bluuebunny/crossref_metadata_2025 huggingface dataset:
РЕФОРМУВАННЯ ЕНЕРГЕТИЧНОГО СЕКТОРУ УКРАЇНИ ДЛЯ ЗАБЕЗПЕЧЕННЯ СТАЛОГО РОЗВИТКУ
Authors: БУРЯЧЕНКО Андрій , СЛАВКОВА Алла
Published: February 2024

У статті розглянуто необхідність проведення реформи енергетичного сектору економіки України, зважаючи на незмінний курс на набуття членства в ЄС, а також у відповідності до встановлених Цілей Сталого Розвитку ООН. Проаналізовано динаміку енергоємності ВВП України та світу. Визначено фінансові та нефінансові фактори впливу на енергоємність ВВП та проаналізовано зміну кінцевого енергоспоживання, загального первинного постачання енергії та виробництва. Проаналізовано енергетичну політику ЄС, узагальнено ключові цілі Енергетичного Співтовариства до 2030 року. Визначено можливості для подальшого реформування енергетичного сектору України шляхом впровадження енергоефективних практик, поширенню відповідних технологій та прийняті необхідних змін в нормативно-правовій площині, що будуть узгоджуватися з європейським законодавством.
СТАТИСТИЧНА ОЦІНКА РІВНЯ ІМІДЖЕВОСТІ НАЦІОНАЛЬНОЇ ЕКОНОМІКИ ТА БРЕНДІВ КОМПАНІЙ УКРАЇНИ В СИСТЕМІ ТРАНСПОРТНО-ЛОГІСТИЧНОГО БІЗНЕСУ
Authors: СТЕГНЕЙ Маріанна , ГРИНЧАК Ігор , МЕЙСАР Богдан , ОСУСЬКИЙ Станіслав
Published: February 2024

Стаття присвячена розгляду питань іміджевості національної економіки та окремих брендів компаній, статистичній оцінці рівнів іміджевості та характеристиці їх впливу на розвиток транспортно-логістичного бізнесу. Наведено визначення понять «іміджевість національної економіки», «іміджевість компанії», «статистична оцінка рівня іміджевості». Охарактеризовано вплив іміджевості на конкурентоспроможність і привабливість національної економіки за допомогою брендингу, який є складовою маркетингових технологій. Доведено, що брендинг допомагає залучати іноземні інвестиції, розвивати експорт, збільшувати кількість туристів і підвищувати почуття гордості у громадян країни. Доведено також, що розвиток брендингу стимулює розвиток транспортно-логістичного бізнесу. Окреслено шляхи розвитку національного брендингу. Охарактеризовано класифікацію брендів за Індексом міцності бренда. Досліджено динаміку вартості національного бренду України топ найдорожчих брендів компаній України. Доведено, що Україні необхідно продовжувати працювати над розвитком своїх брендів, що передбачає постійний моніторинг громадської думки, дослідження ринку та внесення необхідних коректив у маркетингові стратегії. Все це позитивно буде впливати на розвиток транспортно-логістичного бізнесу.
SISTEM REKRUTMEN KARYAWAN DALAM PERSPEKTIF MANAJEMEN SYARIAH PADA PT. SUMBER GRAHA SEJAHTERA KABUPATEN LUWU
Authors: Rianto Rianto
Published: February 2024

Studi yang dilakukan mempunyai tujuan untuk mengetahui bagaimana sistem rekrutmen karyawan pada PT. Sumber Graha Sejahtera di Kabupaten Luwu. Disamping itu juga  untuk mengetahui sistem rekrutmen karyawan pada PT. Sumber Graha Sejahtera di Kabupaten Luwu dalam perspektif manajemen syariah. Peneliti menggunakan jenis penelitian lapangan (field research). Adapun metode yang digunakan adalah deskriptif kualitatif. Hasil penelitian ini menunjukkan bahwa sistem rekrutmen karyawan yang dilakukan oleh pihak PT. Sumber Graha Sejahtera sangat memperhatikan kinerja karyawan dalam proses rekrutmen, karena dilakukannya evaluasi setiap 6 bulan, dan dilihat dari absensi calon karyawan apabila calon karyawan tersebut telah melewati semua prosesnya dan telah menjadi Pegawai Kontrak Waktu Tertentu (PKWT),  maka akan diangkat menjadi pegawai tetap, dan semua rangkaian tersebut sesuai dengan ukuran kinerja yang dibutuhkan oleh perusahaan. Disamping itu juga PT. Sumber Graha Sejahtera telah melaksanakan rekrutmen pegawai berdasarkan sikap profesionalisme yang ditunjukkan oleh karyawan, Berdasarkan sikap profesionalisme dalam pandangan syariah dicirikan pada tiga hal, yakni : Kafa’ah, Himmatul amal, dan Amanah.
PENGARUH INDEKS PEMBANGUNAN MANUSIA DAN PENGANGGURAN TERHADAP PRODUK DOMESTIK REGIONAL BRUTO DI PROVINSI SULAWESI SELATAN
Authors: Wardani Safitri Ulfa
Published: February 2024

