Nonlinear Modeling and Analysis of AAC infilled Sandwich Panels for out of Plane Loads

Sandwich panels are widely used in the construction industry for their ease of assembly, light weight and efficient thermal performance. They are composed of two RC thin outer layers separated by an insulating inner layer. In this research the inner insulating layer is made of lightweight Autoclaved Aerated Concrete (AAC) blocks which has good thermal insulation properties and yet possess reasonable mechanical strength. The shear strength of the AAC infill is relied upon to replace the traditionally used insulating foam and to provide the shear capacity of the panel. A comprehensive experimental program was conducted on full scale sandwich panels subjected to bending. In this paper, detailed numerical modeling of the tested sandwich panels is reported. Nonlinear 3-D finite element modeling of the composite action of the sandwich panel is developed using ANSYS. Solid elements with different crashing and cracking capabilities and different constitutive laws were selected for the concrete and the AAC. Contact interface elements are used in this research to adequately model the shear transfer at the interface between the different layers. The numerical results showed good correlation with the experimental ones indicating the adequacy of the model in estimating the loading capacity of panels.

An Experimental Study on Autoignition of Wood

Experiments were conducted to characterize fire properties of wood exposed to the certain external heat flux and under variety of wood moisture content. Six kinds of Indonesian wood: keruing, sono, cemara, kamper, pinus, and mahoni were exposed to radiant heat from a conical heater, result in appearance of a stable flame on the wood surface caused by spontaneous ignition. A thermocouple K-type was used to measure the wood surface temperature. Temperature histories were recorded throughout each experiment at 1 s intervals using a TC-08. Data of first ignition time and temperature, end ignition time and temperature, and charring rate have been successfully collected. It was found that the ignition temperature and charring rate depend on moisture content of wood.

Patents Analysis and Design Suggestions for the Mandibular Advancement Devices

Snoring is prevalent and is the most significant feature of sleep-disordered breathing (SDB). Ignore the therapies of SDB will lead to serious problems in health. Based on the research of mechanisms, diagnosis, and treatments of snoring, oral appliances are ensured in therapeutic effect and compliance, especially the mandibular advancement devices (MADs). Market survey includes commercial product reviews and patent analyses. Due to pay more attention to the sleep medicine, the oral appliances are considered as a standard treatment of snoring that promoted by American Academy of Sleep Medicine (AASM). There are more and more adjustable MADs developed since 1995. According to the patent analyses, there are many drawbacks existed in the present design, such as uncomfortable, high cost, bulky volume, and complex adjustment. In this study, several new designs of the MAD are proposed.

The Evaluation and Application of FMEA in Sepahan Oil Co

Failure modes and effects analysis (FMEA) is an effective technique for preventing potential problems and actions needed to error cause removal. On the other hand, the oil producing companies paly a critical role in the oil industry of Iran as a developing country out of which, Sepahan Oil Co. has a considerable contribution. The aim of this research is to show how FMEA could be applied and improve the quality of products at Sepahan Oil Co. For this purpose, the four liter production line of the company has been selected for investigation. The findings imply that the application of FMEA has reduced the scraps from 50000 ppm to 5000 ppm and has resulted in a 0.92 percent decrease of the oil waste.

Curvature Ductility Factor of Rectangular Sections Reinforced Concrete Beams

The present work presents a method of calculating the ductility of rectangular sections of beams considering nonlinear behavior of concrete and steel. This calculation procedure allows us to trace the curvature of the section according to the bending moment, and consequently deduce ductility. It also allowed us to study the various parameters that affect the value of the ductility. A comparison of the effect of maximum rates of tension steel, adopted by the codes, ACI [1], EC8 [2] and RPA [3] on the value of the ductility was made. It was concluded that the maximum rate of steels permitted by the ACI [1] codes and RPA [3] are almost similar in their effect on the ductility and too high. Therefore, the ductility mobilized in case of an earthquake is low, the inverse of code EC8 [2]. Recommendations have been made in this direction.

Efficient and Extensible Data Processing Framework in Ubiquitious Sensor Networks

This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.

