bluuebunny/crossref_metadata_2025 huggingface dataset:
FAKTOR- FAKTOR YANG MEMPENGARUHI PARTISIPASI ANGKATAN KERJA WANITA DALAM BERWIRAUSAHA
Authors: Haris Purwoningsih
Published: February 2024

Studi ini bertujuan untuk mengetahui faktor-faktor apa saja dan faktor mana yang lebih dominan berpengaruh terhadap partisipasi angkatan kerja wanita dalam berwirausaha. Jenis penelitian yag digunakan adalah penelitian lapangan dengan pendekatan kuantitatif. Populasi penelitian merupakan seluruh angakatan kerja wanita yang berwirausaha di Kec. Tanete Riattang Kab. Bone. Sampel penelitian sebanyak 100 orang responden dengan teknik pengumpulan data menggunakan kuisioner (angket). Penelitian bersifat eksplorasi dan belum memiliki variabel yang jelas, karena itu akan dirumuskan variabel yang akan digunakan, untuk memudahkan perumusannya digunakan dua faktor utama beserta sub faktornya yaitu faktor internal yang terdiri dari 15 sub faktor dan faktor eksternal yang terdiri dari 13 sub faktor, kemudian diuji menggunakan teknik deskriptif persentase, uji validitas & reabilitas, uji prasyarat analisis faktor yaitu uji Kaiser Mayor Oikin (KMO) dan uji Barlett, serta Analisis Faktor. Berdasarkan uji validitas dan realibilitas dihasilkan masing-masing 10 rumusan sub faktor internal & eskternal yang berkorelasi signifikan, masing-masing dari faktor tersebut setelah diuji KMO dan Bartlett juga dinyantakan signifikan dan berpengaruh untuk kemudian dilanjutkan melakukan uji analisis faktor. Berdasarkan uji analisis faktor dan hasil Rotated Component Matrix, 10 sub faktor internal tersebut dikelompokkan menjadi 3 faktor diberikan nama faktor keinginan pribadi, keadaan, dan membantu perekonomian keluarga dengan faktor yang paling dominan berpengaruh adalah faktor keinginan pribadi,nilai varians 23,366%. Sub faktor eksternal dikelompokkan menjadi 2 faktor yaitu faktor peluang dan besarnya potensi berwirausaha dengan faktor yang paling dominan adalah faktor lingkungan, nilai varians 24,727%.
Prediksi Cepat Gangguan Jaringan Tegangan Menengah Menggunakan Metode Knowledge Growing System (KGS)
Authors: Syamsiana Ika Noer , Yohana Puspa Ayu Yohana , Sirajuddin Indrazno , Sumari Arwin Datumaya Wahyudi , Sulistio Andhika
Published: February 2024

Semakin meningkatnya kebutuhan energi listrik di sektor rumah tangga hingga industri menyebabkan energi listrik menjadi salah satu kebutuhan yang sangat penting dalam kehidupan sehari hari, sehingga keandalan dalam pendistribusian energi listrik harus sangat diperhatikan. Adanya gangguan-gangguan yang terjadi karena beberapa factor gangguan dapat menyebabkan terganggunya keandalan pada supply listrik. Situasi seperti ini sering terjadi di unit Perusahan Listrik Negara (PLN) di wilayah Surabaya Selatan, hal inilah yang melatar belakangi penelitian ini dibuat salah satunya dengan memprediksi gangguan distribusi listrik yang bertujuan untuk menguji metode Knowledge Growing System (KGS) dalam memprediksi masalah gangguan listrik dengan cara mengenali pola gangguan yang terjadi di setiap bulannya yang kemudian di akumulasi menjadi pola gangguan pertahun. KGS adalah agen cerdas yang dapat menghasilkan pengetahuannya sendiri tentang fenomena yang diamati dan menggunakan pengetahuan yang dihasilkan untuk membuat prediksi. Dengan memiliki pengetahuan tentang 10 pola gangguan listrik di lokasi distribusi listrik, KGS telah mampu memprediksi bahwa gangguan yang paling mungkin terjadi karena gangguan belum ditemukan/gangguan sesaat di Gardu induk Rungkut, Waru, Wonorejo, Sukolilo dan Ngagel dengan rata rata terjadi gangguan sebesar 26,91 %. Dengan prediksi yang cepat, unit PLN dapat mengembangkan rencana yang tepat untuk mengatasi gangguan dan memulihkan pasokan listrik dengan cepat.
Range and Velocity Resolution of Linear- Frequency-Modulated Signals on Subarray-Mimo Radar
Authors: Sabaria Sabaria , Tahcfulloh Syahfrizal
Published: February 2024

