bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Intelligent Scheduling System for Wine Grape Agricultural Equipment Based on User Requirement
Authors: Huang Haoran , Hou Tianlong , Li Wen , Zhang Tao
Published: December 2022

User requirement analysis and agricultural machinery scheduling are of great significance to promote the mechanized development of wine grape industry. In order to improve the field intelligent scheduling efficiency of wine grape agricultural equipment, reduce the manual scheduling cost and waste of farm machinery resources, this paper analyses the requirements through literature analysis and field investigation, and then designs the business process and divides the functional structure based on the requirements. The intelligent scheduling system of agricultural equipment for wine grape is designed and implemented based on the user’s demand. According to the operation requirements of different farmers for different agricultural equipment, the order execution order is arranged as a whole, and a scheduling scheme of agricultural equipment is generated. After confirmation by the administrator, agricultural operators and farmers, scheduling starts, and the scheme is evaluated and fed back after scheduling. It can promote the informatization development of wine grape industry in Ningxia.
Gold or BTC: The Best Trading Strategy
Authors: Lyu Yiyang , Hu Kangnong , Xu Haonan , Zhang Biao
Published: December 2022

This paper focuses on the Trading strategy issues of gold, US dollar and bitcoin in the financial markets.We are supposed to deal with the C problem of 2022 Mathematical Contest In Modeling. To solve this problem, we firstly build a VMD(CEEMD)-LSTM-AdaBoost-SVM model to predict the price of gold and BTC. Based on the forecast data, we build the optimal investment dynamic planning problem by using Floyd algorithm to find the maximum profit route of daily optimal trading strategy from September 11, 2016 to September 11, 2021. Our assets went from an initial $1,000 to $52,048 with an annual profit margin of 219.58%. Then, we performed sensitivity analysis and error analysis of the developed model. Finally, we improved and extended the existing model by building the Measure-VaR multi-stage portfolio model and solve it by using the PSO algorithm, the theoretical results is good.
Facial Expression Recognition Based on Improved Residual Network
Authors: Hu Pengfei , Kang Qiao , Zeng Can , Dong Fangyan , Chen Kewei
Published: December 2022

Facial expression is the external expression of inner emotion, and is the main medium for analyzing emotion-guided sentiment, which has great research value. And for the problems of low accuracy and slow convergence of current models for face expression recognition. This paper proposed the ReSE face expression recognition model based on the residual network through the study of face expression recognition. The ReSE model is mainly constructed by ResNet18 and RE module, while using PReLU function instead of ReLU function, introducing Dropout function, and finally using island loss classification function. Through experimental validation, the average accuracy of the ReSE model for face expression recognition on the Fer2013 dataset is 1.33 percentage points higher than that of the VGG16 model; the average accuracy of the ReSE model for face expression recognition on the CK+ dataset is 1.36 percentage points higher than that of the ResNet18 model. Follow-up research needs to reduce the number of model parameters and further optimize the network structure for improving the accuracy of facial expression recognition.
Research on Optimization Model of Traffic Light Timing Based on Multi-Objective Programming—Take Jude Road, Haizhu District, Guangzhou City as an Example
Authors: Guo Kaichun , Li Zhiqiang , Liu Weiguo
Published: December 2022

This paper collects the data of a certain intersection of Jude Road in Guangzhou, and through the analysis of the survey data, it is proved that the traffic flow obeys the Poisson distribution. Combined with the characteristic that the arriving traffic volume obeys Poisson distribution, the relevant knowledge of traffic flow is used to analyze and study the intersection, and the Webster timing algorithm and the multi-objective optimal signal light timing algorithm are used to optimize the timing of the traffic lights at the intersection. This paper compares the optimization degree of the current status of the delay time, the number of stops, the traffic capacity, the average fuel consumption and carbon emission of each vehicle at the intersection under two different timing methods. Finally, a reasonable traffic light timing scheme is proposed for this intersection.
Core-Firm Financial Structure on Reverse Factoring with Machine Learning Models
Authors: Liang Zhuomin , Xie Tongtong , Yi Zelong
Published: December 2022

This study presents the most significant financial factors in reverse factoring decision based on accounts receivable. We compare 4 machine learning models (GBDT, SVM, random forest, and KNN) and find that GBDT outperforms the others. The results show that the primary factors in the financial structure of companies on successful reverse factoring are book leverage, company size, and non-debt tax shield, respectively. We also conduct interpretable machine learning methods to analyze these indicators further. This study may shed light on focal firms’ reverse factoring decisions in practice.
A Harmonic Contribution Evaluation Method Based on Dynamic Parameter Model of Harmonic Source
Authors: Liu Youwei , Xiao Yan , Xu Jing
Published: December 2022

The Norton model (NM) has been widely applied in the determination method of harmonic contribution, which cannot always precisely represent the harmonic source especially when the background voltage fluctuates, the accuracy is not satisfactory. To solve this problem, a new harmonic contribution determination method using the dynamic parameter model (DPM) was proposed. In this paper, the establishment of the DPM and the reason to use harmonic current to evaluate the contribution was briefly introduced. According to the expression of the DPM, a method to determine the specific contribution between the utility and customer side was proposed. Finally, a method to evaluate the correctness of the determination results was put forward and some simulated cases were developed to verify the accuracy. The simulation results show the proposed method can correctly distinguish the harmonic contribution on various occasions, the accuracy is much higher than the widely used superposition method.
Investigation on the Effect of Anti-Braking System on Nose Landing Gear Shimmy
Authors: Zhang Jiaxian , Tu Jiliang , Liu Hui , Zhang Shixue
Published: December 2022

