Search results for: Ride comfort improvement

Authors: A. Rajesh Kanna, G. Suresh Kumar, Sathyanaryana N. Gummadi

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There are various sources of energies available worldwide and among them, crude oil plays a vital role. Oil recovery is achieved using conventional primary and secondary recovery methods. In-order to recover the remaining residual oil, technologies like Enhanced Oil Recovery (EOR) are utilized which is also known as tertiary recovery. Among EOR, Microbial enhanced oil recovery (MEOR) is a technique which enables the improvement of oil recovery by injection of bio-surfactant produced by microorganisms. Bio-surfactant can retrieve unrecoverable oil from the cap rock which is held by high capillary force. Bio-surfactant is a surface active agent which can reduce the interfacial tension and reduce viscosity of oil and thereby oil can be recovered to the surface as the mobility of the oil is increased. Research in this area has shown promising results besides the method is echo-friendly and cost effective compared with other EOR techniques. In our research, on laboratory scale we produced bio-surfactant using the strain Pseudomonas putida (MTCC 2467) and injected into designed simple sand packed column which resembles actual petroleum reservoir. The experiment was conducted in order to determine the efficiency of produced bio-surfactant in oil recovery. The column was made of plastic material with 10 cm in length. The diameter was 2.5 cm. The column was packed with fine sand material. Sand was saturated with brine initially followed by oil saturation. Water flooding followed by bio-surfactant injection was done to determine the amount of oil recovered. Further, the injection of bio-surfactant volume was varied and checked how effectively oil recovery can be achieved. A comparative study was also done by injecting Triton X 100 which is one of the chemical surfactant. Since, bio-surfactant reduced surface and interfacial tension oil can be easily recovered from the porous sand packed column.

Keywords: Bio-surfactant, Bacteria, Interfacial tension, Sand column.

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: Constrained integer problems, enumerative search algorithm, Heuristic algorithm, tunneling algorithm.

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Satyanadh Gundimada, Vijayan K Asari

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A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings (GFBs) are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional (3D) fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: Fluid structure interaction multi-physics simulations, gas foil bearing, oil-free, transient thermohydrodynamic.

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Authors: Nachawit Tikul

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This study aimed to determine low-income housing adaptations for flooding, which causes living problems and housing damage, and the results from improvement. Three low-income settlements in Chiang Mai which experienced different flood types, i.e. flash floods in Samukeepattana, drainage floods in Bansanku, and river floods in Kampangam, were chosen for the study. Almost all of the residents improved their houses to protect the property from flood damage by changing building materials to flood damage resistant materials for walls, floors, and other parts of the structure that were below the base of annual flood elevation. They could only build some parts of their own homes, so hiring skilled workers or contractors was still important. Building materials which have no need for any special tools and are easy to access and use for construction, as well as low cost, are selected for construction. The residents in the three slums faced living problems for only a short time and were able to cope with them. This may be due to the location of the three slums near the city where assistance is readily available. But the housing and the existence in the slums can endure only the regular floods and residence still have problems in unusual floods, which have been experienced 1-2 times during the past 10 years. The residents accept the need for evacuations and prepare for them. When faced with extreme floods, residence have evacuated to the nearest safe place such as schools and public building, and come back to repair the houses after the flood. These are the distinguishing characteristics of low-income living which can withstand serious situations due to the simple lifestyle. Therefore, preparation of living areas for use during severe floods and encouraging production of affordable flood resistant materials should be areas of concern when formulating disaster assistance policies for low income people.

Keywords: Flooding, low-income settlement, housing, adaptation.

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Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

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Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of it over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation, respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model’. The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. A flow-chart showing procedure for compution of deformation and mobilized tension is also incorporated in the paper. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models. 

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

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Authors: Vahid Mazloum, Mansour Sahebozamani, Amirhossein Barati, Nouzar Nakhaee, Pouya Rabiei

