Search results for: low data rate

Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Hammad Khan, Wookeun Bae

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Major concerns regarding nitritation of low-strength ammonium wastewaters include low ammonium loading rates (usually below 0.2 kg/m3-d) and uncertainty about long-term stability of the process. The purpose of this study was to test a sequencing batch reactor (SBR) filled with cell-immobilized polyethylene glycol (PEG) pellets to see if it could achieve efficient and stable nitritation under various environmental conditions. SBR was fed with synthetic ammonium wastewater of 30±2 mg-N/L and pH: 8±0.05, maintaining the dissolved oxygen concentration of 1.7±0.2 mg/L and the temperature at 30±1oC. The reaction was easily converted to partial nitrification mode within a month by feeding relatively high ammonium substrate (~100 mg-N/L) in the beginning. We observed stable nitritation over 300 days with high ammonium loading rates (as high as ~1.1 kg-N/m3-d), nitrite accumulation rates (mostly over 97%) and ammonium removal rate (mostly over 95%). DO was a major limiting substrate when the DO concentration was below ~4 mg/L and the NH4+-N concentration was above 5 mg/L, giving almost linear increase in the ammonium oxidation rate with the bulk DO increase. Low temperatures mainly affected the reaction rate, which could be compensated for by increasing the pellet volume (i.e. biomass). Our results demonstrated that an SBR filled with small cell-immobilized PEG pellets could achieve very efficient and stable nitritation of a low-strength ammonium wastewater.

Keywords: ammonium loading rate (ALR), cell-immobilization, long-term nitritation, sequencing batch reactor (SBR), sewage treatment

Procedia PDF Downloads 256

Authors: Chia-Jung Chang, Sheng-Che Chen, Ming-Long Yeh, Chih-Wei Wang, Chih-Han Chang

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Introduction and Motivation: In recent years, magnesium alloy is used to be a kind of medical biodegradable materials. Magnesium is an essential element in the body and is efficiently excreted by the kidneys. Furthermore, the mechanical properties of magnesium alloy is closest to human bone. However, in some cases magnesium alloy corrodes so quickly that it would release hydrogen on surface of implant. The other product is hydroxide ion, it can significantly increase the local pH value. The above situations may have adverse effects on local cell functions. On the other hand, nowadays magnesium alloy corrode too fast to maintain the function of implant until the healing of tissue. Therefore, much recent research about magnesium alloy has focused on controlling the corrosion rate. The in vitro corrosion behavior of magnesium alloys is affected by many factors, and pH value is one of factors. In this study, we will study on the influence of pH value on the corrosion behavior of magnesium alloy by the Micro-CT (micro computed tomography) and other instruments.Material and methods: In the first step, we make some guiding plates for specimens of magnesium alloy AZ91 by Rapid Prototyping. The guiding plates are able to be a standard for the degradation of specimen, so that we can use it to make sure the position of specimens in the CT image. We can also simplify the conditions of degradation by the guiding plates.In the next step, we prepare the solution with different pH value. And then we put the specimens into the solution to start the corrosion test. The CT image, surface photographs and weigh are measured on every twelve hours. Results: In the primary results of the test, we make sure that CT image can be a way to quantify the corrosion behavior of magnesium alloy. Moreover we can observe the phenomenon that corrosion always start from some erosion point. It’s possibly based on some defect like dislocations and the voids with high strain energy in the materials. We will deal with the raw data into Mass Loss (ML) and corrosion rate by CT image, surface photographs and weigh in the near future. Having a simple prediction, the pH value and degradation rate will be negatively correlated. And we want to find out the equation of the pH value and corrosion rate. We also have a simple test to simulate the change of the pH value in the local region. In this test the pH value will rise to 10 in a short time. Conclusion: As a biodegradable implant for the area with stagnating body fluid flow in the human body, magnesium alloy can cause the increase of local pH values and release the hydrogen. Those may damage the human cell. The purpose of this study is finding out the equation of the pH value and corrosion rate. After that we will try to find the ways to overcome the limitations of medical magnesium alloy.

Keywords: magnesium alloy, biodegradable materials, corrosion, micro-CT

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Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya

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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.

Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation

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Authors: Mefleh Hamideen

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In this investigation, the activity concentrations of ²²⁶Ra, ²³²Th, and ⁴⁰K, of some ceramic tile materials used in the local market of Jordan for interior decoration were determined by making use of High Purity Germanium (HPGe) detector. Twenty samples of the different countries of origin and sizes used in Jordan were analyzed. The concentration values of the last-mentioned radionuclides ranged from 30 Bq.kg⁻¹ (Sample from Jordan) to 98 Bq.kg⁻¹ (Sample from China) for ²²⁶Ra, 31 Bq.kg⁻¹ (Sample from Italy) to 98 Bq.kg⁻¹ (Sample from China) for ²³²Th, and 129 Bq.kg⁻¹ (Sample from Spain) to 679 Bq.kg⁻¹ (Sample from Italy) for ⁴⁰K. Based on the calculated activity concentrations, some radiological parameters have been calculated to test the radiation hazards in the ceramic tiles. In this work, the following parameters: Total absorbed dose rate (DR), Annual effective dose rate (HR), Radium equivalent activity (Raeq), Radon emanation coefficient F (%) and Radon mass exhalation rate (Em) were calculated for all ceramic tiles and listed in the body of the work. Fortunately, the average calculated values of all parameters are less than the recommended values for each parameter. Consequently, almost all the examined ceramic materials appear to have low radon emanation coefficients. As a result of that investigation, no problems on people can appear by using those ceramic tiles in Jordan.

Keywords: radon emanation coefficient, radon mass exhalation rate, total annual effective dose, radon level

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Authors: Luksanaporn Krungkraipetch

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Pterygium is a frequent ocular surface lesion that begins in the limbal conjunctiva within the palpebral fissure and spreads to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a wing-like aspect. Indications for surgery, in decreasing order of significance, are growth over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and esthetic concerns. The aim of this study is twofold: first, to determine the frequency of pterygium recurrence after surgery at the mentioned hospital, and second, to identify the factors that influence the recurrence of pterygium. The research design is a retrospective examination of 164 patient samples in an eastern Thai university hospital (Code 13766). Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium, and for factor analysis, the inferential statistics chi-square and ANOVA are utilized. Twenty-four of the 164 patients who underwent surgery exhibited recurrent pterygium. Consequently, the incidence of recurrent pterygium after surgery was 14.6%. There were an equal number of men and women present. The participants' ages ranged from 41 to 60 years (62, 8 percent). According to the findings, the majority of patients were female (60.4%), over the age of 60 (51.2%), did not live near the beach (83.5%), did not have an underlying disease (92.1%), and 95.7% did not have any other eye problems. Gender (X² = 1.26, p = .289), age (X² = 5.86, p = .119), an address near the sea (X² = 3.30, p = .081)), underlying disease (X² = 0.54, p = .694), and eye disease (X² = 0.00, p = 1.00) had no effect on pterygium recurrence. Recurrences occurred in 79.1% of all surgical procedures and 11.6% of all patients using the bare sclera technique. The recurrence rate for conjunctival autografts was 20.9% for all procedures and 3.0% for all participants. Mitomycin-C and amniotic membrane transplant techniques had no recurrence following surgery. Comparing the surgeries done on people with recurrent pterygium did not show anything important (F = 1.13, p = 0.339). In conclusion, the prevalence of pterygium recurrence following pterygium, 14.6%, does not differ from earlier research. Underlying disease, other eye conditions, and surgical procedures such as pterygium recurrence are unaffected by pterygium surgery.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Abdulkarim Yusuf

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Motivation: The Nigerian economy has seen significant macroeconomic instability, fuelled mostly by an overreliance on fluctuating oil revenues. The rising disparity between tax receipts and government spending in Nigeria necessitates government borrowing to fund the anticipated pace of economic growth. Rising public debt and fiscal sustainability are limiting the government's ability to invest in key infrastructure that promotes private investment and growth in Nigeria. Objective: This paper fills an empirical research vacuum by examining the impact of public debt on fiscal sustainability in Nigeria, given the significance of fiscal stability in decreasing poverty and the constraints that an unsustainable debt burden imposes on it. Data and method: Annual time series data covering the period 1980 to 2022 exposed to conventional and structural breaks stationarity tests and the Autoregressive Distributed Lag estimation approach were adopted for this study. Results: The results reveal that domestic debt stock, debt service payment, foreign reserve stock, exchange rate, and private investment all had a major adverse effect on fiscal stability in the long and short run, corroborating the debt overhang and crowding-out hypothesis. External debt stock, prime lending rate, and degree of trade openness, which boosted fiscal stability in the long run, had a major detrimental effect on fiscal stability in the short run, whereas foreign direct investment inflows had an important beneficial impact on fiscal stability in both the long and short run. Implications: The results indicate that fiscal measures that inspire domestic resource mobilization, sustainable debt management techniques, and dependence on external debt to boost deficit financing will improve fiscal stability and drive growth.