Penelitian ini bertujuan untuk mengetahui pengaruh indeks pembangunan manusia (IPM)  dan pengangguran terhadap produk domestik regional bruto (PDRB) di Provinsi Sulawesi Selatan periode tahun 2010-2019. Penelitian ini merupakan penelitian kuantitatif. Sumber data yang digunakan dalam penelitian ini adalah data sekunder yang bersifat time series dan diperoleh dari website resmi Badan Pusat Statistik Provinsi Sulawesi Selatan.Teknik pengumpulan data yang di gunakan adalah teknik dokumentasi.Teknik analisis data menggunakan model analisis regresi linear berganda yang didukung dengan uji asumsi klasik dan uji hipotesis. Hasil penelitian menunjukkan bahwa indeks pembangunan manusia berpengaruh positif dan signifikan terhadap produk domestik regional bruto (PDRB) di Provinsi Sulawesi Selatan periode tahun 2010-2019. Pembangunan manusia memberikan sumbangan yang relatif besar terhadap peningkatan produktivitas, ketika indeks pembangunan manusia naik maka produk domestik regional bruto (PDRB) di Provinsi Sulawesi Selatan akan meningkat. Sedangkan pengangguran berpengaruh negatif terhadap produk domestik regional bruto (PDRB) di Provinsi Sulawesi Selatan periode tahun 2010-2019, ketika pengangguran naik maka produk domestik regional bruto (PDRB) di Provinsi Sulawesi Selatan akan menurun.
PEMBANGUNAN MANUSIA DALAM PERSPEKTIF EKONOMI ISLAM UNTUK MENCAPAI FALAH
Authors: Jaya Arisman
Published: February 2024

Penelitian ini bertujuan untuk mengetahui tentang pembangunan manusia dalam perspektif ekonomi islam. Pembangunan manusia dipandang sebagai proses perluasan pilihan dalam hidup manusia atau peningkatan kualitas hidup manusia. Adapun dimensi pembangunan manusia tersebut adalah pendidikan, kesehatan dan hidup yang layak. Ketiga dimensi tersebut merupakan hal yang esensial dalam kehidupan. Ekonomi islam sebagai suatu sistem prekonomian bertujuan untuk menghantarkan manusia untuk mencapai falah. Berdasarkan pada tujuan penelitian, maka pendekatan penelitan yang digunakan adalah penelitian kualitatif. Penelitan ini menggunakan dokumentasi dalam mengumpulkan data yang dipublikasikan dan beserta literasi-literasi yang terkait dengan penelitian. Data yang telah terkumpul kemudian dideskripsikan dengan menggunakan analisis deskriptif.  Hasil penilitian ini adalah pembangunan manusia dalam ekonomi islam merupakan pembangunan sumber daya manusia yang religius. Dimana tidak hanya berorientasi pada kepentingan dunia semata, mereka akan menyeimbangkanya dengan akhirat untuk mencapai falah.
MEDIA SOSIAL DAN PROGRAM “JOGO TONGGO” PADA MASA PANDEMI COVID-19: STUDI ETNOGRAFI DIGITAL
Authors: Arianto Bambang , Handayani Bekti
Published: February 2024

Penelitian ini bertujuan untuk mengelaborasi peran media sosial dalam memperkuat program “Jogo Tonggo” pada masa pandemi COVID-19 di Jawa Tengah. Kebermanfaatan media sosial telah menjadikan sebagai saluran utama komunikasi dan informasi kewargaan pada masa pandemi COVID-19. Hal itu membuat media sosial digunakan sebagai saluran utama untuk mendapatkan informasi kesehatan tentang pencegahan dan penanganan wabah COVID-19. Berbagai informasi ini sangat penting bagi kewargaan untuk dapat membangun semangat sukarelawan dan gotong royong digital pada masa pandemi Covid-19. Penelitian ini menggunakan pendekatan etnografi digital dengan teknik wawancara mendalam (In-depth interview) dan observasi partisipatif secara digital kepada para pengguna media sosial di Jawa Tengah. Hasil penelitian menemukan bahwa media sosial sangat berkontribusi dalam mensukseskan program “Jogo Tonggo”. Penelitian ini juga menemukan bahwa platform media sosial Whatsapp telah menjadi saluran utama komunikasi digital dalam program “Jogo Tonggo” pada masa pandemi COVID-19.
ANALISIS DESKRIPTIF GAYA KEPEMIMPINAN DAN FAKTOR-FAKTOR YANG MEMPENGARUHI KINERJA KARYAWAN PADA PABRIK GULA PT. PERKEBUNAN NUSANTARA XIV (PERSERO) KABUPATEN BONE
Authors: Irmayani Irmayani
Published: February 2024

Penelitian ini bertujuan untuk mengetahui gambaran penerapan gaya kepemimpinan dan faktor-faktor yang mempengaruhi kinerja karyawan pada pada pabrik gula PT. Perkebunan Nusantara XIV (persero) Kabupaten Bone. Penulis menggunakan metode field research (penelitian lapangan) dengan melakukan observasi, wawancara, dokumentasi dan kuisioner untuk memperoleh data dari masalah tersebut,. Selanjutnya dalam menganalisis data, penulis melalui     tiga tahap kegiatan yaitu seleksi data, klasifikasi data, dan sistematika data. Hasil penelitian menunjukkan bahwa berdasarkan mean (rata-rata) dari 20 responden dan diberikan 10 pertanyaan dalam bentuk kuisioner yang terdiri 5 pertanyaan untuk variable gaya kepemimpinan berdasarkan dari rata-rata tersebut maka sangat jelas bahwa pemimpin menerapkan gaya kepemimpinan dalam pengembangan keputusan. Sedangkan faktor-faktor yang mempengaruhi kinerja karyawan adalah sikap disiplin, motivasi kerja, kompensasi atau insentif, gaya kepemimpinan, lingkungan kerja, pelatihan terhadap karyawan, perkembangan teknologi, delegasi tugas, dan komunikasi yang kuat.
PENGARUH HARGA DAN E-SERVICE QUALITY TERHADAP KEPUTUSAN PEMBELIAN PADA LAYANAN APLIKASI VIDIO
Authors: Mitalia Mitalia
Published: February 2024

