Search results for: capacity of neural networks.

Authors: Tatjana Rakcejeva, Ingrida Augspole, Lija Dukalska, Fredijs Dimins

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carrot is one of the important root vegetable crops, and it is highly nutritious as it contains appreciable amount of vitamins, minerals and β-carotene. The major objective of current research was to evaluate the chemical composition of carrot variety 'Nante' hybrids in general and to select the best samples for fresh-cut salad production. The research was accomplished on fresh in Latvia cultivated carrots harvested in Zemgale region in the first part of October, 2011 and immediately used for experiments. Late-bearing variety 'Nante' hybrid carrots were used for analysis: 'Nante/Berlikum', 'Nante/Maestro', 'Nante/Forto', 'Nante/Bolero' and 'Nante/Champion'. The quality parameters as moisture, soluble solid, firmness, b-carotene, carotenoid, color, polyphenols, total phenolic compounds and total antioxidant capacity were analyzed using standard methods. For fresh-cut salad production as more applicable could be recommended hybrids 'Nante/Forto' and 'Nante/Berlikum' - mainly because it-s higher nutritive value, as higher total phenolic compounds, polyphenols and pronounced antioxidant capacity.

Keywords: carrots, chemical composition, evaluation

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Authors: Prakash G L, Chaitra K Meti, Poojitha K, Divya R.K.

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Wireless Sensor Network is Multi hop Self-configuring Wireless Network consisting of sensor nodes. The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high energy node as cluster head. The different methods of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with cluster head only. The energy constraint and limited computing resources of the sensor nodes present the major challenges in gathering the data. In this paper we propose a framework to study how partially correlated data affect the performance of clustering algorithms. The total energy consumption and network lifetime can be analyzed by combining random geometry techniques and rate distortion theory. We also present the relation between compression distortion and data correlation.

Keywords: Clusters, multi hop, random geometry, rate distortion.

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Authors: Mohd Fairuz Iskandar Othman, Nazrulazhar Bahaman, Zulkiflee Muslim, Faizal Abdollah

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This paper discusses a curriculum approach that will give emphasis on practical portions of teaching network security subjects in information and communication technology courses. As we are well aware, the need to use a practice and application oriented approach in education is paramount. Research on active learning and cooperative groups have shown that students grasps more and have more tendency towards obtaining and realizing soft skills like leadership, communication and team work as opposed to the more traditional theory and exam based teaching and learning. While this teaching and learning paradigm is relatively new in Malaysia, it has been practiced widely in the West. This paper examines a certain approach whereby students learning wireless security are divided into and work in small and manageable groups where there will be 2 teams which consist of black hat and white hat teams. The former will try to find and expose vulnerabilities in a wireless network while the latter will try their best to prevent such attacks on their wireless networks using hardware, software, design and enforcement of security policy and etc. This paper will try to show that the approach taken plus the use of relevant and up to date software and hardware and with suitable environment setting will hopefully expose students to a more fruitful outcome in terms of understanding of concepts, theories and their motivation to learn.

Keywords: Curriculum approach, wireless networks, wirelesssecurity.

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Authors: Vera Varazashvili, Murman Tsarakhov, Tamar Mirianashvili, Teimuraz Pavlenishvili, Tengiz Machaladze, Mzia Khundadze

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Standard Gibbs energy of formation ΔGfor(298.15) of lanthanide-iron double oxides of garnet-type crystal structure R3Fe5O12 - RIG (R – are rare earth ions) from initial oxides are evaluated. The calculation is based on the data of standard entropies S298.15 and standard enthalpies ΔH298.15 of formation of compounds which are involved in the process of garnets synthesis. Gibbs energy of formation is presented as temperature function ΔGfor(T) for the range 300-1600K. The necessary starting thermodynamic data were obtained from calorimetric study of heat capacity – temperature functions and by using the semi-empirical method for calculation of ΔH298.15 of formation. Thermodynamic functions for standard temperature – enthalpy, entropy and Gibbs energy - are recommended as reference data for technological evaluations. Through the structural series of rare earth-iron garnets the correlation between thermodynamic properties and characteristics of lanthanide ions are elucidated.

