Search results for: vector borne diseases

Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: J. S. Kim

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This paper presents a 0.13-µm Complementary Metal-Oxide Semiconductor (CMOS) vector modulator for beamforming system. The vector modulator features a 360° phase and gain range of -10 dB to 10 dB with a root mean square phase and amplitude error of only 2.2° and 0.45 dB, respectively. These features make it a suitable for wireless backhaul system in the 5 GHz industrial, scientific, and medical (ISM) bands. It draws a current of 20.4 mA from a 1.2 V supply. The total chip size is 1.87x1.34 mm².

Keywords: CMOS, vector modulator, beamforming, 802.11ac

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Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki

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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.

Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Mansur Abdulrasheed, Ibrahim I. Hussein, Ahmed M. Mubarak, Ahmed F. Umar

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This study was aimed at evaluating the phytochemical constituents and the antimicrobial activity of the seed oil of Moringa oleifera and garlic against some selected food-borne microorganisms (Staphylococcus aureus, Escherichia coli, Salmonella spp and Pseudomonas aeruginosa) using disc diffusion method. The results of the phytochemical screening revealed differences in the presence of the phytochemicals among the extracts. Saponins were detected in both Moringa oleifera and garlic seed oil, while alkaloid and tannins were observed in seed oil of garlic. Furthermore, the antibacterial assay results show that the seed oil of Moringa oleifera was inactive against all the tested organisms, even at 100 % concentration. In contrast, garlic oil was found to be active against all the tested organisms. The highest inhibition was observed in E. coli (12 mm) at 100 % concentration, while at 20 % concentration, Salmonella Sp and P. aeruginosa showed the least inhibiton (6 mm). The antimicrobial activity of the seed oil of garlic may be attributed to its phytochemicals components which were not detected in the seed oil of Moringa oleifera. The results of this study have shown the potentials of the seed oil of garlic as an antimicrobial agent more especially in foods, by inhibiting the growth of the test organisms, which range from food-borne pathogens to food spoilage organisms.

Keywords: antimicrobial, garlic, Moringa oleifera, food borne pathogens

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Authors: Mansur Abdulrasheed, Ibrahim I. Hussein, Ahmed M. Mubarak, Ahmed F. Umar

Abstract:

This study was aimed at evaluating the phytochemical constituents and the antimicrobial activity of the seed oil of Moringa oleifera and garlic against some selected food-borne microorganisms (Staphylococcus aureus, Escherichia coli, Salmonella spp and Pseudomonas aeruginosa) using disc diffusion method. The results of the phytochemical screening revealed differences in the presence of the phytochemicals among the extracts. Saponins were detected in both Moringa oleifera and garlic seed oil, while alkaloid and tannins were observed in seed oil of garlic. Furthermore, the antibacterial assay results show that the seed oil of Moringa oleifera was inactive against all the tested organisms, even at 100 % concentration. In contrast, garlic oil was found to be active against all the tested organisms. The highest inhibition was observed in E. coli (12 mm)at 100 % concentration, while at 20 % concentration, Salmonella Sp and P. aeruginosa showed the least inhibit on (6 mm). The antimicrobial activity of the seed oil of garlic may be attributed to its phytochemicals components which were not detected in the seed oil of Moringa oleifera. The results of this study have shown the potentials of the seed oil of garlic as an antimicrobial agent more especially in foods, by inhibiting the growth of the test organisms, which range from food-borne pathogens to food spoilage organisms.

Keywords: antimicrobial, garlic, Moringa oleifera, food borne pathogens

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Authors: Huai-Cong Liu, Tae Chul Jeong, Ju Lee

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The aim of this study was to develop an electric circuit method (ECM) to ascertain the core loss influence on a Synchronous Reluctance Motor (SynRM) in the condition of the maximum torque per ampere (MTPA). SynRM for fan usually operates on the constant torque region, at synchronous speed the MTPA control is adopted due to current vector. However, finite element analysis (FEA) program is not sufficient exactly to reflect how the core loss influenced on the current vector. This paper proposed a method to calculate the current vector with consideration of core loss. The precision of current vector by ECM is useful for MTPA control. The result shows that ECM analysis is closer to the actual motor’s characteristics by testing with a 7.5kW SynRM drive System.

