Search results for: hybrid genetic algorithms

Authors: Jennifer Chen, Pei Y. Hsu, Yu W. Chen

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Groundwater resources play a vital role in regional water supply because over 1/3 of total demand is satisfied by groundwater resources. Because over-pumpage might cause environmental impact such as land subsidence, a sustainable management of groundwater resource is required. In this study, a blueprint of smart management for groundwater resource is proposed and planned. The framework of the smart management can be divided into two major parts, hardware and software parts. First, an internet of groundwater (IoG) which is inspired by the internet of thing (IoT) is proposed to observe the migration of groundwater usage and the associated response, groundwater levels. Second, algorithms based on data mining and signal analysis are proposed to achieve the goal of providing highly efficient management of groundwater. The entire blueprint is a 4-year plan and this year is the first year. We have finished the installation of 50 flow meters and 17 observation wells. An underground hydrological model is proposed to determine the associated drawdown caused by the measured pumpages. Besides, an alternative to the flow meter is also proposed to decrease the installation cost of IoG. An accelerometer and 3G remote transmission are proposed to detect the on and off of groundwater pumpage.

Keywords: groundwater management, internet of groundwater, underground hydrological model, alternative of flow meter

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Authors: William Wong, Zakaria Alomari, Hon Ching Lai, Zhida Li

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Modern-day information security depends on implementing Diffie-Hellman, which requires the generation of prime numbers. Because the number of primes is infinite, it is impractical to store prime numbers for use, and therefore, primality tests are indispensable in modern-day information security. A primality test is a test to determine whether a number is prime or composite. There are two types of primality tests, which are deterministic tests and probabilistic tests. Deterministic tests are adopting algorithms that provide a definite answer whether a given number is prime or composite. While in probabilistic tests, a probabilistic result would be provided, there is a degree of uncertainty. In this paper, we review three probabilistic tests: the Fermat Primality Test, the Miller-Rabin Test, and the Baillie-PSW Test, as well as one deterministic test, the Agrawal-Kayal-Saxena (AKS) Test. Furthermore, we do an analysis of these tests. All of the reviews discussed are not based on the Elliptic Curve. The analysis demonstrates that, in the majority of real-world scenarios, the Baillie- PSW test’s favorability stems from its typical operational complexity of O(log 3n) and its capacity to deliver accurate results for numbers below 2^64.

Keywords: primality tests, Fermat’s primality test, Miller-Rabin primality test, Baillie-PSW primality test, AKS primality test

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Authors: Mohammad Hajjartabar, Tahereh Kermani Ranjbar

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P. aeruginosa EF2 was isolated and identified from human infection sources before in our previous study. The present study was performed to determine the characteristics and activity role of bioflocculant produced by the bacterium in flocculation of the wastewater active sludge treatment. The bacterium was inoculated and then was grown in an orbital shaker at 250 rpm for 5 days at 35 °C under TSB and peptone water media. After incubation period, culture broths of the bacterial strain was collected and washed. The concentration of the bacteria was adjusted. For the extraction of the bacterial bioflocculant, culture was centrifuged at 6000 rpm for 20 min at 4 °C to remove bacterial cells. Supernatant was decanted and pellet containing bioflocculant was dried at 105 °C to a constant weight according to APHA, 2005. The chemical composition of the extracted bioflocculant from the bacterial sample was then analyzed. Wastewater active sludge sample obtained from aeration tank from one of wastewater treatment plants in Tehran, was first mixed thoroughly. After addition of bioflocculant, improvements in floc density were observed with an increase in bioflocculant. The results of this study strongly suggested that the extracted bioflucculant played a significant role in flocculation of the wastewater sample. The use of wild bacteria and nutrient regulation techniques instead of genetic manipulation opens wide investigation area in the future to improve wastewater treatment processes. Also this may put a new path in front of us to attain and improve the more effective bioflocculant using the purified microbial culture in wastewater treatment.

