bluuebunny/crossref_metadata_2025 huggingface dataset:
Interpretation of Hue Diversity and Coloring Pigment Analysis onto the Wooden Ksitigarbha Bodhisattva Triad and Clay Ten Underworld Kings in Namwon Seonwonsa Temple, Korea
Authors: Jeong Dong Hee , Han Doo Roo , Choi Il Kyu , Lee Chan Hee
Published: August 2024

The Wooden seated Ksitigarbha Bodhisattva triad and Clay Statues of Ten Underworld Kings within the Myeongbujeon Hall of Namwon Seonwonsa Temple are known to have clear creators, and documented to be in 1610. The Statues serve as significant academic resources for examining the morphological changes in the statues that were actively produced in the late Joseon period. However, various damages such as exfoliation of pigment layer, cracks and breakages occurred in the studied Statues, and the pigments showed complex chemical composition. In particular, large amounts of Ca and P were detected in the white basement layer, which suggesting the existence of a whitewashed at the time of creation. The blue pigments on the Clay Statues of Ten Underworld Kings generally shows the characteristics of Sinamchae, a mixture of colored metal oxides and glassy powder. The studied Statues have been recorded in multiple repairing, and various coloration components were detected even in pigments of similar colors, indicating that were toned. Based on the coloring techniques such as over and filler paintings, it is interpreted that there was a supply and demand of materials reflected the period and social situation of the time. The results of this study can be utilized as basic data for future conservations on the Statues in Seonwonsa Temple.
Implication and Chemical Composition of Ancient Green Glass from Hong Nang Sida Temple in Champasak, Lao PDR
Authors: Choi Hye Ji , Yang Hye Ri , Chun Yu Gun , Lee Chan Hee
Published: August 2024

In southern part of Laos, once prospered under the Khmer Empire in the past, lots of ancient cultural heritage including Hong Nang Sida temple is still preserved. In this study, the chemical compositions, chromaticity and occurrences for five ancient green glasses excavated from Hong Nang Sida temple by Korea Heritage Agency were analyzed, and their implication was examined. As a result, all glasses showed some differences in hue, size, weight and shape, however, the compositions of flux, stabilizer and colorant revealed large differences. These have been identified as potash, soda and lead glass based on their composition. Considering the diversity of composition, it is interpreted that the production location and period of each glass was different. Meanwhile, if it estimates the inflow route reflecting the characteristics of glass, may be possible to infer regional or international exchanges in Laos at the time. This will be important data for understanding not only the ancient glass of Laos but also the glass artifacts technology and trade of Southeast Asian countries in the Khmer Empire cultural sphere.
An analysis of clinical application effects of 3d-printed act titanium trabecular intervertebral fusion cage in posterior lumbar interbody fusion (PLIF)
Authors: Li Zhijun , Wang Hong , Wang Zhaoqi , Qi Zhiming , Yao Qi
Published: August 2024

Objective: To compare the clinical effects of applying a 3D-printed ACT titanium trabecular intervertebral fusion cage and a Polyetheretherketone (PEEK) cage in posterior lumbar interbody fusion (PLIF).
Methods: This was a clinical comparative study. Forty patients with degenerative lumbar diseases admitted at The Second People’s Hospital of Dalian from January 2020 to December 2021 were selected and divided into an observation group (3D cage) and a control group (PEEK cage) using the random number table method, with each group of 20 cases. The visual analogue scale (VAS) scores, Japanese Orthopaedic Association (JOA) scores, Cobb angles at fusion segments, intervertebral height and intervertebral fusion situations of the patients between the groups were compared.
Results: No significant differences were found in their operation time, intraoperative blood losses and operation related complications(p>0.05). In terms of postoperative VAS and JOA scores in both groups, they are all significantly improved compared with those before the operation, and their differences are also statistically significant(p<0.05). However, no statistical significance exists in inter-group differences(p>0.05). Postoperative Cobb angles and intervertebral height of patients in both groups are considerably bettered compared with those before the operation. Their differences show statistical significance(p<0.05), while inter-group differences are proved to be not statistically significant(p>0.05).
Conclusions: Applying a 3D-printed ACT titanium trabecular intervertebral fusion cage or PEEK cage in PLIF has the potential to improve clinical symptoms of patients with degenerative lumbar diseases, and restore the Cobb angle and intervertebral height. 3D-printed ACT titanium trabecular intervertebral fusion cage can accelerate intervertebral fusion without increasing operation related complications.
doi: https://doi.org/10.12669/pjms.40.8.8759
How to cite this: Li Z, Wang H, Wang Z, Qi Z, Yao Q. An analysis of clinical application effects of 3d-printed act titanium trabecular intervertebral fusion cage in posterior lumbar interbody fusion (PLIF). Pak J Med Sci. 2024;40(8):---------. doi: https://doi.org/10.12669/pjms.40.8.8759
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
100 + 1 λόγοι να αγαπήσουμε τα βιβλία
Authors: Βίγκου Κατερίνα
Published: August 2024

