Search results for: Vallejo Michael

Authors: Sean Paulsen, Michael Casey

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In this work, we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: Transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training.

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Authors: M. Michael Gromiha, Kiyonobu Yokota, Kazuhiko Fukui

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We have developed an energy based approach for identifying the binding sites and important residues for binding in protein-protein complexes. We found that the residues and residuepairs with charged and aromatic side chains are important for binding. These residues influence to form cation-¤Ç, electrostatic and aromatic interactions. Our observation has been verified with the experimental binding specificity of protein-protein complexes and found good agreement with experiments. The analysis on surrounding hydrophobicity reveals that the binding residues are less hydrophobic than non-binding sites, which suggests that the hydrophobic core are important for folding and stability whereas the surface seeking residues play a critical role in binding. Further, the propensity of residues in the binding sites of receptors and ligands, number of medium and long-range contacts, and influence of neighboring residues will be discussed.

Keywords: Protein-protein interactions, energy based approach;binding sites, propensity, long-range contacts, hydrophobicity

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Authors: Samar Raffoul, Martin Heywood, Dimitrios Moutaftsis, Michael Rowell

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This paper comprises an experimental investigation into the structural performance of cold formed steel (CFS) and timber board composite floor systems. The tests include a series of small-scale pushout tests and full-scale bending tests carried out using a refined loading system to simulate uniformly distributed constant load. The influence of connection details (screw spacing and adhesives) on floor performance was investigated. The results are then compared to predictions from relevant existing models for composite floor systems. The results of this research demonstrate the significant benefits of considering the composite action of the boards in floor design. Depending on connection detail, an increase in flexural stiffness of up to 40% was observed in the floor system, when compared to designing joists individually.

Keywords: Cold formed steel joists, composite action, flooring systems, shear connection.

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Authors: Diego Felix, Eugene Hyun, Michael McGuire, Mihai Sima

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Terminal localization for indoor Wireless Local Area Networks (WLANs) is critical for the deployment of location-aware computing inside of buildings. A major challenge is obtaining high localization accuracy in presence of fluctuations of the received signal strength (RSS) measurements caused by multipath fading. This paper focuses on reducing the effect of the distance-varying noise by spatial filtering of the measured RSS. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of clusters and survey points uniformly distributed over the network area. The results show that the location accuracy improves by 16% when the filter is used and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. The estimated locations are within 2 m of the true location, which indicates that clustering the survey points provides better localization accuracy due to superior noise removal.

Keywords: Position measurement, Wireless LAN, Radio navigation, Filtering

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Authors: Alejandra Rodríguez Villalobos, Michael Padilla-Mora, Jaime Fornaguera Trías

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Remarkable changes, like the progress in the ability to understand others' minds, can be identified in several socio-cognitive dimensions between age four and seven. Recently, the parenting attitudes have been considerate as one of the potential extrinsic modifiers of these important developmental aspects. The aim of present study is to explore the relationship among authoritarian parenting attitudes and individual differences in Theory of Mind performance. The study included ninety-two Costarrican preschoolers. Six False-belief tasks, an Advanced Theory of Mind test and the Parenting Attitudes Inventory were used. The results demonstrate that participants with high and low Authoritarian Parenting Received differ in their performance on First and Second Order False-belief tasks, but not in Advanced Theory of Mind tasks. Theoretical considerations about possible explanations regarding these results are discussed and methodological limitations are considered to shed light over future directions.

Keywords: Authoritarian parenting, cognitive development, false- belief, individual differences, theory of mind, parenting.

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Authors: Michael Ajide Oyinloye

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Generally the natural environment is made up of air, water and soil. The release of emission of industrial waste into anyone of the components of the environment causes pollution. Industrial pollution significantly threatens the inherent right of people, to the enjoyment of a safe and secure environment. The aim of this paper is to assess the effect of environmental pollution and health risks of residents living near Ewekoro cement factory. The research made use of IKONOS imagery for Geographical Information System (GIS) to buffer and extract buildings that are less than 1km to the factory, within 1km to 5km and above 5km to the factory. Also questionnaire was used to elicit information on the socio-economic factors, effect of environmental pollution on residents and measures adopted to control industrial pollution on the residents. Findings show that most buildings that fall between less than 1km and 1km to 5km to the factory have high health risk in the study area. The study recommended total relocation for the residents of the study area to reduce health risk problems.