The most important radar system performance is determining the range-velocity of the detected target. This performance is obtained from processing an ambiguity-function (AF) between signals from target reflections and radar radiation signals. Selection of the appropriate waveform transmitted by the radar is a key factor in supporting high resolution radar performance in the AF. There are many waveforms that have been studied in radar systems, especially for multi-antenna radars, i.e., subarray-MIMO (SMIMO) radar which can form phased array (PA) and MIMO radars simultaneously, in the form of linear-frequency-modulated (LFM) signals. In this paper, we examine the use of LFM waveforms combined with SMIMO radar to produce plots of three-dimensional AF as a function of time delay and Doppler shift. The results of the comparison with the Hadamard signal determine the effectiveness of the observed AF performance on parameters such as magnitude, range-velocity resolution, peak sidelobe level ratio, and integrated sidelobe ratio by taking into account the factors of the number of Tx antennas on the PA radar and the number of Tx subarrays on the MIMO radar. The evaluation results of the SMIMO radar configuration (M = 6) with the number of Tx-Rx antenna elements the being 8 provide the best mainlobe magnitude, sidelobe magnitude, range resolution, velocity resolution, PSLR, and ISLR of AF LFM signals compared to conventional radars are 235.2dB, 7.54dB, 37.5m, 75km/s, 29.89dB, and 29.8dB, respectively. Meanwhile, the LFM signal is far superior to the Hadamard signal which has PSLR and ISLR 1.16dB and -3.36dB, respectively.
Investigation of the effect of flexural strength test damage on compressive strength of construction materials
Authors: HAFÇI ALKAN
Published: February 2024

Concrete, the principal material of the construction sector, has been the subject of many scientific researches for decades. As a result of these investigations, new scientific information has been obtained on the weak points of cement-based products, especially concrete, their behaviour under load, etc. In light of this information, it is recommended that some test methods specified in international standards be revised. In this study, the effect of damage caused by flexural strength test performed on samples prepared with mortar prisms, of dimensions 160 mm x 40 mm x 40 mm within the scope of EN 13813, EN 13888, EN 13279-1, EN 197-1, TS 13566 and TS 13687 standards, on the results of compressive strength test performed on the broken samples was investigated. In the final analysis, some improvement suggestions have been made in the test methods in question.
Study on the Simulation of Flapping-Wing Aircraft
Authors: Li Xue , Dun Guoqiang , Zheng Xinxin , Zhang Dandan , Jiang Zengyu
Published: February 2024

Based on the research status of flapping-wing aircraft at home and abroad, the overall scheme of bionic flapping-wing aircraft is established in this paper. In the aspect of trajectory planning, the three-dimensional modeling and simulation analysis of bionic flapping-wing aircraft are carried out, and a new flapping-wing mechanism is adopted. Finally, the trajectory of flapping-wing aircraft is analyzed from the point of view of the operation, and verification experiments are carried out to obtain the best flapping-wing effect.
An Overview of Artificial Intelligence Security Issues
Authors: Wang Zhihui , Dong Yongqiang , Xiang Zhining , Cheng Shaochi
Published: February 2024

Artificial intelligence (AI) technology promotes human civilization, while it also raises concerns, mainly related to security. AI plays a double-edged sword role in the network space closely related to human life. On the one hand, AI assists in network protection by intelligently detecting network intrusion, reducing missed alarm rates and false alarm rates, forecasting network threats, automatically searching for malicious code, and supporting network defense. On the other hand, AI can also assist in network attacks, such as attacking voice recognition systems and malicious software detection. AI algorithms and computational data pose many security threats, affecting the security of face recognition, speech detection, malware detection, automated driving, and other security applications based on AI technology.
Application and Practice of Intelligent Temporary Construction Management Technology in UHV Project
Authors: Zhang Haojie , Jiang Weijie , Xu Bin , Zhang Hyperplasia , Wang Shu
Published: February 2024

