Search results for: transmission error

Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: Tydra Preyear, Victor Clincy

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Quantum computing presents many computational advantages over classical computing methods due to the utilization of quantum mechanics. The capability of this computing infrastructure poses threats to standard cryptographic systems such as RSA and AES, which are designed for classical computing environments. This paper discusses the impact that quantum computing has on cryptography, while focusing on the evolution from classical cryptographic concepts to quantum and post-quantum cryptographic concepts. Standard Cryptography is essential for securing data by utilizing encryption and decryption methods, and these methods face vulnerability problems due to the advancement of quantum computing. In order to counter these vulnerabilities, the methods that are proposed are quantum cryptography and post-quantum cryptography. Quantum cryptography uses principles such as the uncertainty principle and photon polarization in order to provide secure data transmission. In addition, the concept of Quantum key distribution is introduced to ensure more secure communication channels by distributing cryptographic keys. There is the emergence of post-quantum cryptography which is used for improving cryptographic algorithms in order to be more secure from attacks by classical and quantum computers. Throughout this exploration, the paper mentions the critical role of the advancement of cryptographic methods to keep data integrity and privacy safe from quantum computing concepts. Future research directions that would be discussed would be more effective cryptographic methods through the advancement of technology.

Keywords: quantum computing, quantum cryptography, cryptography, data integrity and privacy

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Authors: Muhammad Jamil, Ning He, Aqib Mashood Khan, Munish Kumar Gupta

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Ti-6Al-4V has numerous applications in the medical, automobile, and aerospace industries due to corrosion resistivity, structural stability, and chemical inertness to most fluids at room temperature. These peculiar characteristics are beneficial for their application and present formidable challenges during machining. Machining of Ti-6Al-4V produces an elevated cutting temperature above 1000oC at dry conditions. This accelerates tool wear and reduces product quality. Therefore, there is always a need to employ sustainable/effective coolant/lubricant when machining such alloy. In this study, Finite Element Modeling (FEM) and experimental analysis when cutting Ti-6Al-4V under a distinctly developed dry ice mixed hybrid lubri-coolant are presented. This study aims to model the milling process of Ti-6Al-4V under a proposed novel hybrid lubri-coolant using different cutting speeds and feed per tooth DEFORM® software package was used to conduct the FEM and the numerical model was experimentally validated. A comparison of experimental and simulation results showed a maximum error of no more than 6% for all experimental conditions. In a nutshell, it can be said that the proposed model is effective in predicting the machining temperature precisely.

Keywords: friction coefficient, heat transfer, finite element modeling (FEM), milling Ti-6Al-4V

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Authors: Dilin Chen, Kang Luo, Jian Wu, Chun Yang, Hongliang Yi

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Electrically driven flows (EDF) systems play an important role in fuel cells, electrochemistry, bioseparation technology, fluid pumping, and microswimmers. The core scientific problem is multifield coupling, the further development of which depends on the exploration of nonlinear instabilities, force competing mechanisms, and energy budgets. In our study, two categories of electrostatic force-dominated phenomena, induced charge electrosmosis (ICEO) and ion conduction pumping are investigated while considering polymer rheological characteristics and heat gradients. With finite volume methods, the thermal modulation strategy of ICEO under the thermal buoyancy force is numerically analyzed, and the electroelastic instability turn associated with polymer addition is extended. The results reveal that the thermal buoyancy forces are sufficient to create typical thermogravitational convection in competition with electroconvective modes. Electroelastic instability tends to be promoted by weak electrical forces, and polymers effectively alter the unstable transition routes. Our letter paves the way for improved mixing and heat transmission in microdevices, as well as insights into the non-Newtonian nature of electrohydrodynamic dynamics.

Keywords: non-Newtonian fluid, electroosmotic flow, electrohydrodynamic, viscoelastic liquids, heat transfer

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Authors: A. Suresh, Sreehari Rao Patri, K. S. R. Krishnaprasad

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An ultra low power capacitor less low-dropout voltage regulator with improved transient response using gain enhanced feed forward path compensation is presented in this paper. It is based on a cascade of a voltage amplifier and a transconductor stage in the feed forward path with regular error amplifier to form a composite gain-enhanced feed forward stage. It broadens the gain bandwidth and thus improves the transient response without substantial increase in power consumption. The proposed LDO, designed for a maximum output current of 100 mA in UMC 180 nm, requires a quiescent current of 69 µA. An undershoot of 153.79mV for a load current changes from 0mA to 100mA and an overshoot of 196.24mV for current change of 100mA to 0mA. The settling time is approximately 1.1 µs for the output voltage undershoot case. The load regulation is of 2.77 µV/mA at load current of 100mA. Reference voltage is generated by using an accurate band gap reference circuit of 0.8V.The costly features of SOC such as total chip area and power consumption is drastically reduced by the use of only a total compensation capacitance of 6pF while consuming power consumption of 0.096 mW.

