Search results for: granular computing

Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Dohwan Kim, Dongchoon Ryou, Pyungjong Yoo

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In public water facilities, drinking water distribution systems have played an important role along with water purification systems. The water distribution network is one of the most expensive components of water supply infrastructure systems. To improve the reliability for the drinking rate of tap water, advanced water treatment processes such as granular activated carbon and membrane filtration were used by water service providers in Korea. But, distrust of the people for tap water are still. Therefore, accurate diagnosis and condition assessment for water pipelines are required to supply the clean water. The internal corrosion of water pipe has increased as time passed. Also, the cross-sectional areas in pipe are reduced by the rust, deposits and tubercles. It is the water supply ability decreases as the increase of hydraulic pump capacity is required to supply an amount of water, such as the initial condition. If not, the poor area of water supply will be occurred by the decrease of water pressure. In order to solve these problems, water managers and engineers should be always checked for the current status of the water pipe, such as water leakage and damage of pipe. If problems occur, it should be able to respond rapidly and make an accurate estimate. In Korea, replacement and rehabilitation of aging drinking water pipes are carried out based on the circumstances of simply buried years. So, water distribution system management may not consider the entire water pipeline network. The long-term design and upgrading of a water distribution network should address economic, social, environmental, health, hydraulic, and other technical issues. This is a multi-objective problem with a high level of complexity. In this study, the thickness of the old water pipes, corrosion levels of the inner and outer surface for water pipes, basic data research (i.e. pipe types, buried years, accident record, embedded environment, etc.), specific resistance of soil, ultimate tensile strength and elongation of metal pipes, samples characteristics, and chemical composition analysis were performed about aging drinking water pipes. Samples of water pipes used in this study were cement mortar lining ductile cast iron pipe (CML-DCIP, diameter 100mm) and epoxy lining steel pipe (diameter 65 and 50mm). Buried years of CML-DCIP and epoxy lining steel pipe were respectively 32 and 23 years. The area of embedded environment was marine reclamation zone since 1940’s. The result of this study was that CML-DCIP needed replacement and epoxy lining steel pipe was still useful.

Keywords: drinking water distribution system, water supply, replacement, rehabilitation, water pipe

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Authors: Bezhan Tutberidze

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The Neogene-Quaternary volcanic rocks of the Javakheti Highland are products of post-collisional continental magmatism and are related to divergent and convergent margins of Eurasian-Afroarabian lithospheric plates. The studied area constitutes an integral part of the volcanic province of Central South Georgia. Three cycles of volcanic activity are identified here: 1. Late Miocene-Early Pliocene, 2. Late Pliocene-Early /Middle/ Pleistocene and 3. Late Pleistocene. An intense basic dolerite magmatic activity occurred within the time span of the Late Pliocene and lasted until at least Late /Middle/ Pleistocene. The age of the volcanogenic and volcanogenic-sedimentary formation was dated by geomorphological, paleomagnetic, paleontological and geochronological methods /1.7-1.9 Ma/. The volcanic area of the Javakheti Highland contains multiple dolerite Plateaus: Akhalkalaki, Gomarethi, Dmanisi, and Tsalka. Petrographic observations of these doleritic rocks reveal fairly constant mineralogical composition: olivine / Fo₈₇.₆₋₈₂.₇ /, plagioclase / Ab₂₂.₈ An₇₅.₉ Or₁.₃; Ab₄₅.₀₋₃₂.₃ An₅₂.₉₋₆₂.₃ Or₂.₁₋₅.₄/. The pyroxene is an augite and may exhibit a visible zoning: / Wo 39.7-43.1 En 43.5-45.2 Fs 16.8-11.7/. Opaque minerals /magnetite, titanomagnetite/ is abundant as inclusions within olivine and pyroxene crystals. The texture of dolerites exhibits intergranular, holocrystalline to ophitic to sub ophitic granular. Dolerites are most common vesicular rocks. Vesicles range in shape from spherical to elongated and in size from 0.5 mm to than 1.5-2 cm and makeup about 20-50 % of the volume. The dolerites have been subjected to considerable alteration. The secondary minerals in the geothermal field are: zeolite, calcite, chlorite, aragonite, clay-like mineral /dominated by smectites/ and iddingsite –like mineral; rare quartz and pumpellyite are present. These vesicles are filled by secondary minerals. In the chemistry, dolerites are the calc-alkalic transition to sub-alkaline with a predominance of Na₂O over K₂O. Chemical analyses indicate that dolerites of all plateaus of the Javakheti Highland have similar geochemical compositions, signifying that they were formed from the same magmatic source by crystallization of olivine basalis magma which less differentiated / ⁸⁷Sr \ ⁸⁶Sr 0.703920-0704195/. There is one argument, which is less convincing, according to which the dolerites/basalts of the Javakheti Highland are considered to be an activity of a mantle plume. Unfortunately, there does not exist reliable evidence to prove this. The petrochemical peculiarities and eruption nature of the dolerites of the Javakheti Plateau point against their plume origin. Nevertheless, it is not excluded that they influence the formation of dolerite producing primary basaltic magma.

