bluuebunny/crossref_metadata_2025 huggingface dataset:
Trajectory Planning of Spherical Pendulum Pattern for Application in Creating Batik Patterns
Authors: Putri Indah Radityo , Ekawati Estiyanti , Budi Eko Mursito , Juwandana Alfisena , Mulyawan Naufan Aurezan , Kho Philip Inarta , Kudiya Komarudin
Published: January 2024

Batik Pendulum is a new batik pattern created by Rumah Batik Komar using a single-string pendulum filled with wax. However, current production is still manual, so it is impossible to re-manufacture in large quantities. This research is part of a machine and software development project to produce Batik Pendulum, where this research will only focus on software development. The designed software will have a spherical pendulum trajectory planning feature through parameter changes. The spherical pendulum path was chosen because it has the same pattern as the currently produced Batik Pendulum. In planning the spherical pendulum trajectory, an algorithm that receives input in the form of parameters to produce a spherical pendulum pattern has been designed. From these inputs, it is proven that the proposed parameters can provide a variety of spherical pendulum patterns. Implementing the spherical pendulum trajectory planning in the software shows that the time required to change parameters until the output trajectory is generated is 1 – 2 seconds. So, there is no need for any feedback to the user.
Medical Association in Fiume (Associazione Medica Fiumana)
Authors: Alebić-Juretić Ana
Published: January 2024

The second half of the 19th century in Fiume (now Rijeka) was characterized by the expansion of industrial activity and trade, and the new wealth resulted in a dynamic social life. As a consequence, many new associations were founded in the city, including the Medical Association in Fiume (Associazione medica fiumana), which was established in 1901. The founding procedure was really fast. On January 10th, 1901, the founding committee delivered four samples of the Statute in Italian and one in Hungarian to the Municipality. These were to be passed on via the Governor’s office to the Hungarian Ministry of the Interior for approval. On May 4th, 1901, the governor informed the Municipality about the received approval and returned two copies of the statute to the Association. The founding assembly was held on May 23rd, 1901, in the building of the Municipal School for Boys (Ciotta St. 1). The Association’s goals included the improvement of medical knowledge, the protection of professional interests, and the enhancement of communication between colleagues. The first president elected was Dr. Giorgio Catti, who held this position until 1913. The members were divided into two categories: ordinary members, who were residents of the town, and extraordinary members residing elsewhere. The official language was Italian, but lectures and discussions could be conducted in any language. The association ceased its activity with the beginning of World War I.
Health Care in Slavonian Province during the 19th Century
Authors: Čandrlić Slavko , Šabanović Danijel , Mahaček Karlo , Holik Dubravka , Miškulin Maja , Beneš Miodrag , Miškulin Ivan , Včev Ivan , Lešić Davor , Čandrlić Marija
Published: January 2024

Zbog neposredne blizine s Osmanskim Carstvom, u Slavoniji je postojala stalna opasnost od ulaska brojnih zaraznih i nezaraznih bolesti. Dodatna su otegotna okolnost bili loši životni i higijenski uvjeti, siromaštvo, suše i poplave. Odlaskom Osmanlija krajem 17. stoljeća zdravstvenu skrb pružala je tek nekolicina brijača i ranarnika, koji su ostali živjeti u slavonskom Provincijalu. Zbog loše zdravstvene zaštite, carica i kraljica Marija Terezija 1770. donosi Opći zdravstveni zakon koji se primjenjivao na području cijele Habsburške Monarhije, uključujući i Slavoniju. Među ostalim, njime je predviđeno uvođenje formalnog obrazovanja za zdravstvene radnike, što je u konačnici rezultiralo stvaranjem kvalitetnijega medicinskog kadra. Usporedno s tim, šarlatanima se sve češće izricala zabrana rada. Nedostatak obrazovanih liječnika, stomatologa, primalja, ljekarnika i veterinara pokušalo se riješiti različitim mjerama kojima se poticalo njihovo školovanje i usavršavanje. Nakon stjecanja diplome ti su stručnjaci bili raspoređeni u bolnice, domove za starije i nemoćne osobe, domove za invalide i u druge zdravstvene ustanove u kojima se stanovnicima slavonskog Provincijala pružala zdravstvena skrb.
Religious Moderation Education: An Interpreation
Authors: Rahman Pathur , Supriyanto John , Takrip Muhamad
Published: January 2024

The fact of the dynamics of the views of different religious communities towards the verses of the Koran shows conflict. Moderation education is very important to ask about in social life, especially in the academic world which can be carried out concretely with certain approaches based on values or exemplary technology based where data is compilation in cyberspace and can be used in all areas of life. The qualitative method that the researcher did observed activities in detail related to moderation education through the verses of interpretation in Penakita and analyzed them qualitatively with interview or documentation observation techniques to then analyze the data obtained, the data collected was presented related. The study of Majlis ta`lim at Pena Kita Indralaya Islamic boarding school provides stories of friends, tabi`in and scholars, by developing the concept of religious moderation education through the study of verses of interpretation to teach the congregation a moderate, inclusive and respectful attitude in understanding and implementing religious teachings such as justice, peace, tolerance, and interfaith harmony.
Revitalization the Function of Traditional Nagari Density in Handling Criminal Cases Based on Restorative Justice
Authors: Efendi Roni , Maghfira Saadatul , Utamy Hebby Rahmatul , Ardiyanto Erwin Radon
Published: January 2024

