Search results for: parallel techniques

Authors: K. Verma, v. S. Moholkar

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In developed countries, water pollution caused by industrial discharge has emerged as a significant environmental concern over the past decades. However, despite ongoing efforts, a fully effective and sustainable remediation strategy has yet to be identified. This paper describes how enzymatic and sonochemical treatments have demonstrated great promise in degrading bio-refractory pollutants. Mainly, a compelling area of interest lies in the combined technique of sono-enzymatic treatment, which has exhibited a synergistic enhancement effect surpassing that of the individual techniques. This study employed the covalent attachment method to immobilize Laccase from Trametes versicolor onto amino-functionalized magnetic Fe₃O₄ nanoparticles. To comprehensively characterize the synthesized free nanoparticles and the laccase-immobilized nanoparticles, various techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), vibrating sample magnetometer (VSM), and surface area through Brunauer-Emmett-Teller (BET) were employed. The size of immobilized Fe₃O₄@Laccase was found to be 60 nm, and the maximum loading of laccase was found to be 24 mg/g of nanoparticle. An investigation was conducted to study the effect of various process parameters, such as immobilized Fe₃O₄ Laccase dose, temperature, and pH, on the % Chemical oxygen demand (COD) removal as a response. The statistical design pinpointed the optimum conditions (immobilized Fe₃O₄ Laccase dose = 1.46 g/L, pH = 4.5, and temperature = 66 oC), resulting in a remarkable 65.58% COD removal within 60 minutes. An even more significant improvement (90.31% COD removal) was achieved with ultrasound-assisted enzymatic reaction utilizing a 10% duty cycle. The investigation of various kinetic models for free and immobilized laccase, such as the Haldane, Yano, and Koga, and Michaelis-Menten, showed that ultrasound application impacted the kinetic parameters Vmax and Km. Specifically, Vmax values for free and immobilized laccase were found to be 0.021 mg/L min and 0.045 mg/L min, respectively, while Km values were 147.2 mg/L for free laccase and 136.46 mg/L for immobilized laccase. The lower Km and higher Vmax for immobilized laccase indicate its enhanced affinity towards the substrate, likely due to ultrasound-induced alterations in the enzyme's confirmation and increased exposure of active sites, leading to more efficient degradation. Furthermore, the toxicity and Liquid chromatography-mass spectrometry (LC-MS) analysis revealed that after the treatment process, the wastewater exhibited 70% less toxicity than before treatment, with over 25 compounds degrading by more than 75%. At last, the prepared immobilized laccase had excellent recyclability retaining 70% activity up to 6 consecutive cycles. A straightforward manufacturing strategy and outstanding performance make the recyclable magnetic immobilized Laccase (Fe₃O₄ Laccase) an up-and-coming option for various environmental applications, particularly in water pollution control and treatment.

Keywords: kinetic, laccase enzyme, sonoenzymatic, ultrasound irradiation

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Authors: Sherrene Bogle, Verlia Bogle, Tyrone Anderson

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In recent years, organizations have become increasingly interested in the possibility of analyzing social media as a means of gaining meaningful feedback about their products and services. The aspect based sentiment analysis approach is used to predict the sentiment for Twitter datasets for Digicel and Lime, the main mobile companies in Jamaica, using supervised learning classification techniques. The results indicate an average of 82.2 percent accuracy in classifying tweets when comparing three separate classification algorithms against the purported baseline of 70 percent and an average root mean squared error of 0.31. These results indicate that the analysis of sentiment on social media in order to gain customer feedback can be a viable solution for mobile companies looking to improve business performance.

Keywords: machine learning, sentiment analysis, social media, supervised learning

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Mala Nath, Nagamani Kompelli, Partha Roy, Snehasish Das

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Two new metal-based anticancer chemotherapeutic agents, [(Ph2Sn)2(HGuO)2(phen)Cl2] 1 and [(Ph3Sn)(HGuO)(phen)]- Cl.CH3OH.H2O 2, were designed, prepared and characterized by analytical and spectral (IR, ESI-Mass, 1H, 13C and 119Sn NMR) techniques. The proposed geometry of Sn(IV) in 1 and 2 is distorted octahedral and distorted trigonal-bipyramidal, respectively. Both 1 and 2 exhibit potential cytotoxicity in vitro against MCF-7, HepG-2 and DU-145 cell lines. The intrinsic binding constant (Kb) values of 1 (2.33 × 105 M-1) and 2 (2.46 × 105 M-1) evaluated from UV-Visible absorption studies suggest non-classical electrostatic mode of interaction via phosphate backbone of DNA double helix. The Stern-Volmer quenching constant (Ksv) of 1 (9.74 × 105 M-1) and 2 (2.9 × 106 M-1) determined by fluorescence studies suggests the groove binding and intercalation mode for 1 and 2, respectively. Effective cleavage of pBR322 DNA is induced by 1. Their interaction with DNA of cancer cells may account for potency.

