Search results for: optimization procedure

Authors: Drutika Upadhyay

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Rape is one of the most heinous crimes committed against the body of a woman violating her privacy and dignity. The Right to Privacy and the Right to Live with Dignity constitute the very essence of the Right to Life and Personal Liberty, a Fundamental Right guaranteed under Article 21 of the Indian Constitution. The study is conducted with the primary objective of analyzing the efficacy of rape laws in India. The study begins by explaining the origin, meaning, and kinds of rape recognised under Indian jurisprudence. Further, it explains various statutory and penal provisions relating to rape and the loopholes in such provisions. It focuses on the procedure followed during investigation and trial and also aims at developing an understanding of the rights of the victim and the sentence in cases of rape. The study also throws some light upon the amendments made to the criminal law and the recommendations of the Law Commission of India to meet the demands of the changing criminal justice delivery system. The outcome of the study suggests that the laws relating to rape have proved to be a major failure owing to the lack of proper implementation. Also, the lack of education among the masses leads to gender biasness, which is the ultimate cause for the commission of such crime. At last, the author concludes that the present criminal law system of the country contains various lacunae that need to be filled in so as to make the criminal justice system more stringent. Further, the scope of the definition of ‘rape’ needs to be widened in order to include such other acts of non-consensual and sexual nature that are currently not included in the definition. The author has adopted a non-doctrinal and analytical approach and relied upon the secondary sources of data for the purpose of the study. The scope of the study is limited to the crime committed against women.

Keywords: amendment, criminal law, fundamental right, personal liberty, privacy, rape

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Authors: Mohd Ruzlin Mohd Mokhtar

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At present, most operators who are working on projects for utilities such as power, water, oil, gas, telecommunication and sewerage are using technologies e.g. Total station, Global Positioning System (GPS), Electromagnetic Locator (EML) and Ground Penetrating Radar (GPR) to perform underground utility mapping. With the increase in popularity of Horizontal Directional Drilling (HDD) method among the local authorities and asset owners, most of newly installed underground utilities need to use the HDD method. HDD method is seen as simple and create not much disturbance to the public and traffic. Thus, it was the preferred utilities installation method in most of areas especially in urban areas. HDDs were installed much deeper than exiting utilities (some reports saying that HDD is averaging 5 meter in depth). However, this impacts the accuracy or ability of existing underground utility mapping technologies. In most of Malaysia underground soil condition, those technologies were limited to maximum of 3 meter depth. Thus, those utilities which were installed much deeper than 3 meter depth could not be detected by using existing detection tools. The accuracy and reliability of existing underground utility mapping technologies or work procedure were in doubt. Thus, a mitigation action plan is required. While installing new utility using Horizontal Directional Drilling (HDD) method, a more accurate underground utility mapping can be achieved by using Gyro OMU compared to existing practice using e.g. EML and GPR. Gyro OMU is a method to accurately identify the location of HDD thus this mapping can be used or referred to avoid those cost of breakdown due to future HDD works which can be caused by inaccurate underground utility mapping.

Keywords: Gyro Orientation Measurement Unit (Gyro OMU), Horizontal Directional Drilling (HDD), Ground Penetrating Radar (GPR), Electromagnetic Locator (EML)

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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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 novel 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. To the best of our knowledge, this is the first work to apply 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: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Violeta Damjanovic-Behrendt

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This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

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Authors: Taufik Rizkiandi, Teuku Yuri M. Zagloel, Andri Dwi Setiawan

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Distribution and growth in the transportation and warehousing business sector decreased by 15,04%. There was a decrease in Gross Domestic Product (GDP) contribution level from rank 7 of 4,41% in 2019 to 3,81% in rank 8 in 2020. A decline in the transportation and warehousing business sector contributes to GDP, resulting in oil and gas companies implementing an efficient supply chain strategy to ensure the availability of goods, especially lubricants. Fluctuating demand for lubricants and warehouse service time limits are essential things that are taken into account in determining an efficient route. Add depots points as a solution so that demand for lubricants is fulfilled (not stock out). However, adding a depot will increase operating costs and storage costs. Therefore, it is necessary to optimize the addition of depots using the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). This research case study was conducted at an oil and gas company that produces lubricants from 2019 to 2021. The study results obtained the optimal route and the addition of a depot with a minimum additional cost. The total cost remains efficient with the addition of a depot when compared to one depot from Jakarta.