Keywords: wastewater treatment, P. aeruginosa, sludge treatment

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Authors: K. Kannapathi-Naidoo

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The higher education landscape has undergone changes in the past decade, with concepts such as blended learning, online learning, and hybrid models appearing more frequently in research and practice. The year 2020 marked a mass migration from face-to-face learning and more traditional forms of education to online learning in higher education institutions across the globe due to the Covid-19 pandemic. As a result, contact learning students and lecturing staff alike were thrust into the world of online learning at an unprecedented pace. Traditional modes of learning had to be amended, and pedagogical strategies required adjustments. This study was located within a compulsory first-year academic literacy module in a higher education institution. The study aimed to explore students’ learning preferences between online, face-face, and blended learning within the context of academic literacy. Data was collected through online qualitative questionnaires administered to 150 first-year students, which were then analysed thematically. The findings of the study revealed that 48.5% of the participants preferred a blended learning approach to academic literacy. The main themes that emerged in support of their preference were best of both worlds, flexibility, productivity, and lecturer accessibility. As a result, this paper advocates for the blended learning approach for academic literacy skills-based modules.

Keywords: academic literacy, blended learning, online learning, student learning preferences

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Authors: Priyanka Sharma, Tarkewshwar Dubey, Hemalatha Siva

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Hemorrhoids are one of the most common anorectal diseases around the world. Severalfactors are involved in causing hemorrhoids including irregularbowel function (constipation, diarrhea), exercise, gravity, low fiberdiet, pregnancy, obesity, high abdominal pressure, prolongedsitting, genetic factors, and aging. Pain, bleeding, itching,swelling and anal discharge are the symptoms of the disease. Due to limitedmodern pharmacotherapeutic options available for treatment, theherbal medicines remain the choice of therapy. Blumea lacera (Burm f.) DC. belonging to the Asteraceae family is a common plain land weed of Bangladesh. Traditionally it has been used for treatment of hemorrhoids.Considering the above fact, present study was aimed to validate the ethnomedicinal use of B. lacera leaves on experimental hemorrhoids in rats. The anti-hemorrhoid activity was performed by using croton oil induced rat models. The parameters studied were assessment of TNF-α and IL-6, Evans blue exudation, macroscopic severity score, recto-anal coefficient, histomorphological scores. Also, in vivo antioxidant parameters and histopathological studies were also performed. All paramaters exhibited significant anti-hemorrhoid activity. Moreover ethanolic extract of B. lacera (EBL) leaves 400mg/kg showed ameliorative effect oncroton oil induced hemorrhoids.In conclusion, EBL exhibitedbeneficial effect on croton oil- induced hemorrhoids and validates its ethnomedicinal use in treatment of piles.

Keywords: haemorrhoids, IL-6, piles, TNF-α

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Authors: Ritesh K. Shukla

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Degradation of biological samples in terms of macromolecules (DNA, RNA, and protein) are the major challenges in the forensic investigation which misleads the result interpretation. Currently, there are no precise methods available to circumvent this problem. Therefore, at the preliminary level, some methods are urgently needed to solve this issue. In this order, Comet assay is one of the most versatile, rapid and sensitive molecular biology technique to assess the DNA degradation. This technique helps to assess DNA degradation even at very low amount of sample. Moreover, the expedient part of this method does not require any additional process of DNA extraction and isolation during DNA degradation assessment. Samples directly embedded on agarose pre-coated microscopic slide and electrophoresis perform on the same slide after lysis step. After electrophoresis microscopic slide stained by DNA binding dye and observed under fluorescent microscope equipped with Komet software. With the help of this technique extent of DNA degradation can be assessed which can help to screen the sample before DNA fingerprinting, whether it is appropriate for DNA analysis or not. This technique not only helps to assess degradation of DNA but many other challenges in forensic investigation such as time since deposition estimation of biological fluids, repair of genetic material from degraded biological sample and early time since death estimation could also be resolved. With the help of this study, an attempt was made to explore the application of well-known molecular biology technique that is Comet assay in the field of forensic science. This assay will open avenue in the field of forensic research and development.