Keywords: core loss, SynRM, current vector, magnetic saturation, maximum torque per ampere (MTPA)

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Authors: Ji Xi, Cheng Song Chin, Ehsan Mesbahi

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Structure-borne noise is an important aspect of offshore platform sound field. It can be generated either directly by vibrating machineries induced mechanical force, indirectly by the excitation of structure or excitation by incident airborne noise. Therefore, limiting of the transmission of vibration energy throughout the offshore platform is the key to control the structure-borne noise. This is usually done by introducing damping treatment to the steel structures. Two types of damping treatment using on-board are presented. By conducting a statistical energy analysis (SEA) simulation on a jack-up rig, the noise level in the source room, the neighboring rooms, and remote living quarter cabins are compared before and after the damping treatments been applied. The results demonstrated that, in the source neighboring room and living quarter area, there is a significant noise reduction with the damping treatment applied, whereas in the source room where air-borne sound predominates that of structure-borne sound, the impact is not obvious. The subsequent optimization design of damping treatment in the offshore platform can be made which enable acoustic professionals to implement noise control during the design stage for offshore crews’ hearing protection and habitant comfortability.

Keywords: statistical energy analysis, damping treatment, noise control, offshore platform

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Chandan Kumar

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Background and Context: Population growth and rapid urbanization resulted nearly 2 Lacs migrants along with families moving to Delhi each year in search of jobs. Most of these poor migrant families end up living in slums and constitute an estimated population of 1.87 lacs every year. Further, more than half (52 per cent) of Delhi’s population resides in places such as unauthorized and resettled colonies. Slum population is fully dependent on public toilet to defecate. In Public toilets, manholes either connected with Sewer line or septic tank. Septic tank connected public toilet faces major challenges to dispose of waste water. They have to dispose of waste water in outside open drain and waste water struck out side of public toilet complex and near to the slum area. As a result, outbreak diseases such as Malaria, Dengue and Chikungunya in slum area due to stagnated waste water. Intervention and Innovation took place by Save the Children in 21 Public Toilet Complexes of South Delhi and North Delhi. These public toilet complexes were facing same waste water disposal problem. They were disposing of minimum 1800 liters waste water every day in open drain. Which caused stagnated water-borne diseases among the nearest community. Construction of Soak Well: Construction of soak well in urban context was an innovative approach to minimizing the problem of waste water management and increased water table of existing borewell in toilet complex. This technique made solution in Ground water recharging system, and additional water was utilized in vegetable gardening within the complex premises. Soak well had constructed with multiple filter media with inlet and safeguarding bed on surrounding surface. After construction, soak well started exhausting 2000 liters of waste water to raise ground water level through different filter media. Finally, we brought a change in the communities by constructing soak well and with zero maintenance system. These Public Toilet Complexes were empowered by safe disposing waste water mechanism and reduced stagnated water-borne diseases.

Keywords: diseases, ground water recharging system, soak well, toilet complex, waste water

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Authors: Basavaraj Yenagi, P. Nagaraju, C. R. Patil