Keywords: Calorimetry, entropy, enthalpy, heat capacity, gibbs energy of formation, rare earth iron garnets.

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Authors: Y. Aldali, F. Ahwide

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This paper investigates the application of large scale (LS-PV) two-axis tracking photovoltaic power plant in Al-Jagbob, Libya. A 50MW PV-grid connected (two-axis tracking) power plant design in Al-Jagbob, Libya has been carried out presently. A hetero-junction with intrinsic thin layer (HIT) type PV module has been selected and modeled. A Microsoft Excel-VBA program has been constructed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency for this system, for tracking system. The results for energy production show that the total energy output is 128.5 GWh/year. The average module efficiency is 16.6%. The electricity generation capacity factor (CF) and solar capacity factor (SCF) were found to be 29.3% and 70.4% respectively. A 50MW two axis tracking power plant with a total energy output of 128.5 GWh/year would reduce CO₂ pollution by 85,581 tonnes of each year. The payback time for the proposed LS-PV photovoltaic power plant was found to be 4 years.

Keywords: Large PV power plant, solar energy, environmental impact, Dual-axis tracking system.

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Authors: M. Ali, K. Alam, E. Ohioma

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This paper presents a numerical investigation on the behavior of fiber reinforced polymer composite tubes (FRP) under thermomechanical coupled loading using finite element software ABAQUS and a special add-on subroutine, CZone. Three cases were explored; pure mechanical loading, pure thermal loading, and coupled thermomechanical loading. The failure index (Tsai-Wu) under all three loading cases was assessed for all plies in the tube walls. The simulation results under pure mechanical loading showed that composite tube failed at a tensile load of 3.1 kN. However, with the superposition of thermal load on mechanical load on the composite tube, the failure index of the previously failed plies in tube walls reduced significantly causing the tube to fail at 6 kN. This showed 93% improvement in the load carrying capacity of the composite tube in present study. The increase in load carrying capacity was attributed to the stress effects of the coefficients of thermal expansion (CTE) on the laminate as well as the inter-lamina stresses induced due to the composite stack layup.

Keywords: Thermal, mechanical, composites, square tubes.

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Authors: B. Kabane, G. G. Redhi

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An ammonium based ionic liquid (methyltrioctylammonium chloride) [N_{8 8 8 1}] [Cl] was investigated as an extraction potential solvent for volatile organic solvents (in this regard, solutes), which includes alkenes, alkanes, ketones, alkynes, aromatic hydrocarbons, tetrahydrofuran (THF), alcohols, thiophene, water and acetonitrile based on the experimental activity coefficients at infinite THF measurements were conducted by the use of gas-liquid chromatography at four different temperatures (313.15 to 343.15) K. Experimental data of activity coefficients obtained across the examined temperatures were used in order to calculate the physicochemical properties at infinite dilution such as partial molar excess enthalpy, Gibbs free energy and entropy term. Capacity and selectivity data for selected petrochemical extraction problems (heptane/thiophene, heptane/benzene, cyclohaxane/cyclohexene, hexane/toluene, hexane/hexene) were computed from activity coefficients data and compared to the literature values with other ionic liquids. Evaluation of activity coefficients at infinite dilution expands the knowledge and provides a good understanding related to the interactions between the ionic liquid and the investigated compounds.

Keywords: Separation, activity coefficients, ionic liquid, methyltrioctylammonium chloride, capacity.

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Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny

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Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: Cancer, metabolites, metabolic pathway, signaling pathway.

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Authors: Burcu Akyildiz, Cigdem Kadaifci, Y. Ilker Topcu, Burc Ulengin

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In today’s business environment, companies should  make strategic decisions to gain sustainable competitive advantage.  Order selection is a crucial issue among these decisions especially for  steel production industry. When the companies allocate a high  proportion of their design and production capacities to their ongoing  projects, determining which customer order should be chosen among  the potential orders without exceeding the remaining capacity is the  major critical problem. In this study, it is aimed to identify and  prioritize the evaluation factors for the customer order selection  problem. Conjoint Analysis is used to examine the importance level  of each factor which is determined as the potential profit rate per unit  of time, the compatibility of potential order with available capacity,  the level of potential future order with higher profit, customer credit  of future business opportunity, and the negotiability level of  production schedule for the order.

