Search results for: combining forecasts.

Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

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Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

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Authors: K. Paradkar, S. N. Mudliar, A. Sharma, A. B. Pandit, R. A. Pandey

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The study explores the hybrid combination of Hydrodynamic Cavitation (HC) and Subcritical Wet Air Oxidation-based pretreatment of complex industrial effluent to enhance the biodegradability selectively (without major COD destruction) to facilitate subsequent enhanced downstream processing via anaerobic or aerobic biological treatment. Advanced oxidation based techniques can be less efficient as standalone options and a hybrid approach by combining Hydrodynamic Cavitation (HC), and Wet Air Oxidation (WAO) can lead to a synergistic effect since both the options are based on common free radical mechanism. The HC can be used for initial turbulence and generation of hotspots which can begin the free radical attack and this agitating mixture then can be subjected to less intense WAO since initial heat (to raise the activation energy) can be taken care by HC alone. Lab-scale venturi-based hydrodynamic cavitation and wet air oxidation reactor with biomethanated distillery wastewater (BMDWW) as a model effluent was examined for establishing the proof-of-concept. The results indicated that for a desirable biodegradability index (BOD: COD - BI) enhancement (up to 0.4), the Cavitation (standalone) pretreatment condition was: 5 bar and 88 min reaction time with a COD reduction of 36 % and BI enhancement of up to 0.27 (initial BI - 0.17). The optimum WAO condition (standalone) was: 150oC, 6 bar and 30 minutes with 31% COD reduction and 0.33 BI. The hybrid pretreatment (combined Cavitation + WAO) worked out to be 23.18 min HC (at 5 bar) followed by 30 min WAO at 150oC, 6 bar, at which around 50% COD was retained yielding a BI of 0.55. FTIR & NMR analysis of pretreated effluent indicated dissociation and/or reorientation of complex organic compounds in untreated effluent to simpler organic compounds post-pretreatment.

Keywords: BI, hybrid, hydrodynamic cavitation, wet air oxidation.

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Authors: K. Venkateswari, U. K. Balaji Saravanan, K. Thangaraj, K. V. Deepana

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Image search engines rely on the surrounding textual keywords for the retrieval of images. It is a tedious work for the search engines like Google and Bing to interpret the user’s search intention and to provide the desired results. The recent researches also state that the Google image search engines do not work well on all the images. Consequently, this leads to the emergence of efficient image retrieval technique, which interprets the user’s search intention and shows the desired results. In order to accomplish this task, an efficient image re-ranking framework is required. Sequentially, to provide best image retrieval, the new image re-ranking framework is experimented in this paper. The implemented new image re-ranking framework provides best image retrieval from the image dataset by making use of re-ranking of retrieved images that is based on the user’s desired images. This is experimented in two sections. One is offline section and other is online section. In offline section, the reranking framework studies differently (reference classes or Semantic Spaces) for diverse user query keywords. The semantic signatures get generated by combining the textual and visual features of the images. In the online section, images are re-ranked by comparing the semantic signatures that are obtained from the reference classes with the user specified image query keywords. This re-ranking methodology will increases the retrieval image efficiency and the result will be effective to the user.

Keywords: CBIR, Image Re-ranking, Image Retrieval, Semantic Signature, Semantic Space.

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Authors: Mohamad K. Hasan, Hameed Al-Qaheri

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Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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Authors: R.N.Pise, S.A.Kulkarni, R.V.Pawar

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MultiProtocol Label Switching (MPLS) is an emerging technology that aims to address many of the existing issues associated with packet forwarding in today-s Internetworking environment. It provides a method of forwarding packets at a high rate of speed by combining the speed and performance of Layer 2 with the scalability and IP intelligence of Layer 3. In a traditional IP (Internet Protocol) routing network, a router analyzes the destination IP address contained in the packet header. The router independently determines the next hop for the packet using the destination IP address and the interior gateway protocol. This process is repeated at each hop to deliver the packet to its final destination. In contrast, in the MPLS forwarding paradigm routers on the edge of the network (label edge routers) attach labels to packets based on the forwarding Equivalence class (FEC). Packets are then forwarded through the MPLS domain, based on their associated FECs , through swapping the labels by routers in the core of the network called label switch routers. The act of simply swapping the label instead of referencing the IP header of the packet in the routing table at each hop provides a more efficient manner of forwarding packets, which in turn allows the opportunity for traffic to be forwarded at tremendous speeds and to have granular control over the path taken by a packet. This paper deals with the process of MPLS forwarding mechanism, implementation of MPLS datapath , and test results showing the performance comparison of MPLS and IP routing. The discussion will focus primarily on MPLS IP packet networks – by far the most common application of MPLS today.

