Plasmodium Vivax Malaria Transmission in a Network of Villages

Malaria is a serious, acute and chronic relapsing infection to humans. It is characterized by periodic attacks of chills, fever, nausea, vomiting, back pain, increased sweating anemia, splenomegaly (enlargement of the spleen) and often-fatal complications.The malaria disease is caused by the multiplication of protozoa parasite of the genus Plasmodium. Malaria in humans is due to 4 types of malaria parasites such that Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale. P.vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax malaria can experience relapses of the disease. Between the relapses, the malaria parasite will remain dormant in the liver of the patient, leading to the patient being classified as being in the dormant class. A mathematical model for the transmission of P. vivax is developed in which the human population is divided into four classes, the susceptible, the infected, the dormant and the recovered. In this paper, we formulate the dynamical model of P. vivax malaria to see the distribution of this disease at the district level.

Shear Strengthening of RC T Beam using CFRP Laminate: A Review

This paper presents the Literature Review of carbon fiber reinforced polymer (CFRP) strips to reinforced concrete (RC) as a strengthening solution for T-beams. Although a great deal of research has been carried out on Rectangular beams strengthened with Fibre-Reinforced Polymer composites (FRP), Fiber reinforced polymer (FRP) composites have been increasingly studied for their application in the flexural or shear strengthening of reinforced concrete (RC) members. A detailed discussion of the shearstrengthening repair with FRP is undertaken. This paper will be limited to research of CFRP material externally bonded to the tensile face of concrete beams. In particular, research studying the effect of externally applied CFRP materials on the shear performance of reinforced concrete beams will be reported.

Production of Apricot Vinegar Using an Isolated Acetobacter Strain from Iranian Apricot

Vinegar or sour wine is a product of alcoholic and subsequent acetous fermentation of sugary precursors derived from several fruits or starchy substrates. This delicious food additive and supplement contains not less than 4 grams of acetic acid in 100 cubic centimeters at 20°C. Among the large number of bacteria that are able to produce acetic acid, only few genera are used in vinegar industry most significant of which are Acetobacter and Gluconobacter. In this research we isolated and identified an Acetobacter strain from Iranian apricot, a very delicious and sensitive summer fruit to decay, we gathered from fruit's stores in Isfahan, Iran. The main culture media we used were Carr, GYC, Frateur and an industrial medium for vinegar production. We isolated this strain using a novel miniature fermentor we made at Pars Yeema Biotechnologists Co., Isfahan Science and Technology Town (ISTT), Isfahan, Iran. The microscopic examinations of isolated strain from Iranian apricot showed gram negative rods to cocobacilli. Their catalase reaction was positive and oxidase reaction was negative and could ferment ethanol to acetic acid. Also it showed an acceptable growth in 5%, 7% and 9% ethanol concentrations at 30°C using modified Carr media after 24, 48 and 96 hours incubation respectively. According to its tolerance against high concentrations of ethanol after four days incubation and its high acetic acid production, 8.53%, after 144 hours, this strain could be considered as a suitable industrial strain for a production of a new type of vinegar, apricot vinegar, with a new and delicious taste. In conclusion this is the first report of isolation and identification of an Acetobacter strain from Iranian apricot with a very good tolerance against high ethanol concentrations as well as high acetic acid productivity in an acceptable incubation period of time industrially. This strain could be used in vinegar industry to convert apricot spoilage to a beneficiary product and mentioned characteristics have made it as an amenable strain in food and agricultural biotechnology.

Research Topic Map Construction

While the explosive increase in information published on the Web, researchers have to filter information when searching for conference related information. To make it easier for users to search related information, this paper uses Topic Maps and social information to implement ontology since ontology can provide the formalisms and knowledge structuring for comprehensive and transportable machine understanding that digital information requires. Besides enhancing information in Topic Maps, this paper proposes a method of constructing research Topic Maps considering social information. First, extract conference data from the web. Then extract conference topics and the relationships between them through the proposed method. Finally visualize it for users to search and browse. This paper uses ontology, containing abundant of knowledge hierarchy structure, to facilitate researchers getting useful search results. However, most previous ontology construction methods didn-t take “people" into account. So this paper also analyzes the social information which helps researchers find the possibilities of cooperation/combination as well as associations between research topics, and tries to offer better results.