Το άρθρο περιγράφει την εξέλιξη ενός προγράμματος φιλαναγνωσίας στο δημοτικό σχολείο. Η δράση ξεκίνησε ως ένα πρόγραμμα σχολικών δραστηριοτήτων σε συνδυασμό με ένα κύκλο των εργαστηρίων δεξιοτήτων της τρίτης δημοτικού. Ωστόσο, τα γεγονότα μας οδήγησαν να αναπτύξουμε και να πραγματοποιήσουμε δράσεις φιλαναγνωσίας σε πολλές στιγμές της σχολικής χρονιάς, σε διάφορα μαθήματα, και κυρίως στο μάθημα της γλώσσας. Η φιλαναγνωσία έγινε κομμάτι της σχολικής μας καθημερινότητας και κουλτούρας. Οι συνθήκες που δημιουργήθηκαν κατά τη διάρκεια του σχολικού έτους, κατέστησαν το κλείσιμο της σχολικής χρονιάς και τη δημιουργία της λέσχης ανάγνωσης της τάξης μας μία φυσική εξέλιξη της πορείας μας προς την ανακάλυψη 100 + 1 λόγων για να αγαπήσουμε τα βιβλία.
Οι πολιτικές ανταμοιβής των Εκπαιδευτικών με βάση την επίδοση των μαθητών/τριών τους (erformance-based pay).
Authors: ΚΑΡΑΤΖΑΣ ΦΙΛΙΠΠΟΣ
Published: August 2024

Μέσα από την βελτίωση της ποιότητας  του εκπαιδευτικού συστήματος κάθε κράτος επιδιώκει τη βελτίωση των επιδόσεων των μαθητών με απώτερο σκοπό να αξιοποιηθούν στο  έπακρο τα ταλέντα και οι ικανότητες τους  ώστε να βοηθήσουν στην ανάπτυξη και την ευημερία της κοινωνίας. Οι εκπαιδευτικοί αποτελούν  την καρδιά των σχολείων και επομένως βρίσκονται  στο επίκεντρο κάθε προγράμματος σχολικής βελτίωσης. Για το λόγο αυτό τα τελευταία χρόνια οι εκπαιδευτικές πολιτικές δίνουν μεγάλη σημασία στην βελτίωση της ποιότητας των εκπαιδευτικών που διδάσκουν. Αυτό επιτυγχάνεται με την χορήγηση  κίνητρων για  συνεχή βελτίωση τα οποία εκτός από εσωτερικά είναι και εξωτερικά. Τα τελευταία χρόνια η ανταμοιβή των εκπαιδευτικών βασισμένη στην απόδοση των μαθητών σε τυποποιημένες δοκιμασίες αποτελεί κυρίαρχο θέμα για την αξιολόγηση και την επιβράβευση των καλύτερων εκπαιδευτικών, δημιουργώντας και εγείροντας αντιρρήσεις για την ορθότητά της. Η ανασκόπηση της βιβλιογραφίας δείχνει ότι η επιστημονική κοινότητα είναι διχασμένη από τη χρήση των μαθητικών επιδόσεων για  την εξαγωγή συμπερασμάτων που αφορούν την  ποιότητα  των εκπαιδευτικών και παρόλο που η πρακτική αυτή θα παραμείνει δεν μπορεί να δώσει έγκυρα αποτελέσματα για την σχέση ποιότητας των εκπαιδευτικών και των επιδόσεων που πραγματοποιούν οι μαθητές.
Γνωρίζουμε την τοπική πολιτιστική & φυσική κληρονομιά και την αναδεικνύουμε αξιοποιώντας τις Νέες Τεχνολογίες
Authors: Τσολοπούλου Βασιλική
Published: August 2024

Η παρούσα εργασία παρουσιάζει μια διδακτική πρόταση τύπου Project που αφορά στη γνωριμία των μαθητών/τριών με την τοπική πολιτιστική και φυσική κληρονομιά. Η εν λόγω διδακτική πρόταση αναδύθηκε από δύο πανομοιότυπα προγράμματα που υλοποιήθηκαν τα δύο τελευταία σχολικά έτη, 2022-2023 και 2023-2024, σε δύο σχολεία του Νομού Μεσσηνίας, το 10Ο Πειραματικό Δημοτικό Καλαμάτας και το 2ο Δημοτικό Κυπαρισσίας, αντιστοίχως. Και τα δύο αυτά προγράμματα υλοποιήθηκαν στο πλαίσιο του μαθήματος Εργαστήρια Δεξιοτήτων, υπάγονταν στη θεματική «Φροντίζω το περιβάλλον» και στην υποθεματική «Παγκόσμια & τοπική κληρονομιά», απευθύνονταν στους μαθητές και στις μαθήτριες της Στ΄ τάξης των προαναφερόμενων σχολείων και είχαν διάρκεια δυόμιση περίπου μηνών. Αξίζει να σημειωθεί ότι τα δύο προγράμματα θα περιγραφούν ως ένα καθώς η ροή και το περιεχόμενο των επιμέρους δραστηριοτήτων που περιλάμβαναν συμπίπτουν πέραν του τελευταίου σκέλους τους, που αφορά στην επιλογή του τρόπου διάχυσης των αποτελεσμάτων τους, όπου και διαφοροποιούνται.
Μαθαίνω για τα ανθρώπινα δικαιώματα μέσα από βιωματικές δράσεις
Authors: Μαρκοπούλου Αικατερίνη
Published: August 2024