 

Keywords: Conjoint analysis, order prioritization, profit management, structural steel firm.

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Authors: Alexei M. Mikhailov

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The paper discusses the mathematics of pattern indexing and its applications to recognition of visual patterns that are found in video clips. It is shown that (a) pattern indexes can be represented by collections of inverted patterns, (b) solutions to pattern classification problems can be found as intersections and histograms of inverted patterns and, thus, matching of original patterns avoided.

Keywords: Artificial neural cortex, computational biology, data mining, pattern recognition.

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Authors: Shahrinaz Ismail, Roslina Abdul Latif

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Social media has led to paradigm shifts in ways people work and do business, interact and socialize, learn and obtain knowledge. So much so that social media has established itself as an important spatial extension of this nation-s historicity and challenges. Regardless of the enabling reputation and recommendation features through social networks embedded in the social media system, the overflow of broadcasted and publicized media contents turns the table around from engendering trust to doubting the trust system. When the trust is at doubt, the effects include deactivation of accounts and creation of multiple profiles, which lead to the overflow of 'ghost' contents (i.e. “the abundance of abandoned ships"). In most literature, the study of trust can be related to culture; hence the difference between Western-s “openness" and Eastern-s “blue-chip" concepts in networking and relationships. From a survey on issues and challenges among Malaysian social media users, 'authenticity' emerges as one of the main factors that causes and is caused by other factors. The other issue that has surfaced is credibility either in terms of message/content and source. Another is the quality of the knowledge that is shared. This paper explores the terrains of this critical space which in recent years has been dominated increasingly by, arguably, social networks embedded in the social media system, the overflow of broadcasted and publicized media content.

Keywords: Authenticity, credibility, knowledge quality and social media.

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Authors: Randhir Singh Baghel

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In this study, the fundamental ideas guiding the dynamic area of machine learning—where models thrive and algorithms change over time—are rooted in an innate mathematical link. This study explores the fundamental ideas that drive the development of intelligent systems, providing light on the mutually beneficial link between mathematics and machine learning.

Keywords: Machine Learning, deep learning, Neural Network, optimization.

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Authors: Imen Sfaihi, Noureddine Hamdi

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In this paper, we investigate the study of techniques for scheduling users for resource allocation in the case of multiple input and multiple output (MIMO) packet transmission systems. In these systems, transmit antennas are assigned to one user or dynamically to different users using spatial multiplexing. The allocation of all transmit antennas to one user cannot take full advantages of multi-user diversity. Therefore, we developed the case when resources are allocated dynamically. At each time slot users have to feed back their channel information on an uplink feedback channel. Channel information considered available in the schedulers is the zero forcing (ZF) post detection signal to interference plus noise ratio. Our analysis study concerns the round robin and the opportunistic schemes. In this paper, we present an overview and a complete capacity analysis of these schemes. The main results in our study are to give an analytical form of system capacity using the ZF receiver at the user terminal. Simulations have been carried out to validate all proposed analytical solutions and to compare the performance of these schemes.

Keywords: MIMO, scheduling, ZF receiver, spatial multiplexing, round robin scheduling, opportunistic.

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Authors: Gulzar A. Khuwaja, Mohammad S. Laghari

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capability to reliably distinguish between an authorized person and an imposter. Signature verification systems can be categorized as offline (static) and online (dynamic). This paper presents a neural network based recognition of offline handwritten signatures system that is trained with low-resolution scanned signature images.

Keywords: Pattern Recognition, Computer Vision, AdaptiveClassification, Handwritten Signature Recognition.

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

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Authors: Vladimir I. Ponomarenko, Mikhail D. Prokhorov, Anatoly S. Karavaev

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The interaction between respiration and low-frequency rhythms of the cardiovascular system is studied. The obtained results count in favor of the hypothesis that low-frequency rhythms in blood pressure and R-R intervals are generated in different central neural structures involved in the autonomic control of the cardiovascular systems.

Keywords: Cardiovascular system, R-R intervals, blood pressure, synchronization.

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Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: Data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional.