Keywords: calc-alkalic, dolerite, Georgia, Javakheti Highland

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Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

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Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

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Authors: Veronica Caprai, Katrin Schollbach, Miruna V. A. Florea, H. J. H. Brouwers

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Nowadays MSWI (Municipal Solid Waste Incineration) bottom ash (BA) produced by Waste-to-Energy (WtE) plants represents the majority of the solid residues derived from MSW incineration. Once processed, the BA is often landfilled resulting in possible environmental problems, additional costs for the plant and increasing occupation of public land. In order to limit this phenomenon, European countries such as the Netherlands aid the utilization of MSWI BA in the construction field, by providing standards about the leaching of contaminants into the environment (Dutch Soil Quality Decree). Commonly, BA has a particle size below 32 mm and a heterogeneous chemical composition, depending on its source. By washing coarser BA, an MSWI sludge is obtained. It is characterized by a high content of heavy metals, chlorides, and sulfates as well as a reduced particle size (below 0.25 mm). To lower its environmental impact, MSWI sludge is filtered or centrifuged for removing easily soluble contaminants, such as chlorides. However, the presence of heavy metals is not easily reduced, compromising its possible application. For lowering the leaching of those contaminants, the use of MSWI residues in combination with cement represents a precious option, due to the known retention of those ions into the hydrated cement matrix. Among the applications, the European standard for common cement EN 197-1:1992 allows the incorporation of up to 5% by mass of a minor additional constituent (MAC), such as fly ash or blast furnace slag but also an unspecified filler into cement. To the best of the author's knowledge, although it is widely available, it has the appropriate particle size and a chemical composition similar to cement, FC has not been investigated as possible MAC in cement production. Therefore, this paper will address the suitability of MSWI FC as MAC for CEM I 52.5 R, within a 5% maximum replacement by mass. After physical and chemical characterization of the raw materials, the crystal phases of the pastes are determined by XRD for 3 replacement levels (1%, 3%, and 5%) at different ages. Thereafter, the impact of FC on mechanical and environmental performances of cement is assessed according to EN 196-1 and the Dutch Soil Quality Decree, respectively. The investigation of the reaction products evidences the formation of layered double hydroxides (LDH), in the early stage of the reaction. Mechanically the presence of FC results in a reduction of 28 days compressive strength by 8% for a replacement of 5% wt., compared with the pure CEM I 52.5 R without any MAC. In contrast, the flexural strength is not affected by the presence of FC. Environmentally, the Dutch legislation for the leaching of contaminants for unshaped (granular) material is satisfied. Based on the collected results, FC represents a suitable candidate as MAC in cement production.

Keywords: environmental impact evaluation, Minor additional constituent, MSWI residues, X-ray diffraction crystallography

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Authors: Wesley H. Brewer, John C. Sanford

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SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Raja Omman Zafar, Yves Rybarczyk, Johan Borg

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This article proposes a conceptual framework for the application of digital twin technology in home care. The main goal is to bridge the gap between advanced digital twin concepts and their practical implementation in home care. This study uses a literature review and thematic analysis approach to synthesize existing knowledge and proposes a structured framework suitable for homecare applications. The proposed framework integrates key components such as IoT sensors, data-driven models, cloud computing, and user interface design, highlighting the importance of personalized and predictive homecare solutions. This framework can significantly improve the efficiency, accuracy, and reliability of homecare services. It paves the way for the implementation of digital twins in home care, promoting real-time monitoring, early intervention, and better outcomes.