Keywords: comet assay, DNA degradation, forensic, molecular biology

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Authors: Adedayo Ajayi, Patrick Luk, Liyun Lao

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This paper studies the supportive needs for the electrical infrastructure of the green airport. In particular, the core objective revolves around the choice of electric grid configuration required to meet the expected electrified loads, i.e., the taxiing and charging loads of hybrid /pure electric aircraft in the airport. Further, reliability and resilience are critical aspects of a newly proposed grid; the concept of mobile energy storage as energy as a service (EAAS) for grid support in the proposed green airport is investigated using an autonomous electric taxiing robot (A-ETR) at a case study (Cranfield Airport). The performance of the model is verified and validated through DigSILENT power factory simulation software to compare the networks in terms of power quality, short circuit fault levels, system voltage profile, and power losses. Contingency and reliability index analysis are further carried out to show the potential of EAAS on the grid. The results demonstrate that the low voltage a.c network ( LVAC) architecture gives better performance with adequate compensation than the low voltage d.c (LVDC) microgrid architecture for future green airport electrification integration. And A-ETR can deliver energy as a service (EaaS) to improve the airport's electrical power system resilience and energy supply.

Keywords: reliability, voltage profile, flightpath 2050, green airport

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar

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In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.

Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques

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Authors: Seyedmilad Kazemisangdehi, Seyedmehdi Kazemisangdehi

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Flux switching permanent magnet machines are considered for wide range of applications because of their outstanding merits including high torque/power densities, high efficiency, simple and robust rotor structure. Therefore, several topologies have been proposed like the PM exited flux switching machine, hybrid excited flux switching type, and so on. Recently, a novel laminated segmented rotor flux switching permanent magnet machine was introduced. It features flux barriers on rotor structure to enhance the performances of machine including torque ripple reduction and also torque and efficiency improvements at the same time. This is while, the design of barriers was not optimized by the authors. Therefore, in this paper three coefficients regarding the position of the barriers are considered for optimization. The effect of each coefficient on the performance of this machine is investigated by finite element method and finally an optimized design of flux barriers based on these three coefficients is proposed from different points of view including electromagnetic torque maximization and cogging torque/torque ripple minimization. At optimum design from maximum developed torque aspect, this machine generates 0.65 Nm torque higher than that of the not-optimized design with an almost 0.4 % improvement in efficiency.

Keywords: finite element analysis, FSPM, laminated segmented rotor flux switching permanent magnet machine, optimization

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Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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Authors: Chao Sima, Shanaz Ghandhi, Sally A. Amundson, Michael L. Bittner, David J. Brenner

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In a large-scale radiologic emergency, potentially affected population need to be triaged efficiently using various biomarkers where personal dosimeters are not likely worn by the individuals. It has long been established that radiation injury can be estimated effectively using panels of genetic biomarkers. Furthermore, the rate of radiation, in addition to dose of radiation, plays a major role in determining biological responses. Therefore, a better and more accurate triage involves estimating both the dose level of the exposure and the length of time of that exposure. To that end, a large in vivo study was carried out on mice with internal emitter caesium-137 (¹³⁷Cs). Four different injection doses of ¹³⁷Cs were used: 157.5 μCi, 191 μCi, 214.5μCi, and 259 μCi. Cohorts of 6~7 mice from the control arm and each of the dose levels were sacrificed, and blood was collected 2, 3, 5, 7 and 14 days after injection for microarray RNA gene expression analysis. Using a generalized linear model with penalized maximum likelihood, a panel of 244 genes was established and both the doses of injection and the number of days after injection were accurately predicted for all 155 subjects using this panel. This has proven that microarray gene expression can be used effectively in radiation biodosimetry in predicting both the dose levels and the length of exposure time, which provides a more holistic view on radiation exposure and helps improving radiation damage assessment and treatment.

