Abstract: This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topologically order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for exchange photon energy with molecules without changes in topology (i.e., chemical transformation into products do not propagate any changes or variation in the network topology of physical configuration). The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure, and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies, which are automated, real-time, reliable, reproducible and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody–antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due the pathogenic archival architecture of cell clusters.
Abstract: For emergency and relief service providers such as pre-hospital emergencies, quick arrival at the scene of an accident or any EMS mission is one of the most important requirements of effective service delivery. EMS Response time (the interval between the time of the call and the time of arrival on scene) is a critical factor in determining the quality of pre-hospital Emergency Medical Services (EMS). This is especially important for heart attack, stroke, or accident patients that seconds are vital in saving their lives. Location-based e-services can be broadly defined as any service that provides information pertinent to the current location of an active mobile handset or precise address of landline phone call at a specific time window, regardless of the underlying delivery technology used to convey the information. According to research, one of the effective methods of meeting this goal is determining the location of the caller via the cooperation of landline and mobile phone operators in the country. The follow-up of the Communications Regulatory Authority (CRA) organization has resulted in the receipt of two separate secured electronic web services. Thus, to ensure human privacy, a secure technical architecture was required for launching the services in the pre-hospital EMS information management system. In addition, to quicken medics’ arrival at the patient's bedside, rescue vehicles should make use of an intelligent transportation system to estimate road traffic using a GPS-based mobile navigation system independent of the Internet. This paper seeks to illustrate the architecture of the practical national model used by the Iranian EMS organization.
Abstract: This paper presents a multiple criteria evaluation analysis for airline quality rating using the preference analysis for reference ideal solution (PARIS) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The airline quality rating was developed as an objective method for assessing airline quality on combined multiple performance criteria and the importance weights of criteria. The selected multiple performance criteria were determined as on-time arrivals, mishandled baggage, involuntary denied boardings, and consumer complaints. The multiple criteria decision making analysis results show that the alternative ( a2) airline is the best-rated airline.
Abstract: Most educational institutions were compelled to switch over to the online mode of teaching, learning, and assessment due to the lockdown when the corona pandemic started around the globe in the early part of the year 2020. However, they faced a unique set of challenges in delivering knowledge and skills to their students as well as formulating a proper assessment policy. This paper investigates whether there is an impact on the student Semester Grade Point Average (SGPA) due to the online mode of teaching and learning assessment at the Department of Electrical and Electronic Engineering (EEE) of Southeast University (SEU). Details of student assessments are discussed. Then students’ grades were analyzed to find out the impact on SGPA based on the z-test by finding the standard deviation (). It also pointed out the challenges associated with the online classes and assessment strategies to be adopted during the online assessment. The student admission, course advising, and registration statistics were also presented in several tables and analyzed based on the change in percentage to observe the impact on it due to the pandemic. In summary, it was observed that the students’ SGPAs are not affected but student course advising and registration were affected slightly by the pandemic. Finally, the paper provides some recommendations to improve the online teaching, learning, assessment, and evaluation system.
Abstract: Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat and case recorded using long wave infrared, short wave infrared, medium wave infrared and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using You Only Look Once, background subtraction, silhouettes extraction and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the Principal Component Analysis and recognized using different classifiers. The comparative results with the different classifier show that Linear Discriminant Analysis outperform other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.
Abstract: All companies are confronted with the need to innovate in order to meet market demands. In so doing they are challenged with the dilemma of whether to aim to be first into the market with a new innovative product, or to deliberately wait and learn from a pioneers’ mistakes; potentially avoiding higher risks. It is therefore important to critically understand from a first mover advantage and disadvantage perspective the decision-making implications of defence industry transformation onset by an innovative paradigm shift. This paper will argue that the type of industry characteristics matter, especially when considering what role the clients play in the innovation process and what their level of influence is. Through investigation of qualitative case study research, this inquiry will focus on first mover advantages and first mover disadvantages with a view to establish practical and value-added academic findings by focusing on specific industries where the clients play an active role in cooperation with the supplier innovation. The resulting findings will help managers to mitigate risk in innovative technology introduction. A selection from several defence industry innovations is specifically chosen because of the client–supplier relationship that typically differs from traditional first mover research. In this instance, case studies will be used referencing vertical-take-off-and-landing defence equipment innovations.