Τα ανθρώπινα δικαιώματα και πιο συγκεκριμένα τα δικαιώματα του παιδιού αποτελούν αξίες για όλους τους ανθρώπους ανεξαρτήτως εθνικότητας, θρησκείας και καταγωγής. Αντικείμενο της συγκεκριμένης εργασίας είναι η εισαγωγή της έννοιας των δικαιωμάτων και η ενασχόληση του παιδιού με αυτά, στο Νηπιαγωγείο και στις πρώτες τάξεις του Δημοτικού σχολείου μέσα από μια διαθεματική προσέγγιση με σκοπό να κατανοήσουν οι μαθητές/τριες την ευρύτερη έννοια της διαπολιτισμικότητας, της ενσυναίσθησης, της ισότητας και την προώθηση της ανθρώπινης αξιοπρέπειας. Οι προτεινόμενες δραστηριότητες αναπτύσσουν την πολυπολιτισμική επίγνωση των παιδιών και καλλιεργούν όλους τους γνωστικούς τομείς ανάπτυξης. Μέσα από την υλοποίηση ατομικών αλλά κυρίως, ομαδικών δραστηριοτήτων, οι οποίες επιδιώκουν να κρατήσουν αμείωτο το ενδιαφέρον, οι μικροί μαθητές/τρίες θα έρθουν σε επαφή με έννοιες που σχετίζονται με την πολυπολιτισμικότητα, θα μάθουν να αποδέχονται το διαφορετικό και να κρατούν ασφαλείς αποστάσεις από ρατσιστικές πρακτικές και στερεότυπα.
Editorial
Authors: Σουλιώτη Μάγδα
Published: August 2024

Editorial
Οι Απαρχές του Εξεταστικού Ζητήματος στην Εκπαίδευση: Δυσλειτουργίες και Αναθεωρήσεις
Authors: Κανταράκη Σοφία
Published: August 2024

Το εξεταστικό ζήτημα και η σύστοιχη ιδεολογία που συμπυκνώνει, ως σημαίνουσα πτυχή της εκπαίδευσης, θα απασχολήσει πολυεπίπεδα τους κατά περιόδους ιθύνοντες υπουργούς Εκκλησιαστικών και Δημοσίας Εκπαιδεύσεως του νεοσύστατου ελληνικού κράτους και θα διέλθει από αρκετές διακυμάνσεις, οι οποίες χρωματίζονται κοινωνικά και ιδεολογικά. Είναι σημαντικό ότι ο δημόσιος χαρακτήρας των εξετάσεων πιστοποιούσε τον βαθμό ικανότητας του προσωπικού και της συνολικής λειτουργίας του σχολείου. Παρόλα αυτά η ίδια η σχολική πραγματικότητα θα αναδείξει κατά καιρούς δυσλειτουργίες της εξεταστικής διαδικασίας που καταστρατηγούσαν και υπονόμευαν τον παιδαγωγικό της ρόλο. Στη σύντομη αυτή αναδρομή διαφαίνεται ο εύθραυστος χαρακτήρας των εξετάσεων και η αποτύπωση αυτού στα εκπαιδευτικά πράγματα
Radioactivity studies in soils from Northwestern Greece
Authors: Zafeiris Thomas , Siltzovalis Georgios , Lagaki Varvara , Madesis Ioannis , Mertzimekis Theodoros
Published: August 2024

Natural radioactivity is examined in soil samples collected from Northwestern Epirus, specifically in Pogoni and Zagori areas. The focus was to determine experimentally the specific activity for naturally occurring isotopes (40K, U and Th series) and the anthropogenic 137Cs, in the samples collected from a generally unexplored area of Greece. The measurements were carried out with the use of two High-Purity Germanium (HPGe) detectors, calibrated with two different bulk geometry samples. Based on the measurements of specific activities, the absorbed dosage and index of external hazard, Hex have been estimated through models of UNSCEAR, contributing to the level of environmental sustainability of the area.
TALYS calculations for α capture reactions on Cu isotopes
Authors: Peoviti Maria , Axiotis Michail , Patronis Nikolaos , Dimitriou Paraskevi , Foteinou Varvara , Harissopulos Sotirios , Maragkos Fotios , Rogalla Detlef
Published: August 2024

Within the present work, previously measured experimental cross-sections of the 63Cu(α,γ)67Ga reaction at astrophysical energies are compared with a variety of different theoretical calculations. Utilizing the nuclear reaction code TALYS (v1.96), the research incorporates all available models for the α-particle Optical Model Potential (α-OMP), Nuclear Level Densities (NLD), and γ-ray Strength Functions (γ-SF), as well as, all the combinations of the aforementioned parameters, resulting in a large number of theoretical calculations. The primary goal is to optimize the parametrization of the HF calculations to best describe the experimental data. The same methodology is applied to the 65Cu(α,γ)69Ga reaction to comprehensively examine the impact of different models on cross-section calculations in this mass region. While this work is ongoing, preliminary results are presented within this contribution.
Quarkyonic matter and applications in neutron stars
Authors: Folias Konstantinos , Moustakidis Charalambos
Published: August 2024

We consider a quarkyonic matter model in which, for large values of density and Fermi energies, weassume particles as quasiparticles where the low Fermi momentum states are occupied by quarks and the higherstates in phase space are occupied by baryons. This idea has the aim to explain with a consistent way the phasetransition in the interior of a neutron star or a hybrid star and to provide an equation of state which can produceneutron stars with masses greater than 2Msun without violating causality. At extremely high density, quarkyonicmatter is inferred from the properties of QCD when Nc is large and is a qualitative way to describe the particlesin the momentum space. This state of matter can provide the sound velocity as a non-monotonic function of thebaryon density which for higher values of density tends asymptotically to the conformal limit 1/√3.
A Study of natural radioactivity in urban parks
Authors: Gelatsoras Foivos Panagiotis , Mertzimekis Theo , Krassakis Pavlos , Lagaki Varvara , Madesis Ioannis , Siltzovalis Georgios
Published: August 2024