The influence of anti-braking system on the shimmy region and oscillation characteristics of the nose landing gear is studied. The moment generated by the braking system is modeled as a function of the adhesion coefficient and the torsional oscillation speed, and it is incorporated into the landing gear oscillation non-linear dynamic model. The results of analysis show that the braking frequency is increased by 50%, the area of the lateral dominant shimmy region is increased by 6.9%, the area of the torsional dominant shimmy region is reduced by 18.8%, and the amplitude of the torsional oscillation is suppressed. The braking amplitude is increased by 22%, the area of lateral dominant shimmy region is decreased by 3.1%, and the area of torsional dominant shimmy region is increased by 15.5%.
Application of Score Algorithm in Astronomy
Authors: Cai Hongbing , Fang Hang , Tian Jiayi , Xu Jinsong
Published: December 2022

Since the seventeenth century, there have been many mathematicians to study the score algorithm. Until today, it is still a topic worth of studying. The theory of the fraction algorithm has an important role in mathematics, which is an important tool in the study of the number theory and linear equations. The fraction algorithm is associated with probability theory, progression recursion, function approximation, engineering technology, and computer science. The fraction algorithm has some classic applications, such as using the fraction algorithm to solve the indefinite form of first order equation, calculating the ancient calendar with the fraction algorithm, and using the score algorithm for password analysis. This paper mainly discusses the history, definition, nature, and specific applications of the fraction algorithm in astronomy. Although the systematic induction and arrangement about the concept of continued fraction is all from the West, the ancient Chinese scientists had grasped this mathematical method and already applied it to production practices such as calendar and solar terms. This article summarizes these astronomical achievements, and it also poses a look at the application of the continued fraction in modern society.
Simulation Analysis of Radio Frequency Heated Tobacco Based on COMSOL Multiphysics
Authors: Xu Yifei , Wu Chaoqun , Li Guchun , Nei Guangjun
Published: December 2022

With the further expansion and implementation of similar smoking bans around the world, research on heat-not-burn tobacco is considered to be one of the most important research areas for the transformation and upgrading of tobacco companies. At present, the working principles of the heat-not-burn tobacco heating equipment currently on the market or under research are mainly categorizeded into three types: carbon heating type, resistance heating type, and induction heating type. High-cost issue. Radiofrequency heating is a method of wireless energy transmission, which has the advantages of fast heating speed, high efficiency, non-contact, and so on, and has a wide application prospect in tobacco heating. However, the research and application of radiofrequency heating for tobacco heating is very limited at present. Therefore, it is significant to conduct related research on radiofrequency heating-not-burn tobacco. Based on the finite element simulation software COMSOL Multiphysics, this paper starts with the three-dimensional simulation model of bipolar plate RF heating tobacco and describes the simulation settings in detail. The solid heat transfer module simulates the heating results of the tobacco matrix from the transient and steady-state aspects, analyzes the simulation results, and obtains the temperature rise law of the tobacco matrix under different conditions, which provides a basis for subsequent equipment development. theoretical basis.
Design and Implementation of Embedded Face Recognition System
Authors: He Yuanzi
Published: December 2022

This paper introduces the design scheme of embedded face recognition system, and introduces the face detection and recognition algorithm of MTCNN and FaceNet. A simple face recognition system is implemented on the RK-3399 embedded platform by using the traditional face recognition database of OpenCV. The face detection test is carried out under the conditions of different lighting conditions, diverse postures and partial occlusion of the face, The results show that the embedded face recognition system based on ARM can run stably and normally with high recognition rate, and has a good application prospect.
Crime Prediction with Quantitative Information
Authors: Wang Zhiyuan , Zhang Chen , Hu Dingding
Published: December 2022

Aiming at the poor prediction effect in the crime prediction task, a crime prediction model incorporating quantitative information is proposed. According to the numerical basis of judicial sentencing, quantify the values in the text, use the self-attention mechanism and maximum pooling to highlight the weight of quantitative information and keywords, then use the bidirectional long and short memory cycle network to extract the joint features between quantitative information and keywords, and use the capsule network to extract the depth features; Due to the imbalance of data, a priori weight is used in the loss function to balance the data. Experiments show that this method has better prediction effect than other models.
Investigation of the Displacement Transfer Characteristic and Parameter Optimization Design of Fluid-Elastic Isolator
Authors: Li Zhenkun , Cheng Qiyou , Feng Qian , Liu Chen , Zhu Yan , Sun Fengnan
Published: December 2022

The main parameters influencing the displacement transfer rate of the fluid-elastic isolator are studied and optimized. Firstly, the equation of motion is derived by applying the Lagrange principle. The effects of the main design parameters on the displacement transfer rate of the fluid-elastic isolator are analyzed. Secondly, parameter optimization design is conducted by employing the genetic algorithm for a civil helicopter. by Aiming at the minimum displacement transfer rate, the optimal parameters are determined. Lastly, the criterion for parameter optimization design is proposed considering both the displacement transfer rate and the weight cost. Design parameters with a high vibration isolation rate and low weight are obtained. Results reveal that the vibration isolation behavior of a fluid-elastic vibration isolator depends on the coupling effects of multiple parameters. The parameters obtained by the genetic algorithm demonstrate a higher vibration isolation rate than the ordinary parameter design. Based on the optimization criterion, the fluid elastic isolator possesses a higher vibration isolation rate and lower weight cost than the experimental result in the literature. And it will be helpful for the parameter design of the fluid elastic isolator.
Study on Damage Mechanism of Fracturing Fluid Reservoir and RBF Neural Network Prediction
Authors: Chen Fei , Yan Chaohui , Zhou Bo
Published: December 2022