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Non-specific chronic low back pain (NSCLBP) is a common condition with no exact diagnosis and mechanism for its occurrence. Recently, different therapeutic exercises have taken into account to manage NSCLBP. So, the aim of this study has mainly been placed on comparing the effects of Pilates and Mackenzie exercises on quality of life (QOL) lumbar spine position sense (LSPS) in patients with NSCLBP. In this randomized clinical trial, 47 patients with NSCLBP were voluntarily divided into three groups of Pilates (n=16) (with mean age 37.1 ± 9.5 years, height 168.9 ± 7.4 cm, body mass 76.1 ± 5.9 k), McKenzie (n=15) (with mean age 42.7 ± 8.1 years, height 165.7 ± 6.8, body mass 74.1 ± 4.8 kg) and control (n=16) (with mean age 39.3 ± 9.8 years, height 168.1 ± 8.1 cm, body mass 74.2 ± 5.8 kg). Primary outcome included QOL and secondary was LSPS. Both variables were assessed by the WHOQOL-BREF questionnaires and electrogoniameter, respectively. The measurements were performed at baseline, following a 6-week intervention, and after a 4-week follow-up. The ANCOVA test at P < 0.05 was administrated to analyze the collected data using SPSS software. There was a statistically significant difference between experimental groups and the control group to improve QOL. But, no difference was seen regarding the effects of two exercises on LSPS (p < 0.05). Both Pilates and Mackenzie exercises demonstrated improvement in QOL after 6-week intervention and a 4-week follow-up while none of them considerably affected LSPS. Further studies are required to establish a supporting evidence for the effectiveness of two exercises on NSCLBP.

Keywords: Pilates, Mackenzie, proprioception, low back pain, physical health.

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Authors: Tahsien Mohamed Okasha, Warda Youssef Mohamed Morsy, Hanan Elsayed Zaghla

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We hypothesized that post cardiac arrest patients with Glasgow Coma Scale (GCS) score of less than 8 and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. 17 subjects were enrolled in this study all over one year. The study was carried out using Quasi-experimental research design. Four tools were used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). The mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% subjects were initially arrested in form of ventricular tachycardia (VT), 23.5% initially arrested in form of ventricular fibrillation (VF), and 29.4% in form of A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also, initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. Therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than 8. Replication of the study on larger probability sample, with randomized control trial design is recommended with further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia is recommended.

Keywords: Therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest, initial arrest rhythm.

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Authors: Mohammad T. Uddin, Aurup R. Dhar

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The study was conducted to assess the impact of conservation agriculture practice on farmers’ socioeconomic condition and soil environmental quality in Bangladesh. A total of 450 (i.e., 50 focal, 150 proximal and 250 control) farmers from five districts were selected for this study. Descriptive statistics like sum, averages, percentages, etc. were calculated to evaluate the socioeconomic data. Using Enyedi’s crop productivity index, it was found that the crop productivity of focal, proximal and control farmers was increased by 0.9, 1.2 and 1.3 percent, respectively. The result of DID (Difference-in-difference) analysis indicated that the impact of conservation agriculture practice on farmers’ average annual income was significant. Multidimensional poverty index (MPI) indicates that poverty in terms of deprivation of health, education and living standards was decreased; and a remarkable improvement in farmers’ socioeconomic status was found after adopting conservation agriculture practice. Most of the focal and proximal farmers stated about increased soil environmental condition where majority of control farmers stated about constant environmental condition in this regard. The Probit model reveals that minimum tillage operation, permanent organic soil cover, and application of compost and vermicompost were found significant factors affecting soil environmental quality under conservation agriculture. Input support, motivation, training programmes and extension services are recommended to implement in order to raise the awareness and enrich the knowledge of the farmers on conservation agriculture practice.

Keywords: Conservation agriculture, crop productivity, socioeconomic status, soil environment quality.

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: Data mining, ensemble, radial basis function, support vector machine, accuracy.

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Authors: Shunya Wakayama, Kazuya Okubo, Toru Fujii, Daisuke Sakata, Noriyuki Kado, Hiroshi Furutachi

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The purpose of this study is to propose an effective method to improve frictional coefficient between shoe rubber soles with added glass fibers and the surfaces of icy and snowy road in order to prevent slip-and-fall accidents by the users. The additional fibers into the rubber were uniformly tilted to the perpendicular direction of the frictional surface, where tilting angles were -60, -30, +30, +60, 90 degrees and 0 (as normal specimen), respectively. It was found that parallel arraignment was effective to improve the frictional coefficient when glass fibers were embedded in the shoe rubber, while perpendicular to normal direction of the embedded glass fibers on the shoe surface was also effective to do that once after they were exposed from the shoe rubber with its abrasion. These improvements were explained by the increase of stiffness against the shear deformation of the rubber at critical frictional state and adequate scratching of fibers when fibers were protruded in perpendicular to frictional direction, respectively. Most effective angle of tilting of frictional coefficient between rubber specimens and a stone was perpendicular (= 0 degree) to frictional direction. Combinative modified rubber specimen having 2 layers was fabricated where tilting angle of protruded fibers was 0 degree near the contact surface and tilting angle of embedded fibers was 90 degrees near back surface in thickness direction to further improve the frictional coefficient. Current study suggested that effective arraignments in tilting angle of the added fibers should be applied in designing rubber shoe soles to keep the safeties for users in regions of cold climates.

