Search results for: constriction factor based particle swarm optimization (CPSO)

Authors: Shuen-Tai Wang, Yu-Ching Lin

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With more and more workflow systems adopting cloud as their execution environment, it presents various challenges that need to be addressed in order to be utilized efficiently. This paper introduces a method for resource provisioning based on our previous research of dynamic allocation and its pipeline processes. We present an abstraction for workload scheduling in which independent tasks get scheduled among various available processors of distributed computing for optimization. We also propose an integrated web-based workflow designer by taking advantage of the HTML5 technology and chaining together multiple tools. In order to make the combination of multiple pipelines executing on the cloud in parallel, we develop a script translator and an execution engine for workflow management in the cloud. All information is known in advance by the workflow engine and tasks are allocated according to the prior knowledge in the repository. This proposed effort has the potential to provide support for process definition, workflow enactment and monitoring of workflow processes. Users would benefit from the web-based system that allows creation and execution of pipelines without scripting knowledge.

Keywords: workflow systems, resources provisioning, workload scheduling, web-based, workflow engine

Procedia PDF Downloads 160

Authors: Kurudzirayi Robson Musikavanhu

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Nanophase particles exhibit quantum behavior by virtue of their small size, being particles of gamma to x-ray wavelength [atomic range]. Such particles exhibit high frequencies, high energy/photon, high penetration power, high ionization power [atomic behavior] and are stable at low energy levels as opposed to bulk phase matter [macro particles] which exhibit higher wavelength [radio wave end] properties, hence lower frequency, lower energy/photon, lower penetration power, lower ionizing power and are less stable at low temperatures. The ‘unique’ behavioral motion of Nano systems will remain a mystery as long as quantum theory remains a mystery, and for pharmacology, pharmacovigilance profiling of Nano systems becomes virtually impossible. Quantum theory is the 4 – 3 – 5 electromagnetic law of life and life motion systems on planet earth. Electromagnetic [wave-particle] properties of all particulate matter changes as mass [bulkiness] changes from one phase to the next [Nano-phase to micro-phase to milli-phase to meter-phase to kilometer phase etc.] and the subsequent electromagnetic effect of one phase particle on bulk matter [different phase] changes from one phase to another. All matter exhibit electromagnetic properties [wave-particle duality] in behavior and the lower the wavelength [and the lesser the bulkiness] the higher the gamma ray end properties exhibited and the higher the wavelength [and the greater the bulkiness], the more the radio-wave end properties are exhibited. Quantum theory is the 4 [moon] – 3[sun] – [earth] 5 law of the Electromagnetic spectrum [solar system]. 4 + 3 = 7; 4 + 3 + 5 = 12; 4 * 3 * 5 = 60; 42 + 32 = 52; 43 + 33 + 53 = 63. Quantum age is overdue.

Keywords: electromagnetic solar system, nano-material, nano pharmacology, pharmacovigilance, quantum theory

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Authors: Mohammad Qasim Mohammadi, Mohammad Arif Rohman

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Although socially sustainable building is becoming increasingly popular worldwide, past studies indicate that when policymakers support sustainable building development, the social dimension is often given insufficient attention or entirely disregarded. There are not many studies that focus on the problems of socially sustainable buildings in Afghanistan. This research investigates the factors that may hinder social sustainability implementation in residential building construction. The study will gather data from construction professionals by purposive sampling and employ Exploratory Factor Analysis (EFA) and Varimax for analysis. The results will undergo rigorous examination and thorough discussion. The expected results in this research will analyze the underlying barrier structure (factors) that hinder social sustainability, and each of these factors will represent a set of observed variables. In addition, the factor loadings show which barriers pose the greatest challenges. The primary goal of this study is to provide valuable insights into the impediment factors of social sustainability within the residential building environment, aiming to inform decision-making in the industry and encourage the adoption of more socially sustainable construction practices.

