bluuebunny/crossref_metadata_2025 huggingface dataset:
PSYCHOLOGICAL WELLBEING AND JOB SATISFACTION IN MIDDLE-AGED ADULTS
Authors:   Department of Psychology, and University of Karachi, Kamrani Farhan , Zia Asbah ,   DHA Suffa University, Mumtaz Saba ,   Indus Hospital Karachi
Published: February 2024

This study was an attempt to investigate the predictive relationship between psychological wellbeing, its 6 dimensions and job satisfaction in a purposive sample of 250 (125 male, 125 female) adults of ages between 35-45 years. The sample belonged to a number of professions (like doctors, teachers, bankers etc.). Psychological wellbeing scale (Ryff et al., 1995) and generic job satisfaction scale (Mcdonald et al., 1997) were administered on the sample. Pearson product moment correlation scores indicate that correlation between job satisfaction and psychological wellbeing was not significant. Also the correlations between various dimensions of psychological wellbeing and job satisfaction were not significant, except for environmental mastery that has a significant positive predictive relationship with psychological wellbeing. Keywords: Job satisfaction; Psychological wellbeing; Environmental Mastery.
MEASURING THE LEVEL OF PSYCHOLOGICAL DISTRESS AND ITS IMPACT ON QUALITY OF LIFE AMONG INFERTILE WOMEN IN SOUTH PUNJAB, PAKISTAN
Authors:   Department of Applied Psychology, Islamia University, Bahawalpur, Sultana Sarwat , Nadeem Masood ,   Department of Applied Psychology, Islamia University, Bahawalpur
Published: February 2024

This research study was planned to check the level of psychological distress in relation with the infertility among women. This study also explored the impact of this psychological distress with the level of quality of life among women. In this connection, a sample of (N=284) was approached by using purposive sampling technique. To measure the variables two valid and reliable scales were administered and the collected responses were further analyzed by using SPSS. The results revealed that the infertile women were facing moderate level of psychological distress. Both the level of depression and anxiety were at moderate level among the infertile women. Similarly, the quality of life was lower among infertile women. The analysis also showed that the women with anxiety and depression scored lower quality of life scale. Furthermore, there was a significant correlation between psychological distress i.e. depression and anxiety with the level of quality of life among infertile women. On the basis of results, the study concluded that infertile women are suffering from anxiety and depression with lower level of quality of life. Hence, there is a dire need to address this issue and implement some interventions to reduce the level of psychological distress and uplift the quality of life of infertile women in south Punjab, Pakistan. Keywords: Anxiety, Depression, Infertility, Quality of life, Psychological distress.
DISTRESS TOLERANCE, MENTAL HEALTH PROBLEMS AND MARITAL SATISFACTION AMONG MARRIED COUPLES
Authors:   Department of Psychology GC Women University, Sialkot, Rauf Umara , Fatima Hamile ,   Department of Psychology GC Women University, Sialkot, Mushtaq Muazma ,   Department of Psychology GC Women University, Sialkot
Published: February 2024

Distress tolerance is known an ability to deal with unpleasant circumstances and maintain better mental health and congenial interpersonal relations. To explore the role of distress tolerance among married couples, current study focusses to investigate the relationship between distress tolerance, mental health problems and marital satisfaction among married couples. It was hypothesized that 1) Distress tolerance is likely to have a relationship with mental health problems among married couples. 2) Distress tolerance is likely to have relationship with marital satisfaction among married couples. 3) Mental health problems are likely to have a relationship with marital satisfaction among married couples. 4) Distress tolerance is likely to predict mental health problems and marital satisfaction among married couples. A convenient sample of 300 married couples (150 males, 150 females) was taken from different areas of Sialkot. A self-developed demographic sheet was administered along with Distress Tolerance Scale (Simons & Gaher, 2005), Depression, Anxiety, Stress Scale (DASS-21 by Lovibond, & Lovibond, 1995) and Relationship Assessment Scale (RAS by Hendrick, S.S, 1988). For data analysis, descriptive analysis, Pearson Product Moment Correlation Coefficient, and regression model was used. Results showed positive significant relationship between distress tolerance and mental health problems (r=.549**, **p<0.01), negative significant relationship between distress tolerance and marital satisfaction (r= -.437**, **p<0.01) and significant negative relationship was found between mental health problems and marital satisfaction among married couples (r= -.565**, p<.0.01). Further, regression analysis revealed that DT has potential to predict and bring 29% change in MHP, and 18% change in MS. It is also noted that B’s of MHP is positive which means that 1-unit change in DT brings 0.54-unit change in MHP. Further, B’s of MS is negative which shows that as DT increases by 1-unit then MS decreases by -0.43 times. Findings of the current study have implications for future avenues. Keywords: Distress Tolerance, Depression, Anxiety, Stress, Marital Satisfaction.
IDENTIFYING THE PSYCHOLOGICAL CORRELATES OF LOW ACADEMIC GRADES AMONG UNIVERSITY STUDENTS: SOCIO-ECONOMIC STATUS AS A MEDIATOR
Authors:   Government Sadiq College Women University, Bahawalpur Pakistan, Perveen Abida , Akhlaq Bisma ,   Department of Applied Psychology, IUB, Sajjad Sara ,   SSS (Education) QAED (W) Bahawalpur
Published: February 2024