The purpose of this study is to explore the application of intelligent temporary construction management technology in extra-high voltage projects and analyze its effect through practical cases. Firstly, we will introduce the basic concept and development history of wisdom-based pro-construction management technology, and then elaborate its features and advantages in extra-high voltage projects. Finally, this paper will take a special high voltage project as an example for empirical analysis to explore the application of intelligent temporary construction management technology and its impact on construction progress. The wisdom of temporary construction management technology is a kind of intelligent construction management method based on big data, cloud computing and Internet of things. It can realize real-time collection, storage, processing and analysis of engineering data, so as to improve construction efficiency, reduce cost and guarantee quality. In extra-high voltage projects, intelligent temporary construction management technology has the following advantages: first, it can effectively avoid problems during construction; second, it can optimize the construction process and shorten the construction period; third, it can provide more comprehensive data to support decision-making. Therefore, intelligent construction management technology is one of the indispensable technical means in the field of extra-high voltage engineering.
Maintenance Disassembly Sequence Planning of Airborne Equipment Based on Improved Ant Colony Optimization
Authors: Xia Jian
Published: February 2024

In aircraft maintainability design, disassembly sequence planning of airborne equipment is a primary aspect. Current ant colony algorithm has solved the combinatorial explosion problem for disassembly sequence planning, and also has some problems simultaneously, such as inaccurate description of constraint relations of airborne and algorithm is vulnerable to the initial sequence. On the basis of existing DCPN model, according to the characteristics of airborne equipment, a disassembly accessibility graph is proposed. The disassembly sequence planning problem is transformed into a mathematical solution problem. An improved ant colony optimization algorithm in maintenance disassembly sequence planning of airborne equipment is proposed, the improved algorithm takes the minimum disassembly cost as the optimization objective, it raises the search range and convergence speed of disassembly sequence planning.
A Novel Default Prediction Model Based on DNN and LightGBM
Authors: Pan Yujin , Zhang Feiran , Xu Tianxiao , Cai Yeming
Published: February 2024

Given the credit risk losses brought by Loan default to commercial banks, this paper, based on the America Express data set of the Kaggle platform, builds a hybrid model to predict customer default, to reduce credit risk. We first conduct data cleaning and feature engineering processing, dividing the data into category data and continuous data, and calculating the correlation between different features. We build DNN and lightGBM for credit default prediction. From the comprehensive results, the prediction effect of the mixed model is significantly better than that of the single prediction model. Among these models, our hybrid approach achieves the leading metric of 0.798. This metric is higher than XGBoost, LightGBM, and DNN by 0.013, 0.002, and 0.008 respectively.
Area Control Error Prediction Based on PCA-XGBoost
Authors: Sun Zhangling , Fan Hui , Yuan Qihai , Liu Shan , Wang Yajun , Li Xiaoming , Zhang Yue , Wang Yu
Published: February 2024

In order to fully explore the temporal characteristic relation between power grid operation information and area control error, and improve the prediction accuracy of area control error, an area control error prediction method based on principal component analysis (PCA) and extreme gradient boosting (XGBoost) was proposed. The feature selection of the relevant variables affecting the area control error was carried out with PCA, and the coupling between the features was eliminated. The principal components of the extracted variables were input into XGBoost, and the mapping relationship between the current power grid operation data and the future ACE in high-dimensional space was determined through the training model parameters. Therefore, an area control error prediction model based on PCA-XGBoost is established. Through the actual data verification of a regional power grid, compared with other methods, the proposed area control error prediction model has significant advantages in forecasting accuracy and generalization ability.
Combinatorial Model-Based Demand Forecast Analysis of E-Commerce Agricultural Products
Authors: Liu Jianglong , Wu Tianhao , Wu Junhui , Chen Zixi , Gong Jue , Chi Hongyi
Published: February 2024

