Search results for: enhanced data encryption

Authors: Sayor Ajfar Aaron, Ashif Newaz, Sajjat Hossain Abir, Mushfiqur Rahman

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This paper examines the transformative potential of quantum computing in the field of cybersecurity, with a focus on advanced penetration testing and forensics. It explores how quantum technologies can be leveraged to identify and exploit vulnerabilities more efficiently than traditional methods and how they can enhance the forensic analysis of cyber-attacks. Through theoretical analysis and practical simulations, this study highlights the enhanced capabilities of quantum algorithms in detecting and responding to sophisticated cyber threats, providing a pathway for developing more resilient cybersecurity infrastructures.

Keywords: cybersecurity, cyber forensics, penetration testing, quantum computing

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: A. Sathiya Susuman, Hamisi F. Hamisi

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Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: André Lages, Victor Dmitriev, Juliano Bazzo, Gianni Portela

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This work evaluates the feasibility of the graphene application to perform as a wideband reconfigurable material for lens antennas in 5G/6G and satellite applications. Based on transformation optics principles, the electromagnetic waves can be efficiently guided by modifying the effective refractive index. Graphene behavior can range between a lossy dielectric and a good conductor due to the variation of its chemical potential bias, thus arising as a promising solution for electromagnetic devices. The graphene properties and a lens antenna comprising multiples layers and periodic arrangements of graphene patches were analyzed using full-wave simulations. A dipole directivity was improved from 7 to 18.5 dBi at 29 GHz. In addition, the realized gain was enhanced 7 dB across a 14 GHz bandwidth within the Ka/5G band.

Keywords: 5G/6G, graphene, lens, reconfigurable, satellite

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Authors: Donghyun Lee, Cam Nguyen

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Multi-band systems offer a great deal of benefit in modern communication and radar systems. In particular, multi-band antenna-array radar systems with their extended frequency diversity provide numerous advantages in detection, identification, locating and tracking a wide range of targets, including enhanced detection coverage, accurate target location, reduced survey time and cost, increased resolution, improved reliability and target information. An accurate calibration is a critical issue in antenna array systems. The amplitude and phase errors in multi-band and multi-polarization antenna array transceivers result in inaccurate target detection, deteriorated resolution and reduced reliability. Furthermore, the digital beam former without the RF domain phase-shifting is less immune to unfiltered interference signals, which can lead to receiver saturation in array systems. Therefore, implementing integrated front-end architecture, which can support calibration function with low insertion and filtering function from the farthest end of an array transceiver is of great interest. We report a dual K/Ka-band T/R/Calibration switch module with quasi-elliptic dual-bandpass filtering function implementing a Q-enhanced metamaterial transmission line. A unique dual-band frequency response is incorporated in the reception and calibration path of the proposed switch module utilizing the composite right/left-handed meta material transmission line coupled with a Colpitts-style negative generation circuit. The fabricated fully integrated T/R/Calibration switch module in 0.18-μm BiCMOS technology exhibits insertion loss of 4.9-12.3 dB and isolation of more than 45 dB in the reception, transmission and calibration mode of operation. In the reception and calibration mode, the dual-band frequency response centered at 24.5 and 35 GHz exhibits out-of-band rejection of more than 30 dB compared to the pass bands below 10.5 GHz and above 59.5 GHz. The rejection between the pass bands reaches more than 50 dB. In all modes of operation, the IP1-dB is between 4 and 11 dBm. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: microwaves, millimeter waves, T/R switch, wireless communications, wireless communications

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Authors: Samera Salimpour Abkenar

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In this work, silk yarns were treated using ß-cyclodextrin (ß-CD) and cross-linked with citric acid (CA) via pad-dry-cure method. Elemental and FESEM analyses confirmed the presence of ß-CD on the treated silk samples even after five washing cycles. Then, the treated samples were dyed using natural dyes (carrot, orange and tomato). Results showed that the color strength (K/S) of the treated samples had been markedly enhanced compared with the control sample (after treatment with metal mordant). Finally, the color strength (K/S value) and color fastness (fading, staining and light fastness) of the treated samples with ß-CD were investigated and compared.