The criminal justice system, which was previously focused on the criminal aspect or retributive perspective, is now confronted with the reality that there are only a few legal structures, ranging from judges, prosecutors, and police to a small number of prison institutions that serve as execution venues. The author is concerned with this legal fact, so he uses primary data sources and sociological juridical studies to try and find a remedy. According to the author's findings, to prevent the issues mentioned above, criminal cases in Minangkabau can be resolved through the Nagari Traditional Meeting Institution using the restorative justice idea, which aims to repair the social discord caused by criminal acts. When applying restorative justice, the Nagari Customary Association makes use of the relevant legal source of the Nan Salapan Law, while the formal legal procedures can use the Nan Duo Puluah Law.
Alfateema Business Communication Strategy in Increasing Consumer Loyalty
Authors: Kurnia Renita , Prasetyo Bahariandi Aji , Marzal Novrizon
Published: January 2024

Online business requires business communication that is useful for persuading potential consumers while making existing consumers loyal. One of the UMKM brands that uses business communication is Alfateema. The purpose of this research is to determine Alfateema's business communication strategy for increasing consumer loyalty. This research uses a qualitative descriptive method by collecting data through observation, interviews, and literature studies. The data analysis technique uses source triangulation. This research uses elements of communication, 7C business communication principles, and consumer loyalty characteristics. Alfateema builds relationships with consumers and increases loyalty through effective communication that the company owns across various platforms. The business employs communication principles such as completeness, conciseness, courtesy, and consideration to achieve this, as revealed by the results of the research. Then the business communication carried out by Alfateema produces a positive reputation so that consumers turn into loyal customers and faithfully use Alfateema products by making repeat buyers, recommending to others, and demonstrating immunity to the full competition.
Sustainable Tourism Development in The Development of Pontianak Equator Weaving Tourism Village
Authors: Alamri Annisa Rizqa , Nurwati Nunung , Aristy Yayang , Purba Olivia Rovince , Frastika Dhea , Fadri Zainal
Published: January 2024

This research aims to analyze more deeply the development of a weaving tourism village in Pontianak City. The method used in this research is descriptive qualitative data collection techniques using in-depth interviews and literature studies, where metadata is taken from books, online journals, and secondary references related to this research. This research was analyzed using sustainable tourism development. The results of the study found that the development of the equator weaving village has paid attention to economic, ecological, and social aspects so that the equator weaving village can become one of the booming tourism village pilots in Pontianak City.
Peran Badan Permusyawaratan Nagari (BPN) Di Nagari Saniangbaka Kabupaten Solok
Authors: Ramadhani Mutiara , Fitri Ulya
Published: January 2024

Mutiara Ramadhani, NIM. 1930307004, Judul Skripsi Peran Badan Permusyawaratan Nagari (BPN) Di Nagari Saniangbaka Kabupaten Solok Program Studi Pemikiran Politik Islam Fakultas Ushuluddin Adab dan Dakwah Universitas Islam Negeri (UIN) Mahmud Yunus Batusangkar, Program Sarjana (S-1) tahun 2023.Pokok permasalahan dalam skripsi ini memiliki fokus pembahasan tentang Peran Badan Permusyawaratan Nagari (BPN) di Nagari Saniangbaka. Tujuan dalam penulisan skripsi ini ialah untuk melihat Peranan dan Fungsi Badan Permusyawaratan Nagari di Nagari Saniangbaka.Jenis penelitian yang penulis gunakan ialah metode penelitian kualitatif dengan analisis deskriptif. Teknik pengumpulan data dalam penelitian ini adalah menggunakan teknik observasi, wawancara dan dokumentasi. Teknik analisis data dengan menggunakan (penarikan simpulan dan verifikasi data), Data display (penyajian data) dan Data reduction (reduksi data). Penulis menganalisis data menggunakan metode analisis deskriptif dengan pola pikir deduktif, Dalam teknik analisis data purposive, peneliti memilih sampel berdasarkan kriteria tertentu yang relevan dengan tujuan penelitian dan Teknik pemilihan informan dalam penelitian ini menggunakan metode Purposive Sampling. Penelitian ini dilakukan berlandaskan pada UU No.6 Tahun 2014 tentang desa yang bertujuan untuk kesejahteraan masyarakat desa.Berdasarkan penelitian yang penulis lakukan di Nagari Saniangbaka melalui wawancara dan observasi serta dokumentasi di lapangan menemukan bahwa BPN Saniangbaka telah melaksanakan tugas dan wewenangnya sebagai wujud peranan Badan Permusyawaratan Nagari di Saniangbaka. Hal ini didasarkan bahwa BPN telah melaksanakan rembuk jorong untuk menjemput aspirasi dan usulan pembangunan, setelah itu dilakukan Badan Permusyawaratan Nagari melakukan rapat koordinasi dengan wali Nagari untuk melakukan musyawarah Nagari (Musna) yang dihadiri oleh seluruh elemen masyarakat demi terwujudnya di Nagari Saniangbaka. Hasil dari Musna inilah menemukan kesepakatan tentang perencanaan pembangunan yang akan dilaksanakan di Nagari.
Development of al-khawada a traditional Saudi food by adding olive oil or black seed
Authors: Mariod Abdalbasit Adam , Alsulami Ahmed Nami , Mohamedain Ahmed
Published: January 2024

