Search results for: drying techniques

Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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Authors: Partha Saha, Uttam Kumar Banerjee

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Maternal and Child Healthcare (MCH) has always been regarded as one of the important issues globally. Reduction of maternal and child mortality rates and increase of healthcare service coverage were declared as one of the targets in Millennium Development Goals till 2015 and thereafter as an important component of the Sustainable Development Goals. Over the last decade, worldwide MCH indicators have improved but could not match the expected levels. Progress of both maternal and child mortality rates have been monitored by several researchers. Each of the studies has stated that only less than 26% of low-income and middle income countries (LMICs) were on track to achieve targets as prescribed by MDG4. Average worldwide annual rate of reduction of under-five mortality rate and maternal mortality rate were 2.2% and 1.9% as on 2011 respectively whereas rates should be minimum 4.4% and 5.5% annually to achieve targets. In spite of having proven healthcare interventions for both mothers and children, those could not be scaled up to the required volume due to fragmented health systems, especially in the developing and under-developed countries. In this research, a knowledge discovery based interactive Decision Support System (DSS) has been developed on web platform which would assist healthcare policy makers to develop evidence-based policies. To achieve desirable results in MCH, efficient resource planning is very much required. In maximum LMICs, resources are big constraint. Knowledge, generated through this system, would help healthcare managers to develop strategic resource planning for combatting with issues like huge inequity and less coverage in MCH. This system would help healthcare managers to accomplish following four tasks. Those are a) comprehending region wise conditions of variables related with MCH, b) identifying relationships within variables, c) segmenting regions based on variables status, and d) finding out segment wise key influential variables which have major impact on healthcare indicators. Whole system development process has been divided into three phases. Those were i) identifying contemporary issues related with MCH services and policy making; ii) development of the system; and iii) verification and validation of the system. More than 90 variables under three categories, such as a) educational, social, and economic parameters; b) MCH interventions; and c) health system building blocks have been included into this web-based DSS and five separate modules have been developed under the system. First module has been designed for analysing current healthcare scenario. Second module would help healthcare managers to understand correlations among variables. Third module would reveal frequently-occurring incidents along with different MCH interventions. Fourth module would segment regions based on previously mentioned three categories and in fifth module, segment-wise key influential interventions will be identified. India has been considered as case study area in this research. Data of 601 districts of India has been used for inspecting effectiveness of those developed modules. This system has been developed by importing different statistical and data mining techniques on Web platform. Policy makers would be able to generate different scenarios from the system before drawing any inference, aided by its interactive capability.

Keywords: maternal and child heathcare, decision support systems, data mining techniques, low and middle income countries

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Authors: S. Thomet, S. De-Paoli, F. Ghaffari, J. M. Daveau, P. Roche, O. Romain

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In this paper, we present a hardware module dedicated to understanding the fail reason of a System on Chip (SoC) exposed to a particle beam. Impact of Single-Event Effects (SEE) on processor-based SoCs is a concern that has increased in the past decade, particularly for terrestrial applications with automotive safety increasing requirements, as well as consumer and industrial domains. The SEE created by the impact of a particle on an SoC may have consequences that can end to instability or crashes. Specific hardening techniques for hardware and software have been developed to make such systems more reliable. SoC is then qualified using cosmic ray Accelerated Soft-Error Rate (ASER) to ensure the Soft-Error Rate (SER) remains in mission profiles. Understanding where errors are occurring is another challenge because of the complexity of operations performed in an SoC. Common techniques to monitor an SoC running under a beam are based on non-intrusive debug, consisting of recording the program counter and doing some consistency checking on the fly. To detect and understand SEE, we have developed a module embedded within the SoC that provide support for recording probes, hardware watchpoints, and a memory mapped register bank dedicated to software usage. To identify CPU failure modes and the most important resources to probe, we have carried out a fault injection campaign on the RTL model of the SoC. Probes are placed on generic CPU registers and bus accesses. They highlight the propagation of errors and allow identifying the failure modes. Typical resulting errors are bit-flips in resources creating bad addresses, illegal instructions, longer than expected loops, or incorrect bus accesses. Although our module is processor agnostic, it has been interfaced to a RISC-V by probing some of the processor registers. Probes are then recorded in a ring buffer. Associated hardware watchpoints are allowing to do some control, such as start or stop event recording or halt the processor. Finally, the module is also providing a bank of registers where the firmware running on the SoC can log information. Typical usage is for operating system context switch recording. The module is connected to a dedicated debug bus and is interfaced to a remote controller via a debugger link. Thus, a remote controller can interact with the monitoring module without any intrusiveness on the SoC. Moreover, in case of CPU unresponsiveness, or system-bus stall, the recorded information can still be recovered, providing the fail reason. A preliminary version of the module has been integrated into a test chip currently being manufactured at ST in 28-nm FDSOI technology. The module has been triplicated to provide reliable information on the SoC behavior. As the primary application domain is automotive and safety, the efficiency of the module will be evaluated by exposing the test chip under a fast-neutron beam by the end of the year. In the meantime, it will be tested with alpha particles and electromagnetic fault injection (EMFI). We will report in the paper on fault-injection results as well as irradiation results.