Perkembangan bisnis di dunia saat ini telah melegit dengan pesat didukung dengan peningkatan teknologi, keadaan ini mendorong timbulnya persaingan di antara pelaku bisnis, sehingga mereka diharapkan memiliki strategi yang bersifat kompetitif, terus-menerus melakukan improvisasi, dan berinovasi untuk mempertahankan basis pelanggan mereka. Harga dan kualitas layanan elektronik dirancang sebagai strategi yang paling sesuai untuk memenuhi keinginan dan harapan pelanggan. Penelitian dilakukan untuk mengevaluasi pengaruh Harga dan e-service quality terhadap keputusan pembelian pada aplikasi layanan Vidio. Data penelitian ini dikumpulkan dari 100 responden yang mengisi kueisoner secara online yang disebarluaskan melalui google form kemudian data diolah dengan metode kuantitatif Penelitian ini dilakukan pada individu yang telah atau sedang menjadi pelanggan langganan SVOD Vidio. Temuan dari penelitian menunjukkan bahwa Harga memiliki dampak negatif yang tidak signifikan pada keputusan pembelian, sementara e-service quality memiliki dampak negatif terhadap keputusan pembelian aplikasi Vidio.
PENGARUH KESEHATAN DAN KESELAMATAN KERJA, LINGKUNGAN KERJA TERHADAP TINGKAT PRODUKTIVITAS KERJA KARYAWAN PT. KBU BAYUNG LENCIR KABUPATEN MUSI BANYUASIN
Authors: Sahputra Rheci , Wahyudi Pipen , Ghozali Julianto
Published: February 2024

Penelitian ini bertujuan untuk menguji dan menganalisis pengaruh K3, Lingkungan kerja terhadap tingkat Produktivitas Kinerja karyawan di PT. KBU Bayung Lencir Kabupaten Musi Banyuasin. Data penelitian ini diperoleh dari 100 responden yang mengisi kuisoner secara online yang disebarluaskan melalui google form kemudian data diolah dengan metode kuantitatif agar dapat menghasilkan jawaban menyeluruh mengenai pengaruh dua variabel, yaitu Kesehatan dan keselamatan, lingkungan kerja terhadap tingkat produktivitas kinerja karyawan PT. KBU Bayung Lencir Kabupaten Musi Banyuasin. Hasil penelitian ini menunjukkan bahwa K3 berpengaruh negatif terhadap Tingkat Produktivitas kerja karyawan di PT KBU Bayung Lencir Kabupaten Musi Banyuasin. Ketika K3 tidak diterapkan maka Tingkat Produktivitas kerja karyawan akan menurun pada PT. KBU Bayung Lencir Kabupaten Musi Banyuasin. Sedangkan Lingkungan Kerja berpengaruh positif terhadap Tingkat Produktivitas kerja karyawan di PT KBU Bayung Lencir Kabupaten Musi Banyuasin. Ketika Lingkungan kerja positif maka Tingkat Produktivitas kerja karyawan akan meningkat pada PT. KBU Bayung Lencir Kabupaten Musi Banyuasin.
Penentuan Tingkat Kerusakan Pantai Air Kodok, Desa Hatu - Pulau Ambon
Authors: Lilipory Isak , Pattiselanno Steanly R.R.
Published: February 2024

Pola pengembangan dan penempatan infrastruktur di sepanjang pesisir pantai yang diterapkan di Pulau Ambon, selain menyajikan daya tarik yang luar biasa, juga menyimpan potensi kerawanan yang tinggi.  Karena infrastruktur yang dibangun akan terdampak langsung menghadapi daya rusak alam lewat kondisi perairan pantai saat tejadi gelombang yang besar.  Akibatnya adalah abrasi, erosi, ataupun sedimentasi yang langsung  mempengaruhi morfologi pantai.

Hal ini juga yang terjadi pada Pantai Air Kodok Desa Hatu  yang terletak pada posisi bentang koordinat -3.7219 BT, 128.0636 LS sampai dengan Pantai Waikiri pada koordinat -3.7243 BT, 128.0606 LS, di mana pada daerah pantai Desa Hatu adanya objek vital seperti Aproach Light (Lampu Pendaratan Pesawat), jalan provinsi yang menghubungan akses msayarakat dari Hatu, Liliboi dan Allang ke Kota Ambon, serta pemukiman penduduk yang masuk area sempadan pantai.  Fenomena tersebut, menarik untuk didalami terhadap besarnya dampak yang terjadi, dan salah satu alat ukur yang dapat digunakan untuk menilai kriteria kerusakan daerah pantai adalah menggunakan standar Surat Edaran Menteri PUPR No.8/SE/M/2010 tentang Pemberlakukan Pedoman Penilaian Kerusakan Pantai dan Prioritas Penanganannya.

Hasil penelitian menunjukkan bahwa analisa penilaian kerusakan pantai dan penentuan prioritasnya berdasarkan kerusakan lingkungan dan tingkat kepentingannya pada lokasi Desa Hatu masuk kategori prioritas E (tidak diutamakan), untuk kerusakan akibat erosi/abrasi dan kerusakan bangunan pantai Desa Hatu, temasuk kategori kurang diutamakan (prioritas D), sampai dengan amat sangat diutamakan – darurat (prioritas A), yaitu pada kerusakan tembok laut  sepajang 55 m, di antara STA 0+100 s/d 0+200 akibat gerusan gelombang.