Background: The success of food products is significantly influenced by their development, aimed at achieving a new product characterized by excellent flavor, distinctive color, desirable texture, and widespread consumer acceptance. In line with these objectives, the product "al-Khawada" has been innovatively developed. This popular food item is crafted from millet flour and ghee to meet consumer preferences and expectations.Objective: The objective of our study was to enhance al-khawada by refining its flavor, color, and texture, ultimately improving overall liking degree. Acceptance is evaluated through hedonic tests to assess the overall liking and degree of liking for individual sensory attributes. This was achieved by incorporating either olive oil or Nigella sativa into the formulation.Methods: In this study, al-khawada was formulated with the addition of 1% and 2% olive oil, known for its richness in fat and vitamins. This variation is recognized for its ease of digestion. Additionally, black seed was incorporated at 1% and 2%, contributing seeds with high antioxidant content and numerous essential vitamins. The standard al-khawada was utilized as the control group in this comparative analysis.Results: The results of the panalists  were analyzed using the SAS program and showed that the addition of olive oil by 1% and 2% in the manufacturing of al-khawada received the satisfaction of the panelists in terms of flavor, color, texture, and overall acceptance while the addition of black seed by 1% and 2% did not have the satisfaction of the panelists in terms of flavor, color, texture, and overall acceptance.Conclusion:The study recommended the need to develop an al-khawada product by adding olive oil at concentration of around 1% and 2% because of its good flavor, distinctive color, desirable texture, and good overall liking. Other studies are needed to increase the ratios of acceptance of al-khawada product to give good flavor, distinctive color, and desired texture.Keywords: Al-khwada, Millet, Ghee, Olive oil, Black cumin seed
Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer’s Disease: A Multi-Database Validation Study
Authors: Fan Xiang , Cai Yuan , Zhao Lei , Liu Wanting , Luo Yishan , Au Lisa Wing Chi , Shi Lin , Mok Vincent Chung Tong
Published: January 2024

Background: Pilot study showed that Alzheimer’s disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia. Objective: The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender. Methods: AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance. Results: The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment. Conclusions: AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.
Programme Dementia Prevention (pdp): A Nationwide Program for Personalized Prevention in Luxembourg
Authors: Schröder Valerie E. , Skrozic Amna , Erz Dorothee , Kaysen Anne , Fritz Joëlle V. , Loureiro Joao M. , McIntyre Deborah , Pauly Laure , Kemp Jennifer , Schmitz Sabine K. , Wagner Sophie , Reyes Margarita , Soare Ruxandra , Satagopam Venkata , Vega Carlos , Gawron Piotr , Roomp Kirsten , Conde Patricia Martins , Klucken Jochen , Köhler Sebastian , Hartmann Tobias , Dodel Richard , Leist Anja K. , Kalbe Elke , Krüger Rejko
Published: January 2024

Background: With continuously aging societies, an increase in the number of people with cognitive decline is to be expected. Aside from the development of causative treatments, the successful implementation of prevention strategies is of utmost importance to reduce the high societal burden caused by neurodegenerative diseases leading to dementia among which the most common cause is Alzheimer’s disease. Objective: The aim of the Luxembourgish “programme dementia prevention (pdp)” is to prevent or at least delay dementia in an at-risk population through personalized multi-domain lifestyle interventions. The current work aims to provide a detailed overview of the methodology and presents initial results regarding the cohort characteristics and the implementation process. Methods: In the frame of the pdp, an extensive neuropsychological evaluation and risk factor assessment are conducted for each participant. Based on the results, individualized multi-domain lifestyle interventions are suggested. Results: A total number of 450 participants (Mean age = 69.5 years; SD = 10.8) have been screened at different recruitment sites throughout the country, among whom 425 participants (94.4%) met the selection criteria. Conclusions: We provide evidence supporting the feasibility of implementing a nationwide dementia prevention program and achieving successful recruitment of the target population by establishing a network of different healthcare providers.
Rethinking Dementia Risk Prediction: A Critical Evaluation of a Multimodal Machine Learning Predictive Model
Authors: Ottaviani Silvia , Monacelli Fiammetta
Published: January 2024

A recent study by Ding et al. explores the integration of artificial intelligence (AI) in predicting dementia risk over a 10-year period using a multimodal approach. While revealing the potential of machine learning models in identifying high-risk individuals through neuropsychological testing, MRI imaging, and clinical risk factors, the imperative of dynamic frailty assessment emerges for accurate late-life dementia prediction. The commentary highlights challenges associated with AI models, including dimensionality and data standardization, emphasizing the critical need for a dynamic, comprehensive approach to reflect the evolving nature of dementia and improve predictive accuracy.
The Oxytocin Puzzle: Unlocking Alzheimer’s Disease
Authors: Selles Maria Clara , Oliveira Mauricio Martins
Published: January 2024

Alzheimer’s disease is a multi-factorial disease that disrupts many aspects of human behavior. In this comment, we highlight the work by Koulousakis et al. published in a recent issue of the Journal of Alzheimer’s Disease. In this study, the authors tested the therapeutic potential of the neuropeptide oxytocin in a pre-clinical model of Alzheimer’s disease and found positive behavioral outcomes on memory assessments. We discuss these findings in the context of oxytocin research in the field of Alzheimer’s disease and the literature regarding oxytocin-based therapeutics, including administration protocols and potential underlying cellular and molecular mechanisms.
Statistical analysis of lexemes generated in ‘C’ programming using fuzzy automation
Authors: Kaur Ranjeet , Tripathi Alka
Published: January 2024

