bluuebunny/crossref_metadata_2025 huggingface dataset:
IMPLIKASI PERATURAN MENTERI LINGKUNGAN HIDUP NOMOR 83 TAHUN 2016 TENTANG PERHUTANAN SOSIAL TERHADAP SWADAYA EKONOMI MASYARAKAT DALAM PROGRAM PERHUTANAN SOSIAL
Authors: Sami Rima Gulam
Published: December 2023

Pengelolaan hutan, industri kehutanan yang ekstraktif dan pencurian kayu ilegal yang berlangsung di akhir 1990-an telah mengurangi luas hutan Indonesia dari 162 juta hektar menjadi 98 juta hektar. Dari 70 ribu desa di Indonesia, 30 ribuan desa berada di dalam dan sekitar kawasan hutan, di mana 70% penduduknya menggantungkan hidupnya dari sumber daya hutan. Banyak komunitas lokal di lingkungan kawasan hutan yang tidak memiliki akses legal terhadap sumber daya hutan yang ada di sekitar mereka, dan hingga saat ini hanya terdapat kurang dari 1 juta hektar lahan di kawasan hutan yang secara legal telah dikelola oleh komunitas lokal dan diberikan ijin pengelolaan hutannya oleh negara. Untuk mengani hal tersebut, Pada tahun 2002, Menteri Kehutanan pernah mengeluarkan pernyataan bahwa perhutanan sosial akan menjadi payung bagi lima kebijakan prioritas Departemen Kehutanan. Kemudian pada tahun 2016 pemerintah menerbitkan Peraturan Menteri No 83 Tahun 2016 tentang Perhutanan Sosial yang di dalamnya terdapat tata c ara untuk memberikan pedoman pemberian hak pengelolaan, perizinan, kemitraan dan Hutan Adat di bidang Perhutanan Sosial yang bertujuan untuk menyelesaikan permasalahan tenurial dan keadilan bagi masyarakat setempat dan masyarakat hukum adat yang berada di dalam atau di sekitar kawasan hutan dalam rangka kesejahteraan masyarakat dan pelestarian fungsi hutan. Permasalahan yang diteliti dalam penelitian ini adalah: Pertama: Bagaimana implikasi Peraturan Menteri Lingkungan Hidup Nomor 83 Tahun 2016 tentang Perhutanan Sosial terhadap swadaya ekonomi masyarakat dalam program Perhutanan Sosial Pada Kelompok Tani Nagari Latang Kab. Sijunjung? Kedua: Bagaimana efektivitas program perhutanan sosial terhadap peningkatan perekonomian kelompok tani Nagari Latang Kab. Sijunjung? Berdasarkan hasil penelitian yang telah dilakukan, Implikasi Peraturan Menteri Lingkungan Hidup Nomor 83 Tahun 2016 Tentang Perhutanan Sosial secara nyata telah memberikan dampak positif dalam rangka peningkatan ekonomi masyarakat di Nagari Latang. Program Perhutanan Sosial telah menumbuhkambangkan usaha-usaha baru di Nagari Latang seperti pengelolaan madu, pengelolaan teh asam gelugur, teh asam kandi, dan kopi asam gelugur. Sementara efektivitas program perhutanan sosial terhadap peningkatan perekonomian masyarakat terlihat dari indicator: Efisiensi hutan kemasyarakatan sudah berjalan dengan baik dan masyarakat sudah dapat merasakan manfaat berupa tambahan penghasilan dari hasil pengelolaan lahan HKm. Adil, dalam artian pengelolaan lahan HKm yang dilakukan oleh masyarakat tidak merusak alam. Moral, dalam artian penggarapan lahan HKm tidak mengubah status dan fungsi hutan, karena status HKm tetap sebagai hutan lindung.
FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN
Authors: Martianto Ishma Alfisa , Iriani Sri Setyo , Witjaksono Andre Dwijanto
Published: December 2023

Tujuan utama sebuah perusahaan adalah memberikan lebih banyak pilihan kepada pelanggan dan memudahkan pelanggan dalam menentukan keputusan. Dalam menjalankan bisnisnya, sebuah faktor yang mempengaruhi keputusan pembelian adalah Brand Ambassador, Brand Experience dan Brand Image. Penelitian ini menganalisis pengaruh Brand Ambassador, Brand Experience dan Brand Image terhadap keputusan pembelian produk Somethinc. Penelitian ini bersifat kuantitatif. Populasi dan sampel penelitian ini adalah konsumen Somethinc, teknik Purposive Sampling digunakan untuk memilih sampel dari yang mewakili 136 responden. Hasil analisis statistik menunjukkan Brand Ambassador tidak berpengaruh signifikan terhadap Keputusan Pembelian, Brand Experience dan Brand Image berpengaruh signifikan terhadap Keputusan Pembelian, Brand Ambassador berpengaruh signifikan terhadap Brand Image dan Brand Ambassador berpengaruh signifikan secara tidak langsung melalui Brand Image terhadap Keputusan Pembelian. Penelitian ini menyiratkan penerapan Brand Image dan Brand Experience yang bagus dapat meningkatkan Keputusan Pembelian Konsumen terhadap produk Somethinc.
THE INFLUENCE OF EMPLOYEE TRAINING, COMPENSATION AND EMPLOYEE CREATIVITY ON INNOVATIVE BEHAVIOR
Authors: Maulana Ramli , Wijanarko Adrian Azhar
Published: December 2023

