Modeling Cost Structure for Assessment Production Cost of Algal - Biofue

Algae-based fuel are considered a promising sources of clean energy, and because it has many advantages over traditional biofuel, research and business ventures have driven into developing and producing Algal-biofuel. But its production stages create a cost structure that it is not competitive with traditional fuels. Therefore, cost becomes the main obstacle in commercial production purpose. However, the present research which aims at using cost structure model, and designed MS-Dose program, to investigate the a mount of production cost and determined the parameter had great effect on it, second to measured the amount of contribution rate of algae in process the pollution by capturing Co2 from air . The result generated from the model shows that the production cost of biomass is between $0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than cost of other studies, while gallon costs between $3.4 - 3.5, more than traditional sources of oil about $1 ,which regarded as a rate of contribution of algal in capturing CO2 from air.

Multidimensional and Data Mining Analysis for Property Investment Risk Analysis

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Structure and Magnetic Properties of Nanocomposite Fe2O3/TiO2 Catalysts Fabricated by Heterogeneous Precipitation

The aim of our work is to study phase composition, particle size and magnetic response of Fe2O3/TiO2 nanocomposites with respect to the final annealing temperature. Those nanomaterials are considered as smart catalysts, separable from a liquid/gaseous phase by applied magnetic field. The starting product was obtained by an ecologically acceptable route, based on heterogeneous precipitation of the TiO2 on modified g-Fe2O3 nanocrystals dispersed in water. The precursor was subsequently annealed on air at temperatures ranging from 200 oC to 900 oC. The samples were investigated by synchrotron X-ray powder diffraction (S-PXRD), magnetic measurements and Mössbauer spectroscopy. As evidenced by S-PXRD and Mössbauer spectroscopy, increasing the annealing temperature causes evolution of the phase composition from anatase/maghemite to rutile/hematite, finally above 700 oC the pseudobrookite (Fe2TiO5) also forms. The apparent particle size of the various Fe2O3/TiO2 phases has been determined from the highquality S-PXRD data by using two different approaches: the Rietveld refinement and the Debye method. Magnetic response of the samples is discussed in considering the phase composition and the particle size.

Visual Attention Analysis on Mutated Brand Name using Eye-Tracking: A Case Study

Brand name plays a vital role for in-shop buying behavior of consumers and mutated brand name may affect the selling of leading branded products. In Indian market, there are many products with mutated brand names which are either orthographically or phonologically similar. Due to presence of such products, Indian consumers very often fall under confusion when buying some regularly used stuff. Authors of the present paper have attempted to demonstrate relationship between less attention and false recognition of mutated brand names during a product selection process. To achieve this goal, visual attention study was conducted on 15 male college students using eye-tracker against a mutated brand name and errors in recognition were noted using questionnaire. Statistical analysis of the acquired data revealed that there was more false recognition of mutated brand name when less attention was paid during selection of favorite product. Moreover, it was perceived that eye tracking is an effective tool for analyzing false recognition of brand name mutation.

An Energy Efficient Protocol for Target Localization in Wireless Sensor Networks

Target tracking and localization are important applications in wireless sensor networks. In these applications, sensor nodes collectively monitor and track the movement of a target. They have limited energy supplied by batteries, so energy efficiency is essential for sensor networks. Most existing target tracking protocols need to wake up sensors periodically to perform tracking. Some unnecessary energy waste is thus introduced. In this paper, an energy efficient protocol for target localization is proposed. In order to preserve energy, the protocol fixes the number of sensors for target tracking, but it retains the quality of target localization in an acceptable level. By selecting a set of sensors for target localization, the other sensors can sleep rather than periodically wake up to track the target. Simulation results show that the proposed protocol saves a significant amount of energy and also prolongs the network lifetime.

Development of Indwelling Wireless pH Telemetry of Intraoral Acidity

As the increase of intraoral acidity due to ingestion of sweet foods and acidic beverages usually bring forth a dental caries and a erosion, the measurement of intraoral pH is essential in the study of oral environment. The indwelling intraoral pH telemetry for lasting longer than 24 hours in the mouth was developed to overcome the limits of conventional wire electrode method previously used for salivary and plaque pH measurement, and to assess its effectiveness.