The present work is an effort to support the typographical errors of keywords that are not supported by existing compilers and integrated development environment(IDE) in ’C’ language. The fuzzy automata modelling approximate string matching is proposed for error handling during lexical analysis. By introducing fuzziness to lexemes the typographical errors can be rectified at the time of compilation and flexibility of lexical analyser can be greatly improved. The recognition of fuzzy tokens during lexical analysis is described in order to correct errors caused by sticking key, deletion, typing and swapping key in keywords during C programming. Algorithms and pseudo code are being developed to measure the degree of membership of crisp and fuzzy lexemes. Accuracy is tested and examined once the fuzzy lexemes are trained using a neural network. The proposed method is an add on feature that can be incorporated in existing compilers and IDEs to increase their flexibility.
Fuzzy RBF neural network fault diagnosis method based on knowledge and data fusion for the recoil system
Authors: Yang Xiangfei , Zhang Faping , Wei Jianfeng
Published: January 2024

To improve the accuracy of fault diagnosis for recoil systems under multiple operating conditions, a fuzzy RBF neural network (Radial Basis Function, RBF) fault diagnosis method based on knowledge and data fusion is proposed. A kinetic model for the recoil system is first established to describe the system’s behavior. Next, fuzzy RBF neural network is used to establish the relationship between abnormal operating parameters and fault causes, achieving a fault cause diagnosis accurately based on the integration of expert experience knowledge and system operation data. A study case demonstrate that the algorithm has strong knowledge and data fusion capabilities and can effectively identify faults in recoil system.
Collocated control of double electric pushrod in a harvester header based on an improved gray wolf PID algorithm
Authors: Sun Ruixia , Xiao Ping , Tang Wei , Chen Long , Chen Dandan
Published: January 2024

In order to further enhance energy conservation and emission reduction, the header lifting structure of a harvester is studied. First, a double electric pushrod structure is used to replace the oil cylinder and air cylinder lifting structure of a traditional header to reduce fuel consumption and harmful gas emission. Furthermore, a mathematical model and a simulation model of the electric pushrod are established. To enhance the control effect of the header lifting structure, an improved version of the traditional gray wolf optimization (GWO) algorithm is designed. The nonlinear convergence factor, Kent chaotic mapping and convergence surrounding and spiral updating operations are introduced to increase the convergence speed and optimization accuracy of this algorithm. The improved GWO (IGWO) algorithm is applied to optimize the proportional-integral-derivative (PID) controller of the double pushrod coordinated control system. Then, a new IGWO-PID control algorithm is also designed. The cross-coupling control strategy of header’s double pushrods is then studied. Results of the simulation and bench test show that the IGWO-PID control algorithm and the cross-coupling control strategy can effectively enhance controlling effect of the harvester header. The left and right pushrods can achieve good synchronous and coordinated movements.
A supplier selection method based on cobweb similarity and prospect theory for prefabricated components
Authors: Zhang Xiang , Huang Jianhua , Fang Liting , Li Qian
Published: January 2024

Selecting suppliers for prefabricated components (PCs) involves a complex decision-making process, frequently relying on ambiguous information and subjective judgment. However, most existing methods use precise values to portray indicator information and overlook the uncertainty of weights and the subjective preferences of decision-makers (DMs). In order to address these limits, this paper proposes a novel approach to select suppliers of PCs. Initially, an evaluation index system for suppliers is established through literature analysis and a questionnaire survey. The system comprises six layers: product quality, price, service level, comprehensive ability, supply ability, and environmental sustainability. The group decision matrix is then constructed using the set-valued statistical method and the prospect theory. The index weights are determined by a combination weighting method. Next, the cobweb model is introduced to analyze the disparity between the alternative and ideal solutions, describing their similarities in terms of area and shape. Lastly, cobweb similarity is employed instead of comprehensive distance, combined with the minimum sum of squares criterion, to improve the closeness algorithm and contrast the alternatives. The results demonstrate that this method facilitates a comprehensive evaluation of the benefits and drawbacks of various alternatives from diverse perspectives. Furthermore, it allows flexible adjustments based on the risk preferences of DMs, ensuring accurate and reliable decision results.
Delta robot control by learning systems: Harnessing the power of deep reinforcement learning algorithms
Authors: dos Santos Lima Matheus , Kich Victor Augusto , Steinmetz Raul , Tello Gamarra Daniel Fernando
Published: January 2024

The present study focuses on the implementation of Deep Reinforcement Learning (Deep-RL) techniques for a parallel manipulator robot, specifically the Delta Robot, within a simulated setting. We introduced a simulation framework designed to guide the Delta Robot’s end-effector to a designated spatial point accurately. Within this environment, the robotic agent undergoes a learning process grounded in trial and error. It garners positive rewards for successful predictions regarding the next action and faces negative repercussions for inaccuracies. Through this iterative learning mechanism, the robot refines its strategies, thereby establishing improved decision-making rules based on the ever-evolving environment states. Our investigation delved into three distinct Deep-RL algorithms: the Deep Q-Network Algorithm (DQN), the Double Deep Q-Network (DDQN), and the Trust Region Policy Optimization Algorithm (TRPO). All three methodologies were adept at addressing the challenge presented, and a comprehensive discussion of the findings is encapsulated in the subsequent sections of the paper.
Feature selection for hybrid information systems based on fuzzy β covering and fuzzy evidence theory
Authors: Ma Xiaoqin , Liu Jianming , Wang Pei , Yu Wenchang , Hu Huanhuan
Published: January 2024