Considering the psychological factors that significantly associated either positive or negative with student’s academic grades is vital to help the student’s success and persist in higher education. Therefore, this study was carried out to address the psychological correlates of low academic grades among university students. This study also highlighted the mediating role of socio-economic status in relation to psychological correlates (stress, anxiety, and depression) that affect the low level of academic outcomes among university students. For that purpose, a sample of (N=300) students belonging to diversified socio-economic status were selected by using an online G. Power sample calculator. The sample was chosen by using a convenient sampling method. In this study, the psychological correlates were level of stress, anxiety and depression that was measured by using DASS-42 item scale and the current CGPA was considered as student’s level of academic grade. Similarly, self reported socio-economic status was considered as a mediating variable in relation to stress, depression, and anxiety among students. The collected data was analyzed by using SPSS. The results of this study revealed that stress, anxiety, and depression were significantly correlated with the low level of academic grades among the students. The findings also showed that the level of socio-economic status of university students plays a significant mediating role in relation to stress, anxiety, and depression. Based on the results, the study suggested minimizing the level of stress, anxiety, and depression to improve the academic grades of the students. Keywords: Stress, Anxiety, Depression, Socio-Economic Status, Mediator.
ANALYZING ISABEL ALLENDE’S THE HOUSE OF SPIRIT: A DISCIPLINARY POWER
Authors:   Department of Linguistics the University of Haripur, Haripur Pakistan, Albaz Abdul Latif , Jamil Kashif ,   Department of Linguistics the University of Haripur, Haripur Pakistan, Waheed Manahil ,   Department of Linguistics the University of Haripur, Haripur Pakistan
Published: February 2024

This study discusses Isabel Allende’s The House of Spirit in relation to the notion of disciplinary power. The House of the Spirit explores the amalgamation of diverse social groupings and their collective pursuit of dominance. The novel's actions and motifs are influenced by a class system that is characterized by a division into two distinct groups. One group consists of the white, educated elite of European descent who hold positions of power in politics, business, and administration. This qualitative research employs Foucault’s notion of disciplinary power refers to a specific form of power used by those in positions of authority over their subordinates, with the aim of influencing and regulating their behavior according to their own desires. The study concludes that power moves from different institutions to daily life and affects with routine and pattern of life on large scales. It has also discovered that power is common issue and debate of daily life Latin America. There are number of events and incidents in Latin American society portrayed in the selected novel which are changed, molded and regularized on the basis of power. Keywords: disciplinary power, dominance, elites, authority.
Antibacterial Activity of the Combination of Calcium Hydroxide and Ellagic Acid towards Enterococcus faecalis and Lactobacillus acidophilus
Authors: Nirwana Intan , Meizarini Rr. Asti , Rachmadi Priyawan , Hary Agustantina Titien , Wan Huei Koh , Nisha Kumar Eshleen , Zhaffrano Razan Naufal
Published: February 2024

Calcium hydroxide is a material commonly used in pulp capping because of its substantial antibacterial property. However, this antibacterial property of calcium hydroxide is less effective on Enterococcus faecalis and Lactobacillus acidophilus due to their resistance factors. Ellagic acid is a natural phenolic acid with extraordinary antibacterial properties. Combining calcium hydroxide with ellagic acid is expected to enhance its antibacterial properties towards Enterococcus faecalis and Lactobacillus acidophilus. This study aimed to determine the antibacterial activity of the combination of ellagic acid and calcium hydroxide on Enterococcus faecalis and Lactobacillus acidophilus. A suspension of Enterococcus faecalis and Lactobacillus acidophilus bacteria comparable to a McFarland standard 0.5 of 1.5 x 108CFU/ml was made. Three different calcium hydroxide and ellagic acid ratios were made by mixing 0.099g, 0.097g, and 0.095g calcium hydroxide powder with 0.001g, 0.003g, and 0.005g ellagic acid powder, respectively. These powder mixtures were then added with 0.1 mL of sterile distilled water. Four Mueller Hinton Petri dishes were divided into four sections each. The mixtures of these powders were applied to the petri dish with the diffusion method. There are significant differences (p<0.05) between every group for Lactobacillus acidophilus. Similar results are also observed between all groups of Enterococcus faecalis except for group 5 (ratio 97:3) and group 6 (ratio 95:5). The combination of ellagic acid and calcium hydroxide decreases the zone of inhibition of Enterococcus faecalis and Lactobacillus acidophilus.
Gain curves and sex allocation: why the Shaw-Mohler equation works and when it doesn't
Authors: Burd Martin
Published: February 2024