Keywords: social sustainability, residential building, barriers, drivers, afghanistan, factor analysis

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Authors: Khan Shahid, Shahid Zakia

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The article demonstrates how Theology and Islamic Philosophy can be illuminated and enhanced through the application of the SOUL framework (Sincere act, Optimization effort, Ultimate goal, Law compliance). The study explores historical development using a phenomenological approach and integrates the SOUL framework to enrich Theology and Islamic Philosophy. The proposed framework highlights the significance of these elements, ultimately leading to a deeper understanding of Theology and Islamic Philosophy.

Keywords: SOUL framework, illuminating human identity, theology, Islamic Philosophy, sincerity act, optimization effort, ultimate goals, law compliance

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Authors: Rachmat Mauludin, Novita R. Kusuma, Diky Mudhakir

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Famotidine (FMT) is one of used substances in the treatment of hiperacidity and peptic ulcer, administered orally and parenterally via intravenous injection. Oral administration, which is more favorable, has been reported to have many obstacles in the process of the treatment, includes decreasing the bioavailability of FMT. This research was aimed to prepare FMT in form of solid lipid nanoparticles (SLN) with size ranging between 100-200 nm. The research was carried out also by optimizing factors that may affect physical stability of SLN. Formulation of Famotidine SLN was carried out by optimizing factors, such as duration of homogenization and sonication, lipid concentration, stabilizer composition and stabilizer concentration. SLN physical stability was evaluated (particle size distribution) for 42 days in 3 diferent temperatures. Entrapment efficiency and drug loading was determined indirectly and directly. The morphology of SLN was visualized by transmission electron microscope (TEM). In vitro release study of FMT was conducted in 2 mediums, at pH of 1.2 and 7.4. Chemical stability of FMT was determined by quantifying the concentration of FMT within 42 days. Famotidin SLN consisted of GMS as lipid and poloxamer 188, lecithin, and polysorbate 80 as stabilizers. Homogenization and sonication was performed for 5 minutes and 10 minutes. Physyical stability of nanoparticles at 3 different temperatures was no significant difference. The best formula was physically stable until 42 days with mean particle size below 200 nm. Nanoparticles produced was able to entrap FMT until 86.6%. Evaluation by TEM showed that nanoparticles was spherical and solid. In medium pH of 1.2, FMT was released only 30% during 4 hour. On the other hand, within 4 hours SLN could release FMT completely in medium pH of 7.4. The FMT concentration in nanoparticles dispersion was maintained until 95% in 42 days (40oC, RH 75%). Famotidine SLN was able to be produced with mean particle size ranging between 100-200 nm and physically stable for 42 days. SLN could be loaded by 86,6% of FMT. Morphologically, obtained SLN was spheric and solid. During 4 hours in medium pH of 1.2 and 7.4, FMT was released until 30% and 100%, respectively.

Keywords: solid lipid nanoparticle (SLN), famotidine (FMT), physicochemical properties, release study

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Authors: Veronique Jubera, Ka-Young Kim, U-Chan Chung, Amelie Veillere, Jean-Marc Heintz

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Emitting materials and all solid state lasers are widely used in the field of optical applications and materials science as a source of excitement, instrumental measurements, medical applications, metal shaping etc. Recently promising optical efficiencies were recorded on ceramics which result from a cheaper and faster ways to obtain crystallized materials. The choice and optimization of the sintering process is the key point to fabricate transparent ceramics. It includes a high control on the preparation of the powder with the choice of an adequate synthesis, a pre-heat-treatment, the reproducibility of the sintering cycle, the polishing and post-annealing of the ceramic. The densification is the main factor needed to reach a satisfying transparency, and many technologies are now available. The symmetry of the unit cell plays a crucial role in the diffusion rate of the material. Therefore, the cubic symmetry compounds having an isotropic refractive index is preferred. The cubic Y3NbO7 matrix is an interesting host which can accept a high concentration of rare earth doping element and it has been demonstrated that SPS is an efficient way to sinter this material. The optimization of diffusion losses requires a microstructure of fine ceramics, generally less than one hundred nanometers. In this case, grain growth is not an obstacle to transparency. The ceramics properties are then isotropic thereby to free-shaping step by orienting the ceramics as this is the case for the compounds of lower symmetry. After optimization of the synthesis route, several SPS parameters as heating rate, holding, dwell time and pressure were adjusted in order to increase the densification of the Eu3+ doped Y3NbO7 pellets. The luminescence data coupled with X-Ray diffraction analysis and electronic diffraction microscopy highlight the existence of several distorted environments of the doping element in the studied defective fluorite-type host lattice. Indeed, the fast and high crystallization rate obtained to put in evidence a lack of miscibility in the phase diagram, being the final composition of the pellet driven by the ratio between niobium and yttrium elements. By following the luminescence properties, we demonstrate a direct impact on the SPS process on this material.