Keywords: capacitor-less LDO, frequency compensation, transient response, latch, self-biased differential amplifier

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Authors: Samad Sajjadi

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Machine translation is a new subject increasingly being used by academic writers, especially students and researchers whose native language is not English. There are numerous studies conducted on machine translation, but few investigations have assessed the accuracy of machine translation from Persian to English at lexical, semantic, and syntactic levels. Using Groves and Mundt’s (2015) Model of error taxonomy, the current study evaluated Persian-to-English translations produced by two famous online translators, Google Translate and Bing Translator. A total of 240 texts were randomly selected from different academic fields (law, literature, medicine, and mass media), and 60 texts were considered for each domain. All texts were rendered by the two translation systems and then by four human translators. All statistical analyses were applied using SPSS. The results indicated that Google translations were more accurate than the translations produced by the Bing Translator, especially in the domains of medicine (lexis: 186 vs. 225; semantic: 44 vs. 48; syntactic: 148 vs. 264 errors) and mass media (lexis: 118 vs. 149; semantic: 25 vs. 32; syntactic: 110 vs. 220 errors), respectively. Nonetheless, both machines are reasonably accurate in Persian-to-English translation of lexicons and syntactic structures, particularly from mass media and medical texts.

Keywords: machine translations, accuracy, human translation, efficiency

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Authors: S. Said, Asmaa A. Abdulrahman

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MoOₓ/Al₂O₃ based catalyst has long been widely used as an active catalyst in oxidative desulfurization reaction due to its high stability under severe reaction conditions and high resistance to sulfur poisoning. In this context, 4 & 9wt.% MoO₃ grafted on mesoporous γ-Al₂O₃ has been synthesized using the modified atomic layer deposition (ALD) method. Another MoO₃/Al₂O₃ sample was prepared by the conventional wetness impregnation (IM) method, for comparison. The effect of the preparation methods on the metal-support interaction was evaluated using different characterization techniques, including X-ray diffraction, X-ray photoelectron spectroscopy (XPS), N₂-physisorption, transmission electron microscopy (TEM), H₂- temperature-programmed reduction and FT-IR. Oxidative desulfurization (ODS) reaction of the model fuel oil was used as a probe reaction to examine the catalytic efficiency of the prepared catalysts. ALD method led to samples with much better physicochemical properties than those of the prepared one via the impregnation method. However, the 9 wt.%MoO₃/Al₂O₃ (ALD) catalyst in the ODS reaction of model fuel oil shows enhanced catalytic performance with ~90%, which has been attributed to the more Mo⁶⁺ surface concentrations relative to Al³⁺ with large pore diameter and surface area. The kinetic study shows that the ODS of DBT follows a pseudo first-order rate reaction.

Keywords: mesoporous Al₂O₃, xMoO₃/Al₂O₃, atomic layer deposition, wetness impregnation, ODS, DBT

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Authors: Abubakar Abdulkareem, Nasir Haruna Soba

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Artificial intelligence (AI) is developing at a rapid pace, revolutionizing several industries, including education. This talk looks at how useful AI can be for academic writing, with an emphasis on how it can help researchers be more accurate, productive, and creative. The academic world now relies heavily on AI technologies like grammar checkers, plagiarism detectors, and content generators to help with the writing, editing, and formatting of scholarly papers. This study explores the particular uses of AI in academic writing and assesses how useful and helpful these applications may be for both students and scholars. By means of an extensive examination of extant literature and a sequence of empirical case studies, we scrutinize the merits and demerits of artificial intelligence tools utilized in academic writing. Important discoveries indicate that although AI greatly increases productivity and lowers human error, there are still issues that need to be resolved, including reliance, ethical concerns, and the potential loss of critical thinking abilities. The talk ends with suggestions for incorporating AI tools into academic settings so that they enhance rather than take the place of the intellectual rigor that characterizes scholarly work. This study adds to the continuing conversation about artificial intelligence (AI) in higher education by supporting a methodical strategy that uses technology to enhance human abilities in academic writing.