Keywords: CVRPTW, optimal route, depot, tabu search algorithm

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Authors: Gamze Karanfil Celep, Kevser Dincer

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The effects of polymer concentration and electrospinning process parameters on the average diameters of electrospun polyacrylonitrile (PAN) nanofibers were experimentally investigated. Besides, mechanical and thermal properties of PAN nanofibers were examined by tensile test and thermogravimetric analysis (TGA), respectively. For this purpose, the polymer concentration, solution feed rate, supply voltage and tip-to-collector distance were determined as the control factors. To succeed these aims, Taguchi’s L16 orthogonal design (4 parameters, 4 level) was employed for the experimental design. Optimal electrospinning conditions were defined using the signal-to-noise (S/N) ratio that was calculated from diameters of the electrospun PAN nanofibers according to "the-smaller-the-better" approachment. In addition, analysis of variance (ANOVA) was evaluated to conclude the statistical significance of the process parameters. The smallest diameter of PAN nanofibers was observed. According to the S/N ratio response results, the most effective parameter on finding out of nanofiber diameter was determined. Finally, the Taguchi design of experiments method has been found to be an effective method to statistically optimize the critical electrospinning parameters used in nanofiber production. After determining the optimum process parameters of nanofiber production, electrical conductivity and fuel cell performance of electrospun PAN nanofibers on the carbon papers will be evaluated.

Keywords: nanofiber, electrospinning, polyacrylonitrile, Taguchi method

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Authors: Samira K. Al-Nasser, Siamak Noroozi, Roya Haratian, Adrian Harvey

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A total knee replacement (TKR) is a surgical procedure necessary when there is severe pain and/or loss of function in the knee. Surgeons balance the load in the knee and the surrounding soft tissue by feeling the tension at different ranges of motion. This method can be unreliable and lead to early failure of the joint. The ideal kinematics and load distribution have been debated significantly based on previous biomechanical studies surrounding both TKRs and normal knees. Intraoperative sensors like VERASENSE and eLibra have provided a method for the quantification of the load indicating a balanced knee. A review of the literature written about intraoperative sensors and tension/stability of the knee was done. Studies currently debate the quantification of the load in medial and lateral compartments specifically. However, most research reported that following a TKR the medial compartment was loaded more heavily than the lateral compartment. In several cases, these results were shown to increase the success of the surgery because they mimic the normal kinematics of the knee. In conclusion, most research agrees that an intercompartmental load differential of between 10 and 20 pounds, where the medial load was higher than the lateral, and an absolute load of less than 70 pounds was ideal. However, further intraoperative sensor development could help improve the accuracy and understanding of the load distribution on the surgical outcomes in a TKR. A reduction in early revision surgeries for TKRs would provide an improved quality of life for patients and reduce the economic burden placed on both the National Health Service (NHS) and the patient.

Keywords: intraoperative sensors, joint load forces, kinematics, load balancing, and total knee replacement

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Authors: R. Posia, J. Mistry, K. Kamani

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The health screening of laboratory rodents is essential for ensuring animal health and the validity of biomedical research data. Routine health monitoring is necessary to verify the effectiveness of biosecurity and the specific pathogen free (SPF) status of the colony. The present screening was performed in barrier maintained rat (Rattus norvegicus) colony. Rats were maintained under a controlled environment and strict biosecurity in the facility. The screening was performed on quarterly bases from randomly selected animals from breeding and or maintenance colonies. Selected animals were subject to blood collection under isoflurane anaesthesia. Serum was separated from the collected blood and stored samples at -60 ± 10 °C until further use. A total of 88 samples were collected quarterly bases from animals in a year. In the serological test, enzyme-linked immunosorbent assay (ELISA) was used for screening of serum samples against sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV). ELISA kits were procured from XpressBio, USA. Test serum samples were run along with positive control, negative control serum in 96 well ELISA plates as per the procedure recommended by the vendor. Test ELISA plate reading was taken in the microplate reader. This screening observed that none of the samples was observed positive for the sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV), indicating that effectiveness of biosecurity practices followed in the rodent colony. The result of serological screening helps us to declare that our rodent colony is specifically pathogen free for these pathogens.