The existence of companies in the era of modernization really requires innovation to be able to compete. By using innovation, companies can provide better service to consumers and add value to the products they produce. PT. Jakarta Transportation has company values which encourage creativity summarized in the tagline "BISA". The respondents selected were 100 employees of PT Transportation Jakarta. There are 30 questions were distributed to respondents. The research results stated that training had no impact on innovative behavior. This is caused by inappropriate training methods. Apart from that, compensation and employee creativity have an impact on Transjakarta's innovative behavior
Pengembangan Multimedia Interaktif Menggunakan Aplikasi Articulate Storyline 3 pada Mata Pelajaran PAI dan Budi Pekerti di SMA 2 Padang Panjang
Authors: Hakim Nurdiah , Pebrina Rizki
Published: December 2023

This study was motivated by the rapid development of information technology, which has had a positive impact to the world of education. An educator must be able to use information technology and be innovative in the learning process, including the use of technology-based learning media that is interesting, fun, and easy to understand for students. Therefore, the Articulate Storyline 3 application must be used to change learning media. The purpose of this study is to determine the validity and practicality of interactive multimedia using the Articulate Storyline 3 application in Islamic Education and Character subject at SMA 2 Padang Panjang. This study is research and development using ADDIE development model, which has five stages: Analyze, Design, Develop, Implement, and Evaluate. Sources of data were observation, interview, validity, practicability, and documentation. The research findings revealed that the validity of interactive multimedia was 0.860 in the "highly valid" category, and the practicality testing of interactive multimedia was 0.925 in the "very practical" category. Thus, it can be concluded that interactive multimedia in Islamic Education and Character subject, as well as other scientific fields, is very suitable for use in learning activities.
Latihan Batuk Efektif Dalam Meningkatkan Kemampuan Pengeluaran Sputum Pada Lansia Dengan Gangguan Saluran Pernapasan
Authors: Marwansyah Marwansyah , Endang Sri Purwanti Ningsih  , Iswiyanti Novita
Published: December 2023

Background: An ineffective cough condition will have an impact on increasing energy use which makes the patient feel tired quickly, decreased appetite, weight loss if this continues can cause bradypnoea (decreased respiratory rate) to apnoea. The client's goal is to gain increased knowledge, attitudes and skills in the health sector, especially respiratory problems and effective cough practice independently. Method: this community service uses education and simulation. Results: Most clients can identify health problems in the elderly, especially respiratory disorders such as Pneumonia, Bronchitis, Asthma, COPD, Pulmonary TB and clients can demonstrate effective coughing techniques in overcoming respiratory problems. It is hoped that before being given coughing exercises it is very effective to give warm fluids orally as much as 250 – 500 ml which is taken 2 hours before practice and the effect can help the phlegm become thinner making it easier to expel phlegm when coughing
Kolesterol dan Tekanan Darah Lansia di Posyandu Abiyoso Polkesbaya
Authors: Christyaningsih Juliana , Luthfi Rusyadi  , Minarti Minarti , Mamik  , Pestariati  , Diah Titik Mutiarawati  , Suliati  , Retno Sasongkowati  , Evy Diah Woelansari  , Suhariyadi  , Wisnu Istanto  , Lully Hanni Endarini  , Museyaroh
Published: December 2023

Pada masa lanjut usia, kondisi fisik seseorang akan mulai menurun akibat penurunan jumlah sel dalam tubuh, sehingga mengakibatkan penurunan fungsi perlahan yang dinamakan sebagai penuaan. Pada manusia lanjut usia (umur lebih dari 60 tahun) kadar kolesterol berlebih dan tingginya tekanan darah merupakan salah satu penyebab timbulnya penyakit-penyakit seperti penyakit jantung yang telah diakui WHO sebagai penyebab nomor satu kematian di dunia. Meningkatnya penumpukan deposit lemak pada dinding pembuluh darah dapat mengakibatkan penyumbatan pembuluh darah yang serius. Penelitian ini bertujuan untuk meningkatkan kesadaran di kalangan warga mengenai risiko tingginya kadar kolesterol dalam tubuh. Kegiatan pengabdian ini diadakan pada bulan Juli 2023 dan berlokasi di Posyandu Abiyoso Politeknik Kesehatan Surabaya. Rangkaian kegiatan melibatkan beberapa tahap, yaitu: 1) survey lokasi di Posyandu Abiyoso Politeknik Kesehatan Surabaya, 2) pendaftaran peserta dan pengumpulan data pribadi, 3) wawancara kesehatan dengan peserta, serta 4) pengukuran kadar kolesterol dan tekanan darah peserta. Dari kegiatan pengabdian masyarakat yang dilakukan, didapati 42 (64,6%) dari 65 peserta lanjut usia Kertajaya yang mengikuti pemeriksaan di posyandu memiliki kadar kolesterol yang tinggi, dan 60 (92,3%) dari 65 peserta memiliki tekanan darah tinggi atau hipertensi. Dengan diadakan pemeriksaan kesehatan kadar kolesterol dan tekanan darah, diharapkan peserta dapat menyadari bahaya hipertensi dan kolesterol tinggi sehingga setiap orang dapat mencegah timbulnya penyakit jangka panjang.
Kontrol Kesehatan, Promkes dan Aktifitas Fisik Pada Lansia Wilayah Puskesmas Banjarbaru Utara Dan Martapura1
Authors: Ilmi Bahrul , Fauziah Erna , Rizani Akhmad
Published: December 2023