Keywords: Forwarding equivalence class, incoming label map, label, next hop label forwarding entry.

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: Multimodal image registration, GAN, cycle consistency, deep learning.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: Thermal remote sensing, insolation model, land surface temperature, geothermal anomalies.

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Authors: Mehdi Hosseinzadeh, Somayyeh Jafarali Jassbi, Keivan Navi

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Residue Number System (RNS) is a modular representation and is proved to be an instrumental tool in many digital signal processing (DSP) applications which require high-speed computations. RNS is an integer and non weighted number system; it can support parallel, carry-free, high-speed and low power arithmetic. A very interesting correspondence exists between the concepts of Multiple Valued Logic (MVL) and Residue Number Arithmetic. If the number of levels used to represent MVL signals is chosen to be consistent with the moduli which create the finite rings in the RNS, MVL becomes a very natural representation for the RNS. There are two concerns related to the application of this Number System: reaching the most possible speed and the largest dynamic range. There is a conflict when one wants to resolve both these problem. That is augmenting the dynamic range results in reducing the speed in the same time. For achieving the most performance a method is considere named “One-Hot Residue Number System" in this implementation the propagation is only equal to one transistor delay. The problem with this method is the huge increase in the number of transistors they are increased in order m² . In real application this is practically impossible. In this paper combining the Multiple Valued Logic and One-Hot Residue Number System we represent a new method to resolve both of these two problems. In this paper we represent a novel design of an OHRNS-based adder circuit. This circuit is useable for Multiple Valued Logic moduli, in comparison to other RNS design; this circuit has considerably improved the number of transistors and power consumption.

Keywords: Computer Arithmetic, Residue Number System, Multiple Valued Logic, One-Hot, VLSI.

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Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: Gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated& sustainable electric.

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Authors: S. Sutin, M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee

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This study investigated morphology of the Spanner Barb (Puntius lateristriga Valenciennes, 1842) and water quality at Thepchana waterfall. This study was conducted at Thepchana Waterfall, Khao Nan National Park from March to May 2007. There were 40 Spanner Barb collected with 20 males and 20 females. Males had an average of 5.57 cm in standard length, 6.62 cm in total length and 5.18 g in total body weight. Females had an average of 7.25 cm in standard length, 8.24 cm in total length and 10.96 g in total body weight. The length (L) – weight (W) relationships for combining sexes, males and females were LogW = -2.137 + 3.355logL, log W = -0.068 + 3.297logL, and log W = -2.068 + 3.297logL, respectively. The Spanner Barb were smaller size fish with a compressed form; terminal mouth; villiform teeth; ctenoid scale; concave tail; general body color yellowish olive, with slight reddish tint to fins; vertical band beginning below dorsal and horizontal stripe from base of tail almost to vertical band. They also had a vertical band midway between the eye and first vertical band. There was a black spot above anal fin. The bladder looked like J-shape. Inside of the bladder was found small insects and insect lava. The body length and the bowels length was 1:1 ratio. The water temperature ranged from 25.00 – 27.00 °C which was appropriate for their habitat characteristics. Acid - alkalinity ranged from 6.65 – 6.90 mg/l. Dissolved oxygen ranged from 4.55 – 4.70 mg/l. Water hardness ranged from 31.00 – 48.00 mg/l. The amount of ammonia was about 0.25 mg/l.

Keywords: Spanner barb, morphology, water quality.

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Authors: Nurul Bahiyah Ahmad Khairudin, Habibah A Wahab

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A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.