Keywords: anticancer agents, DNA binding studies, NMR spectroscopy, organotin

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Authors: Rilwan Kayode Apalowo, Dimitrios Chronopoulos

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An approach for identifying the geometric and material characteristics of layered composite structures through an inverse wave and finite element methodology is proposed. These characteristics are obtained through multi-frequency single shot measurements. However, it is established that the frequency regime of the measurements does not matter, meaning that both ultrasonic and structural dynamics frequency spectra can be employed. Taking advantage of a full FE (finite elements) description of the periodic composite, the scheme is able to account for arbitrarily complex structures. In order to demonstrate the robustness of the presented scheme, it is applied to a sandwich composite panel and results are compared with that of experimental characterization techniques. Excellent agreement is obtained with the experimental measurements.

Keywords: structural identification, non-destructive evaluation, finite elements, wave propagation, layered structures, ultrasound

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Authors: Kourosh Modarresi

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The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

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Authors: Abolfazl Bezaatpour, Sahar Khatami

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Fe3O4 nanoparticles were prepared by the co-precipitation method and silica was then coated on the magnetic nanoparticles followed by modification with (3-aminopropyl) trimethoxysilane. Then, dioxomolybdenum(VI) Schiff base complex of N,N′-bis(5-chloromethyl-salicylidine)-1,2-phenylenediamine) was immobilized on the surface of magnetic nanoparticles as a heterogeneous catalyst. The catalyst was identified by scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM), X-ray diffraction, IR spectroscopy, diffuse reflectance spectra and atomic absorption spectroscopy techniques. The catalyst shows excellent catalytic activity in epoxidation of olefins using tert-butylhydroperoxide in 1,2-dichloroethane. In this report, the supported complex exhibited 100% selectivity for epoxidation with 100% conversion for cyclooctene. Nanocatalyst can be easily recovered by a magnetic field and reused for subsequent reactions for at least 5 times with less deterioration in catalytic activity.

Keywords: dioxomolybdenum (VI), epoxidation, nanocatalysis, nanoparticles, Schiff base

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Authors: Senem Suna

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Extraction of bioactive compounds from several food/food products comes as an important topic and new trend related with health promoting effects. As a result of the increasing interest in natural foods, different methods are used for the acquisition of these components especially polyphenols. However, special attention has to be paid to the selection of proper techniques or several processing technologies (supercritical fluid extraction, microwave-assisted extraction, ultrasound-assisted extraction, powdered extracts production) for each kind of food to get maximum benefit as well as the obtainment of phenolic compounds. In order to meet consumer’s demand for healthy food and the management of quality and safety requirements, advanced research and development are needed. In this review, advantages, and disadvantages of different extraction methods, their opportunities to be used in food industry and the effects of polyphenols are mentioned in details. Consequently, with the evaluation of the results of several studies, the selection of the most suitable food specific method was aimed.

Keywords: bioactives, extraction, powdered extracts, supercritical fluid extraction

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Authors: H. Mekki, A. Djerioui, S. Zeghlache, L. Chrifi-Alaoui

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Induction motor (IM)Induction motor (IM) are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system.

Keywords: electric vehicles, sliding mode control, induction motor drive, high gain observer

