Search results for: COD removal efficiency

Authors: Zaheer Ahmad, Afzal Shah

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pH responsive block copolymers consist of mPEG and glutamic acid units were syntheiszed in different formulations. The synthesized polymers were structurally investigated. Doxorubicin Hydrocholide (DOX-HCl) as a chemotherapy medication for the treatment of cancer was selected. DOX-HCl was loaded and their drug loading content and drug loading efficiency were determined. The nanocarriers were obtained in small size, well shaped and slightly negative surface charge. The release study was carried out both at pH 7.4 and 5.5 and it was revealed that the release was sustained and in controlled manner and there was no initial burst release. The in vitro release study was further carried out for different formulations with different glutamic acid moieties. Time dependent cell proliferation inhibition of the free drug and drug loaded nanoparticles against human breast cancer cell lines MCF-7 and Zr-75-30 was observed. Cellular uptakes and endocytosis were investigated by confocal laser scanning microscopy (CLSM) and flow cytometery. The biocompatibility, optimum size, shape and surface charge of the developed nanoparticles make the nanoparticles an efficient drug delivery carrier.

Keywords: doxorubicin, glutamic acid, cell proliferation inhibition, breast cancer cell

Procedia PDF Downloads 143

Authors: Mabrouka Algherinai, Fatma Karkouri

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Today, Short Message Service (SMS) is an important means of communication. SMS is not only used in informal environment for communication and transaction, but it is also used in formal environments such as institutions, organizations, companies, and business world as a tool for communication and transactions. Therefore, there is a need to secure the information that is being transmitted through this medium to ensure security of information both in transit and at rest. But, encryption has been identified as a means to provide security to SMS messages in transit and at rest. Several past researches have proposed and developed several encryption algorithms for SMS and Information Security. This research aims at comparing the performance of common Asymmetric encryption algorithms on SMS security. The research employs the use of three algorithms, namely RSA, McEliece, and RABIN. Several experiments were performed on SMS of various sizes on android mobile device. The experimental results show that each of the three techniques has different key generation, encryption, and decryption times. The efficiency of an algorithm is determined by the time that it takes for encryption, decryption, and key generation. The best algorithm can be chosen based on the least time required for encryption. The obtained results show the least time when McEliece size 4096 is used. RABIN size 4096 gives most time for encryption and so it is the least effective algorithm when considering encryption. Also, the research shows that McEliece size 2048 has the least time for key generation, and hence, it is the best algorithm as relating to key generation. The result of the algorithms also shows that RSA size 1024 is the most preferable algorithm in terms of decryption as it gives the least time for decryption.

Keywords: SMS, RSA, McEliece, RABIN

Procedia PDF Downloads 163

Authors: Gustavo J. Costa, Felipe J. Costa, Bruno L. Coelho, Ronaldo L. Cardoso, Rafael O. Santos, Israel S. Rêgo, Marco A. S. Minucci, Antonio C. Oliveira, Paulo G. P. Toro

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The Prof. Henry T. Nagamatsu Aerothermodynamics and Hipersonics Laboratory, of the Institute for Advanced Studies (IEAv) conducts research and development (R&D) of the Technological Demonstrator scramjet 14-X S, aiming atmospheric flight at 30 km altitude with the speed correspondent to Mach number 7, using scramjet technology providing hypersonic propulsion system based on supersonic combustion. Hypersonic aerospace vehicles with air-breathing supersonic propulsion system face extremal environments for super/hypersonic flights in terms of thermal and aerodynamic loads. Thus, it is necessary to use aerodynamic protection at the scramjet engine inlet to face the thermal and aerodynamic loads without compromising the efficiency of scramjet engine, taking into account: i) inlet design (boundary layer, oblique shockwave and reflected oblique shockwave); ii) wall temperature of the cowl and of the compression ramp; iii) supersonic flow into the combustion chamber. The aerodynamic protection of the scramjet engine inlet will act to prevent the engine unstart and match the predictions made by theoretical-analytical, numerical analysis and experimental research, during the atmospheric flight of the Technological Demonstrator scramjet 14-X S.