Fitness gain curves were introduced into the framework of the Shaw-Mohler equation, the foundation of sex allocation theory. I return to this equation to consider how it embodies the rare-sex advantage underlying frequency-dependent selection on the sex ratio. The Shaw-Mohler formulation is based on the numbers of males and females randomly mating in a panmictic population. Gain curves were meant to describe reproductive success through male and female functions in hermaphrodites and were inserted in place of male and female numbers in the Shaw-Mohler equation. In doing so, gain curves bypass the implicit mating process in the Shaw-Mohler argument that creates frequency-dependent selection. Gain curves can then lead to anomalies like unequal total male and female fitness in a population. If gain curves truly represent fitness gain, they must have a population-level effect on both sexes, a basic necessity of sexual reproduction. The blurring of inputs with fitness outcome has lead to misinterpretation of what gain curves mean in reproductive ecology. They lack causal efficacy with respect to sex allocation. Because gain curves have been a staple of evolutionary ecology for decades, the implication is that much of our understanding of sexual allocation in hermaphrodites needs to be revisited. I outline some directions such an effort might take.
Jurisprudence on the likelihood of confusion of trademarks: focusing on the recent judgments of the Court of Justice of the European Union
Authors:   Institute of Legal Myungji Uiversity, Kim Jinyup
Published: February 2024

The essential function of trademark is to distinguish the goods and services of one undertaking from those of other undertakings. However, if likelihood of confusion between the two trademarks occurs, that could trigger damage to the proprietor of the earlier trademark while customers cannot purchase goods or services they want.
Accordingly, domestic courts in many jurisdictions have given verdicts on this important issue and particularly, the Court of Justice of the European Union (CJEU) also has handed over some relevant rulings. Therefore, this article would like to focus on judgments on the likelihood of confusion in the CJEU, analyzing main points and issues of the rulings. On that basis, this article aims to discuss controversial and important issues in those rulings.
Salmonelas isoladas de queijos tipo "coalho": Caracterização sorológica e resistência a agentes antimicrobianos - Recife (PE)
Authors: José de Sena Maria , M. O. P. Cerqueira Mônica , A. dos Santos Deise , Leocadio Filho Geraldo , Souza Dias Ricardo
Published: February 2024

Com o objetivo de isolar, identificar e avaliar a resistência antimicrobiana de linhagens de Salmonella, 107 amostras de queijo tipo"coalho" foram colhidas no período de janeiro a maio de 1997, no comércio varejista de Recife (PE). As amostras, obtidas de estabelecimentos comerciais que acondicionavam o produto em temperatura ambiente, variando entre 29,0 e 33,0°C eram transportadas em embalagens plásticas hermeticamente fechadas, sob refrigeração por via aérea até Belo Horizonte (MG) onde eram prontamente analisadas pelo Serviço de Microbiologia de Alimentos da Fundação Ezequiel Dias (FUNED). O isolamento e identificação de Salmonella foram realizados segundo metodologia preconizada por VANDERZANT & SPLITTSTOESSER (1992). Das amostras analisadas, 8,41 % (9/107) apresentaram-se positivas para Salmonella. Salmonella I (011:-:1,6; 018; 6,7:k:-; 3,1.O:y:-; 6,7:-:enz,s; 13,23:z:- ); Salmonella sp. Salmonella enteritidis foi identificada individualmente em 11,11% (1/9) das amostras. Apenas Salmonella enterica subsp I (6,7:-:enz15) apresentou frequência de 22,22% de positividade (2/9). As linhagens isoladas apresentaram resistência frente a 37,5% (6/16) dos produtos antimicrobianos testados: ampicilina, tetraciclina, cefotaxirna, sulfametropina, trimetoprin e sulfazotrim. A sensibilidade foi observada em 62,5% (10/16), frente aos seguintes antimicrobianos: ciprofloxacina, tobramicina, ceftazidima, amoxacilina, polimixina B, gentamicina, cloranfenicol, amicacina, ofloxacina e cefoxitina.
A survey of the occurrence of aflatoxins in groundnuts (peanuts) and groundnut products in São Paulo state, Brazil in 1994
Authors: Sabino Myrna , Ikejiri Inomata Emiko , Conceição Antonia Lamardo Leda , Valéria Milanez Thaís , Aparecida Navas Sandra , Ângela Pompeu Zorbetto Maria
Published: February 2024

Foram analisadas 321 amostras de amendoim e produtos de amendoim, comercializados no Estado de São Paulo, em 1994 e colhidos pela Vigilância Sanitária da Secretaria de Saúde do Estado de São Paulo quanto ao teor de aflatoxinas. Um total de 116 amostras ( 36%) mostraram níveis de aflatoxinas B1 + G1 acima do limite permitido pela legislação brasileira (30 ug.kg'). As amostras foram analisadas por cromatografia em camada delgada e o resultado, quantificado visualmente. As concentrações variaram de 5 a 2.440 ug.kg' e o 90 th percentil foi de 489 ug.kg'. °limite de quantificação do método é de 5 ug.kg'. Os dados confirmam a extensão e o nível de ocorrência de aflatoxinas em amendoim e produtos de amendoim em São Paulo e também mostra que este problema ainda existe, principalmente em condições de temperatura e umidade alta, clima predominante no Estado de São Paulo favorável ao crescimento de fungos toxigênicos.
Avaliação bacteriológica dos recursos hídricos do município de Eldorado - Vale do Ribeira (SP)
Authors: P. S. Valente José , A. M. Lopes Carlos , M. T. Caminhas Ana , Horácio Antonia
Published: February 2024