Keywords: Frictional coefficient, icy and snowy road, shoe rubber soles, tilting angle.

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Authors: S. Fore, L. Zuze

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Frequent machine breakdowns, low plant availability and increased overtime are a great threat to a manufacturing plant as they increase operating costs of an industry. The main aim of this study was to improve Overall Equipment Effectiveness (OEE) at a manufacturing company through the implementation of innovative maintenance strategies. A case study approach was used. The paper focuses on improving the maintenance in a manufacturing set up using an innovative maintenance regime mix to improve overall equipment effectiveness. Interviews, reviewing documentation and historical records, direct and participatory observation were used as data collection methods during the research. Usually production is based on the total kilowatt of motors produced per day. The target kilowatt at 91% availability is 75 Kilowatts a day. Reduced demand and lack of raw materials particularly imported items are adversely affecting the manufacturing operations. The company had to reset its targets from the usual figure of 250 Kilowatt per day to mere 75 per day due to lower availability of machines as result of breakdowns as well as lack of raw materials. The price reductions and uncertainties as well as general machine breakdowns further lowered production. Some recommendations were given. For instance, employee empowerment in the company will enhance responsibility and authority to improve and totally eliminate the six big losses. If the maintenance department is to realise its proper function in a progressive, innovative industrial society, then its personnel must be continuously trained to meet current needs as well as future requirements. To make the maintenance planning system effective, it is essential to keep track of all the corrective maintenance jobs and preventive maintenance inspections. For large processing plants these cannot be handled manually. It was therefore recommended that the company implement (Computerised Maintenance Management System) CMMS.

Keywords: Maintenance, Manufacturing, Overall Equipment Effectiveness

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Authors: Ching-Tsan Tsai, Sih-Rong Chen, Chi-Hung Hsieh

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The technique of inducing micro ecosystem restoration is one of aquatic ecology engineering methods used to retrieve the polluted water. Batch scale study, pilot plant study, and field study were carried out to observe the eutrophication using the Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting mainly degraded products by using lactobacillus, saccharomycete, and phycomycete. The results obtained from the experiments of the batch scale and pilot plant study allowed us to development the parameters for the field study. A pond, 5 m to the outlet of a lake, with an area of 500 m2 and depth of 0.6-1.2 m containing about 500 tons of water was selected as a model. After the treatment with 10 mg IERSA/L water twice a week for 70 days, the micro restoration mechanisms consisted of three stages (i.e., restoration, impact maintenance, and ecology recovery experiment after impact). The COD, TN, TKN, and chlorophyll a were reduced significantly in the first week. Although the unexpected heavy rain and contaminate from sewage system might slow the ecology restoration. However, the self-cleaning function continued and the chlorophyll a reduced for 50% in one month. In the 4th week, amoeba, paramecium, rotifer, and red wriggle worm reappeared, and the number of fish flies appeared up to1000 fish fries/m3. Those results proved that inducing restorative mechanism can be applied to improve the eutrophication and to control the growth of algae in the lakes by gaining the selfcleaning through inducing and competition of microbes. The situation for growth of fishes also can reach an excellent result due to the improvement of water quality.

Keywords: Ecosystem restoration, eutrophication, lake.

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Authors: E. P. Nurlaili, M. Astuti, Y. Marsono, S. Naruki

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Iron is an essential nutrient with limited bioavailability. Nutritional anemia caused mainly by iron deficiency is the most recognized nutritional problem in both countries as well as affluent societies. Rice (Oryza sativa L.) has become the most important cereal crop for the improvement of human health due to the starch, protein, oil, and the majority of micronutrients, particularly in Asian countries. In this study, the iron availability and profile lipid were evaluated for the extracts from Cibeusi varieties (black rices) of ancient rice brans. Results: The quality of K, B, R, E diets groups shows the same effect on the growth of rats. Hematocrit and MCHC levels of rats fed K, B, R and E diets were not significantly (P<0.05). MCV and MCH levels of rats K, B, R were significantly (P<0.05) with E groups but rats K, B, R were not significantly (P<0.05). The iron content in the serum of rats fed with K, B, R and E diets were not significantly (P<0.05). The highest level of iron in the serum was founded in the B group. The iron content in the liver of rats fed with K, B, R and E diets were not significantly (P<0.05). The highest level of iron in the liver was founded in the R group. HDL cholesterol levels were significantly (P<0.05) between rats of fed B, E with K, R, but K and R were not significantly (P<0.05). LDL cholesterol levels of rats fed K and E significantly (P<0.05) with B and R. Conclusions: the bran of pigmented rice varieties has, with some exceptions, greater antioxidant and free-radical scavenging activities. The results also show that pigmented rice extracts acted as prooxidants in the lipid peroxidation assay, possibly by mechanisms described for the pro-oxidant activities of tocopherol and ascorbic. Pigmented rice bran extracts more effectively increases iron stores and reduces the prevalence of iron deficiency.