Effective Personal Knowledge Management: A Proposed Online Framework

This paper presents an analytical framework for an effective online personal knowledge management (PKM) of knowledge workers. The development of this framework is prompted by our qualitative research on the PKM processes and cognitive enablers of knowledge workers in eight organisations selected from three main industries in Malaysia. This multiple-case research identifies the relationships between the effectiveness of four online PKM processes: get/retrieve, understand/analyse, share, and connect. It also establishes the importance of cognitive enablers that mediate this relationship, namely, method, identify, decide and drive. Qualitative analysis is presented as the findings, supported by the preceded quantitative analysis on an exploratory questionnaire survey.

Effects of Energy Consumption on Indoor Air Quality

Continuous measurements and multivariate methods are applied in researching the effects of energy consumption on indoor air quality (IAQ) in a Finnish one-family house. Measured data used in this study was collected continuously in a house in Kuopio, Eastern Finland, during fourteen months long period. Consumption parameters measured were the consumptions of district heat, electricity and water. Indoor parameters gathered were temperature, relative humidity (RH), the concentrations of carbon dioxide (CO2) and carbon monoxide (CO) and differential air pressure. In this study, self-organizing map (SOM) and Sammon's mapping were applied to resolve the effects of energy consumption on indoor air quality. Namely, the SOM was qualified as a suitable method having a property to summarize the multivariable dependencies into easily observable two-dimensional map. Accompanying that, the Sammon's mapping method was used to cluster pre-processed data to find similarities of the variables, expressing distances and groups in the data. The methods used were able to distinguish 7 different clusters characterizing indoor air quality and energy efficiency in the study house. The results indicate, that the cost implications in euros of heating and electricity energy vary according to the differential pressure, concentration of carbon dioxide, temperature and season.

Human-s Anthropological Appearance in Abai Kunanbayev-s Works

The issue of human anthropology took an important role in the last epochs and still hasn-t lost its importance. Scientists of different countries were interested in investigating the appearance of human being and the idea of life after death. While writing this article we noticed that scientists who made research in this issue, despite of the different countries and different epochs in which they lived, had similarities in their opinions. In given article we wrote great Kazakh poet AbaiKunanbayev-s philosophical view to the problem of human anthropology.

6DSpaces: Multisensory Interactive Installations

Interactive installations for public spaces are a particular kind of interactive systems, the design of which has been the subject of several research studies. Sensor-based applications are becoming increasingly popular, but the human-computer interaction community is still far from reaching sound, effective large-scale interactive installations for public spaces. The 6DSpaces project is described in this paper as a research approach based on studying the role of multisensory interactivity and how it can be effectively used to approach people to digital, scientific contents. The design of an entire scientific exhibition is described and the result was evaluated in the real world context of a Science Centre. Conclusions bring insight into how the human-computer interaction should be designed in order to maximize the overall experience.

Comparison of the Music Sound System between Thailand and Vietnam

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.

Integrating Visual Modeling throughout the Computer Science Curriculum

The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors- and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors- experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.

A Search Algorithm for Solving the Economic Lot Scheduling Problem with Reworks under the Basic Period Approach

In this study, we are interested in the economic lot scheduling problem (ELSP) that considers manufacturing of the serviceable products and remanufacturing of the reworked products. In this paper, we formulate a mathematical model for the ELSP with reworks using the basic period approach. In order to solve this problem, we propose a search algorithm to find the cyclic multiplier ki of each product that can be cyclically produced for every ki basic periods. This research also uses two heuristics to search for the optimal production sequence of all lots and the optimal time length of the basic period so as to minimize the average total cost. This research uses a numerical example to show the effectiveness of our approach.

Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Hybrid GA Tuned RBF Based Neuro-Fuzzy Controller for Robotic Manipulator

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function based Neuro-Fuzzy rule base knowledge is not required. Hybrid Genetic Algorithm with generalized Pattern Search is used for tuning weights of radial basis function based Neuro- fuzzy controller. All the controllers are checked for butterfly trajectory tracking and results in the form of Cartesian and joint space errors are being compared. ANFIS based controller is showing better performance compared to Radial Basis Function based Neuro-Fuzzy Controller but rule base independency of RBF based Neuro-Fuzzy gives it an edge over ANFIS

Removal of Heavy Metals from Wastewater by Adsorption and Membrane Processes: a Comparative Study

This research aimed at investigating the Cr (III), Cd (II) and Pb (II) removal efficiencies by using the newly synthesized metal oxides/ polyethersulfone (PES), Al2O3/PES and ZrO2/PES, membranes from synthetic wastewater and exploring fouling mechanisms. A Comparative study between the removal efficiencies of Cr (III), Cd (II) and Pb (II) from synthetic and natural wastewater by using adsorption onto agricultural by products and the newly synthesized Al2O3/PES and ZrO2/PES membranes was conducted to assess the advantages and limitations of using the metal oxides/PES membranes for heavy metals removal. The results showed that about 99 % and 88 % removal efficiencies were achieved by the tested membranes for Pb (II) and Cr (III), respectively.