Angka tertinggi Covid-19  kelurahan Banjarbaru Utara, sebanyak 2237 kasus,  dipantau 110, dirawat 24 orang sumber data Dinas Kesehatan Kota Banjarbaru (2022) Hipertensi dan Diabetes merupakan komorbid yang dapat memperparah infeksi virus Covid-19, dan menjadi penyebab kematian tertinggi pada penderita Covid-19 berdasarkan laporan CNN Indonesia (2020). Tujuan melaksanakan peningkatan kapasitas Lansia melalui Kontrol kesehatan, promosi kesehatan; konsep Era Normal Covid-19, pentingnya menjaga imun tubuh, dan penyakit komorbid Hipertensi serta melakukan aktifitas fisik.

Hasil pengabdian masyarakat; hipertensi pada Lansia cukup tinggi sebanyak 47% dengan resiko komorbid Covid-19, penyakit jantung, serta stroke. hasil pemeriksaan lansia untuk Glukosa sampai 19%, Cholesterol mengalami peningkatan sampai 88% dan Asam urat sampai dengan 33%. Kontrol kesehatan, penyuluhan, senam Lansia dan Anti stroke, tidak serta merta dapat menurunkan Tekanan darah lansia, namun tetap dapat mempertahankan kesehatannya agar tekanan darah dalam batas normal.
Pemanfaatan Buku Kia Untuk Optimalisasi 1000 Hari Pertama Kehidupan Di Wilayah Kelurahan Palam
Authors: Rohmah Nur , Hapisah  , Daiyah Isrowiyatun , Megawati  , Rizani Ahmad , Ismarini Novi
Published: December 2023

1000 Hari Pertama Kehidupan merupakan masa periode emas dimana terjadi proses tumbuh kembang yang sangat pesat dimulai sejak masa janin  sampai  anak  usia  dua  tahun dan tidak terjadi pada  kelompok  usia  lain. Upaya kesehatan ibu dan anak, bayi yang sehat dan bertumbuh kembang optimal serta untuk menjaga kualitas sumber daya manusia Indonesia, produktifitas, dan daya saing bangsa diperlukan media Komunikasi, Informasi dan Edukasi serta pencatatan yang efektif dan efisien. Sehingga Kementerian Kesehatan menetapkan bahwa Buku Kesehatan Ibu dan Anak (Buku KIA) menjadi alat pencatatan pelayanan kesehatan ibu dan anak sejak ibu hamil, melahirkan, nifas, dan bayi yang dilahirkan mencapai usia 5 tahun, termasuk pelayanan imunisasi, gizi, tumbuh kembang anak dan KB. Kementerian Kesehatan telah mencetak dan mendistribusikan Buku KIA ke daerah sejumlah 94% dari jumlah sasaran ibu hamil, dan seluruh Puskesmas telah menerima Buku KIA yang didistribusikan Dinas Kesehatan Kab/Kota. Data survei kesehatan nasional (2016) menunjukkan sebanyak 81,5% ibu hamil menyatakan memiliki Buku KIA, namun hanya 60,5% di antaranya yang bisa menunjukkan buku KIA. Metode pada kegiatan pengabdian masyarakat ini adalah bentuk program promosi kesehatan dan pemberdayaan masyarakat melalui penyuluhan kepada ibu hamil dalam memanfaatkan buku KIA. Penyuluhan tentang pemanfaatan buku KIA untuk optimalisasi 1000 hari pertama kehidupan di Kelurahan Palam didapatkan hasil bahwa terjadi peningkatan pengetahuan pada ibu hamil setelah dilakukan penyuluhan. Pengetahuan yang baik dapat meningkatkan pemanfaatan Buku KIA menjadi lebih efektif dan optimal. Perlu adanya evaluasi lanjut terkait pengetahuan Ibu hamil tentang pemanfaatan buku KIA.

Kata kunci: Buku KIA, Ibu Hamil, Anak
PENYULUHAN DAN PELATIHAN PENCEGAHAN MALARIA SERTA DETEKSI DINI MALARIA DAN ANEMIA DENGAN PEMERIKSAAN LABORATORIUM PADA PEKERJA PROYEK PENGHIJAUAN DI KECAMATAN ARANIO KABUPATEN BANJAR
Authors: Rifqoh Rifqoh
Published: December 2023

