Lei Feng, Key Laboratory of Computational Optical Imaging Technology, Academy of Opto-electronics, Chinese Academy of Sciences, Beijing, China
Wide spectral band, combination of imaging and spectrum and fine spectral detection capability are the outstanding advantages of imaging spectrometer. Rich spectral information combined with spatial image of the object point greatly improves the accuracy of target detection, expands the function of traditional detection technology, and realizes the qualitative analysis of target characteristics. Spectrometer plays an irreplaceable role compared with other technologies. It has been widely used in many military and civilian fields, such as land and ocean remote sensing, remote sensing monitoring of pollutants in atmosphere, soil and water, military target detection, medical spectral imaging diagnosis, scientific experiments and so on. Curved prism spectrometer is widely used because of its high energy and no ghost image. However, curved prism spectrometer is as a non coaxial symmetric system and its aberration theory is complex. Therefore, it is necessary to establish a numerical model and construct an initial structure to provide a good starting point for system optimization. In a practical imaging spectrometer based on prism, there are many aberrations when ray incidented on the surface of each element. In the design, it is very important to establish a mathematical model to analyze these aberrations. Curved prism is a kind of non-coaxial prism which is obtained by processing the front and rear surfaces of triangular prism into two spheres. Its front and rear surfaces are not coaxial with the optical axis, so its characteristics are complex. Firstly, on the basis of the primary aberration theory, the numerical calculation model of curved prism is established, and the optimal object distance of curved prism and the effective incident angle of curved prism are solved according to the principle of minimum aberration. For given system parameters, the coordinates of object points are known, and then the numerical model of curved surface prism spectrometer is established. The vector method is used to solve the incident and output vectors of given light rays. After transmission, the optical path extremum function is established, and the second-order partial differential equation is derived. The surface equation of each element is expanded by higher order Taylor series, that is, each surface is expressed as a functional expression of the incident point and structural parameters. A set of partial differential equations is constructed, and the least square method is used to solve the minimum of the equations, and then the initial structural parameters are calculated.
Mathematical computation, partial differential equations, vector solving, curved prism
Hamidreza Bolhasani, Amir Masoud Rahmani and Farid Kheiri, Department of Computer Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran
Since 1982 that Richard Feynman proposed the idea of quantum computing for the first time, it has become a new field of interest for many physics and computer scientists. Although it’s more than 30 years that this concept has been presented but it’s still considered as unknown and several subjects are open for research. Accordingly, concepts and theoretical reviews may always be useful. In this paper, a brief history and fundamental ideas of quantum computers are introduced with focus on architecture part.
Quantum, Computer, Hardware, Qubit, Gate
Vahab Pournaghshband1 and Peter Reiher2 , 1Computer Science Department, University of San Francisco, San Francisco, USA, 2Computer Science Department, University of California, Los Angeles, Los Angeles,USA
The market is currently sated with mobile medical devices and new technology is continuously emerging. Thus, it is costly, and in some cases impractical, to replace these devices for new ones with greater security. In this paper, we present the implementation of a prototype for Personal Security Device a self-contained, specialized wearable device that augments security to existing mobile medical devices. The main research challenge for, and hence the state of the art of, the proposed hardware design is that the device, to work with legacy devices, must require no changes to either the medical device or its monitoring software. This requirement is essential since we aim to protect already existing devices, as making modifications to the device or its proprietary software often impossible or impractical (e.g., closed source executables and implantable medical devices). Through performance evaluation of this prototype, we confirmed the feasibility of having a special-purpose hardware with limited computational and memory resources to perform necessary security operations.
Wireless medical device security, Man-in-the-middle attack.
Hirantha Athapaththu1, Shavinda Herath1, Geeth Sameera1, Supun Gamlath1, Pramadhi Atapattu2 and Malitha Wijesundara3, 1Department of Software Engineering, Sri Lanka Institute of Information Technology, Sri Lanka,2Pulzsolutions (Pvt) Ltd., Sri Lanka Technology Incubator and 3Department of Information Systems Engineering, Sri Lanka Institute of Information Technology, Sri Lanka
This paper proposes a WebRTC based live teaching platform which facilitates the e-learning requirements of universities and other institutes. This solution includes lecture live streaming, lecture playback, a vector based interactive whiteboard, chatting and file sharing module and a real-time lecture movement tracking module using a PTZ camera. The system is capable of streaming two simultaneous streams of a 1080p camera and a 720p screen capture seamlessly using a network connection with 256KB/s bandwidth. Live streaming component is very less CPU intensive and it use around 14% of the CPU for streaming 10 simultaneous sessions with 10 listeners per each on a AWS t2.micro instance with 1 vCPU 2.5 GHz, Intel Xeon Family, 1 GiB memory. The original recorded videos get down-scaled and re-encoded to make the file size smaller up to 1% of the original file size. With adaptive streaming enabled player, users with an internet connection of 128KB/s bandwidth can experience an uninterrupted playback of the recorded lectures.