This paper constructs the e-commerce agricultural products feature data set by using technical means such as web crawler and carries out preprocessing operations such as data filling and cleaning. K-Means algorithms are utilized to perform cluster analysis on the e-commerce agricultural products feature data set to realize multi-dimensional and multi-angle summarization of sales factors. Taking the dataset as the data support of the prediction model and based on the limitations of a single prediction model in the scope of application and accuracy, ARIMA, PSO-LSTM model and other combined models are constructed by using the arithmetic weight method and the integrated learning method respectively. According to the weights calculated out in the different arithmetic methods, the weights of the model are assigned to synthesize the prediction results. Among them, the best prediction results were obtained from the combined model using the inverse error weighted average method to calculate the weight composition.
Analysis of Factors Affecting the Uniformity of Cooling Water Velocity Inside the Hot Blast Valve Plate
Authors: Wang Yi , Xu Honghai
Published: February 2024

To address the problem of short service life of the blast furnace hot blast valve plate due to uneven heating, a finite element simulation model of the valve plate is established by Solidworks, and the steady-state flow field analysis of the valve plate is completed by using STAR-CCM+. On this basis, the orthogonal experimental design was used to research the influence of inner ring thickness, inner ring width, outer ring thickness and outer ring width on the uniformity of cooling water velocity inside the valve plate. The results show that the valve plate inner ring thickness, outer ring thickness and outer ring width have significant influence on the uniformity of cooling water velocity inside the valve plate; the degree of influence is in descending order of inner ring thickness, outer ring width and outer ring thickness. The uniformity decreases with the decrease of inner ring thickness and inner ring width, and increases with the decrease of outer ring thickness and outer ring width. The results of the study have important reference value for the improvement of the structural parameters of the hot blast valve plate.
Development of Reduced-Order Models Based on Singular Value Decomposition and Neural Network Regression
Authors: Tang Qi , Sun Yujie , Zhu Yuhan , Kang Lei , Liu Changli
Published: February 2024

This article proposes a method for building reduced-order models (ROMs) to address the issue of long solving time in traditional ANSYS finite element models, which can provide fast simulation results based on different loading conditions. Firstly, an orthogonal experiment is designed to obtain simulation results from the ANSYS model as training data. Secondly, the singular value decomposition (SVD) is combined with neural network regression to establish the reduced-order model. Then, the ROM generator software is built based on MATLAB. Finally, a stress reduced-order model of a specific finite element model is constructed, and the accuracy and efficiency of the proposed method are verified by comparing the simulation results with the results calculated by the reduced-order model, which can improve the solving efficiency while ensuring the accuracy of the solution.
Research and Application of Data Mining Algorithms in Power Marketing
Authors: Meng Qingchun , Xu Yan , Chen Long , Zheng Bowen , Song Xiaochen
Published: February 2024

With the continuous advancement of smart grid construction and the integration of more and more distributed power sources for new energy generation into the grid, higher requirements have been put forward for power marketing information management. This article takes the typical application of big data technology in power marketing as an example, analyzes the reasons for the problems faced by specific power enterprises in marketing, and with the aim of solving the problems, refines the problems into multiple information needs of power marketing. Finally, compression testing and response testing were conducted, and the system experienced no more than 1.1 interruptions and no more than 0.5 seconds of delay during the testing process.
Short-Term Electricity Load Forecasting Method Based on Attention and Time Series Forecasting
Authors: Hua Ke , Wang Zhichao , Zuo Feng , Wang Qihang
Published: February 2024

Short-term electricity load forecasting is critical in power system operation and control. However, accurate prediction of electricity load is challenging due to its non-stationary and intermittent characteristics. This paper proposes a hybrid deep learning model optimized with the attention mechanism for short-term electricity load forecasting, named CNN-LSTM-Attention. CNN-LSTM-Attention uses temporal convolution and long short-term memory network to extract temporal features of electricity load data and uses attention mechanism to optimize the fusion of long-term temporal features. The empirical study uses real electricity consumption data from four seasons in two regions. The forecasting results of the proposed model outperform all benchmark methods, demonstrating the advanced forecasting ability of the CNN-LSTM-Attention model.
A Remote Out-of-Tolerance Classification Method of Gateway Electric Energy Meters Based on Feature Selection and Deep Belief Network
Authors: Li Chong , Wang Hao , Li Chuan , Shen Hongtao , Wang Junlong , Guo Juchuan
Published: February 2024