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Authors: Kulwinder Singh

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Punjab is one of the major labour exporting states of India. Every year more than 20,000 youths from Punjab attempt irregular migration. About 84 irregular migrants are from rural areas and 16 per cent from urban areas. Irregular migration could only be achieved if be organized through highly efficient international networks with the countries of origin, transit, and destination. A good number of Punjabis continue to immigrate into the UK for work through unauthorized means entering the country on visit visas and overstaying or getting ‘smuggled into’ the country with the help of transnational networks of agents. Although, the efforts are being made by the government to curb irregular migration through The Punjab Prevention of Human Smuggling Rules (2012, 2014) and Punjab Travel Regulation Act (2012), but yet it exists parallel to regular migration. Despite unprecedented miseries of irregular migrants and strict laws implemented by the state government to check this phenomenon, ‘why do Punjabis migrate abroad irregularly’ is the important question to answer. This study addresses this question through the comparison of irregular migration with regular one. In other words, this analysis reveals major causes, specifically economic ones, of irregular migration from rural Punjab. This study is unique by presenting economics of irregular migration, given previous studies emphasize the role of sociological and psychological factors. Addressing important question “why do Punjabis migrate abroad irregularly?”, the present study reveals that Punjabi, being far-sighted, endeavor irregular migration as it is, though, economically nonviable in short run, but offers lucrative economic gains as gets older. Despite its considerably higher cost viz-a-viz regular migration, it is the better employment option to irregular migrants with higher permanent income than local low paid jobs for which risking life has become the mindset of the rural Punjabis. Although, it carries considerably lower economic benefits as compared to regular migration, but provides the opportunity of migrating abroad to less educated, semi-skilled and language-test ineligible Punjabis who cannot migrate through regular channels. As its positive impacts on source and destination countries are evident, it might not be restricted, rather its effective management, through liberalising restrictive migration policies by destination nations, can protect the interests of all involved stakeholders.

Keywords: cost, migration, income, irregular, regular, remittances

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Authors: Hazel S. Cometa-Lamberte

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This paper presents the residential care workers reflections in working with children who were under protective custody and placed in a residential care facility for children. Key informant interviews and focus group discussion were employed in this study to analyze the views of residential care workers on the programs and services and case management system in residential care for children. Results suggest that working in a residential care facility for children needs the interplay of both the worker’s personal and professional values, knowledge and skills in working with children. Analyzing the residential care workers experiences in handling children in residential care facilities is vital for the improvement of the policies, programs and services, the repertoire of techniques and facilitate the creation of a new social work practice framework/model in child protection specifically in residential care facilities.

Keywords: child protection, residential care, residential care workers, social workers

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Authors: M. Arun, A. Kannan

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Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: acid orange 10, activated carbon, optimum adsorption conditions, statistical design

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Authors: Josep Domenech Mingot, Francisco Javier Esclapes Jover

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The arrival of the age of information and new technologies allowed humanity to see what the future has in store, but occasionally it also brings the opportunity to look through a window to the past, an opportunity to relive history. This paper introduces a prototype of a digital system that lets us peek into our past making use of augmented reality technologies. A 3D scene will be modeled and animated based on an old image, depicting an event of historical significance. From this scene, a video will be rendered, recreating the events that were taking place at the time. Also, a smartphone app will be created. This app will detect the original image with the smartphone’s camera, overlay the rendered video so that it fully covers it and track the detected image, so that the overlaying video can keep covering the image. The recreation of Alicante’s Central Market bombing during the Spanish Civil War is presented as a case study.

Keywords: augmented reality, digital heritage, history, multimedia, smartphone

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Authors: Babatunde Akeem Lawal

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In any organization, the primary aim is to maximize profit, but the major challenges facing them is the increase in cost of operation because of this there is increase in cost of production that could lead to inevitable cost control and cost reduction scheme which make it difficult for most organizations to operate at the cost efficient frontier. The study aims to critically examine and evaluate the application of cost control and cost reduction in organization performance and also to review budget as an effective tool of cost control and cost reduction. A descriptive survey research was adopted. A total number of 40 respondent retrieved were used for the study. The analysis of data collected was undertaken by applying appropriate statistical tools. Regression analysis was used to test the hypothesis with the use of SPSS. Based on the findings; it was evident that cost control has a positive impact on organizational performance and also the style of management has a positive impact on organizational performance.

Keywords: organization, cost reduction, cost control, performance, budget, profit

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

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The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

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Authors: Fangwen Ni, Hongpeng Xu

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When disasters occur, it is important to provide temporary shelters to protect victims from their environment and to comfort them with privacy and dignity. However, the commonly used shelters like tents and shanties can not ensure a comfortable condition. Furthermore, the demand for more energy and less pollution has become a major challenge. Focusing on the sustainable of temporary shelters, this study intends to clarify the essential role of temporary shelters before the reconstruction work is done. The paper also identifies the main problems from three aspects including spatial layout, thermal comfort and utilization of passive technology. Moreover, it expounds the passive strategies of ecological design by case study and simulation. It is found that the living condition of shelters can be improved from the perspective of architectural space, ventilation theory and construction techniques. Regardless of being temporary, these shelters are crucial elements in emergency situations and should be taken more seriously.

