Search results for: Shared Memory Parallel Computing

Authors: Jackson H. W. Chang, Jedol Dayou, Justin Sentian

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Long terms variation of solar insolation had been widely studied. However, its parallel observations in short time scale is rather lacking. This paper aims to investigate the short time scale evolution of solar radiation spectrum (UV, PAR, and NIR bands) due to atmospheric aerosols and water vapors. A total of 25 days of global and diffused solar spectrum ranges from air mass 2 to 6 were collected using ground-based spectrometer with shadowband technique. The result shows that variation of solar radiation is the least in UV fraction, followed by PAR and the most in NIR. Broader variations in PAR and NIR are associated with the short time scale fluctuations of aerosol and water vapors. The corresponding daily evolution of UV, PAR, and NIR fractions implies that aerosol and water vapors variation could also be responsible for the deviation pattern in the Langley-plot analysis.

Keywords: Aerosol, short time scale variation, solar radiation, water vapor.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Features selection, learning with kernels, support vector machine, genetic algorithms and classification.

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Authors: M. N. Nwodo, Y. P. Cheng, N. H. Minh

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In the process of recovering oil in weak sandstone formations, the strength of sandstones around the wellbore is weakened due to the increase of effective stress/load from the completion activities around the cavity. The weakened and de-bonded sandstone may be eroded away by the produced fluid, which is termed sand production. It is one of the major trending subjects in the petroleum industry because of its significant negative impacts, as well as some observed positive impacts. For efficient sand management therefore, there has been need for a reliable study tool to understand the mechanism of sanding. One method of studying sand production is the use of the widely recognized Discrete Element Method (DEM), Particle Flow Code (PFC^3D) which represents sands as granular individual elements bonded together at contact points. However, there is limited knowledge of the particle-scale behavior of the weak sandstone, and the parameters that affect sanding. This paper aims to investigate the reliability of using PFC^3D and a simple Darcy flow in understanding the sand production behavior of a weak sandstone. An isotropic tri-axial test on a weak oil sandstone sample was first simulated at a confining stress of 1MPa to calibrate and validate the parallel bond models of PFC^3D using a 10m height and 10m diameter solid cylindrical model. The effect of the confining stress on the number of bonds failure was studied using this cylindrical model. With the calibrated data and sample material properties obtained from the tri-axial test, simulations without and with fluid flow were carried out to check on the effect of Darcy flow on bonds failure using the same model geometry. The fluid flow network comprised of every four particles connected with tetrahedral flow pipes with a central pore or flow domain. Parametric studies included the effects of confining stress, and fluid pressure; as well as validating flow rate – permeability relationship to verify Darcy’s fluid flow law. The effect of model size scaling on sanding was also investigated using 4m height, 2m diameter model. The parallel bond model successfully calibrated the sample’s strength of 4.4MPa, showing a sharp peak strength before strain-softening, similar to the behavior of real cemented sandstones. There seems to be an exponential increasing relationship for the bigger model, but a curvilinear shape for the smaller model. The presence of the Darcy flow induced tensile forces and increased the number of broken bonds. For the parametric studies, flow rate has a linear relationship with permeability at constant pressure head. The higher the fluid flow pressure, the higher the number of broken bonds/sanding. The DEM PFC^3D is a promising tool to studying the micromechanical behavior of cemented sandstones.

Keywords: Discrete Element Method, fluid flow, parametric study, sand production/bonds failure.

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Authors: Khaled E. A. Negm

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A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the relevant information in the neurons' delays. One of the fundamental findings of the this research also is that when using overlapping receptive fields to encode the data patterns it increases the network-s clustering capacity. The clustering algorithm that is discussed here is interesting from computer science and neuroscience point of view as well as from a perspective.

Keywords: Temporal Neurons, RBF Recognition, Perturbation, On Line Recognition.