At present, tight oil and gas reservoirs must adopt fracturing technology to obtain productivity, which will not only transform the reservoir, but also bring reservoir damage. Taking Chang-7 member of Ordos Basin as the research object, the relationship between physical properties of tight oil reservoir and fracturing fluid damage is analyzed based on experimental analysis of reservoir physical properties, cast thin sections, electron microscope scanning, X-ray diffraction and sensitivity test. Using the traditional damage evaluation method requires a large number of cores, and core resources, as a nonrenewable precious resource, have been paid more and more attention. Therefore, the use of prediction is conducive to protecting core resources, reducing experimental costs, and improving work efficiency. Therefore, a mathematical prediction model of RBF neural network is proposed, which establishes the complex nonlinear relationship between the physical properties of Chang 7 reservoir and fracturing fluid damage in Ordos Basin. Taking 22 groups of data of Chang 7 reservoir as training data, the fitting rate of training data is 90%. Taking the other two groups of data as detection data, the error between prediction and actual experiment is less than 10%. The prediction shows that the error inside and outside the sample predicted by RBF neural network is small, the prediction accuracy of the model is high, the generalization ability is strong, and the prediction value is closer to the value obtained by laboratory experiments than BP neural network, which can provide a good theoretical basis for fracturing fluid optimization.
Research on Curve Lane Detection Method Based on Deep Learning
Authors: Ding Wenfei , Sun Huinan , Ma Dezhong
Published: December 2022

Curve Lane detection is an indispensable part of auto-sensing technology, and plays a key role in auto-driving. The traditional curve lane detection methods are based on Hough transform and YOLOv5 Algorithm. Based on Hough transform method, the detection effect is not ideal when the lane line is discontinuous and short, that is, the dotted line is prone to detection errors. Yolov5 Algorithm is not effective for continuous lane detection or long lane detection. In this paper, deep learning based on the combination of Hough transform and Yolov5 Algorithm is studied, which can effectively detect the solid line and dotted line, and can accurately detect the curve. The experimental results show that the curvature radius has a good detection effect in the case of large or small curvature radius, which is of great significance for reducing the probability of traffic accidents on the curve section.
Analysis of Food Sampling Data Based on CARMA Algorithm
Authors: Jiao Yongchun , Jiang Tongqiang , Liu Tianqi , Dong Wei , Yang Qi , Zhang Qingchuan
Published: December 2022

At present, China’s food sampling inspection work has the problems of large workload and high cost. In this paper, we try to extract some valuable association rules from the national sampling data by analyzing them. Based on the data of spices major category in the 2019 national sampling database, this paper applies CARMA algorithm to mine association rules for the data studied in terms of food categories (sub-categories), sampling provinces, testing sites, contaminant categories, and relative risk levels of contaminants, and eight relatively valuable and effective strong association rules are obtained after the experiment, and some of them are interpreted. The results show that through association rule mining of relevant sampling data, the connection existing between some key and non-key testing objects and some unqualified items can be determined, which in turn can provide some reference for the allocation of resources for sampling work.
Research on Deadline Division and Scheduling of Batch Scientific Workflow in Cloud Environment
Authors: Zhao Qing , Feng Kuo , Shi Yancui , Zhang Chengkui , Sun Le , Zhang Mengxiang
Published: December 2022

Data intensive batch processing scientific workflow is a typical application model in the era of big data. A reasonable scheduling method can improve the resource utilization rate and reduce the rental cost on the premise of meeting the deadline requirements. In this paper, an iterative floating interval allocation method suitable for batch scientific workflow is proposed in the deadline allocation stage, and then in the resource mapping stage, a task scheduling algorithm considering the utilization of time gaps and minimizing the cost of renting virtual machines is proposed, which weighted the expected utilization of time slices. Experiments show that compared with similar scheduling algorithms, in the specified deadline time, it can not only better solve the data transmission bottleneck, but also better improve the execution efficiency and reduce the total rental cost.
Hopf Bifurcation, Chaos and Bursting in a Generalized Logistic Model with Time Delays
Authors: Li Shunyi , Wan Xiaoli , Xiong Mei
Published: December 2022

A generalized Logistic system with two delays is investigated, and the conditions for the positive equilibrium occurring local Hopf bifurcation are obtained. Numerical results show that delayed system considered have complicated dynamic behaviours, such as period oscillation, doubling-bifurcations, chaos and Hopf bursting.
Application of Immersion Virtual Reality System in Assistant Decision Making of Hydropower Station Maintenance
Authors: Kong Jihong , Huang Kun , Lv Yisong , Luo Xi , Shi Tao , He Man
Published: December 2022

In order to solve the problems of difficulty, time-consuming, and high energy in the establishment of maintenance methods for power station turbines, this paper proposes a method based on immersive virtual reality system to build a virtual environment that is completely consistent with real hydropower plant equipment and facilities, using virtual reality technology With the characteristics of immersive high-level simulation and the advantages of unlimited time and unlimited space, virtual simulation maintenance preview can quickly provide auxiliary decision-making basis for the maintenance of real hydro-turbine generator sets, so as to shorten the maintenance period and improve the quality of maintenance. Taking a power plant equipment emergency repair and maintenance plan as a case, the validity and correctness of this article are demonstrated.
Malaysia Traffic Signs Classification and Recognition Using CNN Method
Authors: Chew Yingxin , Zulkoffli Zuliani , Chu Yihing , Ilyas Mohammad Arif , Khan M.K.A. Ahamed , Ang Chun Kit , Hong Limwei
Published: December 2022

