bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Tindak Tutur Lokusi dalam Konten YouTuber Jerome Polin
Authors: Hasanah Niswatun , Nurjanah Ulfiatun Dwi , Utomo Asep Purwo Yudi
Published: August 2023

Abstrak:Analisis ini bertujuan untuk mendeskripsikan tindak tutur, yaitu tindak tutur lokusi dalam konten Jerome Polin. Metode yang digunakan dalam analisis ini adalah deskriptif kualitatif. Sumber data yang digunakan adalah video-video yang diunggah oleh Jerome Polin dalam channel YouTubenya. Pengumpulan data dilakukan dengan cara menonton video-video Jerome Polin, kemudian mencatat hal-hal penting untuk dianalisis. Hasil analisis ini menunjukkan bahwa Jerome Polin sering menggunakan tindak tutur lokusi dalam kontennya. Tindak tutur lokusi merupakan tindak tutur yang disampaikan untuk mengatakan sesuatu. Dari hasil analisis terdapat 30 data berupa tindak tutur lokusi. Tindak tutur tersebut masuk ke dalam dua kategori yakni tindak tutur lokusi kategori berita dan tindak tutur lokusi kategori tanya. 14 tindak tutur lokusi kategori berita dan 16 tindak tutur lokusi kategori tanya. Dengan adanya penelitian ini, diharapkan pembaca mampu memahami mengenai tindak tutur lokusi. Penulis berharap penelitian ini dapat membawa manfaat bagi pembaca dan penulis lain sebagai sumber referensi mengenai tindak tutur lokusi.Abstract:  This analysis aims to describe speech acts, namely locutionary speech acts in Jerome Polin's content. The method used in this analysis is descriptive qualitative. The data sources used are videos uploaded by Jerome Polin on his YouTube channel. Data collection was done by watching Jerome Polin's videos, then recording important things for analysis. The results of this analysis indicate that Jerome Polin often uses locutionary speech acts in his content. Locutionary speech acts are speech acts that are conveyed to say something. From the results of the analysis there are 30 data in the form of locutionary speech acts. These speech acts fall into two categories, namely locutionary speech acts in the news category and locutionary speech acts in the question category. 14 locutionary speech acts in news category and 16 locutionary speech acts in question category. With this research, it is hoped that the reader will be able to understand the locutionary speech act. The author hopes that this research can bring benefits to readers and other writers as a reference source regarding locutionary speech acts.
Kajian Penggunaan Waktu Menonton Tayangan Layar Kaca Terhadap Disiplin Belajar Siswa di Rumah
Authors: Winata Aliahardi , Yunus Muhamad , Muttaqin Zedi
Published: August 2023

Abstrak: Tayangan layar kaca tidak bisa dipungkiri memberikan efek yang cukup besar dalam kehidupan masyarakat, baik itu secara positif maupun negative. Salah satu efek negative yang ditimbulkan oeh yayangan layar kaca ini adalah dapat menyita waktu keseharian masyarakat khususnya siswa yaitu disiplin belajar mereka. Televisi dan video gem sebagai media layar kaca yang paling disukai, sebagai factor penyebab siswa menjadi malas dalam belajar dan mengerjakan tugas-tugas sekolah. Berdasarkan isi pokok masalah dapat dirumuskan bagaimana penggunaan waktu menonton tayangan layar kaca terhadap disiplin belajar siswa dirumah yan kemudian di spesifikan lagi untuk mencari jumlah waktu yang digunakan, waktu penggunaaan ,tempat penggunaan baru kemudian dicari hubungannya dengan disiplin belajar siswa tersebut Pendekatan dalam penelitian ini menggunakan penelitian kualitatif dengan jenis penelitian deskriptif. Hasil penelitian ini menemukan bahwa jumlah waktu yang digunakan oleh siswa dalam menonton layar kaca rata-rata selama 4-5 jam dalam sehari anak laki-laki dan anak SMA lebih banyak menonton dari pada anak SMP dan anak perempuan. Sedangkan waktu yang digunakan untuk menonton lebih sering pada malam hari dari pada siang atau sore harinya. Tempat untuk menonton televisi juga lebih banyak dirumah daripada diluar rumah, tetapi untuk bermain video game lebih sering diluar rumah. Berasarkan jumlah, waktu dan tempat tersebut ditemukan bahwa sebanyak 80% siswa lebih banyak menggunakan waktunya untuk menonton tanyangan layar kaca daripada belajar dirumah. Abstract: It is undeniable that glass screen shows have a considerable effect on people's lives, both positively and negatively. One of the negative effects caused by the glass screen foundation is that it can take up people's daily time, especially students, namely their learning discipline. Television and video gems are the most preferred screen media, as factors that cause students to be lazy in studying and doing school assignments. Based on the main content of the problem, it can be formulated how the use of screen time watching television shows on students' learning discipline at home which is then specified again to find the amount of time used, the time of use, the place of use and then look for the relationship with the student's learning discipline. The approach in this study uses research qualitative with descriptive research type. The results of this study found that the average amount of time spent by students watching television for 4-5 hours a day, boys and high school students watched more than junior high school students and girls. While the time spent watching more often at night than in the afternoon or evening. There are also more places to watch television at home than outside, but to play video games more often outside the home. Based on the number, time and place, it was found that 80% of students spent more time watching television than studying at home.
Analisis Pengaruh Pendidikan dan Pelatihan Terhadap Kinerja Perangkat Desa pada Desa Pemepek
Authors: Yunus Muhamad , Haeri Zul , Suryanirmala Neni
Published: August 2023