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Authors: M.Puviyarasan, C.Praveen

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In this study, Friction Stir Processing (FSP) a recent grain refinement technique was employed to disperse micron-sized (2 *m) SiCp particles into aluminum alloy AA6063. The feasibility to fabricate bulk composites through FSP was analyzed and experiments were conducted at different traverse speeds and wider volumes of the specimens. Micro structural observation were carried out by employing optical microscopy test of the cross sections in both parallel and perpendicular to the tool traverse direction. Mechanical property including micro hardness was evaluated in detail at various regions on the specimen. The composites had an excellent bonding with aluminum alloy substrate and a significant increase of 30% in the micro hardness value of metal matrix composite (MMC) as to that of the base metal has observed. The observations clearly indicate that SiC particles were uniformly distributed within the aluminum matrix.

Keywords: Friction Stir Processing, Metal matrix composite, Bulk composite.

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Authors: Devin Atkin, Orly Yadid-Pecht

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The continual demands for increasing resolution and dynamic range in complimentary metal-oxide semiconductor (CMOS) image sensors have resulted in exponential increases in the amount of data that need to be read out of an image sensor, and existing readouts cannot keep up with this demand. Interesting approaches such as sparse and burst readouts have been proposed and show promise, but at considerable trade-offs in other specifications. To this end, we have begun designing and evaluating various readout topologies centered around an attempt to parallelize the sensor readout. In this paper, we have designed, simulated, and started testing a light-controlled oscillator topology with dual column and row readouts. We expect the parallel readout structure to offer greater speed and alleviate the trade-off typical in this topology, where slow pixels present a major framerate bottleneck.

Keywords: CMOS image sensors, high-speed capture, wide dynamic range, light controlled oscillator.

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Authors: Emanuela Paranhos Lima, Vitaly Félix Rodríguez Esquerre

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In this work, efficient directional coupler composed of dielectric waveguides and metallic film has been analyzed in details by simulations using finite element method (FEM). The structure consists of a step-index fiber with dielectric core, silica cladding, and a metal nanowire parallel to the core. The results show that an efficient conversion of optical dielectric modes to long range plasmonic is possible. Low insertion losses in conjunction with short coupling length and a broadband operation can be achieved under certain conditions. This kind of couplers has potential applications for the design of photonic integrated circuits for signal routing between dielectric/plasmonic waveguides, sensing, lithography, and optical storage systems. A high efficient focusing of light in a very small region can be obtained.

Keywords: Directional coupler, finite element method, metallic nanowire, plasmonic, surface plasmon polariton.

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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Authors: Choulseung Hyun, Hunki Kwon, Jaeho Kim, Eujoon Byun, Jongmoo Choi, Donghee Lee, Sam H. Noh

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Most file systems overwrite modified file data and metadata in their original locations, while the Log-structured File System (LFS) dynamically relocates them to other locations. We design and implement the Evergreen file system that can select between overwriting or relocation for each block of a file or metadata. Therefore, the Evergreen file system can achieve superior write performance by sequentializing write requests (similar to LFS-style relocation) when space utilization is low and overwriting when utilization is high. Another challenging issue is identifying performance benefits of LFS-style relocation over overwriting on a newly introduced SSD (Solid State Drive) which has only Flash-memory chips and control circuits without mechanical parts. Our experimental results measured on a SSD show that relocation outperforms overwriting when space utilization is below 80% and vice versa.

Keywords: Evergreen File System, Overwrite, Relocation, Solid State Drive.

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Authors: R. Sridevi, G. Jagajothi

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Artificial Immune Systems (AIS), inspired by the human immune system, are algorithms and mechanisms which are self-adaptive and self-learning classifiers capable of recognizing and classifying by learning, long-term memory and association. Unlike other human system inspired techniques like genetic algorithms and neural networks, AIS includes a range of algorithms modeling on different immune mechanism of the body. In this paper, a mechanism of a human immune system based on apoptosis is adopted to build an Intrusion Detection System (IDS) to protect computer networks. Features are selected from network traffic using Fisher Score. Based on the selected features, the record/connection is classified as either an attack or normal traffic by the proposed methodology. Simulation results demonstrates that the proposed AIS based on apoptosis performs better than existing AIS for intrusion detection.