Keywords: digital twin, homecare, older adults, healthcare, IoT, artificial intelligence

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Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

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Authors: Abd Latif Abdul Rahman, Zuraidah Arif, Muhammad Faizal Iylia, Mohd Ghazali, Asmadi Mohammed Ghazali

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Mobile information is a significant access point for human information activities. Theories and models of human information behavior have developed over several decades but have not yet considered the role of the user’s computing device in digital information interactions. This paper reviews the literature that leads to developing a conceptual framework of a study on the managers mobile information behavior. Based on the literature review, dimensions of mobile information behavior are identified, namely, dimension information needs, dimension information access, information retrieval and dimension of information use. The study is significant to understand the nature of librarians’ behavior in searching, retrieving and using information via the mobile device. Secondly, the study would provide suggestions about various kinds of mobile applications which organization can provide for their staff to improve their services.

Keywords: mobile information behavior, information behavior, mobile information, mobile devices

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Authors: Maryam Amiri, Leyli Mohammad-Khanli

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Cloud computing is becoming increasingly popular and more business applications are moving to cloud. In this regard, services that provide similar functional properties are increasing. So, the ability to select a service with the best non-functional properties, corresponding to the user preference, is necessary for the user. This paper presents an Evaluation Framework of Service Trustworthiness (EFST) that evaluates the trustworthiness of equivalent services without need to additional invocations of them. EFST extracts user preference automatically. Then, it assesses trustworthiness of services in two dimensions of qualitative and quantitative metrics based on the experiences of past usage of services. Finally, EFST determines the overall trustworthiness of services using Fuzzy Inference System (FIS). The results of experiments and simulations show that EFST is able to predict the missing values of Quality of Service (QoS) better than other competing approaches. Also, it propels users to select the most appropriate services.

Keywords: user preference, cloud service, trustworthiness, QoS metrics, prediction

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Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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Authors: Modesta E. Ezema, Chikwendu V. Alabekee, Victoria N. Ishiwu, Ifeyinwa NwosuArize, Chinedu I. Nwoye

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The advent of wireless networking in computing technology cannot be overemphasized, it opened up easy accessibility to information resources, networking made easier and brought internet accessibility to our doorsteps, but despite all these, some mishap came in with it that is causing mayhem in today ‘s overall information security. The cyber criminals will always compromise the integrity of a message that is not encrypted or that is encrypted with a weak algorithm.In other to correct the mayhem, this study focuses on cryptosystem and cryptography. This ensures end to end crypt messaging. The study of various cryptographic algorithms, as well as the techniques and applications of the cryptography for efficiency, were all considered in the work., present and future applications of cryptography were dealt with as well as Quantum Cryptography was exposed as the current and the future area in the development of cryptography. An empirical study was conducted to collect data from network users.

Keywords: algorithm, cryptography, cryptosystem, network

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Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

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Authors: Chien-Chun Huang, P. W. Yuan

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Banana is one of the important fruits which constitute a valuable source of energy, vitamins and minerals and an important food component throughout the world. The fruit ripening and maturity standards vary from country to country depending on the expected shelf life of market. During ripening there are changes in appearance, texture and chemical composition of banana. The changes of component of banana during ethylene-induced ripening are categorized as nutritive values and commercial utilization. The objectives of this study were to investigate the changes of chemical composition and physicochemical properties of banana during ethylene-induced ripening. Green bananas were harvested and ripened by ethylene gas at low temperature (15℃) for seven stages. At each stage, banana was sliced and freeze-dried for banana flour preparation. The changes of total starch, resistant starch, chemical compositions, physicochemical properties, activity of amylase, polyphenolic oxidase (PPO) and phenylalanine ammonia lyase (PAL) of banana were analyzed each stage during ripening. The banana starch was isolated and analyzed for gelatinization properties, pasting properties and microscopic appearance each stage of ripening. The results indicated that the highest total starch and resistant starch content of green banana were 76.2% and 34.6%, respectively at the harvest stage. Both total starch and resistant starch content were significantly declined to 25.3% and 8.8%, respectively at the seventh stage. Soluble sugars content of banana increased from 1.21% at harvest stage to 37.72% at seventh stage during ethylene-induced ripening. Swelling power of banana flour decreased with the progress of ripening stage, but solubility increased. These results strongly related with the decreases of starch content of banana flour during ethylene-induced ripening. Both water insoluble and alcohol insoluble solids of banana flour decreased with the progress of ripening stage. Both activity of PPO and PAL increased, but the total free phenolics content decreased, with the increases of ripening stages. As ripening stage extended, the gelatinization enthalpy of banana starch significantly decreased from 15.31 J/g at the harvest stage to 10.55 J/g at the seventh stage. The peak viscosity and setback increased with the progress of ripening stages in the pasting properties of banana starch. The highest final viscosity, 5701 RVU, of banana starch slurry was found at the seventh stage. The scanning electron micrograph of banana starch showed the shapes of banana starch appeared to be round and elongated forms, ranging in 10-50 μm at the harvest stage. As the banana closed to ripe status, some parallel striations were observed on the surface of banana starch granular which could be caused by enzyme reaction during ripening. These results inferred that the highest resistant starch was found in the green banana could be considered as a potential application of healthy foods. The changes of chemical composition and physicochemical properties of banana could be caused by the hydrolysis of enzymes during the ethylene-induced ripening treatment.