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Authors: Mostafa Osman, Ata El-Kareim Shoeib Soliman

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Since columns are the most important elements of the structures, failure of one column in a critical location can cause a progressive collapse. In this respect, the repair and strengthening of columns is a very important subject to reduce the building failure and to keep the columns capacity. Twenty columns with different parameters is tested and analysis. Eleven typical confined reinforced concrete (RC) columns with different types of techniques are assessment. And also, four confined concrete columns with plastic tube (PVC) are tested with and with four paralleling tested of unconfined plain concrete. The techniques of confined RC columns are mortar strengthening, Steel rings strengthening, FRP strengthening. Moreover, the technique of confined plain concrete (PC) column is used PVC tubes. The columns are tested under uniaxial compressive loads studied the effect of confinement on the structural behavior of circular RC columns. Test results for each column are presented in the form of crack patterns, stress-strain curves. Test results show that confining of the RC columns using different techniques of strengthening results significant improvement of the general behavior of the columns and can used in construction. And also, tested confined PC columns with PVC tubes results shown that the confined PC with PVC tubes can be used in economical building. The theoretical model for predicted column capacity is founded with experimental factor depends on the confined techniques used and the strain reduction.

Keywords: Confined reinforced concrete column, CFRP, GFRP, Mortar.

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Authors: Moneeb Gohar, Seok Joo Koh, Tae-Won Um, Hyun-Woo Lee

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This paper proposes a fast tree join scheme to provide seamless multicast handover in the mobile networks based on the Fast Mobile IPv6 (FMIPv6). In the existing FMIPv6-based multicast handover scheme, the bi-directional tunnelling or the remote subscription is employed with the packet forwarding from the previous access router (AR) to the new AR. In general, the remote subscription approach is preferred to the bi-directional tunnelling one, since in the remote subscription scheme we can exploit an optimized multicast path from a multicast source to many mobile receivers. However, in the remote subscription scheme, if the tree joining operation takes a long time, the amount of data packets to be forwarded and buffered for multicast handover will increase, and thus the corresponding buffer may overflow, which results in severe packet losses. In order to reduce these costs associated with packet forwarding and buffering, this paper proposes the fast join to multicast tree, in which the new AR will join the multicast tree as fast as possible, so that the new multicast data packets can also arrive at the new AR, by which the packet forwarding and buffering costs can be reduced. From numerical analysis, it is shown that the proposed scheme can give better performance than the existing FMIPv6-based multicast handover schemes in terms of the multicast packet delivery costs.

Keywords: Mobile Multicast, FMIPv6, Seamless Handover, Fast Tree Join.

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Authors: Rizik Al-Sayyed, Colin Pattinson, Tony Dacre

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This paper presents the findings of two experiments that were performed on the Redundancy in Wireless Connection Model (RiWC) using the 802.11b standard. The experiments were simulated using OPNET 11.5 Modeler software. The first was aimed at finding the maximum number of simultaneous Voice over Internet Protocol (VoIP) users the model would support under the G.711 and G.729 codec standards when the packetization interval was 10 milliseconds (ms). The second experiment examined the model?s VoIP user capacity using the G.729 codec standard along with background traffic using the same packetization interval as in the first experiment. To determine the capacity of the model under various experiments, we checked three metrics: jitter, delay and data loss. When background traffic was added, we checked the response time in addition to the previous three metrics. The findings of the first experiment indicated that the maximum number of simultaneous VoIP users the model was able to support was 5, which is consistent with recent research findings. When using the G.729 codec, the model was able to support up to 16 VoIP users; similar experiments in current literature have indicated a maximum of 7 users. The finding of the second experiment demonstrated that the maximum number of VoIP users the model was able to support was 12, with the existence of background traffic.

Keywords: WLAN, IEEE 802.11b, Codec, VoIP, OPNET, Background traffic, and QoS.

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Authors: Zhou Xiong, Kang Shao Bo, Yang Bo

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To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.

Keywords: Axial compression, Finite element analysis, Overall stability, Q460GJ steel, Welded box columns.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.

Keywords: WSN, TBDFC, LEACH, PEGASIS, TREEPSI.