Abstract: In this paper, the comparison of composite programming and compromise programming for the aircraft selection problem is discussed using the multiple criteria decision analysis method. The decision making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as aircraft selection problems. The proposed technique gives more efficient results by extending the composite programming and compromise programming, which are widely used in modeling multiple criteria decisions. The proposed model is applied to a practical decision problem for evaluating and selecting aircraft problems.A selection of aircraft was made based on the proposed approach developed in the field of multiple criteria decision making. The model presented is solved by using the following methods: composite programming, and compromise programming. The importance values of the weight coefficients of the criteria are calculated using the mean weight method. The evaluation and ranking of aircraft are carried out using the composite programming and compromise programming methods. In order to determine the stability of the model and the ability to apply the developed composite programming and compromise programming approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ and q in the first part. The second part of the sensitivity analysis relates to the application of different multiple criteria decision making methods, composite programming and compromise programming. In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient of the ranks obtained was calculated which confirms the applicability of all the proposed approaches.
Abstract: In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.
Abstract: The refractory high entropy alloys are potential materials for high-temperature applications because of their ability to retain high strength up to 1600°C. However, their practical applications were limited due to poor elongation at room temperature. Therefore, decreasing the average valence electron concentrations (VEC) is an effective design strategy to improve the intrinsic ductility of refractory high entropy alloys. In this work, the high-entropy alloy TaNbHfZrTi was processed at room temperature by each step reverse rolling up to a 90% reduction in thickness. Subsequently, the reverse rolled 90% samples were utilized for annealing treatment at 800°C and 1000°C for 1 h to understand phase stability, microstructure, texture, and mechanical properties. The reverse rolled 90% condition contains body-centered cubic (BCC) single-phase; upon annealing at 800 °C, the formation of secondary phase BCC-2 prevailed. The partial recrystallization and complete recrystallization microstructures were developed for annealed at 800°C and 1000°C, respectively. The reverse rolled condition and 1000°C annealed temperature exhibit extraordinary room temperature tensile properties with high ultimate tensile strength (UTS) without compromising loss of ductility called “strength-ductility” trade-off. The reverse-rolled 90% and annealing treatment carried out at temperature about 1000°C for 1 h consist of UTS 1430 MPa and 1556 MPa with an appreciable amount of 21% and 20% elongation, respectively. The development of hierarchical microstructure prevailed for the annealed 1000°C which led to the simultaneous increase in tensile strength and elongation.
Abstract: With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.
Abstract: Energy is the major force that drives any country`s socio-economic development. Without electricity, the country could be at risk of losing many potential investors. As such, good policy implementation could play a significant role in harnessing all the available energy resources. Nigeria has the prospects of meeting its energy demand and supply if there are good policies and proper implementation of them. The current energy supply needs to improve in order to meet the present and future demand. Sustainable energy development is the way forward. Renewable energy plays a significant role in socio-economic development of any country. Nigeria is a country blessed with abundant natural resources such as, solar radiation for solar power, water for hydropower, wind for wind power, and biomass from both plants and animal’s waste. Both conventional energy (fossil fuel) and unconventional energy (renewable) could be harmonized like in the case of energy mix or biofuels. Biofuels like biodiesel could be produced from biomass and combined with petro-diesel in different ratios. All these can be achieved if good policy is in place. The challenges could be well overcome with good policy, masses awareness, technological knowledge and other incentives that can attract investors in Nigerian energy sector.
Abstract: As the deployment of the Fifth Generation (5G) mobile communication networks take shape all over the world, achieving spectral efficiency, energy efficiency, and dealing with interference are among the greatest challenges encountered so far. The aim of this study is to mitigate inter-cell interference (ICI) in a multi-cell multi-antenna system while maximizing the spectral efficiency of the system. In this study, a system model was devised that showed a miniature representation of a multi-cell multi-antenna system. Based on this system model, a convex optimization problem was formulated to maximize the spectral efficiency of the system while mitigating the ICI. This optimization problem was solved using CVX, which is a modeling system for constructing and solving discipline convex programs. The solutions to the optimization problem are sub-optimal coordinated beamformers. These coordinated beamformers direct each data to the served user equipments (UEs) in each cell without interference during downlink transmission, thereby maximizing the system-wide spectral efficiency.