Keywords: fault injection, SoC fail reason, SoC soft error rate, terrestrial application

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Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

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The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: Naman Jain, Shaun Fernandes

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With the increasing prevalence of online healthcare services, selecting the most suitable doctor has become a complex task, requiring careful consideration of both public sentiment and personal preferences. This paper proposes a sentiment analysis-driven method that integrates public reviews with user-specific criteria and correlated attributes to recommend online doctors. By leveraging Natural Language Processing (NLP) techniques, public sentiment is extracted from online reviews, which is then combined with user-defined preferences such as specialty, years of experience, location, and consultation fees. Additionally, correlated attributes like education and certifications are incorporated to enhance the recommendation accuracy. Experimental results demonstrate that the proposed system significantly improves user satisfaction by providing personalized doctor recommendations that align with both public opinion and individual needs.

Keywords: sentiment analysis, online doctors, personal preferences, correlated attributes, recommendation system, healthcare, natural language processing

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Authors: Naima Boudieb, Mohamed Loucif Seaid, Imad Rati, Imane Benammane

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The aim of this study is to synthesis of a copolymer PANI/PEDOT:PSS by electrochemical means to apply in supercapacitors. Polyaniline (PANI) is a conductive polymer; it was synthesized by electrochemical polymerization. It exhibits very stable properties in different environments, whereas PEDOT:PSS is a conductive polymer based on poly(3,4-ethylenedioxythiophene) (PEDOT) and poly(styrene sulfonate)(PSS). It is commonly used with polyaniline to improve its electrical conductivity. Several physicochemical and electrochemical techniques were used for the characterization of PANI/PEDOT:PSS: cyclic voltammetry (VC), electrochemical impedance spectroscopy (EIS), open circuit potential, SEM, X-ray diffraction, etc. The results showed that the PANI/PEDOT:PSS composite is a promising material for supercapacitors due to its high electrical conductivity and high porosity. Electrochemical and physicochemical characterization tests have shown that the composite has high electrical and structural performances, making it a material of choice for high-performance energy storage applications.

Keywords: energy storage, supercapacitors, SIE, VC, PANI, poly(3, 4-ethylenedioxythiophene, PEDOT, polystyrene sulfonate

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: Jamal Ahmed Hama Kareem, Noraini Abu Talib

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The purpose of this paper is to explore the literature on 5S and Total Productive Maintenance (TPM) and the benefits that are to be derived from their implementation. It also seeks to highlight the main phases for implementing both the 5S and the TPM successfully, along with highlighting aspects that are needed for successful implementation of these two techniques simultaneously in the contemporary manufacturing scenario. The literature on classification of 5S and TPM has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of several of implementation practices of 5S and TPM, and the benefits that can be achieved by the implementation of 5S and TPM as a one system by industrial organizations globally. The paper systematically categorizes the published literature and reveals important issues that influence the successful implementation of 5S and TPM in organizations to improve production effectiveness for competitiveness. Further, the paper also highlights various phases suggested by researchers and practitioners, which ensure smooth and effective implementation of the 5S and TPM in industrial organizations. In the end, study puts forth propositions based on the model of the study after extensive review of literature. The paper will be useful to researchers, maintenance professionals and other concerned officials with improving the performance of production processes effectiveness in industrial organizations.