Removal of Methylene Blue Dye Using Roselle Petals from Aqueous Solutions

The present study based on removal of natural dyes of Roselle petals, then used Roselle petals powder (RPP) as an adsorbent for the removal of methylene blue dye (as a typical cationic or basic dye) from aqueous solutions. The present study shows that used Roselle petals powder exhibit adsorption trend for the dye. The adsorption processes were carried out at various conditions of temperatures ranging from 278 to 338 K ± 2 K , concentrations, processing time and a wide range of pH between 2.5-11. Adsorption isotherm equations such as Freundlich, and Langmuir were applied to calculate the values of respective constants. Adsorption study was found that the currently introduced adsorbent can be used to remove cationic dyes such as methylene blue from aqueous solutions.

Object Detection based Weighted-Center Surround Difference

Intelligent traffic surveillance technology is an issue in the field of traffic data analysis. Therefore, we need the technology to detect moving objects in real-time while there are variations in background and natural light. In this paper, we proposed a Weighted-Center Surround Difference method for object detection in outdoor environments. The proposed system detects objects using the saliency map that is obtained by analyzing the weight of each layers of Gaussian pyramid. In order to validate the effectiveness of our system, we implemented the proposed method using a digital signal processor, TMS320DM6437. Experimental results show that blurred noisy around objects was effectively eliminated and the object detection accuracy is improved.

Energy Efficient Reliable Cooperative Multipath Routing in Wireless Sensor Networks

In this paper, a reliable cooperative multipath routing algorithm is proposed for data forwarding in wireless sensor networks (WSNs). In this algorithm, data packets are forwarded towards the base station (BS) through a number of paths, using a set of relay nodes. In addition, the Rayleigh fading model is used to calculate the evaluation metric of links. Here, the quality of reliability is guaranteed by selecting optimal relay set with which the probability of correct packet reception at the BS will exceed a predefined threshold. Therefore, the proposed scheme ensures reliable packet transmission to the BS. Furthermore, in the proposed algorithm, energy efficiency is achieved by energy balancing (i.e. minimizing the energy consumption of the bottleneck node of the routing path) at the same time. This work also demonstrates that the proposed algorithm outperforms existing algorithms in extending longevity of the network, with respect to the quality of reliability. Given this, the obtained results make possible reliable path selection with minimum energy consumption in real time.

Analytical Model Based Evaluation of Human Machine Interfaces Using Cognitive Modeling

Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Effect of Na2O Content on Durability of Geopolymer Mortars in Sulphuric Acid

This paper presents the findings of an experimental investigation to study the effect of alkali content in geopolymer mortar specimens exposed to sulphuric acid. Geopolymer mortar specimens were manufactured from Class F fly ash by activation with a mixture of sodium hydroxide and sodium silicate solution containing 5% to 8% Na2O. Durability of specimens were assessed by immersing them in 10% sulphuric acid solution and periodically monitoring surface deterioration and depth of dealkalization, changes in weight and residual compressive strength over a period of 24 weeks. Microstructural changes in the specimens were studied with Scanning electron microscopy (SEM) and EDAX. Alkali content in the activator solution significantly affects the durability of fly ash based geopolymer mortars in sulphuric acid. Specimens manufactured with higher alkali content performed better than those manufactured with lower alkali content. After 24 weeks in sulphuric acid, specimen with 8% alkali still recorded a residual strength as high as 55%.

An Owl Ontology for Commonkads Template Knowledge Models

This paper gives an overview of how an OWL ontology has been created to represent template knowledge models defined in CML that are provided by CommonKADS. CommonKADS is a mature knowledge engineering methodology which proposes the use of template knowledge model for knowledge modelling. The aim of developing this ontology is to present the template knowledge model in a knowledge representation language that can be easily understood and shared in the knowledge engineering community. Hence OWL is used as it has become a standard for ontology and also it already has user friendly tools for viewing and editing.

Multi Switched Split Vector Quantization of Narrowband Speech Signals

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization (MSSVQ), which is a hybrid of Multi, switched, split vector quantization techniques. The spectral distortion performance, computational complexity, and memory requirements of MSSVQ are compared to split vector quantization (SVQ), multi stage vector quantization(MSVQ) and switched split vector quantization (SSVQ) techniques. It has been proved from results that MSSVQ has better spectral distortion performance, lower computational complexity and lower memory requirements when compared to all the above mentioned product code vector quantization techniques. Computational complexity is measured in floating point operations (flops), and memory requirements is measured in (floats).