Foram coletadas 48 amostras de água provenientes de caixas d' água comunitárias, de torneiras localizadas em escolas e residências e de fontes, rios e poços, para a determinação do número mais provável de coliformes através do método dos tubos múltiplos. As amostras foram captadas em diferentes Bairros Rurais do Município de Eldorado pertencentes ao Parque Estadual Jacupiranga e apenas duas delas não demonstraram contaminação por coliformes. A densidade de coliformes nas amostras de água foi considerada elevada e associada à facilidade e rapidez com que a matéria de origem fecal humana e animal atinge os recursos hídricos, bem como a práticas agrícolas inadequadas, falta de mata ciliar, monocultura de banana nas montanhas e bordas dos rios, clima chuvoso, pobreza, baixa qualidade de vida e nível educacional da população.
Rezension von: Cucuel, Ernst u.a., Die Inschriften des badischen Main- und Taubergrundes ...
Authors: Wunder Gerd , Cucuel Ernst
Published: February 2024

Die deutschen Inschriften: Hrsg, von den vereinigten deutschen Akademien. Stuttgart: Druckenmüller.1. Bd. - Heidelberger Reihe -1. Bd.: Die Inschriften des badischen Main- und Taubergrunde Wertheim-Tauberbischofsheim. Ges. und bearb. von Ernst Cucuel und Hermann Eckert. 1969. 222 S., 136 Abb., 1 Karte.4. Bd. - Münchener Reihe - 2. Bd.: Die Inschriften der Stadt Wimpfen am Neckar. Ges. und bearb. von Fritz Viktor Arens. 1968. 120 S., 33 Abb.8. Bd. - Heidelberger Reihe - 5. Bd.: Die Inschriften der Landkreise Mosbach, Buchen, Miltenberg. Auf Grund der Vorarbeiten von Ernst Cucuel ges. von Heinrich Köllenberger. 1964. 287 S.13. Bd. - Münchener Reihe - 3. Bd.: Die Inschriften der Friedhöfe St. Johannis, St. Rochus und Wöhrd zu Nürnberg. Ges. undbearb. von Peter Zahn. 1972. 441 S., 138 Abb., 2 Karten.
Rezension von: Hepach, Wolf-Dieter, Ulm im Königreich Württemberg 1810-1848
Authors: Döring Walter , Hepach Wolf-Dieter
Published: February 2024

Wolf-Dieter Hepach: Ulm im Königreich Württemberg 1810-1848 (= Forschungen zur Geschichte der Stadt Ulm, hrsg. vom Stadtarchiv Ulm, 16). Ulm 1979. 223 S.
Rezension von: Specker, Hans Eugen (Hrsg.), Einstein und Ulm
Authors: Ulshöfer Kuno , Specker Hans Eugen
Published: February 2024

Hans Eugen Specker (Hrsg.): Einstein und Ulm (= Forschungen zur Geschichte der Stadt Ulm, hrsg. vom Stadtarchiv Ulm, Dokumentation 1). Ulm 1979. 135 S.
Rezension von: Fleischhauer, Werner, Barock im Herzogtum Württemberg
Authors: Mehl Heinrich , Fleischhauer Werner
Published: February 2024

Werner Fleischhauer: Barock im Herzogtum Württemberg. Hrsg, von derKommission für geschichtliche Landeskunde in Baden-Württemberg. 2. Aufl. Stuttgart: Kohlhammer 1981. 348 S., 120 Abb.
Durian Species Classification Using Deep Learning Method
Authors: Teo Boon Chen , Ting Huong Yong , Atanda Abdulwahab Funsho
Published: February 2024

Durian is a popular fruit in Southeast Asia, and the market offers various species of durians. Accurate species classification is crucial for quality control, grading, and marketing. However, the complexity of this task has led to the utilization of machine learning and deep learning methods. Traditional machine learning algorithms, such as K-Nearest Neighbors, Linear Discriminant Analysis, Support Vector Machines, and Random Forests, have demonstrated good accuracy, but they require extensive feature engineering. Deep learning algorithms, particularly Convolutional Neural Networks, can automatically extract features, making them less dependent on manual feature selection. This research aims to review deep learning classification algorithms, including Convolutional Neural Networks and Recurrent Neural Networks, to determine the most suitable algorithm for an efficient and accurate durian classification system. The objective is to enhance the precision and speed of durian species classification, presenting potential advantages for both durian producers and consumers. The literature review revealed that Convolutional Neural Networks outperformed other deep learning and traditional machine learning algorithms on datasets of varying sizes, achieving the highest accuracy of 98.96% through techniques like image resizing, color conversion, and additional parameters such as days harvested and dry weight. Deep learning emerges as a promising approach for robust and accurate durian species recognition, with future directions including developing models to classify durian species from different plant parts and even real-time video analysis. However, while Convolutional Neural Networks lead the way, a critical research gap exists in identifying optimal features, necessitating further investigation to refine durian species recognition accuracy.
Health Risk Assessment of Heavy metals, Physicochemical properties and Microbes in Groundwater near Igando Dumpsite in Lagos, Nigeria
Authors: Yahaya Tajudeen , Chidi Okeke , Abdulrahman Sani , Oladele Esther , Abdulrakib Abdulrahim  , Abdulganiyu Yunusa , Izuafa Abdulrazaq
Published: February 2024