WebRTC, MPEG-DASH, PTZ Camera, e-Learning, Simulcast
Shailja Dalmia, Ashwin T S and Ram Mohana Reddy Guddeti, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India
With the ever-growing variety of information, the retrieval demands of different users are so multifarious that the traditional search engine cannot afford such heterogeneous retrieval results of huge magnitudes. Harnessing the advancements in a user-centered adaptive search engine will aid in groundbreaking retrieval results achieved efficiently for high-quality content. Previous work in this field have made using the excessive server load to achieve good retrieval results but with the limited extended ability and ignoring on demand generated content. To address this gap, we propose a novel model of adaptive search engine and describe how this model is realized in a distributed cluster environment. Using an improved current algorithm of topic-oriented web crawler with User Interface based Information Extraction Technique was able to produce a renewed set of user-centered retrieval results with higher efficiency than all existing methods. The proposed method was found to exceed by 1.5 times and two times for crawler and indexer, respectively than all prevailing methods with improved and highly precise results in extracting semantic information from Deep web.
Search Engine, WWW, Web Content Mining, Inverted Indexing, Hidden Crawler, Distributed Web Crawler, Precision, Deep Web
Ikwu Ruth and Louvieris Panos, Department of Computer Sciences, Brunel University, London
Cyberspace has gradually replaced the physical reality, its role evolving from a simple enabler of daily live processes to a necessity for modern existence. As a result of this convergence of physical and virtual realities, for all processes being critically dependent on networked communications, information representative of our physical, logical and social thoughts are constantly being generated in cyberspace. The interconnection and integration of links between our physical and virtual realities create a new hyperspace as a source of data and information. Additionally, significant studies in cyber analysis have predominantly revolved around a single linear analysis of information from a single source of evidence (The Network). These studies are limited in their ability to understand the dynamics of relationships across the multiple dimensions of cyberspace. This paper introduces a multi-dimensional perspective for data identification in cyberspace. It provides critical discussions for identifying entangled relationships amongst entities across cyberspace.
Cyberspace, Data-streams, Multi-Dimensional Cyberspace
Solomon Cheung1, Yu Sun1 and Fangyan Zhang2, 1Department of Computer Science, California State Polytechnic University, Pomona, CA, 91768 and 2ASML, San Jose, CA, 95131
As an act of disposing waste and maintaining homeostasis, humans have to use the restroom multiple times a day. One item that is consumed in the process is toilet paper; it often runs out easily in the most inconvenient times. One of the most fatal positions to be in is to be stuck without toilet paper. Since humans are not capable of a 100% resupply rate, we should give this task to a computer. The approach we selected was to use a pair of laser sensors to detect whether toilet paper was absent or not. Utilizing an ultrasound sensor, we would be able to detect whether a person was nearby and send a notification to a database. The online app, PaperSafe, takes the information stored and displays it onto a device for quick access. Once a sufficient amount of data is acquired, we can train a machine learning algorithm to predict the next supply date, optimized for the specific scenario.
Amenity, Homeostasis, Machine Learning, Mobile Application
Vijayalakshmi M,Shanthi ThangamM and Bushra H, Department of Information Science and Technology, Anna University, Chennai City, Tamil Nadu, India
The usages of mobile devices are drastically increasing every day with high end support to the users. Due to high end configurations mobile devices such as smart phones, laptops, tablets, etc., computations are complex in these devices. Computation intensive and data intensive are plays a vital role in the mobile devices. The main challenges in the mobile devices are handling the mobile applications in the devices with high computation and high storage. The above mentioned challenges can be overcome by using mobile cloud computing. The limitations while handling the mobile cloud computing is offloading decision making, which part of computation should offload and which should execute in the mobile side. The proposed work provides the solution to the limitations and challenges mentioned earlier by providing agent based offloading decision maker for mobile cloud. The decision maker should decide which computation part is executed in the mobile side and the cloud side. The evaluation shows the mobile applications having high complexity get benefited over other high applications.
Agent based, Mobile cloud, Offloading, Computational device.
Ho Joong Kim1 and Shahid Ali2, 1Department of Information Technology, AGI Institute, Auckland, New Zealand, 2Department of Information Technology, AGI Institute, Auckland, New Zealand
Regression testing is a necessary process to ensure that the existing functionalities of a piece of software are not affected by new features or fixing defects. However, in the case for the web application of PB Tech, this process is very repetitive and time-consuming. In order to solve this issue, automation testing is implemented and a new test case prioritisation technique is proposed based on a combination of human-evaluation and statistical data of the highest earning features of retailer websites. Using this technique, a regression test suite is created and the test execution times are compared against a full regression test suite. The results revealed that the prioritisation technique is effective at reducing test execution times. This technique could prove to be effective for use in projects missing defect and requirements documentation.