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Authors: A. K. Pradhan, M. K. Mohanty, S. K. Kar

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The power system utility has started to think about the green power technology in order to have an eco-friendly environment. The green power technology utilizes renewable energy sources for reduction of GHG emissions. Odisha state (India) is very rich in potential of renewable energy sources especially in solar energy (about 300 solar days), for installation of grid connected photovoltaic system. This paper focuses on the utilization of photovoltaic systems in an Institute building of Bhubaneswar city, Odisha. Different data like solar insolation (kW/m²/day), sunshine duration has been collected from metrological stations for Bhubaneswar city. The required electrical power and cost are calculated for daily load of 1.0 kW. The HOMER (Hybrid Optimization Model of Electric Renewable) software is used to estimate system size and its performance analysis. The simulation result shows that the cost of energy (COE) is $ 0.194/kWh, the Operating cost is $63/yr and the net present cost (NPC) is $3,917. The energy produced from PV array is 1,756kWh/yr and energy purchased from grid is 410kWh/yr. The AC primary load consumption is 1314 kWh/yr and the Grid sales are 746 kWh/yr. One battery is connected in parallel with 12V DC Bus and the usable nominal capacity 2.4 kWh with 9.6 h autonomy capacity.

Keywords: Economic assessment, HOMER, Optimization, Photovoltaic (PV), Renewable energy.

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Authors: K. P. Valdés García, E. I. Rodríguez Fonseca, L. G. Juárez Cantú

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Suicide is a global, multidimensional and dynamic problem of mental health, which requires a constant study for its understanding and prevention. When research of this phenomenon is done, it is necessary to consider the different characteristics it may have because of the individual and sociocultural variables, the importance of this consideration is related to the generation of effective treatments and interventions. Adolescents are a vulnerable population due to the characteristics of the development stage. The investigation was carried out with the objective of identifying and describing the conceptualization of adolescents of suicide, and in this process, we find possible differences between men and women. The study was carried out in Saltillo, Coahuila, Mexico. The sample was composed of 418 volunteer students aged between 11 and 18 years. The ethical aspects of the research were reviewed and considered in all the processes of the investigation with the participants, their parents and the schools to which they belonged, psychological attention was offered to the participants and preventive workshops were carried in the educational institutions. Natural semantic networks were the instrument used, since this hybrid method allows to find and analyze the social concept of a phenomenon; in this case, the word suicide was used as an evocative stimulus and participants were asked to evoke at least five words and a maximum 10 that they thought were related to suicide, and then hierarchize them according to the closeness with the construct. The subsequent analysis was carried with Excel, yielding the semantic weights, affective loads and the distances between each of the semantic fields established according to the words reported by the subjects. The results showed similarities in the conceptualization of suicide in adolescents, men and women. Seven semantic fields were generated; the words were related in the discourse analysis: 1) death, 2) possible triggering factors, 3) associated moods, 4) methods used to carry it out, 5) psychological symptomatology that could affect, 6) words associated with a rejection of suicide, and finally, 7) specific objects to carry it out. One of the necessary aspects to consider in the investigations of complex issues such as suicide is to have a diversity of instruments and techniques that adjust to the characteristics of the population and that allow to understand the phenomena from the social constructs and not only theoretical. The constant study of suicide is a pressing need, the loss of a life from emotional difficulties that can be solved through psychiatry and psychological methods requires governments and professionals to pay attention and work with the risk population.

Keywords: Adolescents, semantic networks, speech analysis, suicide.

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Authors: Yao-Tang Chang, Chuen-Ching Wang, Shu-Han Hu

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In order to implement flexibility as well as survivable capacities over passive optical network (PON), a new automatic random fault-recovery mechanism with array-waveguide-grating based (AWG-based) optical switch (OSW) is presented. Firstly, wavelength-division-multiplexing and optical code-division multiple-access (WDM/OCDMA) scheme are configured to meet the various geographical locations requirement between optical network unit (ONU) and optical line terminal (OLT). The AWG-base optical switch is designed and viewed as central star-mesh topology to prohibit/decrease the duplicated redundant elements such as fiber and transceiver as well. Hence, by simple monitoring and routing switch algorithm, random fault-recovery capacity is achieved over bi-directional (up/downstream) WDM/OCDMA scheme. When error of distribution fiber (DF) takes place or bit-error-rate (BER) is higher than 10-9 requirement, the primary/slave AWG-based OSW are adjusted and controlled dynamically to restore the affected ONU groups via the other working DFs immediately.