Keywords: 14-X, hypersonic, scramjet, supersonic combustion

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Authors: S. Kudlacik-Kramarczyk, M. Kedzierska, B. Tyliszczak

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Recently, the continuous development of medicine and related sciences has been observed. Particular emphasis is directed on the development of biomaterials, i.e., non-toxic, biocompatible and biodegradable materials that may improve the effectiveness of treatment as well as the comfort of patients. This is particularly important in the case of cancer treatment. Currently, there are many methods of cancer treatment based primarily on chemotherapy and the surgical removal of the tumor, but it is worth noting that these therapies also cause many side effects. Among women, the most common cancer is breast cancer. It may be completely cured, but the consequence of treatment is partial or complete breast mastectomy and radiation therapy, which results in severe skin burns. The skin of the patient after radiation therapy is very burned, and therefore requires intensive care and high frequency of dressing changes. The traditional dressing adheres to the burn wounds and does not absorb adequate amount of exudate from injuries and the patient is forced to change the dressing every 2 hours. Therefore, the main purpose was to develop an innovative combination of dressing material with drug carriers that may be used in anti-cancer therapy. The innovation of this solution is the combination of these two products into one system, i.e., a transdermal system with the possibility of a controlled release of the drug- cytostatic. Besides, the possibility of modifying the hydrogel matrix with aloe vera juice provides this material with new features favorable from the point of view of healing processes of burn wounds resulting from the radiation therapy. In this study, hydrogel materials containing protein spheres with the active substance have been obtained as a result of photopolymerization process. The reaction mixture consisting of the protein (albumin) spheres incorporated with cytostatic, chitosan, adequate crosslinking agent and photoinitiator has been subjected to the UV radiation for 2 minutes. Prepared materials have been subjected to the numerous studies including the analysis of cytotoxicity using murine fibroblasts L929. Analysis was conducted based on the mitochondrial activity test (MTT reduction assay) which involves the determining the number of cells characterized by proper metabolism. Hydrogel materials obtained using different amount of crosslinking agents have been subjected to the cytotoxicity analysis. According to the standards, tested material is defined as cytotoxic when the viability of cells after 24 h incubation with this material is lower than 70%. In the research, hydrogel polymer materials containing protein spheres incorporated with the active substance, i.e. a cytostatic, have been developed. Such a dressing may support the treatment of cancer due to the content of the anti-cancer drug - cytostatic, and may also provide a soothing effect on the healing of the burn wounds resulted from the radiation therapy due to the content of aloe vera juice in the hydrogel matrix. Based on the conducted cytotoxicity studies, it may be concluded that the obtained materials do not adversely affect the tested cell lines, therefore they can be subjected to more advanced analyzes.

Keywords: hydrogel polymers, cytostatics, drug carriers, cytotoxicity

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Authors: S. H. Abo Sabah, A. B. H. Kueh, M. A. Megat Johari, T. A. Majid

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In a recent study, a new bio-inspired honeycomb sandwich beam (BHSB) mimicking the head configuration of the woodpecker was developed. The beam consists of two carbon/epoxy composite face sheets, aluminum honeycomb core, and rubber core to enhance the repeated low-velocity impact resistance of sandwich structures. This paper aims to numerically enhance the repeated low-velocity impact resistance of the BHSB via optimizing the aluminum honeycomb core thickness. The beam was investigated employing three core thicknesses: 20 mm, 25 mm, and 30 mm at three impact energy levels (13.5 J, 15.55 J, 21.43 J). The results revealed that increasing the thickness of the aluminum honeycomb core to a certain level enhances the sandwich beam stiffness. The beam with the 25 mm honeycomb core thickness was the only beam that can sustain five repeated impacts achieving the highest impact resistance efficiency index, especially at high energy levels. Furthermore, the bottom face sheet of this beam developed the lowest stresses indicating that this thickness has a relatively better performance during impact events since it allowed minimal stress to reach the bottom face sheet. Overall, increasing the aluminum core thickness will increase the height of its cells subjecting it to buckling phenomenon. Therefore, this study suggests that the optimal thickness of the aluminum honeycomb core should be 65 % of the overall thickness of the sandwich beam to have the best impact resistance.