Malaria masih menjadi masalah di Indonesia maupun di dunia dan angka kesakitan dan kematiannya yang cukup tinggi, disebabkan oleh gigitan nyamuk Anopheles yang membawa parasit Plasmodium.sp. Malaria berdampak pada penurunan kadar hemoglobin dalam darah yang menjadi penyebab terjadinya anemia. Pekerja hutan merupakan individu rentan terhadap malaria dan anemia. Keterbatasan pengetahuan tentang pencegahan malaria dan anemia dapat menjadi faktor peningkatan kejadian malaria dan anemia. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pengetahuan tentang penyakit malaria, meningkatkan sikap dan perilaku pencegahan malaria, mendeteksi malaria dan anemia pada pekerja dengan pemeriksaan laboratorium. Metode pelaksanaan berupa penyuluhan dan pelatihan, kuesioner, observasi, pemeriksaan laboratorium untuk deteksi malaria yaitu Rapid Diagnostic Test (RDT) dan Mikroskopis malaria, serta pemeriksaan kadar hemoglobin (Hb) metode Point of Care Testing (POCT) sebagai indikator anemia pada spesimen darah 50 pekerja hutan proyek penghijauan di Kecamatan Aranio. Hasil kegiatan ini meningkatkan pengetahuan, sikap dan perilaku responden terhadap pencegahan malaria menjadi 100% baik setelah kegiatan penyuluhan, pemeriksaan laboratorium malaria baik RDT maupun mikroskopis 100% negatif malaria. Kadar Hb didapatkan berkisar dari 8,4 gr/dl sampai dengan 15,2 g/dl dimana 35 orang (70%) normal dan 15 orang (30%) di bawah batas normal. Luaran lain dari kegiatan ini adalah dibentuknya kelompok masyarakat (pokmas) “Kelaan Tangkal dan Cegah Penularan (Tanggap) Malaria”. Disarankan untuk pengabdian masyarakat selanjutnya agar melanjutkan dengan program lainnya berbasis konsep desa sehat yang mendukung terwujudnya transformasi kesehatan di Indonesia.

Kata kunci: Penyuluhan, Pengetahuan, Malaria, Anemia, Pekerja Hutan
UJI KANDUNGAN TANIN DAUN SALAM (SIZYGIUM POLYANTHUM) MENGGUNAKAN BERBAGAI KONSENTRASI ETANOL
Authors: Soraya Soraya
Published: December 2023

Ekstrak daun salam mengandung alkaloid, flavonoid, saponin, steroid, terpenoid, minyak atsiri , sitral, dan eugenol, tanin. Tanin diketahui merupakan senyawa aktif metabolit sekunder yang memiliki berbagai manfaat dalam pengobatan dan industri makanan, karena memiliki sifat antioksidan, antibakteri, anti diare dan antitumor. Sampel daun salam yang digunakan dalam penelitian ini berasal dari daerah Banjarnaru, Kalimantan Selatan, Indonesia. Penelitian ini dilakukan dalam beberapa tahap, yaitu pengolahan bahan baku, pembuatan ekstrak, pemisahan ekstrak dan uji kadar tanin. Analisa produk menggunakan metode Spektrofotometri UV-Vis dengan larutan K₄Fe₆ dan FeCl₃ dan indikator asam galat. Dengan konsentrasi etanol 96% didapatkan kandungan tanin tertinggi yaitu 0,854 mg/mL dan kandungan kadar tanin terkecil pada konsentrasi 60% yaitu 0,188 mg/mL.
Effects of AI on Smart Agriculture: A Case Study of Digital Agriculture Base
Authors: Wang Dongxue , Rajamanickam Leelavathi
Published: December 2023

Smart agriculture in China still faces difficulties in the transformation of agricultural achievements by AI technology and the scattering of land. The current problems in smart agriculture are a serious shortage of talent, scattered data, a weak mass base, unfocused land and weak agricultural technology companies. To address the problems in the development of smart agriculture. Based on the earlier research, the hypothesis that AI technology plays a positive role in the development of smart agriculture. Combining case study and phenomenology of qualitative analysis theory, field observation, focus group discussion and in-depth interviews were used to conduct an in-depth qualitative analysis using the digital agriculture base as a typical smart agriculture construction. Artificial intelligence technology has been widely used in agricultural production, especially in the Digital Agriculture Base, and is an important part of the construction of smart agriculture. It has played a catalytic role in the development of the agricultural economy and the improvement of agricultural production efficiency. This paper explores the impact of AI technology on the development of smart agriculture, and the obstacles to implement AI technology into the construction of smart agriculture, with a view to propose strategies to sustainably promote the construction of smart agriculture. The results show that the hypothesis of AI technology has a positive effect on the construction of smart agriculture holds true.
Application of AI Algorithms in Power System Load Forecasting Under the New Situation
Authors: Rong Jian , Liu Xiaohua , Gao Kunyang
Published: December 2023

AI algorithms can analyze historical data, weather patterns, and other relevant factors to predict electricity demand. Accurate load forecasting helps in efficient power generation, resource allocation, and grid stability. They are utilized by energy providers, grid operators, and system planners for short-term load forecasting, medium-term capacity planning, and long-term demand projections. These algorithms support decision-making in power generation, resource allocation, load balancing, demand response, and grid stability management. This article provides a detailed explanation of the principles, steps, applicable conditions, and application scenarios of the most promising AI intelligent algorithms, and provide valuable literature research results.
Research on Water Supply Pipe Leakage Diagnosis Algorithm
Authors: Dou Likai , Wang Jie , Wang Baoren , Guan Shengfu , Wang Pengju , Su Ziao
Published: December 2023

In this paper, we address the difficult problems in pipeline leakage diagnosis and investigate the leakage diagnosis algorithm based on vibration signal analysis with pipeline vibration signal as the basis. The SSA-VMD algorithm is used to decompose the pipeline vibration signal and conduct comparative experiments. The results of the comparison experiments show the superiority of the SSA-VMD algorithm. Then the decomposed IMF components are feature extracted to construct single feature vectors and then combined feature vectors. Finally, the support vector machine is optimized using the improved grid search method, and comparative experiments are conducted for the single feature vector and the combined feature vector, respectively. The experimental results show that the support vector machine optimized by the improved grid search method has a higher recognition accuracy.
Design of a Graduate Employment Intelligent Recommendation System Based on Data Analysis Algorithms
Authors: Jiang Xiaolin , Wang Ruiyang
Published: December 2023