Keywords: caesium-137, gene expression microarray, multivariate responses prediction, radiation biodosimetry

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Sanjeev Kumar Shukla, Govind Singh, Prabhat Pant Shahzad Ahmad

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Background: Graves’ disease is an autoimmune disorder with a genetic predisposition, and CD40 plays a pathogenic role in various autoimmune diseases. A single nucleotide polymorphism at position –1 of the Kozak sequence of the 5 untranslated regions of the CD40 gene of exon 1 has been reported to be associated with the development of Graves’ Disease. Objective: The aim of the present study was to investigate whether CD40 gene polymorphism confers susceptibility to Graves’ disease in the Kumaon region. CD40 gene polymorphisms were studied in Graves’ Disease patients (n=50) and healthy control subjects without anti-thyroid autoantibodies or a family history of autoimmune disorders (n=50). Material and Method: CD40 gene polymorphisms were studied in fifty Graves’ Disease patients and fifty healthy control subjects. All samples were collected from STG Hospital, Haldwani, Nainital. A C/T polymorphism at position –1 of the CD40 gene was measured using the polymerase chain reaction-restriction fragment length polymorphism. Results: There was no significant difference in allele or genotype frequency of the CD40 SNP between Graves’ Disease and control subjects. There was a significant decrease in the TT genotype frequency in the Graves’ Disease patients who developed Graves’ Disease after 40 years old than those under 40 years of age. These data suggest that the SNP of the CD40 gene is associated with susceptibility to the later onset of Graves’ Disease. Conclusion: The CD40 gene was a different susceptibility gene for Graves’ Disease within certain families because it was both linked and associated with Graves’ Disease.

Keywords: autoimmune diseases, pathogenesis, diagnosis, therapy

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Authors: Arun Prasad

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Background: Robotic Bariatric Surgery is a good option for the super obese where laparoscopy demands challenging technical skills. Gastric bypass can be difficult due to inability of the robot to work in two quadrants at the same time. Lonroth technique of gastric bypass involves a totally supracolic surgery where all anastomosis are done in one quadrant only. Methods: We have done 78 robotic gastric bypass surgeries using the modified Lonroth technique. The robot is docked above the head of the patient in the midline. Camera port is placed supra umbilically. Two ports are placed on the left side of the patient and one port on the right side of the patient. An assistant port is placed between the camera port and right sided robotic port for use of stapler. Gastric pouch is made first followed by the gastrojejunostomy that is a four layered sutured anastomosis. Jejuno jejunostomy is then performed followed by a leak test and then the jejunum is divided. A 150 cm biliopancreatic limb and a 75 cm alimentary limb are finally obtained. Mesenteric and Petersen’s defects are then closed. Results: All patients had a successful robotic procedure. Mean time taken in the first 5 cases was 130 minutes. This reduced to a mean of 95 minutes in the last five cases. There were no intraoperative or post operative complications. Conclusions: While a hybrid technique of partly laparoscopic and partly robotic gastric bypass has been done at many centres, we feel using the modified Lonroth technique, a totally robotic gastric bypass surgery fully utilizes the potential of robotic bariatric surgery.

Keywords: robot, bariatric, totally robotic, gastric bypass

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Authors: Othman Elmahdy Othman

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The objectives of this study were to identify polymorphisms in the STAT5A using Restriction Fragment Length Polymorphism and DGAT1 using Single-Strand Conformation Polymorphism genes among three Egyptian goat breeds (Barki, Zaraibi, and Damascus) as well as investigate the effect of their genotypes on milk composition traits of Zaraibi goats. One hundred and fifty blood samples were collected for DNA extraction, 60 from Zaraibi, 40 from Damascus and 50 from Barki breeds. Fat, protein and lactose percentages were determined in Zaraibi goat milk using an automatic milk analyzer. Two genotypes, CC and CT (for STAT5A) and C-C- and C-C+ (for DGAT1), were identified in the three Egyptian goat breeds with different frequencies. The associations between these genotypes and milk fat, protein and lactose were determined in Zaraibi breed. The results showed that the STAT5A genotypes had significant effects on milk yield, protein, fat and lactose with the superiority of CT genotype over CC. Regarding DGAT1 polymorphism, the result showed the only association between it with milk fat where the animals with C-C+ genotype had greater milk fat than animals possess C-C- genotype. The association of combined genotypes with milk trait declared that the does with heterozygous genotypes for both genes are preferred than does with homozygous genotypes where the animals with CTC-C+ have more milk yield, fat and protein than those with CCC-C- genotype. In conclusion, the result showed that C/T and C-/C+ SNPs of STAT5A and DGAT1 genes respectively may be useful markers for assisted selection programs to improve goat milk composition