Keywords: ARDL co-integration, debt overhang, debt servicing, fiscal stability, public debt

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Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

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In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Ola A. Nassr, Ali M. Abd Alridha, Rua A. Naser, Rasha S. Abbas

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Background: Excessive and inappropriate use of antimicrobial agents among hospitalized patients remains an important patient safety and public health issue worldwide. Not only does this behavior incur unnecessary cost but it is also associated with increased morbidity and mortality. The objective of this study is to obtain an insight into the prescribing patterns of antibiotics in surgical and medical wards, to help identify a scope for improvement in service delivery. Method: A simple point prevalence survey included a convenience sample of 200 patients admitted to medical and surgical wards in a government teaching hospital in Baghdad between October 2017 and April 2018. Data were collected by a trained pharmacy intern using a standardized form. Patient’s demographics and details of the prescribed antibiotics, including dose, frequency of dosing and route of administration, were reported. Patients were included if they had been admitted at least 24 hours before the survey. Patients under 18 years of age, having a diagnosis of cancer or shock, or being admitted to the intensive care unit, were excluded. Data were checked and entered by the authors into Excel and were subjected to frequency analysis, which was carried out on anonymized data to protect patient confidentiality. Results: Overall, 88.5% of patients (n=177) received 293 antibiotics during their hospital admission, with a small variation between wards (80%-97%). The average number of antibiotics prescribed per patient was 1.65, ranging from 1.3 for medical patients to 1.95 for surgical patients. Parenteral third-generation cephalosporins were the most commonly prescribed at a rate of 54.3% (n=159) followed by nitroimidazole 29.4% (n=86), quinolones 7.5% (n=22) and macrolides 4.4% (n=13), while carbapenems and aminoglycosides were the least prescribed together accounting for only 4.4% (n=13). The intravenous route was the most common route of administration, used for 96.6% of patients (n=171). Indications were reported in only 63.8% of cases. Culture to identify pathogenic organisms was employed in only 0.5% of cases. Conclusion: Broad-spectrum antibiotics are prescribed at an alarming rate. This practice may provoke antibiotic resistance and adversely affect the patient outcome. Implementation of an antibiotic stewardship program is warranted to enhance the efficacy, safety and cost-effectiveness of antimicrobial agents.

Keywords: Acute care, Antibiotic misuse, Iraq, Prescribing

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Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu

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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.

Keywords: evaporator, heat pump, hybrid, laundry dryer, textile

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Authors: Ahmed A. Abdel-Khalek, Reham A. Mohamed

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The kinetics of oxidation of binary complex [CrIII(DMG)2(H2O)4 ]+ to Cr(VI) by periodate has been investigated spectrophotometrically where, [DMG= Dimethylglyoxime] at 370nm under pseudo first order reaction conditions in aqueous medium over 20- 40ºC range, PH 2-3, and I=0.07 mol dm-3. The reaction is first order with respect to both [IO4-] and Cr(III), and the reaction increased with PH increased. Thermodymanic activation parameters have been calculated. It is suggested that electron transfer proceeds through an inner sphere mechanism via coordination of IO4- to Cr (III). The reaction obeys the following rate law Rate= {k1 K5+ k2 K6 K2 } [Cr III (DMG)2(H2O)4 ]+ [H5IO6].

Keywords: chromium, dimethylglyoxime, kinetics, oxidation, periodate

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Authors: Hamed Saremi, Shahla Saremi

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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

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Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

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Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

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Authors: Muhammad Saad, AzherBaig, Anwar Maqsood, Muhammad Waseem

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The grey wolf has been ranked endangered and Asiatic jackal as near threatened in Pakistan. Scientific data on population and threats to these species are not available in Pakistan, which is required for their proper management and conservation. The present study was conducted to collect data on distribution range, population status and threats to both of these Canis species in Lehri Nature Park. The data were collected using direct observations and indirect signs in the field. The population of grey wolf and Asiatic jackal were scattered into pocket of the study area and its surroundings. The current population of grey wolf was estimated 06 individuals and that of Asiatic jackal 28 individuals in the study area. The present study showed that grey wolf and Asiatic jackal were distributed in the northern and southern part of the study area having dense vegetation cover of tress and shrub between the altitudes of 330 m and 515 m. The research finding revealed that the scrub forest is the most preferred habitat of both the species but due to anthropogenic pressure the scrub forest is under severe threat. The dominant trees species were Acacia modesta, Zizyphus nummularia, and Prosopis juliflora and shrubs species of Dodonea-viscosa, Calotropis procera and Adhatoda vasica. Urial is one of the natural prey species: their population is low due to a number of reasons and therefore the maximum dependence of the wolves was on the livestock of the local and nomadic shepherds. The main prey species in the livestock was goats and sheep. The interviews were conducted with the eye witnesses of wolf attacks including livestock being killed by 5-6 numbers of wolves in different hamlets in the study area. The killing rate of the livestock by the wolves was greater when the nomadic shepherds were present in the area and decreased when they left the area. Presence of nomadic shepherds and killing rate has relation with the shifting of the wolves from the study area. It is further concluded that the population of the grey wolf and Asiatic jackal has decreased over time due to less availability of the natural prey species and habitat destruction.