Keywords: emission, niobate of rare earth, Spark plasma sintering, lack of miscibility

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Authors: Qazi Mahdia Ghyas

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Electronic Government Procurement (e-GP) has implemented in Bangladesh to ensure the good Governance. e-GP has transformed Bangladesh's procurement process electronically. But, to our best knowledge, there is no study to understand the key features of e-GP in Bangladesh. So, this study tries to identify the features of performance improvement after implementing an e-GP system that will help for further improvements. Data was collected from the PROMIS Overall Report (Central Procurement Technical Unit website) for the financial year from Q1 _July- Sep 2015-16 to Q4 _Apr- Jun 2021-22. This study did component factor analysis on KPIs and found nineteen KPIs that are statistically significant and represent time savings, efficiency, accountability, anti-corruption and compliance key features in procurement activities of e-GP. Based on the analysis, some practical measures have been recommended for better improvement of e-GP. This study has some limitations. Because of having multicollinearity issues, all the 42 KPIs (except 19) did not show a good fit for component factor analysis.

Keywords: public procurement, electronic government procurement, KPI, performance evaluation

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Authors: Hatem A. El-Mezayen, Hossam Darwesh

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Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between vascular endothelial growth factor (VEGF) and HCC progression, we aimed to develop a novel score based on combination of VEGF and routine laboratory tests for early prediction of HCC. Methods: VEGF was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-VEGF score)=1.26 (numerical constant) + 0.05 ×AFP (U L-1)+0.038 × VEGF(ng ml-1)+0.004× INR –1.02 × Albumin (g l-1)–0.002 × Platelet count × 109 l-1 was developed. HCC-VEGF score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 4.4 (ie less than 4.4 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-VEGF score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, tumor markers

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Authors: Qian Zaijian

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E-government is one of the hot issues in the current academic research of public policy and management. As the organic integration of information and communication technology (ICT) and public administration, e-government is one of the most important areas in contemporary information society. Policy information system is a basic subsystem of public policy system, its operation affects the overall effect of the policy process or even exerts a direct impact on the operation of a public policy and its success or failure. The basic principle of its operation is information collection, processing, analysis and release for a specific purpose. The function of E-government for public policy information system lies in the promotion of public access to the policy information resources, information transmission through e-participation, e-consultation in the process of policy analysis and processing of information and electronic services in policy information stored, to promote the optimization of policy information systems. However, due to many factors, the function of e-government to promote policy information system optimization has its practical limits. In the building of E-government in our country, we should take such path as adhering to the principle of freedom of information, eliminating the information divide (gap), expanding e-consultation, breaking down information silos and other major path, so as to promote the optimization of public policy information systems.

Keywords: China, e-consultation, e-democracy, e-government, e-participation, ICTs, public policy information systems

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Authors: M. Moayeri, A. Kaflou

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Decreasing the size of heat exchangers in industries is favorable due to a reduction in the initial costs and maintenance. This can be achieved generally by increasing the heat transfer coefficient, which can be done by increasing tube surface by passive methods named “porous coat”. Since these coatings are often in contact with the fluid, mechanical strength of coatings should be considered as main concept beside permeability and porosity in design, especially in high velocity services. Powder shape affected mechanical property more than other factors. So in this study, the Copper powder with three different shapes (spherical, dendritic and irregular) was coated on Cu-Ni base metal with thickness of ~300µm in a reduction atmosphere (5% H2-N2) and programmable furnace. The morphology and physical properties of coatings, such as porosity, permeability and mechanical strength were investigated. Results show although irregular particle have maximum porosity and permeability but strength level close to spherical powder, in addition, mentioned particle has low production cost, so for creating porous coats in high velocity services these powder recommended.