Keywords: biosecurity, ELISA, specific pathogen free, serological screening, serum

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Lobna Ahmed Galal

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Modal integration has given minimal consideration in cities of developing countries, as well as the declining dominance of public transport, and predominance of informal transport, the modal share of informal taxis in greater Cairo has increased from 6% in 1987 to 37% in 2001 and this has since risen even higher, informal and non-motorized modes of transport acting as a gap filler by feeding other modes of transport, not by design or choice, but often by lack of accessible and affordable public transport. Yet non-motorized transport is peripheral, with minimal priority in urban planning and investments, lacking of strong polices to support non-motorized transport, for authorities development is associated with technology and motorized transport, and promotion of non-motorized transport may be considered corresponding to development, as well as social stigma against non-motorized transport, as it is seen a travel mode for the poor. Cairo as a city of a developing country, has poor quality infrastructure for non-motorized transport, suffering from absence of dedicated corridors, and when existing they are often encroached for commercial purposes, widening traffic lanes at the expense of sidewalks, absence of footpaths, or being overcrowded, poor lighting, making walking unsafe and yet, lack of financial supply to such facilities as it is often considered beyond city capabilities. This paper will deal with the objective measuring of the built environment relating to walking, in some neighborhoods of new cities around Cairo, In addition to comparing the results of the objective measures of the built environment with the level of self-reported survey. The first paper's objective is to show how the index ‘walkability of community neighborhoods’ works in the contexts in neighborhoods of new cities around Cairo. The procedure of objective measuring is of a high potential to be carried out by using GIS.

Keywords: assessing, built environment, Cairo, walkability

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Authors: Devendra Gupta, Sushilk K. Agarwal, Amit Kesari, P. K. Singh

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Objectives: Pediatric patients often may experience persistent respiratory failure that requires tracheostomy placement in Pediatric ICU. We have designed a technique of tracheostomy in pediatric patients with S-shaped incision on the tracheal wall with higher success rate and lower complication rate. Technique: Following general anesthesia and positioning of the patient, the trachea was exposed in midline by a vertical skin incision. In order to make S-shaped tracheostoma, second tracheal ring was identified. The conventional vertical incision was made in second tracheal ring and then extended at both its ends laterally in the inter-cartilaginous space parallel to the tracheal cartilage in the opposite direction to make the incision S-shaped. The trachea was dilated with tracheal dilator and appropriate size of tracheostomy tube was then placed into the trachea. Results: S-shaped tracheostomy was performed in 20 children with mean age of 6.25 years (age range is 2-7) requiring tracheostomy placement. The tracheostomy tubes were successfully placed in all the patients in single attempt. There was no incidence of significant intra-operative bleeding, subcutaneous emphysema, vocal cord palsy or pneumothorax. Two patients developed pneumonia and expired within a year. However, there was no incidence of tracheo-esophageal fistula, suprastomal collapse or difficulty in decannulation on one year of follow up related to our technique. One patient developed late trachietis managed conservatively. Conclusion: S-shaped tracheoplasty was associated with high success rate, reduced risk of the early and late complications in pediatric patients requiring tracheostomy.

Keywords: peatrics, tracheostomy, ICU, tracheostoma

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Authors: Siwarak Kitchanapaibul, Warren Gillibrand, Rob Burton

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The prevalence of diabetes mellitus has been rising all over the world. Self-management is required for diabetes mellitus patients. The objective of this study is to explore the self-management among the ethnic groups with type 2 diabetes mellitus in Thailand, an upper middle-income country which is located in South East Asia. The ethnic groups in Thailand are a minority group which has limited education and a different culture, language, costume and lifestyle from Thai people. The qualitative exploratory study was used in this study. In-depth interviews with semi-structured open questions were conducted by 20 participants from purposive sampling. These participants were the ethnic groups who have type 2 diabetes mellitus, received the services from a region hospital, understood Thai and were willing to participate. Content analysis was adopted for the study. The results showed that all of the participants controlled their diet before the appointment day and never miss their appointment. Only 3 participants did their exercise while 2 participants stated that they occasionally forgot to take medicine. 10 participants use the herbs for reducing the sugar level. 12 participants drank a lot of water after a lapse in the diet because they believed that water could dilute the sugar. The findings identified 5 themes; ‘controlling diet before appointment day’; ‘drinking water after a lapse in diet’; ‘medication being a vital importance’; ‘exercise is unimportant’; and ‘taking herbs for sugar reduction’. The results of this study are important to the health professionals to understand the self-management of Ethnic groups and use the data to create the appropriate intervention for promoting health among the ethnic groups with type 2 diabetes mellitus in Thailand. The findings will lead to the revision of health policy and the procedure for promoting health in this special ethnic groups.