Kata kunci: Desa Hatu, Kerusakan Pantai, Pulau Ambon.
PID Parameter Optimization of Hydro-Turbine Speed Control System Based on CPG Algorithm
Authors: Li Yang , Zhang Mingxu , Yang Yun
Published: February 2024

In order to achieve optimal control of the Hydro-Turbine Speed Control System (HTSCS), this paper presents a speed control system parameter optimization method based on the Convergence Factor Particle Swarm Optimization and Gravitational Search Algorithm (CPG). Firstly, the basic model of the HTSCS is established, and then the parameters of the PID controller are optimized using the CPG algorithm. Simulation results demonstrate that the CPG algorithm can rapidly obtain the optimal initial parameters for the PID controller. Furthermore, compared to the traditional PID control system, the PID control system based on the CPG algorithm exhibits smaller speed fluctuations, shorter stabilization time, and faster dynamic response speed under frequency and load power disturbances. The application of the CPG-based PID control strategy to the HTSCS provides enhanced dynamic stability.
Coupling Analysis and Optimization of Vehicle Frame and the Vehicle-Mounted Equipment Installation Frame
Authors: Meng Lingru , Zhao Dong , Zhang Chuansheng , Wang Jinyang , Pang Jianning , Kong Linghui
Published: February 2024

The vehicle-mounted equipment installation frame and its key components may produce plastic deformation and fracture due to the gravity and vibration of the equipment in the process of road transportation. In this paper, the strength of the vehicle equipment installation frame and vehicle frame was chosen and the structured to be optimized based on the static analysis, modal analysis and random vibration analysis. The results show that the maximum stress value of the whole structure is 403.41 Mpa under full load condition and the frame frequency does not coincide with the motor frequency and the maximum equivalent stress is 491.36 Mpa in the random vibration analysis. The structure design of the frame and equipment installation frame is reasonable and reliable.
Design and Bionic Analysis of the Driving Mechanism for the Tail of a Bionic Fish Robot
Authors: Sun Feiyang , Zhang Runfeng
Published: February 2024

All along, human exploration of the ocean has never stopped, and bionic fish robots have been produced. Currently, bionic fish have been used in a range of fields, including underwater archaeology, water quality monitoring, and other fields, because of their camouflage and flexibility. The bionic fish also can perform observation, reconnaissance, and other jobs, reduce battle risks, and play a crucial role in contemporary military tasks. It is increasingly being implemented in the military sphere. The efficacy of the bionic fish’s tail mechanism in terms of swimming and reconnaissance is crucial to the design of the fish. However, multiple servo joints are frequently used in the current bionic fishtail system, which increases the likelihood of failure. This research suggests a fishtail design strategy based on the transmission mechanism to operate more steadily. After analyzing the existing bionic fish mechanical structures, research proposes the schemes of living in three mechanical structures. By combining the actual fish body size, the comprehensive modeling design was carried out using Solid Work software, and the motion performance analysis of the mechanism was analyzed by Adams software. The experimental results provide a theoretical and reference for the actual design of bionic robotic fish.
Optimal Step-Size Control with Bayesian Optimization for Correlation Integral Based Real Time Optimization
Authors: Zhao JingWei , Zhao Zhong
Published: February 2024

Conventional real-time optimization (RTO) requires detailed process models, which may be challenging or expensive to obtain. Data-driven correlation integral based RTO method is an attractive alternative to circumvent the challenge of developing accurate process models. However, the searching step size in conventional correlation integral based RTO is set by trial-and-error. In order to improve the efficiency of the correlation integral based real-time RTO method optimiszation algorithm and enhance the applicability of the system, an Bayesian optimal optimisation step-size control strategy using Bayesian optimization based on correlation integral is proposed for the traditional correlation integral optimisation method applied in industrial systems. Based on the data-driven steady state model, the adaptive control of the step size is achieved by avoiding the change of the tuning step size through the trial-and-error method due to different working conditions during the real-time optimisation control. Based on the proposed method, the application software has been developed. The simulation and industrial application results have verified the feasibility and effectiveness of the proposed method.original real-time optimisation software is improved, and the practicality of the method is proved by simulation and industrial practical application.
Influence of the Compactness on the Mechanical Properties of Ballasted Track
Authors: Zhao Zemin , Wang Lihua , Huang Hongyi , Chu Yang , Tang Hao
Published: February 2024

Compactness is one of the indexes to measure ballast stability, and the dynamic stabilization operation parameters change with the initial ballast compactness. To improve the operation efficiency of the dynamic stabilization unit, a coupling model of dynamic stabilization unit-ballast was established by using the discrete element-finite element coupling method. The single-factor method was adopted to study the influence of different initial compactness on the mechanical characteristics of ballasted bed during the dynamic stabilization unit operation. The dynamic stabilization unit test rig was built to verify the rationality of the simulation model. Through simulation and experimental verification, the results show that the ballast lateral resistance increases with initial compactness and the ballast vertical displacement decreases with increasing compactness. When the sleeper is in the left and right pole position, the ballast particle force angle under the sleeper is 35°, and the ballast force error in the left and right pole position is reduced by 14.2% when the compactness is 0.654.
Uncertainty Analysis of Remote Sensing Soil Moisture Estimation Over the Qinghai-Tibetan Plateau: Feature, Target, and Model
Authors: Zhang Ling , Xue Zhaohui , Yu Jing , Yue Guijie
Published: February 2024