The most common and cost-effective waste disposal method is the dumpsite; however, leachate from dumpsites may percolate and compromise groundwater sources. This study evaluated the levels of heavy metals (lead, cadmium, chromium, copper, and arsenic), physicochemical parameters (pH, electrical conductivity, total dissolved solids, hardness, calcium, magnesium, and chloride), and microorganisms in borehole water samples obtained at distances of 50, 100, 200, and 400 meters from the Igando dumpsite in Lagos, Nigeria. The health hazards associated with the heavy metals were also calculated. Physicochemical analysis indicated that the water samples were acidic, with pH values ranging from 4.30±0.01 to 5.21±0.008. They contained levels of calcium (166.73±0.01 - 328.66±0.06 mg/l), magnesium (83.72±0.02 - 119.40±0.17 mg/l), hardness (416.01±0.11 mg/l - 820.00±1.63 mg/l), and chloride (20.07±0.02 - 120.90±0.81 mg/l) that exceeded the limits set by the World Health Organization. Heavy metal analysis showed that, in all locations, lead exceeded the permissible limits, cadmium exceeded the limits except for the 400-m location, and copper, chromium, and arsenic (except for the 50-m location) were within permissible limits. The average daily intake and hazard quotient of the heavy metals were both within recommended limits, but the carcinogenic risks of lead, cadmium, and copper in water collected at a distance of ≤100m exceeded the threshold. Microbiological examinations revealed non-permissible levels of bacteria at all locations, coliforms at the 400-m location, and fungi at the 50-m and 400-m locations. On average, the parameters significantly (p<0.05) increased in concentrations as the proximity to the dumpsite decreased. These findings indicate that borehole water is not suitable for drinking without treatment.
commonmeta-py now supports metadata lists
Authors: Fenner Martin
Published: February 2024

This week the commonmeta-py Python library adds an important new feature: metadata lists. With this feature commonmeta-py no longer only operates on metadata for a single scholarly work (e.g. a journal article, book, dataset, software, or blog post), but can handle lists of scholarly works.
Research on Voiceprint Recognition based on Densenet
Authors: Tang Yongkang , Sun Xiangguo
Published: February 2024

To date, most methods for voiceprint recognition are implemented based on convolutional neural networks. In order to combine the spatial features and temporal features of sound and improve computational efficiency, a combined model of DenseNet169 and Bidirectional Gated Recurrent Unit (BiGRU), named DenseNet169-BiGRU, is proposed. Firstly, deep separable convolution is employed to reduce the number of network parameters and enhance computational efficiency. The speech FBank feature map is extracted after preprocessing, and experimental results show that the DenseNet169-BiGRU model outperforms both DenseNet169 and DenseNet169-GRU models, with an improvement in accuracy rate of 2.7% compared to DenseNet169, and an improvement of 1.1% compared to Densenet-GRU. This validates the effectiveness of the proposed method in both improving computational efficiency and achieving good performance.
Difference and Integration of Chinese Traditional and Modern Management Thoughts
Authors: Li Yizheng , Chaiwattanaporn Salinee , Gerdruang Atiporn
Published: February 2024

Chinese culture has undergone its development and evolution of five thousand years, leaving people with valuable ideological inside information. However, influenced by western culture, the contemporary world has gradually shown a trend of modern management, which is quite different from the cultural philosophy and management thought involved in Chinese tradition.  Therefore, this paper studies the differences between Chinese traditional and modern management thoughts, and proposes the relevant integration methods of taking the essence and discarding the dross, seeking the golden mean in competition and cooperation, promoting the integration of rule of virtue and rule of law, regulating the relationship between interests, righteousness and benefits, and advocating people first.
Research on Simulation and Optimization of Regional Express Cabinet Modeling based on Flexsim
Authors: Zhan Kaixia , Yan Qinghong , Chen Wei
Published: February 2024

In order to solve the problems of intelligent express cabinet quantity distribution and unreasonable grid configuration at the end of express delivery, improve customer satisfaction, and coordinate the investment cost and profitability of enterprises. Using the Flexsim software to simulate the distribution mode of regional express cabinets, set relevant parameters, analyze the utilization rate of intelligent express cabinets and the utilization rate of express cabinets, optimize the number of intelligent express cabinets and the configuration of the number of lattices, and enhance the corporate brand image.
On Credit Dilemma of Witkey Sites and Countermeasures
Authors: Wang Qiangchun
Published: February 2024

Since the concept of witkey was put forward for the first time in 2005, the witkey sites have developed rapidly; at the same time, they faced severe dilemmas of the credit system in three aspects: task publisher, task submitter, and the credit of witkey sites. As integrity is essential to the sustainable development of witkey sites, it will significantly benefit their development. Accordingly, it is urgent to find out the solutions to the problems.
The Study on Recognition and Detection of Express Package Grabbing Based on Machine Vision
Authors: Qi Weixiang , Sun Xiangguo
Published: February 2024