Keywords: Environmental pollution, Ewekoro, GIS, Health risk, Satellite imagery.

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Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Panut Mulyono, Widi Astuti

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In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The red mud sample came from the Tayan mine, Indonesia, which contains high hematite (Fe2O3). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30-110 °C. Current density and temperature variations were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 11.8% recovery at a current density of 796 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: Alumina, electrochemical reduction, iron production, red mud.

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Authors: Michael Lissack

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We depend upon explanation in order to “make sense" out of our world. And, making sense is all the more important when dealing with change. But, what happens if our explanations are wrong? This question is examined with respect to two types of explanatory model. Models based on labels and categories we shall refer to as “representations." More complex models involving stories, multiple algorithms, rules of thumb, questions, ambiguity we shall refer to as “compressions." Both compressions and representations are reductions. But representations are far more reductive than compressions. Representations can be treated as a set of defined meanings – coherence with regard to a representation is the degree of fidelity between the item in question and the definition of the representation, of the label. By contrast, compressions contain enough degrees of freedom and ambiguity to allow us to make internal predictions so that we may determine our potential actions in the possibility space. Compressions are explanatory via mechanism. Representations are explanatory via category. Managers are often confusing their evocation of a representation (category inclusion) as the creation of a context of compression (description of mechanism). When this type of explanatory error occurs, more errors follow. In the drive for efficiency such substitutions are all too often proclaimed – at the manager-s peril..

Keywords: Coherence, Emergence, Reduction, Model

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Authors: Michael Amberg, Dipl. Kfm. Johannes C. Panitz

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Compliance requires an effective communication within an enterprise as well as towards a company-s external environment. This requirement commences with the implementation of compliance within large scale compliance projects and still persists in the compliance reporting within standard operations. On the one hand the understanding of compliance necessities within the organization is promoted. On the other hand reduction of asymmetric information with compliance stakeholders is achieved. To reach this goal, a central reporting must provide a consolidated view of different compliance efforts- statuses. A concept which could be adapted for this purpose is the balanced scorecard by Kaplan / Norton. This concept has not been analyzed in detail concerning its adequacy for a holistic compliance reporting starting in compliance projects until later usage in regularly compliance operations. At first, this paper evaluates if a holistic compliance reporting can be designed by using the balanced scorecard concept. The current status of compliance reporting clearly shows that scorecards are generally accepted as a compliance reporting tool and are already used for corporate governance reporting. Additional specialized compliance IT - solutions exist in the market. After the scorecard-s adequacy is thoroughly examined and proofed, an example strategy map as the basis to derive a compliance balanced scorecard is defined. This definition answers the question on proceeding in designing a compliance reporting tool.

Keywords: Balanced Scorecard, Compliance, ComplianceReporting, Compliance Scorecard.

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Authors: Stephan Rupp, Matthias Elter, Michael Breitung, Walter Zink, Christian Küblbeck

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Camera calibration is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, a camera calibration is obtained by taking images of a special calibration object and extracting the image coordinates of projected calibration marks enabling the calculation of the projection from the 3d world coordinates to the 2d image coordinates. Thus such a procedure exhibits typical steps, including feature point localization in the acquired images, camera model fitting, correction of distortion introduced by the optics and finally an optimization of the model-s parameters. In this paper we propose to extend this list by further step concerning the identification of the optimal subset of images yielding the smallest overall calibration error. For this, we present a Monte Carlo based algorithm along with a deterministic extension that automatically determines the images yielding an optimal calibration. Finally, we present results proving that the calibration can be significantly improved by automated image selection.

Keywords: Camera Calibration, Discrete Optimization, Monte Carlo Method.

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Authors: Michael J. Hamlin, Apiwan Manimmanakorn, Gavin R. Sandercock, Jenny J. Ross, Robert H. Creasy, John Hellemans

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The aim of this study was to compare the effects of an altitude training camp on heart rate variability and performance in elite triathletes. Ten athletes completed 20 days of live-high, train-low training at 1650m. Athletes underwent pre and post 800-m swim time trials at sea-level, and two heart rate variability tests at 1650m on the first and last day of the training camp. Based on their time trial results, athletes were divided into responders and non-responders. Relative to the non-responders, the responders sympathetic-toparasympathetic ratio decreased substantially after 20 days of altitude training (-0.68 ± 1.08 and -1.2 ± 0.96, mean ± 90% confidence interval for supine and standing respectively). In addition, sympathetic activity while standing was also substantially lower post-altitude in the responders compared to the non-responders (-1869 ± 4764 ms2). Results indicate that responders demonstrated a change to more vagal predominance compared to non-responders.