Keywords: wildlife ecology, population conservation, rehabilitation, conservation

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Raquel Balon Quintana

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This study aims to help the Students-At-Risk of Dropping Out to finish their studies in their grade/year level category for this school year by finding out students’ behavior in and out the school, community involvement in the learning process and the causes or reasons behind drop-out rate that affect the performance level of the school. This study also looked for the intervention measures to reduce the drop-out rate of the school. The Normative Survey Method of research was used to achieve its purpose and objective of conducting interview with students and their parents, subject teachers, classmates and friends; undertaking observation and monitoring to find out the whereabouts of SARDO’s on and off classes hours; using questionnaires; and conducting home visitation to be able to link the community involvement into dropping-out of student. Results of the study revealed that out of 32 Students-At-Risk of Dropping Out, 50% were over age for high school (16 years old to 21 years old) while the other 50% came from the regular high school students. These 16 students came from the 41 students who dropped-out from their classes last school year. All Students-At-Risk of Dropping-Out are single and seventy-eight percent of them are male. Top five (5) among the factors that affect their school performance were peer pressure, self-drive, malnutrition, family problem/support and truancy. The five (5) least factors that affect their schooling were problems within their community, school-administration factor, harassment, teacher factor and distance from the school.

Keywords: students-at-risk of dropping-out, drop-out rate, Leocadio Alejo Entienza High School, Philippines

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Authors: Chellammal Surianarayanan

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Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

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Authors: Kanica Goel, Nilam

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Infectious diseases are a leading cause of death worldwide and hence a great challenge for every nation. Thus, it becomes utmost essential to prevent and reduce the spread of infectious disease among humans. Mathematical models help to better understand the transmission dynamics and spread of infections. For this purpose, in the present article, we have proposed a nonlinear time-delayed SVIRS (Susceptible-Vaccinated-Infected-Recovered-Susceptible) mathematical model with nonlinear type incidence rate and nonlinear type treatment rate. Analytical study of the model shows that model exhibits two types of equilibrium points, namely, disease-free equilibrium and endemic equilibrium. Further, for the long-term behavior of the model, stability of the model is discussed with the help of basic reproduction number R₀ and we showed that disease-free equilibrium is locally asymptotically stable if the basic reproduction number R₀ is less than one and unstable if the basic reproduction number R₀ is greater than one for the time lag τ≥0. Furthermore, when basic reproduction number R₀ is one, using center manifold theory and Casillo-Chavez and Song theorem, we showed that the model undergoes transcritical bifurcation. Moreover, numerical simulations are being carried out using MATLAB 2012b to illustrate the theoretical results.

Keywords: nonlinear incidence rate, nonlinear treatment rate, stability, time delayed SVIRS epidemic model

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

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Authors: Serier Bouchenak NORA, Bouguerni ABDELMADJID

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Algeria is a Mediterranean country which provides an ideal habitat for a wide range of species of medicinal plants. The objective of this current work is to extract the gel contained in the leaves of Aloe vera in order to formulate an oral gel as a prebiotic and see its effects on probiotics (lactic and pseudo lactic bacteria and bifido bacterium). Aloe vera polysaccharid extract is a matrix mainly composed of non-digestible oligosaccharids or slow-fermentation polysaccharids, as this produces a lower pH. The behavior of Aloe vera during in vitro fermentation of the colon was similar to that of lactulose, indicating the possibility of using Aloe vera and its polysaccharids extracts as a prebiotic. The microbiological control of the two kinds of bacteria (bifidobacteria and staphylococci) has demonstrated the gel capacity to stimulate them by these bioactive compounds. The generation time of Bifidobacteria in fermented milk with added prebiotic Aloe vera gel is 80.408 min with a µ growth rate equal to 0.012 min -1. The doubling time is 61.459 min with a growth rate µ equal to 0.016 min -1 for the Streptococcus sp. species.