Keywords: ß-cyclodextrin, dyeing, natural dyes, silk yarn

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Authors: Tassia Batista Pessato, Francielli Pires Ribeiro Morais, Fernanda Guimaraes Drummond Silva, Flavia Maria Netto

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Proteins and phenolic compounds can interact mainly by hydrophobic interactions. Those interactions may lead to structural changes in both molecules, which in turn could affect positively or negatively their functional and nutritional properties. Here, the structural changes of whey proteins (WPI) due to interaction with caffeic acid (CA) were investigated by intrinsic and extrinsic fluorescence. The effects of protein-phenolic compounds interactions on the total phenolic content and antioxidant activity were also assessed. The WPI-CA complexes were obtained by mixture of WPI and CA stock solutions in deionized water. The complexation was carried out at room temperature during 60 min, using 0.1 M NaOH to adjust pH at 7.0. The WPI concentration was fixed at 5 mg/mL, whereas the CA concentration varied in order to obtain four different WPI:CA molar relations (1:1; 2:1; 5:1; 10:1). WPI and phenolic solutions were used as controls. Intrinsic fluorescence spectra of the complexes (mainly due to Trp fluorescence emission) were obtained at λex = 280 nm and the emission intensities were measured from 290 to 500 nm. Extrinsic fluorescence was obtained as the measure of protein surface hydrophobicity (S0) using ANS as a fluorescence probe. Total phenolic content was determined by Folin-Ciocalteau and the antioxidant activity by FRAP and ORAC methods. Increasing concentrations of CA resulted in decreasing of WPI intrinsic fluorescence. The emission band of WPI red shifted from 332 to 354 nm as the phenolic concentration increased, which is related to the exposure of Trp residue to the more hydrophilic environment and unfolding of protein structure. In general, the complexes presented lower S0 values than WPI, suggesting that CA hindered ANS binding to hydrophobic sites of WPI. The total phenolic content in the complexes was lower than the sum of two compounds isolated. WPI showed negligible AA measured by FRAP. However, as the relative concentration of CA increased in the complexes, the FRAP values enhanced, indicating that AA measure by this technique comes mainly from CA. In contrast, the WPI ORAC value (82.3 ± 1.5 µM TE/g) suggest that its AA is related to the capacity of H+ transfer. The complexes exhibited no important improvement of AA measured by ORAC in relation to the isolated components, suggesting complexation partially suppressed AA of the compounds. The results hereby presented indicate that interaction of WPI and CA occurred, and this interaction caused a structural change in the proteins. The complexation can either hide or expose antioxidant sites of both components. In conclusion, although the CA can undergo an AA suppression due to the interaction with proteins, the AA of WPI could be enhanced due to protein unfolding and exposure of antioxidant sites.

Keywords: bioactive properties, milk proteins, phenolic acids, protein-phenolic compounds complexation

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Authors: Abhisek Sinha, Debobrata Rajak, Shilpa Rani, Ram Gopal, Vandana Sharma

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The interaction of femtosecond laser pulses with metallic tips has been studied extensively, and they have proved to be a very good source of ultrashort electron pulses. A study of the interaction of femtosecond Laguerre-Gaussian (LG) laser modes with Tungsten tips is presented here. Laser pulses of 35 fs pulse durations were incident on Tungsten tips, and their electron emission rates were studied for LG (l=1, p=0) and Gaussian modes. A change in the order of the interaction for LG beams is reported, and the difference in the order of interaction is attributed to ponderomotive shifts in the energy levels corresponding to the enhanced near-field intensity supported by numerical simulations.