Keywords: maturation of banana, appearance, texture, soluble sugars, resistant starch, enzyme activities, physicochemical properties of banana starch

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: Yaping Zhao, Yimin Zhang

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In the present paper, the stationary random vibration of a uniform cantilever beam is investigated. Two types of damping mechanism, i.e. the external and internal viscous dampings, are taken into account simultaneously. The excitation form is the support motion, and it is ideal white. Because two type of damping mechanism are considered concurrently, the product of the modal damping ratio and the natural frequency is not a constant anymore. As a result, the infinite definite integral encountered in the process of computing the mean square response is more complex than that in the existing literature. One signal progress of this work is to have calculated these definite integrals accurately. The precise solution of the mean square response is thus obtained in the infinite series form finally. Numerical examples are supplied and the numerical outcomes acquired confirm the validity of the theoretical analyses.

Keywords: random vibration, cantilever beam, mean square response, white noise

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Authors: Fariborz Ahmadi, Reza Tati

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Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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Authors: Dana Kristalova

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Long Kim Vu

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The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

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Authors: M. Tammaro, S. Manzo, J. Rimauro, A. Salluzzo, S. Schiavo

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The solar photovoltaic (PV) modules are considered to have a negligible environmental impact compared to the fossil energy. Therefore also the waste management and the corresponding potential environmental hazard needs to be considered. The case of the photovoltaic panel is unique because the time lag from the manufacturing to the decommissioning as waste usually takes 25-30 years. Then the environmental hazard associated with end life of PV panels has been largely related to their metal contents. The principal concern regards the presence of heavy metals as Cd in thin film (TF) modules or Pb and Cr in crystalline silicon (c-Si) panels. At the end of life of PV panels, these dangerous substances could be released in the environment, if special requirements for their disposal are not adopted. Nevertheless, in literature, only a few experimental study about metal emissions from silicon crystalline/thin film panels and the corresponding environmental effect are present. As part of a study funded by the Italian national consortium for the waste collection and recycling (COBAT), the present work was aimed to analyze experimentally the potential release into the environment of hazardous elements, particularly metals, from PV waste. In this paper, for the first time, eighteen releasable metals a large number of photovoltaic panels, by c-Si and TF, manufactured in the last 30 years, together with the environmental effects by a battery of ecotoxicological tests, were investigated. Leaching tests are conducted on the crushed samples of PV module. The test is conducted according to Italian and European Standard procedure for hazard assessment of the granular waste and of the sludge. The sample material is shaken for 24 hours in HDPE bottles with an overhead mixer Rotax 6.8 VELP at indoor temperature and using pure water (18 MΩ resistivity) as leaching solution. The liquid-to-solid ratio was 10 (L/S=10, i.e. 10 liters of water per kg of solid). The ecotoxicological tests were performed in the subsequent 24 hours. A battery of toxicity test with bacteria (Vibrio fisheri), algae (Pseudochirneriella subcapitata) and crustacea (Daphnia magna) was carried out on PV panel leachates obtained as previously described and immediately stored in dark and at 4°C until testing (in the next 24 hours). For understand the actual pollution load, a comparison with the current European and Italian benchmark limits was performed. The trend of leachable metal amount from panels in relation to manufacturing years was then highlighted in order to assess the environmental sustainability of PV technology over time. The experimental results were very heterogeneous and show that the photovoltaic panels could represent an environmental hazard. The experimental results showed that the amounts of some hazardous metals (Pb, Cr, Cd, Ni), for c-Si and TF, exceed the law limits and they are a clear indication of the potential environmental risk of photovoltaic panels "as a waste" without a proper management.