Feature selection can remove data noise and redundancy and reduce computational complexity, which is vital for machine learning. Because the difference between nominal attribute values is difficult to measure, feature selection for hybrid information systems faces challenges. In addition, many existing feature selection methods are susceptible to noise, such as Fisher, LASSO, random forest, mutual information, rough-set-based methods, etc. This paper proposes some techniques that consider the above problems from the perspective of fuzzy evidence theory. Firstly, a new distance incorporating decision attributes is defined, and then a relation between fuzzy evidence theory and fuzzy β covering with an anti-noise mechanism is established. Based on fuzzy belief and fuzzy plausibility, two robust feature selection algorithms for hybrid data are proposed in this framework. Experiments on 10 datasets of various types have shown that the proposed algorithms achieved the highest classification accuracy 11 times out of 20 experiments, significantly surpassing the performance of the other 6 state-of-the-art algorithms, achieved dimension reduction of 84.13% on seven UCI datasets and 99.90% on three large-scale gene datasets, and have a noise tolerance that is at least 6% higher than the other 6 state-of-the-art algorithms. Therefore, it can be concluded that the proposed algorithms have excellent anti-noise ability while maintaining good feature selection ability.
A genetic algorithm concerning diversity information for solving the robust influence maximization problem on networks
Authors: Chen Minghao , Wang Shuai , Zhang Jiazhong
Published: January 2024

The influence maximization problem is one of the hot research topics in the field of complex networks in recent years. The so-called influence maximization problem is how to select the seed set that propagates the largest amount of information on a given network. In practical applications, networks are often exposed to complicated environments, and both link-specific and node-specific attacks can have a significant impact on the network’s propagation performance. Several pilot studies have revealed the crux of the robust influence maximization problem, but the current work available is not comprehensive. On the one hand, existing studies only consider the case that the network structure is stable or under link-specific attacks, and few researches have concentrated on the case when the network structure is under node-specific attacks. On the other hand, the current algorithm fails to combine the information of the search process well to solve the robust influence maximization problem. Aiming at these deficiencies, in this paper, a metric for evaluating the robust influence performance of seeds under node-specific attacks is developed. Guided by this, a genetic algorithm (GA) maintaining the principle of diversity concern (DC) to solve the Robust Influence Maximization (RIM) problem is designed, called DC-GA-RIM. DC-GA-RIM contains several problem-orientated operators and fully considers diverse information in the optimization process, which significantly improves the search ability of the algorithm. The effectiveness of DC-GA-RIM in solving the RIM problem is demonstrated on a variety of networks. The superiority of this algorithm over other approaches is shown.
Projection-based TOPSIS method to MAGDM in dual probabilistic linguistic information environment
Authors: Jiang Guangtian , Song Anbin
Published: January 2024

The dual probabilistic linguistic term sets (DPLTSs) are more effective than PLTSs in solving the problem of multi-attribute group decision-making (MAGDM). In this paper, an improved TOPSIS method is developed combining the TOPSIS method and projection measure of DPLTS to supplement the existing research. Firstly, considering the mathematical characteristics of DPLTS, this paper defines the concepts of the module, cosine function, and projection of DPLTS, and then proves the mathematical properties of the cosine function. Secondly, considering the uncertainty of decision-making problems, the weight-solving models are established respectively under the condition that the weight information is completely unknown and partially known. Furthermore, a novel DPLPrj-TOPSIS approach is established based on the projection measure proposed. It involves integrating experts’ DPLTS evaluations, normalizing different DPLTSs, calculating alternatives’ relative closeness and score, etc. Secondly, the proposed method’s feasibility is demonstrated through a case study that entails selecting network promotion plans for food manufacturers. Finally, the proposed method’s effectiveness and validity are verified by comparing and analyzing it with the traditional TOPSIS method based on a distance measure and other existing decision methods.
Knee cartilage MR images segmentation based on multi-dimensional hybrid convolutional neural network
Authors: Chen Wenda , Shi Cao
Published: January 2024

Accurate segmentation of knee cartilage in MR images is crucial for early diagnosis and treatment of knee conditions. Manual segmentation is time-consuming, leading researchers to explore automatic deep learning methods. However, the choice between 2D and 3D networks for organ segmentation remains debated. In this paper, we propose a hybrid 2D and 3D deep neural network approach, named UVNet, which combines the strengths of both techniques to enhance segmentation performance. Within this network structure, the 3D segmentation network serves as the backbone for feature extraction, while the 2D segmentation network functions as an information supplement network. Local and global MIP images are generated by employing various maximum intensity projection modes of knee MRI volumes as input for the information supplement network. By constructing a local and global MIP feature fusion module, the supplementary information obtained from the 2D segmentation network is fully integrated into the backbone network. We assess the quality of the proposed method using the Osteoarthritis Initiative (OAI) dataset and the 2010 Grand Challenge Knee Image Segmentation (SKI-10) dataset, comparing it to the Baseline Network and other advanced 2D and 3D segmentation methods. The experiments demonstrate that UVNet achieves competitive performance in the aforementioned two cartilage segmentation tasks.
Dilated convolution for enhanced extractive summarization: A GAN-based approach with BERT word embedding
Authors: Wu Huimin
Published: January 2024