Keywords: artificial intelligence, academic writing, ai tools, productivity, ethics, higher education

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Authors: Mehdi Rahimi-Nasrabadi, Seied Mahdi Pourmortazavi

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Taguchi robust design as a statistical method was applied for optimization of the process parameters in order to tunable, simple and fast synthesis of europium (III) tungstate nanoparticles. Europium (III) tungstate nanoparticles were synthesized by a chemical precipitation reaction involving direct addition of europium ion aqueous solution to the tungstate reagent solved in aqueous media. Effects of some synthesis procedure variables i.e., europium and tungstate concentrations, flow rate of cation reagent addition, and temperature of reaction reactor on the particle size of europium (III) tungstate nanoparticles were studied experimentally in order to tune particle size of europium (III) tungstate. Analysis of variance shows the importance of controlling tungstate concentration, cation feeding flow rate and temperature for preparation of europium (III) tungstate nanoparticles by the proposed chemical precipitation reaction. Finally, europium (III) tungstate nanoparticles were synthesized at the optimum conditions of the proposed method and the morphology and chemical composition of the prepared nano-material were characterized by means of X-Ray diffraction, scanning electron microscopy, transmission electron microscopy, FT-IR spectroscopy, and fluorescence.

Keywords: europium (III) tungstate, nano-material, particle size control, procedure optimization

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Authors: M. Malekian, M. E. Heydari, M. Irani Estyar

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Human papillomavirus (HPV) is one of the most common sexually transmitted infection, which may lead to cervical cancer as the main cause of it. With early diagnosis and treatment in health care services, cervical cancer and its complications are considered to be preventable. This study was aimed to compare the efficiency, sensitivity, and specificity of Pap smear and polymerase chain reaction (PCR) in detecting HPV. A literature search was performed in Google Scholar, PubMed and SID databases using the keywords 'human papillomavirus', 'pap smear' and 'polymerase change reaction' to identify studies comparing Pap smear and PCR methods for the detection. No restrictions were considered.10 studies were included in this review. All samples that were positive by pop smear were also positive by PCR. However, there were positive samples detected by PCR which was negative by pop smear and in all studies, many positive samples were missed by pop smear technique. Although The Pap smear had high specificity, PCR based HPV detection was more sensitive method and had the highest sensitivity. In order to promote the quality of detection and high achievement of the maximum results, PCR diagnostic methods in addition to the Pap smear are needed and Pap smear method should be combined with PCR techniques according to the high error rate of Pap smear in detection.

Keywords: human papillomavirus, cervical cancer, pap smear, polymerase chain reaction

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

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Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

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Authors: Wassana Naiyapo, Atichat Sangtong

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The processes in software development by Object Oriented methodology have many stages those take time and high cost. The inconceivable error in system analysis process will affect to the design and the implementation process. The unexpected output causes the reason why we need to revise the previous process. The more rollback of each process takes more expense and delayed time. Therefore, the good test process from the early phase, the implemented software is efficient, reliable and also meet the user’s requirement. Unified Modelling Language (UML) is the tool which uses symbols to describe the work process in Object Oriented Analysis (OOA). This paper presents the approach for automatically generated UML use case diagram and test cases. UML use case diagram is generated from the event table and test cases are generated from use case specifications and Graphic User Interfaces (GUI). Test cases are derived from the Classification Tree Method (CTM) that classify data to a node present in the hierarchy structure. Moreover, this paper refers to the program that generates use case diagram and test cases. As the result, it can reduce work time and increase efficiency work.

Keywords: classification tree method, test case, UML use case diagram, use case specification

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Authors: Kirti, Samanta Sekhar Khora

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Inflation serves different purposes in different organisms and adds beauty to their behavioral attributes. Pufferfishes are also known as blowfish, swellfish, and globefish due to their remarkable ability to puff themselves up like a balloon when threatened. This ability to inflate can be correlated with anatomical features that are unique to pufferfishes. Pufferfish skin provides a rigid framework to support the body contents and a flexible covering to allow whatever changes are necessary for remarkable inflation mechanism. Skin, the outer covering of animals is made up of collagen fibers arranged in more or less ordered arrays. The ventral skin of pufferfish stretches more than dorsal skin during inflation. So, this study is of much of the interest in comparing the structure and mechanical properties of these two skin regions. The collagen fibers were found to be arranged in different ordered arrays for ventral and dorsal skin and concentration of fibers were also found to be different for these two skin parts. Scanning electron microscopy studies of the ventral skin showed a unidirectional arrangement of the collagen fibers, which provide more stretching capacity. Dorsal skin, on the other hand, has an orthogonal arrangement of fibers. This provides more stiffness to the ventral skin at the time of inflation. In this study, the possible role of collagen fibers was determined which significantly contributed to the remarkable inflation mechanism of pufferfishes.