Keywords: sandwich beams, core thickness, impact behavior, finite element analysis, modeling

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Authors: Ross Lee, Pritpal Singh, Andrew Jester

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, new battery technology is necessary for grid applications to curtail these risks. Biological cells, such as human neurons and electrolytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell, akin to the charging/discharging of a battery cell. This work serves as the first step to developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na⁺-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior similar to human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: battery, biomimetic, electrolytes, human neurons, ion-selective membranes, membrane potential

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Authors: Maryam Esfandiari, Bohdan Fridrich

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On December 28, 2017, a wave of protests erupted in several Iranian cities. Protesters demonstrated against the president, Hasan Rohani, and theocratical nature of the regime. Iran has a recent history with protest movements, such as Green Movement responsible for demonstrations after 2009 Iranian presidential election. However, the 2017/2018 protests differ from the previous ones in terms of organization and agenda. The events show little to no central organization and seem as being sparked by grass root movements and by citizens’ fatigue of government corruption, authoritarianism, and economic problems of the country. Social media has played important role in communicating the protests to the outside world and also in general coordination. By using content analyses, this paper analyzes the visual content of Twitter posts published during the protests. It aims to find the correlation between their decentralized nature and nature of the tweets – either emotionally arousing or efficiency-elicit. Pictures are searched by hashtags and coded by their content, such as ‘crowds,’ ‘protest activities,’ ‘symbols of unity,’ ‘violence,’ ‘iconic figures,’ etc. The study determines what type of content prevails and what type is the most impactful in terms of reach. This study contributes to understanding the role of social media both as a tool and a space in protest organization and portrayal in countries with limited Internet access.

Keywords: twitter, Iran, collective action, protest

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Authors: Zhiyuan Jia, Xiuxiu Sun, Yong Chen, Liu Hai, Shuangqing Li

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The engine cooling water and exhaust gas contain a large amount of available energy. In order to improve energy efficiency, a steam injection technology based on waste heat recovery is proposed. The models of cooling water waste heat utilization, exhaust gas waste heat utilization, and exhaust gas-cooling water waste heat utilization were constructed, and the effects of the three modes on the performance of steam injection were analyzed, and then the feasibility of in-cylinder water injection steam technology based on waste heat recovery was verified. The research results show that when the injection water flow rate is 0.10 kg/s and the temperature is 298 K, at a cooling water temperature of 363 K, the maximum temperature of the injection water heated by the cooling water can reach 314.5 K; at an exhaust gas temperature of 973 K and an exhaust gas flow rate of 0.12 kg/s, the maximum temperature of the injection water heated by the exhaust gas can reach 430 K; Under the condition of cooling water temperature of 363 K, exhaust gas temperature of 973 K and exhaust gas flow rate of 0.12 kg/s, after cooling water and exhaust gas heating, the maximum temperature of the injection water can reach 463 K. When the engine is 1200 rpm, the water injection volume is 30 mg, and the water injection time is 36°CA, the engine power increases by 2% and the fuel consumption is reduced by 2.6%.

Keywords: cooling water, exhaust gas, extended range engine, steam injection, waste heat recovery

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: Fina O. Faithpraise, Effiong O. Obisung, Azele E. Peter, Chris R. Chatwin

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This study investigates and identifies consumer attitude as a major influence that results in non-technical losses in the Nigerian electricity supply sector. This discovery is revealed by the combination of quantitative and qualitative research to complete a survey. The dataset employed is a simple random sampling of households using electricity (public power supply), and the number of units chosen is based on statistical power analysis. The units were subdivided into two categories (household with and without electrical meters). The hypothesis formulated was tested and analyzed using a chi-square statistical method. The results obtained shows that the critical value for the household with electrical prepared meter (EPM) was (9.488 < 427.4) and those without electrical prepared meter (EPMn) was (9.488 < 436.1) with a p-value of 0.01%. The analysis demonstrated so far established the real-time position, which shows that the wrong attitude towards handling the electricity supplied (not turning off light bulbs and electrical appliances when not in use within the rooms and outdoors within 12 hours of the day) characterized the non-technical losses in the power sector. Therefore the adoption of efficient lighting attitudes in individual households as recommended by the researcher is greatly encouraged. The results from this study should serve as a model for energy efficiency and use for the improvement of electricity consumption as well as a stable economy.