Keywords: porous coat, permeability, mechanical strength, porosity

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Authors: Wen-Bin Liau, Wan-Ting Wang, Chiang-Jen Hsiao, Sheng-Mao Tseng

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In this paper, an interesting and easy method to prepare one-dimensional nanostructured polyaniline/dendritic silver composites is reported. It is well known that the morphology of metal particle is a very important factor to influence the properties of polymer-metal composites. Usually, the dendritic silver is prepared by kinetic control in reduction reaction. It is not a thermodynamically stable structure. It is the goal to reduce silver ion to dendritic silver by polyaniline polymer via kinetic control and form one-dimensional nanostructured polyaniline/dendritic silver composites. The preparation is a two steps sequential reaction. First step, the polyaniline networks composed of nano fibrillar polyaniline are synthesized from aniline monomers aqueous with ammonium persulfate as the initiator at room temperature. In second step, the silver nitrate is added into polyaniline networks dispersed in deionized water. The dendritic silver is formed via reduction by polyaniline networks under the kinetic control. The formation of polyaniline is discussed via transmission electron microscopy (TEM). Nanosheets, nanotubes, nanospheres, nanosticks, and networks are observed via TEM. Then, the mechanism of formation of one-dimensional nanostructured polyaniline/dendritic silver composites is discussed. The formation of dendritic silver is observed by TEM and X-ray diffraction.

Keywords: 1D nanostructured polyaniline, dendritic silver, synthesis

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

Procedia PDF Downloads 153

Authors: N. R. Putra, A. H. Abdul Aziz, A. S. Zaini, Z. Idham, F. Idrus, M. Z. Bin Zullyadini, M. A. Che Yunus

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The content of omega-3 in soybean oil is important in the development of infants and is an alternative for the omega-3 in fish oils. The investigation of extraction of soybean oil is needed to obtain the bioactive compound in the extract. Supercritical carbon dioxide extraction is modern and green technology to extract herbs and plants to obtain high quality extract due to high diffusivity and solubility of the solvent. The aim of this study was to obtain the optimum condition of soybean oil extraction by modified supercritical carbon dioxide. The soybean oil was extracted by using modified supercritical carbon dioxide (SC-CO₂) under the temperatures of 40, 60, 80 °C, pressures of 150, 250, 350 Bar, and constant flow-rate of 10 g/min as the parameters of extraction processes. An experimental design was performed in order to optimize three important parameters of SC-CO₂ extraction which are pressure (X₁), temperature (X₂) to achieve optimum yields of soybean oil. Box Behnken Design was applied for experimental design. From the optimization process, the optimum condition of extraction of soybean oil was obtained at pressure 338 Bar and temperature 80 °C with oil yield of 2.713 g. Effect of pressure is significant on the extraction of soybean oil by modified supercritical carbon dioxide. Increasing of pressure will increase the oil yield of soybean oil.

Keywords: soybean oil, SC-CO₂ extraction, yield, optimization

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Authors: Raymond Dominic Uzoh

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Starch fillers were extracted from three plant sources namely amora tuber (a wild variety of Irish potato), sweet potato and yam starch and their particle size, pH, amylose, and amylopectin percentage decomposition determined accordingly by high performance liquid chromatography (HPLC). The starch was introduced into natural rubber in liquid phase (through gelatinization) by the latex compounding method and compounded according to standard method. The prepared starch/natural rubber composites was characterized by Instron Universal testing machine (UTM) for tensile mechanical properties. The composites was further characterized by x-ray diffraction and crosslink density analysis. The particle size determination showed that amora starch granules have the highest particle size (156 × 47 μm) followed by yam starch (155× 40 μm) and then the sweet potato starch (153 × 46 μm). The pH test also revealed that amora starch has a near neutral pH of 6.9, yam 6.8, and sweet potato 5.2 respectively. Amylose and amylopectin determination showed that yam starch has a higher percentage of amylose (29.68), followed by potato (22.34) and then amora starch with the lowest value (14.86) respectively. The tensile mechanical properties testing revealed that yam starch produced the best tensile mechanical properties followed by amora starch and then sweet potato starch. The structure, crystallinity/amorphous nature of the product composite was confirmed by x-ray diffraction, while the nature of crosslinking was confirmed by swelling test in toluene solvent using the Flory-Rehner approach. This research study has rendered a workable strategy for enhancing interfacial interaction between a hydrophilic filler (starch) and hydrophobic polymeric matrix (natural rubber) yielding moderately good tensile mechanical properties for further exploitation development and application in the rubber processing industry.