Keywords: architectural space, construction technique, sustainable strategy, temporary shelter

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Authors: Lucia Varra, Marzia Timolo

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The interest of scholars towards corporate sustainability has strengthened in recent years in parallel with the growing need to undertake paths of cultural and organizational change, as a way for greater competitiveness and stakeholders’ satisfaction. In fact, studies on the business sustainability, while on the one hand have integrated the three dimensions of sustainability that existed for some time in the economic approaches (economic, environmental and social dimensions), on the other hand did not give rise to an organic construct that puts together the aspects of strategic management with corporate social responsibility and even less with the organizational issues. Therefore some important questions remain open: Which organizational structure and which operational mechanisms are coherent or propitious to a sustainability strategy? Existing studies appear to be fragmented, although some aspects have shared importance: knowledge management, human resource, management, leadership, innovation, etc. The construction of a model of sustainable organization that supports the sustainability strategy no longer seems to be postponed, as is its connection with the main practices of measuring corporate social responsibility performance. The paper aims to identify the organizational characteristics of a sustainable corporate. To this end, from a theoretical point of view the work examines the main existing literary contributions and, from a practical point of view, it presents a business case referring to a service organization that for years has undertaken the sustainability strategy. This paper is divided into two parts: the first part concerns a review of the main articles on the strategic management topic and the main organizational issues raised by the literature, such as knowledge management, leadership, innovation, etc.; later, a modeling of the main variables examined by scholars and an integration of these with the international measurement standards of CSR is proposed. In the second part, using the methodology of the case study company, the hypotheses and the structure of the proposed model that aims to integrate the strategic issues with the organizational aspects and measurement of sustainability performance, are applied to an Italian company, which has some organizational and human resource management interventions are in place to align strategic decisions with the structure and operating mechanisms of the structure. The case presented supports the hypotheses of the model.

Keywords: CSR, strategic management, sustainable leadership, sustainable human resource management, sustainable organization

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Authors: Stephen V. Crowder, Jonathan W. Lane

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With short production development times, there is an increased need to demonstrate product reliability relatively quickly with minimal testing. In such cases there may be few if any observed failures. Thus it may be difficult to assess reliability using the traditional reliability test plans that measure only time (or cycles) to failure. For many components, degradation measures will contain important information about performance and reliability. These measures can be used to design a minimal test plan, in terms of number of units placed on test and duration of the test, necessary to demonstrate a reliability goal. In this work we present a case study involving an electronic component subject to degradation. The data, consisting of 42 degradation paths of cycles to failure, are first used to estimate a reliability function. Bootstrapping techniques are then used to perform power studies and develop a minimal reliability test plan for future production of this component.

Keywords: degradation measure, time to failure distribution, bootstrap, computational science

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Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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Authors: Paulomi Polly Burey, Mark Lynch

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It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

Procedia PDF Downloads 152

Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 75

Authors: Yameen Ahmed, Jamshid Hussain, Farman Ullah, Sohaib Asif

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The investigation aims at the synthesis of copper oxide and cobalt oxide nanoparticles using Spinacia oleracea leaf extract. These nanoparticles have many properties and applications. They possess antimicrobial catalytic properties and also they can be used in energy storage materials, gas sensors, etc. The Spinacia oleracea leaf extract behaves as a reducing agent in nanoparticle synthesis. The plant extract was first prepared and then treated with copper and cobalt salt solutions to get the precipitate. The salt solutions used for this purpose are copper sulfate pentahydrate (CuSO₄.5H₂O) and cobalt chloride hexahydrate (CoCl₂.6H₂O). The UV-Vis, XRD, EDX, and SEM techniques are used to find the optical, structural, and morphological properties of copper oxide and cobalt oxide nanoparticles. The UV absorption peaks are at 326 nm and 506 nm for copper oxide and cobalt oxide nanoparticles.

Keywords: cobalt oxide, copper oxide, green synthesis, nanoparticles

Procedia PDF Downloads 195

Authors: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

Procedia PDF Downloads 156

Authors: H. Jeries, N. Volkova, C. G. Iglesias, M. Najjar, M. Rosenblat, M. Aviram, T. Hayek