Keywords: 3D model, Chicken villin headpiece subdomain, Molecular dynamic simulation NMR-MDavg, RMSD.

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Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: Dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment.

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Authors: Yudhajit Datta, Jonathan Bandi, Ankit Sethia, Hamsi Iyer

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Motion Tracking and Stereo Vision are complicated, albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining the two approaches. The study aims to explore a strategy to combine the two techniques of two-dimensional motion tracking using Kalman Filter; and depth detection of object using Stereo Vision. In conventional approaches objects in the scene of interest are observed using a single camera. However for Stereo Motion Tracking; the scene of interest is observed using video feeds from two calibrated cameras. Using two simultaneous measurements from the two cameras a calculation for the depth of the object from the plane containing the cameras is made. The approach attempts to capture the entire three-dimensional spatial information of each object at the scene and represent it through a software estimator object. In discrete intervals, the estimator tracks object motion in the plane parallel to plane containing cameras and updates the perpendicular distance value of the object from the plane containing the cameras as depth. The ability to efficiently track the motion of objects in three-dimensional space using a simplified approach could prove to be an indispensable tool in a variety of surveillance scenarios. The approach may find application from high security surveillance scenes such as premises of bank vaults, prisons or other detention facilities; to low cost applications in supermarkets and car parking lots.

Keywords: Kalman Filter, Stereo Vision, Motion Tracking, Matlab, Object Tracking, Camera Calibration, Computer Vision System Toolbox.

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Authors: Sansanee Jasuwan

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Thai and Vietnamese music had been influenced and inspired by the traditional Chinese music. Whereby the differences of the tuning systems as well as the music modes are obviously known . The research examined the character of musical instruments, songs and culture between Thai and Vietnamese. An analyzing of songs and modes and the study of tone vibration as well as timbre had been done accurately. This qualitative research is based on documentary and songs analysis, field study, interviews and focus group discussion of Thai and Vietnamese masters. The research aims are to examine the musical instruments and songs of both Thai and Vietnamese as well as the comparison of the sounding system between Thailand and Vietnam. The finding of the research has revealed that there are similarities in certain kinds of instruments but differences in the sound systems regarding songs and scale of Thailand and Vietnam. Both cultural musical instruments are diverse and synthetic combining native and foreign inspiring. An integral part of Vietnam has been highly impacted by Chinese musical convention. Korea, Mongolia and Japan music have also play an active and effectively influenced as their geographical related. Whereas Thailand has been influenced by Chinese and Indian traditional music. Both Thai and Vietnamese musical instruments can be divided into four groups: plucked strings, bowed strings, winds and percussion. Songs from both countries have their own characteristics. They are playing a role in touching people heart in ceremonies, social functions and an essential element of the native performing arts. The Vietnamese music melodies have been influenced by Chinese music and taken the same character as Chinese songs. Thai song has specific identity and variety showed in its unique melody. Pentatonic scales have effectively been used in composing Thai and Vietnamese songs, but in different implementing concept.

Keywords: Music sound system, Thailand, Vietnam.

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Authors: Feng-Sheng Wang, Wu-Hsiung Wu, Kai-Cheng Hsu

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The optimization of biological systems, which is a branch of metabolic engineering, has generated a lot of industrial and academic interest for a long time. In the last decade, metabolic engineering approaches based on mathematical optimizations have been used extensively for the analysis and manipulation of metabolic networks. In practical optimization of metabolic reaction networks, designers have to manage the nature of uncertainty resulting from qualitative characters of metabolic reactions, e.g., the possibility of enzyme effects. A deterministic approach does not give an adequate representation for metabolic reaction networks with uncertain characters. Fuzzy optimization formulations can be applied to cope with this problem. A fuzzy multi-objective optimization problem can be introduced for finding the optimal engineering interventions on metabolic network systems considering the resilience phenomenon and cell viability constraints. The accuracy of optimization results depends heavily on the development of essential kinetic models of metabolic networks. Kinetic models can quantitatively capture the experimentally observed regulation data of metabolic systems and are often used to find the optimal manipulation of external inputs. To address the issues of optimizing the regulatory structure of metabolic networks, it is necessary to consider qualitative effects, e.g., the resilience phenomena and cell viability constraints. Combining the qualitative and quantitative descriptions for metabolic networks makes it possible to design a viable strain and accurately predict the maximum possible flux rates of desired products. Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. Two case studies will present in the conference to illustrate the phenomena.