Keywords: natural rubber, fillers, starch, amylose, amylopectin, crosslink density

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: John M. Basey, Clinton D. Francis, Maxwell B. Joseph

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After gathering data from experimental procedures, inquiry-oriented-science labs often allow students the freedom to stay and complete the write up in class or leave lab early and complete the write up later. Teachers must decide whether to allow students this freedom to self-regulate this time. Student interviews have indicated four time-target strategies that may influence how students utilize this time: grade-target-A, grade-target-C, time-limited, and proficiency. The hypothesis tested was that variability in class composition relative to the four grade-target strategies has an impact on when students leave class, which in turn may influence their overall learning as exemplified by grades. Students were divided into the four indicated groups with a survey. Class composition and the GTA teaching the class had significant impacts on how long students stayed in class with class composition having the greatest impact. A factor analysis identified two factors. Factor 1 included classes with percentages of grade-target students opposite time-limited/proficiency students and explained 43% of the variance. Factor 2 included classes with percentages of grade-target-A/proficiency students opposite grade-target-C students and explained 33% of the variance. Students who stayed longer received significantly higher grades (P = 0.008) with no significant relationships between grade and Factor 1 or Factor 2 (P > 0.05). The time students stayed in class was significantly positively related to Factor 1 (P = 0.006) and significantly negatively related to Factor 2 (P = 0.008). These results support the hypothesis and indicate that teachers may want to know the composition of student-target strategies before deciding on how to have students allocate study time at the end of inquiry-oriented labs. According to these results, ideal classes for self-regulation have a high proportion of proficiency and time-limited students and a low proportion of grade-target students, or a high proportion of grade-target-A and proficiency students and a low proportion of grade-target-C students. Non-ideal classes for self-regulation were comprised of the inverse proportions.

Keywords: grades, inquiry lab design, synergism in student motivation, class composition

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Authors: Hong Kai, Zhong Jun Jie, Chen Lin Qi, Wang Chen Guang

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There are inefficient global scheduling parallelism and local scheduling parallelism prone to processor starvation in current scheduling algorithms. Regarding this issue, this paper proposed a load-aware queue partitioning scheduling strategy by first allocating the queues according to the number of processor cores, calculating the load factor to specify the load queue capacity, and it assigned the awaiting nodes to the appropriate perceptual queues through the precursor nodes and the communication computation overhead. At the same time, real-time computation of the load factor could effectively prevent the processor from being starved for a long time. Experimental comparison with two classical algorithms shows that there is a certain improvement in both performance metrics of scheduling length and task speedup ratio.

Keywords: load-aware, scheduling algorithm, perceptual queue, heterogeneous multi-core

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Authors: T. G. Asmitha Chandini

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Web-based image search re-ranking, as an successful method to get better the results. In a query keyword, the first stair is store the images is first retrieve based on the text-based information. The user to select a query keywordimage, by using this query keyword other images are re-ranked based on their visual properties with images.Now a day to day, people projected to match images in a semantic space which is used attributes or reference classes closely related to the basis of semantic image. though, understanding a worldwide visual semantic space to demonstrate highly different images from the web is difficult and inefficient. The re-ranking images, which automatically offline part learns dissimilar semantic spaces for different query keywords. The features of images are projected into their related semantic spaces to get particular images. At the online stage, images are re-ranked by compare their semantic signatures obtained the semantic précised by the query keyword image. The query-specific semantic signatures extensively improve both the proper and efficiency of image re-ranking.