Keywords: femtosecond, Laguerre-Gaussian, OAM, tip

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Authors: Kittisak Jantanasakulwong, Toshiaki Ougizawa

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Thermoplastic starch (TPS) was prepared by melt-blending of cassava starch with glycerol (70/30 wt%/wt%) at 130 ◦C for 10 min. Chitosan (CTS) was used as a compatibilizer. TPS/CTS blend was melt-blended with maleic anhydride grafted ethylene-1-butene rubber (EB-MAH) in the composition of 80/20 respectively. Addition of CTS in TPS/EB-MAH blend decreased particles size of EB-MAH rubber to 1µm in TPS matrix. Mechanical properties, solubility, swelling property, morphology, and water contact angle of TPS/EB-MAH blend were improved by CTS incorporation. FTIR confirmed a reaction had occurred between amino groups (-NH2) of CTS and the MAH groups of EB-MAH. This reaction and the enhanced miscibility between TPS and CTS improved morphology and properties of the TPS/EB-MAH/CTS blend.

Keywords: thermoplastic starch, rubber, reactive blending, chitosan

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

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Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

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Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

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In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: material ordering, project scheduling, quantity discount, space availability

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Giap Pham Ngoc Tram, Tran Hong Quan, Tran Tieu Yen, Nguyen Phung Tien

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The use of natural ingredients to enhance the nutritional and sensory properties of food products has gained significant interest in recent years. This study focuses on the effect of Golden oyster mushroom powder (GOMP) on the physiochemical, antioxidative, and sensory properties of noodles. The aim of this study is to investigate the influence of GOMP on the nutritional, antioxidant, and sensory properties of noodles. The study determined the color, moisture, total ash, protein, total phenolic, flavonoid contents, water activity, and antioxidant activity of GOMP and noodles. The incorporation of GOMP at levels of 5-15% increased the ash, protein, flavonoid, and total phenolic contents of the noodles. It also enhanced their antioxidant activities, as evidenced by improved DPPH radical scavenging activity and metal chelating activity. However, the incorporation of GOMP resulted in a decrease in the L* and b* values of the noodles. Furthermore, the GOMP-enriched noodles exhibited a lower cutting force compared to the control. This study highlights the potential of GOMP as a nutritional and antioxidant ingredient in noodle preparation. It adds to the existing literature by providing evidence of the positive effects of GOMP on the nutritional and functional properties of noodles. The researchers collected data on the physiochemical properties, nutritional contents, and antioxidant activities of GOMP and noodles. Statistical analysis was then performed to assess the differences between the control and GOMP-enriched noodles. The results of this study demonstrate that the inclusion of GOMP at the amount of 5-15% can increase the nutritional and antioxidant properties of noodles without significantly impacting sensory attributes.

Keywords: oyster mushroom, noodles, antioxidant activity, phytochemical, sensory property

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Authors: A.Knox

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Student diversity in postgraduate classes puts major challenges on educators seeking to encourage student engagement and desired to learn outcomes. This paper outlines the impact of a set of teaching initiatives aimed at addressing challenges associated with teaching and learning in an environment characterized by diversity in the student cohort. The study examines postgraduate students completing the core capstone unit within a specialized business degree. Although relatively small, the student cohort is highly diverse in terms of cultural backgrounds represented, prior learning and/or qualifications, as well as duration and type of work experience relevant to the degree, is completed. The wide range of cultures, existing knowledge and experience create enormous challenges with respect to students’ learning needs and outcomes. Subsequently, a suite of teaching innovations has been adopted to enhance curriculum content/delivery and the design of assessments. This paper explores the impact of these specific teaching and learning practices, examining the ways they have supported students’ diverse needs and enhanced students’ learning outcomes. Data from surveys and focus groups are used to assess the effectiveness of these practices. The results highlight the effectiveness of peer-assisted learning, cultural competence-building, and advanced assessment options in addressing diverse student needs and enhancing student engagement and learning outcomes. These findings suggest that such practices would benefit students’ learning in environments marked by diversity in the student cohort. Specific recommendations are offered for other educators working with diverse classes.