Abstract: The construction industry plays an important role in environmental and carbon emissions as it consumes a huge amount of natural resources and energy. Sustainable engineering involves the process of planning, design, procurement, construction and delivery in which the whole building and construction process resulting from building and construction can be effectively and sustainability managed to achieve the use of natural resources. Implementation of sustainable technology development and innovation, adoption of the advanced construction process and facilitate the facilities management to implement the energy and waste control more accurately and effectively. Study and research in the relationship of BIM and environment assessment tools lack a clear discussion. In this paper, we will focus on the synergy of BIM technology and sustainable engineering in the AEC industry and outline the key factors which enhance the use of advanced innovation, technology and method and define the role of stakeholders to achieve zero-carbon emission toward the Paris Agreement to limit global warming to well below 2°C above pre-industrial levels. A case study of the adoption of Building Information Modeling (BIM) and environmental assessment tools in Hong Kong will be discussed in this paper.
Abstract: There has been a rising trend in using impulse current generators to investigate the lightning strike protection of materials including aluminum and composites in structures such as wind turbine blade and aircraft body. The focus of this research is to present an impulse current generator built in the High Voltage Lab at Mississippi State University. The generator is capable of producing component A and D of the natural lightning discharges in accordance with the Society of Automotive Engineers (SAE) standard, which is widely used in the aerospace industry. The generator can supply lightning impulse energy up to 400 kJ with the capability of producing impulse currents with magnitudes greater than 200 kA. The electrical circuit and physical components of an improved impulse current generator are described and several lightning strike waveforms with different amplitudes is presented for comparing with the standard waveform. The results of this study contribute to the fundamental understanding the functionality of the impulse current generators and present an impulse current generator developed at the High Voltage Lab of Mississippi State University.
Abstract: Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC’s dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.
Abstract: The paper presents a process to obtain glutathione-modified titanium oxide nanoparticles. The processes were carried out in a microwave radiation field. The influence of the molar ratio of glutathione to titanium oxide and the effect of the fold of NaOH vs. stoichiometric amount on the size of the formed TiO2 nanoparticles was determined. The physicochemical properties of the obtained products were evaluated using dynamic light scattering (DLS), transmission electron microscope- energy-dispersive X-ray spectroscopy (TEM-EDS), low-temperature nitrogen adsorption method (BET), X-Ray Diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) microscopy methods. The size of TiO2 nanoparticles was characterized from 30 nm to 336 nm. The release of titanium ions from the prepared products was evaluated. These studies were carried out using different media in which the powders were incubated for a specific time. These were: water, SBF and Ringer's solution. The release of titanium ions from modified products is weaker compared to unmodified titanium oxide nanoparticles. The reduced release of titanium ions may allow the use of such modified materials as substances in drug delivery systems.
Abstract: Marine shipping has now become one of the major worldwide contributors to pollution and greenhouse gas emissions. Hybrid ships technology based on multiple energy sources has taken a great scope of research to get rid of ship emissions and cut down fuel expenses. Insufficiency between power generated and the demand load to withstand the transient behavior on ships during severe climate conditions will lead to a blackout. Thus, an efficient energy management system (EMS) is a mandatory scope for achieving higher system efficiency while enhancing the lifetime of the onboard storage systems is another salient EMS scope. Considering energy storage system conditions, both the battery state of charge (SOC) and temperature represent important parameters to prevent any malfunction of the storage system that eventually degrades the whole system. In this paper, a two battery packs ratio fuzzy logic control model is proposed. The overall aim is to control the charging/discharging current while including both the battery SOC and temperature in the energy management system. The full designs of the proposed controllers are described and simulated using Matlab. The results prove the successfulness of the proposed controller in stabilizing the system voltage during both loading and unloading while keeping the energy storage system in a healthy condition.
Abstract: Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.
Abstract: E-maintenance is a relatively recent concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This is clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification, cellular connectivity, connectivity to the vehicle computer, and connectivity to analog and digital sensors by means of a specially targeted design of expansion board. Specifically, the latter offers a number of adaptability features to cope with the diverse sensor types employed in different vehicles. In standard mode, the IoT sensor node communicates to the data center through cellular network, transmitting all digital/digitized sensor data, IoT device identity and position. Moreover, the proposed IoT sensor node offers connectivity, through WiFi and an appropriate application, to smart phones or tablets allowing the registration of additional vehicle- and driver-specific information and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware.
Abstract: Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization were only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the Hydrocarbon Spectra Slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven different hydrocarbon oils (crude and refined oil) taken on 10 different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).