Keywords: Query, keyword, image, re-ranking, semantic, signature

Procedia PDF Downloads 551

Authors: Young-Kwang Lee, Eun-Gu Ji, Min-Joo Kim, Seung-Jae Oh

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The purpose of this study is to develop a social participation activity scale for the elderly. As a result of exploratory factor analysis, confirmatory factor analysis was conducted using maximum likelihood method using bundled items. In conclusion, thirteen items of social participation activity scale seemed appropriate. Finally, convergent validity and discriminant validity were verified on the scale with the fit. The convergent validity was based on the variance extracted value. In other words, the hypothesis that the variables are the same is rejected and the validity is confirmed. This study extensively considered the measurement items of the social participation activity scale used to measure social participation activities of the elderly. In the future, it will be meaningful that it can be used as a tool to verify the effectiveness of services in organizations that provide social welfare services to elderly people such as comprehensive social welfare centers and the elderly comprehensive social welfare centers.

Keywords: elderly, social participation, scale development, validity

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Y. Kalachyova, O. Lyutakov, V. Svorcik

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One of the most significant obstacles for the application of surface enhanced Raman spectroscopy (SERS) is the poor reproducibility of SERS active substrates: SERS intensity can be varied from one substrate to another and moreover along the one substrate surface. High enhancement of the near-field intensity is the key factor for ultrasensitive SERS realization. SERS substrate can be prepared through introduction of highly ordered metal array, where light focusing is achieved through excitation of surface plasmon-polaritons (SPPs). In this work, we report the preparation of silver nanostructures with plasmon absorption peaks tuned by the metal arrangement. Excimer laser modification of poly(methyl methacrylate) followed by silver evaporation is proposed as an effective way for the creation of reproducible and effective surface plasmon-polaritons (SPP)-based SERS substrate. Theoretical and experimental studies were performed to optimize structure parameter for effective SPP excitation. It was found that the narrow range of grating periodicity and metal thickness exist, where SPPs can be most efficiently excited. In spite of the fact, that SERS response was almost always achieved, the enhancement factor was found to vary more with the effectivity of SPP excitation. When the real structure parameters were set to optimal for SPP excitation, a SERS enhancement factor was achieved up to four times. Theoretical and experimental investigation of SPP excitation on the two-dimensional periodical silver array was performed with the aim to make SERS response as high as possible.

Keywords: grating, nanostructures, plasmon-polaritons, SERS

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Authors: Igor Bilenko, Artem Shitikov, Michael Gorodetsky

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Optical whispering gallery mode (WGM) resonators combine very high optical quality factor (Q) with small size. Resonators made from low loss crystalline fluorites (CaF2, MgF2) may have Q as high as 1010 that make them unique devices for modern applications including ultrasensitive sensors, frequency control, and precision spectroscopy. While silicon is a promising material transparent from near infrared to terahertz frequencies, fundamental limit for Si WGM quality factor was not reached yet. In our paper, we presented experimental results on the preparation and testing of resonators at 1550 nm wavelength made from crystalline silicon grown and treated by different techniques. Q as high as 3x107 was demonstrated. Future steps need to reach a higher value and possible applications are discussed.

Keywords: optical quality factor, silicon optical losses, silicon optical resonator, whispering gallery modes

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Authors: Nakul V. Naphade, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