Keywords: attitudinal change, household, non-technical losses, prepared meter

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Andrey Norov

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In the recent years, Samoilov Research Institute for Mineral Fertilizers JSC “NIUIF”, the oldest (established in September 1919) industry-oriented institute in Russia, has developed a range of sustainable, environment-friendly, zero-waste technologies that ensure minimal consumption of materials and energy resources and fully consistent with the principles of Green Chemistry that include: - Ecofriendly energy and resource saving technology of sulfuric acid from sulfur according to DC-DA scheme (double conversion - double absorption); - Improved zero-waste technology of wet phosphoric acid (WPA) by dihydrate-hemihydrate process applicable to various types of phosphate raw materials; - Flexible, efficient, zero-waste, universal technology of NP / NPS / NPK / NPKS fertilizers with maximum heat recovery from chemical processes; - Novel, zero-waste, no-analogue technology of granular PK / PKS / NPKS fertilizers with controlled dissolution rate and nutrient supply into the soil, which allows to process a number of wastes and by-products; - Innovative resource-saving joint processing of wastes from the production of phosphogypsum and fluorosilicic acid (FSA) into ammonium sulfate with simultaneous neutralization of fluoride compounds with no lime used. - New fertilizer technology of increased environmental and agrochemical efficiency (currently under development). All listed green technologies are patented with Russian and Eurasian patents. The development of ecofriendly, safe, green technologies is ongoing in JSC “NIUIF”.

Keywords: NPKS fertilizers, FSA, sulfuric acid, WPA

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Authors: Rajat Mittal, Jung Hee Seo, Jacob Turner, Harshal Raut

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The perpetual advancement in computational capabilities, coupled with the continuous evolution of software tools and numerical algorithms, is creating novel avenues for research, exploration, and application at the nexus of computational fluid and structural mechanics. Fish leverage their remarkably flexible bodies and fins to harness energy from vortices, propelling themselves with an elegance and efficiency that captivates engineers. Bats fly with unparalleled agility and speed by using their flexible membrane wings. Wave-assisted propulsion (WAP) systems, utilizing elastically mounted hydrofoils, convert wave energy into thrust. Each of these problems involves a complex and elegant interplay between fluid dynamics and structural mechanics. Historically, investigations into such phenomena were constrained by available tools, but modern computational advancements now facilitate exploration of these multi-physics challenges with an unprecedented level of fidelity, precision, and realism. In this work, the author will discuss projects that harness the capabilities of high-fidelity sharp-interface immersed boundary methods to address a spectrum of engineering and biological challenges involving fluid-structure interaction.

Keywords: immersed boundary methods, CFD, bioflight, fluid structure interaction

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Authors: Valeria Corinaldesi, Nicola Generosi, Jacopo Donnini

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Ultra high performance concrete (UHPC) is an innovative material which tends to exhibit superior properties such as incredible mechanical and durability performance and non-brittleness behavior. Over the last twenty years, phenomenal advances have taken place in the research and application of UHPC. Recently, the approach is to improve UHPC sustainability by reducing its embodied energy. First of all, this goal can be achieved by reducing Portland cement dosage. In this work, an experimental investigation was carried out to characterize the mechanical behavior and durability of UHPCs prepared by reducing the cement amount by 30% in order to verify the impact of lower cement content and higher water-to-cement ratio on both mechanical performance and durability, if any. Eight different UHPC mixtures were compared, with two different cement dosages (either 1000 or 700 kg) and four different brass-coated steel fibres dosages (0 - 50 - 100 - 150 kg), in terms of 28-day compressive and flexural strengths. Then, the mixtures prepared with the lower cement content were further investigated in terms of abrasion resistance, water absorption, freezing and thawing cycles, and resistance to sulphate attack. Results obtained showed the feasibility of reducing cement dosage without compromising mechanical performance and UHPC's extraordinary durability.