Keywords: DGAT1, genetic polymorphism, milk trait, STAT5A

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Md. Danish Eqbal, Venkat Gundabala

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Microparticles and microcapsules are basically used as a carrier for cells, tissues, drugs, and chemicals. Due to its biocompatibility, non-toxicity and biodegradability, alginate based microparticles have numerous applications in drug delivery, tissue engineering, organ repair and transplantation, etc. The production of uniform monodispersed microparticles was a challenge for the past few decades. However, emergence of microfluidics has provided controlled methods for the generation of the uniform monodispersed microparticles. In this work, we present a successful method for the generation of both microparticles and microcapsules (single and double core) using merging approach of two droplets, completely inside the microfluidic device. We have fabricated hybrid glass- PDMS (polydimethylsiloxane) based microfluidic device which has coflow geometry as well as the T junction channel. Coflow is used to generate the single as well as double oil-alginate emulsion in oil and T junction helps to form the calcium chloride droplets in oil. The basic idea is to match the frequency of the alginate droplets and calcium chloride droplets perfectly for controlled generation. Using the merging of droplets technique, we have successfully generated the microparticles and the microcapsules having single core as well as double and multiple cores. The cores in the microcapsules are very stable, well separated from each other and very intact as seen through cross-sectional confocal images. The size and the number of the cores along with the thickness of the shell can be easily controlled by controlling the flowrate of the liquids.

Keywords: double-core, droplets, microcapsules, microparticles

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Authors: Renkai Wang, Tingcun Wei

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In this paper, a digital control algorithm based on delta-operator is presented for high-frequency digitally-controlled DC-DC switching converters. The stability and the controlling accuracy of the DC-DC switching converters are improved by using the digital control algorithm based on delta-operator without increasing the hardware circuit scale. The design method of voltage compensator in delta-domain using PID (Proportion-Integration- Differentiation) control is given in this paper, and the simulation results based on Simulink platform are provided, which have verified the theoretical analysis results very well. It can be concluded that, the presented control algorithm based on delta-operator has better stability and controlling accuracy, and easier hardware implementation than the existed control algorithms based on z-operator, therefore it can be used for the voltage compensator design in high-frequency digitally- controlled DC-DC switching converters.

Keywords: digitally-controlled DC-DC switching converter, digital voltage compensator, delta-operator, finite word length, stability

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Authors: Jyoti Singh, Swati Dubey, Mukta Singh, R. P. Singh

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The freshwater microalgae Chlorella sp. is alluring considerable interest as a source for biofuel production due to its fast growth rate and high lipid content. Under nitrogen limited conditions, they can accumulate significant amounts of lipids. Thus, it is important to gain insight into the molecular mechanism of their lipid metabolism. In this study under nitrogen limited conditions, regular pattern of growth characteristics lipid accumulation and gene expression analysis of key regulatory genes of lipid biosynthetic pathway were carried out in microalgae Chlorella sp 3. Our results indicated that under nitrogen limited conditions there is a significant increase in the lipid content and lipid productivity, achieving 44.21±2.64 % and 39.34±0.66 mg/l/d at the end of the cultivation, respectively. Time-course transcript patterns of lipid biosynthesis genes i.e. acetyl coA carboxylase (accD) and diacylglycerol acyltransferase (dgat) showed that during late log phase of microalgae Chlorella sp.3 both the genes were significantly up regulated as compared to early log phase. Moreover, the transcript level of the dgat gene is two-fold higher than the accD gene. The results suggested that both the genes responded sensitively to the nitrogen limited conditions during the late log stage, which proposed their close relevance to lipid biosynthesis. Further, this transcriptome data will be useful for engineering microalgae species by targeting these genes for genetic modification to improve microalgal biofuel quality and production.