Keywords: Random fault recovery mechanism, Array-waveguide-grating based optical switch (AWG- based OSW), wavelength-division-multiplexing and optical code-divisionmultiple-access (WDM/ OCDMA)

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Authors: Ricardo A. Martins, Matheus S. da Silva, Gabriel H. F. Iarossi, Helen C. M. Senefonte, Cinthyan R. S. C. de Barbosa

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This paper is the development of a concept of the man/robot interaction. More accurately in developing of an autistic child that have more troubles with interaction, here offers an efficient solution, even though simple; however, less studied for this public. This concept is based on code applied thought out the Lego NXT kit, built for the interpretation of the robot, thereby can create this interaction in a constructive way for children suffering with Autism.

Keywords: Lego NXT, autism, ANN (Artificial Neural Network), Backpropagation.

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Authors: Y. Wang, H. Fukuda, A. Ozaki, H. Sato

Abstract:

In this study, we discussed the effects on the thermal comfort of super high-rise residences that how effected by the high thermal capacity structural components. We considered different building orientations, structures, and insulation methods. We used the dynamic simulation software THERB (simulation of the thermal environment of residential buildings). It can estimate the temperature, humidity, sensible temperature, and heating/cooling load for multiple buildings. In the past studies, we examined the impact of air-conditioning loads (hereinafter referred to as AC loads) on the interior structural parts and the AC-usage patterns of super-high-rise residences. Super-high-rise residences have more structural components such as pillars and beams than do ordinary apartment buildings. The skeleton is generally made of concrete and steel, which have high thermal-storage capacities. The thermal-storage capacity of super-high-rise residences is considered to have a larger impact on the AC load and thermal comfort than that of ordinary residences. We show that the AC load of super-high-rise units would be reduced by installing insulation on the surfaces of interior walls that are not usually insulated in Japan.

Keywords: High-rise Residences, AC Load, Thermal Comfort, Thermal Storage, Insulation Patterns

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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Authors: F. A. M. Safwan, H. N. N. Dilrukshi, P. U. S. Peiris

Abstract:

Less availability of high quality green forages leads to low productivity of national dairy herd of Sri Lanka. Growing grass and fodder to suit the production system is an efficient and economical solution for this problem. CO-3 is placed in a higher category, especially on tillering capacity, green forage yield, regeneration capacity, leaf to stem ratio, high crude protein content, resistance to pests and diseases and free from adverse factors along with other fodder varieties grown within the country. An experiment was designed to determine the effect of organic sheep manure, inorganic fertilizers and liquid sheep manure on growth, yield and nutritive value of CO-3. The study was consisted with three treatments; sheep manure (T1), recommended inorganic fertilizers (T2) and liquid sheep manure (T3) which was prepared using bucket fermentation method and each treatment was consisted with three replicates and those were assigned randomly. First harvest was obtained after 40 days of plant establishment and number of leaves (NL), leaf area (LA), tillering capacity (TC), fresh weight (FW) and dry weight (DW) were recorded and second harvest was obtained after 30 days of first harvest and same set of data were recorded. SPSS 16 software was used for data analysis. For proximate analysis AOAC, 2000 standard methods were used. Results revealed that the plants treated with T1 recorded highest NL, LA, TC, FW and DW and were statistically significant at first and second harvest of CO-3 (p˂ 0.05) and it was found that T1 was statistically significant from T2 and T3. Although T3 was recorded higher than the T2 in almost all growth parameters; it was not statistically significant (p ˃0.05). In addition, the crude protein content was recorded highest in T1 with the value of 18.33±1.61 and was lowest in T2 with the value of 10.82±1.14 and was statistically significant (p˂ 0.05). Apart from this, other proximate composition crude fiber, crude fat, ash, moisture content and dry matter were not statistically significant between treatments (p ˃0.05). In accordance with the results, it was found that the organic fertilizer is the best fertilizer for CO-3 in terms of growth parameters and crude protein content.

Keywords: Fertilizer, growth parameters, Hybrid Napier CO-3, proximate composition.

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