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Groundnut (Arachis hypohaea L.) is called as “King of oilseeds” and one of the most important food and cash crops in Indian subcontinent. Yield and quality of oil are negatively correlated with poor or imbalanced nutrition and constant exposure to both biotic and abiotic stress factors. Variety of diseases affect groundnut plant, most of them are caused by fungi and lead to severe yield loss. Imbalanced nutrition increases the concerns of environmental deterioration which includes soil fertility. Among different microbial antagonists, Pseudomonas is common member of the plant growth promoting rhizobacteria microflora present in the rhizosphere of groundnut. These are known to produce a beneficial effect on groundnut due to their high metabolic activity leading to the production of enzymes, exopolysaccharides, secondary metabolites, and antibiotics. The ability of pseudomonas lies on their ability to produce antibiotic metabolites such as 2, 4-diacetylphloroglucinol (DAPG). DAPG can inhibit the growth of fungal pathogens namely collar rot and stem rot and also increase the availability of plant nutrients through increased solubilization and uptake of nutrients. Hence, the present study was conducted for three consecutive years (2014 to 2016) in vertisol during the rainy season to assess the efficacy of DAPG producing fluorescent pseudomonas for enhancing nutrient use efficacy, bio-control of soil-borne diseases and yield of groundnut at University of Agricultural Sciences, Dharwad farm. The experiment was laid out in an RCBD with three replications and seven treatments. The mean of three years data revealed that the effect of DAPG-producing producing fluorescent pseudomonas enhanced groundnut yield, uptake of nitrogen and phosphorus and nutrient use efficiency and also found to be effective in bio-control of collar rot and stem rot incidence leading to increase pod yield of groundnut. Higher dry pod yield of groundnut was obtained with DAPG 2(3535 kg ha-1) closely followed by DAPG 4(3492 kg ha-1), FP 98(3443 kg ha-1), DAPG 1(3414 kg ha-1), FP 86(3361 kg ha-1) and Trichoderma spp. (3380 kg ha-1) over control(3173 kg ha-1). A similar trend was obtained with other growth and yield attributing parameters. N uptake ranged from 8.21 percent to FP 86 to 17.91 percent with DAPG 2 and P uptake ranged between 5.56 percent with FP 86 to 16.67 percent with DAPG 2 over control. The first year, there was no incidence of collar rot. During the second year, the control plot recorded 2.51 percent incidence and it ranged from 0.82 percent to 1.43 percent in different DAPG-producing fluorescent pseudomonas treatments. The similar trend was noticed in the third year with lower incidence. The stem rot incidence was recorded during all the three years. Mean data indicated that the control plot recorded 2.65 percent incidence and it ranged from 0.71 percent to 1.23 percent in different DAPG-producing fluorescent pseudomonas treatments. The increase in net monetary benefits ranged from Rs.5975 ha-1 to Rs.11407 ha 1 in different treatments. Hence, as a low-cost technology, seed treatment with available DAPG-producing fluorescent pseudomonas has a beneficial effect on groundnut for enhancing groundnut yield, nutrient use efficiency and bio-control of soil-borne diseases.

Keywords: groundnut, DAPG, fluorescent pseudomonas, nutrient use efficiency, collar rot, stem rot

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Authors: Young Kwon Yang, In Sung Kang, Jung Ha Hwang, Jin Chul Park

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The present study is a foundational study for performance improvements on isolation wards to prevent proliferation of secondary infection of infectious diseases such as SARS, H1N1, and MERS inside hospitals. Accordingly, the present study conducted an analysis of the effect of sealing mechanisms and filling of openings on ensuring air tightness performance in isolation wards as well as simulation on air currents in improved isolation wards. The study method is as follows. First, previous studies on aerial infection type and mechanism were reviewed, and the review results were utilized as basic data of analysis on simulation of air current. Second, national and international legislations and regulations in relation to isolation wards as well as case studies on developed nations were investigated in order to identify the problems in isolation wards in Korea and improvement plans. Third, construction and facility plans were compared and analyzed between general and isolation wards focusing on large general hospitals in Korea, thereby conducting comparison and analysis on the performance and effects of air-tightness of general and isolation wards through CFD simulations. The study results showed that isolation wards had better air-tightness performance than that of general wards.

Keywords: AII Room, air-borne infection, CFD, computational fluid dynamics

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Authors: Folorunsho J. O., Umar M. A.

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Access to potable water supply in both the rural and urban regions of the world has been neglected, and this has severely affected man and the aesthetics of the natural environment of man. This has further worsened the issue of diseases prevalence. This study considered the effects of inadequate domestic water supply on human health in selected neighbourhoods of Lokoja. The study used descriptive statistics such as relative frequencies, percentages and inferential statistics to analyse the data obtained through the use of structured questionnaire. The results revealed that the females and male constituted 56% and 44% of the respondents respectively; 62% of the respondents married and 32% are unmarried; respondents between ages 31 and 40 years constitute majority of the study population, while respondents with tertiary education constituted 35%, and those with secondary education were 32% of the total respondents. Furthermore, civil servants constituted 40% and unemployed 16% of the total respondents. In terms of monthly income, 40% of the respondents was found to earn between ₦31,000 - 40,000 monthly. On the perception of households on the availability and adequacy of domestic water supply, the study revealed that 64.7% of the respondents have pipe-borne water as their main source of water supply, with only 28.5% out of the 64.7% have pipe-borne water supply daily. On the relationship between water supply characteristics and health status among households, the result shows that 76% of the respondents perceived a strong relationship between water supply and health status. Cumulatively, 67% of the respondents confirm that both the quality and quantity of water supplied play a critical role in determining health status of residents of the study area. The respondents also reported skin diseases (96%), diarrhoea (96%), malaria (91%), cholera (67%), dysentery (67%), and respiratory diseases (67%) as the most perceived and experienced in the area, the disease rate in the prevalence order of malaria (81%), diarrhoea (61%), skin diseases (58%), cholera (34%), dysentery (31%) and respiratory disease (14%) respectively. Finally, the results further showed how households cope with inadequate water supply with 52% of the respondents confirm that they regularly treat their water before it was deployed for domestic uses, while 35%, 26%, 25%, 10% and 4% of the 52% respectively, adopted boiling, addition of alums, filtering with fabrics, chlorination and bleaching as the preferred treatment methods. The study thus recommended policy options that will aggressively launch adequate potable water supply infrastructure in the study area.Keywords: Potable Water, Supply, Human Health, Perception, Chlorination