This study aims to analyze the effect of education and training on the performance of village officials. This research was held in Pemepek Village, Pringgarata District, Central Lombok Regency. The sampling technique used in this study is Saturated Sampling. The sample in this study was employees of the Village Apparatus, which totaled 30 respondents. This research is a quantitative research and data analysis model using multiple linear regression. The results of this study show that partially in education and training research the calculated F value was obtained 9,061 while the F value of the table was 3.35, it can be known that the F value is calculated 9,061 > the F value of the table 3.35 with a significant level of 0.001 because the significant level < 0.05, then this regression model can be used for performance variables at the pekpek village office, in other words, it can be said that the variables of education and training together (simultaneously) have an effect on  significant to performance.
Analisis Teks Iklan Rokok A Mild : Kajian Semiologi Roland Barthes
Authors: Syakur Ahmad Abdan , Purnawarman Purnawarman
Published: August 2023

Abstrak: Peneltian ini bertujuan untuk: 1) menemukan penanda (signifier) dan petanda (signified) yang terdapat pada iklan rokok A Mild. 2) Memahami makna simbol iklan rokok  A Mild menurut kajian semiologi Roland Barthes. Data dalam penelitian ini adalah teks iklan rokok A Mild. Metode pengumpulan data yang digunakakan adalah studi pustaka kemudian dianalisis secara deskriptif. Adapun hasil penelitian menunjukan bahwa terdapat penanda (signifier),  petanda (signified) dan Mitos dalam Iklan Rokok A Mild yang digambarkan melalui konsep-konsep tentang gaya, kesenangan, dan percaya diri. Di dalam tataran mitos, yakni sistem semiologis lapis kedua, penanda berupa “gaya” ini merujuk pada petanda berupa aktualisasi diri: kesenangan, kenikmatan, percaya diri, dan keberanian. Dalam tataran inilah kemudian peneliti melihat bahwa konsep aktualisasi diri berupa: kesenangan, kenikmatan, percaya diri, dan keberanian menjadi mitos dari kenyataan hidup. Analogi inilah yang ditemukan peneliti hadir dalam iklan rokok A Mild berdasarkan kajian semiologi Roland BarthesAbstract: This research aims to: 1) find signifiers and signifiers contained in A Mild cigarette advertisements. 2) Understand the meaning of the A Mild cigarette advertising symbol according to Roland Barthes' semiological studies. The data in this study is the text of A Mild cigarette advertisements. The data collection method used is a literature study and then analyzed descriptively. The results showed that there are signifiers, signifieds and myths in A Mild cigarette advertisements that are described through concepts about style, fun, and confidence. In the mythical level, the second-layer semiological system, these markers of "style" refer to signs of self-actualization: pleasure, enjoyment, confidence, and courage. It is at this level that researchers then see that the concept of self-actualization in the form of: pleasure, enjoyment, confidence, and courage becomes a myth of the reality of life. This analogy is what researchers found present in the A Mild cigarette advertisement based on Roland Barthes' semiological studies
Human disturbance affects behavioural time allocation in a fiddler crab (Austruca annulipes) in Southern Thailand
Authors: Chumsri Anantanit , Tina Fahmida Wazed , Vongkok Areerat , Chinnanon Malinee , Chuaytanee Nipaporn , Angajchariya Amornrat , Sujarit Chutinut
Published: August 2023

Human disturbances affect the macroinvertebrate populations in coastal regions. They respond to disturbances by altering their density and behaviour. Therefore, many of them are used as bioindicator species of human disturbance. Here, we pioneer the use of fiddler crabs to examine whether they alter their behaviour under human disturbance. Male fiddler crabs possess one large claw used for courting (waving) and fighting, and one small feeding claw, whereas females have two feeding claws. They show several surface activities. This study investigates (1) the effects of human disturbance on density and sex-ratio, and (2) the effects of human disturbance, and sex on behavioural time allocations in Austruca annulipes. Their density, sex-ratio, and time allocations were investigated in human-disturbed area (DA) and nondisturbed area (NDA). They showed feeding, feeding and walking, walking, running, standing/vigilance, inside burrows, burrowing, grooming, fighting, and waving. The results showed that crab density was higher and the sex ratio was more male biased in NDA than in DA. Human disturbance and sex affected time allocations but their interaction had no effect. Crabs in DA spent more time running, standing, and inside burrows but less time walking, burrowing, fighting, and waving than crabs in NDA. Between sexes, males spent more time standing, burrowing, grooming, and fighting but less time feeding, and walking than females. This indicates that human disturbances force the crabs to spend more time on anti-predator and escape behavior (standing/vigilance, running, inside burrows) rather than courting (waving) and constructing burrows (mating/breeding sites), which are important for breeding.
Surviving heat: Resilience of Nellore bulls to solar radiation exposure
Authors: Santos Mateus Medeiros dos , Souza-Junior João Batista Freire , Castelo Thibério de Souza , Queiroz João Paulo Araújo Fernandes de , Costa Leonardo Lelis de Macedo
Published: August 2023