Keywords: Anemia, black rice bran extract, iron, profile lipid.

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Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi

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The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. Here, a direct conversion of analog signal to residue domain is done to reduce the conversion complexity using sigma-delta based parallel analog-to-residue converter. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Keywords: Analog-to-residue converter, Concatenated codes, OFDM, Redundant Residue Number System, Sigma-delta modulator, Wireless communication

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Authors: Raad Nari, Maura Moriaty, Maha T. Barakat

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Introduction: Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a new class of oral anti-diabetic drugs with a unique mechanism of action. They are used to improve glycaemic control in adults with type 2 diabetes by enhancing urinary glucose excretion. In the UAE, there has been certainly an increased use of these medications. As with any new medication, there are safety considerations related to their use in patients with type two diabetes. A retrospective study was conducted at the three main centres of the Imperial College London Diabetes Centre. Methodology: All patients in electronic database (Diamond) from October 2014 to October 2017 were included with a minimum of six months usage of sodium glucose co-transporter inhibitors that comprise canagliflozin, dapagliflozin and empagliflozin. There were 15 paired sample biochemical and clinical correlations. The analysis was done at the start of the study, three months and six months apart. SPSS version 24 was used for this study. Conclusion: This study of sodium glucose co-transporter-2 inhibitors used showed significant reductions in weight, glycated haemoglobin A1C, systolic and diastolic blood pressures. As the case with systematic reviews, there were similar changes in liver enzymes, raised total cholesterol, low density lipopoptein and high density lipoprotein. There was slight improvement in estimated glomerular filtration rate too. Our analysis also showed that they increased in the incidence of urinary tract symptoms and incidence of urinary tract infections.

Keywords: SGLT2 inhibitors dapagliflozin empagliflozin canagliflozin, adverse effects, amputation diabetic ketoacidosis DKA, urinary tract infection.

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Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

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The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: Acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation.

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Authors: Mohanchur Sakar, K.K.Shukla, K.S.Dasgupta

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This paper attempts to establish the fact that Multi State Network Classification is essential for performance enhancement of Transport protocols over Satellite based Networks. A model to classify Multi State network condition taking into consideration both congestion and channel error is evolved. In order to arrive at such a model an analysis of the impact of congestion and channel error on RTT values has been carried out using ns2. The analysis results are also reported in the paper. The inference drawn from this analysis is used to develop a novel statistical RTT based model for multi state network classification. An Adaptive Multi State Proactive Transport Protocol consisting of Proactive Slow Start, State based Error Recovery, Timeout Action and Proactive Reduction is proposed which uses the multi state network state classification model. This paper also confirms through detail simulation and analysis that a prior knowledge about the overall characteristics of the network helps in enhancing the performance of the protocol over satellite channel which is significantly affected due to channel noise and congestion. The necessary augmentation of ns2 simulator is done for simulating the multi state network classification logic. This simulation has been used in detail evaluation of the protocol under varied levels of congestion and channel noise. The performance enhancement of this protocol with reference to established protocols namely TCP SACK and Vegas has been discussed. The results as discussed in this paper clearly reveal that the proposed protocol always outperforms its peers and show a significant improvement in very high error conditions as envisaged in the design of the protocol.