Keywords: biofuel, gene, lipid, microalgae

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Authors: Amanuel Bekuma, Rebecca Swift, Sarah Jackson, Ben Biddulph

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Economic loss to frost damage is increasing over the past years in the Western Australian Wheatbelt. Agronomic, genetic, and climatic works have still found a weak correlation between temperature and frost damage. One possibility that has not been explored within the Australian cropping system is whether ice nucleation active bacteria (INB) either present in situ on crop residue or introduced by rainfall could be responsible for the increased sensitivity of cereal plants to frost at different stages of development. This study investigated upper and lower leaf canopy, stubble, and soil as a potential site of ice nucleation activity (INA) and tracked the changes in INA during the plant development. We found that older leaves of wheat are the primary sites of ice nucleation (-4.7 to -6.3°C) followed by stubble (-5.7 to -6.7°C) which increases the risk of frost damage during heading and flowering (the most susceptible stages). However, healthy and green upper canopy leaves (flag and flag-2) and the soil have lower INA (< -11°C) during the frost-sensitive stage of wheat. We anticipate the higher INA on the stubble and older leaves to be due to the presence of biologically active ice-nucleating bacteria (INB), known to cause frost injury to sensitive plants at -5°C. Stubble retained or applied during the growing season further exacerbates additional frost risk by potentially increasing the INB load. The implications of the result for stubble and frost risk management in a frost-prone landscape will be discussed.

Keywords: frost, ice-nucleation-activity, stubble, wheat

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Authors: Kaori Mori Want

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American society is a racially diverse society and there are children books that tell the importance of respecting racial differences. Through reading books, children understand the world around them little by little along with their direct interaction with the world in reality. They find role models in books, strive to be like role models, and grow confidence in who they are. Books thus nurture the mind of children. On the other hand, because of their small presence, children books for multiracial Asian American children are scarce. Multiracial Asian American population is increasing but they are still minority in number. The lack of children’s books for these children may deprive the opportunities of them to embrace their multiraciality positively because they cannot find someone like them in any books. Children books for multiracial Asian American are still not that many, but a few have been being published recently. This paper introduces children books for multiracial Asian American children, and examines how they address issues pertaining to these children, and how they could nurture their self-esteem. Many states of the US used to ban interracial marriages and interracial families and their children once were discriminated against in American society. There was even a theory called the hybrid degeneracy theory which claimed that mixed race children were inferior mentally and physically. In this negative social environment, some multiracial Asian American people report that they had trouble embracing their multiracial identity positively. Yet, children books for these children are full of positive messages. This paper will argue the importance of children books for the mental growth of multiracial Asian American children, and how these books can contribute to the development of multiculturalism in the US in general.

Keywords: critical mixed race studies in the US, hapa children literature, interracial marriage, multiraciality

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Authors: Jude Opara, Esemokumo Perewarebo Akpos

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This paper is on non-parametric linear regression over its parametric counterparts with large sample size. Data set on anthropometric measurement of primary school pupils was taken for the analysis. The study used 50 randomly selected pupils for the study. The set of data was subjected to normality test, and it was discovered that the residuals are not normally distributed (i.e. they do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Anderson-Darling technique. The algorithms for the nonparametric Theil’s regression are stated in this paper as well as its parametric OLS counterpart. The use of a programming language software known as “R Development” was used in this paper. From the analysis, the result showed that there exists a significant relationship between the response and the explanatory variable for both the parametric and non-parametric regression. To know the efficiency of one method over the other, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) are used, and it is discovered that the nonparametric regression performs better than its parametric regression counterparts due to their lower values in both the AIC and BIC. The study however recommends that future researchers should study a similar work by examining the presence of outliers in the data set, and probably expunge it if detected and re-analyze to compare results.