We aimed to assess the physiological and biophysical responses of Nellore bulls exposed to solar radiation in semiarid conditions throughout the day. Sixteen Nellore bulls were examined in Tibau city, Northeast Brazil (5°52ʹ South, 37°20ʹ West, and 37 m above sea level) over four nonconsecutive days, with data collection taking place at one-hour intervals between 7:00 am and 5:00 pm. Four animals were analyzed each day and kept exposed to the sun for the duration of the study. The average age of the animals was three years, and their average body weight was 650±32 kg. The meteorological station measured air temperature (°C), relative humidity (%), solar radiation (W.m-2), and black globe temperatures (°C) every minute, while a digital anemometer thermohygrometer measured wind speed (m.s-1) at the same time. Respiratory rate (breaths.min-1), expired air temperature (°C), rectal temperature (°C), and body surface temperature (°C) were measured as physiological variables. Biophysical equations were used to estimate the sensible and latent heat transfer mechanisms (W.m-2). The air temperature ranged from 28.5 to 32.5°C, and direct solar radiation was between 21 and 891 W.m-². Between 11:00 am and 1:00 pm, the study observed heat gain through longwave radiation, which reached an average of 250 W.m-2, with a significant increase (P < 0.05) in respiratory rate and body surface temperature during this time. Convection was significant in heat dissipation, particularly when the wind speed was increased from 11:00 am. However, latent heat loss mechanisms were more effective in losing excess body heat under total sun exposure, despite the positive effect of convection. The study findings showed that Nellore bulls maintained their body temperature within a narrow range even when exposed to high solar radiation, thus demonstrating the efficiency of physiological and biophysical mechanisms during times of greater thermal challenge.
ANALYSIS OF DIMSUM PRODUCT QUALITY CONTROL AT PT. XYZ
Authors: Kurniawan Adji Candra , Gusnadi Erul
Published: August 2023

Penelitian ini dilakukan untuk mengatasi masalah kecacatan produk pada PT. XYZ yang bergerak dalam produksi frozen food hasil olahan perikanan dan udang. Masalah yang dihadapi adalah adanya cacat pada kulit dimsum dan ketidakseragaman bentuk dimsum dalam proses produksi dimsum. Dalam penelitian ini, digunakan pendekatan Six Sigma dengan metode DMAIC. Hasil penelitian mengungkapkan bahwa ada dua jenis cacat pada dimsum, yaitu kerusakan pada kulit dimsum mencapai 66% dan ketidakseragaman bentuk dimsum mencapai 34%. Dengan menggunakan peta kendali p-chart, diketahui bahwa ada satu kejadian di mana cacat produk berada di luar batas kendali, sementara yang lainnya berada dalam batas kendali. Meskipun demikian, jumlah cacat produk secara keseluruhan masih melebihi nilai rata-rata cacat. Dalam perhitungan Defect Per Million Opportunities (DPMO), ditemukan bahwa terdapat 23,506.90 produk cacat per satu juta produk yang diproduksi, dengan tingkat sigma sebesar 3.51. Untuk itu, dilakukan analisis sebab-akibat menggunakan fishbone diagram dengan faktor penyebab yang teridentifikasi, yaitu material, mesin, pekerja, dan metode. Setelah analisis sebab-akibat, dilakukan perbaikan dengan metode Kepner Tregoe Potential Problem Analysis (KTPPA) dan Action Plan. Dengan menerapkan pendekatan Six Sigma dan metode DMAIC, diharapkan PT. XYZ dapat mengurangi jumlah cacat produk, meningkatkan mutu dan kualitas dimsum, serta meningkatkan efisiensi dalam proses produksi. Semoga hasil penelitian ini dapat memberikan manfaat bagi perusahaan dan industri dalam menghadapi tantangan produksi frozen food.
PENGARUH MEDIA SOSIAL INSTAGRAM TERHADAP KEPUTUSAN PEMBELIAN DI WAROENG PAK MUH CIJANTUNG
Authors: Apriyanti Adelia Gusria , Busyra Nur
Published: August 2023

Tujuan dari penelitian ini untuk mengetahui pengaruh sosial media instagram terhadap keputusan pembelian. Dalam penelitian ini populasinya adalah konsumen yang pernah membeli produk di warung pak Muh cabang Cijantung, dengan menggunakan teknik pengambilan sampel yaitu proposive sampling. Uji instrument yang digunakan dalam penelitian ini adalah uji validitas dan uji reliabelitas. Teknik analisis data yang digunakan dalam penelitian ini adalah analisis deskriptif, uji normalitas. Uji analisis yang digunakan yaitu regresi linear sederhana, uji hipotesis yang digunakan dalam penelitian ini adalah uji T dan uji R. Hasil penelitian ini menunjukkan bahwa: (1) sosisal media instagram berpengaruh positif terhadap keputusan pembelian di warung pak Muh Cijantung, dibuktikan dengan thitung adalah 11,859 dengan tingkat signifikansi 0,000 < 0,05 ; (2). koefisien korelasi (R) sebesar 0,481 menunjukkan indikasi keberadaan yang kuat antara variabel (X) dan variabel (Y). Mengenai hasil berdasarkan output tersebut, besaran pengaruh atau koefisien determinasi (R Square) ditunjukkan oleh variabel kualitas produk (X) terhadap keputusan pembelian (Y) sebesar 0,481 atau 48,1%, sedangkan sisanya 51,9% dipengaruhi oleh variabel’yang tidak diteliti dalam penelitian seperti WOM (Word Of Mouth), Endorsement, Kualitas Produk, Kualitas Rasa, Harga, Dll.
Width residual neuro fuzzy system based on random feature selection
Authors: Chen Dewang , Kong Lingkun , Gao Liangpeng
Published: August 2023