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Background: Synthetic forms of glucocorticoids (e.g., prednisone, prednisolone) are anti-inflammatory drugs which are widely used in clinical practice. The role of glucocorticoids (GCs) in cardiovascular diseases including atherosclerosis is highly controversial, and their impact on macrophage foam cell formation is still unknown. Our aim was to investigate the effects of prednisone or its active metabolite, prednisolone, on macrophage oxidative stress and lipid metabolism using in-vivo, ex-vivo and in-vitro systems. Methods: The in-vivo study included C57BL/6 mice which were intraperitoneally injected with prednisone or prednisolone (5mg/kg) for 4 weeks, followed by lipid metabolism analyses in the mice aorta, and in peritoneal macrophages (MPM). In the ex-vivo study, we analyzed the effect of serum samples obtained from 9 healthy volunteers before or after treatment with oral prednisone (20mg for 5 days), on J774A.1 macrophage atherogenicity. In-vitro studies were conducted using J774A.1 macrophages, human monocyte derived macrophages (HMDM) and fibroblasts. Cells were incubated with increasing concentrations (0-200 ng/ml) of prednisone or prednisolone, followed by determination of cellular oxidative status, triglyceride and cholesterol metabolism. Results: Prednisone or prednisolone treatment resulted in a significant reduction in triglycerides and mainly in cholesterol cellular accumulation in MPM or in J774A.1 macrophages incubated with human serum. Similar resulted were noted in HMDM or in J774A.1 macrophages which were directly incubated with the GCs. These effects were associated with GCs inhibitory effect on triglycerides and cholesterol biosynthesis rates, throughout downregulation of diacylglycerol acyltransferase1 (DGAT1) expression, and of the sterol regulatory element binding protein (SREBP2) and HMGCR expression, respectively. In parallel to prednisone or prednisolone induced reduction in macrophage triglyceride content, paraoxonase 2 (PON2) expression was significantly upregulated. GCs-induced reduction of cellular triglyceride and cholesterol mass was mediated by the GCs receptors on macrophages since the GCs receptor antagonist (RU 486) abolished these effects. In fibroblasts, unlike macrophages, prednisone or prednisolone showed no anti-atherogenic effects. Conclusions: Prednisone or prednisolone are anti-atherogenic since they protected macrophages from lipid accumulation and foam cell formation.

Keywords: atherosclerosis, cholesterol, foam cell, macrophage, prednisone, prednisolone, triglycerides

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Authors: Jian Xu, Xiaochun Yun, Yongzheng Zhang, Yafei Sang, Zhenyu Cheng

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Network attack prevention is a critical research area of information security. Network attack would be oppressed if attribution techniques are capable to trace back to the attackers after the hacking event. Therefore attributing these attacks to a particular identification becomes one of the important tasks when analysts attempt to differentiate and profile the attacker behind a piece of attack trace. To assist analysts in expose attackers behind the scenes, this paper researches on the connections between attribution traces and proposes probabilistic relevance based attribution patterns. This method facilitates the evaluation of the plausibility relevance between different traceable identifications. Furthermore, through analyzing the connections among traces, it could confirm the existence probability of a certain organization as well as discover its affinitive partners by the means of drawing relevance matrix from attribution traces.

Keywords: attribution trace, probabilistic relevance, network attack, attacker identification

Procedia PDF Downloads 347

Authors: Temesgen Geremew

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This study investigates the evolution of polythiophene nanoparticles (PThNPs) as surface-enhanced Raman spectroscopy (SERS) sensors for Pb²⁺ detection in river water. We analyze the PThNPs' optical, structural, and morphological properties at different stages of their development to understand their SERS performance. Techniques like UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) are employed for characterization. The SERS sensitivity towards Pb²⁺ is evaluated by monitoring the peak intensity of a specific Raman band upon increasing metal ion concentration. The study aims to elucidate the relationship between the PThNPs' characteristics and their SERS efficiency for Pb²⁺ detection, paving the way for optimizing their design and fabrication for improved sensing performance in real-world environmental monitoring applications.

Keywords: polythiophene, Pb2+, SERS, nanoparticles

Procedia PDF Downloads 33

Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

Procedia PDF Downloads 465

Authors: Osama Terra, Hatem Hussein

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Calibration of Optical Time Domain Reflectometer (OTDR) is crucial for the accurate determination of loss budget for long optical fiber links. In this paper, the calibration of the attenuation scale of an OTDR using two different techniques is discussed and implemented. The first technique is the external modulation method (EM). A setup is proposed to calibrate an OTDR over a dynamic range of around 15 dB based on the EM method. Afterwards, the OTDR is calibrated using two standard reference fibers (SRF). Both SRF are calibrated using cut-back technique; one of them is calibrated at our home institute (the National Institute of Standards – NIS) while the other at the National Physical Laboratory (NPL) of the United Kingdom to confirm our results. In addition, the parameters contributing the calibration uncertainty are thoroughly investigated. Although the EM method has several advantages over the SRF method, the uncertainties in the SRF method is found to surpass that of the EM method.

Keywords: optical time domain reflectometer, fiber attenuation measurement, OTDR calibration, external source method

Procedia PDF Downloads 449