Rigorous Electromagnetic Model of Fourier Transform Infrared (FT-IR) Spectroscopic Imaging Applied to Automated Histology of Prostate Tissue Specimens

Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that provides both chemically and spatially resolved information. The rich chemical content of data may be utilized for computer-aided determinations of structure and pathologic state (cancer diagnosis) in histological tissue sections for prostate cancer. FT-IR spectroscopic imaging of prostate tissue has shown that tissue type (histological) classification can be performed to a high degree of accuracy [1] and cancer diagnosis can be performed with an accuracy of about 80% [2] on a microscopic (≈ 6μm) length scale. In performing these analyses, it has been observed that there is large variability (more than 60%) between spectra from different points on tissue that is expected to consist of the same essential chemical constituents. Spectra at the edges of tissues are characteristically and consistently different from chemically similar tissue in the middle of the same sample. Here, we explain these differences using a rigorous electromagnetic model for light-sample interaction. Spectra from FT-IR spectroscopic imaging of chemically heterogeneous samples are different from bulk spectra of individual chemical constituents of the sample. This is because spectra not only depend on chemistry, but also on the shape of the sample. Using coupled wave analysis, we characterize and quantify the nature of spectral distortions at the edges of tissues. Furthermore, we present a method of performing histological classification of tissue samples. Since the mid-infrared spectrum is typically assumed to be a quantitative measure of chemical composition, classification results can vary widely due to spectral distortions. However, we demonstrate that the selection of localized metrics based on chemical information can make our data robust to the spectral distortions caused by scattering at the tissue boundary.

Effects of Length of Time of Fasting upon Subjective and Objective Variables When Controlling Sleep, Food and Fluid Intakes

Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance. A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.

Studying Effects of Alternative Biodiesel Fuel in Performance and Pollutants of Diesel Engines

Since injection engines have a considerable portion, in consumption of energy and environmental pollution, using an alternative source of energy with lower pollutant effects in this regard is necessary. Biodiesel fuel is a suitable alternative for gasoline in diesel engines. In this research the property of biodiesel, the function and the pollution effects of diesel engine, when using 100% biodiesel, using 100% gasoline and mixing ratio of both fuels for comparing them, have been investigated. The researches have shown, using biodiesel fuel in prevalent diesel engine, will reduce the pollutants such as Co, half burned carbohydrate and suspended particles and a little increase in oxidation will achieve while power consumption, particularly fuel and thermal efficiency of diesel fuel has the same.

Effect of Endplate Shape on Performance and Stability of Wings-in Ground (WIG) Craft

Numerical analysis for the aerodynamic characteristics of the WIG (wing-in ground effect) craft with highly cambered and aspect ratio of one is performed to predict the ground effect for the case of with- and without- lower-extension endplate. The analysis is included varying angles of attack from 0 to10 deg. and ground clearances from 5% of chord to 50%. Due to the ground effect, the lift by rising in pressure on the lower surface is increased and the influence of wing-tip vortices is decreased. These two significant effects improve the lift-drag ratio. On the other hand, the endplate prevents the high-pressure air escaping from the air cushion at the wing tip and causes to increase the lift and lift-drag ratio further. It is found from the visualization of computation results that two wing-tip vortices are generated from each surface of the wing tip and their strength are weak and diminished rapidly. Irodov-s criteria are also evaluated to investigate the static height stability. The comparison of Irodov-s criteria shows that the endplate improves the deviation of the static height stability with respect to pitch angles and heights. As the results, the endplate can improve the aerodynamic characteristics and static height stability of wings in ground effect, simultaneously.

An Improved Data Mining Method Applied to the Search of Relationship between Metabolic Syndrome and Lifestyles

A data cutting and sorting method (DCSM) is proposed to optimize the performance of data mining. DCSM reduces the calculation time by getting rid of redundant data during the data mining process. In addition, DCSM minimizes the computational units by splitting the database and by sorting data with support counts. In the process of searching for the relationship between metabolic syndrome and lifestyles with the health examination database of an electronics manufacturing company, DCSM demonstrates higher search efficiency than the traditional Apriori algorithm in tests with different support counts.

Modeling Ambient Carbon Monoxide Pollutant Due to Road Traffic

Rapid urbanization, industrialization and population growth have led to an increase in number of automobiles that cause air pollution. It is estimated that road traffic contributes 60% of air pollution in urban areas. A case by case assessment is required to predict the air quality in urban situations, so as to evolve certain traffic management measures to maintain the air quality levels with in the tolerable limits. Calicut city in the state of Kerala, India has been chosen as the study area. Carbon Monoxide (CO) concentration was monitored at 15 links in Calicut city and air quality performance was evaluated over each link. The CO pollutant concentration values were compared with the National Ambient Air Quality Standards (NAAQS), and the CO values were predicted by using CALINE4 and IITLS and Linear regression models. The study has revealed that linear regression model performs better than the CALINE4 and IITLS models. The possible association between CO pollutant concentration and traffic parameters like traffic flow, type of vehicle, and traffic stream speed was also evaluated.

Ontology-based Concept Weighting for Text Documents

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas.

Partial 3D Reconstruction using Evolutionary Algorithms

When reconstructing a scenario, it is necessary to know the structure of the elements present on the scene to have an interpretation. In this work we link 3D scenes reconstruction to evolutionary algorithms through the vision stereo theory. We consider vision stereo as a method that provides the reconstruction of a scene using only a couple of images of the scene and performing some computation. Through several images of a scene, captured from different positions, vision stereo can give us an idea about the threedimensional characteristics of the world. Vision stereo usually requires of two cameras, making an analogy to the mammalian vision system. In this work we employ only a camera, which is translated along a path, capturing images every certain distance. As we can not perform all computations required for an exhaustive reconstruction, we employ an evolutionary algorithm to partially reconstruct the scene in real time. The algorithm employed is the fly algorithm, which employ “flies" to reconstruct the principal characteristics of the world following certain evolutionary rules.