Urban parks are typically undisturbed natural locations inside metropolitan areas, attracting human recreation activities. The present work focuses on studying the radioactivity levels in urban parks in the metropolitan areas of Athens, Barcelona, and Bucharest to establish a baseline of the overall environmental load and the associated contribution to background radiation dose levels. A total of 25 soil samples were collected, prepared, and measured with high-resolution gamma spectroscopy at the Environmental Radioactivity Laboratory of NKUA. Specific activities for naturally occurring isotopes (40K, U-, and Th-series) and anthropogenic radiocesium have been deduced. The results are correlated to the level of human intervention in the parks but also show that traces of 137Cs from the Chernobyl fallout are still present in the most undisturbed soils, reaching values up to 86±4 Bq/kg. All the data has been used to populate a GIS-based informational database featuring various layers of storyboards and metadata.
Recent results on elastic scattering and single-neutron stripping reaction in the 18O+48Ti collision at 275 MeV
Authors: Sgouros Onoufrios , Brischetto G. A. , Cappuzzello F. , Cavallaro M. , Carbone D. , Agodi C. , Calvo D. , Chavez Lomeli E. R. , Ciraldo I. , Cutuli M. , De Gregorio G. , Delaunay F. , Djapo H. , Eke C. , Finocchiaro P. , Fisichella M. , Gargano A. , Guazzelli M. A. , Hacisalihoglu A. , Linares R. , Lubian J. , Medina N. H. , Moralles M. , Oliveira J. R. B. , Pakou A. , Pandola L. , Soukeras V. , Souliotis G. , Spatafora A. , Torresi D. , Yildirim A. , Zagatto V. A. B.
Published: August 2024

A global study of the 18O+48Ti collision at 275 MeV was carried out within the NUMEN and NURE experimental campaigns by measuring the complete net of nuclear reactions which may be involved in the 48Ti→48Ca double charge exchange transition. The relevant experiment was visualized at the INFN-LNS in Catania, where angular distribution measurements for a plethora of reaction channels were performed by means of the MAGNEX large acceptance magnetic spectrometer. The present work provides an overview of the analyses of the elastic scattering and one-neutron transfer reaction channels.
Radio-dating method of 210Pb in a marine sediment core from the deep basin Northern of Skyros Isl., Aegean Sea
Authors: Roumelioti Spyridoula - Konstantina , Patiris Dionysios , Tsabaris Christos , Alexakis Stylianos
Published: August 2024

In this work, the level of natural and artificial radioactivity in a marine sediment core obtained from the Northern basin of Skyros (Sporades region - Aegean Sea, Greece) was measured by a high-purity germanium detector. More specifically, the activity concentration was determined for the radionuclides 226Ra, 214Pb, 214Bi and 210Pb, 208Tl, and 228Ac, the natural potassium radioisotope 40K, and the anthropogenic cesium radionuclide 137Cs. The vertical distribution was obtained for each of them in the core and subsequently, based on the radio-dating method of 210Pb, the time reconstruction of their activity was realized. The sediment accumulation rate was calculated at (0.17±0.02) cm y-1 which in the specific core is equivalent to sediment deposition of 1 cm per (6 ± 1) years. The vertical distribution of 137Cs was also used to validate the accumulation rate. According to the time reconstruction, a significant increase of both 226Ra and 208Tl was revealed in the period 1950-1960. The results highlight that the radio dating method of 210Pb, even though it is widely used in coastal marine areas, can be successfully applied in deep-sea regions where the accumulation of sediment is high enough (mm per year) due to sediment gravity flow.
Cross Section Biasing Technique in 3H(d,n)4He Reaction using the GEANT4 Toolkit
Authors: Tsormpatzoglou Ioannis , Ziagkova Anastasia , Kokkoris Michael , Diakaki Maria , Vlastou Roza , Kaperoni Kalliopi
Published: August 2024

Simulations using Monte Carlo GEANT4 [1] toolkit was performed to quantify parasitic neutrons production from the 3H(d,n)4He reaction in the TANDEM [2] accelerator laboratory at N.C.S.R "Demokritos". In this reaction, parasitic neutrons are produced, which contaminate the main neutron beam. For studying parasitic neutrons, the cross section biasing technique has been applied to increase the cross sections of the reactions and to obtain accurate statistical results in a short computational time. However, the implementation of a biasing technique can significantly impact the physical processes simulated. The experimental setup contains the accelerator line and the tritium flange, which consists of molybdenum, tritium and copper. Then, the target materials are purposefully exposed to the neutron beam to conduct cross section measurement experiments. The simulation code aims to understand neutron flux distribution and transport through the targets. Finally, the corresponding results obtained using GEANT4, through the application of biasing techniques, were compared to those resulting from the combined use of the MCNP 6.1 [3] and NeuSDesc [4] codes.
An Improved Technique for Monitoring Radon Progeny in Ambient Air
Authors: Kanoutos Konstantinos , Petropoulos Nick , Anagnostakis Marios
Published: August 2024