Keywords: Theil’s regression, Bayesian information criterion, Akaike information criterion, OLS

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Authors: Rana Gill, Chandandeep Kaur

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Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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Authors: Jun Hong Lee

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Background: Alzheimer`s disease (AD) I: creases with age and is characterized by the premature progressive loss of neuronal cell. In contrast, cancer cells have inappropriate cell proliferation and resistance to cell death. Objective: We evaluated the association between cancer and AD and also examined the specific types of cancer. Patients and Methods/Material and Methods: This retrospective, nationwide, longitudinal study used National Health Insurance Service – Senior cohort (NHIS-Senior) 2002-2013, which was released by the KNHIS in 2016, comprising 550,000 random subjects who were selected from over than 60. The study included a cohort of 4,408 patients who were first diagnoses as AD between 2003 and 2005. To match each dementia patient, 19,150 subjects were selected from the database by Propensity Score Matching. Results: We enrolled 4,790 patients for analysis in this cohort and the prevalence of AD was higher in female (19.29%) than in male (17.71%). A higher prevalence of AD was observed in the 70-84 year age group and in the higher income status group. A total of 540 cancers occurred within the observation interval. Overall cancer was less frequent in those with AD (12.25%) than in the control (18.46%), with HR 0.704 (95% Confidence Intervals (CIs)=0.0.64-0.775, p-Value < 0.0001). Conclusion: Our data showed a decreased incidence of overall cancers in patients with AD similar to previous studies. Patients with AD had a significantly decreased risk of colon & rectum, lung and stomach cancer. This finding lower than but consistent with Western countries. We need further investigation of genetic evidence linking AD to cancer.

Keywords: Alzheimer, cancer, nationwide, longitudinal study

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

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Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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Authors: Alamgir Naushad, Ghulam Abbas, Shehzad Ali Shah, Ziaul Haq Abbas

Abstract:

Unlike conventional networks, it is particularly challenging to manage resources efficiently in Wireless Sensor Networks (WSNs) due to their inherent characteristics, such as dynamic network topology and limited bandwidth and battery power. To ensure energy efficiency, this paper presents a routing protocol for WSNs, namely, Enhanced Hybrid Multipath Routing (EHMR), which employs hierarchical clustering and proposes a next hop selection mechanism between nodes according to a maximum residual energy metric together with a minimum hop count. Load-balancing of data traffic over multiple paths is achieved for a better packet delivery ratio and low latency rate. Reliability is ensured in terms of higher data rate and lower end-to-end delay. EHMR also enhances the fast-failure recovery mechanism to recover a failed path. Simulation results demonstrate that EHMR achieves a higher packet delivery ratio, reduced energy consumption per-packet delivery, lower end-to-end latency, and reduced effect of data rate on packet delivery ratio when compared with eminent WSN routing protocols.

Keywords: energy efficiency, load-balancing, hierarchical clustering, multipath routing, wireless sensor networks

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Authors: Nadia Samantha Zuñiga-Peña, Norberto Hernández-Romero, Omar Aguilar-Mejia, Salatiel García-Nava

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Using unmanned aerial vehicles (UAVs) for load transport has gained significant importance in various sectors due to their ability to improve efficiency, reduce costs, and access hard-to-reach areas. Although UAVs offer numerous advantages for load transport, several complications and challenges must be addressed to exploit their potential fully. Complexity relays on UAVs are underactuated, non-linear systems with a high degree of coupling between their variables and are subject to forces with uncertainty. One of the biggest challenges is modeling and controlling the system formed by UAVs carrying a load. In order to solve the controller problem, in this work, a hybridization of Neural Network and Hunger Games Search (HGS) metaheuristic algorithm is developed and implemented to find the parameters of the Super Twisting Sliding Mode Controller for the 8 degrees of freedom model of UAV with payload. The optimized controller successfully tracks the UAV through the three-dimensional desired path, demonstrating the effectiveness of the proposed solution. A comparison of performance shows the superiority of the neural network HGS (NNHGS) over the HGS algorithm, minimizing the tracking error by 57.5 %.

Keywords: neural networks, hunger games search, super twisting sliding mode controller, UAVs.

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