Text summarization (TS) plays a crucial role in natural language processing (NLP) by automatically condensing and capturing key information from text documents. Its significance extends to diverse fields, including engineering, healthcare, and others, where it offers substantial time and resource savings. However, manual summarization is a laborious task, prompting the need for automated text summarization systems. In this paper, we propose a novel strategy for extractive summarization that leverages a generative adversarial network (GAN)-based method and Bidirectional Encoder Representations from Transformers (BERT) word embedding. BERT, a transformer-based architecture, processes sentence bidirectionally, considering both preceding and following words. This contextual understanding empowers BERT to generate word representations that carry a deeper meaning and accurately reflect their usage within specific contexts. Our method adopts a generator and discriminator within the GAN framework. The generator assesses the likelihood of each sentence in the summary while the discriminator evaluates the generated summary. To extract meaningful features in parallel, we introduce three dilated convolution layers in the generator and discriminator. Dilated convolution allows for capturing a larger context and incorporating long-range dependencies. By introducing gaps between filter weights, dilated convolution expands the receptive field, enabling the model to consider a broader context of words. To encourage the generator to explore diverse sentence combinations that lead to high-quality summaries, we introduce various noises to each document within our proposed GAN. This approach allows the generator to learn from a range of sentence permutations and select the most suitable ones. We evaluate the performance of our proposed model using the CNN/Daily Mail dataset. The results, measured using the ROUGE metric, demonstrate the superiority of our approach compared to other tested methods. This confirms the effectiveness of our GAN-based strategy, which integrates dilated convolution layers, BERT word embedding, and a generator-discriminator framework in achieving enhanced extractive summarization performance.
PmcaNet: Pyramid multiscale channel attention network for electron microscopy image segmentation
Authors: Gao Kaihan , Ju Yiwei , Li Shuai , Yang Xuebing , Zhang Wensheng , Li Guoqing
Published: January 2024

Recent advances in high-throughput electron microscopy (EM) have revolutionized the examination of microstructures by enabling fast EM image generation. However, accurately segmenting EM images remains challenging due to inherent characteristics, including low contrast and subtle grayscale variations. Moreover, as manually annotated EM images are limited, it is usually impractical to utilize deep learning techniques for EM image segmentation. To address these challenges, the pyramid multiscale channel attention network (PmcaNet) is specifically designed. PmcaNet employs a convolutional neural network-based architecture and a multiscale feature pyramid to effectively capture global context information, enhancing its ability to comprehend the intricate structures within EM images. To enable the rapid extraction of channel-wise dependencies, a novel attention module is introduced to enhance the representation of intricate nonlinear features within the images. The performance of PmcaNet is evaluated on two general EM image segmentation datasets as well as a homemade dataset of superalloy materials, regarding pixel-wise accuracy and mean intersection over union (mIoU) as evaluation metrics. Extensive experiments demonstrate that PmcaNet outperforms other models on the ISBI 2012 dataset, achieving 87.85% pixel-wise accuracy and 73.11% mean intersection over union (mIoU), while also advancing results on the Kathuri and SEM-material datasets.
RETRACTED: Optimizing solar power plant efficiency through advanced analytical framework and comparative analysis
Authors: Senthil Kumar V. , Aruna R. , Varalatchoumy M. , Manikannan P. , Santhana Krishnan T. , Usha Rani B. , Kumar Ashok , Rajaram A.
Published: January 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Leaf disease classification with Multiple-model deep learning
Authors: Tran-Anh Dat , Nguyen Huu Quynh , Nguyen Thi Phuong Thao , Dao Thi Thuy Quynh
Published: January 2024

The wilting of leaves caused by disease poses risks to both harvest yield and the environment. Therefore, the timely detection of disease signs on leaves is crucial to enable farmers to prevent disease outbreaks and safeguard their crops. However, manually observing all diseased leaves on a large scale demands substantial time and human effort. In this study, we propose an effective method for automated disease detection on leaves. Specifically, this method utilizes images captured from mobile phones. The proposed technique combines four models (ensemble of models) with distinct features: (1) ResNeXt50 model with a high-quality image processing, (2) ViT model with a low-quality image processing, (3) Efficientnet B5 model combines a self-learning with noisy input, and (4) Mobilenet V3 model with image segmentation. Experimental results demonstrate that the proposed method outperforms some of the state-of-the-art methods on TLU-Leaf dataset (ours) with F1-score of 90% and Cassava Leaf Disease dataset with F1-score of 87%.
Exploring measure of uncertainty via a discernibility relation for partially labeled real-valued data
Authors: Zhang Baishun , Su Xue
Published: January 2024

In practical applications of machine learning, only part of data is labeled because the cost of assessing class label is relatively high. Measure of uncertainty is abbreviated as MU. This paper explores MU for partially labeled real-valued data via a discernibility relation. First, a decision information system with partially labeled real-valued data (p-RVDIS) is separated into two decision information systems: one is the decision information system with labeled real-valued data (l-RVDIS) and the other is the decision information system with unlabeled real-valued data (u-RVDIS). Then, based on a discernibility relation, dependence function, conditional information entropy and conditional information amount, four degrees of importance on an attribute subset in a p-RVDIS are defined. They are calculated by taking the weighted sum of l-RVDIS and u-RVDIS based on the missing rate, which can be considered as four MUs for a p-RVDIS. Combining l-RVDIS and u-RVDIS provides a more accurate assessment of the importance and classification ability of attribute subsets in a p-RVDIS. This is precisely the novelty of this paper. Finally, experimental analysis on several datasets verify the effectiveness of these MUs. These findings will contribute to the comprehension of the essence of the uncertainty in a p-RVDIS.
UPAYA PENINGKATAN KINERJA PELAYANAN SURAT KETERANGAN CATATAN KEPOLISISAN (SKCK) DI POLRES SLEMAN
Authors: Untoro Agung , Chasanah Uswatun
Published: January 2024