Keywords: Fuzzy multi-objective optimization problem, kinetic model, metabolic engineering.

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Authors: Brody R. Clark, Chaminda Gallage, John Yeaman

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Multigrade bitumen asphalt is a quality asphalt product that is not utilised in many places globally. Multigrade bitumen is believed to be less sensitive to temperature, which gives it an advantage over conventional binders. Previous testing has shown that asphalt temperature changes greatly with depth, but currently the industry standard is to nominate a single temperature for design. For detailed design of asphalt roads, perhaps asphalt layers should be divided into nominal layer depths and different modulus and fatigue equations/values should be used to reflect the temperatures of each respective layer. A collaboration of previous laboratory testing conducted on multigrade bitumen asphalt beams under a range of temperatures and loading conditions was analysed. The samples tested included 0% or 15% recycled asphalt pavement (RAP) to determine what impact the recycled material has on the fatigue life and stiffness of the pavement. This paper investigated the temperature susceptibility of multigrade bitumen asphalt pavements compared to conventional binders by combining previous testing that included conducting a sweep of fatigue tests, developing complex modulus master curves for each mix and a study on how pavement temperature changes through pavement depth. This investigation found that the final design of the pavement is greatly affected by the nominated pavement temperature and respective material properties. This paper has outlined a potential revision to the current design approach for asphalt pavements and proposes that further investigation is needed into pavement temperature and its incorporation into design.

Keywords: Asphalt, complex modulus, fatigue life, flexural stiffness, four-point bending, master curves, multigrade bitumen, thermal gradient.

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards health information application in Smart National Identity Card. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the factors of trust, perceived risk, Privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. Empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: Unified Theory of Acceptance and Use of Technology (UTAUT) model, UTAUT2 model, Smart National Identity Card (SNIC), Health information application, Privacy Calculus Model (PCM).

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Md. Shafiqul Islam, Abdullah Khan, Sharon Kao-Walter, Li Jian

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Shear testing is one of the most complex testing areas where available methods and specimen geometries are different from each other. Therefore, a modified shear test specimen (MSTS) combining the simple uniaxial test with a zone of interest (ZOI) is tested which gives almost the pure shear. In this study, material parameters of polypropylene (PP) and high density polyethylene (HDPE) are first measured by tensile tests with a dogbone shaped specimen. These parameters are then used as an input for the finite element analysis. Secondly, a specially designed specimen (MSTS) is used to perform the shear stress tests in a tensile testing machine to get the results in terms of forces and extension, crack initiation etc. Scanning Electron Microscopy (SEM) is also performed on the shear fracture surface to find material behavior. These experiments are then simulated by finite element method and compared with the experimental results in order to confirm the simulation model. Shear stress state is inspected to find the usability of the proposed shear specimen. Finally, a geometry correction factor can be established for these two materials in this specific loading and geometry with notch using Linear Elastic Fracture Mechanics (LEFM). By these results, strain energy of shear failure and stress intensity factor (SIF) of shear of these two polymers are discussed in the special application of the screw cap opening of the medical or food packages with a temper evidence safety solution.

Keywords: Shear test specimen, Stress intensity factor, Finite Element simulation, Scanning electron microscopy, Screw cap opening.

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Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: Collaborative filtering, e-learning, ontology, recommender system.