Keywords: abrasion resistance, durability, eco-efficiency, freeze-thawing cycles, steel fibres, sulphate exposure, sustainability, UHPC

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Lianxue Shi

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Riverfront street has the dual characteristics of street space and waterfront space, which is not only a vital place for residents to travel and communicate but also a high-frequency space for people's leisure and entertainment. However, under the development of cities and towns pursuing efficiency, riverfront streets appear to have a variety of problems, such as a lack of multifunctionality, insufficient facilities, and loss of characteristics, which fail to meet the needs of various groups of people, and their inclusiveness is facing a great challenge. It is, therefore, evident that the optimization of riverfront street space from an inclusivity perspective is important to the establishment of a human-centered, high-quality urban space. Therefore, this article starts by exploring the interactive relationship between inclusive design and street space. Based on the analysis of the characteristics of the riverfront street space and people's needs, it proposes the four inclusive design orientations of natural inclusion, group inclusion, spatial inclusion, and social inclusion. It then constructs a design framework for the inclusive optimization of riverfront street space, aiming to create streets that are “safe and accessible, diverse and shared, distinctive and friendly, green and sustainable”. Riverfront streets in Wansheng District, Chongqing, are selected as a practice case, and specific strategies are put forward in four aspects: the creation of an accessible slow-traffic system, the provision of diversified functional services, the reshaping of emotional bonds and the integration of ecological spaces.

Keywords: inclusiveness design, riverfront street, spatial optimization, street spaces

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Authors: Leonor Varandas, Pedro D. Gaspar, Martim L. Aguiar

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One of the biggest concerns in the field of agriculture is around the energy efficiency of robots that will perform agriculture’s activity and their charging methods. In this paper, two different charging methods for agricultural standalone docking stations are shown that will take into account various variants as field size and its irregularities, work’s nature to which the robot will perform, deadlines that have to be respected, among others. Its features also are dependent on the orchard, season, battery type and its technical specifications and cost. First charging base method focuses on wireless charging, presenting more benefits for small field. The second charging base method relies on battery replacement being more suitable for large fields, thus avoiding the robot stop for recharge. Existing many methods to charge a battery, the CC CV was considered the most appropriate for either simplicity or effectiveness. The choice of the battery for agricultural purposes is if most importance. While the most common battery used is Li-ion battery, this study also discusses the use of graphene-based new type of batteries with 45% over capacity to the Li-ion one. A Battery Management Systems (BMS) is applied for battery balancing. All these approaches combined showed to be a promising method to improve a lot of technical agricultural work, not just in terms of plantation and harvesting but also about every technique to prevent harmful events like plagues and weeds or even to reduce crop time and cost.

Keywords: agricultural mobile robot, charging methods, battery replacement method, wireless charging method

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Authors: Muhammad Anwar, Ameen Ullah, Intakhab Alam Qadri

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This study presents a technique utilizing the Iterative Rational Krylov Algorithm (IRKA) to reduce the order of large-scale descriptor systems. Descriptor systems, which incorporate differential and algebraic components, pose unique challenges in Model Order Reduction (MOR). The proposed method partitions the descriptor system into polynomial and strictly proper parts to minimize approximation errors, applying IRKA exclusively to the strictly adequate component. This approach circumvents the unbounded errors that arise when IRKA is directly applied to the entire system. A comparative analysis demonstrates the high accuracy of the reduced model and a significant reduction in computational burden. The reduced model enables more efficient simulations and streamlined controller designs. The study highlights IRKA-based MOR’s effectiveness in optimizing complex systems’ performance across various engineering applications. The proposed methodology offers a promising solution for reducing the complexity of large-scale descriptor systems while maintaining their essential characteristics and facilitating their analysis, simulation, and control design.

Keywords: model order reduction, descriptor systems, iterative rational Krylov algorithm, interpolatory model reduction, computational efficiency, projection methods, H₂-optimal model reduction

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Authors: Ludmila Polechonska, Agnieszka Klink