Keywords: 5S, Total Productive Maintenance (TPM), phases of implementation of 5S and TPM, industrial organizations

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Authors: Merey M. Sarsengeldin, Alexandr S. Kolokhmatov, Galiya Seidaliyeva, Alexandr Ozerov, Sanim T. Imatayeva

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This series of interdisciplinary studies is an attempt to investigate and develop a scalable model of fair socioeconomic relations on the base of blockchain using positive psychology techniques and Machine Learning algorithms for data analytics. In this particular study, we use hyperinteraction approach and intuition to investigate their influence on 'wisdom of crowds' via created mobile application which was created for the purpose of this research. Along with the public blockchain and private Decentralized Autonomous Organization (DAO) which were elaborated by us on the base of Ethereum blockchain, a model of fair financial relations of members of DAO was developed. We developed a smart contract, so-called, Fair Price Protocol and use it for implementation of model. The data obtained from mobile application was analyzed by ML algorithms. A model was tested on football matches.

Keywords: blockchain, Naïve Bayes algorithm, hyperinteraction, intuition, wisdom of crowd, decentralized autonomous organization

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Authors: Mohammad Al-Refai, Majed Wakid

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Introduction: Soil-transmitted diseases (STD) are caused by intestinal worms that are transmitted via various routes into the human body resulting in various clinical manifestations. The intestinal worms causing these infections are known as soil transmitted helminths (STH), including Hook worms, Ascaris lumbricoides (A. lumbricoides), Trichuris trichiura (T. trichiura), and Strongyloides sterocoralis (S. sterocoralis). Objectives: The aim of this study was to investigate the prevalence of STH among newly arrived expatriate labors in Jeddah city, Saudi Arabia, using three different techniques (direct smears, sedimentation concentration, and real-time PCR). Methods: A total of 188 stool specimens were collected and investigated at the parasitology laboratory in the Special Infectious Agents Unit at King Fahd Medical Research Center, King Abdulaziz University in Jeddah, Saudi Arabia. Microscopic examination of wet mount preparations using normal saline and Lugols Iodine was carried out, followed by the formal ether sedimentation method. In addition, real-time PCR was used as a molecular tool to detect several STH and hookworm speciation. Results: Out of 188 stool specimens analyzed, in addition to STH parasite, several other types were detected. 9 samples (4.79%) were positive for Entamoeba coli, 7 samples (3.72%) for T. trichiura, 6 samples (3.19%) for Necator americanus, 4 samples (2.13%) for S. sterocoralis, 4 samples (2.13%) for A. lumbricoides, 4 samples (2.13%) for E. histolytica, 3 samples (1.60%) for Blastocystis hominis, 2 samples (1.06%) for Ancylostoma duodenale, 2 samples (1.06%) for Giardia lamblia, 1 sample (0.53%) for Iodamoeba buetschlii, 1 sample (0.53%) for Hymenolepis nana, 1 sample (0.53%) for Endolimax nana, and 1 sample (0.53%) for Heterophyes heterophyes. Out of the 35 infected cases, 26 revealed single infection, 8 with double infections, and only one triple infection of different STH species and other intestinal parasites. Higher rates of STH infections were detected among housemaids (11 cases) followed by drivers (7 cases) when compared to other occupations. According to educational level, illiterate participants represent the majority of infected workers (12 cases). The majority of workers' positive cases were from the Philippines. In comparison between laboratory techniques, out of the 188 samples screened for STH, real-time PCR was able to detect the DNA in (19/188) samples followed by Ritchie sedimentation technique (18/188), and direct wet smear (7/188). Conclusion: STH infections are a major public health issue to healthcare systems around the world. Communities must be educated on hygiene practices and the severity of such parasites to human health. As far as drivers and housemaids come to close contact with families, including children and elderlies. This may put family members at risk of developing serious side effects related to STH, especially as the majority of workers were illiterate, lacking the basic hygiene knowledge and practices. We recommend the official authority in Jeddah and around the kingdom of Saudi Arabia to revise the standard screening tests for newly arrived workers and enforce regular follow-up inspections to minimize the chances of the spread of STH from expatriate workers to the public.