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Authors: S. Looser, W. Wehrmeyer

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Given the limited research on Small and Mediumsized Enterprises’ (SMEs) contribution to Corporate Social Responsibility (CSR) and even scarcer research on Swiss SMEs, this paper helps to fill these gaps by enabling the identification of supranational SME parameters. Thus, the paper investigates the current state of SME practices in Switzerland and across 15 other countries. Combining the degree to which SMEs demonstrate an explicit (or business case) approach or see CSR as an implicit moral activity with the assessment of their attributes for “variety of capitalism” defines the framework of this comparative analysis. To outline Swiss small business CSR patterns in particular, 40 SME owner-managers were interviewed. A secondary data analysis of studies from different countries laid groundwork for this comparative overview of small business CSR. The paper identifies Swiss small business CSR as driven by norms, values, and by the aspiration to contribute to society, thus, as an implicit part of the day-to-day business. Similar to most Central European, Mediterranean, Nordic, and Asian countries, explicit CSR is still very rare in Swiss SMEs. Astonishingly, also British and American SMEs follow this pattern in spite of their strong and distinctly liberal market economies. Though other findings show that nationality matters this research concludes that SME culture and an informal CSR agenda are strongly formative and superseding even forces of market economies, nationally cultural patterns, and language. Hence, classifications of countries by their market system, as found in the comparative capitalism literature, do not match the CSR practices in SMEs as they do not mirror the peculiarities of their business. This raises questions on the universality and generalisability of unmediated, explicit management concepts, especially in the context of small firms.

Keywords: CSR, comparative study, cultures of capitalism, Small and Medium-sized Enterprises.

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Authors: A. Javed, K. Djidjeli, J. T. Xing, S. J. Cox

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A method for simulating flow around the solid bodies has been presented using hybrid meshfree and mesh-based schemes. The presented scheme optimizes the computational efficiency by combining the advantages of both meshfree and mesh-based methods. In this approach, a cloud of meshfree nodes has been used in the domain around the solid body. These meshfree nodes have the ability to efficiently adapt to complex geometrical shapes. In the rest of the domain, conventional Cartesian grid has been used beyond the meshfree cloud. Complex geometrical shapes can therefore be dealt efficiently by using meshfree nodal cloud and computational efficiency is maintained through the use of conventional mesh-based scheme on Cartesian grid in the larger part of the domain. Spatial discretization of meshfree nodes has been achieved through local radial basis functions in finite difference mode (RBF-FD). Conventional finite difference scheme has been used in the Cartesian ‘meshed’ domain. Accuracy tests of the hybrid scheme have been conducted to establish the order of accuracy. Numerical tests have been performed by simulating two dimensional steady and unsteady incompressible flows around cylindrical object. Steady flow cases have been run at Reynolds numbers of 10, 20 and 40 and unsteady flow problems have been studied at Reynolds numbers of 100 and 200. Flow Parameters including lift, drag, vortex shedding, and vorticity contours are calculated. Numerical results have been found to be in good agreement with computational and experimental results available in the literature.

Keywords: CFD, Meshfree particle methods, Hybrid grid, Incompressible Navier Strokes equations, RBF-FD.

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: Continuous wavelet transform, convolution neural network, gated recurrent unit, health indicators, remaining useful life.

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Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

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This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: Analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges.

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Authors: Smaali Assia, Outemzabet Ratiba, Media El Mahdi, Kadi Mohamed

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Films of pure tin oxide SnO2 and in presence of antimony atoms (SnO2-Sb) deposited onto glass substrates have shown a sufficiently high energy gap to be transparent in the visible region, a high electrical mobility and a carrier concentration which displays a good electrical conductivity [1]. In this work, the effects of polycrystalline silicon substrate on the optical properties of pure and Sb doped tin oxide is investigated. We used the APCVD (atmospheric pressure chemical vapour deposition) technique, which is a low-cost and simple technique, under nitrogen ambient, for growing this material. A series of SnO2 and SnO2-Sb have been deposited onto polycrystalline silicon substrates with different contents of antimony atoms at the same conditions of deposition (substrate temperature, flow oxygen, duration and nitrogen atmosphere of the reactor). The effect of the substrate in terms of morphology and nonlinear optical properties, mainly the reflectance, was studied. The reflectance intensity of the device, compared to the reflectance of tin oxide films deposited directly on glass substrate, is clearly reduced on the overall wavelength range. It is obvious that the roughness of the poly-c silicon plays an important role by improving the reflectance and hence the optical parameters. A clear shift in the minimum of the reflectance upon doping level is observed. This minimum corresponds to strong free carrier absorption, resulting in different plasma frequency. This effect is followed by an increase in the reflectance depending of the antimony doping. Applying the extended Drude theory to the combining optical and electrical obtained results these effects are discussed.