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The biogeochemical studies of macrophytes shed light on elements bioavailability, transfer through the food webs and their possible effects on the biota, and provide a basis for their practical application in aquatic monitoring and remediation. Measuring the accumulation of elements in plants can provide time-integrated information about the presence of chemicals in aquatic ecosystems. The aim of the study was to determine and compare the contents of micro- and macroelements in two cosmopolitan macrophytes, submerged Ceratophyllum demersum (hornworth) and free-floating Hydrocharis morsus-ranae (European frog-bit), in order to assess their bioaccumulation potential, elements stock accumulated in each plant and their role in nutrients cycling in small water reservoirs. Sampling sites were designated in 25 oxbow lakes in urban areas in Lower Silesia (SW Poland). In each sampling site, fresh whole plants of C. demersum and H. morsus-ranae were collected from squares of 1x1 meters each where the species coexisted. European frog-bit was separated into leaves, stems and roots. For biomass measurement all plants growing on 1 square meter were collected, dried and weighed. At the same time, water samples were collected from each reservoir and their pH and EC were determined. Water samples were filtered and acidified and plant samples were digested in concentrated nitric acid. Next, the content of Ca, Cu, Fe, K, Mg, Mn, Ni and Zn was determined using atomic absorption method (AAS). Statistical analysis showed that C. demersum and organs of H. morsus-ranae differed significantly in respect of metals content (Kruskal-Wallis Anova, p<0.05). Contents of Cu, Mn, Ni and Zn were higher in hornwort, while European frog-bit contained more Ca, Fe, K, Mg. Bioaccumulation Factors (BCF=content in plant/concentration in water) showed similar pattern of metal bioaccumulation – microelements were more intensively accumulated by hornwort and macroelements by frog-bit. Based on BCF values both species may be positively evaluated as good accumulators of Cu, Fe, Mn, Ni and Zn. However, the distribution of metals in H. morsus-ranae was uneven – the majority of studied elements were retained in roots, which may indicate to existence of physiological barriers developed for dealing with toxicity. Some percent of Ca and K was actively transported to stems, but to leaves Mg only. Although the biomass of C. demersum was two times greater than biomass of H. morsus-ranae, the element off-take was greater only for Cu, Mn, Ni and Zn. Nevertheless, it can be stated that despite a relatively small biomass, compared to other macrophytes, both species may have an influence on the removal of trace elements from aquatic ecosystems and, as they serve as food for some animals, also on the incorporation of toxic elements into food chains. There was a significant positive correlation between content of Mn and Fe in water and roots of H. morus-ranae (R=0.51 and R=0.60, respectively) as well as between Cu concentration in water and in C. demersum (R=0.41) (Spearman rank correlation, p<0.05). High bioaccumulation rates and correlation between plants and water elements concentrations point to their possible use as passive biomonitors of aquatic pollution.

Keywords: aquatic plants, bioaccumulation, biomonitoring, macroelements, phytoremediation, trace metals

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Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Lior Davidovitch

Abstract:

Traditional training based on static models and case studies is the backbone of most teaching and training programs of engineering education. However, project management learning is characterized by dynamics models that requires new and enhanced learning method. The results of empirical experiments evaluating the effectiveness and efficiency of using cognitive simulator as a new training technique are reported. The empirical findings are focused on the impact of keeping and reviewing learning history in a dynamic and interactive simulation environment of engineering education. The cognitive simulator for engineering project management learning had two learning history keeping modes: manual (student-controlled), automatic (simulator-controlled) and a version with no history keeping. A group of industrial engineering students performed four simulation-runs divided into three identical simple scenarios and one complicated scenario. The performances of participants running the simulation with the manual history mode were significantly better than users running the simulation with the automatic history mode. Moreover, the effects of using the undo enhanced further the learning process. The findings indicate an enhancement of engineering students’ learning and decision making when they use the record functionality of the history during their engineering training process. Furthermore, the cognitive simulator as educational innovation improves students learning and training. The practical implications of using simulators in the field of engineering education are discussed.

Keywords: cognitive simulator, decision making, engineering learning, project management

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Authors: Patricia N. Baguio, Angel Amy M. Bunag, Paul Bryan E. Ornopia, John Paul C. Suel

Abstract:

This research investigates the viability and efficiency of employing ceramic tile additives derived from horn snail shell material, specifically calcium carbonate (CaCO₃). The study aims to evaluate the mechanical properties of ceramic tiles with Calcium Carbonate with varying amounts of CaCO₃, focusing on breaking and flexural strength. The research employs a comprehensive methodology, including material collection, slurry forming, shaping, drying, firing, and statistical analysis using paired sample T-tests. The result indicates a positive correlation between calcium carbonate (CaCO₃) application and ceramic tile strength, revealing increased breaking strength from 29.41 N (non-calcium Carbonate) to 46.02 N (70g CaCO3) and a substantial enhancement to 82.61 N with 150g CaCO₃. Comparative analyses show higher breaking and flexural strength in tiles with Calcium Carbonate with 150g CaCO₃ analysis (p = 0.011), indicating its feasibility for ceramic tile manufacturing, while 70g CaCO₃ shows no significant difference from non-calcium Carbonate tiles (p = 0.135). The addition of horn snail shells shows potential for improving ceramic tile quality and contributes positively to waste management in standard tile production processes.