Keywords: self-management, diabetes, ethnic groups, Thailand

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Authors: M. Kowalski, M. Brodowski, K. Dziabowska, E. Czaczyk, W. Bialobrzeska, N. Malinowska, S. Zoledowska, R. Bogdanowicz, D. Nidzworski

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Boron-doped-carbon nanowall (BCNW) electrodes are recently in much interest among scientists. BCNWs are good candidates for biosensor purposes as they possess interesting electrochemical characteristics like a wide potential range and the low difference between redox peaks. Moreover, from technical parameters, they are mechanically resistant and very tough. The production process of the microwave plasma-enhanced chemical vapor deposition (MPECVD) allows boron to build into the structure of the diamond being formed. The effect is the formation of flat, long structures with sharp ends. The potential of these electrodes was checked in the biosensing field. The procedure of simple carbon electrodes modification by antibodies was adopted to BCNW for specific antigen recognition. Surface protein D deriving from H. influenzae pathogenic bacteria was chosen as a target analyte. The electrode was first modified with the aminobenzoic acid diazonium salt by electrografting (electrochemical reduction), next anti-protein D antibodies were linked via 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride/N-hydroxysuccinimide (EDC/NHS) chemistry, and free sites were blocked by BSA. Cyclic voltammetry measurements confirmed the proper electrode modification. Electrochemical impedance spectroscopy records indicated protein detection. The sensor was proven to detect protein D in femtograms. This work was supported by the National Centre for Research and Development (NCBR) TECHMATSTRATEG 1/347324/12/NCBR/ 2017.

Keywords: anti-protein D antibodies, boron-doped carbon nanowall, impedance spectroscopy, Haemophilus influenzae.

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Authors: Mohammadreza Heydariazad

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Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

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Authors: A. Qayyum, G. Bilal, H. M. Waheed

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The objectives of the study were to determine phenotypic variations in Hairy goats for quantitative and qualitative traits and to analyze the relationship between different body measurements and body weight in Hairy goats. Data were collected from the Barani Livestock Production Research Institute (BLPRI) at Kherimurat, Attock and potential farmers who were raising hairy goats in the Potohar region. Twelve (12) phenotypic parameters were measured on 99 adult Hairy goat (18 male and 81 female). Four qualitative and 8 quantitative traits were investigated. Qualitative traits were visually observed and expressed as percentages. Descriptive analysis was done on quantitative variables. All hairy goats had predominately black body coat color (72%), whereas white (11%) and brown (11%) body coat color were also observed. Both the pigmented (45.5%) and non-pigmented (54.5%) type of body skin were observed in the goat breed. Horns were present in the majority (91%) of animals. Most of the animals (83%) had straight facial head profiles. Analysis was performed in SAS On-Demand for Academics using PROC mixed model procedure. Overall means ± SD of body weight (BW), body length (BL), height at wither (HAW), ear length (EL), head length (HL), heart girth (HG), tail length (TL) and MC (muzzle circumference) were 41.44 ± 12.21 kg, 66.40 ± 7.87 cm, 75.17 ± 7.83 cm, 22.99 ± 6.75 cm, 15.07 ± 3.44 cm, 76.54 ± 8.80 cm, 18.28 ± 4.18 cm, and 26.24 ± 5.192 cm, respectively. Sex had a significant effect on BL and HG (P < 0.05), whereas BW, HAW, EL, HL, TL, and MC were not significantly affected (P > 0.05). The herd had a significant effect on BW, BL, HAW, HL, HG, and TL (P < 0.05) except EL and MC (P > 0.05). Hairy goats appear to have the potential for selection as mutton breeds in the Potohar region of Punjab. The findings of the present study would help in the characterization and conservation of hairy goats using genetic and genomic tools in the future.