Automation Testing, Regression Testing, Test Case Prioritization.
Roberto Bruzzese, Freelancer
The present work aims to enhance the application logs of a hypothetical infrastructure platform, and to build an App that displays the synthetic data about performance, anomalies and security incidents synthesized in the form of a Dashboard. The reference architecture, with multiple applications and multiple HW distribution, implementing a Service Oriented Architecture, is a real case of which the details have been abstracted because we want to extend the concept to all architectures with similar characteristics. This paper is taken from my Master Thesis in Cybersecurity for which I express a special thank to Prof. M. Bernaschi.
Dr.Djamal Ziani and Nada Alfaadhel, King Saud University, College of Computer since, Department of Information Systems, Riyadh, Saudi Arabia
Recently, organizations have shown more interest in cloud computing because of the many advantages they provide (cost savings, storage capacity, scalability, and speed of loading). Enterprise resource planning (ERP) systems are one of the most important systems that have been upgraded to cloud computing. In this thesis, we focus on cloud ERP interoperability, which is an important challenge in cloud ERP. Interoperability is the ability of different components to work in independent clouds with no or minimum user effort. More than 20% of the risk rate of cloud adoption is caused by interoperability. Thus, we propose web services as a solution for cloud ERP interoperability. The proposed solution increases interoperability between different cloud service providers and between cloud ERP systems with other applications in a company.
Cloud computing, ERP,interoperability, web services.
Ruchita Dahiya and Shahid Ali, Department of Information Technology, AGI Institute, Auckland, New Zealand
Automation testing has become increasingly needed due to the nature of the current software development project which comprises of complex application with shorter development time. Most of the companies in the industry have used Selenium extensively as functional automation tool to verify their web application’s functionalities are working as expected. However, for any new project Manual testing is equally important instead of automating. Thus, this research project is about the importance of manual and exploratory testing in industry when our project is under develop stage.
Automation Testing, Regression Test Suite, Selenium, Java Automation Framework, Test Ng, Manual Testing, Exploratory Testing
Ayodeji Oyewale1 and Chris Hughes2, 1School of Computing, Science and Engineering, University of Salford, Salford, Manchester and 2The Crescent, Salford, Manchester, United Kingdom
A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Data & Knowledge Engineering (DKE) has been known to stimulate the exchange of ideas and interaction between these two related fields of interest. DKE makes it possible to understand, apply and assess knowledge and skills required for the development and application data mining systems. With present technology, companies are able to collect vast amounts of data with relative ease. With no hesitation, many companies now have more data than they can handle. A vital portion of this data entails large unstructured data sets which amount up to 90 percent of an organization’s data. With data quantities growing steadily, the explosion of data is putting a strain on infrastructures as diverse companies having to increase their data center capacity with more servers and storages. This study conceptualized handling enormous data as a stream mining problem that applies to continuous data stream and proposes an ensemble of unsupervised learning methods for efficiently detecting anomalies in stream data.
Stream data, Steam Mining, Compact data structurres, FP Tree, Path Adjustment Method
N. Rada, L. E. Mendoza, E. G. Florez ,TelecommunicationsEngineering, Biomedical engineering, Mechanical Engineering, Research Group in Mechanical Engineering, Universityof Pamplona, Colombia
This article presents a robust compression method known as compression sensitivity (CS). CS, allows to reconstruct scat-tered signals with very few samples unlike the Shannon-Nyquist theorem. In this article the discrete cosine transform and the wavelet transform were used to find most adequate sparse space. Angiographic images were used, which were reconstructed using algorithms such as Large-scale Sparse Reconstruction (SPGL) and Gradient Projection for Sparse Reconstruction (GPRS). In this work, it was demonstrated that using the wavelet-cosine transformed transpose allowed achieving a more satisfactory sparse space than those obtained by other research. Finally, it was demonstrated that CS works in a relevant way for compressing angiographic images and the maximum percentage of error in the reconstruction was 3.56% for SPGL.
Compressive Sensing, sparse signal, images, reconstruction, SPGL1, SPSR.
Hyun Woo Jung, Hankuk Academy of Foreign Studies, Yongin, South Korea
Deep learning has facilitated major advancements in various fields including image detection. This paper is an exploratory study on improving the performance of Convolutional Neural Network (CNN) models in environments with limited computing resources, such as the Raspberry Pi. A pretrained state-of-art algorithm for doing near-real time object detection in videos, YOLO (“You-Only-Look-Once”) CNN model, was selected for evaluating strategies for optimizng the runtime performance. Various performance analysis tools provided by the Linux kernel were used to measure CPU time and memory footprint. Our results show that loop parall