Keywords: collagen, histology, inflation, pufferfish, scanning electron microscopy, Small-Angle X-Ray Scattering (SAXS), transmission electron microscopy

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

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In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

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Authors: M. Srilatha, R. Hemalatha, T. Sri Aditya

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Communication of today world is dominated by wireless technology. This is mainly due to the revolutionary development of new wireless communication system generations. The evolving new generations of wireless systems are accommodating the demand through better resource management including improved transmission technologies with optimized communication devices. To keep up with the evolution of technologies, the communication systems must be designed to optimize transparent insertion of newly evolved technologies virtually at all stages of their life cycle. After the insertion of new technologies, the upgraded devices should continue the communication without squalor in quality. The concern of improving spectrum access and spectrum efficiency combined with both the introduction of Software Defined Radios (SDR) and the possibility of the software application to radios has led to an evolution of wireless radio research. The software defined radio term was coined in the 1970s to overcome the problems in the application of software to wireless radios which eliminates the requirement of hardware changes. SDR has become the prime theme of research since it eliminates the drawbacks associated with conventional wireless communication systems implementation. This paper identifies and discusses key enabling technologies and possibility of research and development in SDRs. In addition transmitter and receiver architectures of SDR are also discussed along with their feasibility for reconfigurable radio application.

Keywords: software defined radios, wireless communication, reconfigurable, reconfigurable transmitter, reconfigurable receivers, FPGA, DSP

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Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

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Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

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Authors: Stanley Dula, Oluwatosini A. Ijabadeniyi

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Biofilm formation is a major source of materials and foodstuffs contamination, contributing to occurrence of pathogenic and spoilage microbes in food processing resulting in food spoilage, transmission of diseases and significant food hygiene and safety issues. This study elucidates biofilm formation of E. coli O157:H7 and L. monocytogenes ATCC 7644 grown under food related environmental stress conditions of varying pH (5.0;7.0; and 8.5) and temperature (15, 25 and 37 ℃). Both strains showed confluent biofilm formation at 25 ℃ and 37 ℃, at pH 8.5 after 5 days. E. coli showed curli fimbriae production at various temperatures, while L. monocytogenes did not show pronounced expression. Swarm, swimming and twitching plate assays were used to determine strain motilities. Characterization of cell hydrophobicity was done using the microbial adhesion to hydrocarbons (MATH) assay using n-hexadecane. Both strains showed hydrophilic characteristics as they fell within a < 20 % interval. FT-IR revealed COOH at 1622 cm-1, and a strong absorption band at 3650 cm-1 – 3200 cm-1 indicating the presence of both -OH and -NH groups. Both strains were hydrophilic and could form biofilm at different combinations of temperature and pH. EPS produced in both species proved to be an acidic hetero-polysaccharide.

Keywords: biofilm, pathogens, hydrophobicity, motility

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Authors: Bilal Ahmad Ashwar, Inam u nisa, Asima Shah, Adil Gani, Farooq Ahmad Masoodi

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The effects of 5% BHT and green tea extracts (GTE) on the physical, barrier, mechanical, thermal and antioxidant properties of potato starch films were investigated. Results showed both BHT and GTE significantly lowered solubility of films. Addition of BHT significantly decreased water vapour transmission rate. Both BHT and GTE promoted significant increase in the elastic modulus but a decrease in % EAB, however BHT was more effective in increasing elastic modulus. Increase in glass transition temperature (Tg) and enthalpy of transition (ΔH) of films was observed with the incorporation of GTE and BHT. Scanning electron microscopy (SEM) revealed smooth surface of the films. The DPPH radical scavenging ability of both BHT and GTE films were stronger in fatty food stimulant (95% ethanol. The GTE and BHT films were individually applied to fresh beef samples and were stored at 4 0C and room temperature for 10 days. Metmyoglobin formation and lipid oxidation (TBARS) were monitored periodically. The addition of GTE extracts and BHT resulted in decreases in metmyoglobin and TBARS values. We conclude that extracts of GTE and BHT have potential as preservatives for fresh beef.