Keywords: GEO, ns2, Proactive TCP, SACK, Vegas

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Authors: Daohong Yang, Xiang Zhang, Wanting Zhou, Lei Li

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that gathers information about the surrounding environment to ascertain its own position and create a map. It is widely used in computer vision, robotics, and various other fields. Many visual SLAM systems, such as OBSLAM3, utilize a constant velocity motion model. The utilization of this model facilitates the determination of the initial pose of the current frame, thereby enhancing the efficiency and precision of feature matching. However, it is often difficult to satisfy the constant velocity motion model in actual situations. This can result in a significant deviation between the obtained initial pose and the true value, leading to errors in nonlinear optimization results. Therefore, this paper proposes a motion model based on acceleration that can be applied to most SLAM systems. To provide a more accurate description of the camera pose acceleration, we separate the pose transformation matrix into its rotation matrix and translation vector components. The rotation matrix is now represented by a rotation vector. We assume that, over a short period, the changes in rotating angular velocity and translation vector remain constant. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of the constant velocity model is analyzed theoretically. Finally, we apply our proposed approach to the ORBSLAM3 system and evaluate two sets of sequences from the TUM datasets. The results show that our proposed method has a more accurate initial pose estimation, resulting in an improvement of 6.61% and 6.46% in the accuracy of the ORBSLAM3 system on the two test sequences, respectively.

Keywords: Error estimation, constant acceleration motion model, pose estimation, visual SLAM.

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Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: Cloud storage, decision trees, diagnostic image, search, telemedicine.

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Authors: B. Nassar, W. Hussein, M. Mokhtar

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The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: Space telemetry monitoring, multivariate analysis, PCA algorithm, space operations.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: M.C. Zaghdoudi, S. Maalej, J. Mansouri, M.B.H. Sassi

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An experimental study is realized in order to verify the Mini Heat Pipe (MHP) concept for cooling high power dissipation electronic components and determines the potential advantages of constructing mini channels as an integrated part of a flat heat pipe. A Flat Mini Heat Pipe (FMHP) prototype including a capillary structure composed of parallel rectangular microchannels is manufactured and a filling apparatus is developed in order to charge the FMHP. The heat transfer improvement obtained by comparing the heat pipe thermal resistance to the heat conduction thermal resistance of a copper plate having the same dimensions as the tested FMHP is demonstrated for different heat input flux rates. Moreover, the heat transfer in the evaporator and condenser sections are analyzed, and heat transfer laws are proposed. In the theoretical part of this work, a detailed mathematical model of a FMHP with axial microchannels is developed in which the fluid flow is considered along with the heat and mass transfer processes during evaporation and condensation. The model is based on the equations for the mass, momentum and energy conservation, which are written for the evaporator, adiabatic, and condenser zones. The model, which permits to simulate several shapes of microchannels, can predict the maximum heat transfer capacity of FMHP, the optimal fluid mass, and the flow and thermal parameters along the FMHP. The comparison between experimental and model results shows the good ability of the numerical model to predict the axial temperature distribution along the FMHP.

Keywords: Electronics Cooling, Micro Heat Pipe, Mini Heat Pipe, Mini Heat Spreader, Capillary grooves.

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Authors: A. Parizad, A. Khazali, M. Kalantar

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Voltage collapse is instability of heavily loaded electric power systems that cause to declining voltages and blackout. Power systems are predicated to become more heavily loaded in the future decade as the demand for electric power rises while economic and environmental concerns limit the construction of new transmission and generation capacity. Heavily loaded power systems are closer to their stability limits and voltage collapse blackouts will occur if suitable monitoring and control measures are not taken. To control transmission lines, it can be used from FACTS devices. In this paper Harmony search algorithm (HSA) and Genetic Algorithm (GA) have applied to determine optimal location of FACTS devices in a power system to improve power system stability. Three types of FACTS devices (TCPAT, UPFS, and SVC) have been introduced. Bus under voltage has been solved by controlling reactive power of shunt compensator. Also a combined series-shunt compensators has been also used to control transmission power flow and bus voltage simultaneously. Different scenarios have been considered. First TCPAT, UPFS, and SVC are placed solely in transmission lines and indices have been calculated. Then two types of above controller try to improve parameters randomly. The last scenario tries to make better voltage stability index and losses by implementation of three types controller simultaneously. These scenarios are executed on typical 34-bus test system and yields efficiency in improvement of voltage profile and reduction of power losses; it also may permit an increase in power transfer capacity, maximum loading, and voltage stability margin.

Keywords: FACTS Devices, Voltage Stability Index, optimal location, Heuristic methods, Harmony search, Genetic Algorithm.