To shorten the operating time of the high-dimensional problems on fuzzy systems, we proposed the width residual neuro fuzzy system (WRNFS) before, but the discussion on the structure of WRNFS was insufficient, especially on the divide-and-conquer strategies of the input dimensions. In previous research, the optimization methods for WRNFS were not discussed. In this paper we proposed the first optimization method for WRNFS, which is an improved scheme for grouping the input dimensions of WRNFS, using random feature selection(RFS) to find a better solution, so as to improve the overall capability of the system. We call the width residual neuro fuzzy system based on random feature-selection as RFS-WRNFS. In this paper, the exhaustive experiment analysis and practical test of WRNFS and RFS-WRNFS are carried out on the reconstructed MG dataset, and the following conclusions are obtained: ding172 The performance of WRNFS is generally consistent when the structure of the WRNFS sub-systems and the input-output pairs are fixed; ding173 When searching for the optimal solution on the WRNFS, the time cost of exhaustive search is acceptable when the system remains in a small scale; ding174 In most cases, RFS-WRNFS carries out several random tests and produces better results than WRNFS. Furthermore, assuming that the input dimension is N and the times of attempts used to random feature selection for a better solution of WRNFS is M, we found:1) when M = 1 N, there is a certain probability to get an acceptable solution, and the system takes the shortest time; 2) When M = 2 N, there is a great chance to get an acceptable solution in a limited time; 3) When M = 3 N, best solution can be obtained with the longest search time. We suggest M = 2 N for the RFS-WRNFS for the comprehensive performance. Comparing the experiment results of exhaustive search and random feature selection, WRNFS always reaches the optimal solution by exhaustive search through a finite set in a limited time, while RFS-WRNFS in most time keeps a good balance between prediction precision and time efficiency.
Features reduction collaborative fuzzy clustering for hyperspectral remote sensing images analysis
Authors: Dang Trong Hop , Do Viet Duc , Mai Dinh Sinh , Ngo Long Thanh , Trinh Le Hung
Published: August 2023

In image processing, segmentation is a fundamental problem but an important step for advanced image processing problems. When dealing with hyperspectral image data, the task becomes much more challenging due to the large number of features (dimension), higher nonlinearity, and greater capacity of the data. This paper proposes a solution of features reduction collaborative fuzzy c-means clustering (FR-CFCM) for hyperspectral remote sensing image analysis using random projection. The dimensional reduction technique is based on the Johnson Lindenstrauss lemma algorithm, preserving the relative distance between data samples. This can make clustering easier without affecting the clustering results. Moreover, by reducing dimensionality and sharing information among sub-data in collaborative clustering, it is possible to improve the performance and accuracy of hyperspectral remote sensing image analysis results. The experiments conducted on two hyperspectral image data sets with five validity indexes show that the proposed methods perform better compared with the other methods.
Application of fuzzy support vector regression machine in power load prediction
Authors: Xia Yan , Yu Shun , Jiang Liu , Wang Liming , Lv Haihua , Shen Qingze
Published: August 2023

Power system load forecasting is a method that uses historical load data to predict electricity load data for a future time period. Aiming at the problems of general prediction accuracy and slow prediction speed in using typical machine learning methods, an improved fuzzy support vector regression machine method is proposed for power load forecasting. In this method, the boundary vector extraction technique is employed in the design of the membership function for fuzzy support vectors to differentiate the importance of different samples in the regression process. This method utilizes a membership function based on boundary vectors to assign differential weights to different sample points that used to differentiate the importance of different types of samples in the regression analysis process in order to improve the accuracy of electricity load prediction. The key parameters of the fuzzy support vector regression model are optimized, further enhancing the precision of the forecasting results. Simulation experiments are conducted using real power load data sets, and the experimental results demonstrate the effectiveness of the proposed method in terms of accuracy and speed in predicting power load data compared to other prediction models. This method can be widely applied in real power production and scheduling processes.
Multi-attribute decision-making based on dual probabilistic interval-valued intuitionistic hesitant fuzzy weighted heronian mean aggregation operator
Authors: Zhang Ping , Lv Wangyong , Zhang Ce , Song Jiacheng
Published: August 2023

Probabilistic interval-valued intuitionistic hesitant fuzzy sets (PIVIHFSs) can well describe the evaluation information of decision-makers (DMs) in multi-attribute decision-making (MADM) problems. However, PIVIHFSs only depict the situation where both membership and non-membership information occur with equal probability while ignoring the situations of non-equal possibility due to DMs’ subjective preferences. In this paper, we develop dual probabilistic interval-valued intuitionistic hesitant fuzzy sets (DPIVIHFSs) concept based on the truncated normal distribution. The DPIVIHFSs overcome the shortcomings of PIVIHFSs and are more interpretable. Then, the operations and ranking method of DPIVIHFSs are introduced. Furthermore, we study MADM methods in dual probabilistic interval-valued intuitionistic hesitant fuzzy environments by aggregation operators (AOs). We propose a series of AOs including the DPIVIHF heronian mean (DPIVIHFHM) operator and the DPIVIHF weighted heronian mean (DPIVIHFWHM) operator. The basic properties of the presented are discussed and proved. Finally, a novel method for solving the MADM problem is proposed based on the DPIVIHFWHM operator and a numerical example of express company selection strategy is used to illustrate the effectiveness of the method. The proposed method in this article can capture more fuzzy and uncertain information when solving MADM problems and have a wider application range.
Examining the college English classroom teaching quality using the fuzzy evaluation model
Authors: Lv Qian
Published: August 2023