Radon progeny fluctuation outdoors has been widely studied for decades, with increasing interest in the last few years towards the investigation of possible correlation with atmospheric parameters and various environmental processes. Within this context, Bi-214 activity in ambient air has been systematically monitored at the Nuclear Engineering Laboratory of NTUA for several decades. However, the measuring technique and data analysis demonstrated various shortcomings. Currently, the measuring system has been upgraded and a new approach has been implemented for signal analysis. Measures were also taken to reduce background radiation and enhance the signal. Analysis of the collected data deemed challenging because of the effect of precipitation to the detected Bi‑214; efforts were made to monitor and interpret this effect. Analysis of experimental data over a period of ~6 months together with data for rain events confirmed that precipitation led to elevated signals. Furthermore, the results pointed towards a possible correlation between rain rate and Bi-214 count rate, indicating the need for further work on the subject. When concluded, this study will hopefully contribute to the ongoing investigation of radon progeny fluctuations in atmospheric air.
Η Στρατηγική Θαλάσσιας Ασφάλειας της EE και η συμβολή της στην περιφερειακή ολοκλήρωση των κρατών της Ανατολικής Μεσογείου.
Authors: Κουκάκης Γεώργιος
Published: August 2024

Το παρόν κείμενο πολιτικής αξιολογεί κριτικά τη Στρατηγική Θαλάσσιας Ασφάλειας της Ευρωπαϊκής Ένωσης που δημοσιεύτηκε τον Μάρτιο του 2023, η οποία αποτελεί αναθεώρηση του αντίστοιχου στρατηγικού εγγράφου που είχε δημοσιευθεί το 2014. Υποστηρίζεται δε ότι η εν λόγω στρατηγική συμβάλλει σημαντικά στην περιφερειακή ολοκλήρωση των κρατών της Ανατολικής Μεσογείου, καθώς παρέχει το απαραίτητο θεσμικό πλαίσιο συνεργασίας σε πολιτικό και οικονομικό επίπεδο μέσω του οποίου οι κρατικοί και μη δρώντες μπορούν να αναπτύξουν τη δράση τους σε μία πληθώρα τομέων πολιτικής, εκμεταλλευόμενοι παράλληλα την ασφάλεια που απορρέει από τη στρατηγική, η οποία αποτελεί προϋπόθεση της ανάπτυξης.
Approaches towards pragmatic language assessment in Indian pre-schoolers: A survey among speech-language pathologists
Authors: Rasheeka Saniya , Karuppali Sudhin , Bhat Jayashree , Mohan Megha , Varghese Aiswarya
Published: August 2024

Background Pragmatic language assessment in children is performed in line with standard protocols, guidelines, and best practices. The absence of these aspects in the Indian context has resulted in the quest to explore the approaches used by speech-language pathologists (SLPs) to assess pragmatic language impairments. This survey explored the current practices of SLPs towards the assessment of pragmatic language among preschool children in India. It also aimed to identify the barriers, facilitators and identify the level of knowledge, skill and overall practice of SLPs towards their practices using self-appraisal. Methods A total of 100 SLPs(94 females and 6 males) working with preschool aged children (three-to-six-year-olds) from across different Indian states participated in the survey. Participants were enquired about the aspects of pragmatic language assessed, methods used for assessment, awareness and use of Indian tools, the settings, members, and language used for the assessment. Additionally, they were asked to mention the specific tools used, informal methods used, barriers and facilitators, and self-appraise their knowledge, skill and overall practice. Results Majority of participants assessed multiple aspects of pragmatic language. All used a combination of different assessment methods, with the participants commonly using informal compared to formal approaches. Preschoolers were assessed at multiple settings, along with different communication partners. Lack of awareness on assessment tools developed in India was the major barrier, while the use of informal tasks or activities were the major facilitators influencing pragmatic language assessment to a greater extent. The knowledge and skills for the assessment of pragmatic language obtained poorer scores compared to practices. Conclusions The assessment practices of the SLPs were largely influenced by the unavailability of developed or adapted tools for Indian preschoolers, leading to the need to develop indigenous assessment tools. Certain considerations for further assessment practices have been identified and discussed.
The Trajectory Data Mining Model for College Students in Compus Life and Academic Management
Authors: Liu Wugang
Published: August 2024

The main objective of the study is to address the lack of comprehensive management technology in student campus life in universities. Starting from the life trajectory data of students in campus life, a trajectory mining model combining data mining technology and university information system is designed. In addition, an applied clustering algorithm is designed to classify different trajectory feature types. The research results show that in actual trajectory analysis, the categories of action trajectories from dormitories to canteens, from 0 to 4, are 87.64%, 87.86%, 86.97%, 88.63%, and 88.71%, respectively, which are the most matched effective action trajectories. It can be seen that the trajectory analysis model designed in the study is effective and can provide assistance for the comprehensive academic management of college students.
Research on the Construction of Intelligent System of Landscape in Science and Innovation Park of Smart City - Based on the Concept of Smart Garden Design
Authors: Xie Ke
Published: August 2024

With the advancement of urbanization in China, there is a growing demand for intelligent landscape management in urban science and innovation parks. To improve landscape management efficiency in science and technology innovation parks, this study adjusted the Inception module and activation function of the GoogLeNet algorithm, designed an improved GoogLeNet algorithm, and based on this, constructed a multi clue science and technology innovation park landscape vegetation intelligent recognition system. This is also the main contribution of this study. The experimental results show that the average image recognition accuracy of the “Improve GoogLe Net+MM” model designed from the study is 92.95%, which is higher than all the comparison models. Additionally, the computation time is significantly lower than the comparison models when the computation data volume is larger. The model designed in this study has a certain application value to improve the performance of the landscape intelligent management system within smart cities’ science and technology parks.
Scalable and Distributed Mathematical Modeling Algorithm Design and Performance Evaluation in Heterogeneous Computing Clusters
Authors: Liu Zhouding , Li Jia
Published: August 2024