Keywords: Horn snail shell, calcium carbonate, breaking strength, flexural strength

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Authors: Patricia N. Baguio, Angel Amy M. Buñag, Paul Bryan E. Ornopia, John Paul C. Suel

Abstract:

This research investigates the viability and efficiency of employing ceramic tile additives derived from horn snail shell material, specifically calcium carbonate (CaCO₃). The study aims to evaluate the mechanical properties of ceramic tiles with calcium carbonate with varying amounts of CaCO₃, focusing on breaking and flexural strength. The research employs a comprehensive methodology, including material collection, slurry forming, shaping, drying, firing, and statistical analysis using paired sample T-tests. The result indicates a positive correlation between calcium carbonate (CaCO₃) application and ceramic tile strength, revealing increased breaking strength from 29.41 N (non-calcium carbonate) to 46.02 N (70g CaCO₃) and a substantial enhancement to 82.61 N with 150g CaCO₃. Comparative analyses show higher breaking and flexural strength in tiles calcium carbonate with 150g CaCO₃ analysis (p = 0.011), indicating its feasibility for ceramic tile manufacturing, while 70g CaCO₃ shows no significant difference from non-calcium carbonate tiles (p = 0.135). The addition of horn snail shells shows potential for improving ceramic tile quality and contributes positively to waste management in standard tile production processes.

Keywords: horn snail shell, calcium carbonate, breaking strength, flexural strength

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Authors: PR

Abstract:

Renewable energy is a sustainable substitute to fossil fuels, which are depleting and attributing to global warming as well as greenhouse gas emissions. Renewable energy innovations including solar, wind, and geothermal have grown significantly and play a critical role in meeting energy demands recently. Consequently, Artificial Intelligence (AI) could further enhance the benefits of renewable energy systems. The combination of renewable technologies and AI could facilitate the development of smart grids that can better manage energy distribution and storage. AI thus has the potential to optimize the efficiency and reliability of renewable energy systems, reduce costs, and improve their overall performance. The conventional methods of using smart micro-grids are to connect these micro-grids in series or parallel or a combination of series and parallel. Each of these methods has its advantages and disadvantages. In this study, the proposal of using the method of connecting microgrids in a spiral manner is investigated. One of the important reasons for choosing this type of structure is the two-way reinforcement and exchange of each inner layer with the outer and upstream layer. With this model, we have the ability to increase energy from a small amount to a significant amount based on exponential functions. The geometry used to close the smart microgrids is based on nature.This study provides an overview of the applications of algorithms and models of AI as well as its advantages and challenges in renewable energy systems.

Keywords: artificial intelligence, renewable energy sources, spiral model, optimize

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Authors: Shidrokh Goudarzi, Wan Haslina Hassan

Abstract:

Heterogeneous wireless networks are converging towards an all-IP network as part of the so-called next-generation network. In this paradigm, different access technologies need to be interconnected; thus, vertical handovers or vertical handoffs are necessary for seamless mobility. In this paper, we conduct a review of existing vertical handover decision-making mechanisms that aim to provide ubiquitous connectivity to mobile users. To offer a systematic comparison, we categorize these vertical handover measurement and decision structures based on their respective methodology and parameters. Subsequently, we analyze several vertical handover approaches in the literature and compare them according to their advantages and weaknesses. The paper compares the algorithms based on the network selection methods, complexity of the technologies used and efficiency in order to introduce our vertical handover decision framework. We find that vertical handovers on heterogeneous wireless networks suffer from the lack of a standard and efficient method to satisfy both user and network quality of service requirements at different levels including architectural, decision-making and protocols. Also, the consolidation of network terminal, cross-layer information, multi packet casting and intelligent network selection algorithm appears to be an optimum solution for achieving seamless service continuity in order to facilitate seamless connectivity.