Keywords: Apoptosis, Artificial Immune System (AIS), Fisher Score, KDD dataset, Network intrusion detection.

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Authors: Anil Kumar

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The Public Bicycle System (PBS), generally known as Public Bicycle Share System or Bike-Share, is a service provided to the everyday commuter, in which several cycles are available on the shared system. The concept of PBS is new to the people of India and requires more study in the fields of essential requirements, major infrastructural requirements, social acceptability and various challenges. In various Indian cities, Mass Rapid Transit System (MRTS), Bus Rapid Transit System (BRTS), Monorail and other modes of transport have been adopted for the main haul of transport. These modes take more time, space and are also expensive to implement. At the same time, the PBS system is more economical and takes less time to implement. The main benefit of the PBS system is that it is more environmentally friendly. PBS is being implemented in many Indian cities for public use, but various challenges are associated with this. The study aims to determine what are the basic infrastructural requirements for PBS in India, as well as to determine to what extent a Public Bike Sharing System can provide a quality and efficient service to passengers as a primary method of transportation.

Keywords: Public Bicycle Sharing system, sustainable transport, infrastructure, smart city.

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Authors: Abdu Masanawa Sagir

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In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations of the form y′′ = f(x,y), a < = x < = b with associated initial or boundary conditions. The continuaous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different three discrete schemes, each of order (4,4,4)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on linear and non-linear ordinary differential equations whose solutions are oscillatory or nearly periodic in nature, and the results obtained compared favourably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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Authors: R. Abdul Wahab, R. Mohd Fuad Tengku Aziz, N. Othman, S. Saleh, N. Razali, M. Al Baqir Zinal Abidin, M. Hanif Md Nasir

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This paper will discuss how we optimize our physical verification flow in our IC Design Department having various rule decks from multiple foundries. Our ultimate goal is to achieve faster time to tape-out and avoid schedule delay. Currently the physical verification runtimes and memory usage have drastically increased with the increasing number of design rules, design complexity, and the size of the chips to be verified. To manage design violations, we use a number of solutions to reduce the amount of violations needed to be checked by physical verification engineers. The most important functions in physical verifications are DRC (design rule check), LVS (layout vs. schematic), and XRC (extraction). Since we have a multiple number of foundries for our design tape-outs, we need a flow that improve the overall turnaround time and ease of use of the physical verification process. The demand for fast turnaround time is even more critical since the physical design is the last stage before sending the layout to the foundries.

Keywords: Physical verification, DRC, LVS, XRC, flow, foundry, runset.

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Authors: Iman Zangeneh, Mostafa Moradi, Mazyar Baranpouyan

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System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.

Keywords: Multiprocessor system, genetic algorithms, time implementation process.

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Authors: I. Alberdi, H. Iribas, A. Martin, N. Aginako

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This paper describes a platform that faces the main research areas for e-learning educational contents. Reusability tackles the possibility to use contents in different courses reducing costs and exploiting available data from repositories. In our approach the production of educational material is based on templates to reuse learning objects. In terms of interoperability the main challenge lays on reaching the audience through different platforms. E-learning solution must track social consumption evolution where nowadays lots of multimedia contents are accessed through the social networks. Our work faces it by implementing a platform for generation of multimedia presentations focused on the new paradigm related to social media. The system produces videos-courses on top of web standard SMIL (Synchronized Multimedia Integration Language) ready to be published and shared. Regarding interfaces it is mandatory to satisfy user needs and ease communication. To overcome it the platform deploys virtual teachers that provide natural interfaces while multimodal features remove barriers to pupils with disabilities.