A growing number of scalable and distributed methods are required to effectively simulate complicated events as computing needs in the research and industrial sectors keep growing. A novel approach for developing and accessing mathematically modeled methods in heterogeneous computing clusters is proposed in this study to meet this difficulty. The suggested methodology uses DRL based Parallel Computational model for the evaluation of Heterogenous computing clusters. The algorithms makes use of parallelization methods to split up the processing burden among several nodes, supporting the variety of topologies seen in contemporary computing clusters. Through the utilization of heterogeneous hardware parts such as CPUs, GPUs, and acceleration devices, the architecture seeks to maximize speed and minimize resource usage. To evaluate the effectiveness of the proposed approach, a comprehensive performance assessment is conducted. The evaluation encompasses scalability analysis, benchmarking, and comparisons against traditional homogeneous computing setups. The research investigates the impact of algorithm design choices on the efficiency and speed achieved in diverse computing environments.
Application of Intelligent Analysis based on Engineering Management and Decision making for Economic Development of Regional Enterprise
Authors: Song Qianzhen , Yao Tong , Dai Yuhong
Published: August 2024

The convergence of advanced detection mechanisms, engineering management, and intelligence analysis presents a disruptive model for local companies pursuing economic growth. The paper presents a thorough strategy meant to improve regional processes for making decisions to promote long-term economic growth by utilizing modern technology. Using deep learning techniques, such as neural networks and deep neural architectures, to examine large datasets that are pertinent to local businesses. This makes data-driven decision-making easier and empowers stakeholders to choose wisely and strategically for the best possible economic results. incorporating management of engineering concepts to optimize resource allocation, improve operational efficiency, and streamline operations. To guarantee the successful implementation of economic development programs, management of projects, quality control, and methods for optimization must be applied. The research’s findings have great potential to further regional businesses’ goals for economic development. Through the integration of robust engineering management concepts and the analytical capacity of deep learning, this framework aims to equip decision-makers with the essential skills to navigate the intricacies of local economic environments, propel sustainable expansion, and promote equitable prosperity.
Blockchain-based E-commerce Marketing Strategy for Agricultural Supply Chain
Authors: Xu Yingzi , Yu Li
Published: August 2024

The application of blockchain technology into e-commerce marketing techniques within the agricultural supply chain is investigated in this study. Given the volatility and complexity of agricultural markets, creative techniques to ensuring the authenticity, traceability, and efficiency of these systems are urgently needed. Blockchain offers a decentralized and transparent approach, ensuring data integrity and building trust among stakeholders. We analyze the potential of blockchain to revolutionize e-commerce practices by enabling smart contracts, real-time data access, and immutable records, which can lead to cost savings, reduced fraud, and enhanced marketing capabilities. Through case studies and modeling, we demonstrate how blockchain can be leveraged to create a seamless farm-to-table journey, empowering farmers, distributors, and consumers. Our strategic framework provides actionable insights for practitioners to capitalize on blockchain’s capabilities, fostering sustainable growth in the agricultural sector. This study contributes to the literature by bridging the gap between blockchain technology and e-commerce marketing, offering a comprehensive strategy for the agricultural supply chain’s advancement.
Application of Artificial Intelligence Technology and Deep Learning in Laboratory Intelligent Management Platform
Authors: Lu Xing
Published: August 2024

In order to effectively utilize data for laboratory management, a laboratory management model was studied, the author proposed a data-driven intelligent laboratory management process and logical architecture. For actual management work, there are mainly two types of operations: ”Selection” and ”action”, the author proposes a data-driven laboratory intelligent management process and logical architecture; Based on the idea of big data, label systems are used to classify and store laboratory related data and laboratory evaluation GBDT and other algorithmic models; Building an intelligent laboratory management platform based on the label system has realized laboratory management functions, which are widely used and highly scalable. This data-driven laboratory intelligent management platform plays a role in the entire life cycle of laboratories, including laboratory demonstration construction, construction process management, experimental teaching and open use, operation management and maintenance, and experimental effect evaluation, and can promote the maximum effectiveness of laboratories, provide strong support for later construction project approval.
Research on Intelligent Building Integrated Cabling System Based on Internet of Things and Deep Learning
Authors: Zhou Rong
Published: August 2024

In order to solve the problem that the traditional integrated wiring system has many inconveniences in management, which affects the stability and efficient operation of the entire system, an intelligent building energy management control system in the Internet of Things era is proposed. In terms of hardware, design intelligent building switches, and in terms of software, plan the IP address of intelligent building wiring based on the Internet of Things, formulate comprehensive backbone wiring layout structure of intelligent building, set up auxiliary power distribution horizontal lines, and connect intelligent building wiring data, so as to realize intelligent building integrated wiring .On this basis, the architecture design of the wiring assistant design system is carried out, and the artificial intelligence building integrated wiring assistant system is realized with the help of the Net platform, and the system test is carried out. The experimental results show that the PM10 concentration parameters and the energy consumption simulation curve are highly consistent with the actual value curve. According to the calculation of the data volume points, the coincidence degrees can reach 96.4% and 98.9%, respectively. The experimental results show that the designed wiring system is superior to the traditional wiring system in terms of energy saving, and has certain reference value.
Optimization of E-commerce Product Recommendation Algorithm Based on User Behavior
Authors: Ji Yifan , Chen Lan , Xiong Rui
Published: August 2024