Keywords: expatriate labors, Jeddah, prevalence, soil transmitted helminths

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Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

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The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate

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Authors: Dana Madalina Pohrib, Elena Irina Ciobanu

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In compaction works, the most often used codes and standards are those for road embankments and refer to a maximum filling height of 3.00m. When filling a height greater than 3.00m, such codes are no longer valid and thus their application may lead to technical difficulties in the process of compaction and to the achievement of a sufficient degree of compaction. For this reason, in the case of controlled fillings with heights greater than 3.00m it is necessary to formulate and apply a number of special techniques, which can be determined by performing a full scale test. This paper presents the results of the studies and full scale tests conducted for the stabilization of a ravine with vertical banks and a depth of about 12.00m. The fillings will support a heavy traffic road connecting the two parts of a village in Vaslui County, Romania. After analyzing two comparative intervention solutions, the variant of a controlled filling bordered by a monolith concrete retaining wall was chosen. The results obtained by the authors highlighted the need to insert a geogrid reinforcement at every 2.00m for creating a 12.00m thick compacted fill.

Keywords: compaction, dynamic probing, stability, soil stratification

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Authors: Eny Syatriana

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The purpose of this study is to find out the effective instruction for classroom management, with the main identification of organizing and managing effective learning environments, to identify characteristics of effective lesson planning, identify resources and materials dealing with positive and effective classroom management. Knowing the effective instruction management is one of the characteristics of well managed teacher. The study was carried out in three randomly selected classes of STKIP YPUP in South Sulawesi. The design adopted for the study was a descriptive survey approach. Simple descriptive analysis was used. The major instrument used in this study were student questionnaire, teacher questionnaire, data were gathered with the research instrument and were analyzed, the research question were investigated and two hypothesis were duly tested using t-test statistics. Based on the findings of this research, it was concluded that effective classroom management skills or techniques have strong and positive influence on student achievement.

Keywords: effective classroom management skills, students’ achievement, students academic, effective learning environments

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Authors: Qasim Zafar, Matthew Anderson, Esteban Garcia, Steven Drager

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Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices.

Keywords: software testing, software metrics, testing effectiveness, black box testing, random testing, adaptive random testing, combinatorial testing, fuzz testing, equivalence partition, boundary value analysis, white box testing

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Authors: M. A. Medeiros, A. A. N. Dantas, F. A. N. França, R. F. Amaral

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There are several alternatives of coastal erosion control with geosynthetics. As an important stage of any Civil Engineering project, literature review is necessary in order to evaluate these alternatives and to guide the decisions. Ponta Negra beachfront has a very intensive urban pressure. In addition, a very short sand area induces high intensity erosion processes. Different attempts of solving the problem were already built. However, erosion issues are still an important concern since these structures collapsed. Geosynthetics present a great potential to be applied in this area. In order to study coastal erosion control alternatives with the use of geosynthetics, this paper presents a literature review about this subject. Several studies were collected in which beach conditions are similar to those found in Ponta Negra beach. It was possible to evaluate the alternatives that might be used in the area. Further studies include the application of such techniques in pilot areas and the evaluation of the erosion process. Finally, the best alternative for futures studies on Ponta Negra beach is geocontainers of geotextiles.

Keywords: geosynthetics, coastal erosion control, alternatives, Ponta Negra beach

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Authors: Vitali Kremez

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The researcher monitored an organized ransomware campaign in order to gain significant visibility into the tactics, techniques, and procedures employed by a campaign boss operating a ransomware scheme out of Russia. As the Russian hacking community lowered the access requirements for unsophisticated Russian cybercriminals to engage in ransomware campaigns, corporations and individuals face a commensurately greater challenge of effectively protecting their data and operations from being held ransom. This report discusses two notorious ransomware campaigns. Though the loss of data can be devastating, the findings demonstrate that sending ransom payments does not always help obtain data. Key learnings: 1. From the ransomware affiliate perspective, such campaigns have significantly lowered the barriers for entry for low-tier cybercriminals. 2. Ransomware revenue amounts are not as glamorous and fruitful as they are often publicly reported. Average ransomware crime bosses make only $90K per year on average. 3. Data gathered indicates that sending ransom payments does not always help obtain data. 4. The talk provides the complete payout structure and Bitcoin laundering operation related to the ransomware-as-a-service campaign.