English teaching at college levels is more sophisticated and advanced compared to high schools and professionals. The teaching must have high-quality meetings, real-world interactions, and professional applications. Therefore teaching quality evaluation periodically is performed internally and externally through skill validation and joint training. This article introduces a Regressive Fuzzy Evaluation Model (RFEM) for analyzing the quality of college classroom English teaching quality. This evaluation model operates over the teaching quality metrics such as performance, student understandability, and application. The understandability and English application to the real world is modeled by referring to the performance as the regressive factor. The regressive factor is analyzed for two fuzzification outputs: high and low, by analyzing the individual factors over cumulative teaching grades. The regression for low fuzzy outputs is analyzed using mean understandability and application score from the previous assessment instance. This is required for training the fuzzification from the mean score rather than the low level. Therefore the quality improvements from the lagging features are addressed by providing a new teaching method. Further fuzzy regression is initiated from the mean to the high level reducing the computation time and errors.
Applying deep learning in brain computer interface to classify motor imagery
Authors: Cano-Izquierdo Jose-Manuel , Ibarrola Julio , Almonacid Miguel
Published: August 2023

Deep-learning (DL) is a new paradigm in the artificial intelligence field associated with learning structures able to connect directly numeric data with high-level patterns or categories. DL seems to be a suitable technique to deal with computationally challenging Brain Computer Interface (BCI) problems. Following DL strategy, a new modular and self-organized architecture to solve BCI problems is proposed. A pattern recognition system to translate the measured signals in order to establish categories representing thoughts, without previous pre-processing, is developed. To achieve an easy interpretability of the system internal functioning, a neuro-fuzzy module and a learning methodology are carried out. The whole learning process is based on machine learning. The architecture and the learning method are tested on a representative BCI application to detect and classify motor imagery thoughts. Data is gathered with a low-cost device. Results prove the efficiency and adaptability of the proposed DL architecture where the used classification module (S-dFasArt) exhibits a better behaviour compared with the usual classifiers. Additionally, it employs neuro-fuzzy modules which allow to offer results in a rules format. This improves the interpretability with respect to the black-box description. A DL architecture, going from the raw data to the labels, is proposed. The proposed architecture, based on Adaptive Resonance Theory (ART) and Fuzzy ART modules, performs data processing in a self-organized way. It follows the DL paradigm, but at the same time, it allows an interpretation of the operation stages. Therefore this approach could be called Transparent Deep Learning.
Mining the English application learning patterns of college students based on time series clustering
Authors: Niu Lili
Published: August 2023

As a convenient learning tool in the We Media era, mobile apps have been paid more and more attention by college students because of their accompanying timeliness and practicality. With the increasing number of English learning apps, many such apps provide college students with new ways to obtain learning resources and diversified learning modes. The related research in the field of mobile-assisted language learning at home and abroad has developed over nearly 20 years, basically following the route from theory to application in practice, but there have been few process studies on learners’ individual language skill learning behaviors based on mobile platform data. In this study, the time series clustering method was adopted, and the learning behavior of college students in an English vocabulary learning app in China was selected for data mining. Firstly, taking the “single-day memorization amount” as the measurement index, the memorization records of college students in the whole use cycle were extracted and processed into trajectory data, and the KmL algorithm was used to cluster the trajectory of the memorization amount in the time series. According to the intra-class average trajectory, the characteristics of learning behavior changes among the different college students are summarized, and two learning modes are depicted. Secondly, through the experimental analysis, it was found that adopting the English learning model three weeks before an exam can effectively stimulate college students and improve their willingness to learn and continue using the app.
E-commerce utilization analysis and growth strategy for smes using an artificial intelligence
Authors: Zhong Yijie
Published: August 2023

E-commerce is becoming a robust catalyst to enlarge the business actions and construct an active consumer based on emergence of a global economy. E-commerce is offering the opportunities for Small and Medium-sized Enterprises (SMEs) with limited resources to decrease the operating costs and improve the profitability by overcoming the operational problems. In addition, SMEs use e-commerce websitesas sales channels between the businesses, their competitor, and consumers. Between the success of e-commerce and manufacturing SMEs, however, the moderating influence of entrepreneurial competencies does not seem to be as significant. Hence, in this paper, Deep Convolutional Neural Network based onSales Prediction Model (DCNN-SPM) has been suggested for analyzing SME enterprises’ e-commerce utilization and development. Consistent with the user decision-making requirements of online product sales, united with the impelling factors of online product sales in different SME industries and the benefits of Artificial Intelligence (AI), this study builds a sales prediction model appropriate for online products. Furthermore, it evaluates the model’s adaptability to different types of online products. Our model can automatically extract the useful features from raw log data and predict the sales utilizing those extracted features by DCNN. The experimental outcomes show that our suggested DCNN-SPM has achieved a high customer satisfaction ratio of 98.7% and a customer is buying behaviour analysis of 97.6%.
Dominance-based rule acquisition of multi-scale single-valued neutrosophic decision system
Authors: Wang Tianxing , Wang Wenjue , Huang Bing , Li Huaxiong
Published: August 2023