Keywords: aloe vera, probiotics, prebiotics, growth rate, bifidobacteria

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

Abstract:

Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Yosika Dian Komala, Uke Kurniawan Usman, Yuyun Siti Rohmah

Abstract:

The enable technology fills up needs of high-speed data service is Universal Mobile Telecommunications Service (UMTS). UMTS has a data rate up to 2Mbps.UMTS terrestrial system has a coverage area about 1-2km. High Altitude Platform Station (HAPS) can be built by a macro cell that is able to serve the wider area. Design method of UMTS using HAPS is planning base on coverage and capacity. The planning method is simulated with 2.8.1 Atoll’s software. Determination of radius of the cell based on the coverage uses free space loss propagation model. While the capacity planning to determine the average cell through put is available with the Offered Bit Quantity (OBQ).

Keywords: UMTS, HAPS, coverage planning, capacity planning, signal level, Ec/Io, overlapping zone, throughput

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Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay

Abstract:

One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.

Keywords: big data, data analytics, higher education, republic of the philippines, assessment

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Authors: Mahmoud Said Jneid, Péter Harth

Abstract:

EVs with independent wheel driving greatly improve vehicle stability in poor road conditions. Wheel torques can be precisely controlled through electric motors driven using advanced technologies. As a result, various types of advanced chassis assistance systems (ACAS) can be implemented. This paper proposes an integrated torque vectoring control based on wheel slip regulation in both braking and traction modes. For generating the corrective yaw moment, the vehicle yaw rate and sideslip angle are monitored. The corrective yaw moment is distributed into traction and braking torques based on an equal-opposite components approach. The proposed torque vectoring control scheme is validated in simulation and the results show its superiority when compared to conventional schemes.

Keywords: all-wheel-drive, electric vehicle, torque vectoring, regenerative braking, stability control, traction control, yaw rate control

Procedia PDF Downloads 69

Authors: Anurag Sharma, Manoj Kumar, Ashima, Sooraj Parkash

Abstract:

The work in this paper presents simulative comparison for different modulation formats such as NRZ, Manchester and CRZ in a 100 subscribers at 5 Gbps bit rate Gigabit Ethernet Passive Optical Network (GEPON) FTTH network. It is observed from the simulation results that the CRZ modulation format is best suited for the designed system. A link design for 1:100 splitter is used as Passive Optical Network (PON) element which creates communication between central offices to different users. The Bit Error Rate (BER) is found to be 2.8535e-10 at 5 Gbit/s systems for CRZ modulation format.

Keywords: PON , FTTH, OLT, ONU, CO, GEPON

Procedia PDF Downloads 684

Authors: M. S. Nandana, K. Udaya Bhat, C. M. Manjunatha

Abstract:

In this study aluminum alloy 7010 was subjected to three different ageing treatments i.e., peak ageing (T6), over-ageing (T7451) and retrogression and re ageing (RRA) to study the influence of precipitate microstructure on the fatigue crack growth rate behavior. The microstructural modification was studied by using transmission electron microscope (TEM) to examine the change in the size and morphology of precipitates in the matrix and on the grain boundaries. The standard compact tension (CT) specimens were fabricated and tested under constant amplitude fatigue crack growth tests to evaluate the influence of heat treatment on the fatigue crack growth rate properties. The tests were performed in a computer-controlled servo-hydraulic test machine applying a load ratio, R = 0.1 at a loading frequency of 10 Hz as per ASTM E647. The fatigue crack growth was measured by adopting compliance technique using a CMOD gauge attached to the CT specimen. The average size of the matrix precipitates were found to be of 16-20 nm in T7451, 5-6 nm in RRA and 2-3 nm in T6 conditions respectively. The grain boundary precipitate which was continuous in T6, was disintegrated in RRA and T7451 condition. The PFZ width was lower in RRA compared to T7451 condition. The crack growth rate was higher in T7451 and lowest in RRA treated alloy. The RRA treated alloy also exhibits an increase in threshold stress intensity factor range (∆Kₜₕ). The ∆Kₜₕ measured was 11.1, 10.3 and 5.7 MPam¹/² in RRA, T6 and T7451 alloys respectively. The fatigue crack growth rate in RRA treated alloy was nearly 2-3 times lower than that in T6 and was one order lower than that observed in T7451 condition. The surface roughness of RRA treated alloy was more pronounced when compared to the other conditions. The reduction in fatigue crack growth rate in RRA alloy was majorly due to the increase in roughness and partially due to increase in spacing between the matrix precipitates. The reduction in crack growth rate and increase in threshold stress intensity range is expected to benefit the damage tolerant capability of aircraft structural components under service loads.

Keywords: damage tolerance, fatigue, heat treatment, PFZ, RRA

Procedia PDF Downloads 139