Keywords: body weight, Hairy goat, type traits Punjab, Pakistan

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Yanhua Zhao, Chenli Rao, Dongdong Li, Chuanmin Tao

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The Chinese Centers for Disease Control and Prevention (CCDC) issued a new laboratory-based algorithm for HIV diagnosis on April 2016, which initially screens with a combination HIV-1/HIV-2 antigen/antibody fourth-generation immunoassay (IA) followed, when reactive, an HIV-1/HIV-2 undifferentiated antibody IA in duplicate. Reactive specimens with concordant results undergo supplemental tests with western blots, or HIV-1 nucleic acid tests (NATs) and non-reactive specimens with discordant results receive HIV-1 NATs or p24 antigen tests or 2-4 weeks follow-up tests. However, little data evaluating the application of the new algorithm have been reported to date. The study was to evaluate the performance of new laboratory-based HIV diagnostic algorithm in an inpatient population of Southwest China over the initial 6 months by compared with the old algorithm. Plasma specimens collected from inpatients from May 1, 2016, to October 31, 2016, are submitted to the laboratory for screening HIV infection performed by both the new HIV testing algorithm and the old version. The sensitivity and specificity of the algorithms and the difference of the categorized numbers of plasmas were calculated. Under the new algorithm for HIV diagnosis, 170 of the total 52 749 plasma specimens were confirmed as positively HIV-infected (0.32%). The sensitivity and specificity of the new algorithm were 100% (170/170) and 100% (52 579/52 579), respectively; while 167 HIV-1 positive specimens were identified by the old algorithm with sensitivity 98.24% (167/170) and 100% (52 579/52 579), respectively. Three acute HIV-1 infections (AHIs) and two early HIV-1 infections (EHIs) were identified by the new algorithm; the former was missed by old procedure. Compared with the old version, the new algorithm produced fewer WB-indeterminate results (2 vs. 16, p = 0.001), which led to fewer follow-up tests. Therefore, the new HIV testing algorithm is more sensitive for detecting acute HIV-1 infections with maintaining the ability to verify the established HIV-1 infections and can dramatically decrease the greater number of WB-indeterminate specimens.

Keywords: algorithm, diagnosis, HIV, laboratory

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Kelly F. Delgado-De Agrela, Sonia E. Ruiz, Marco A. Santos-Santiago

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An approach is proposed for the design of regular buildings equipped with non-linear viscous dissipating devices. The approach is based on a direct-displacement seismic design method which satisfies seismic performance objectives. The global system involved is formed by structural regular moment frames capable of supporting gravity and lateral loads with elastic response behavior plus a set of non-linear viscous dissipating devices which reduce the structural seismic response. The dampers are characterized by two design parameters: (1) a positive real exponent α which represents the non-linearity of the damper, and (2) the damping coefficient C of the device, whose constitutive force-velocity law is given by F=Cvᵃ, where v is the velocity between the ends of the damper. The procedure is carried out using a substitute structure. Two limits states are verified: serviceability and near collapse. The reduction of the spectral ordinates by the additional damping assumed in the design process and introduced to the structure by the viscous non-linear dampers is performed according to a damping reduction factor. For the design of the non-linear damper system, the real velocity is considered instead of the pseudo-velocity. The proposed design methodology is applied to an 8-story steel moment frame building equipped with non-linear viscous dampers, located in intermediate soil zone of Mexico City, with a dominant period Tₛ = 1s. In order to validate the approach, nonlinear static analyses and nonlinear time history analyses are performed.

Keywords: based design, direct-displacement based design, non-linear viscous dampers, performance design

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Authors: Anish Desai, Reshmi Pillai, Nilesh Mahajan, Hitesh Chopra, Vishal Mahajan, Ajay Grover, Ashish Kohli