Keywords: Collaborative, multimedia e-learning, reusability, SMIL, virtual teacher

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Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

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Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: Pronunciation variations, dynamic programming, machine learning, natural language processing.

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Authors: Yu. I. Pigolkin, M. A. Garcia Corro

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Age determination of unknown dead bodies in forensic personal identification is a complicated process which involves the application of numerous methods and techniques. Skeletal remains are less exposed to influences of environmental factors. In order to enhance the accuracy of forensic age estimation additional properties of bones correlating with age are required to be revealed. Material and Methods: Dimensional examination of the sella turcica was carried out on cadavers with the cranium opened by a circular vibrating saw. The sample consisted of a total of 90 Russian subjects, ranging in age from two months and 87 years. Results: The tendency of dimensional variations throughout life was detected. There were no observed gender differences in the morphometry of the sella turcica. The shared use of the sella turcica depth and length values revealed the possibility to categorize an examined sample in a certain age period. Conclusions: Based on the results of existing methods of age determination, the morphometry of the sella turcica can be an additional characteristic, amplifying the received values, and accordingly, increasing the accuracy of forensic biological age diagnosis.

Keywords: Age–related changes in bone structures, forensic personal identification, Sella turcica morphometry, body identification.

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Authors: S. Mulholland

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Octree compression techniques have been used for several years for compressing large three dimensional data sets into homogeneous regions. This compression technique is ideally suited to datasets which have similar values in clusters. Oil engineers represent reservoirs as a three dimensional grid where hydrocarbons occur naturally in clusters. This research looks at the efficiency of storing these grids using octree compression techniques where grid cells are broken into active and inactive regions. Initial experiments yielded high compression ratios as only active leaf nodes and their ancestor, header nodes are stored as a bitstream to file on disk. Savings in computational time and memory were possible at decompression, as only active leaf nodes are sent to the graphics card eliminating the need of reconstructing the original matrix. This results in a more compact vertex table, which can be loaded into the graphics card quicker and generating shorter refresh delay times.

Keywords: 3D visualisation, compressed vertex tables, octree compression techniques, oil reservoir grids.

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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Authors: Ala'eddin A. Saif , Z. A. Z. Jamal, Z. Sauli, P. Poopalan

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The ferroelectric behavior of barium strontium titanate (BST) in thin film form has been investigated in order to study the possibility of using BST for ferroelectric gate-field effect transistor (FeFET) for memory devices application. BST thin films have been fabricated as Al/BST/Pt/SiO2/Si-gate configuration. The variation of the dielectric constant (ε) and tan δ with frequency have been studied to ensure the dielectric quality of the material. The results show that at low frequencies, ε increases as the Ba content increases, whereas at high frequencies, it shows the opposite variation, which is attributed to the dipole dynamics. tan δ shows low values with a peak at the mid-frequency range. The ferroelectric behavior of the Al/BST/Pt/SiO2/Si has been investigated using C-V characteristics. The results show that the strength of the ferroelectric hysteresis loop increases as the Ba content increases; this is attributed to the grain size and dipole dynamics effect.

Keywords: BST thin film, Electrical properties, Ferroelectrichysteresis, Ferroelectric FET.

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Authors: Ahmad M. Awwad, Jehad Al-Sadi

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The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: Interconnection networks, Load balancing, Star network.

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Authors: Benmabrouk. Zaineb, Ben Hamed. Mouna, Lassaad. Sbita

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This paper discusses the development of wireless structure control of an induction motor scalar drives. This was realised up on the wireless WiFi networks. This strategy of control is ensured by the use of Wireless ad hoc networks and a virtual network interface based on VNC which is used to make possible to take the remote control of a PC connected on a wireless Ethernet network. Verification of the proposed strategy of control is provided by experimental realistic tests on scalar controlled induction motor drives. The experimental results of the implementations with their analysis are detailed.

Keywords: Digital drives, Induction motor, Remote control, Virtual Network Computing VNC, Wireless Local Area NetworkWiFi.