Keywords: potable water, human health, perception, chlorination

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Authors: Mahvish Maqbool, Muhmmad Sohail Sajid

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Ticks (Acari: Ixodidae); bloodsucking parasites of domestic animals, have significant importance in the transmission of diseases and causing huge economic losses. This study aimed to screen endophilic ticks for the Piroplasms using polymerase chain reaction in three districts Sialkot, Gujranwala and Gujarat of Punjab, Pakistan. Ticks were dissected under a stereomicroscope, and internal organs (midguts& salivary glands) were procured to generate pools of optimum weights. DNA extraction was done through standard protocol followed by primer specific PCR for Piroplasma spp. A total of 22.95% tick pools were found positive for piroplasma spp. In districts, Sialkot and Gujranwala Piroplasma prevalence are higher in riverine animals while in Gujarat Prevalence is higher in non-riverine animals. Female animals were found more prone to piroplasma as compared to males. This study will provide useful data on the distribution of Piroplasma in the vector population of the study area and devise future recommendations for better management of ruminants to avoid subclinical and clinical infections and vector transmitted diseases.

Keywords: babesia, hyalomma, piroplasmposis, tick infectivity

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Authors: Sandra Rizkallah, Amir F. Atiya

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This work presents a novel word to vector representation that is based on embedding the words into a sphere, whereby the dot product of the corresponding vectors represents the similarity between any two words. Embedding the vectors into a sphere enabled us to take into consideration the antonymity between words, not only the synonymity, because of the suitability to handle the polarity nature of words. For example, a word and its antonym can be represented as a vector and its negative. Moreover, we have managed to extract an adequate vocabulary. The obtained results show that the proposed approach can capture the essence of the language, and can be generalized to estimate a correct similarity of any new pair of words.

Keywords: natural language processing, word to vector, text similarity, text mining

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Authors: Asad Ali, Asif Jamal

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The agriculture productivity losses due to microbial pathogens have been a serious issue in Pakistan and rest of the world. Present work was designed to isolate soil borne microorganisms having the antagonistic ability against notorious phytopathogens. From the initial collection of 23 bacterial isolates, two potent strains of Bacillus were screened on the basis of their comparative efficacy against devastating fungal pathogens. The strains AK-1 and AK-5 showed excellent inhibitory indexes against the majority of tested fungal strains. It was noted that both strains of Bacillus showed significant biocontrolling activity against Aspergillus flavus, Fusarium moniliforme, Colletotricum falcatum, Botrytis cinerea, Aspergillus niger, Fusarium oxysporum, Phythopthora capsici and Rhizopus oryzae. The strain AK-1 was efficient to suppress Aspergillus species and Rhizopus oryzae while AK-5 expressed significant antagonistic activity against Fusarium, Botrytis and Colletotricum species. On the basis of in vitro assay, it can be postulated that the Bacillus strains AK-1 and AK-5 can be used as bio-protective agent against various plant diseases. In addition, their applications as natural pesticides could be very helpful to prevent the adverse effects of chemical pesticides.