A Framework for Product Development Process including HW and SW Components

This paper proposes a framework for product development including hardware and software components. It provides separation of hardware dependent software, modifications of current product development process, and integration of software modules with existing product configuration models and assembly product structures. In order to decide the dependent software, the framework considers product configuration modules and engineering changes of associated software and hardware components. In order to support efficient integration of the two different hardware and software development, a modified product development process is proposed. The process integrates the dependent software development into product development through the interchanges of specific product information. By using existing product data models in Product Data Management (PDM), the framework represents software as modules for product configurations and software parts for product structure. The framework is applied to development of a robot system in order to show its effectiveness.

Heterogeneous Attribute Reduction in Noisy System based on a Generalized Neighborhood Rough Sets Model

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Determination of Moisture Content and Liquid Limit of Foundations Soils, using Microwave Radiation, in the Different Locations of Sulaimani Governorate, Kurdistan Region-Iraq

Soils are normally dried in either a convection oven or stove. Laboratory moisture content testing indicated that the typical drying durations for a convection oven were, 24 hours. The purpose of this study was to determine the accuracy and soil drying duration of both, moisture content and liquid limit using microwave radiation. The soils were tested with both, convection and microwave ovens. The convection oven was considered to produce the true values for both, natural moisture content and liquid limit of soils; it was, therefore, used as a basis for comparison for the results of the microwave ovens. The samples used in this study were obtained from different projects of Consulting Engineering Bureau of College of Engineering of Sulaimani University. These samples were collected from different locations and at the different depths and consist mostly of brown and light brown clay and silty clay. A total of 102 samples were prepared. 26 of them were tested for natural moisture determination, while the other 76 were used for liquid limits determination

Electrical Performance of a Solid Oxide Fuel Cell Unit with Non-Uniform Inlet Flow and High Fuel Utilization

This study investigates the electrical performance of a planar solid oxide fuel cell unit with cross-flow configuration when the fuel utilization gets higher and the fuel inlet flow are non-uniform. A software package in this study solves two-dimensional, simultaneous, partial differential equations of mass, energy, and electro-chemistry, without considering stack direction variation. The results show that the fuel utilization increases with a decrease in the molar flow rate, and the average current density decreases when the molar flow rate drops. In addition, non-uniform Pattern A will induce more severe happening of non-reaction area in the corner of the fuel exit and the air inlet. This non-reaction area deteriorates the average current density and then deteriorates the electrical performance to –7%.

Sovereign Credit Risk Measures

This paper focuses on sovereign credit risk meaning a hot topic related to the current Eurozone crisis. In the light of the recent financial crisis, market perception of the creditworthiness of individual sovereigns has changed significantly. Before the outbreak of the financial crisis, market participants did not differentiate between credit risk born by individual states despite different levels of public indebtedness. In the proceeding of the financial crisis, the market participants became aware of the worsening fiscal situation in the European countries and started to discriminate among government issuers. Concerns about the increasing sovereign risk were reflected in surging sovereign risk premium. The main of this paper is to shed light on the characteristics of the sovereign risk with the special attention paid to the mutual relation between credit spread and the CDS premium as the main measures of the sovereign risk premium.

Development of NOx Emission Model for a Tangentially Fired Acid Incinerator

This paper aims to develop a NOx emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). Malaysia DOE is actively imposing the Clean Air Regulation to mandate the installation of analytical instrumentation known as Continuous Emission Monitoring System (CEMS) to report emission level online to DOE . As a hardware based analyzer, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive technique is often preferred and considered as a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a LNG Complex. Simulated Annealing (SA) is first used to determine the initial hyperparameters which are then further optimized based on the performance of the model using Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on backpropagation neural networks (BPNN) in both training and testing data.

A New Algorithm for Cluster Initialization

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique are dependent on the initialization of cluster centers. In this article we propose a new algorithm to initialize the clusters. The proposed algorithm is based on finding a set of medians extracted from a dimension with maximum variance. The algorithm has been applied to different data sets and good results are obtained.