Keywords: photovoltaic panel, environment, ecotoxicity, metals emission

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

Abstract:

Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: H. Samadiyeh, R. Khajavi

Abstract:

A new FD-based procedure, modal finite difference method (MFDM), is proposed for seismic wave propagation modeling, in which simulation is dealt with in the modal space. The method employs eigenvalues of a characteristic matrix formed by appropriate time-space FD stencils. Since MFD runs for different modes are totally independent of each other, MFDM can easily be parallelized while considerable simplicity in parallel-algorithm is also achieved. There is no requirement to any domain-decomposition procedure and inter-core data exchange. More important is the possibility to skip processing of less-significant modes, which enables one to adjust the procedure up to the level of accuracy needed. Thus, in addition to considerable ease of parallel programming, computation and storage costs are significantly reduced. The method is qualified for its efficiency by some numerical examples.

Keywords: Finite Difference Method, Graphics Processing Unit (GPU), Message Passing Interface (MPI), Modal, Wave propagation

Procedia PDF Downloads 274

Authors: Sachin B. Patil, Narendra M. Kanhe

Abstract:

A typical cane molasses based distillery generates 15 L of waste water per liter of alcohol production. Distillery waste with COD of over 1,00,000 mg/l and BOD of over 30,000 mg/l ranks high amongst the pollutants produced by industries both in magnitude and strength. Treatment and safe disposal of this waste is a challenging task since long. The high strength of waste water renders aerobic treatment very expensive and physico-chemical processes have met with little success. Thermophilic anaerobic treatment of distillery waste may provide high degree of treatment and better recovery of biogas. It may prove more feasible in most part of tropical country like India, where temperature is suitable for thermophilic micro-organisms. Researchers have reviled that, at thermophilic conditions due to increased destruction rate of organic matter and pathogens, higher digestion rate can be achieved. Literature review reveals that the variety of anaerobic reactors including anaerobic lagoon, conventional digester, anaerobic filter, two staged fixed film reactors, sludge bed and granular bed reactors have been studied, but little attempts have been made to evaluate the usefulness of thermophilic anaerobic treatment for treating distillery waste. The present study has been carried out, to study feasibility of thermophilic anaerobic digestion to facilitate the design of full scale reactor. A pilot scale anaerobic fixed film fixed bed reactor (AFFFB) of capacity 25m3 was designed, fabricated, installed and commissioned for thermophilic (55-65°C) anaerobic digestion at a constant pH of 6.5-7.5, because these temperature and pH ranges are considered to be optimum for biogas recovery from distillery wastewater. In these conditions, working of the reactor was studied, for different hydraulic retention times (HRT) (0.25days to 12days) and variable organic loading rates (361.46 to 7.96 Kg COD/m3d). The parameters such as flow rate and temperature, various chemical parameters such as pH, chemical oxygen demands (COD), biogas quantity, and biogas composition were regularly monitored. It was observed that, with the increase in OLR, the biogas production was increased, but the specific biogas yield decreased. Similarly, with the increase in HRT, the biogas production got decrease, but the specific biogas yield was increased. This may also be due to the predominant activity of acid producers to methane producers at the higher substrate loading rates. From the present investigation, it can be concluded that for thermophilic conditions the highest COD removal percentage was obtained at an HRT of 08 days, thereafter it tends to decrease from 8 to 12 days HRT. There is a little difference between COD removal efficiency of 8 days HRT (74.03%) and 5 day HRT (78.06%), therefore it would not be feasible to increase the reactor size by 1.5 times for mere 4 percent more efficiency. Hence, 5 days HRT is considered to be optimum, at which the biogas yield was 98 m3/day and specific biogas yield was 0.385 CH4 m3/Kg CODr.

Keywords: spent wash, anaerobic digestion, biomass, biogas

Procedia PDF Downloads 247

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

Abstract:

Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 483

Authors: Te-Jen Chang, Ping-Sheng Huang, Shan-Ten Cheng, Chih-Lin Lin, I-Hui Pan, Tsung- Hsien Lin

Abstract:

RSA system is a great contribution for the encryption and the decryption. It is based on the modular exponentiation. We call this system as “a large of numbers for calculation”. The operation of a large of numbers is a very heavy burden for CPU. For increasing the computational speed, in addition to improve these algorithms, such as the binary method, the sliding window method, the addition chain method, and so on, the cluster computer can be used to advance computational speed. The cluster system is composed of the computers which are installed the MPICH2 in laboratory. The parallel procedures of the modular exponentiation can be processed by combining the sliding window method with the addition chain method. It will significantly reduce the computational time of the modular exponentiation whose digits are more than 512 bits and even more than 1024 bits.

Keywords: cluster system, modular exponentiation, sliding window, addition chain

Procedia PDF Downloads 503