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Authors: D. Salari, A. Niaei, P. Chitsaz Yazdi, M. Derakhshani, S. R. Nabavi

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This work aims to test the application of computational fluid dynamics (CFD) modeling to fixed bed catalytic cracking reactors. Studies of CFD with a fixed bed design commonly use a regular packing with N=2 to define bed geometry. CFD allows us to obtain a more accurate view of the fluid flow and heat transfer mechanisms present in fixed bed equipment. Naphtha was used as feedstock and the reactor length was 80cm. It is divided in three sections that catalyst bed packed in the middle section of the reactor. The reaction scheme was involved one primary reaction and 24 secondary reactions. Because of high CPU times in these simulations, parallel processing have been used. In this study the coke formation process in fixed bed and empty tube reactor was simulated and coke in these reactors are compared. In addition, the effect of steam ratio and feed flow rate on coke formation was investigated.

Keywords: Coke Formation, CFD Simulation, Fixed Bed, Catalyitic Cracking.

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Authors: M. Caramihai, Irina Severin, H. Balan, A. Blidaru, V. Balanica

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Accurate assessment of the primary tumor response to treatment is important in the management of breast cancer. This paper introduces a new set of treatment evaluation indicators for breast cancer cases based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The distance principals are applied to pairs of mammograms and/or echograms, recorded before and after treatment, determining a reference point in judging the evolution amount of the studied carcinoma. The obtained numerical results are indeed very transparent and indicate not only the evolution or the involution of the tumor under treatment, but also a quantitative measurement of the benefit in using the selected method of treatment.

Keywords: Breast cancer, Distance metrics, Cancer treatment evaluation.

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Authors: Simone Galati, Adriano Troia

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Ultrasound (US) is widely used in medical field for a variety diagnostic techniques but, in recent years, it has also been creating great interest for therapeutic aims. Regarding drug delivery, the use of US as an activation source provides better spatial delivery confinement and limits the undesired side effects. However, at present there is no complete characterization at a fundamental level of the different signals produced by sono-activated nanocarriers. Therefore, the aim of this study is to obtain a metrological characterization of the cavitation phenomena induced by US through three parallel investigation approaches. US was focused into a channel of a customized phantom in which a solution with oxygen-loaded nanodroplets (OLNDs) was led to flow and the cavitation activity was monitored. Both quantitative and qualitative real-time analysis were performed giving information about the dynamics of bubble formation, oscillation and final implosion with respect to the working acoustic pressure and the type of nanodroplets, compared with pure water. From this analysis a possible interpretation of the observed results is proposed.

Keywords: Cavitation, Drug Delivery, Nanodroplets, Ultrasound.

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Authors: Musbah M. Aqel, P. K. Mahanti, Soumya Banerjee

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This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.

Keywords: Artificial Emotion, Fuzzy logic, Game character, Pheromone label

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Authors: Carsten Röcker

Abstract:

This paper illustrates why existing technology acceptance models are only of limited use for predicting and explaining the adoption of future information and communication technologies. It starts with a general overview over technology adoption processes, and presents several theories for the acceptance as well as adoption of traditional information technologies. This is followed by an overview over the recent developments in the area of information and communication technologies. Based on the arguments elaborated in these sections, it is shown why the factors used to predict adoption in existing systems, will not be sufficient for explaining the adoption of future information and communication technologies.

Keywords: Technology Diffusion, Technology AcceptanceModels, Ambient Intelligence, Ubiquitous and Pervasive Computing.

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Authors: Jian-Wei Li, Yao-Tien Wang, Yi-Chun Chang

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Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.

Keywords: k-nearest neighbor classification, learning community, Cooperative/Collaborative Learning and Environments.

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Authors: C. P. Autry, A.W. Roscoe

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Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: Authentication, enterprise IoT cybersecurity, public key infrastructure, trusted third party.

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