Keywords: parasympathetic predominance, poor performance, triathlon, 800-m swim

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Authors: Chakkrit Snae, Michael Brueckner

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In this paper the authors present the framework of a system for assisting users through counseling on personal health, the Personal Health Assistance Service Expert System (PHASES). Personal health assistance systems need Personal Health Records (PHR), which support wellness activities, improve the understanding of personal health issues, enable access to data from providers of health services, strengthen health promotion, and in the end improve the health of the population. This is especially important in societies where the health costs increase at a higher rate than the overall economy. The most important elements of a healthy lifestyle are related to food (such as balanced nutrition and diets), activities for body fitness (such as walking, sports, fitness programs), and other medical treatments (such as massage, prescriptions of drugs). The PHASES framework uses an ontology of food, which includes nutritional facts, an expert system keeping track of personal health data that are matched with medical treatments, and a comprehensive data transfer between patients and the system.

Keywords: Personal health assistance service, expert system, ontologies, knowledge management, information technology.

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Authors: Ching M. Hsu, Rong F. Huang, Michael E. Loretero

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Shear-layer instabilities of a pulsed stack-issued transverse jet were studied experimentally in a wind tunnel. Jet pulsations were induced by means of acoustic excitation. Streak pictures of the smoke-flow patterns illuminated by the laser-light sheet in the median plane were recorded with a high-speed digital camera. Instantaneous velocities of the shear-layer instabilities in the flow were digitized by a hot-wire anemometer. By analyzing the streak pictures of the smoke-flow visualization, three characteristic flow modes, synchronized flapping jet, transition, and synchronized shear-layer vortices, are identified in the shear layer of the pulsed stack-issued transverse jet at various excitation Strouhal numbers. The shear-layer instabilities of the pulsed stack-issued transverse jet are synchronized by acoustic excitation except for transition mode. In transition flow mode, the shear-layer vortices would exhibit a frequency that would be twice as great as the acoustic excitation frequency.

Keywords: Acoustic excitation, jet in crossflow, shear-layer instability.

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Authors: Michael Grigutsch, Peter Nyhuis

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Due to the volatile global economy, enterprises are increasingly focusing on logistics. By investing in suitable measures a company can increase their logistic performance and assert themselves over the competition. However, enterprises are also faced with the challenge of investing available capital for maximum profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need a suitable model for logistically and monetarily evaluating measures in production. Previously, within the frame of Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems and Logistics, (IFA) a Logistic Information System was developed specifically for providing enterprises in the forging industry with support when making decisions. Based on this research, a new initiative referred to as ‘Transfer Project T7’, aims to develop a universal approach for logistically and monetarily evaluating production measures. This paper focuses on the structural measure echelon storage and their impact on the entire production system.

Keywords: Logistic Operating Curves, Transfer Functions, Production Logistics, Storages Echelon.

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Authors: Azzam Hamaideh, Abbas Al-Omari, Michael Sturm

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This study aims at implementing integrated water resources management principles to the Lafarge Cement Jordan at Al-Fuhais plant. This was accomplished by conducting water audits at all water consuming units in the plant. Based on the findings of the water audit, an action plan to improve water use efficiency in the plant was proposed. The main elements of which are installing water saving devices, re-use of the treated wastewater, water harvesting, raising the awareness of the employees, and linking the plant to the water demand management unit at the Ministry of Water and Irrigation.

The analysis showed that by implementing the proposed action plan, it is expected that the industrial water demand can be satisfied from non-conventional resources including treated wastewater and harvested water. As a consequence, fresh water can be used to increase the supply to Al-Fuhais city which is expected to reflect positively on the relationship between the factory and the city. 

Keywords: Integrated water resources management, non-conventional water resources, water awareness, water demand management, water harvesting, water saving devices.