Keywords: bitcoin, cybercrime, ransomware, Russia

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Authors: Priya Arora, Jaspreet K. Rajput

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Superparamagnetism has accelerated the research and use of more economical and ecological magnetically separable catalysts due to their more efficient isolation by response to an applied magnetic field. Magnetite nanomaterials coated by SiO2 shell have received a great deal of focus in the last decades as it provides high stability and also easy further surface functionalization depending upon the application. In this protocol, Fe3O4 magnetic nanoparticles have been synthesized by co-precipitation combined with sonication method. Further, Fe3O4 superparamagnetic nanoparticles have been functionalized by various moieties to serve as efficient catalysts for multicomponent reactions. The functionalized nanoparticles were characterized by techniques like Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) surface area analysis. The as prepared nanocatalysts can be reused for several times without any significant loss in its activity. The utilization of magnetic nanoparticles as catalysts for this reaction is one approach i.e. green, inexpensive, facile and widely applicable.

Keywords: functionalized, magnetite, multicomponent reactions, superparamagnetic

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Authors: Irfan Nazir Wani, Pushpendra Kumar Shukla, Manoj Kumar

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Debris, also called waste or junk, present in orbit of Earth or orbital debris, offers a substantial challenge to space exploration. Satellite operations and other space-based activities. This research paper delves into the causes and effects of space debris accumulation, explores current mitigation techniques, and presents a hopeful outlook on the potential for future sustainable space activities. The paper emphasizes the necessity of addressing planetary fragments to ensure durable sustainability in universe exploration and utilization. It examines various strategies for mitigating space debris, including debris removal technologies, spacecraft design improvements, and international collaboration efforts. Additionally, the paper highlights the importance of space debris monitoring and tracking systems in preventing collisions and minimizing the growth of orbital debris. By comprehending the complexities of space debris and implementing effective mitigation measures, the space industry can work towards a future where sustainable space activities are achievable.

Keywords: space shuttle, debris, space junk, satellite, fragments, orbit

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Authors: M. Saadi, S. E. H. Abaidia, M. Y. Mokeddem.

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We present the results of a systematic and comparative study of the bulk, the structural properties, and phonon calculations of aluminum alloys using several exchange–correlations functional theory (DFT) with different plane-wave basis pseudo potential techniques. Density functional theory implemented by the Vienna Ab Initio Simulation Package (VASP) technique is applied to calculate the bulk and the structural properties of several structures. The calculations were performed for within several exchange–correlation functional and pseudo pententials available in this code (local density approximation (LDA), generalized gradient approximation (GGA), projector augmented wave (PAW)). The lattice dynamic code “PHON” developed by Dario Alfè was used to calculate some thermodynamics properties and phonon dispersion relation frequency distribution of Aluminium alloys using the VASP LDA PAW and GGA PAW results. The bulk and structural properties of the calculated structures were compared to different experimental and calculated works.

Keywords: DFT, exchange-correlation functional, LDA, GGA, pseudopotential, PAW, VASP, PHON, phonon dispersion

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Montserrrat Dopico Gonzalez, Ramon Lopez Facal

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The development of a critical, open and plural citizenship constitutes one of the main challenges of the school institution in the present multicultural societies. Didactics in Social Sciences has conducted important contributions to the development of active methodologies to promote the development of the intercultural competencies of the student body. Research in intercultural education has demonstrated the efficiency of the cooperative learning techniques to improve the intercultural relations in the classroom. Our study proposes to check the effect that, concerning the development of intercultural competencies of the student body, the emotional education can have in the context of the use of active methodologies such as the learning by projects and the cooperative learning. To that purpose, a programme of intervention based on activities focussed on controversial issues related to cultural diversity has been implemented in several secondary schools. Through a methodology which combines intercultural competence scales with interviews and also with the analysis of the school body’s productions, the persistence of stereotypes against immigration and the efficacy of the introduction of emotional education elements in the development of intercultural competencies have both been observed.