This study aims to improve the service of SKCK (Police Records Certificate) at the Sleman Police. Data collection techniques by interview, observation and literature study. The problem discussed is the performance of the Sleman Police in the service of the Police Record Certificate (SKCK) which is not yet optimal. The purpose of this study was to find out the obstacles that resulted in the SKCK service not being optimal at the Sleman Police, to find out the efforts made to overcome the problem of the non-optimal SKCK service at the Sleman Police. This research is oriented to qualitative descriptive, namely research that describes or describes the results of data collection and processing along with information from sources. The results showed that: 1) Obstacles in SKCK services at Polres Sleman were: a) Lack of technology updates and their mastery by officers. b) Insufficient number of officers. c) Facilities and infrastructure are limited in number. d) The service area is less spacious. 2) Efforts made so that SKCK services can be optimal are: a) Creating an online application for online SKCK applications. b) The need for additional service personnel. c) Training or capacity building for officers. d) Addition of facilities and infrastructure to support services such as generators, computers and laptops. e) Expansion of SKCK service places and facilities for persons with disabilities.
PENGARUH PERSEPSI HARGA, LOKASI DAN KUALITAS PELAYANAN TERHADAP KEPUASAN PELANGGAN PADA MATAPISAU BARBERSHOP YOGYAKARTA
Authors: Fitrianto Heri , Wikaningtyas Suci Utami
Published: January 2024

Penelitian ini bertujuan unntuk mengetahui; pengaruh persepsi harga terhadap kepuasan pelanggan Matapisau Barbershop, pengaruh lokasi terhadap kepuasan pelanggan Matapisau Barbershop, pengaruh kualitas pelayanan terhadap kepuasan pelanggan Matapisau Barbershop, pengaruh persepsi harga, lokasi, dan kualitas pelayanan terhadap kepuasan pelanggan Matapisau Barbershop. Penelitian ini merupakan penelitian survei. Dalam penelitian survei, informasi yang dikumpulkan dari responden dengan menggunakan kuesioner. Populasi pada penelitian ini adalah seluruh pelanggan Matapisau Barbershop di Yogyakarta. Penelitian survei ini adalah pengumpulan data yang menggunakan instrument kuesioner atau wawancara untuk mendapatkan tanggapan dari responden. Teknik pengambilan data menggunakan purposive sampling dengan jumlah sebanyak 100 orang. Teknik analisis data yang digunakan adalah signifikan pengaruh parsial (Uji t). Hasil penelitian menunjukan bahwa; (1) persepsi harga tidak berpengaruh terhadap kepuasan pelanggan, dibuktikan nilai t hitung 2,860 dengan nilai signifikansi sebesar (Sig.) 0,05 lebih besar dari 0,05 (0,05>0,05) dan koefisien regresi mempunyai nilai positif besar 0,242, (2) lokasi berpengaruh terhadap kepuasan pelanggan, dibuktikan dari nilai t hitung 3,607 dengan nilai signifikansi sebesar (Sig.) 0,00 lebih kecil dari 0,05 (0,05<0,00) dan koefisien regresi mempunyai nilai positif 0,316, (3) Kualitas pelayanan berpengaruh terhadap kepuasan pelanggan, dibuktikan dari nilai t hitung 5,738 dengan nilai signifikansi sebesar (Sig.) 0,00 lebih kecil dari 0,05 (0,05<0,00) dan koefisien regresi mempunyai nilai positif 0,409. (4) Terdapat pengaruh persepsi harga, lokasi, dan kualitas pelayanan secara bersama-sama terhadap kepuasan pelanggan, dibuktikan dari nilai F hitung sebesar 173,077 dengan signifikansi sebesar 0,000. Oleh karena itu nilai signifikansi lebih kecil dari 0,05 (0,000<0,05).
PENGARUH PRODUK, HARGA, LOKASI, DAN PROMOSI TERHADAP MINAT BELI PENGUNJUNG PUSAT OLEH OLEH ADREM KHAS SANDEN BANTUL
Authors: Selviyani Siska Hervina , Zurida Lukia
Published: January 2024