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Authors: Anna H. Tadevosyan, Stepan K. Mayrapetyan, Michael P. Schellenberg, Laura M. Ghalachyan, Albert H. Hovsepyan, Khachatur S. Mayrapetyan

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The possibility of radionuclides-related contamination of lands at agricultural holdings defines the necessity to apply special protective measures in plant growing. The aim of researches is to elucidate the influence of polymers applying on biological migration of man-made anthropogenic radionuclides 90Sr and 137Cs in the system water - soil – plant. The tests are being carried out under field conditions with and without application of polymers in root-inhabited media in more radioecological tension zone (with the radius of 7 km from the Armenian Nuclear Power Plant). The polymers on the base of K+, Caµ, KµCaµ ions were tested. Productivity of pepper depending on the presence and type of polymer material, content of artificial radionuclides in waters, soil and plant material has been determined. The character of different polymers influence on the artificial radionuclides migration and accumulation in the system water-soil-plant and accumulation in the plants has been cleared up.

Keywords: accumulation of artificial radionuclides, pepper, polymer, water-soil-plant system

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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Authors: Liping Jing, Michael K. Ng, Xinhua Yang, Joshua Zhexue Huang

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This paper presents a text clustering system developed based on a k-means type subspace clustering algorithm to cluster large, high dimensional and sparse text data. In this algorithm, a new step is added in the k-means clustering process to automatically calculate the weights of keywords in each cluster so that the important words of a cluster can be identified by the weight values. For understanding and interpretation of clustering results, a few keywords that can best represent the semantic topic are extracted from each cluster. Two methods are used to extract the representative words. The candidate words are first selected according to their weights calculated by our new algorithm. Then, the candidates are fed to the WordNet to identify the set of noun words and consolidate the synonymy and hyponymy words. Experimental results have shown that the clustering algorithm is superior to the other subspace clustering algorithms, such as PROCLUS and HARP and kmeans type algorithm, e.g., Bisecting-KMeans. Furthermore, the word extraction method is effective in selection of the words to represent the topics of the clusters.

Keywords: Subspace Clustering, Text Mining, Feature Weighting, Cluster Interpretation, Ontology

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: Assembly, assistive technologies, augmented reality, manufacturing, visualization.

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Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. In the study, 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests that the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: Ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval.

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Authors: K. Adu Michael, K. Alese Boniface

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Developing a reliable and sustainable software products is today a big challenge among up–coming software developers in Nigeria. The inability to develop a comprehensive problem statement needed to execute proper requirements engineering process is missing. The need to describe the ‘what’ of a system in one document, written in a natural language is a major step in the overall process of Software Engineering. Requirements Engineering is a process use to discover, analyze and validate system requirements. This process is needed in reducing software errors at the early stage of the development of software. The importance of each of the steps in Requirements Engineering is clearly explained in the context of using detailed problem statement from client/customer to get an overview of an existing system along with expectations from the new system. This paper elicits inadequate Requirements Engineering principle as the major cause of poor software development in developing nations using a case study of final year computer science students of a tertiary-education institution in Nigeria.

Keywords: Client/Customer, Problem Statement, Requirements Engineering, Software Developers.

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Authors: Alia Alghosoun, Michael Herty, Mohammed Seaid

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We present a new class of numerical techniques to solve shallow water flows over dry areas including run-up. Many recent investigations on wave run-up in coastal areas are based on the well-known shallow water equations. Numerical simulations have also performed to understand the effects of several factors on tsunami wave impact and run-up in the presence of coastal areas. In all these simulations the shallow water equations are solved in entire domain including dry areas and special treatments are used for numerical solution of singularities at these dry regions. In the present study we propose a new method to deal with these difficulties by reformulating the shallow water equations into a new system to be solved only in the wetted domain. The system is obtained by a change in the coordinates leading to a set of equations in a moving domain for which the wet/dry interface is the reconstructed using the wave speed. To solve the new system we present a finite volume method of Lax-Friedrich type along with a modified method of characteristics. The method is well-balanced and accurately resolves dam-break problems over dry areas.

Keywords: Run-up waves, Shallow water equations, finite volume method, wet/dry interface, dam-break problem.