In response to the issues of indiscriminate employment and lengthy contract signing time for university graduates, this research investigates the relationship between graduate behavior and job demand. Taking the past graduates of several universities in Hubei province, China as the research subjects, this study proposes an improved algorithm, Apriori_S, based on the Spark computing framework, to enhance the execution efficiency and applicability of the original Apriori algorithm for analyzing complex datasets. The improved algorithm is applied to mine the association rules between past graduate data and employment information. Experimental analysis demonstrates that the improved algorithm has significantly higher execution efficiency compared to the original algorithm and is suitable for analyzing complex datasets with multiple dimensions. Finally, based on the mining results, an “employment stickiness” model is constructed, and a design for an intelligent job recommendation system for graduates is developed using data analysis algorithms, enabling intelligent job recommendations for employment positions.
The Application of Artificial Intelligence in Geotechnical Investigation
Authors: Mei Haifeng , Zhang Wei , Gu Jing
Published: December 2023

The standard penetration test (SPT) and dynamic probing test (DPT) are commonly used exploration methods in geotechnical investigation. However, errors can occur during data collection, often attributed to factors such as human error. To mitigate this issue, this paper proposes the utilization of an improved YOLOv5 object detection algorithm, a form of artificial intelligence technology, to automatically count the number of hammer strikes during geotechnical investigations. The proposed approach incorporates several enhancements to the YOLOv5 network architecture. Firstly, a focal loss function is introduced to address sample imbalance, ensuring better handling of different classes of hammer strikes. Additionally, online hard example mining technology is employed to improve model accuracy by focusing on challenging samples that are most informative for training. The improved YOLOv5 model is then applied to detect hammer strikes in SPT and DPT tests. To facilitate training and evaluation, a hammer detection dataset is created, tailored to the specific requirements of geotechnical investigation. Experimental results demonstrate the superior performance of the proposed improved YOLOv5 object detection model on the hammer detection dataset.
Research on WSN Node Localization and Identity Authentication System
Authors: Yuan Yusen
Published: December 2023

Currently, WSN is widely used, and it is important to obtain the location information of each node in real time for WSN where localization is the main function or where nodes are subject to unpredictable changes in location by different factors. In this paper, the traditional TDOA algorithm and the FDEM algorithm based on energy consumption are analyzed in the localization section, and the ANP analysis algorithm is analyzed in the identity section. The paper states the necessity and feasibility of combining localization and identity identification techniques, and proposes a general way to achieve self-testing coverage of WSN nodes by analogy with flooding mechanisms and routing protocols, and simulates the parameter changes under various scenarios through experiments. It can be deduced from the results that the quality and speed of the coverage are closely related to the node density and the number of neighbour nodes to receive the information. And according to the key problem of energy consumption in WSN, it is significant to find proper values of all the parameters to realize maximum efficiency in practice.
Research on Ship Fire Scenario Inference Based on Dynamic Bayesian Network
Authors: Xie Shuhao , Yin Yong
Published: December 2023

Aiming at the current situation where the evolution path of ship fire accidents is fuzzy and the evolution process is difficult to predict, making it difficult for fire rescue commanders to make efficient decisions as soon as possible, based on the investigation of the evolution rules of ship fire accident scenarios and three scenario elements: scenario events (I), objective environment (E), and emergency measures (M), combined with dynamic Bayesian networks, a scenario deduction model for ship fire accidents is obtained. Taking the “Xie Chuan Lun” fire accident as an example, the model was deduced through five steps: accident overview, scenario element determination, scenario network drawing, node variable probability determination, and probability calculation. The final result was obtained and analyzed, fully verifying the scientific and effective nature of the model.
Personalized Travel Recommendation System Based on Data Mining Technology
Authors: Nan Xiang , Parthasarathy Rajamohan , Wang Chu
Published: December 2023

With the continuous improvement of people’s living standards, tourism has been a rapid development. In the past, people’s biggest need for life was to have enough food and clothing, but now people have more time and money to relax through travel. The tourism industry has developed into a pillar industry chain supporting the national economy. The development of tourism can affect the gross domestic product (GDP) of a whole region, thus driving the development of regional economy, population and culture. However, with the improvement of people’s living quality, the demand is gradually expanding. In the past, if people could have the time and money to spend on travel, they would feel physically and mentally happy. Now people have been used to a high-quality lifestyle, so the pursuit of tourism has become diversified, some people pursue the process of tourism, some pursue the results of tourism, which also leads to the endless types of tourism industry, so in order to meet people’s increasingly personalized demand for tourism, it is necessary to use data mining technology to design a set of personalized tourism recommendation system. The system can provide users with personalized recommendations and services according to the data information of users’ browsing and collection of tourism pages, as well as other customer information with similar preferences. A questionnaire survey was designed based on the feelings before and after the use of the system. The survey results show that 399 people think scenic spot service is more personalized. Before the system was used, only 181 people thought scenic spots were personalized, and 392 people thought tourist spots were convenient, up from 169. Therefore, it can be shown that people have a high satisfaction index for this personalized travel recommendation system. This study provides reference value for tourism.
Design and Implementation of “Fighting and Dream” E-Sports Data Management System
Authors: Mao Tingting , Lu Junwei
Published: December 2023