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Authors: Wanida Suwunniponth

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The objectives of this research paper were to study the influencing factors that contributed to the success of electronic commerce (e-commerce) and to study the approach to enhance the standard of e-commerce for small and medium enterprises (SME). The research paper focused the study on only sole proprietorship SMEs in Bangkok, Thailand. The factors contributed to the success of SME included business management, learning in the organization, business collaboration, and the quality of website. A quantitative and qualitative mixed research methodology was used. In terms of quantitative method, a questionnaire was used to collect data from 251 sole proprietorships. The System Equation Model (SEM) was utilized as the tool for data analysis. In terms of qualitative method, an in-depth interview, a dialogue with experts in the field of ecommerce for SMEs, and content analysis were used. By using the adjusted causal relationship structure model, it was revealed that the factors affecting the success of e-commerce for SMEs were found to be congruent with the empirical data. The hypothesis testing indicated that business management influenced the learning in the organization, the learning in the organization influenced business collaboration and the quality of the website, and these factors, in turn, influenced the success of SMEs. Moreover, the approach to enhance the standard of SMEs revealed that the majority of respondents wanted to enhance the standard of SMEs to a high level in the category of safety of e-commerce system, basic structure of e-commerce, development of staff potentials, assistance of budget and tax reduction, and law improvement regarding the e-commerce respectively.

Keywords: Electronic Commerce, Influencing Factors, Small and Medium Enterprises.

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Authors: L. Petrosyan

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The problem of psychologist training remains a key priority in Armenia. During the Soviet period, the notion of a psychologist was obscure not only in Armenia but also in other Soviet republics. The breakup of the Soviet Union triggered a gradual change in this area activating the cooperation with specialists from other countries. The need for recovery from the psychological trauma caused by the 1988 earthquake pushed forward the development of practical psychology in Armenia. This phenomenon led to positive changes in perception of and interest to a psychologist profession.Armenian universities started designing special programs for psychologists’ preparation. Armenian psychologists combined their efforts in the field of training relevant specialists. During the recent years, the Bologna educational system was introduced in Armenia which led to implementation of education quality improvement programs. Nevertheless, even today the issue of psychologists’ training is not yet settled in Armenian universities. So far graduate psychologists haven’t got a clear idea of personal and professional qualities of a psychologist. Recently, as a result of educational reforms, the psychology curricula underwent changes, but so far they have not led to a desired outcome. Almost all curricula in certain specialties are aimed to form professional competencies and strengthen practical skills. A survey conducted in Armenia aimed to identify what are the ideas of young psychology specialists on the image of a psychologist. The survey respondents were 45 specialists holding bachelor’s degree as well as 30 master degree graduates, who have not been working yet. The research reveals that we need to change the approach of preparing psychology practitioners in the universities of Armenia. Such an approach to psychologist training will make it possible to train qualified specialists for enhancement of modern psychology theory and practice.

Keywords: Practitioners, Psychology Degree, study, professional competencies.

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Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

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This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarness^TM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HR_max). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: PSM, heart rate, HR, breathing rate, BR.

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Authors: Albana Hasimi, Edlira Tako, Partizan Malkaj, Elvin Çomo, Blerina Papajani, Mirela Ndrita, Ledjan Malaj

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Many endeavors have been exerted during the last years for developing new artificial polymeric membranes, which fulfill the demanded conditions for biomedical uses. One of the most tested polymers is Poly(vinyl alcohol) [PVA]. Our teams are based on the possibility of using PVA for personal protective equipment against COVID-19. In personal protective equipment, we explore the possibility of modifying the properties of the polymer by adding Montmorillonite [MMT]. Heat-treatment above the glass transition temperature is used to improve mechanical properties mainly by increasing the crystallinity of the polymer, which acts as a physical network. Temperature-Modulated Differential Scanning Calorimetry (TMDSC) measurements indicated that the presence of 0.5% MMT in PVA causes a higher Tg value and shaped peak of crystallinity. Decomposition is observed at two of the melting points of the crystals during heating 25-240 oC and overlap of the recrystallization ridges during cooling 240-25 oC. This is indicative of the presence of two types (quality or structure) of polymer crystals. On the other hand, some indication of improvement of the quality of the crystals by heat-treatment is given by the distinct non-reversing contribution to melting. Data on sorption and transport of water in PVA films: PVA pure and PVA/MMT matrix, modified by thermal treatment are presented. The membranes become more rigid as a result of the heat treatment and because of this the water uptake is significantly lower in membranes. That is indicated by analysis of the resulting water uptake kinetics. The presence of 0.5% w/w of MMT has no significant impact on the properties of PVA membranes. Water uptake kinetics deviate from Fick’s law due to slow relaxation of glassy polymer matrix for all types of membranes.

Keywords: Crystallinity, montmorillonite, nanocomposite, poly(vinyl alcohol).

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