This research addresses the automated supply of parcels in logistics by employing a robotic arm to replace manual intervention. The process involves the suction-based retrieval of disorderedly stacked parcels and their placement onto a conveyor belt, presenting an economically significant engineering challenge. This paper designs a visual recognition system to assist the robotic arm in identifying the grasping surface of disorderedly stacked parcels. Leveraging transfer learning, a pre-trained model constructs a multimodal network framework. Pre-trained models of ResNet 169, DenseNet121, ResNet101, and ResNet50 serve as backbone networks to train and test on custom parcel datasets. Post comparative testing of model performance, DenseNet169 is chosen to construct the visual recognition network. Specifically, the RGB and Depth data of parcels are separately fed into DenseNet169 for feature extraction. Post-feature extraction, multimodal fusion is applied, integrating a lightweight attention mechanism, CBAM, to enhance semantic segmentation accuracy. Subsequently, post-processing of image features filters out the background, achieving precise identification of the parcel grasping region. Ultimately, the constructed network achieves an average TOP1 true class accuracy of 95.86% on the test set. Thus, the designed parcel visual recognition system based on this methodology exhibits robustness, meeting the demand for autonomous parcel retrieval by the robotic arm. It offers significant support towards resolving challenges in automated parcel supply within logistics.
Legal Risks and Responses to Artificial Intelligence Technology from the Perspective of Sociology of Technology
Authors: Jiang Linhan
Published: February 2024

Due to the wide application of Artificial Intelligence (AI), it is reconstructing the rules, behavior, and the way of organization and operation in the economy and society. However, AI has also brought many potential risks while promoting high-quality economic growth and achieving effective social governance. AI has powerful intelligent thinking and behavioral decision-making ability. Therefore, there would be huge risks once safety problems related to AI occur. Although all countries are aware of the necessity of strengthening the regulation of AI, the regulatory system and governance concepts in practice are still not sophisticated enough to cope with the rapid progress of AI technology. In this paper, from the perspective of the sociology of technology, we analyze the development boundaries and legal limits of AI technology, and further explore the governance of science and technology ethics, aiming to build an AI that meets human expectations and promotes human well-being.
Research on Collaborative Evaluation of Offshore Wind Power Value Chain in Guangxi-Based on BWM-FVIKOR Model
Authors: Wei Qiushuang , Yang Shuting , Lu Yunying
Published: February 2024

With the dynamic development of the offshore wind power industry and the global value chain, the traditional wind power industry is gradually turning to the offshore wind power value chain system that focuses on the value effect of the value chain, and it is of great significance to carry out value chain collaborative evaluation research. This paper puts forward the evaluation index system of Guangxi offshore wind power value chain from the comprehensive system dimension, key node dimension, subject contribution dimension and resource endowment dimension, builds the BWM-FVIKOR evaluation model, and proves the validity of the evaluation index and the feasibility of the evaluation model through example analysis, and this paper provides scientific and effective decision-making basis for the coordination of Guangxi offshore wind power value chain.
Research on Intelligent Logistics Application based on Blockchain Technology
Authors: Qin Yucheng , Jiang Tengfei , Xie Mei'e
Published: February 2024

With the rapid development of information technology, intelligent logistics has become the development trend of modern logistics industry. As an innovative technology, b aerznm nzn lockchain technology has the characteristics of decentralization, data tamperability and high security, which provides new opportunities for the development of intelligent logistics. This paper first introduces the basic principles and characteristics of blockchain technology, and then analyzes the application scenarios of blockchain technology in intelligent logistics, including logistics tracking, supply chain management and so on. Then, it discusses the key technologies of building intelligent logistics platform based on blockchain technology, such as consensus mechanism. Finally, the advantages and challenges of intelligent logistics application based on blockchain technology are summarized, and the future development trend is prospected.
Flexible Job-shop Scheduling Optimization based on Improved Gray Wolf Algorithm
Authors: Xu Minghong
Published: February 2024

This article proposed an improved gray wolf optimizer to deal with the flexible job-shop scheduling problem. By using a random key for coding job positions and adopting a local search strategy, we achieve group reconstruction and updating with the help of three good fitness values of the population, hence continuously searching for the optimal solution. Simulation experiments were conducted on a standardized test case, demonstrating the effectiveness of this method.
Research on Collaborative Training Mechanism of Prefabricated Construction Talents in Higher Vocational Colleges under the Background of Integration of Production and Education
Authors: Wu Qingling
Published: February 2024

With the rapid development of the construction industry, prefabricated building, as a new building mode, has significant advantages such as high efficiency, environmental protection and sustainability. However, the promotion and development of this new building mode needs a large number of high-quality technical skills as support. Based on the integration of production and education, this paper discusses the cooperative training mechanism of prefabricated construction talents in higher vocational colleges, in order to provide useful reference for improving the quality of talent training.
McDonald's food target recognition and calorie display based on YOLOv5 algorithm
Authors: Zhang Yuhao
Published: February 2024

This research paper delves into the development and assessment of a novel food recognition and evaluation system tailored for McDonald's menu items, leveraging the capabilities of the YOLOv5 algorithm. The study demonstrates that the system can successfully identify McDonald's food items from images and seamlessly query calorie and nutritional information from a backend database. The data is then presented to the user, aiding in more informed dietary choices and promoting public health awareness. The system has particular utility for McDonald's customers, facilitating real-time decisions that align with individual health goals and nutritional requirements. Our experimental findings show a high degree of accuracy and efficiency, although the system's scope is currently limited to five key menu items. Future directions for this work include expanding the range of recognizable food categories and implementing user feedback mechanisms to refine recognition accuracy. Moreover, the paper discusses potential optimizations for reducing system response time and further enhancing the practical utility of the technology. This research serves as a significant step towards utilizing computer vision technologies for public health interventions, aiming to combat the rise of obesity and related diseases.
Research on autonomous mobile robot maze navigation problem based on Dijkstras algorithm
Authors: Wu Qihan
Published: February 2024