Remote sensing soil moisture estimation is a complex process due to the influence of the uneven subsurface, resulting in many uncertainties. This paper focuses on the Qinghai-Tibet Plateau as the study area and discusses the uncertainties of soil moisture estimation from three aspects: feature variables, target variables, and estimation models. The study concludes that the Mean Decrease in Impurity feature selection method with K=12 significantly outperforms other feature selection methods in selecting feature variables. Using measured data as the model target variable results in the highest precision and smallest standard deviation (R=0.9257, RMSE=0.0388cm3/cm3). The enhanced generalized regression neural network (EGRNN) model has higher accuracy, smaller standard deviation values (R=0.9422, RMSE=0.0341 cm3/cm3), and stronger adaptability in soil moisture estimation.
Assessment of the Susceptibility of Gully Type of Debris Flow in Nujiang Prefecture Based on Improved DenseNet
Authors: Liu Cunxi , Wang Baoyun
Published: February 2024

In response to the problem of excessive human intervention and poor accuracy of traditional methods for assessing the susceptibility of large-scale debris flow by selecting disaster-causing factors combined with statistical models, this paper proposes a DMANet (Dense-Multiscale-Attention Net) model for assessing the susceptibility of gully-type debris flows based on an improved Dense Net. Firstly, to improve assessment efficiency without reducing accuracy, the network structure of Dense Net is optimized. Secondly, the model uses an improved inception module to extract features of different scales to obtain local and overall features of the gully and integrates shallow features to reduce feature loss. Finally, to reduce the noise impact in gully images, the CBAM attention mechanism is introduced into the network, allowing the network to focus more on target samples. Based on the similarity between the gully to be assessed and the gully where debris flow has occurred, the susceptibility is predicted, and the results of susceptibility prediction are divided into five levels: extremely low susceptibility zone, low susceptibility zone, medium susceptibility zone, high susceptibility zone, and extremely high susceptibility zone using the natural breakpoint method. Experimental results show that the extremely high susceptibility zone of debris flow is mainly concentrated in the areas with abundant water systems on both sides of the Nu Jiang River, accounting for 56.53% of the entire study area, and the proportion of debris flow is 85.36%. The ACC value and AUC value of the DMANet model reach 77.43% and 0.7903 respectively, indicating that the model is a high-performance method for assessing the susceptibility of debris flow. This method can objectively and efficiently assess the susceptibility of debris flow, providing some ideas for the prevention and control of debris flow in the future.
Numerical Simulation Study on Fire of a Commercial Complex Transformed from a Reused Offshore Platform
Authors: Bao Jinling , Zhang Xia , Guo Jian , Tang Haiqi
Published: February 2024

Through modeling a multi-story commercial complex transformed from an offshore platform, FDS software is used to simulate and analyze its spatial smoke visibility, temperature distribution, smoke, and toxic and harmful gas concentration under different scenarios and combined with post-processing software Smokeview to achieve three-dimensional visual output results. The results showed that a fire occurred inside the first floor of the commercial complex, and the smoke reached the top floor slab in about 80 seconds. Attached to the top slab, it flowed around, forming a ceiling jet. Within about 3 minutes, the visibility at a height of 2 meters in the first-floor aisle is reduced to 10 meters, which is unsuitable for personnel evacuation. A fire broke out on the fifth floor of the three-dimensional column. At 26 seconds, smoke began to spread through the escape door to the commercial complex. Around 130 seconds, the height of the smoke layer at the evacuation exit decreased to 2 meters. After a fire, the shortest time for safe evacuation on the first floor was 165 seconds. In contrast, a fire broke out on the upper level of the column, resulting in only 97 seconds available for safe evacuation in the upper stairwell. In densely populated situations, escape is difficult and can lead to casualties during emergency evacuation. Therefore, in response to this renovation plan, it is necessary to strengthen the design of personnel evacuation and escape, smoke prevention and exhaust, and fire rescue in the future to reduce fire risk.
Bidirectional Interpolation of Photovoltaic Power Based on Deep Learning
Authors: Liao Hui , Guo Yanfei , Wei Wei , Li Yanxin , Xiong Huan
Published: February 2024

In actual operation, photovoltaic electric fields often encounter the problem of missing photoelectric output power. In order to ensure the continuity, timing, and integrity of the optoelectronic power data samples, improve the efficiency of optoelectronic data analysis and mining work, and improve the accuracy of optoelectronic power prediction, it is necessary to reconstruct the missing data of the optoelectronic unit. This article adopts a deep learning-based bidirectional interpolation algorithm for photovoltaic power, starting from both temporal and spatial dimensions, to explore the temporal and spatial dependencies of photovoltaic electric field station-related data and establish corresponding spatiotemporal models. Finally, the rationality of step selection was determined through time-step analysis experiments. When the time step is 4, the predicted power error is 10.43%, and the power interpolation curve has the best fit with the measured power curve. Through bidirectional interpolation experiments, the rationality and effectiveness of the bidirectional interpolation theory in supplementing missing data of photoelectric power were verified. The missing data on photoelectric power is affected by existing data before and after the time period. When the forward and reverse weights are 0.6 and 0.4, respectively, the predicted power error is 9.64%. Through comparative experiments, the power prediction error of the model in this paper is 10.43%, verifying the superiority of the model compared to the other three neural network models in predicting the error of optoelectronic power.
Industrial and Commercial User Load Forecasting Model Considering Incentive Mechanism
Authors: Ye Qiang , Cai Yuqing , Chen Wuxiao , Jiang Zhijun , Cai Jiaxin , Liu Kai
Published: February 2024