Social Networks and Absorptive Capacity

The resource-based view of the firm regards knowledge as one of the most important organizational assets and a key strategic resource that contributes unique value to organizations. The acquisition, absorption and internalization of external knowledge are central to an organization-s innovative capabilities. This ability to evaluate, acquire and integrate new knowledge from its environment is referred to as a firm-s absorptive capacity (AC). This research in progress paper explores the link between interorganizational Social Networks (SNs) and a firm-s Absorptive Capacity (AC). Based on an in-depth literature survey of both concepts, four propositions are proposed that explain the link between AC and SNs. These propositions suggest that SNs are key to a firm-s AC. A qualitative research method is proposed to test the set of propositions in the next stage of this research.

Evaluation of the Possible Effect of Gender, Age and Duration of Diabetes on the Serum Zinc Levels of Diabetic Patients in Murzuk Area-Libya

The aim of this study was to demonstrate the possible effect of some variables such as age, gender, blood sugar level, and duration of diabetes on the serum level of zinc in diabetic individuals from Murzuk area. Serum zinc (Zn), Fasting blood sugar (FBS), hemoglobin HbA1c (HbA1c) were evaluated in 46 type I diabetic subjects (group 1), 48 type II diabetic subjects (group 2) and 43 healthy individuals (control) of both genders aged (30-81) years. Data showed that both diabetic groups have significantly higher (P0.05) differences in serum Zn levels were observed between Males and Females. Serum Zn levels were non-significantly decreased with increasing age. In type II diabetic subjects, serum Zn levels were non-significantly decreased with increasing duration of disease whereas those in type I were non-significantly increased.

Leaching of Mineral Nitrogen and Phosphate from Rhizosphere Soil Stressed by Drought and Intensive Rainfall

This work presents the first results from the long-term experiment, which is focused on the impact of intensive rainfall and long period of drought on microbial activities in soil. Fifteen lysimeters were prepared in the area of our interest. This area is a protection zone of underground source of drinking water. These lysimeters were filed with topsoil and subsoil collected in this area and divided into two groups. These groups differ in fertilization and amount of water received during the growing season. Amount of microbial biomass and leaching of mineral nitrogen and phosphates were chosen as main indicators of microbial activities in soil. Content of mineral nitrogen and phosphates was measured in soil solution, which was collected from each lysimeters. Amount of microbial biomass was determined in soil samples that were taken from the lysimeters before and after the long period of drought and intensive rainfall.

Vessel Inscribed Trigonometry to Measure the Vessel Progressive Orientations in the Digital Fundus Image

In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.

The Effect of the National Culture on the International Business

The aim for this research is to deliberately discuss how and why the contexts of culture are the main significant factors which need to be considered when conducting the international business oversea. As a consequence of understanding these various factors, the researcher would be able to infer some suggestions to the international organizations. With this in mind, the results of the understanding in a national culture environment can support the organizations to settle its international strategies which may be useful to develop the national export and import effectiveness. This data collecting methods will be concentrated upon 5-10 interviews from the senior members and business officers in the international company in Thailand by e-mail interview and analyses the individual manager’s viewpoint. As well as, focus on the questionnaires which the respondents were selected randomly around 100 samples from UK and Thailand, together with providing a functional sample size and comparable to data. The results of the study question the role of national culture, which contributed to in international business effectiveness and emphasize the positive and negative aspects, as well as suggestions to business investors are informed.

Development of Neural Network Prediction Model of Energy Consumption

In the oil and gas industry, energy prediction can help the distributor and customer to forecast the outgoing and incoming gas through the pipeline. It will also help to eliminate any uncertainties in gas metering for billing purposes. The objective of this paper is to develop Neural Network Model for energy consumption and analyze the performance model. This paper provides a comprehensive review on published research on the energy consumption prediction which focuses on structures and the parameters used in developing Neural Network models. This paper is then focused on the parameter selection of the neural network prediction model development for energy consumption and analysis on the result. The most reliable model that gives the most accurate result is proposed for the prediction. The result shows that the proposed neural network energy prediction model is able to demonstrate an adequate performance with least Root Mean Square Error.