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Achieving zero-energy targets in existing buildings is known to be a difficult task requiring important cuts in the building energy consumption, which in many cases clash with the functional necessities of the building wherever the on-site energy generation is unable to match the overall energy consumption. Between the building’s consumption optimization limit and the energy, target stretches a case-specific optimization grey zone, which requires tailored intervention and enhanced user’s commitment. In the view of the future adoption of more stringent energy-efficiency targets in the context of hot-humid tropical climates, this study aims to define the energy optimization grey zone by assessing the energy-efficiency limit in the state-of-the-art typical mid- and high-rise full AC office buildings, through the integration of currently available technologies. Energy models of two code-compliant generic office-building typologies were developed as a baseline, a 20-storey ‘high-rise’ and a 7-storey ‘mid-rise’. Design iterations carried out on the energy models with advanced market ready technologies in lighting, envelope, plug load management and ACMV systems and controls, lead to a representative energy model of the current maximum technical potential. The simulations showed that ZEB targets could be achieved in fully AC buildings under an average of seven floors only by compromising on energy-intense facilities (as full AC, unlimited power-supply, standard user behaviour, etc.). This paper argues that drastic changes must be made in tropical buildings to span the energy optimization grey zone and achieve zero energy. Fully air-conditioned areas must be rethought, while smart technologies must be integrated with an aggressive involvement and motivation of the users to synchronize with the new system’s energy savings goal.

Keywords: energy simulation, office building, tropical climate, zero energy buildings

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Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

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Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

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Authors: Ritu Vashistha, Jitender Kumar

Abstract:

Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

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Authors: Barbara Zapala, Marek Dziechciowski, Olaf Chmura, Monika Piwowar, Katarzyna Gawlik, Dorota Pawlicka-Gosiewska, Krzysztof Skotniczny, Bogdan Solnica, Kazimierz Pitynski

Abstract:

BACKGROUND: Endometrial cancer is one of the most common gynecologic malignancy in developed countries.We hypothesized that amount of circulating micro-particles in blood may be connected with the development of endometrial hyperplasia and endometrial cancer. The aim of this study was to measure the micro-particles amount in uterine venous blood and in peripheral venous blood in women with atypical endometrial hyperplasia and endometrioid endometrial cancer. MATERIALS AND METHODS: By using flow cytometry (BD Canto II cytometer) we measured micro-particles amount in citrate plasma samples from peripheral and uterine venous blood of women with atypical hyperplasia of endometrium or endometrial cancer. We determined the amount of total (TF+), endothelial (CD144+) and monocytic (CD14+) micro- particles. RESULTS: Here we show statistically significant higher micro-particle levels in women with atypical hyperplasia of endometrium or endometrial cancer in comparison to healthy women. Performing measurements of the amounts of total, endothelial and monocytic microparticles allow for reliable differentiation between healthy, atypical hyperplasia and endometrial cancer groups. In blood samples from uterine veins the circulating micro-particle levels were significantly different from peripheral blood samples. The micro-particle levels in uterine blood samples were 7-fold higher than in those from peripheral blood of women with both atypical hyperplasia of endometrium and endometrial cancer when compared to the control group of healthy women. CONCLUSION: These results strongly suggested that the level of circulating micro-particles may be a sign of endometrial cancer development, however the detailed study is needed focusing on molecular processes passed through this small circulating molecules.

Keywords: endometrial cancer, endometrial hyperplasia, microvesicles, uterine blood

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Authors: Harsha Thaira, Ritu Raval, Keyur Raval

Abstract:

Melanin has immense applications in the field of agriculture, cosmetics and pharmaceutical industries due to its photo-protective, UV protective and anti- oxidant activities. However, its production is limited to costly chemical methods or harsh extractive methods from hair which ultimately gives poor yields. This makes the cost of melanin very high, to the extent of US Dollar 300 per gram. Some microorganisms are reported to produce melanin under stress conditions. Out of all melanin producing organisms, Pseudomonas stutzeri can grow in sea water and produce melanin under saline stress. The objective of this study was to develop a sea water based bioprocess. Effects of different growth media and process parameters on melanin production using sea water were investigated. The marine bacterial strain Pseudomonas stutzeri HMGM-7(MTCC 11712) was selected and the effect of different media such as Nutrient Broth (NB), Luria Bertini (LB) broth, Bushnell- Haas broth (BHB) and Trypticase Soy broth (TSB) and various medium components were investigated with one factor at a time approach. Parameters like shaking frequency, inoculum age, inoculum size, pH and temperature were also investigated in order to obtain the optimum conditions for maximum melanin production. The highest yield of melanin concentration, 0.306 g/L, was obtained in Trypticase Soy broth at 36 hours. The yield was 1.88 times higher than the melanin obtained before optimization, 0.163 g/L at 36 hours. Studies are underway to optimize medium constituents to further enhance melanin production.