Automatic Traffic Sign Detection and Recognition (ATDR) system has been expanded and implemented partly in Intelligent Transportation System (ITS) that is actively used today. As traffic congestion increases, the manufacturing industry may have made and installed the ATDR systems in various types of vehicles, including cars, light commercial vehicles, and heavy trucks that act as driver assistance systems. ATDR system not only helps to minimize the number of traffic accidents but also supports road users through legal and compliant guidance and providing all traffic information, so that road users can be more attentive and solve them immediately in a short duration of time. On the point of the safety of the road users and others will be protected throughout a critical situation with identify the driving scene. In this paper, a deep-architectural neural networks, which is the convolutional neural network (CNN/ConvNet) model are chosen to expand in the ATDR system. With its excellent ability to train, research, and organize data, CNN is becoming one of the most widely used machine learning algorithms in key tasks such as prediction and classification. First, various open source of deep learning libraries will be studied. The library has been tested using the Malaysian Traffic Sign (MTS) dataset, which contains 32891 labelled images with real-world signs. Then the combination of both designed detection model and the CNN classification model will be trained under some parameter settings. Finally, the proposed system will detect and recognize the different types of traffic sign images in real-time display and Graphical User Interface (GUI). The achievable test accuracy is exceeded by 98% on a total of 43 different classes of MTS data that is obtained and for all study cases.
Building a “Blockchain+” Short Video Push System
Authors: Lin Ruoyang , Zhang Yiping , Lin Xingzhi
Published: December 2022

The “blockchain+” short video push system is an important field worthy of study in the current short video platforms. Blockchain technology is used to effectively promote the processing speed of short video platforms for user portraits and strengthen the intelligent audit of short video contents according to its unique characteristics, such as decentralized and multi-node. In this paper, we will discuss the data processing, calculation management and application methods of short video push system based on blockchain technology, to elicit the new development of short video push system.
Research on the Prediction of Traffic Accident Severity Based on BP Neural Network
Authors: Wang Xuelian , Zhang Ziwen , Li Hui , Wei Xing , Chen Junhao , Ding Maozhen , Mu Qianwen
Published: December 2022

A traffic accident severity prediction study is an estimation of the expected future traffic accidents in combination with available data. One of the core objectives of this study is to predict the number and severity of possible traffic accidents so that optimal solutions can be taken in case of accidents. In this study, we propose a research method for traffic accident severity prediction based on BP neural network. Firstly, we perform principal component analysis on accident causative factors to determine the input and output factors of BP neural network; then we analyze the principle of neural network based on the composition structure, operation mechanism and learning method of BP neural network model. In the experimental part, a traffic accident dataset of Guangzhou city from 2009 to 2016 is used as an example sample for validation and the prediction results are analyzed. The results show that the prediction value of the model is accurate between 87%-91% compared with the true value, and the prediction accuracy is high, which can effectively predict the severity of traffic accidents and has certain theoretical guidance and practical significance for the prediction of the severity of future road traffic accidents.
Implementing a Theory of a Legal Domain
Authors: Bench-Capon Trevor , Gordon Thomas F.
Published: December 2022

We describe a system for constructing, evaluating and visualising arguments based on a theory of a legal domain, developed using the Angelic methodology and the Carneades argumentation system. The visualisation can be used to explain particular cases and to refine and maintain the theory. A full implementation of the well known US Trade Secrets Domain is used to illustrate the process.
An Automata-Based Formalism for Normative Documents with Real-Time
Authors: Chircop Stefan , Pace Gordon J. , Schneider Gerardo
Published: December 2022

Deontic logics have long been the tool of choice for the formal analysis of normative texts. While various such logics have been proposed many deal with time in a qualitative sense, i.e., reason about the ordering but not timing of events, it was only in the past few years that real-time deontic logics have been developed to reason about time quantitatively. In this paper we present timed contract automata, an automata-based deontic modelling approach complementing these logics with a more operational view of such normative clauses and providing a computational model more amenable to automated analysis and monitoring.
Recognising Legal Characteristics of the Judgments of the European Court of Justice: Difficult but Not Impossible
Authors: Contini Alessandro , Piccolo Sebastiano , Lopez Zurita Lucia , Sadl Urska
Published: December 2022

Machine learning has improved significantly during the past decades. Computers perform remarkably in formerly difficult tasks. This article reports the preliminary results on the prediction of two characteristics of judgments of the European Court of Justice, which require the knowledge of concepts and doctrines of European Union law and judicial decision-making: The legal importance (doctrinal outcome) and leeway to the national courts and legislators (deference). The analysis relies on 1704 manually labelled judgments and trains a set of classifiers based on word embedding, LSTM, and convolutional neural networks. While all classifiers exceed simple baselines, the overall performance is weak. This suggests first, that the models learn meaningful representations of the judgments. Second, machine learning encounters significant challenges in the legal domain. These arise doe to the small training data, significant class imbalance, and the characteristics of the variables requiring external knowledge. The article also outlines directions for future research.
Transfer Learning for Deontic Rule Classification: The Case Study of the GDPR
Authors: Liga Davide , Palmirani Monica
Published: December 2022