In order to implement personalized recommendation algorithms for e-commerce, the author proposes a genetic fuzzy algorithm based on user behavior to improve the sales, personalized recommendation, user satisfaction, and purchase matching performance of e-commerce. Collect data based on e-commerce personalized preference recommendation information, extract the associated feature quantities of personalized data for clustering processing, and then combine fuzzy B-means clustering method to achieve e-commerce personalized recommendation. According to the individual preferences of e-commerce, the collected data samples are fitted with differences and restructured, and a genetic evolution method is adopted for global optimization. The experimental results show that the optimized genetic fuzzy algorithm used in this method has improved stability and accuracy compared to the PSO method, with an  accuracy increase of 4%. This proves that the algorithm can provide the services needed by users more quickly and is an effective means.
Optimizing Task Scheduling: Exploring Advanced Machine Learning in Dew-Powered Cloud Environments
Authors: A Ganesh , Divya K Sree , Sasikala Chinthakunta , E Poornima , Nidamanuru Srinivasa Rao , A.V.L.N Sujith , Gajula Ramesh
Published: August 2024

Research into Dew computing environments has recently emerged as a result of the increasing prevalence and processing power of mobile and IoT devices. In these settings, even low-powered devices can share some of their computational resources with their neighbors. This paper proposes a novel approach to workflow scheduling in dew enabled cloud computing environment, called Deep Q-learning (DQN) + Chronological Geese Migration Optimization (CGMO). DQN is a deep learningbased method for scheduling workflows, while CGMO is a hybrid optimization algorithm that combines the chronological idea and the Wild Geese Migration Optimization (GMO) algorithm. The proposed approach aims to optimize multiple objectives, including predicted energy, Quality of Service (QoS), and resource usage, by scheduling workflows in the cloud. The approach also takes into account the current state of the Virtual Machine (VM) and the job. The assessment measures employed for DCGM include maximum QoS, minimum energy usage, and maximum resource utilization. The results show that DCGM achieved the highest QoS (0.865), lowest energy usage (0.0322), and highest resource utilization (1.000) compared to other approaches.
Secure Medical Image Retrieval Using Fast Image Processing Algorithms
Authors: Abdulsttar Lafta Sameer , Ghazi Hamad Rafash Amaal , Al-Falahi Noaman Ahmed Yaseen , Abdulqader Hussein Hussein , Mahdi abdulkareem Mohanad
Published: August 2024

Content Based Image Retrieval (CBIR) is a relatively new idea in the field of real-time image retrieval applications; it is a framework for retrieving pictures from diverse medical imaging sources using a variety of image-related attributes, such as color, texture, and form. Using both single and multiple input queries, CBIR processes semantic data or the same object for various class labels in the context of medical image retrieval. Due to the ambiguity of image search, optimizing the retrieval of a query picture by comparing it across numerous image sources may be problematic. The goal is to find a way to optimize the process by which requested images are retrieved from various storage locations. To effectively extract medical images, we propose a hybrid framework (consisting of deep convolution neural networks (DCNN) and the Pareto Optimization technique). In order to obtain medical pictures, a DCNN is trained on them, and then its properties and classification results are employed. Explore enhanced effective medical picture retrieval by using a Pareto optimization strategy to eliminate superfluous and dominant characteristics. When it comes to retrieving images by query from various picture archives, our method outperforms more conventional methods. Use the jargon of machine learning to propose a Novel Unsupervised Label Indexing (NULI) strategy for retrieving picture labels. To enhance the effectiveness of picture retrieval, we characterize machine learning as a matrix convex optimization using a cluster rebased matrix representation. We describe an empirical investigation on many medical picture datasets, finding that the searchbased image annotation (SBIA) schema benefits from our suggested method. As a result, CT images of the lung region are explored in this study by constructing a content-based image retrieval system using various machine learning and Artificial Intelligence techniques. Real-world applications of medical imaging are becoming more significant. Medical research facilities acquire and archive a wide variety of medical pictures digitally.
The Application of Information Technology for Athlete Data Analysis and Automatic Generation of Training Plans
Authors: Yuan Shuli
Published: August 2024

In response to the demand for scientific training of sports athletes, the author combined data mining technology to study an improved sports training mode decision support evaluation system. In this regard, the author analyzed the characteristics of association rule algorithms and elaborated on their functions in data preprocessing, data mining, and pattern evaluation. Based on the software design of decision support systems, the characteristics of system operation were analyzed. At the same time, the author focused on explaining the data fusion processing of association rules in sports evaluation decision support systems, and proposed an improved Apriori algorithm output mode to improve the effectiveness of system evaluation. Compared with other algorithms such as Apriori, DC Apriori and Apriori, this algorithm has higher reliability. When the minimum confidence is increased, the advantage of prior information will gradually disappear, and the final result will be obtained. Experimental results show that this method can effectively provide support for sports training decision-making.
Image Recognition Technology Based on Deep Learning in Automation Control Systems
Authors: Wang Jingjing
Published: August 2024