Keywords: starch film, WVTR, tensile properties, SEM, thermal analysis, DPPH scavenging activity, TBARS, metmyoglobin

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Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

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Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

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Authors: Manar Ahmed Elbadawy

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Background: Empirical evidence suggested that improving nursing teamwork (NTW) may be the key to reducing medical error. The functioning nursing teams require open communication, mutual respect, and shared mental models to activate quality patient care. The complexity and the high demands for specialized nursing knowledge and skill also require nursing staff to consult with one another and work in teams regularly. The current study aimed to evaluate the effect of the nursing teamwork training program on nursing teamwork effectiveness. Design: A quasi-experimental (one group pretest-posttest) design was utilized. Three medical intensive care units at a teaching hospital affiliated to Cairo University Hospital, Egypt. Subjects: A convenient sample of 48 nursing staff worked at the selected units. The Nursing Teamwork Observational Checklist was used. Results: Total (NTW) mean scores exhibited quite elevation post-program implementation compared to preprogram and showed little decrease 3 months later ( = 2.52, SD = ± 0.27, mean % =51.98, = 2.72, SD = ± 0.20, mean %=72.45, = 2.67, SD = ± 0.11, mean %= 67.48 respectively). Conclusion: Implementation of (NTW) training program had a positive effect on increasing (NTW) effectiveness. Regular and frequent short-term teamwork training is important to be introduced as well as sustainable monitoring is required to ensure nursing attitudes, knowledge and skills’ change about teamwork effectiveness.

Keywords: effectiveness, nursing, teamwork, training

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Authors: Masoud Mahdavi

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The structure is made using different members and combining them with each other. These members are basically based on technical and engineering principles and are combined in different ways and have their own unique effects on the building. Trusses are one of the most common and important members of the structure, accounting for a large percentage of the power transmission structure in the building. Different types of trusses are based on structural needs and evaluating and making complete comparisons between them is one of the most important engineering analyses. In the present study, four types of trusses have been studied; 1) Hawe truss, 2) Pratt truss, 3) k truss, and 4) warren truss, under cyclic loading for 80 seconds. The trusses are modeled in 3d using st₃₇ steel. The results showed that Hawe trusses had higher values ​​than all other trusses (k, Pratt and Warren) in all the studied indicators. Indicators examined in the study include; 1) von Mises stresses, 2) displacement, 3) support force, 4) velocity, 5) acceleration, 6) capacity (hysteresis curve) and 7) energy diagram. Pratt truss in indicators; Mises stress, displacement, energy have the least amount compared to other trusses. K truss in indicators; support force, speed and acceleration are the lowest compared to other trusses.

Keywords: hawe truss, pratt truss, K truss, warren truss, cyclic loading, finite element method

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Authors: Haile Berihulay, Chenglong Luo

Abstract:

Avian influenza, commonly known as bird flu, is a highly contagious viral disease primarily affecting poultry and wild birds, with significant implications for both animal health and public safety. The influenza virus (IV) is notorious for its ability to mutate and infect multiple species, including humans, leading to severe consequences. Avian influenza poses considerable pandemic risks due to the potential evolution of low pathogenic avian influenza (LPAI) into highly pathogenic avian influenza (HPAI), which can cause rapid outbreaks in domestic flocks. While AVI viruses typically do not replicate well in humans, strains such as H5N1 and H7N9 have crossed the species barrier, raising alarm over human infections. The recent documentation of human transmission of the H5N8 strain from birds underscores the ongoing threat posed by avian influenza. This review necessitates a thorough discussion about the genetic foundation of viral pathogens, identifying key candidate genes linked to disease resilience, and discussing powerful tools. This review can help researchers to comprehensively overview the disease severity and combat related to AIV, which causes significant economic impact and set effective control strategies to mitigate the risks associated with avian influenza outbreaks.