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Surgical Site Infection (SSI) is hospital acquired infection of growing concern. This study presents the efficacy and cost-effectiveness of triclosan-coated suture, in reducing the burden of SSI in India. Methodology: A systematic literature search was conducted for economic burden (1998-2018) of SSI and efficacy of triclosan-coated sutures (TCS) vs. non-coated sutures (NCS) (2000-2018). PubMed Medline and EMBASE indexed articles were searched using Mesh terms or Emtree. Decision tree analysis was used to calculate, the cost difference between TCS and NCS at private and public hospitals, respectively for 7 surgical procedures. Results: The SSI range from low to high for Caesarean section (C-section), Laparoscopic hysterectomy (L-hysterectomy), Open Hernia (O-Hernia), Laparoscopic Cholecystectomy (L-Cholecystectomy), Coronary artery bypass graft (CABG), Total knee replacement (TKR), and Mastectomy were (3.77 to 24.2%), (2.28 to 11.7%), (1.75 to 60%), (1.71 to 25.58%), (1.6 to 18.86%), (1.74 to 12.5%), and (5.56 to 25%), respectively. The incremental cost (%) of TCS ranged 0.1%-0.01% in private and from 0.9%-0.09% at public hospitals across all surgical procedures. Cost savings at median efficacy & SSI risk was 6.52%, 5.07 %, 11.39%, 9.63%, 3.62%, 2.71%, 9.41% for C-section, L-hysterectomy, O-Hernia, L-Cholecystectomy, CABG, TKR, and Mastectomy in private and 8.79%, 4.99%, 12.67%, 10.58%, 3.32%, 2.35%, 11.83% in public hospital, respectively. Efficacy of TCS and SSI incidence in a particular surgical procedure were important determinants of cost savings using one-way sensitivity analysis. Conclusion: TCS suture led to cost savings across all 7 surgeries in both private and public hospitals in India.

Keywords: cost Savings, non-coated sutures, surgical site infection, triclosan-coated sutures

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Authors: Agoston Restas

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Introduction: In case of managing disasters decision makers can face many times such a special situation where any pre-sign of the drastically change is missing therefore the improvised decision making can be required. The complexity, ambiguity, uncertainty or the volatility of the situation can require many times the improvisation as decision making. It can be taken at any level of the management (strategic, operational and tactical) but at tactical level the main reason of the improvisation is surely time pressure. It is certainly the biggest problem during the management. Methods: The author used different tools and methods to achieve his goals; one of them was the study of the relevant literature, the other one was his own experience as a firefighting manager. Other results come from two surveys that are referred to; one of them was an essay analysis, the second one was a word association test, specially created for the research. Results and discussion: This article proves that, in certain situations, the multi-criteria, evaluating decision-making processes simply cannot be used or only in a limited manner. However, it can be seen that managers, directors or commanders are many times in situations that simply cannot be ignored when making decisions which should be made in a short time. The functional background of decisions made in a short time, their mechanism, which is different from the conventional, was studied lately and this special decision procedure was given the name recognition-primed decision. In the article, author illustrates the limits of the possibilities of analytical decision-making, presents the general operating mechanism of recognition-primed decision-making, elaborates on its special model relevant to managers at tactical level, as well as explore and systemize the factors that facilitate (catalyze) the processes with an example with fire managers.

Keywords: decision making, disaster managers, recognition primed decision, model for making decisions in emergencies

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: Kimiyo Shimomai, Mihoko Harada

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This study is a literature review of the psychological reactions that occur in end-of-life cancer patients who are nearing death. It searched electronic databases and selected literature related to psychological studies of end-of-life patients. There was no limit on the search period, and the search was conducted until the second week of December 2021. The keywords were specified as “death and dying”, “terminal illness”, “end-of-life”, “palliative care”, “psycho-oncology” and “research”. These literatures referred to Holly (2017): Comprehensive Systematic Review for Advanced Practice Nursing, P268 Figure 10.3 to ensure quality. These literatures were selected with a dissertation score of 4 or 5. The review was conducted in two stages with reference to the procedure of George (2002). First, these references were searched for keywords in the database, and then relevant references were selected from the psychology and nursing studies of end-of-life patients. The number of literatures analyzed was 76 for overseas and 17 for domestic. As for the independent variables, "physical variable" was the most common in 36 literatures (66.7%), followed by "psychological variable" in 35 literatures (64.8%), "spiritual variable" in 21 literatures (38%), and "social variable" in 17 literatures. (31.5%), "Variables related to medical care / treatment" were 16 literatures (29.6%). To summarize the relationship between these independent variables and the dependent variable, when the dependent variable is "psychological variable", the independent variables are "psychological variable", "social variable", and "physical variable". Among the independent variables, the physical variables were the most common. The psychological responses that occur in end-stage cancer patients who are nearing death are mutually influenced by psychological, social, and physical variables. Therefore, it supported the "total pain" advocated by Cicely Saunders.

Keywords: cancer patient, end-of-life, literature review, psychological process

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