Rule acquisition is significant in real life and extensively utilized in data mining. Currently, most studies have constructed rule acquisition algorithms based on the equivalence relation. However, these algorithms need to be more suitable for dominance-based decision systems and should consider applications in multi-scale environments. In this paper, we establish the dominance relation of the single-valued neutrosophic rough set model using the ranking method with the relative distance favorable degree. We then introduce this approach into a multi-scale environment to obtain the dominance relation of the multi-scale single-valued neutrosophic rough set model, resulting in two discernibility matrices and functions. We propose the algorithm for lower approximation optimal scale reduction and further examine the method of rule acquisition based on the discernibility matrix. Finally, we apply these algorithms to four random data sets to verify their effectiveness.
Enhancing heart disease detection and classification using fuzzy logic and metaheuristic algorithms in a blockchain assisted healthcare environment
Authors: Mohananthini N. , Rajeshkumar K. , Ananth C.
Published: August 2023

Heart disease (HD) is a leading cause of mortality worldwide, emphasizing the need for accurate and efficient detection and classification methods. Recently, Blockchain (BC) provides seamless and secure sharing of heart disease data amongst healthcare providers, specialists, and researchers. This allows collaborative efforts, data exchange, and integration of diverse datasets, leading to a more comprehensive analysis and accurate detection of heart diseases. BC provides a decentralized and tamper-proof platform for storing sensitive patient data related to heart disease. This ensures the integrity and security of the data, reducing the risk of unauthorized access or data manipulation. Therefore, this study presents a new blockchain-assisted heart disease detection and classification model with feature selection with optimal fuzzy logic (BHDDC-FSOFL) technique. The presented BHDDC-FSOFL technique uses BC technology to store healthcare data securely. In addition, the disease detection module encompasses the design of biogeography teaching and learning-based optimization (BTLBO) algorithm for feature selection (FS) procedure. Moreover, an adaptive neuro-fuzzy inference system (ANFIS) classifier can be exploited for HD detection and classification. Furthermore, the ebola search optimization (ESO) algorithm is used for the parameter tuning of the ANFIS classifier. The integration of ANFIS classifier enables the modeling of uncertainty and imprecision in HD data, while metaheuristic algorithms aid in optimizing the classification process. Additionally, the utilization of BC technology ensures secure and transparent storage and sharing of healthcare data. To demonstrate the enhanced HD classification results of the BHDDC-FSOFL technique, a detailed experimental analysis was made on the HD dataset. The extensive result analysis pointed out the improved performance of the BHDDC-FSOFL technique compared to recent approaches in terms of different measures. Therefore, the proposed model offers a reliable and privacy-enhancing solution for healthcare providers and patients in a BC-assisted healthcare environment.
Increasing awareness of rare PSP-F, where rehabilitation is the primary treatment: A case report
Authors: Reisch Anne , Gerety Gregory , Ding Andrew , Narapareddy Laren , Narapareddy Bharat R.
Published: August 2023

BACKGROUND: Progressive Supranuclear Palsy (PSP) is an incurable neurodegenerative disorder. One variant of PSP is a frontal lobe cognitive or behavioral presentation (PSP-F). Currently, the primary management of this disease is rooted in neurological rehabilitation, therefore, early, and accurate diagnosis is key. CASE REPORT: Here we present a 60-year-old man with a 2–3-year history of functional decline and behavioral changes. He was misdiagnosed with a late-onset psychiatric disorder. During his second inpatient admission, a full workup for neurodegenerative diseases was performed, and the patient was ultimately diagnosed with probable PSP-F. We describe his neurological rehabilitation plan, examining recommendations before and after diagnosis. RESULTS: After the neurodegenerative disorder diagnosis, the neurological rehabilitation plan, particularly PT and OT, changed drastically despite no change in clinical presentation emphasizing the value of an appropriate and early diagnosis. Furthermore, in an OT session, the patient demonstrated longitudinal improvement, emphasizing the importance of rehabilitation in these patient’s lives. CONCLUSION: Increased recognition of PSP variants amongst healthcare providers will allow more patients to receive early and appropriate diagnoses, so that they can benefit maximally from their neurological rehabilitation plans, maintain quality of life and experience longer periods of functioning. Furthermore, developing PSP-specific rehabilitation guidelines are crucial for improved outcomes. Correct diagnosis will also reduce the use of inappropriate and potentially harmful medications in these populations.
Effects of anodal tDCS on electroencephalography correlates of cognitive control in mild-to-moderate traumatic brain injury
Authors: Mertens Nickolas , Cavanagh James , Brandt Emma , Fratzke Violet , Story-Remer Jacqueline , Rieger Rebecca , Wilson J. Kevin , Gill Darbi , Campbell Richard , Quinn Davin K.
Published: August 2023