With the rapid development of modern information technology, an industry named “E-sports” was born. The significance of this project lies in providing convenience for E-sports management through the Spring Boot, Vue.js and Mybatis development system. In this system, players can query event data or training arrangements, complete their training tasks in a timely manner, or provide feedback to coaches. Players need to check the official competition arrangements through the system to participate in the competition. Coaches can query the competition data and schedule of players, arrange training arrangements for each player in their team, or provide feedback to the organizers. The organizer can not only arrange the competition and publish it in the system, but also make modifications to various details such as the competition.
Improved Faster RCNN-Based Metal Particle Detection on the Inner Surface of GIS Equipment
Authors: Lv Chao , Shi Chunyu , Xu Baoquan
Published: December 2023

To focus on the problem of low detection rate of metal particles on the inner surface of GIS equipment, an improved Faster RCNN GIS equipment inner surface metal particle target detection network is proposed.The residual network is introduced as the feature extraction network based on the feature of small metal particles on the inner surface, and the feature pyramid network and receptive field block are combined with the residual network,three feature extraction networks, VGG16, ResNet50,ResNet50+RFB-FPN, are used to experimentally compare 2000 metal particle maps.The results show that the accuracy and recall of ResNet50+RFB-FPN feature extraction network are 97.3% and 83.4%, which are improved compared with both VGG16 network and ResNet50 network. It is concluded that the improved Faster RCNN-based metal particle identification on the inner surface of GIS equipment can meet the requirements of detection accuracy and speed.
Research on Risk Evolution of Online Food Delivery Platforms Based on Fuzzy Cognitive Map
Authors: Song Wen , Zhang Yimeng , Zhang Jianxin , Jin Jiayi
Published: December 2023

The rapid growth of the online food delivery market in China has led to a range of risk issues, including food safety and delivery transportation risks. This article aims to address these risks by establishing a fuzzy cognitive map for online food delivery platforms (Taking Meituan as an example) and studying the evolutionary characteristics of these risks. Firstly, a risk criteria system is developed considering multiple business scenarios such as online service, consumption activity, offline service and offline management. Secondly, a fuzzy cognitive map is constructed to represent the relations between risk criteria. Finally, the risk feature evolution results are obtained using the iterative algorithm of the fuzzy cognitive map. By analyzing these results, suggestions for risk management in online food delivery platforms are proposed.
Multi-Scale Segmentation Attention-Based Residual Network for Fault Diagnosis of Rolling Bearings
Authors: Chen Duo , Lai Yuehua , Yang Changjun , Huang Chunhua , Li Wei , Gao Hong , Niu Lei
Published: December 2023

Rolling bearings are widely used in coal mine equipment, real-time monitoring of bearing status and intelligent diagnosis of bearing fault is very important to the safe and efficient mining of coal mine. In order to solve the problem of insufficient representation ability about fault diagnosis model, a multi-scale segmentation attention-based residual network is proposed for the fault diagnosis of rolling bearings, which can fully and accurately extract vibration signal features to realize intelligent diagnosis. For time-frequency images of vibration signals, residual networks was used for feature extraction. Furthermore, the pyramid split attention mechanism was combined to optimize the feature selection to construct the intelligent diagnosis model for bearing. The proposed method has been applied to the task of fault diagnosis on SKF6205 bearing, and the experimental results show its superior diagnostic performance.
Design Logistics Management System Based on Computer Algorithm Model
Authors: Sun Hualin
Published: December 2023

Logistics management system is a kind of computer software system used to manage logistics process. It can help logistics companies manage and coordinate various logistics activities, such as cargo tracking, inventory management, transportation management, order processing, etc. Logistics management systems can improve the efficiency and accuracy of logistics companies, thereby reducing logistics costs and improving customer satisfaction. The logistics management system based on ant colony model is a method to optimize the logistics management by using the collective behavior of insects. The main idea of this method is to make the logistics management system better cope with the complex environment and uncertainty by simulating the navigation and decision-making behavior of ants. In this system, ant behavior is abstracted into a series of algorithms that can be used to optimize problems such as path planning, inventory management, and distribution route selection in logistics management. For example, the ant colony algorithm can be used in the system to solve the complex path planning problem, which can realize the optimal path planning without considering the time and terrain constraints.
A Survey on Masked Face Recognition Amid the COVID-19 Pandemic
Authors: Zhong Shanmei
Published: December 2023

Against the backdrop of the COVID-19 pandemic, the ubiquitous adoption of masks has caused significant hurdles to conventional face recognition technologies and their applications. In order to address these problems, a great deal of research related to masked face recognition has been put forward. Although masked face recognition has made great progress, the review or summary about this field is scanty. Therefore, this paper proposed a survey on masked face recognition. Firstly, the datasets of MFR and the mainstream deep learning methods are introduced. In addition, some common evaluation metrics are explained. Finally, this paper discusses the potential challenges of MFR and make conclusion.
Fine-Grained Classification of Wild Fungi Based on Attention Residual Mechanism
Authors: Wen Shuoyi , Yang Li , Duan Hailong , Zhang Tingting
Published: December 2023