Keywords: bacillus species, biocontrol agent, biopesticides, phytopathogens

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Authors: Asif Jamal, Asad Ali, Muhammad Ishtiaq Ali

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The agriculture productivity losses due to microbial pathogens have been a serious issue in Pakistan and rest of the world. Present work was designed to isolate soil borne microorganisms having the antagonistic ability against notorious phytopathogens. From the initial collection of 23 bacterial isolates, two potent strains of Bacillus were screened on the basis of their comparative efficacy against devastating fungal pathogens. The strains AK-1 and AK-5 showed excellent inhibitory indexes against the majority of tested fungal strains. It was noted that both strains of Bacillus showed significant biocontrolling activity against Aspergillus flavus, Fusarium moniliforme, Colletotricum falcatum, Botrytis cinerea, Aspergillus niger, Fusarium oxysporum, Phythopthora capsici and Rhizopus oryzae. The strain AK-1 was efficient to suppress Aspergillus species and Rhizopus oryzae while AK-5 expressed significant antagonistic activity against Fusarium, Botrytis, and Colletotricum species. On the basis of in vitro assay, it can be postulated that the Bacillus strains AK-1 and AK-5 can be used as a bio-protective agent against various plant diseases. In addition, their applications as natural pesticides could be very helpful to prevent the adverse effects of chemical pesticides.

Keywords: biological control, Bacillus spp, fungal pathogens, agriculture

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Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Stephen Kirkup

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This paper discusses the implementation of the boundary element method (BEM) on an Excel spreadsheet and how it can be used in teaching vector calculus and simulation. There are two separate spreadheets, within which Laplace equation is solved by the BEM in two dimensions (LIBEM2) and axisymmetric three dimensions (LBEMA). The main algorithms are implemented in the associated programming language within Excel, Visual Basic for Applications (VBA). The BEM only requires a boundary mesh and hence it is a relatively accessible method. The BEM in the open spreadsheet environment is demonstrated as being useful as an aid to teaching and learning. The application of the BEM implemented on a spreadsheet for educational purposes in introductory vector calculus and simulation is explored. The development of assignment work is discussed, and sample results from student work are given. The spreadsheets were found to be useful tools in developing the students’ understanding of vector calculus and in simulating heat conduction.

Keywords: boundary element method, Laplace’s equation, vector calculus, simulation, education

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Authors: Sri Yusnita Irda Sari, Deni Kurniadi Sunjaya, Ardini Saptaningsih Raksanagara

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Water is one of the fundamental basic needs for human life, particularly drinking water sources. Although water quality is getting better, fecal-contamination of water is still found around the world, especially in the slum area of mid-low income countries. Drinking water source contamination in urban slum dwellers increases the risk of water borne diseases. Low level of sanitation and poor drinking water supply known as risk factors for diarrhea, moreover bacteria-contaminated drinking water source is the main cause of diarrhea in developing countries. This study aimed to assess risk infection due to Fecal Coliform contamination in various drinking water sources in urban area by applying Quantitative Microbiological Risk Assessment (QMRA). A Cross-sectional survey was conducted in a period of August to October 2015. Water samples were taken by simple random sampling from households in Cikapundung river basin which was one of urban slum area in the center of Bandung city, Indonesia. About 379 water samples from 199 households and 15 common wells were tested. Half of the households used treated drinking water from water gallon mostly refill water gallon which was produced in drinking water refill station. Others used raw water sources which need treatment before consume as drinking water such as tap water, borehole, dug well and spring water source. Annual risk to get infection due to Fecal Coliform contamination from highest to lowest risk was dug well (1127.9 x 10-5), spring water (49.7 x 10-5), borehole (1.383 x 10-5) and tap water (1.121 x 10-5). Annual risk infection of refill drinking water was 1.577 x 10-5 which is comparable to borehole and tap water. Household water treatment and storage to make raw water sources drinkable is essential to prevent risk of water borne diseases. Strong regulation and intense monitoring of refill water gallon quality should be prioritized by the government; moreover, distribution of tap water should be more accessible and affordable especially in urban slum area.

Keywords: drinking water, quantitative microbiological risk assessment, slum, urban

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Authors: Ahmed Abdolkhalig, Rastko Zivanovic

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This paper evaluates the Total Vector Error of an estimated Phasor as define in IEEE C37.118 standard within different medium access in Local Area Networks (LAN). Three different LAN models (CSMA/CD, CSMA/AMP, and Switched Ethernet) are evaluated. The Total Vector Error of the estimated Phasor has been evaluated for the effect of Nodes Number under the standardized network Band-width values defined in IEC 61850-9-2 communication standard (i.e. 0.1, 1, and 10 Gbps).