Keywords: Doping, oxide, reflectance.

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Authors: Mahmoud Amer, Ibrahim El-Sharkawy, Shinichi Ookawara, Ahmed Elwardany

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Gasification and carbonization are two of the most common ways for biomass utilization. Both processes are using part of the waste to be accomplished, either by incomplete combustion or for heating for both gasification and carbonization, respectively. The focus of this paper is to minimize the part of the waste that is used for heating biomass for gasification and carbonization. This will occur by combining both gasifiers and carbonization reactors in a single unit to utilize the heat in the product biogas to heating up the wastes in the carbonization reactors. Three different designs are proposed for the combined gasification/carbonization (CGC) reactor. These include a parallel combination of two gasifiers and carbonized syngas, carbonizer and combustion chamber, and one gasifier, carbonizer, and combustion chamber. They are tested numerically using ANSYS Fluent Computational Fluid Dynamics to ensure homogeneity of temperature distribution inside the carbonization part of the CGC reactor. 2D simulations are performed for the three cases after performing both mesh-size and time-step independent solutions. The carbonization part is common among the three different cases, and the difference among them is how this carbonization reactor is heated. The simulation results showed that the first design could provide only partial homogeneous temperature distribution, not across the whole reactor. This means that the produced carbonized biomass will be reduced as it will only fill a specified height of the reactor. To keep the carbonized product production high, a series combination is proposed. This series configuration resulted in a uniform temperature distribution across the whole reactor as it has only one source for heat with no temperature distribution on any surface of the carbonization section. The simulations provided a satisfactory result that either the first parallel combination of gasifier and carbonization reactor could be used with a reduced carbonized amount or a series configuration to keep the production rate high.

Keywords: Numerical simulation, carbonization, gasification, reactor, biomass.

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Authors: A. A. Zaidan, Anas Majeed, B. B. Zaidan

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Nowadays, the rapid development of multimedia and internet allows for wide distribution of digital media data. It becomes much easier to edit, modify and duplicate digital information Besides that, digital documents are also easy to copy and distribute, therefore it will be faced by many threatens. It-s a big security and privacy issue with the large flood of information and the development of the digital format, it become necessary to find appropriate protection because of the significance, accuracy and sensitivity of the information. Nowadays protection system classified with more specific as hiding information, encryption information, and combination between hiding and encryption to increase information security, the strength of the information hiding science is due to the non-existence of standard algorithms to be used in hiding secret messages. Also there is randomness in hiding methods such as combining several media (covers) with different methods to pass a secret message. In addition, there are no formal methods to be followed to discover the hidden data. For this reason, the task of this research becomes difficult. In this paper, a new system of information hiding is presented. The proposed system aim to hidden information (data file) in any execution file (EXE) and to detect the hidden file and we will see implementation of steganography system which embeds information in an execution file. (EXE) files have been investigated. The system tries to find a solution to the size of the cover file and making it undetectable by anti-virus software. The system includes two main functions; first is the hiding of the information in a Portable Executable File (EXE), through the execution of four process (specify the cover file, specify the information file, encryption of the information, and hiding the information) and the second function is the extraction of the hiding information through three process (specify the steno file, extract the information, and decryption of the information). The system has achieved the main goals, such as make the relation of the size of the cover file and the size of information independent and the result file does not make any conflict with anti-virus software.

Keywords: Cryptography, Steganography, Portable ExecutableFile.

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Authors: Amit Kr. Happy

Abstract:

This paper is motivated by the importance of multi-sensor image fusion with specific focus on Infrared (IR) and Visible image (VI) fusion for various applications including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like Visible camera & IR Thermal Imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (IR) that may be reflected or self-emitted. A digital color camera captures the visible source image and a thermal IR camera acquires the thermal source image. In this paper, some image fusion algorithms based upon Multi-Scale Transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, but they also make it hard to become deployed in system and applications that require real-time operation, high flexibility and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: Image fusion, IR thermal imager, multi-sensor, Multi-Scale Transform.

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