Keywords: Avian, candidate genes, chicken, molecular, pathogen, virus

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Authors: Abdel Ghany F. Shoair, Mai M. A. H. Shanab

Abstract:

The basic aqueous systems NiSO4.6H₂O / K₂S₂O₈ (PH= 14) or NiSO₄.6H₂O / KBrO₃ (PH = 11.5) were ‎investigated ‎for the ‎catalytic conversion benzyl alcohol and ‎some para-substituted benzyl ‎alcohols to their ‎corresponding ‎acids in 75-97 % yield at room ‎temperature. The active species ‎was isolated and characterized by scanning ‎electron ‎microscopy (SEM), ‎‎transmission electron microscopy (TEM), X-ray ‎powder diffraction, EDX and ‎‎FT-IR ‎techniques and identified as NiO₂ nanoparticles (NPNPs). The SEM and ‎TEM images of nickel peroxide samples show a fine spherical-like ‎aggregation of ‎NiO₂ molecules with a nearly homogeneous partial size and confirm the ‎aggregation's size ‎to ‎be in the range of 2-3 nm. The yields, turnover (TO) and turn ‎over frequencies (TOF) were calculated. ‎It was noticed ‎that the aromatic alcohols ‎containing para-substituted electron donation groups gave better ‎‎yields than ‎those having electron-withdrawing groups. The optimum conditions for this ‎‎catalytic reaction ‎were studied using benzyl alcohol as a model. The mechanism ‎of the ‎catalytic conversion reaction was ‎suggested, in which the produced ‎(NPNPs) convert alcohols ‎to acids in two steps through the formation of the ‎‎corresponding aldehyde. The produced ‎NiO, because of this conversion, is ‎converted again to (NPNPs) by ‎an excess of K₂S₂O₈ or KBrO₃. This ‎catalytic cycle continues ‎until all the substrate is oxidized.

Keywords: Nickel, oxidation, catalysts, benzyl alcohol

Procedia PDF Downloads 77

Authors: M. S. Abd El-Sadek, Mahmoud A. Omar, Gharib M. Taha

Abstract:

Photodegradation of methylene blue in the presence of tin dioxide (SnO₂) nanoparticles under solar light irradiation are known to be an effective photocatalytic process. In this study, pure and silver (Ag) doped tin dioxide (SnO₂) nanoparticles were prepared at calcination temperature (800ºC) by a modified sol-gel method and studied for their photocatalytic activity with methylene blue as a test contaminant. The characterization of undoped and doped SnO₂ photocatalyst was studied by X-rays diffraction patterns (XRD), transmission electron microscopy (TEM), Fourier Transform Infrared Spectroscopy (FT-IR) and Energy Dispersive X-ray Microanalysis (EDX). The catalytic degradation of methylene blue in aqueous media was studied using UV-Vis spectrophotometer to monitor the degradation process by measuring its absorption spectra. The main absorption peak of methylene blue is observed at λ= 664 nm. The change in the percent of silver in the catalyst affects the photoactivity of SnO₂ on the degradation of methylene blue. The photoactivity of pure SnO₂ was found to be a maximum at dose 0.2 gm of the catalyst with 100 ml of 5 ppm methylene blue in the water. Within 210 min of photodegradation (under sunlight) after leaving the reaction for 90 minutes in the dark to avoid the effect of adsorption, the pure SnO₂ at calcination temperature 800ºC exhibited the best photocatalytic degradation with removal percentage of 93.66% on methylene blue degradation under solar light.

Keywords: SnO₂ nanoparticles, methylene blue degradation, photocatalysis, silver doped-SnO₂

Procedia PDF Downloads 142

Authors: Jyh-Cherng Gu, Ming-Ta Yang, Chao-Fong Yan, Hsin-Yung Chung, Yung-Ruei Chang, Yih-Der Lee, Chen-Min Chan, Chia-Hao Hsu

Abstract:

There are a number of distributed generations (DGs) installed in microgrid, which may have diverse path and direction of power flow or fault current. The overcurrent protection scheme for the traditional radial type distribution system will no longer meet the needs of microgrid protection. Integrating the intelligent electronic device (IED) and a supervisory control and data acquisition (SCADA) with IEC 61850 communication protocol, the paper proposes a microgrid protection management system (MPMS) to protect power system from the fault. In the proposed method, the MPMS performs logic programming of each IED to coordinate their tripping sequence. The GOOSE message defined in IEC 61850 is used as the transmission information medium among IEDs. Moreover, to cope with the difference in fault current of microgrid between grid-connected mode and islanded mode, the proposed MPMS applies the group setting feature of IED to protect system and robust adaptability. Once the microgrid topology varies, the MPMS will recalculate the fault current and update the group setting of IED. Provided there is a fault, IEDs will isolate the fault at once. Finally, the Matlab/Simulink and Elipse Power Studio software are used to simulate and demonstrate the feasibility of the proposed method.

Keywords: IEC 61850, IED, group Setting, microgrid

Procedia PDF Downloads 461