In recent years, the field of autonomous mobile robotics has garnered significant attention due to its potential applications in various domains such as logistics, surveillance, and search and rescue operations. A crucial challenge in this area is the efficient navigation of robots within complex and dynamic environments, particularly when navigating through maze-like structures. The maze navigation problem involves finding optimal paths for robots to traverse from their initial positions to designated destinations while avoiding obstacles and making intelligent decisions to ensure timely and safe navigation. This study aims to investigate and apply Dijkstras algorithm to solve the maze navigation problem for autonomous mobile robots. By analyzing the navigation challenges faced by autonomous mobile robots in maze environments, a solution based on Dijkstras algorithm is proposed. In conclusion, this study contributes to the field of autonomous mobile robotics by proposing and evaluating the application of Dijkstras algorithm for maze navigation. The experimental results validate its potential to address the challenges of navigating intricate maze environments. However, it is acknowledged that further refinement and innovation are possible to continue improving the performance of autonomous mobile robots in maze navigation scenarios.
Exploring multiple algorithms for leaf classification: A comparative study
Authors: Pan Haoyang
Published: February 2024

In the world there are an estimated nearly half a million plant species, and the leaves of each plant have their own unique characteristics. However, leaf classification has historically been problematic, with some similar-looking leaves being repeatedly identified and errors may even occur. In the past, people used precision instruments, chemical analysis, and other methods to improve the success rate of resolution, but this often required a certain amount of professional knowledge, sometimes it was trouble to operate. And the development of computer in recent years makes the leaf classification problem can be solved better through the image processing and machine learning technology. Therefore, the topic of this paper is to classify leaves by different algorithms and compare the classification results, which include KNN, Random Forest, the neural network algorithm ANN, and CNN. It can be seen through experiments that the classification results obtained by ANN have a higher accuracy rate among these algorithms.
CNN-based image style transformation--Using VGG19
Authors: Xu Yihao
Published: February 2024

eural Style Transfer is a widely used approach in the field of computer vision, which aims to generate visual effects by integrating the information contained in one image into another. In this paper, this work presents an implementation of neural style transfer using TensorFlow and the VGG19 model. The proposed method involves loading and preprocessing the content and style images, extracting features from both images using the VGG19 model, and computing Gram matrices to capture the style information. A StyleContentModel class is introduced to encapsulate the style and content extraction process. The optimization process is performed using the Adam optimizer, where gradients are applied to iteratively update the generated image. The number of epochs and steps per epoch can be adjusted to control the optimization process and achieve desired results. Experiments show that we are effective in generating an image that is able to integrate the content of one image into the other. The generated images exhibit visually appealing characteristics and showcase the potential of neural style transfer as a creative tool in image synthesis. Future work may involve exploring different variations of the style transfer algorithm, optimizing hyperparameters, and evaluating the performance on a wider range of image datasets. Additionally, the integration of other deep learning architectures and techniques could further enhance the capabilities of neural style transfer.
Federated learning method for dynamic weight adjustment: An in-depth analysis of FedDyn algorithm
Authors: Cao Rongchuan
Published: February 2024

With the gradual enrichment of the application of deep learning in daily life, distributed machine learning has played a greater role in daily life, among which federated learning and its optimization algorithm FedDyn algorithm have begun to receive widespread attention. After introducing federated learning and traditional algorithms, this paper starts with the operation mode and framework of the FedDyn algorithm, takes the combination method of port selection strategy and global distribution as an example, analyzes the characteristics of some links in the operation process and uses the innovation points of the FedDyn algorithm : Dynamic weight adjustment is the entry point, which illustrates the advantages of the FedDyn algorithm in current use, and also points out some of the current problems. Finally, from the aspect of market application, the current application status of the algorithm is introduced from the aspects of personalized recommendation, medical treatment and finance, and the future development of the algorithm is prospected.
Application of machine learning to SRAM circuit design
Authors: Wang Haohan
Published: February 2024

This paper discusses the application of machine learning in Static Random Access Memory (SRAM) circuit design. It mentions several aspects of application analysis, including SRAM design for machine learning applications, SRAM PUF design for machine learning modelling attacks, lightweight fault-tolerant mechanism for NVDLA-based edge AI chips, interconnection resource allocation of SRAM FPGAs using reinforcement learning and Markov decision process, and SRAM power optimization and privacy security using machine learning. This article conclude that machine learning can be used to model and optimize SRAM performance, improve system reliability and stability through fault detection and fault tolerance mechanisms, provide a more comprehensive and efficient approach to testing and verification, and automatically correct and repair errors. The significance of machine learning in SRAM design is to provide an intelligent method and tool that can speed up the design process, improve system performance, increase reliability, and drive the advancement of chip manufacturing and processes.
Third generation semiconductor device research: Optimizing CMOS and HEMT designs
Authors: Chen Mengguo , Jing Chunhui , Mou Haoran
Published: February 2024