Identifying wild mushroom species are an important way to prevent poisoning from consuming toxic wild mushrooms. Therefore, an attention-based method for fine-grained classification of wild mushrooms is proposed, in which an attention mechanism is incorporated and a new network model structure is constructed in combination with a residual module. Firstly, nine diseased wild mushroom image samples were collected, and in order to make the model have better generalization ability, the images were pre-processed so that the number of samples reached 7200, and the experimental results showed that the improved deep residual network model achieved about 99.12% accuracy in classifying and recognizing the established wild mushroom database, and the improved neural network had a great improvement in classification accuracy.
Analysis and Prediction of Bank Customer Loyalty Based on XGBoost Algorithm
Authors: Zhang Yuyan , Chen Ke , Chen Ting
Published: December 2023

At present, the homogenization of banking products and the vigorous development of internet finance have intensified the competition among banks. Customers are the core assets of banks, whose size and loyalty is crucial to any bank. Loyal customer’s repeat purchases or recommending products to people around creates higher value for banks. Therefore, in order to improve customer loyalty, a method of identifying customer loyalty is urgently needed which prioritizes providing more personalized services for loyal customers. Based on bank’s long-term customer resource data, this paper divides customer groups by means of feature selection and data processing, compares the experimental results of multiple machine learning models such as GBDT, and selects the optimal XGBoost model to predict customer’s long-term loyalty to banks, in order to predict potential customer churn for banks, attempt to retain high-value customers as much as possible, and to increase potential revenue.
Semantic Segmentation of Remote Sensing Images Based on Swin Transformer
Authors: Lin Yinghao , Zhao Shihao , Wang Yuye , Xie Yi , Qiao Baojun
Published: December 2023

With the evolution of Earth observation technology and remote sensing technologies, the amount of data available for high-resolution remote sensing images has exploded, and high-precision image segmentation has become a current research hotspot. Semantic segmentation technology is becoming increasingly important in fields such as urban planning, land use management, and autonomous driving. Large disparities within intraclass and modest differences intraclass are hallmarks of high resolution remote sensing pictures. Traditional image semantic segmentation methods rely on human-computer interaction and have poor generalization ability. When facing remote sensing images with rich types of ground objects and significant differences in target scales, the segmentation accuracy is not high. In this paper, we suggest an UperSwin decoder structure. The decoder includes several Swin transformer blocks and a fusion upsampling module, where the multi head contextual attention module in the Swin transformer block simultaneously uses multi-scale features and upsampling output features from the backbone network. In addition, the fusion upsampling module concatenates the backbone network features with the output features of the Swin transformer block, and then performs upsampling operations, preserving more detailed information. This article evaluates the accuracy and intersection ratio indicators on the Potsdam and Vaihingen datasets, verifying the feasibility and effectiveness of the model.
User Behavior Analysis Based on Big Data and Artificial Intelligence
Authors: Wang Tao , Ma Yinghui , Wang Ze , Wu Xiaojun , Li Long
Published: December 2023

Thanks to the support of big data technology, the Internet is gradually expanding towards the Internet of Things, and further upgraded to a better experience of artificial intelligence, which is possible based on big data and artificial intelligence. Taking “Big data and artificial intelligence can be used for analysis of library users” as an example, Explore the domestic and foreign authoritative database input user behavior analysis and other keywords to find relevant literature, According to the comprehensive comparison of literature analysis method, 55 core technical documents were selected for close reading, Through the development process of technology, Clarify the core technologies and methods of user behavior personality analysis and credibility analysis and do the key expansion research, According to the literature research results combined with the needs of the actual development of the library, Exploring a set of big data analysis model of user behavior based on traditional data mining and classification learning, The model can effectively combine the user personality analysis and abnormal behavior detection to solve the above two problems.
An End-To-End Fault Diagnosis Method for Emulsion Pump with Class-Imbalance
Authors: Lai Yuehua , Li Ran , Liu Mingliang , Wu Zaoyang , Chen Rongming
Published: December 2023

The condition monitoring data of emulsion pump follow the long-tail distribution. The amount of monitoring data for the normal condition is very large, while the amount of monitoring data for different fault conditions is very small, the problem of class-imbalance is prominent. The traditional intelligent fault diagnosis methods are proposed under the assumption of class balance, which the fault diagnosis model has the shortcoming of insufficient generalization ability when dealing with the class-imbalance problem. Thus, an end-to-end fault diagnosis method for emulsion pump with class-imbalance is proposed. conditional variational autoencoder is used to extract features and learn the state data distribution of emulsion pump, and the loss value of training samples is adjusted based on focal loss to balance the influence of different types of data on the model. Moreover, the end-to-end fault diagnosis model can be obtained based on the decoder model. Finally, the effectiveness of the proposed method is verified by simulation experiment data of emulsion pump faults. Compared with other methods under different types of imbalanced rates, the results show that the fault of emulsion pump can be accurately identified under the condition of only a small amount of fault data by the proposed method and the corresponding recognition accuracy is better than other methods.
A Multi-Dimensional Text Sentiment Analysis Method Based on Joint Network
Authors: Cao Tao , Liu Na , Bai Shuchen
Published: December 2023