This work focuses on the automatic classification of deontic sentences. It presents a novel Machine Learning approach which combines the power of Transfer Learning with the information provided by two famous LegalXML formats. In particular, different BERT-like neural architectures have been fine-tuned on the down-stream task of classifying rules from the European General Data Protection Regulation (GDPR) encoded in Akoma Ntoso and LegalRuleML. This work shows that fine-tuned language models can leverage the information provided in LegalXML documents to achieve automatic classification of deontic sentences and rules.
An Argumentation and Ontology Based Legal Support System for AI Vehicle Design
Authors: Lu Yiwei , Yu Zhe , Lin Yuhui , Schafer Burkhard , Ireland Andrew , Urquhart Lachlan
Published: December 2022

As AI products continue to evolve, increasingly legal problems are emerging for the engineers that design them. Current laws are often ambiguous, inconsistent or undefined when it comes to technologies that make use of AI. Engineers would benefit from decision support tools that provide engineer’s with legal advice and guidance on their design decisions. This research aims at exploring a new representation of legal ontology by importing argumentation theory and constructing a trustworthy legal decision system. While the ideas are generally applicable to AI products, our initial focus has been on Autonomous Vehicles (AVs).
Features of Cerebral Small Vessel Disease Contributes to the Differential Diagnosis of Alzheimer’s Disease
Authors: Cheng Zhao-Zhao , Gao Feng , Lv Xin-Yi , Wang Qiong , Wu Yan , Sun Bao-Liang , Shen Yong
Published: December 2022

Background: Cerebral small vessel disease (CSVD), which comprises the typical features of white matter hyperintensity (WMH) and Vichor-Robin spaces (VRSs) in the brain, is one of the leading causes of aging-related cognitive decline and, ultimately, contributes to the occurrence of dementia, including Alzheimer’s disease (AD). Objective: To investigate whether CSVD imaging markers modify the pathological processes of AD and whether these markers improve AD diagnosis. Methods: 208 participants were enrolled in the China Aging and Neurodegenerative Initiative (CANDI). Fluid AD biomarkers were detected using a single-molecule array, and cerebral small vessel dysfunction was determined using magnetic resonance imaging. Results: WMH contributed to AD pathology only within the NC and MCI groups (CDR ≤0.5), whereas VRSs had no effect on AD pathology. The associations between AD biomarkers and cognitive mental status were consistent with the presence of CSVD pathology. That is, within individuals without CSVD pathology, the MMSE scores were correlated with AD fluid biomarkers, except for plasma Aβ42 and Aβ40. Increased plasma p-Tau levels were associated with worse cognitive performance in individuals with WMH (β= –0.465, p = 0.0016) or VRSs (β= –0.352, p = 0.0257) pathology. Plasma AD biomarkers combined with CSVD markers showed high accuracy in diagnosing dementia. Conclusion: Findings from this cross-sectional cohort study support the notion that CSVD is a risk factor for dementia and highlights that vascular pathology can promote AD biomarker levels, especially in the early course of the disease. Moreover, our results suggest that adding a vascular category to the ATN framework improves the diagnostic accuracy of AD.
Hierarchical Two-Stage Cost-Sensitive Clinical Decision Support System for Screening Prodromal Alzheimer’s Disease and Related Dementias
Authors: Kleiman Michael J. ,   for the Alzheimer’s Disease Neuroimaging Initiative, Ariko Taylor , Galvin James E.
Published: December 2022

Background: The detection of subtle cognitive impairment in a clinical setting is difficult. Because time is a key factor in small clinics and research sites, the brief cognitive assessments that are relied upon often misclassify patients with very mild impairment as normal. Objective: In this study, we seek to identify a parsimonious screening tool in one stage, followed by additional assessments in an optional second stage if additional specificity is desired, tested using a machine learning algorithm capable of being integrated into a clinical decision support system. Methods: The best primary stage incorporated measures of short-term memory, executive and visuospatial functioning, and self-reported memory and daily living questions, with a total time of 5 minutes. The best secondary stage incorporated a measure of neurobiology as well as additional cognitive assessment and brief informant report questionnaires, totaling 30 minutes including delayed recall. Combined performance was evaluated using 25 sets of models, trained on 1,181 ADNI participants and tested on 127 patients from a memory clinic. Results: The 5-minute primary stage was highly sensitive (96.5%) but lacked specificity (34.1%), with an AUC of 87.5% and diagnostic odds ratio of 14.3. The optional secondary stage increased specificity to 58.6%, resulting in an overall AUC of 89.7% using the best model combination of logistic regression and gradient-boosted machine. Conclusion: The primary stage is brief and effective at screening, with the optional two-stage technique further increasing specificity. The hierarchical two-stage technique exhibited similar accuracy but with reduced costs compared to the more common single-stage paradigm.
Accelerator based epithermal neutron source for clinical boron neutron capture therapy
Authors: Hu Naonori , Tanaka Hiroki , Akita Kazuhiko , Kakino Ryo , Aihara Teruhito , Nihei Keiji , Ono Koji
Published: December 2022

The world’s first accelerator based epithermal neutron source for clinical boron neutron capture therapy (BNCT) was designed, developed, and commissioned between 2008 and 2010 by Sumitomo Heavy Industries in collaboration with Kyoto University at the Kyoto University Institute for Integrated Radiation and Nuclear Science. The accelerator system is cyclotron-based and accelerates a proton up to an energy of approximately 30 MeV. The proton strikes a beryllium target, which produces fast neutrons that traverse a beam shaping assembly composed of a combination of lead, iron, aluminum, and calcium fluoride to reduce the neutron energy down to the epithermal range (∼10 keV) suitable for BNCT. The system is designed to produce an epithermal neutron flux of up to 1.4 × 10 9 n · cm − 2 · s − 1 (exiting from the moderator of a 12 cm diameter collimator) with a proton current of 1 mA. In 2017, the same type of accelerator was installed at the Kansai BNCT Medical Center and in March 2020 the system received medical device approval in Japan (Sumitomo Heavy Industries, NeuCure® BNCT system). Soon after, BNCT for unresectable, locally advanced, and recurrent carcinoma of the head and neck region was approved by the Japanese government for reimbursement covered by the national health insurance system.
revista íntima no sistema prisional brasileiro
Authors: Ribeiro Dávila Ferreira , Maia Gretha Leite
Published: December 2022