The third-generation semiconductor device known as High Electron Mobility Transistors (HEMT) has found extensive applications in high-frequency and high-speed electronic systems. Its widespread usage in critical technologies such as radio telescopes, satellite broadcast receivers, and cellular base stations has established HEMT as a foundational technology underpinning our information and communication society. This paper provides an in-depth exploration of these semiconductor advancements. Firstly, the paper utilizes the CMOS inverter as a representative example to elucidate the fundamental structure of Complementary Metal-Oxide-Semiconductor (CMOS) technology. Additionally, it employs Gallium Arsenide (GaAs) HEMT as an illustrative instance to expound upon the architecture of HEMT devices. Furthermore, the paper delves into the optimization of CMOS technology, focusing on topics such as Multi-Threshold CMOS and the impact of the Width/Length (W/L) ratio. These discussions shed light on ways to enhance the performance of CMOS-based components. Additionally, the paper explores strategies to optimize HEMT devices, including the introduction of carbon doping and the application of the Grey-Wolf optimization technique. These approaches are critical in achieving higher efficiency and performance in HEMT-based applications.
Application analysis of data mining in shopping APP
Authors: Shang Jiaqi
Published: February 2024

Dingdong Buying Vegetable is a cohort of emerging entities that have swiftly gained prominence within the business domain in recent times. The data mining function of its data platform APP is undeniably linked to the underlying factor contributing to its commercial success. This article examines the fundamental principles, practical manifestations, and pertinent research instances of data mining. It specifically centers on the primary interface of the Dingdong Buying Vegetable APP, scrutinizing its design and distinctive attributes tailored to specific customers. Furthermore, it conducts an in-depth analysis of the correlation between the platforms commercial success and its data mining functionality. The primary aspect in which the data mining function of the Dingdong Buying Vegetable APP is expected to be manifested is through extensive data mining. The process of mining client data and conducting a full comparison and analysis of sales data for all products sold is a highly intricate and exhaustive endeavor. The use of these data mining functions serves multiple purposes. Firstly, it efficiently identifies customers genuine requirements on the client side, enabling the recommendation of suitable products and fostering customer reliance on the application. Additionally, it facilitates accurate decision-making in marketing products on the product side by comparing and analyzing diverse data pertaining to the sold products. This approach helps prevent the sale of unsought items and effectively minimizes company expenditure.
Design of management database for Mihiyo company
Authors: Zhong Zihao
Published: February 2024

The mihoyo Sales Management System was developed to adjust to the dynamic business environment and maintain a competitive edge. In the context of this era, the mihoyo Sales Management System utilizes a robust database structure to optimize sales operations. In this paper, a management database for Mihiyo company is designed. The customer module stores customer information, linked to orders, payments, and expenses. An order table tracks order details, linked to customers and products. Payment and shipment tables manage transaction and delivery information. The inventory table enables real-time monitoring of stock levels. Financial management tables record sales, payment, and expense data. User tables store information related to different user roles. The system's interface seamlessly interacts with the database, allowing users to access and update information efficiently. The reporting and analytics module analyzes data from the database, facilitating decision-making and performance evaluation. Database testing requires completing relevant test cases and achieving a robust system.
Driver body condition monitoring system based on human-computer interaction
Authors: Hou Zhenyang , Huang Yanqin , Tang Xinye
Published: February 2024

Tired driving is still a significant cause of traffic accidents, often causing huge economic losses to society.Therefore, how to avoid driver fatigue has become a meaningful problem. The purpose of this paper is to review and summarize various research methods of driver fatigue monitoring system at home and abroad, so as to reduce the probability of traffic accidents caused by fatigue driving. The main content of this paper is to review the existing fatigue driving monitoring technologies such as electrocardiogram (ECG), electroencephalogram (EEG), HRV, eye tracking system, CNN, facial state analysis, emotion recognition, 5G and brain wave recognition, and infer the fatigue level of drivers by using these technologies to extract various clues that usually represent the level of human vigilance. Assess cognitive load and identify emotional states to monitor tired driving. By discussing the advantages and disadvantages of various fatigue monitoring systems at home and abroad, this paper proposes an innovative method, which transforms the previous single-mode monitoring system into a multi-mode monitoring system, integrates multiple biosensors, extracts relevant features from the biosensor data and processes the data reasonably in order to understand the drivers physiological state more comprehensively. This method is expected to improve the accuracy of fatigue monitoring system.
The application of automated machine learning in Malaria classification
Authors: Zhou Zheng
Published: February 2024

As the majority of image classification tasks currently rely on intricate algorithms, crafting specific algorithms for image classification can be a complex and daunting endeavor. In this project, a method for the classification of malaria infected cells using automated machine learning technique is proposed, with the aim of using the Edge Impulse platform to demonstrate that automated machine learning can be used to achieve image classification. More specifically, the project uses the Edge Impulse platform and uses two different modules, Image with Transfer Learning and Image with Classification, and comparing the results of data. The test results were used to analyse the feasibility of the method. In short, the data set is trained and tested using two modules in the Edge Impulse platform, and if both modules achieve a satisfactory accuracy, it demonstrates the feasibility of automated machine learning techniques to image classification. Finally, through the test, the test results demonstrated that the two modules can reach almost 92% of the good accuracy, indicating that automated machine learning technology can be used to replace the algorithms to achieve image classification.