Text sentiment analysis in social media has problems such as irregular structure, short length and sparse features. In this paper, a text sentiment analysis method combining emotional symbols is proposed. Based on the BiGRU and capsule network joint network model, this method fully considers the influence of emotional emoji in the text to be analyzed on the sentiment analysis tendency. Secondly, the BiGRU network was used to extract the long-term dependent features of the text context, and the capsule network was used to deal with the problem of losing feature information in the CNN pooling layer to better extract the local features of the text. Finally, the Softmax classifier was used to output the sentiment tendency. Experimental results show that the proposed model is superior to the current mainstream models in accuracy, recall rate and F1 value.
Research on the Construction Method of Historical Heritage Knowledge Map Based on Deep Learning
Authors: Gui Shan
Published: December 2023

For the current museum small-scale knowledge map of historical relics needs to be constructed manually, this paper will introduce the relevant methods of deep learning to construct the knowledge map of historical relics, and conducts an in-depth study and analysis of the entity recognition model and algorithm in the construction of the knowledge map of relics, and improves the accuracy of model detection by improving and optimizing the model. In the process of entity recognition in this paper, the bi-directional long and short-term memory-conditional random field (Bi LSTM-CRF) and convolutional neural network (CNN) are combined to construct a network model for extracting entity information. In the comparison experiments, its data source is a self-built dataset based on historical artifact datasets. The experimental results show that the improved Bi LSTM-CNN-CRF model has a better entity recognition effect compared with the CRF, Bi LSTM, and Bi LSTM-CRF models, and it achieves an accuracy rate of up to 85.77% and an F-value of 84.49%.
A Joint Extraction Method of Entity Relationship in Tourism Domain Based on Multi-Dimensional Features and Mixed Time Series
Authors: Gao Tianyu
Published: December 2023

Aiming at the problems of entity nesting and relationship overlap in the process of tourism domain information extraction, a joint entity relationship extraction method based on multi-dimensional features and mixed time series was proposed. The relationship extraction model based on multi-dimensional features and mixed time series is constructed by coding layer, entity extraction layer and relationship extraction layer. In the coding layer, BiLSTM can better capture the bidirectional semantic dependence, and use the bidirectional long and short memory network to encode sentences in combination with word context information. Entity extraction layer uses CNN to classify annotated text data, relationship extraction layer integrates the representation ability of different dimensions for relationship extraction, and uses weighted dot product to calculate the loss of relationship extraction to improve the effect of relationship extraction. The experimental results show that the recall rate of the model in this paper is 97.46%, the accuracy is 97.18%, and the F1 value is close to 1. When the threshold is 0.41, the F1 value is 0.805, and the curve reaches the inflection point, then the model has the best effect. The problem of entity nesting and relationship overlap is solved effectively.
Applications of Diffusion Model Image Restoration in the Field of Heritage Restoration: Overview and Outlook
Authors: Li Yiran
Published: December 2023

The restoration of museum heritage is an important task with significant cultural and historical value; however, traditional methods of restoration are frequently constrained by the extent of the damage to the heritage as well as the constraints of the restoration techniques. In recent years, a method of restoration known as the diffusion model, which is based on computer vision and machine learning, has been gradually applied to the field of museum relics restoration and has shown enormous potential in relic restoration. This method of restoration was developed in the 1980s and is still in use today. In the field of image restoration, research and application of diffusion models are reviewed, and this article provides a summary of the development history, methodology principles, and application cases associated with these topics. This article provides an introduction to the fundamental ideas and principles underlying diffuse models, as well as a summary of the current state of research and an outlook on potential future trends and prospects pertaining to image repair within the domain of image processing.
Research on the Key Application of Computer Biometric Technology in Power Self-Service Terminal
Authors: Zhu Hui , Li Chen , Yu Bei , Li Xin , Li Mengyuan
Published: December 2023

Biometric is a unique feature that can carry out identity verification and measurement. Biometric tech is a tech on account of computer tech, integrating sound, light, sensors and other technical means, and on account of the characteristics of organisms, which is difficult to forge, not easy to lose, carried with organisms, and easy to use. At present, biometric tech has been widely used in many fields, but it is still in the initial and exploratory stage in the field of power business self-service. Biometric tech has important utilization advantages in the field of power business self-service, especially in the field of identity recognition. On account of this, in order to enrich the functional utilization and user experience of power business AIDS, this paper makes a more in-depth research and analysis on the embedding of computer biometric tech into power related business processes. The experimental test shows that for the same person, the different number of face samples will lead to a certain gap in the recognition rate; when the number of collected face samples increases, the time for face recognition will increase; the average recognition rate is above 93%, achieving the desired effect. The possible reason for the analysis experimental results is that when the camera collects the image of the face to be recognized, the face detection stage produces misdetection, so that part of the recognized pictures are not real faces, which will lead to the decline of the overall recognition rate.
Research on Precision Teaching Management Methods in Universities in the Era of Big Data Based on Entropy Weight Method
Authors: Wei Xiufeng , Jiang Jiaqi , Zhang Le , Feng Hongyan
Published: December 2023

The widespread adoption and advancement of big data technology have led to its integration across various industries, offering convenience and efficiency in various tasks. The field of education is no exception, as the integration of modern technology with education becomes increasingly common. Traditional experiential teaching methods are gradually being replaced by data-driven teaching approaches. The establishment of data-driven platforms enables the collection and analysis of teaching materials, injecting new energy into precision teaching. This article focuses on modeling and evaluating the management method of precision teaching in universities during the era of big data, utilizing the entropy weight method for analysis. Specific analyses are conducted to provide a comprehensive understanding of the subject matter.