Keywords: assessment design, curriculum content, curriculum delivery, student diversity

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Authors: Tanapat Chongkamunkong

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The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Hanen Bouaziz, Françoise Croute, Najiba Zeghal

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In order to investigate the toxic effects of fluoride on cerebrum maturity of suckling mice, we treated adult female mice of Swiss Albinos strain by 500 ppm NaF in their drinking water from the 15th day of pregnancy until the day 14 after delivery. All mice were sacrificed on day 14 after parturition. During treatment, levels of thiobarbituric acid reactive substances, the marker of lipid peroxidation extend, increased, while the activities of the antioxidant enzymes such as glutathione peroxidase, superoxide dismutase and catalase and the level of glutathione decreased significantly in cerebellum compared with those of the control group. These results suggested that fluoride enhanced oxidative stress, thereby disturbing the antioxidant defense of nursing pups. In addition, acetylcholinesterase activity in cerebellum was inhibited after treatment with fluoride. In cerebellum of mice, migration of neurons from the external granular layer to the internal granular layer occurred postnatally. Key guidance signals to these migrating neurons were provided by laminin, an extracellular matrix protein fixed to the surface of astrocytes. In the present study, we examined the expression and distribution of laminin in cerebellum of 14-day-old mice. Immunoreactive laminin was disappeared by postnatal day 14 in cerebellum parenchyma of control pups and was restricted to vasculature despite the continued presence of granular cells in the external granular layer. In contrast, in cerebellum of NaF treated pups, laminin was deposited in organised punctuate clusters in the molecular layer. These data indicated that the disruption of laminin distribution might play a major role in the profound derangement of neuronal migration observed in cerebellum of NaF treated pups.

Keywords: acetylcholinesterase activity, cerebellum, laminin, oxidative stress, suckling mice

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Authors: Pan Hongxia, Wang Zhenhua

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In this paper, the EMD decomposition in the process of endpoint effect adopted data based on AR model to predict the continuation and window function method of combining the two effective inhibition. Proven by simulation of the simulation signal obtained the ideal effect, then, apply this method to the gearbox test data is also achieved good effect in the process, for the analysis of the subsequent data processing to improve the calculation accuracy. In the end, under various working conditions for the gearbox fault diagnosis laid a good foundation.

Keywords: gearbox, fault diagnosis, ar model, end effect

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Authors: Maria Jędrzejczak, Patryk Pieniążek

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The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

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Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: Amal Mohammed Alqahatni

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This paper is a non-empirical analysis of existing literature on digital leadership competency, data-driven organizations, and dealing with AI technology (big data). This paper will provide insights into the importance of developing the leader’s analytical skills and style to be more effective for high-quality decision-making in a data-driven organization and achieve creativity during the organization's transformation to be digitalized. Despite the enormous potential that big data has, there are not enough experts in the field. Many organizations faced an issue with leadership style, which was considered an obstacle to organizational improvement. It investigates the obstacles to leadership style in this context and the challenges leaders face in coaching and development. The leader's lack of analytical skill with AI technology, such as big data tools, was noticed, as was the lack of understanding of the value of that data, resulting in poor communication with others, especially in meetings when the decision should be made. By acknowledging the different dynamics of work competency and organizational structure and culture, organizations can make the necessary adjustments to best support their leaders. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how analytical leadership will assist in overcoming challenges in a data-driven organization's work environment.