O presente artigo tem como objetivo analisar os argumentos trazidos em julgamento, com sede no STF, quanto à constitucionalidade da revista íntima. Para tanto, foram sistematizadas as normas federais e estaduais que regulamentam a revista íntima em cotejo com as restrições de direitos fundamentais acarretadas por esse método de inspeção, especialmente em afronte à dignidade da pessoa humana, à proibição da tortura, à intranscendência da pena e à assistência familiar ao preso. Foram analisadas as posições em disputa no ARE nº 959.620/RS no STF e os fundamentos do voto do ministro relator. Concluiu-se que os materiais apreendidos na realização de revista íntima constituem meio ilícito de prova no processo penal e que não há relação de proporcionalidade entre o argumento da promoção de segurança e ordem pública para defender a constitucionalidade do procedimento diante da constatação de restrição a tantos direitos fundamentais.
Participatory budgeting for public involvement in environmental sustainability at a Thai university
Authors: Watson Todd Richard
Published: December 2022

Participatory democracy where the public influences and feels involved in policy making is an ideal in democratic societies. In this paper, principles of participatory democracy are implemented at a Thai university through participatory budgeting focusing on environmental sustainability projects. On a general education course, students generated and proposed projects for environmental sustainability at the university. All university members were invited to vote on which projects should be actually implemented within the constraints of a limited budget. The study focuses on the public’s bases for selecting projects to implement and their reactions to being invited to take part in participatory budgeting. A corpus-informed analysis of the public’s responses shows that participants engaged in thoughtful community-oriented consideration of the projects and were overwhelmingly positive about their involvement. These findings suggest that participatory budgeting is a valuable tool for raising awareness of and promoting involvement in environmental sustainability.
ŞAMANİST DÖNEMDEN KALMA ORTAK ANILARDAN GÜLBANKLAR VE AK BATALAR
Authors: BAYRAK İŞCANOĞLU İlknur
Published: December 2022

Anadolu ve Kırgızistan; ortak tarihe sahip olmanın verdiği ortak inanışı, ortak kültürü, olaylara ortak bakışı ve olayları ortak algılayışı halk kültürüne dair pek çok uygulamada ve inanışta devam ettirmiştir. Bu ortaklıklar aradan pek çok zaman geçse dahi aynı anlayışla sürdürülmüş ve bugün şaşırtıcı derecede benzerliklerin olduğu uygulamalarda ve inanışlarda kendini göstermiştir. Geçmişteki ortak tarih, kültür ve yaşam zaman içerisinde coğrafyaların değişmesiyle birlikte yerini ortak anılara bırakmıştır. Bu çalışmanın ana konusunu oluşturan kalabalık bir grup eşliğinde ve törensel mahiyette edilen dua, Anadolu ve Kırgız halkında görülen benzerliklerdendir. Özellikle Anadolu’da ve Kırgızistan’da insan hayatında geçiş dönemlerinin önemli görülmesi ve bu dönemlerin dualarla kutsanması, duaların törensel bir uygulama ile kalabalık halk eşliğinde ve toplumca saygın, yaşça büyük kişiler tarafından edilmesi gibi benzer özellikler dua ve dua etme ile ilgili ortaklıklardan bazılarıdır. Bu çalışmada en eski Türk inanışlarından Şamanizm, atalar kültü ve tabiat kültlerinin etrafında şekillenmiş, Şamanizm’deki Şaman dualarından bugünlere ulaşan Anadolu Alevi inanışındaki gülbanklar ile Kırgızistan’daki hayır duası anlamına gelen ak batalar; köken, konu ve işlevsellik açısından karşılaştırılmıştır. Böylece bir zamanlar ortak yaşamanın sonucu olan ortak anılardan dua ve törensel dua etme geleneğinin hem uygulama hem de söyleyişte anımsanarak farklı coğrafyalarda nasıl ve ne şekilde devam ettirildiği benzer ve farklı yönleriyle açıklanmaya çalışılmıştır.
Türkiye’de Çuvaşlara Yönelen İlgi: Zakir Kadirî Ugan’ın Çuvaşlarla İlgili Değerlendirmeleri Üzerine
Authors: YAVUZ Cemalettin
Published: December 2022