In order to solve the problem of recognizing multiple product images, the author proposes the research of image recognition technology based on deep learning in automated control systems. Firstly, the FasterRCNN method is improved by proposing a non class specific FasterRCNN, which can be used for pre annotation of product images by training only on publicly available datasets. Due to the use of position correction networks, the pre annotation effect is more accurate than that of candidate region networks. Then, combining Grabcut with non class specific FasterRCNN, a sample enhancement method was proposed to synthesize a large number of training images containing multiple products and use them for model training. In addition, based on non class specific FasterRCNN, a re identification layer was proposed to improve detection accuracy. In the end, the recognition and positioning of multiple products achieved a recall rate of 93.8% and an accuracy of 96.3%.
Smart Fish Passage Design and Application of Hydroacoustic Communication Technology in Aquatic Ecosystem Restoration
Authors: Yue Chao , Zhu Mengen , Yang Lei , Li Lei
Published: August 2024

The demand for creative solutions to help migrate fish and conservation efforts grows as aquatic environments experience more and more pressure from humans and fragmentation of habitat. The utilization of hydroacoustic technology for communication in conjunction with smart fish pathway architecture is the main emphasis of this research to improve rehabilitation efforts for aquatic environments. Using sophisticated systems for tracking and regulation to improve migratory pathways, the study investigates cutting-edge solutions in engineering for fish passage. Real-time data capture and transmission are made possible by the application of hydroacoustic technology for communication, which means that fish populations and monitoring systems can effectively communicate. The creation of intelligent fish passage structures with actuators, sensors, and communications components is a major focus of the research. The best passage efficiency of these structures is ensured by their dynamic adaptation to fish behavior and variables in the environment. An essential interface for gathering information on behavior, evaluating migratory trends, and putting adaptive management plans into practice is hydroacoustic communications technology. In order to assess the efficacy of the hydroacoustic communication technology and smart fish passage design in a variety of aquatic habitats, a thorough field investigation is part of the suggested methodology. To evaluate the effect on migration of fish rates of achievement, species diversity, and general well-being of the ecosystem, field data will be studied.
Machine Learning based Tool Wear Prediction from Variability of Acoustic Sound Emission Signals
Authors: Krishnamoorthy N V , Joseph Vijay
Published: August 2024

A novel machine learning-based model is introduced in this research paper to forecast tool wear using acoustic emission (AE) signals. Adaptive boosting (AdaBoost) and a sophisticated feature engineering strategy are employed by the model to enhance the precision of its predictions. The proposed model, Machine Learning Tool Wear Prediction (MLTWP), analyzes AE signals generated during machining operations to distinguish between healthy and worn-out tool conditions with remarkable accuracy. The crux of our approach consists of meticulously eliminating and enhancing the temporal and spectral characteristics of the AE signals. We employ the Kolmogorov-Smirnov test to identify the most valuable classification features. We implemented AdaBoost with the objective of progressively enhancing a set of weak classifiers’ ability to identify instances that were incorrectly classified in previous iterations. Utilizing this method increases the model’s sensitivity to minute variations in tool wear conditions and its overall classification precision. The MLTWP model underwent extensive testing on a benchmark data set comprising 25,304 AE signal records from cutting mill tools, using a training tool split of 9,989 worn (positive) and 8,990 benign (negative) instances. The results of our experiments, validated through four-fold cross-validation, indicate that the MLTWP model exhibits superior performance compared to the existing Tool Wear Prediction using Acoustic Emission Signals (TWPAE) model. To provide greater specificity, the MLTWP exhibited the following metrics on average: precision (92.2%), specificity (91.38%), sensitivity (90.42%), accuracy (90.9%), and MCC (81.72%). The fact that these metrics exhibit significant improvement over those of the TWPAE model demonstrates that our method of feature engineering and adaptive boosting is effective at precisely predicting tool wear. This research not only advances the existing understanding of tool wear prediction but also establishes a robust framework for the implementation of machine learning in manufacturing predictive maintenance.
Research on Intelligent Agriculture Based on Artificial Intelligence and Embedded Perception Algorithms
Authors: Zhao Xinhuan , Zhang Fang , Gao Na
Published: August 2024

In order to solve the problems of weak collection link, limited data coverage and poor real-time for big data in agriculture, smart agriculture by implementing artificial intelligence and embedded sensing is proposed. The front-end perceptron and wireless gateway were designed. A steady-state data collection system was constructed according to the characteristics of intelligent agricultural information data. Combining various algorithms such as data unification and data recognition, intelligent perception calculation parameters were extracted. The adaptive steady-state sensing model was designed relying on deep learning technology in the field of artificial intelligence. The experimental results show that the RMSE value of the designed system in the study is 0.028, which meets the requirements of intelligent agricultural information data perception accuracy. It is concluded that agricultural big data is a collection of data involved in the process of agricultural production, transportation and marketing, and data collection is the most important part of it.
Data Collection and Analysis based on Sensor Technology in Sports Training
Authors: Shi Xianbin , Zou Huagang
Published: August 2024

In order to realize the automatic monitoring of physical fitness index in athletic training, a new method of automatic monitoring and identification is put forward in this paper.In this paper, a network structure model is designed to automatically monitor the physical fitness index in sports training based on IOT and WSN.THe collected a number of physical parameters in sports training, including heart rate, maximal oxygen absorption, respiration entropy, and load parameters. Then, by monitoring heart and lung function data, Cooper’s method was used to measure the maximal oxygen intake, and EQO2 was used as the training index.Then, the dynamic parameters of physical fitness index were extracted, and the change of gas metabolism and critical threshold were analyzed. This paper builds a system structure model to monitor the physical fitness index of physical training, and realizes the modular design of the system.The experiment results indicate that the system is not very different from the real one, and it can be used to automatically monitor the physical performance index in sports training.Practice has proved that the system has good stability and reliability, and is suitable for physical monitoring in the process of sports training.