Development of a Water-Jet Assisted Underwater Laser Cutting Process

We present the development of a new underwater laser cutting process in which a water-jet has been used along with the laser beam to remove the molten material through kerf. The conventional underwater laser cutting usually utilizes a high pressure gas jet along with laser beam to create a dry condition in the cutting zone and also to eject out the molten material. This causes a lot of gas bubbles and turbulence in water, and produces aerosols and waste gas. This may cause contamination in the surrounding atmosphere while cutting radioactive components like burnt nuclear fuel. The water-jet assisted underwater laser cutting process produces much less turbulence and aerosols in the atmosphere. Some amount of water vapor bubbles is formed at the laser-metal-water interface; however, they tend to condense as they rise up through the surrounding water. We present the design and development of a water-jet assisted underwater laser cutting head and the parametric study of the cutting of AISI 304 stainless steel sheets with a 2 kW CW fiber laser. The cutting performance is similar to that of the gas assist laser cutting; however, the process efficiency is reduced due to heat convection by water-jet and laser beam scattering by vapor. This process may be attractive for underwater cutting of nuclear reactor components.

Contributory Factors to Diabetes Dietary Regimen Non Adherence in Adults with Diabetes

A cross sectional survey design was used to collect data from 370 diabetic patients. Two instruments were used in obtaining data; in-depth interview guide and researchers- developed questionnaire. Fisher's exact test was used to investigate association between the identified factors and nonadherence. Factors identified were: socio-demographic factors such as: gender, age, marital status, educational level and occupation; psychosocial obstacles such as: non-affordability of prescribed diet, frustration due to the restriction, limited spousal support, feelings of deprivation, feeling that temptation is inevitable, difficulty in adhering in social gatherings and difficulty in revealing to host that one is diabetic; health care providers obstacles were: poor attitude of health workers, irregular diabetes education in clinics , limited number of nutrition education sessions/ inability of the patients to estimate the desired quantity of food, no reminder post cards or phone calls about upcoming patient appointments and delayed start of appointment / time wasting in clinics.

Managing, Sustaining, and Future Proofing the Business of Educational Provision Following Large-Scale Disaster and Disruption

A catastrophic earthquake measuring 6.3 on the Richter scale struck the Christchurch, New Zealand Central Business District on February 22, 2012, abruptly disrupting the business of teaching and learning at Christchurch Polytechnic Institute of Technology. This paper presents the findings from a study undertaken about the complexity of delivering an educational programme in the face of this traumatic natural event. Nine interconnected themes emerged from this multiple method study: communication, decision making, leader- and follower-ship, balancing personal and professional responsibilities, taking action, preparedness and thinking ahead, all within a disruptive and uncertain context. Sustainable responses that maximise business continuity, and provide solutions to practical challenges, are among the study-s recommendations.

A Few Descriptive and Optimization Issues on the Material Flow at a Research-Academic Institution: The Role of Simulation

Lately, significant work in the area of Intelligent Manufacturing has become public and mainly applied within the frame of industrial purposes. Special efforts have been made in the implementation of new technologies, management and control systems, among many others which have all evolved the field. Aware of all this and due to the scope of new projects and the need of turning the existing flexible ideas into more autonomous and intelligent ones, i.e.: Intelligent Manufacturing, the present paper emerges with the main aim of contributing to the design and analysis of the material flow in either systems, cells or work stations under this new “intelligent" denomination. For this, besides offering a conceptual basis in some of the key points to be taken into account and some general principles to consider in the design and analysis of the material flow, also some tips on how to define other possible alternative material flow scenarios and a classification of the states a system, cell or workstation are offered as well. All this is done with the intentions of relating it with the use of simulation tools, for which these have been briefly addressed with a special focus on the Witness simulation package. For a better comprehension, the previous elements are supported by a detailed layout, other figures and a few expressions which could help obtaining necessary data. Such data and others will be used in the future, when simulating the scenarios in the search of the best material flow configurations.

Effects of Beak Trimming on Behavior and Agonistic Activity of Thai Native Pullets Raised in Floor Pens

The effect of beak trimming on behavior of two strains of Thai native pullets kept in floor pens was studied. Six general activities (standing, crouching, moving, comforting, roosting, and nesting), 6 beak related activities (preening, feeding, drinking, pecking at inedible object, feather pecking, and litter pecking), and 4 agonistic activities (head pecking, threatening, avoiding, and fighting) were measured twice a for 15 consecutive days, started when the pullets were 19 wk old. It was found that beak trimmed pullets drank more frequent (P