Türkiye’de Çuvaşlar dâhil olmak üzere Türkiye dışındaki Türklere dönük ilgi, Cumhuriyet sonrasında artmaya başlamıştır. İdil-Ural bölgesinden gelen aydınlar bu konuda önemli katkılar sağlamıştır. Bu aydınlardan biri olan Zakir Kadirî Ugan, 1925 yılında Türk Yurdu dergisinde doğrudan Çuvaşları konu edinen bir makale kaleme almıştır. Söz konusu bu kısa makale Çuvaşların kökeni, dili ve kültürü hakkındaki tartışmaların ve kaynakların Türkiye’de tanıtılması açısından tarihî bir öneme sahiptir. Bu çalışmada öncelikli olarak Zakir Kadirî Ugan’ın Rusya’daki ve Türkiye’deki faaliyetlerinden kısaca bahsedilmiştir. Ardından Ugan’ın söz konusu makalesinin amacı, yöntemi, kaynakları ve Çuvaş kültürüyle ilgili sunduğu bilgiler analiz edilmiş; konuya yaklaşım biçimi, vardığı sonuçların kendi dönemi bağlamında önemi ve ne anlama geldiği sorgulanmıştır. Söz konusu çalışma, Çuvaş dili ve kültürüyle ilgilenen bazı önemli araştırmacıları ve çalışmalarını Türkiye’de tanıtmış olması açısından önemlidir. Ancak Çuvaşların kökeniyle ilgili varılan yargı, yazarın İdil-Ural Türkleri arasındaki siyasi çekişmelerin etkisini açık bir şekilde yansıtmaktadır. Ugan’ın Çuvaş folkloruyla ilgili aktardığı bilgiler ise doğru olmakla birlikte temellendirilmemiş ve yanlış bağlamda yorumlanmıştır.
KIRGIZİSTAN’DA DİN-DEVLET İLİŞKİLERİ VE LAİKLİK TARTIŞMALARI
Authors: JOLDOSHOV Altynbek
Published: December 2022

Kırgızistan’da bağımsızlığından itibaren diğer Orta Asya Cumhuriyetlerinden daha farklı bir siyasal ve toplumsal dönüşüm süreci yaşanmıştır. Bu sürecin yansıması dini alanda da görülmektedir. Kırgızistan’daki dini alan gün geçtikçe farklılaşmakta, çeşitlenmekte ve dinamik bir süreci yansıtmaktadır. Böylece farklılaşan ve çeşitlenen dinamik süreç Kırgızistan’da din-devlet ilişkilerine de yansımaktadır. Diğer Orta Asya Cumhuriyetlerinden farklı olarak Kırgızistan’da devlet daha ziyade “pasif laiklik” anlayışını sürdürmeye yönelmektedir. Bu çalışmada öncelikle “sekülerlik” ve “laiklik” kavramları üzerindeki tartışmalar analiz edilecek; daha sonra günümüz devletlerinin din-devlet ilişkileri değerlendirilerek, laik devletlerin uyguladığı laiklik anlayışları ele alınacaktır. Ardından post-Sovyet Orta Asya Cumhuriyetlerinin siyasal rejimleri laiklik bağlamında incelenecek ve Kırgızistan’ın dini alandaki farklılıkları vurgulanacaktır. Son olarak Kırgızistan’da din-devlet ilişkileri analiz edilecek ve bu bağlamda Kırgızistan’daki laiklik tartışmaları değerlendirilecektir.
Şota Rustaveli'nin “Kaplan Postlu Şövalye” adlı eserinin Doğu rönesansına ait olması ve Türk folkloruna dayanılarak oluşturulması hakkında
Authors: ŞERİFOVA Salide
Published: December 2022

Doğu Rönesansı'nın bir ürünü olan Şota Rustaveli'nin kimliği ve yaratıcılığı konusundaki tartışmaların ve onun Gürcü şairi olarak sunulmasının Azerbaycan bilimi ile ilgisi olmadığı gerçeğiyle karşı karşıyayız.

Şota Rustaveli'nin faaliyetinin 12. yüzyıla kadar uzandığı iddia ediliyor. Bu dönemde Türk dilinin kısaca kıpçagofilliyin kalıtsal bir gelenek olarak Gürcü saraylarında tezahürü, bilimde sözünü söyleyebilen araştırmacılar tarafından vurgulanmıştır.

Şota Rustaveli'nin “Kaplan Postlu Şövalye” adlı eserine birçok millet tarafından sahip çıkılmaya çalışıldığı tarihi bir gerçektir. Menimseme süreci en çok Gürcü ve Fars edebiyatında belirgindir. Hem Gürcü hem de yabancı araştırmacılar, eserin zorla sahiplenilmesi için yüzyıllar boyunca değişikliklere tabi tutulduğunu vurgulamaktadır. Araştırmacılar, eserdeki değişikliklerin sadece işin kısaltılmasında değil, esere eklemeler yapılmasında da karşımıza çıktığını özellikle vurgulamaktadır.

Şota Rustaveli'nin yazdığı şiir romanın hangi gelenek üzerine yaratıldığı veya oluşturulabileceği sorusunu gündeme getirir. Gürcü edebiyatında Şota Rustaveli'ye kadar herhangi bir edebiyat ekolü oluşturmayan bir edebiyatın bu kadar mükemmel bir örnek oluşturabilmesi, o eserin yazıldığı döneme dikkat çeker. 12-13. yüzyıl Doğu edebiyatında şiirler, manzum romanlar vb. türler yaygın olarak gelişmiştir ve bu dönemde Doğu Rönesansının ortaya çıkması, Şota Rustaveli'nin yaratıcılığına ve kişiliğine dikkat çeker. Doğu Rönesansı Gürcü edebiyatını içermez. Doğu Rönesansı, Kafkasya'da yaşayan halklar arasında Azerbaycan Türklerinin edebi ortamını, Farsça veya Arapça edebiyatını içerir ve Gürcü ve diğer halkların edebiyat ve kültürü Doğu Rönesansı'nın dışındadır.