Keywords: active methodologies, didactics in social sciences, intercultural competences, intercultural education

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Widi Astuti

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In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The bauxite residue sample came from the Tayan mine, Indonesia, which contains high hematite (Fe₂O₃). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30 - 110 °C. Variations of current density, red mud: NaOH ratio and temperature were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 20% recovery at a current density of 920,945 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: red mud, electrochemical reduction, Iron production, hematite

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Mahdi Mottahedi, Peter Zahn, Armin Lechler, Alexander Verl

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Optimal topology of components leads to the maximum stiffness with the minimum material use. For the generation of these topologies, normally algorithms are employed, which tackle manufacturing limitations, at the cost of the optimal result. The global optimum result with penalty factor one, however, cannot be fabricated with conventional methods. In this article, an additive manufacturing method is introduced, in order to enable the production of global topology optimization results. For a benchmark, topology optimization with higher and lower penalty factors are performed. Different algorithms are employed in order to interpret the results of topology optimization with lower factors in many microstructure layers. These layers are then joined to form the final geometry. The algorithms’ benefits are then compared experimentally and numerically for the best interpretation. The findings demonstrate that by implementation of the selected algorithm, the stiffness of the components produced with this method is higher than what could have been produced by conventional techniques.

Keywords: topology optimization, additive manufacturing, 3D-printer, laminated object manufacturing

Procedia PDF Downloads 339

Authors: Saurabh Parkhedkar, Rajanikant Tenguria

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The paper proposes revamping the public transportation system in Mumbai with the use of Radio Frequency Identification (RFID) technology in order to provide better integration and compatibility across various modes of transport. In Mumbai, mass transport system suffers from poor inter-compatible ticketing system, subpar money collection techniques, and lack of planning for optimum utilization of resources. Development of suburbs and growth in population will result in growing demand for mass transportation networks. Hence, the growing demand for the already overburdened public transportation system is only going to worsen the scenario. Thus, a superior system is essential in order to regulate, manage and supervise future transportation needs. The proposed RFID based system integrates Mumbai Suburban Railway, BEST (Brihanmumbai Electric Supply and Transport Undertaking transport wing) Bus, Mumbai Monorail and Mumbai Metro systems into a Unified Public Transportation System (UPTS). The UTPS takes into account various drawbacks of the present day system and offers solution, suitable for the modern age Mumbai.

Keywords: urbanization, transportation, RFID, Mumbai, public transportation, smart city.

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Authors: M. R. Abusrea, Shiyi Jiang, Dingding Chen, Kazuo Arakawa

Abstract:

Novel wind-lens turbine designs can augment power output. Vacuum-Assisted Resin Transfer Molding (VARTM) is used to form large and complex structures from a Carbon Fiber Reinforced Polymer (CFRP) composite. Typically, wind-lens turbine structures are fabricated in segments, and then bonded to form the final structure. This paper introduces five new adhesive joints, divided into two groups: One is constructed between dry carbon and CFRP fabrics, and the other is constructed with two dry carbon fibers. All joints and CFRP fabrics were made in our laboratory using VARTM manufacturing techniques. Specimens were prepared for tensile testing to measure joint performance. The results showed that the second group of joints achieved a higher tensile strength than the first group. On the other hand, the tensile fracture behavior of the two groups showed the same pattern of crack originating near the joint ends followed by crack propagation until fracture.

Keywords: adhesive joints, CFRP, VARTM, resin transfer molding

Procedia PDF Downloads 436

Authors: Hanan Rizk

Abstract:

A heat exchanger is a device used to mix liquids having different temperatures. In this case, the temperature control becomes a critical objective. This research work presents the temperature control of the double-pipe heat exchanger (multi-input multi-output (MIMO) system), which is modeled as first-order coupled hyperbolic partial differential equations (PDEs), using conventional and advanced control techniques and develops appropriate robust control strategy to meet stability requirements and performance objectives. We designed a PID controller and H-infinity controller for a heat exchanger (HE) system. Frequency characteristics of sensitivity functions and open-loop and closed-loop time responses are simulated using MATLAB software, and the stability of the system is analyzed using Kalman's test. The simulation results have demonstrated that the H-infinity controller is more efficient than PID in terms of robustness and performance.

Keywords: heat exchanger, multi-input multi-output system, MATLAB simulation, partial differential equations, PID controller, robust control

Procedia PDF Downloads 220