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Authors: Thomas Kerstein, Martin Laurowski, Philipp Klein, Michael Weyrich, Hubert Roth, Jürgen Wahrburg

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Optical 3D measurement of objects is meaningful in numerous industrial applications. In various cases shape acquisition of weak textured objects is essential. Examples are repetition parts made of plastic or ceramic such as housing parts or ceramic bottles as well as agricultural products like tubers. These parts are often conveyed in a wobbling way during the automated optical inspection. Thus, conventional 3D shape acquisition methods like laser scanning might fail. In this paper, a novel approach for acquiring 3D shape of weak textured and moving objects is presented. To facilitate such measurements an active stereo vision system with structured light is proposed. The system consists of multiple camera pairs and auxiliary laser pattern generators. It performs the shape acquisition within one shot and is beneficial for rapid inspection tasks. An experimental setup including hardware and software has been developed and implemented.

Keywords: automated optical inspection, depth from structured light, stereo vision, surface reconstruction

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Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: Aggregation prone regions, amyloids, thermophilic proteins, amino acid residues, machine learning.

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Authors: Indrasen Raghupatruni, Michael Glora, Ralf Diekmann, Thomas Demmer

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As the trend in automotive technology is fast moving towards hybridization and electrification to curb emissions as well as to improve the fuel efficiency, air-conditioning systems in passenger cars have not caught up with this trend and still remain as the major energy consumers amongst others. Adsorption based air-conditioning systems, e.g. with silica-gel water pair, which are already in use for residential and commercial applications, are now being considered as a technology leap once proven feasible for the passenger cars. In this paper we discuss a methodology, challenges and feasibility of implementing an adsorption based air-conditioning system in a passenger car utilizing the exhaust waste heat. We also propose an optimized control strategy with interfaces to the engine control unit of the vehicle for operating this system with reasonable efficiency supported by our simulation and validation results in a prototype vehicle, additionally comparing to existing implementations, simulation based as well as experimental. Finally we discuss the influence of start-stop and hybrid systems on the operation strategy of the adsorption air-conditioning system.

Keywords: Adsorption air-conditioning, feasibility study, optimized control strategy, prototype vehicle.

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Authors: Michael Zimba, Darlison Nyirenda

Abstract:

A novel copy-move image forgery, CMIF, detection method is proposed. The proposed method presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilized to extract robust features. The extracted features are invariant to additive noise, JPEG compression, and affine transformation. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. SATS is a better option than the common shift vector method because SATS is insensitive to affine transformation. Consequently, the proposed CMIF algorithm is not only fast but also more robust to attacks compared to the existing related CMIF algorithms. The experimental results show high detection rates, as high as 100% in some cases.

Keywords: Affine transformation, Radix sort, SATS, Virtual electrostatic field.

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Authors: K. Alese Boniface, K. Adu Michael

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Cybercrime is now becoming a big challenge in Nigeria apart from the traditional crime. Inability to identify perpetrators is one of the reasons for the growing menace. This paper proposes a design for monitoring internet users’ activities in order to curbing cybercrime. It requires redefining the operations of Internet Service Providers (ISPs) which will now mandate users to be authenticated before accessing the internet. In implementing this work which can be adapted to a larger scale, a virtual router application is developed and configured to mimic a real router device. A sign-up portal is developed to allow users to register with the ISP. The portal asks for identification information which will include bio-data and government issued identification data like National Identity Card number, et cetera. A unique username and password are chosen by the user to enable access to the internet which will be used to reference him to an Internet Protocol Address (IP Address) of any system he uses on the internet and thereby associating him to any criminal act related to that IP address at that particular time. Questions such as “What happen when another user knows the password and uses it to commit crime?” and other pertinent issues are addressed.

Keywords: Cybercrime, Sign-up Portal, Internet Service Provider (ISP), Internet Protocol Address (IP address).

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: Boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones.

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Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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Average temperatures worldwide are expected to continue to rise. At the same time, major cities in developing countries are becoming increasingly populated and polluted. Governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of a model, which is able to estimate the occupant exposure to extreme temperatures and high air pollution within domestic buildings. Building physics simulations were performed using the EnergyPlus building physics software. An accurate metamodel is then formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) have been compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: Neural Networks, Radial Basis Functions, Metamodelling, Python machine learning libraries.

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

Abstract:

PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.

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