Şota Rustaveli'nin “Kaplan Postlu Şövalye” adlı eserinde Türk insanının hayatında özel bir yeri olan gelenekler, milli bayramlar vb. anlatılmaktadır. gerçekleşiyor. Mesela eserde Nevruz bayramından söz edilmesi... Şunu da belirtmeliyiz ki eser "kesildikten" sonra hala Nevruz bayramıyla ilgili bölümler vardır. Evren, halklar, milletler, gelenekler, dinler vb. Nevruz bayramı hakkında derinlemesine bilgi sahibi olan Şota Rustaveli, eserinde Nevruz bayramının özelliklerini bilen bir kişi olarak açıklık getirir.

Şota Rustaveli'nin “Kaplan Postlu Şövalye”, Orta Çağ'da Kafkasya'da birleşik bir edebi ortamın olduğunu gösterir. Bu ortamda yazan ve yaratan halklar, Türk halklarının edebiyatı çerçevesinde şekillenmiştir. Kafkasya'nın Türk olmayan halklarının edebiyatı, yalnızca folklorun gelişimi ve İslam'ın yokluğunda dini nitelikteki eserler ile ilgilidir. Dini türlerin de kendi sistemleri vardı. Şota Rustaveli gibi edeblerin eserlerini edebiyat ve kültür açısından incelemek önemlidir. Çünkü bu, Kafkasya'da yaşayan halkların edebiyat ve kültür tahrifatını ortaya koyması açısından önemlidir.
A Consumer’s Perspective of the Clover Tropika Brand: Building Brand Extensions by Leveraging the Parent Brand’s Reputation
Authors: Madlala Phethokuhle , Chivandi Abigail , Maziriri Eugine Tafadzwa
Published: December 2022

The primary objective of the study was to investigate how brand extensions can leverage on the parent brand image in order to achieve a positive brand extension perception. This was investigated in accordance with specific brand building constructs. The study focused on a consumers’ perspective of the Clover Tropika brand within emerging economic areas. The research was based on a quantitative approach which adopted convenience sampling at Mall intercepts. A total sample of 238 consumers responded to a self-administered questionnaire at Southgate and Maponya Mall which are located in the south west of Johannesburg. All respondents were above the age of 18 and consented to participate in the research by willingly placing their completed questionnaires in the box provided on the day. The data techniques used included Structural Equation Modelling (SEM) which had a core focus on Confirmatory Factor Analysis (CFA) which assisted in confirming the relationships proposed in the conceptual model. SEM also focused on path modelling to determine the causal relations. Nine out of the ten hypotheses proposed had a significant level of p<0.001 proving support for the proposed hypotheses. The research found that there is a significant relationship between brand awareness and brand attitudes, as this hypothesis had the highest path coefficient score. After the research was conducted. It was noted that high recall and recognition of the parent brand, accompanied by favorable attitudes, are key factors in leveraging on the parent brand image to build brand extensions. Moreover, brand extensions need to have high perceived fit in order to leverage extensively on the parent brand image.
Pengaruh EIemen PerikIanan Media SosiaI Terhadap Brand Engagement dan Purchase Intention
Authors: Polii Georgia Cathleen Engeline
Published: December 2022

Tujuan dari riset ini iaIah untuk mengetahui faktor-faktor yang memengaruhi pemasaran media sosiaI terhadap keterIibatan merek dan niat beIi merek makanan cepat saji. Kuesioner dibagikan kepada 208 responden sebagai sampeI. DaIam riset ini, metode pengambiIan sampeI menggunakan non-probabiIity sampIing dan menggunakan teknik purposive sampIing. Metode anaIisa data yang dipakai iaIah StructuraI Equation ModeIing (SEM), SPSS dan software AMOS22. HasiI riset menunjukkan variabIe interaktif berdampak positif terhadap Brand Engagement. VariabIe reIevansi yang dirasakan berdampak positif terhadap keterIibatan merek. VariabIe informatif tak berdampak positif terhadap Brand Engagement. Hiburan tak berdampak positif terhadap niat beIi. VariabIe keterIibatan merek berdampak positif terhadap niat beIi.
Penilaian Kinerja Tenaga Harian Lepas Dengan Key Performance Indicators Pada Terminal Cipocok Jaya Kota Serang
Authors: Sulistyo Arif Budi , Setiadi Mochamad , Gautama Pugy
Published: December 2022

Pencapaian retribusi dari Organisasi Perangkat Daerah yang dinaungi oleh Dinas Perhubungan salah satunya dari sektor terminal tidak mencapai target berakibat pemasukan terhadap Pendapatan Anggaran Daerah berkurang yang disebabkan oleh kinerja pegawai. Penelitian ini bertujuan untuk menghitung dan juga mengevaluasi sekaligus memberikan solusi agar target retribusi terminal dapat tercapai. Alternatif untuk mengevaluasi kinerja pegawai adalah dengan Key Performance Indicators. Berdasarkan 5 kriteria penilaian meliputi penjualan karcis, jumlah angkutan masuk terminal, mematuhi perintah atasan, keberlangsungan kegiatan, dan keluhan pelanggan tertangani menghasilkan nilai 41,93. Menurut range penilaian, nilai tersebut dikategorikan rendah sehingga dilakukan analisa menggunakan tools yang terdapat pada seven tools. Hasil yang didapat disebabkan oleh SDM rendah, Kualitas terminal yang buruk, Koordinasi yang kurang baik, dan lain – lain, solusinya adalah membuat Critical  to Quality dan Critical to Process Tree agar dapat diidentifikasi keinginan customer internal dan eksternal dan menambah beberapa proses baru agar dapat meningkatkan semua sektor yang berkaitan dengan kinerja pegawai.