermitian Wilson-Dirac operator $Q$ to compute eigenpairs of this operator corresponding to small eigenvalues. The main idea is to exploit a synergy between the (outer) eigensolver and its (inner) iterative scheme which solves shifted linear systems. This is achieved by adapting the multigrid DD-$\alpha$AMG algorithm to a solver for shifted systems involving the Hermitian Wilson-Dirac operator. We demonstrate that updating the coarse grid operator using eigenvector information obtained in the course of the generalized Davidson method is crucial to achieve good performance when calculating many eigenpairs, as our study of the local coherence shows. We compare our method with the commonly used software-packages PARPACK and PRIMME in numerical tests, where we are able to achieve significant improvements, with speed-ups of up to one order of magnitude and a near-linear scaling with respect to the number of eigenvalues. For illustration we compare the distribution of the small eigenvalues of $Q$ on a $64\times 32^3$ lattice with what is predicted by the Banks-Casher relation in the infinite volume limit

Some aspects of the injection moulding of alumina and other engineering ceramics

The literature concerning the injection moulding of engineering ceramics has been reviewed. This indicated that a number of claims had been made for the successful use of different organic binders during moulding and their removal prior to sintering. However, many of the claims were not supported by detailed/exact eScperimental evidence as to powder-binder compositions, moulding conditions, moulded properties, debinding times/cycles, or details of the structure and properties of the solid ceramic bodies produced. From the available information it was clear that there were few systematic and scientific investigations concerning the understanding of each stage of the injection moulding process. The present research programme has been carried out in two phases as follows. The first phase was concerned with the reinvestigation and re-evaluation of binder systems claimed to be successful for the injection moulding of alumina ceramics. The binders re-investigated included the thermoplastic-based binders such as polystyrene, polyacetal and atactic polypropylene and the water-based methylcellulose (Rivers) binder system. Alumina was chosen as the main powder to be investigated due to its simple handling and, highest applications amongst ceramic materials and on the basis that there is incomplete published work for almost every step of the injection moulding process. During the first stage of this work the optimum properties such as powder-binder compositions, mixing and moulding conditions, debinding properties, green and sintered densities provided by each binder system were determined. The results of these investigations showed that all the previous (re-evaluated) binder systems had major limitations and disadvantages. These included low volume loading (64 % maximum) of the alumina powder resulting in rather low sintered densities (96 % maximum-of theoretical density) and very long debinding times in the case of the thermoplastic-based binders. it ry low alumina volume loading (55 % maximum resulting in a 94 % . sintered theoretical density) and long moulding cycle time (- 5 min) along with adhesion and distortion problems during demoulding occurred in the case of the water-based methylcellulose binder system. Further work did not appear worthwhile. The newly developed binder systems have been used with a number of other powders such as zirconia, silicon nitride, silicon carbide, tungsten carbide-6 weight % cobalt and iron-2 weight % nickel, to establish- whether injection moulding is feasible. Optimum properties such as powder volume loadings, mixing, moulding, demoulding, moulded densities, debinding and some sintered density results showed that these new binder systems can also be used successfully for the injection moulding of other ceramic and metallic powders, although a fuller evaluation of the properties such as optimum sintered densities and mechanical properties is required

Virtualizing super-computation on-board UAS

Unmanned aerial systems (UAS, also known as UAV, RPAS or drones) have a great potential to support a wide variety of aerial remote sensing applications. Most UAS work by acquiring data using on-board sensors for later post-processing. Some require the data gathered to be downlinked to the ground in real-time. However, depending on the volume of data and the cost of the communications, this later option is not sustainable in the long term. This paper develops the concept of virtualizing super-computation on-board UAS, as a method to ease the operation by facilitating the downlink of high-level information products instead of raw data. Exploiting recent developments in miniaturized multi-core devices is the way to speed-up on-board computation. This hardware shall satisfy size, power and weight constraints. Several technologies are appearing with promising results for high performance computing on unmanned platforms, such as the 36 cores of the TILE-Gx36 by Tilera (now EZchip) or the 64 cores of the Epiphany-IV by Adapteva. The strategy for virtualizing super-computation on-board includes the benchmarking for hardware selection, the software architecture and the communications aware design. A parallelization strategy is given for the 36-core TILE-Gx36 for a UAS in a fire mission or in similar target-detection applications. The results are obtained for payload image processing algorithms and determine in real-time the data snapshot to gather and transfer to ground according to the needs of the mission, the processing time, and consumed watts.Unmanned aerial systems (UAS, also known as UAV, RPAS or drones) have a great potential to support a wide variety of aerial remote sensing applications. Most UAS work by acquiring data using on-board sensors for later post-processing. Some require the data gathered to be downlinked to the ground in real-time. However, depending on the volume of data and the cost of the communications, this later option is not sustainable in the long term. This paper develops the concept of virtualizing super-computation on-board UAS, as a method to ease the operation by facilitating the downlink of high-level information products instead of raw data. Exploiting recent developments in miniaturized multi-core devices is the way to speed-up on-board computation. This hardware shall satisfy size, power and weight constraints. Several technologies are appearing with promising results for high performance computing on unmanned platforms, such as the 36 cores of the TILE-Gx36 by Tilera (now EZchip) or the 64 cores of the Epiphany-IV by Adapteva. The strategy for virtualizing super-computation on-board includes the benchmarking for hardware selection, the software architecture and the communications aware design. A parallelization strategy is given for the 36-core TILE-Gx36 for a UAS in a fire mission or in similar target-detection applications. The results are obtained for payload image processing algorithms and determine in real-time the data snapshot to gather and transfer to ground according to the needs of the mission, the processing time, and consumed watts.Postprint (published version

Bubbly, Slug, and Annular Two-Phase Flow in Tight-Lattice Subchannels

AbstractAn overview is given on the work of the Laboratory of Nuclear Energy Systems at ETH, Zurich (ETHZ) and of the Laboratory of Thermal Hydraulics at Paul Scherrer Institute (PSI), Switzerland on tight-lattice bundles. Two-phase flow in subchannels of a tight triangular lattice was studied experimentally and by computational fluid dynamics simulations. Two adiabatic facilities were used: (1) a vertical channel modeling a pair of neighboring subchannels; and (2) an arrangement of four subchannels with one subchannel in the center. The first geometry was equipped with two electrical film sensors placed on opposing rod surfaces forming the subchannel gap. They recorded 2D liquid film thickness distributions on a domain of 16×64 measuring points each, with a time resolution of 10 kHz. In the bubbly and slug flow regime, information on the bubble size, shape, and velocity and the residual liquid film thickness underneath the bubbles were obtained. The second channel was investigated using cold neutron tomography, which allowed the measurement of average liquid film profiles showing the effect of spacer grids with vanes. The results were reproduced by large eddy simulation+volume of fluid. In the outlook, a novel nonadiabatic subchannel experiment is introduced that can be driven to steady-state dryout. A refrigerant is heated by a heavy water circuit, which allows the application of cold neutron tomography