Keywords: digital leadership, big data, leadership style, digital leadership challenge

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Authors: Chaitanya Varma, Arpan Mehar

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The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

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Authors: Prince Chukwuneme Enwereji, Annelien Van Rooyen

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In recent years, technology integration in education has transformed the learning landscape, particularly in online institutions. One technological advancement that has gained popularity is e-tutoring, which offers personalised academic support to students through online platforms. While e-tutoring has become well-known and has been adopted to promote collaborative learning, there are still students who do not use these services for various reasons. However, little attention has been given to understanding the perspectives of students who have not utilized these services. The research objectives include identifying the perceived benefits that non-e-tutoring students believe e-tutoring could offer, such as enhanced academic support, personalized learning experiences, and improved performance. Additionally, the study explored the potential drawbacks or concerns that non-e-tutoring students associate with e-tutoring, such as concerns about efficacy, a lack of face-to-face interaction, and platform accessibility. The study adopted a quantitative research approach with a descriptive design to gather and analyze data on non-e-tutoring students' perspectives. Online questionnaires were employed as the primary data collection method, allowing for the efficient collection of data from many participants. The collected data was analyzed using the Statistical Package for the Social Sciences (SPSS). Ethical concepts such as informed consent, anonymity of responses and protection of respondents against harm were maintained. Findings indicate that non-e-tutoring students perceive a sense of control over their own pace of learning, suggesting a preference for self-directed learning and the ability to tailor their educational experience to their individual needs and learning styles. They also exhibit high levels of motivation, believe in their ability to effectively participate in their studies and organize their academic work, and feel comfortable studying on their own without the help of e-tutors. However, non-e-tutoring students feel that e-tutors do not sufficiently address their academic needs and lack engagement. They also perceive a lack of clarity in the roles of e-tutors, leading to uncertainty about their responsibilities. In terms of communication, students feel overwhelmed by the volume of announcements and find repetitive information frustrating. Additionally, some students face challenges with their internet connection and associated cost, which can hinder their participation in online activities. Furthermore, non-e-tutoring students express a desire for interactions with their peers and a sense of belonging to a group or team. They value opportunities for collaboration, teamwork in their learning experience, the importance of fostering social interactions and creating a sense of community in online learning environments. This study recommended that students seek alternate support systems by reaching out to professors or academic advisors for guidance and clarification. Developing self-directed learning skills is essential, empowering students to take charge of their own learning through setting objectives, creating own study plans, and utilising resources. For HEIs, it was recommended that they should ensure that a variety of support services are available to cater to the needs of all students, including non-e-tutoring students. HEIs should also ensure easy access to online resources, promote a supportive community, and regularly evaluate and adapt their support techniques to meet students' changing requirements.

Keywords: online-tutor;, student support;, online education, educational practices, distance education

Procedia PDF Downloads 82

Authors: Adrian Florin Busu

Abstract:

The communicative approach, or communicative language teaching, used for enhancing communicative skills in students in automatics is a modern teaching approach based on the concept of learning a language through having to communicate real meaning. In the communicative approach, real communication is both the objective of learning and the means through which it takes place. This approach was initiated during the 1970’s and quickly became prominent, as it proposed an alternative to the previous systems-oriented approaches. In other words, instead of focusing on the acquisition of grammar and vocabulary, the communicative approach aims at developing students’ competence to communicate in the target language with an enhanced focus on real-life situations. To put it in an nutshell, CLT considers using the language to be just as important as actually learning the language.

Keywords: communication, approach, objective, learning

Procedia PDF Downloads 161

Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang

Abstract:

Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.

Keywords: human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing

Procedia PDF Downloads 664

Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

Abstract:

Innovation in manufacturing process technologies and associated product design affects the prospects for manufacturing today and in near future. In this study some theoretical methods, useful as tools in advanced manufacturing, are considered. In particular, some basic Mathematical, Operational Research, Heuristic, and Statistical techniques are discussed. These techniques/methods are very handy in many areas of advanced manufacturing processes, including process planning optimization, modelling and analysis. Generally the production rate requires the application of Mathematical methods. The Emerging Trends Processes in Advanced Manufacturing can be enhanced by using Mathematical Modelling and Optimization techniques.

Keywords: mathematical modelling, optimization, emerging trends, advanced manufacturing

Procedia PDF Downloads 298

Authors: Ade Dwi Utami

Abstract:

Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

Procedia PDF Downloads 246