In recent years, many industrial and commercial users have begun to participate in demand response, and demand response measures will affect future load demand, thus affecting the accuracy of load forecasting. Prediction problems for these particular users, this paper describes the implementation of an industrial user load forecasting model considering regulation and incentive by using the time series characteristics of historical data of power load and the influence of reward mechanism on the power demand behavior of industrial users. Firstly, the influence of production cost and reward mechanism on the power utilization behavior of industrial users is investigated. Then, the feature engineering, data preprocessing, improved Adam optimization algorithm, LSTM neural network algorithm, and model evaluation index of industrial user load forecasting are described. Finally, the effect of this method in actual industrial user load forecasting is demonstrated. The power load data of a printing and dyeing enterprise in East China is used for verification. Through the analysis of actual simulation verification, with a mean absolute percentage error (MAPE) of 3.12% on the training set and 5.22% on the test set, respectively, as shown by the experimental results, it has high prediction accuracy.
Surface Roughness Prediction of Ultra-Precision Grinding for Magnesium Aluminum Spinel
Authors: Zhu Chuanmin , Wang Zheng , Wang Dawei , Shi Zhuoqi , Gu Peng
Published: February 2024

Magnesium alumina spinel (MgAl2O4) has excellent properties and is widely used in the field of optics and communication. The high quality and high efficiency of the grinding surface are two important issues in the grinding process. In this paper, the prediction model of grinding surface roughness of magnesia alumina spinel is established. According to the equivalent response surface and contour map, the influence of spindle speed, feed rate and grinding depth on surface roughness and the interaction of various influencing factors are analyzed. The particle swarm optimization algorithm is used to optimize ultra-precision grinding parameters to ensure high efficiency and high machining quality. The analysis shows that the prediction error of the model is less than 10%, and the optimal grinding process parameters can obtain a higher material removal rate on the premise of ensuring the machining quality, which provides an important basis for the efficient processing of magnesia alumina spinel materials.
Design of Equipment and Intelligent IoT System for Kitchen Waste Aerobic Composting Process
Authors: Fan Yuling
Published: February 2024

In order to help reduce food waste and unnecessary carbon emissions, a composting product of household kitchen waste was designed, and a comprehensive comparison was made by brainstorming. The final selected scheme was modeled by rhino software, and the model was rendered by Keyshot and PS software to get the final scheme effect picture, and output the relevant human-computer interface, novice operation diagram and storyboard. to facilitate the product to be better understood and used by users. In order to more intuitively demonstrate the synergy of the Internet of things, a product ecosystem map was drawn. This paper shows the relationship between stakeholders in the way of capital flow, information flow and material flow, and then presents the profit and customer model of the product, and carried on the CMF evaluation and functional semantic feasibility of intelligent composting box analysis of the product.
Elderly Fall Detection Method Using Threshold Based Method and Transfer Learning
Authors: Ma Yuzhi , Tang Lei , Liu Jiahui
Published: February 2024

The lack of elderly data is one of the most challenging issues in elderly fall detection. And the simulated young data is usually used in fall detection researches. In this paper, a wearable elderly fall detection method based on threshold based method (TBM) and transfer learning is proposed to shorten the distribution difference between young data and elderly data. In the process of training, labeled young data (source domain) and unlabeled elderly data (target domain) are utilized so as to weak the adverse effects of distribution difference between young data and elderly data. Finally, the better performance with sensitivity 98.63% and specificity 98.00% is illustrated with elderly data in Sisfall dataset.
Calculation Model of Earthwork Volume in Open Pit Mined Area Based on Step Feature Line
Authors: Li Mingfeng , Cao Xingke , Xu Dongsheng , Huang Yu , Jiang Yuhui , Tan Ding
Published: February 2024

To improve efficiency and accuracy of the calculation method of earthwork volume in the open pit mined area with complex terrain, a model based on the step feature line for the open pit mined area is constructed. With the Delaunay triangulation network constructed by the tilt photogrammetry photography of UAV, the step feature lines are extracted by the algorithm of RANSAC, and a detailed calculation model of earthwork volume is constructed by encrypting triangular network with the lines. With the experiments taken, it is shown that the accuracy of the new model is obviously improved as compared with both DTM model and unconstrained Delaunay triangulation model.
Numerical Simulation and Process Research of 1500mm Twelve-Roll Copper-Steel-Copper Clad Rolling
Authors: Zhang Dazhi , Li Xuan , Luo Wei , Song Shiwen
Published: February 2024

The copper-steel-copper clad strip was commonly applied in many areas of life as a new type of clad material due to its superior mechanical qualities and significant economic benefits. The finite element model of copper-steel-copper clad rolling is created by ABAQUS. The finite element simulation of copper-steel-copper clad rolling is carried out by setting different reduction rates, rolling temperature and rolling speed. With increasing reduction rate, rolling speed and decreasing rolling temperature, the simulation results show a growing tendency toward the Mises stress of Q235. With the increase of rolling temperature, the Mises stress of H96 decreases gradually. The plastic strain of Q235 and H96 shows an upward trend with the increase of reduction rate. The convexity of the copper-steel-copper clad strip increases with the increase of reduction rate. Based on the orthogonal experimental method, taking the residual stress and belt convexity as the evaluation indexes, the optimal rolling process parameters of copper-steel-copper clad strip are studied through range analysis. The results show that the optimal rolling process parameters of copper-steel-copper clad strip are reduction rate of 40%, rolling temperature of 450°C and rolling speed of 100mm/s.
Research on the Economic Scheduling of Multi-Distributed Power Sources Based on the Super-Node Cooperative ADMM Algorithm
Authors: Li Qiang , Ge Zhiping , Zhang Ruishan , Wang Changyi , Zhang Yanbin
Published: February 2024