ABSTRAK

Penelitian ini bertujuan : 1) Untuk mengetahui pengaruh produk, harga, lokasi dan promosi secara parsial terhadap Minat Beli Konsumen di Pusat Oleh Oleh Adrem Khas Sanden Bantul. Variabel penelitian ini adalah produk, harga, lokasi, promosi dan minat beli. Populasi dalam penelitian ini adalah seluruh pengunjung pusat oleh-oleh Adrem Khas Sanden Bantul. Tekning sampling yang digunakan dalam penelitian ini adalah purposive sampling. Teknik purposive sampling adalah teknik penentuan sampel dengan pertimbangan tertentu. Metode pengambilan data menggunakan kuesioner. Teknik analisis yang digunakan adalah regresi linier berganda dengan taraf signifikansi 5%. Hasil penelitian diperoleh Produk berpengaruh positif dan signifikan terhadap minat beli. Artinya produk menjadi faktor penentu minat beli konsumen produk Adrem Khas Sanden Bantul. Harga berpengaruh positif dan signifikan terhadap minat beli. Artinya harga menjadi faktor penentu minat beli konsumen produk Adrem Khas Sanden Bantul. Lokasi berpengaruh positif dan signifikan terhadap minat beli. Artinya lokasi menjadi faktor penentu minat beli konsumen produk Adrem Khas Sanden Bantul. Promosi berpengaruh positif dan signifikan terhadap minat beli. Artinya promosi menjadi faktor penentu minat beli konsumen produk Adrem Khas Sanden Bantul.
Literasi Pasar Modal dan Hukum Investasi untuk Mahasiswa Tingkat Akhir Universitas Pasir Pengaraian
Authors: Sudarman Sudarman , Elfiani Fitri
Published: January 2024

Tujuan dari kegiatan pengabdian kepada masyarakat ini adalah untuk meningkatkan lieterasi investasi dan hukum investasi bagi mahasiswa tingkat akhir universitas pasir pengaraian. Metode pelaksanaan yang dilakukan yaitu dengan merumuskan masalah, merencakan kegiatan, memilih tehnik dan materi, menentukan peserta dan melakukan seminar. Sasaran kegiatan yaitu mahasiswa tingkat akhir universitas pasir pengaraian yang dihadiri oleh 39 peserta. Kegiatan pengabdian kepada masyarakat ini diharapkan mampu memberikan sudut pandang baru bagi mahasisa tentang investasi, meningkatkan minat investasi, dan pengayaan keilmuan terkait aspek hukum dalam investasi.Hasil dari kegiatan Pengabdian masyarakat ini yaitu berupa peningkatan literasi dan hukum investasi, peningkatan minat investasi saham di kalangan mahasiswa. Tindak lanjut yang diharapkan yaitu adanya wadah lanjutan untuk menampung dan membimbing mahasiswa yang tertarik pada investasi saham agar mendapatkan ilmu lebih lanjut terkait investasi saham.
Upaya Peningkatan Pemasaran dan Branding Melalui Digital Marketing Oleh Pelaku UMKM di Desa Pendreh
Authors: Asmawati Asmawati , Alamsyah Sukron , Maulida Sarinah , Kamaliah Nor , Damayanti Anisa , Pratama Yogi
Published: January 2024

Desa Pendreh, yang terletak di Kabupaten Barito Utara, Provinsi Kalimantan Tengah, Indonesia, memiliki potensi besar dalam sektor Usaha Mikro, Kecil, dan Menengah (UMKM). Beberapa sektor UMKM, seperti produksi makanan ringan dan kerajinan rotan, menjadi tulang punggung ekonomi desa ini. Namun, pelaku UMKM di Pendreh menghadapi sejumlah kendala yang perlu diperhatikan. Kendala utama termasuk pemahaman yang terbatas tentang pentingnya branding produk dalam pemasaran, kurangnya pemahaman tentang identitas usaha, dan kesulitan dalam mencapai pasar yang lebih luas. Dalam upaya untuk mengatasi masalah ini, Kelompok KKN 23 dari IAIN Palangkaraya menginisiasi program untuk memberikan sosialisasi tentang pemasaran digital dan desain logo bagi pelaku UMKM di Desa Pendreh. Hasilnya adalah pemahaman yang ditingkatkan di antara pelaku UMKM tentang strategi pemasaran modern dan cara efektif dalam membangun merek produk mereka. Mereka juga berhasil memanfaatkan media digital untuk mempromosikan dan menjual produk mereka. Program ini berhasil dilaksanakan dengan antusiasme tinggi dari pelaku UMKM yang berpartisipasi. Sosialisasi pemasaran digital ini tidak hanya membantu membangun merek produk, tetapi juga berkontribusi secara signifikan pada pertumbuhan ekonomi keseluruhan Desa Pendreh. Dengan pemahaman yang lebih baik tentang strategi pemasaran modern, UMKM dapat bersaing lebih efektif dan meningkatkan penjualan produk mereka, memberikan dampak positif pada ekonomi desa.
Literasi Media Pembelajaran Pada Anak Usia Dini
Authors: Sulistiyaningsih Riski , Ardianingsih Arum
Published: January 2024

Tujuan kegiatan Pengabdian kepada Masyarakat (PKM) adalah memberikan tambahan pengetahuan mengenai media pembelajaran yang dapat digunakan untuk anak-anak selama proses pembelajaran di sekolah.Metode dalam kegiatan Pengabdian kepada Masyarakat adalah metode survey, observasi, dan game. Materi yang diberikan dalam kegiatan ini adalah mengenal angka dan huruf untuk anak usia dini. Adapun kegiatan game yang merupakan inti dari kegiatan PkM ini diikuti oleh para siswa TK B di TK Batik PPIP di Kota Pekalongan. Permainan (game) yang diterapkan dalam kegiatan proses belajar pada kegiatan pengabdian kepada Masyarakat adalah permainan ular tangga. Hasil yang didapatkan menunjukkan bahwa para siswa sangat antusias dalam mengikuti kegiatan belajar angka dan huruf melalui permainan (game) ular tangga, karena kegiatan ini melibatkan aktivitas fisik yang menyenangkan bagi siswa. Para siswa cenderung lebih mudah mengenal kosakata baru dengan cara bermain sambil belajar.