BACKGROUND: Transcranial direct current stimulation (tDCS) may provide a potential therapy for cognitive deficits caused by traumatic brain injury (TBI), yet its efficacy and mechanisms of action are still uncertain. OBJECTIVE: We hypothesized that anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC) would boost the influence of a cognitive training regimen in a mild-to-moderate TBI (mmTBI) sample. Cognitive enhancement was measured by examining event-related potentials (ERPs) during cognitive control tasks from pre- to post-treatment. METHODS: Thirty-four participants with mmTBI underwent ten sessions of cognitive training with active (n = 17) or sham (n = 17) anodal tDCS to the left DLPFC. ERPs were assessed during performance of an auditory oddball (3AOB), N-back, and dot pattern expectancy (DPX) task before and after treatment. RESULTS: P3b amplitudes significantly decreased from baseline to post-treatment testing, regardless of tDCS condition, in the N-back task. The active tDCS group demonstrated a significantly increased P3a amplitude in the DPX task. No statistically significant stimulation effects were seen during the 3AOB and N-back tasks. CONCLUSION: Active anodal tDCS paired with cognitive training led to increases in P3a amplitudes in the DPX, inferring increased cognitive control. P3b decreased in the N-back task demonstrating the effects of cognitive training. These dissociated P3 findings suggest separate mechanisms invoked by different neuroplasticity-inducing paradigms (stimulation versus training) in brain networks that support executive functioning.
Perception of dental students and faculty regarding the practice of professionalism in dentistry using the Professionalism Mini Evaluation Exercise (P-MEX)
Authors: Alam Beenish Fatima , Najmi Muhammad Arqam , Hussain Talib , Babar Bilal Zaman , Ghani Salwan , Khan Amna , Nayab Talha
Published: August 2023

BACKGROUND: Professionalism is one of the fundamental traits which includes behaviors, commitments, standards, and goals that helps define a profession. OBJECTIVE: This study aimed to assess the attitude of dental students and graduates regarding the practice of professionalism in dentistry using the Professionalism Mini Evaluation Exercise (P-MEX) questionnaire. METHOD: This cross-sectional study was conducted amongst the dental undergraduates, lecturers and postgraduate faculty. Views regarding professionalism were assessed using the P-MEX. The 24-questions based survey form is comprised of questions related to doctor and patient relationship skills, reflective abilities, time management, and lastly, interprofessional relationship expertise. Data was analyzed using SPSS version 23. Descriptive statistics were done using mean and SD, whilst associations between responses were assessed using Mann-Whitney U and Kruskal-Wallis tests. P value less than 0.05 was considered significant. RESULTS: From a total of 201 participants, 95 (47.3%) were males and 106 (52.7%) were females. Statistically significant association was seen between time management, reflective skills, and interpersonal skills with gender, as well as the domains of P-MEX and years of education. CONCLUSION: The use of P-MEX provides a valid confirmation for the assessment and awareness of professionalism amongst the dental faculty and students. Females demonstrated higher traits of professionalism as compared to males. The findings from the current study identify that students and faculty members had sufficient awareness regarding professionalism and the practice of professionalism was routinely followed.
Perceived vocational support needs and return-to-work outcomes in the first 12-months post-discharge in individuals with acquired brain injury and spinal cord injury: A retrospective cohort study
Authors: O’Loghlen Jessica , Geraghty Timothy , Kendall Melissa , Nielsen Mandy , Jones Rachel , McLennan Vanette , Watter Kerrin , Ownsworth Tamara
Published: August 2023

BACKGROUND: Return-to-work (RTW) is often viewed as an important outcome following acquired brain injury (ABI) and spinal cord injury (SCI), although not all individuals have vocational goals and many experience barriers to RTW. OBJECTIVE: This study investigated the relationship between RTW and psychosocial functioning at 12-months post-discharge after ABI and SCI and examined patterns of RTW according to perceived need for and receipt of vocational support. METHODS: A file audit was conducted for 69 participants with ABI (n = 44) and SCI (n = 25). Data on employment status and perceived vocational support at 3- and 12-months post-discharge, home and community participation, psychological distress, and health-related quality of life were extracted. RESULTS: Individuals in paid employment at 12-months post-discharge (22%, n = 15) reported significantly better psychosocial functioning at this timepoint compared to those not employed (78%; n = 54). For those not employed, three subgroups were identified: 1) Did not perceive the need for or receive vocational support (50%; n = 27); 2) Perceived vocational support needs were unmet (19%; n = 10); and 3) Perceived and received vocational support (31%; n = 17). Psychological distress was highest for those who perceived and received vocational support but were not employed. CONCLUSION: RTW was associated with better psychosocial functioning after acquired neurological injury. The findings highlight the need for clinicians to explore and revisit individuals’ perceived need for and preferences for vocational support and monitor the psychological well-being of those with RTW goals that are not yet successful.
Global coronavirus vaccination campaign: The role of religious workers in vaccine distribution, public mobilization and the eradication of nationalism
Authors: Niu Long , Miraj Muhammad , Chuntian Lu , ur Rehman Ramiz , Shereen Saima
Published: August 2023

BACKGROUND: Throughout history, the world has faced numerous health challenges and outbreaks, but through the dedication of medical professionals, solutions have been found. Despite this, the emergence of the coronavirus (COVID-19) has presented a new and dangerous threat. Nevertheless, with unwavering commitment, health experts have triumphantly discovered a remedy. OBJECTIVES: The study aimed to examine how religious workers worldwide could contribute positively to ensuring the fair distribution of COVID-19 vaccines, addressing vaccine hesitancy, encouraging people to get vaccinated, and preventing vaccine nationalism. METHOD: Our study employed a refined qualitative content analysis methodology to categorize factual information and pave the way for subsequent policymakers. We meticulously curetted the most trustworthy secondary data sources and utilized them to analyze the study. RESULTS: The content analysis reveals that religious workers played an active role in the global coronavirus vaccination drive by working towards better vaccine distribution, encouraging people to get vaccinated and countering hesitation and nationalism. CONCLUSION: In light of the discoveries, it would be prudent for policymakers to engage religious workers in advancing the cause of public health, regardless of whether the health matters are localized, national, or global in scale. This strategy has the potential to be both alluring and convincing.
Culture Lockdown, Nature Freedom: Respite for Biodiversity during the COVID Pandemic – A Limited Case Study in La Union, Philippines
Authors: Canilao Michael Armand P.
Published: August 2023