To address the problems of large computation and communication in the economic scheduling of multi-distributed power supplies and the difficulty of overall optimization, an economic scheduling method of distributed power supplies based on the supernode cooperative ADMM algorithm is proposed. First, the supernode selection and local set partitioning are performed on the basis of the original communication topology diagram of the distributed power network, with supernodes solving decision variables in parallel and ordinary nodes in the local set only communicating with supernodes; second, the standard ADMM algorithm is improved so that each node searches for the optimal solution of its subproblem in parallel; in a distributed power grid containing multiple renewable energy sources, the operation cost minimization optimization The proposed method is used to solve the large-scale optimization model in a distributed grid with multiple renewable energy sources. Finally, the proposed algorithm is verified to accelerate the convergence speed of iterative optimization search through simulation cases, which can effectively improve the convergence speed of distributed power cooperative consistency.
Safety Risk Assessment of Test Based on AHP/EVM Model Study
Authors: Jia Chun , Zhang Qiong , Wang Junjie , Zhang Hao , Wu Jiajun
Published: February 2024

The test flight is a system engineering spanning multiple systems, disciplines, large scales, and high risks. Safety is the basis of completing a test flight but also the lifeline of the test flight. In recent years, the number of test flight tasks, such as batch test flight, subject test flight, and delivery test flight, has been extremely heavy. While ensuring the quality of test flight tasks, the mission progress is carried out according to the plan, which poses a great challenge to the management of test flight safety. Therefore, the test flight test safety risk assessment, namely, through the specific test category risk factors, the possibility of accidents, possible loss, and severity of investigation and analysis, and then, through the historical experience data, evaluating the calculation model of test safety gives a quantitative assessment conclusion and gives specific prevention and response measures, which will greatly improve the efficiency of test safety management and reduce test safety risk. This study is against the background of this demand.
Assessment Model for Bidding for Major Events
Authors: Wang Miao , Song Zhiyi , Gao Junyi
Published: February 2024

In this paper, we have built an integrated assessment model to assess the economic, social, environmental and other industrial impacts of hosting the Olympic Games on the host country. At the same time, we constructed a comprehensive national strength assessment model to assess the comprehensive strength of the country from nine aspects through AHP and TOPSIS methods. Based on the improved model and seasonal factors, we calculated the most suitable countries for hosting the Spring, Summer, Autumn and Winter Olympic Games. This study provides a scientific basis for the selection of the host country of the Olympic Games and the comprehensive strength of the country.
Application of Big Data Mining Algorithm in Steam Turbine Valve Flow Characteristics Analysis
Authors: Zhu Longfei , Zhang Teng , Xie Changya , Si Paiyou , Liu Shuangbai , Mei Long , Qiu Xiaozhi
Published: February 2024

The flow characteristic of the steam turbine valve is very important for the load regulation ability of the unit. A clustering algorithm based on information entropy is proposed to extract standard parameter vectors under different working conditions from massive historical data. Furthermore, the characteristic relationship between valve opening and flow rate can be obtained by regression. The multivariate state estimation method is introduced to estimate and judge the parameters in real time using the cluster center state vector matrix obtained by clustering. The class center state vector matrix is updated according to the distance between vectors, and then the adaptive update of the valve flow characteristic curve is realized. The actual data of a 300 MW unit is calculated, and results show that the proposed method is accurate and effective and it is suitable for engineering applications.
Selection of Equipment Tender Targets Model Based on Entropy Gray-Correlation Topsis Method
Authors: Dong Wentao , Zhou Wei , Dong Yucai
Published: February 2024

The entropy-gray-correlation-Topsis method is used to establish a tender target selection model. The model normalises indicator values and constructs indicator matrices for the number of people, proportion of professional staff, fixed assets, production infrastructure conditions, procurement contracts and return on assets of the enterprise, calculates the Euclidean distance and grey correlation between units and ideal and negative ideal solutions, analyses the primary indicator weight coefficients and secondary weight indices The final quantitative ranking is carried out to obtain the assessed values of the tenderee in terms of corporate strength, competitiveness, financial position and operational risk, and to select the tenderee with the best conditions. This model provides a reasonable and scientific evaluation index system for the selection of tenders.
Numerical Simulation of Flow Field in Pulper Cavity
Authors: Wang Jinyang , Zhao Dong , Meng Lingru , Zhang Chuansheng
Published: February 2024

The motion characteristics of the fluid in the pulper cavity were obtained by studying its internal area. The interaction between the rotating and stationary areas was handled using a multi-reference frame model in FLUENT software. Fluid simulation analysis was conducted on the wall surface with and without feeding paddle, as well as with different numbers of spoilers (none, one, three, or four), to obtain velocity streamline distribution, turbulent kinetic energy distribution, and cutter surface pressure distribution within the cavity. It’s found that the wall structure with feeding paddle and three spoilers has greatly improved the flow performance of the internal flow field of the pulper.
Research on Power Data Security Classification Based on O-Svm Algorithm
Authors: Zhai Feng , Li Baofeng , Liang Xiaobing , Qin Yu , Ji Wen
Published: February 2024

With the development of the new digital power system, the scale, type and value of power data are increasing, and the security protection of power data is confronted with serious challenges and risks. Through scientific, reasonable and dynamic security grading of electric power data, it can achieve the refinement, differentiation and personalization of electric power data security protection and avoid the phenomenon of “one size fits all”. Therefore, this paper builds a power data security classification and query system, firstly, by analyzing the security requirements of data in multiple scenarios of the electric power industry and carrying out security classification. Based on the improved O-SVM algorithm, it establishes a model applicable to the automatic grading of electric power data, and improves the accuracy rate of the classification algorithm. Finally, it designs an automated query system based on Hadoop, and the experimental results show that The classification retrieval accuracy is above 90%, and the accuracy is significantly improved compared with the existing SVM classification retrieval algorithm.
Evolution of Ecological Damage Probability in the Arid Area Based on SPCA: A Case Study of Yinchuan City
Authors: Zhang Zhilong
Published: February 2024