Keywords: phasor, local area network, total vector error, IEEE C37.118, IEC 61850

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor

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Authors: Muhammad S. Sajid, A. Iqbal, A. Kausar, M. Jawad-ul-Hassan, Z. Iqbal, Hafiz M. Rizwan, M. Saqib

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Among the ixodid ticks, species of genus Hyalomma are of prime importance as they can survive in harsh conditions better than those of other species. Similarly, among various tick-borne pathogens, Theileria (T.) annulata, the causative agent of tropical theileriosis in large ruminants, is responsible for reduced productivity and ultimately substantial economic losses due to morbidity and mortality. The present study was planned to screening of vector ticks through molecular techniques for determination of tick-borne theileriosis in district Toba Tek Singh (T. T. Singh), Punjab, Pakistan. For this purpose, among the collected ticks (n = 2252) from livestock and their microclimate, Hyalomma spp. were subjected to dissection for procurement of salivary glands (SGs) and formation of pool (averaged 8 acini in each pool). Each pool of acini was used for DNA extraction, quantification and primer-specific amplification of 18S rRNA of Theileria (T.) annulata. The amplicons were electrophoresed using 1.8% agarose gel following by imaging to identify the band specific for T. annulata. For confirmation, the positive amplicons were subjected to sequencing, BLAST analysis and homology search using NCBI software. The number of Theileria-infected acini was significantly higher (P < 0.05) in female ticks vs male ticks, infesting ticks vs questing ticks and riverine-collected vs non-riverine collected. The data provides first attempt to quantify the vectoral capacity of ixodid ticks in Pakistan for T. annulata which can be helpful in estimation of risk analysis of theileriosis to the domestic livestock population of the country.

Keywords: Hyalomma anatolicum, ixodids, PCR, Theileria annulata

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Rama Krishna Supramanian, Marzuki Isahak, Noran Naqiah Hairi

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Noise-induced hearing loss (NIHL) is one of the highest recorded occupational diseases, despite being preventable. Hearing Conservation Program (HCP) is designed to protect workers hearing and prevent them from developing hearing impairment due to occupational noise exposures. However, there is still a lack of evidence regarding the effectiveness of this program. The purpose of this study was to determine the effectiveness of a Hearing Conservation Program (HCP) in preventing or reducing audiometric threshold changes among vector control workers. This study adopts a cluster randomized controlled trial study design, with district health offices as the unit of randomization. Nine district health offices were randomly selected and 183 vector control workers were randomized to intervention or control group. The intervention included a safety and health policy, noise exposure assessment, noise control, distribution of appropriate hearing protection devices, training and education program and audiometric testing. The control group only underwent audiometric testing. Audiometric threshold changes observed in the intervention group showed improvement in the hearing threshold level for all frequencies except 500 Hz and 8000 Hz for the left ear. The hearing threshold changes range from 1.4 dB to 5.2 dB with largest improvement at higher frequencies mainly 4000 Hz and 6000 Hz. Meanwhile for the right ear, the mean hearing threshold level remained similar at 4000 Hz and 6000 Hz after 3 months of intervention. The Hearing Conservation Program (HCP) is effective in preserving the hearing of vector control workers involved in fogging activity as well as increasing their knowledge, attitude and practice towards noise-induced hearing loss (NIHL).

Keywords: adult, hearing conservation program, noise-induced hearing loss, vector control worker

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Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

Abstract:

Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

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Authors: E. M. H. Maggie, M. N. A. Nazmey, M. A. Abdel-Sattar, S. A. Saied

Abstract:

A successful trial of transplanting cotton is reported. Seeds grown in trays for 4-5 weeks in an easily prepared supporting medium such as peat moss or similar plant waste are tried. Careful transplanting of seedlings, with root system as intact as possible, is being made in the permanent field. The practice reduced damping-off incidence rate and allowed full winter crop revenues. Further work is needed to evaluate certain parameters such as growth curve, flowering curve, and yield at economic bases.

Keywords: cotton, transplanting cotton, damping-off diseases, environment sciences

Procedia PDF Downloads 340

Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

Abstract:

The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

Procedia PDF Downloads 409

Authors: Sagri Sharma

Abstract:

Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

Procedia PDF Downloads 407

Authors: Ravija Gunawardana, Banuka Athuraliya

Abstract:

Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 113