Keywords: melanin, marine, bioprocess, pseudomonas

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Authors: Erin M. Durke, Monica L. McEntee, Meilu He, Suresh Dhaniyala

Abstract:

Aerosols are one of the most important and significant surfaces in the atmosphere. They can influence weather, absorption, and reflection of light, and reactivity of atmospheric constituents. A notable feature of aerosol particles is the presence of a surface charge, a characteristic imparted via the aerosolization process. The existence of charge can complicate the interrogation of aerosol particles, so many researchers remove or neutralize aerosol particles before characterization. However, the charge is present in real-world samples, and likely has an effect on the physical and chemical properties of an aerosolized material. In our studies, we aerosolized different materials in an attempt to characterize the charge imparted via the aerosolization process and determine what impact it has on the aerosolized materials’ properties. The metal oxides, TiO₂ and SiO₂, were aerosolized expulsively and then characterized, using several different techniques, in an effort to determine the surface charge imparted upon the particles via the aerosolization process. Particle charge distribution measurements were conducted via the employment of a custom scanning mobility particle sizer. The results of the charge distribution measurements indicated that expulsive generation of 0.2 µm SiO₂ particles produced aerosols with upwards of 30+ charges on the surface of the particle. Determination of the degree of surface charging led to the use of non-traditional techniques to explore the impact of additional surface charge on the overall reactivity of the metal oxides, specifically TiO₂. TiO₂ was aerosolized, again expulsively, onto a gold-coated tungsten mesh, which was then evaluated with transmission infrared spectroscopy in an ultra-high vacuum environment. The TiO₂ aerosols were exposed to O₂, H₂, and CO, respectively. Exposure to O₂ resulted in a decrease in the overall baseline of the aerosol spectrum, suggesting O₂ removed some of the surface charge imparted during aerosolization. Upon exposure to H₂, there was no observable rise in the baseline of the IR spectrum, as is typically seen for TiO₂, due to the population of electrons into the shallow trapped states and subsequent promotion of the electrons into the conduction band. This result suggests that the additional charge imparted via aerosolization fills the trapped states, therefore no rise is seen upon exposure to H₂. Dosing the TiO₂ aerosols with CO showed no adsorption of CO on the surface, even at lower temperatures (~100 K), indicating the additional charge on the aerosol surface prevents the CO molecules from adsorbing to the TiO₂ surface. The results observed during exposure suggest that the additional charge imparted via aerosolization impacts the interaction with each probe gas.

Keywords: aerosols, charge, reactivity, infrared

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Authors: Seung-Min Yang, Seong-Han Park, Sang-Hoon Lee, Seung-Wan Yoo, Chan-Soo Kim, Nong-Moon Hwang

Abstract:

The theory of charged nanoparticles suggested that in many Chemical Vapour Depositions (CVD) processes, Charged Nanoparticles (CNPs) are generated in the gas-phase and become a building block of thin films and nanowires. Recently, the nanoparticle-based crystallization has become a big issue since the growth of nanorods or crystals by the building block of nanoparticles was directly observed by transmission electron microscopy observations in the liquid cell. In an effort to confirm charged gas-phase nuclei, that might be generated under conventional processing conditions of thin films and nanowires during CVD, we performed an in-situ measurement using differential mobility analyser and particle beam mass spectrometer. The size distribution and number density of CNPs were affected by process parameters such as precursor flow rate and working temperature. It was shown that many films and nanostructures, which have been believed to grow by individual atoms or molecules, actually grow by the building blocks of such charged nuclei. The electrostatic interaction between CNPs and the growing surface induces the self-assembly into films and nanowires. In addition, the charge-enhanced atomic diffusion makes CNPs liquid-like quasi solid. As a result, CNPs tend to land epitaxial on the growing surface, which results in the growth of single crystalline nanowires with a smooth surface.

Keywords: chemical vapour deposition, charged nanoparticle, electrostatic force, nanostructure evolution, differential mobility analyser, particle beam mass spectrometer

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