The cities in the arid area of northwest China are restricted by climate, and their economic development is affected to varying degrees. The oasis cities are located in an ecological fragile region, which is stressed by natural conditions and human activities, and has a high ecological risk. Based on Geographic Information System (GIS) and Remote Sensing (RS) technology, this paper selected human stress and landscape vulnerability as two types of evaluation indices from multiple perspectives. The random forest method was used for supervised classification to obtain land use data and the Kappa value was greater than 0.85. Each landscape index was calculated by Fragstats. Spatial principal component analysis (SPCA) was used to objectively determine weights. Finally, weighted superposition was used to calculate the ecological damage probability of the urban built-up areas in Yinchuan from 2000 to 2020. The results show that: (1) From 2000 to 2020, the high-value area of ecological damage probability of urban built-up areas in Yinchuan continued to increase, and the area of each grade changed from the dominant position of the low-value area to the equilibrium of each grade. (2) The spatial distribution of ecological damage probability is high in the central urban areas and low in the surrounding suburbs, and the medium value area as the transition area shrinks significantly. The ecological damage probability of the Yellow River and its banks decreases partly but still increases overall. (3) Human stress is the main factor in the ecological damage probability. (4) The risk of local areas in the central urban areas is reduced, and the ecological restoration projects achieve obvious results. Therefore, reducing man-made damage and implementing effective ecological restoration are the key points to protect the ecological environment, and also the key to scientifically preventing future ecological risks in the ecological fragile region.
Construction of Multimodal Knowledge Graph for Power System
Authors: Feng Jun , Wang Hongkai , Peng Liangying , Pan Sichen , Zhao Shuai , Wang Yidan
Published: February 2024

The professional vocabulary of the electric power industry is numerous, and the relationship is complex. How to mine valuable information from multi-source data of the power industry and describe the relationship between words is of great significance to assisting multi-business management of power systems. Aiming at the multimodal knowledge data of power systems, this paper uses the BiLSTM-CRF model and BiLSTM-Attention model to extract entity knowledge and relationship, respectively, and identifies image data through the CNN model. The experimental results show that the power industry knowledge graph based on multi-modal deep learning constructed in this paper can better realize the intelligent representation and management of many kinds of business in the power industry.
OOD Problem Research in Biochemistry Based on Backdoor Adjustment
Authors: Gu Pengfei , Yu Daao
Published: February 2024

Due to its ability to deal well with the features of graph structure (social network, molecular structure), graph neural network (GNN) has recently shown amazing capabilities in many fields (biology, chemistry), which has aroused the attention of a large number of researchers on the operation mechanism of GNN model. In order to apply graph neural network to real environment, the problem of out-of-distribution generalization is solved. The difference of data distribution between training environment and real environment is an urgent problem to be solved. In the present study, from the point of view of data, the input graph data is processed to find the core part and filter out the noise part; From the perspective of model method, the parts related to this task (graph classification) in the model are extracted, so as to improve the accuracy and efficiency of the model. However, while these methods are valid from a theoretical point of view, they are using methods that are too simple to actually cut off the effects of non-causal components. However, the current methods of model Angle are to cut the network directly, without considering the information transfer between the model parameters. To solve these problems, the main work of this paper is to propose a distance-based environment selection method, which enables the backdoor adjustment to be implemented to the maximum extent and ensures the robustness of the model. At the same time, it proposes a way for the network to squeeze information during the clipping process, so that the effect of the model pruning algorithm can be optimized. Reduce the complexity of the model and improve the generalization of the model. The method presented in this paper has been validated on data sets in several biochemical fields, and the best performance has been achieved.
Bearing Performance Degradation Assessment with RCMRBE Based on Teager Energy Operator
Authors: Li Shenlong , Zhang Jinbao , Zhang Jinle , An Yuanyuan , Bian Jixuan , Wang Fang
Published: February 2024

A new entropy named refined composite multi-scale reverse bubble entropy (RCMRBE) is proposed in this paper for bearing performance degradation (BPD) assessment. Firstly, Teager energy operator (TEO) was employed for enhancement of the fault information in vibration signals. Secondly, RCMRBE values were extracted from enhanced vibration signals concerning different bearing status, and the RCMRBE values at the first or second scale were selected as the bearing performance degradation indicators (PDIs) based on the correlations with time. Finally, a group of the life-cycle bearing tests were employed for verification. The results show that the proposed approach could clearly demonstrate the degradation process of bearing performance with time, which illustrates the effectiveness of the proposed method.
Detection of Suspicious Front Yard-View Burglary Aided with Moving Service
Authors: Wang Shilong , Leung Maylor Karhang , Khor Siak Wang , Sultan Hasnain
Published: February 2024

This work is devoted to the implementation and evaluation of a front-yard human abnormal/crime activity detection system. This system identifies abnormal/crime activities (burglary emptying site with moving service) in the front yard and gives an early warning message in time. In this way, the system realizes the maximum protection of the owner’s life and property. The system combines video surveillance systems and computer vision technology to detect abnormal human behavior in videos. Based on the human action understanding of burglary emptying sites with moving services in the real world, this paper designs an abnormal behavior detection system in the front yard scene. The system mainly uses YOLO5 and OpenCV for computer vision-related design. First, YOLO is used to identify the objects in the video scene, and then the OpenCV color comparison algorithm is used to track the relevant people in the scene. The activity relationship between people, vehicles, and buildings in the scene is combined to evaluate whether abnormal behavior occurs.