Keywords: heterogeneous wireless networks, vertical handovers, vertical handover metric, decision-making algorithms

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Authors: Jo Anne Rey

Abstract:

Caring for Country (Ngurrain Dharug language) is core to Aboriginal identity, Law/Lore, practice, and resilience within the continent called ‘Australia’. It is the basis of thousands of years of sustainability. However, when Ngurra is a city known as Sydney, due to 235 years of colonial impact, caring for the Country is limited, being controlled by the State and private ownership of the land title. Recent research indicates that localised Indigenous activism is most successful when community members are geographically proximate to the presences and places of connection, caring, and belonging. This article frames these findings through the cadence that proximity provides. This presentation is centred on the proximate agency that is being exercised by Dharug community through three significant sites within the Sydney basin. Those sites include, firstly, Shaw’s Creek Aboriginal Place, at the foot of the Blue Mountains in far western Sydney. Second inclusion is the site of Blacktown Native Institution, that was the part of the authoritarian colonial governance of British Governor Lachlan Macquarie (after who Macquarie University is named), which saw the beginnings of the removal of children from their families and culture to ‘civilize’ them. The third site is that of the so-called Brown’s Waterhole in the State government administered Lane Cove National Park. Each of these sites is being activated through Dharug and, more broadly, Aboriginalways of knowing, doing, and being. These ways involvethe land, water, wind, and star-based ecologies interwoven with traditional transgenerational storying of the presences (Ancestral and spiritual) creating them. Activations include, but are not limited to, the return of cultural fire for reviving plants, soils, animals, and birds. These fire practices have traditionally been at the basis of sustainable, regenerative biodiversity. These practices involve the literacy of reading Ngurra and the seasonal interactions across the ecologies. Together, they both care for the Country and support humanity, and have done so across thousands of years. However, when the cost of real-estate and rental accommodation prevents community members from being able to live on Dharug Ngurra when bureaucratic governance restricts and/or excludes traditional custodial relationships, and when private treaty land title destroys the presences and places while disconnecting people from their Ancestral practices, it becomes clear that caring for Country is only possible when the community can afford to live nearby. Recognising the cadence of proximityas the agency that underpinscaring for Country-in-the-city, sustainable change opportunities don’t have to only focus on regional and remote areas. Urban-based Aboriginal relationality offers an alternative to the unsustainable practices that underpin human-centric disconnection. Weaving Indigenous cadence offers opportunities for sustainable futures even when facing the extremes of climate changing catastrophes.

Keywords: australian aboriginal, biocultural knowledges, climate change, dharug ngurra, sustainability, resilience

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Authors: Tzu-Wen Liu, Yi-Feng Lin, Yu-Shao Chen

Abstract:

CO_2 is believed to be partly responsible for changes to the global climates. Carbon capture and storage (CCS) is one way to reduce carbon dioxide emissions in the past. Recently, how to convert the captured CO_2 into fine chemicals gets lots of attention owing to reducing carbon dioxide emissions and providing greener feedstock for the chemicals industry. A variety of products can be manufactured from carbon dioxide and the most attractive products are cyclic carbonates. Therefore, the kind of catalyst plays an important role in cycloaddition of carbon dioxide to epoxides. Magnesium oxide can be an efficiency heterogeneous catalyst for the cycloaddition of carbon dioxide to epoxides because magnesium oxide has both acid and base active sites and can provide the adsorption of carbon dioxide, promoting ring-opening reaction. Spinning disk reactor (SDR) is one of the device of high-gravity technique and has successfully used for synthesis of nanoparticles by precipitation methods because of the high mass transfer rate. Synthesis of nanoparticles in SDR has advantages of low energy consumption and easy to scale up. The aim of this research is to synthesize magnesium hydroxide nanoparticles in SDR as precursors for magnesium oxide. Experimental results showed that the calcination temperature of magnesium hydroxide to magnesium oxide, and the pressure and temperature of cycloaddition reaction had significantly effect on the conversion and selectivity of the reaction.

Keywords: magnesium oxide, catalyst, cycloaddition, spinning disk reactor, carbon dioxide

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