In dealing with treatment regimes for planetary health, a more nuanced approach to isolate the dialectics of nature-humanized and humans-naturalized may be possible by looking at case studies and areas of interest where the interregnum in human activities (culture lockdown) may have become an opening for biodiversity recovery. Such a recovery may best be characterized as nature freedom– a true instance of freedom in the Anthropocene. As quaternary consumers, the Kali or Brahminy kite serves as a beacon, signaling areas with intact biodiversity pyramids. The presence or absence may be a cue to the state of illegal wildlife trade and habitat loss in an area. The paper will present Kali or Brahminy kite observations logged using consumer off-the-shelf remotely piloted aircraft systems (COTS-RPAS) and compare this data with easing COVID-19 pandemic lockdown restrictions in La Union Province in the Philippines. As our communities transition to the new normal that looks a lot like the old normal, subordination of nature is once again the gameplay of autonomous humans.
Cooling Beer With a Wet Paper Towel
Authors: Butts David , Murillo Michael
Published: August 2023

Beer is a drink often stored warm but served cold, a fact that has led to the development of many ways to cool beer and other beverages rapidly. One method suggests that wrapping a beer in a wet paper towel accelerates the cooling in a freezer, but the effectiveness of this method has been debated across the internet. Does a wet paper towel slow cooling by insulating a beer, or does evaporation from the towel enhance cooling? We performed low-cost, easily reproducible experiments and simulations to answer these questions. We employed a Radau, finite-volume method to solve the heat equation in cylindrical coordinates and simulated each material using the best available thermal conductivities, densities, and specific heats. Experiments were performed in the presence of varying levels of advection in the surrounding air. We found increasing advection by placing beers near the freezer fan reduced the cooling time (\(70^\circ\)F (\(21.1^\circ\)C) to \(45^\circ\)F (\(7.2^\circ\)C)) by 60%-70%; the wet paper towel had a negligible impact. With two lower levels of advection, we found that the wet paper towel reduced the cooling time by approximately 25%. Experiments with multiple thermometers were used to generate time-space diagrams that showed the evolving radial temperature profile in materials. Infrared images revealed convection patterns caused by the warm bottle, even when the bottle was protected from airflow from the fan. Our simulations agreed with our data when we used boundary conditions that mimicked convection. This agreement was also evident when comparing data from an environment without air advection, implying the presence of natural convection.
On Solé and Planat criterion for the Riemann Hypothesis
Authors: Vega Frank
Published: August 2023

There are several statements equivalent to the famous Riemann hypothesis. In 2011, Solé and Planat stated that the Riemann hypothesis is true if and only if the inequality \(\zeta(2) \cdot \prod_{q\leq q_{n}} (1+\frac{1}{q}) > e^{\gamma} \cdot \log \theta(q_{n})\) holds for all prime numbers \(q_{n}> 3\), where \(\theta(x)\) is the Chebyshev function, \(\gamma \approx 0.57721\) is the Euler-Mascheroni constant, \(\zeta(x)\) is the Riemann zeta function and \(\log\) is the natural logarithm. In this note, using Solé and Planat criterion, we prove that the Riemann hypothesis is true.
Ginger, Galangal, and Turmeric Production in Florida
Authors: Fisher Paul , Freyre Rosanna , Gómez Celina , Pearson Brian , Sanchez-Jones Tatiana , Steed Shawn , Laughlin Wanda , Hochmuth Robert , Wasielewski Jeff , Lieurance Deah , Harmon Carrie , Paret Mathews , Osborne Lance , Athearn Kevin , Sargent Steven , Zhang Mengzi , Flores Sofia , Nelson Carly , Retana-Cordero Marlon , Tello Nathalia
Published: August 2023

Ginger, galangal, and turmeric (Figure 1) are emerging crops for Florida production. All of these plants are in the Zingiberaceae family and share most aspects of their production. This bulletin describes production in containers or the field under Florida conditions to help guide growers interested in ginger, turmeric, and galangal production or expanding their market. All species have been evaluated by the UF/IFAS Assessment of Non-native Plants in Florida’s Natural Areas (UF/IFAS Assessment) using the Predictive Tool (an invasion risk assessment) and all present a low risk of invasion in Florida (https://assessment.ifas.ufl.edu).
Prescribed Fire Size, Patchiness, and Pyrodiversity in the Southeastern United States
Authors: Fill Jennifer , Crandall Raelene
Published: August 2023

This publication aims to provide information on how variation in prescribed fire size and heterogeneity and their impact over time relate to the habitat needs of animals and plants that live in frequently burned savannas. Written by Jennifer M. Fill and Raelene M. Crandall, and published by the UF/IFAS School of Forest, Fisheries, and Geomatics Sciences, August 2023.