Accurate identification of the out-of-tolerance of the gateway electric energy meter plays a vital role in ensuring the stability of the new power system and maintaining the fairness of the transaction. As a key metering device in power generation enterprises, network connections between power grids, inter-provincial network connections, and other metering devices, the importance of checkpoint energy measurement is self-evident. Therefore, studying the causes of metering errors and the classification of outlier checkpoint metering devices is significant. A remote out-of-tolerance gateway electric energy meters classification method based on feature selection and deep belief network is proposed. This paper first uses Spearman and Pearson correlation coefficients to select the main influencing factors of checkpoint energy metering error and then trains a deep belief network model to complete the detection of outlier checkpoint energy metering. Finally, experimental results verify the superiority of the proposed method.
An Ancient Glass Component Analysis Identification Model Based on Correlation Analysis and Neural Network Algorithm
Authors: Jiang Jiamin , Yang Jinchen , Chen Xiao
Published: February 2024

Identification models for glassware are important because the influence of the burial environment on the degree of weathering of old glass can lead to an inaccurate assessment of its category. This paper explores the relationship between glass surface weathering and decoration, color and type by Chi-square test and Fisher’s exact test. The experiment results show that the surface weathering degree of glass is not related to its pattern and color, but is significantly related to its type. This paper has introduced a new method to obtain important characteristic factors for distinguishing high potash glass and barium lead glass and for subclassification by Random Forest Model, so as to carry out R-type clustering to obtain classification results with 95% accuracy and high sensitivity. To identify the unknown category of cultural relics, the method of applying the BP neural network with the Bayesian regularization algorithm for training is proposed to improve the generalization ability of the model. In addition, based on the Spearman correlation coefficient, the differences in chemical composition correlation between different types of glass are compared in this paper. In conclusion, this paper explores a method for modeling and validation of glass component data and constructs an identification model that takes the accuracy of classification and prediction results and high robustness into account.
Preventive Maintenance Method of Brake Pads According to CNN-LSTM Model
Authors: Wang Shuo , Yu Zhenliang
Published: February 2024

In this paper, a preventive maintenance method of brake pads according to CNN-LSTM is proposed to solve the problem of brake pads reaching their service life and failing to call for maintenance in time. In this method, CNN network is used to complete the multidimensional extraction of spatial features of brake pads, and LSTM network is used to complete the capture of time series features, and the spatial-temporal relation between the initial signal of brake disc and the abrasion value is constructed. When the abrasion value exceeds the specified range, intelligent warning is carried out to realize the preventive maintenance of brake pads. According to the data, it can be seen that the CNN-LSTM hybrid algorithms can accurately monitoring the abrasion value of brake disc, the MAE and RMSE value are decreased, and the Determining parameter R2 is increased.
Predictive Modelling for Wordle Game: Analysing Word Attributes and Future Trends
Authors: He Jingdi
Published: February 2024

Wordle, an engaging online crossword puzzle, challenges players to decipher a hidden five-letter word. In this manuscript, our primary focus lies in predicting the distribution of reported results in the Wordle game. To accomplish this, we devised and compared multiple predictive models, seeking the most accurate and stable solution. The foundation of our research revolves around training 31 distinct word attributes through five diverse multi-output regression data processing models. Then we choose a model whose average error of the test set error is very small, indicating that the prediction accuracy of our model is better, and also more stable than other models. Finally, to illustrate the practical application of our model, we provide a concrete example of predicting the associated percentages of (1, 2, 3, 4, 5, 6, X) for the word “EERIE” in future game instances.
Navigating Complexity: Uncovering the Intricate Dynamics Between Intellectual Capital, Efficiency, and Performance in Taiwan’s Banking Sector
Authors: Martens Wil
Published: February 2024

As the global landscape places greater emphasis on intangible assets, the role of intellectual capital (IC) in adding value has gained heightened importance. This study examines the role of IC, technical efficiency, and income diversity in shaping the performance of Taiwan’s banks. Using the resource-based view of the firm, it investigates the relationship between IC and firm performance, the impact of well-organized technical efficiency on bank performance, and the influence of income diversity on bank performance. This paper employs Fixed Effects regression and Generalized Method of Moments models to analyze the research questions. The findings reveal a complex landscape wherein it is shown that IC has a limited impact on profitability, but technical and intellectual capital efficiency can positively influence bank performance. Implications for both theory and practice are discussed.
UPAYA PENINGKATAN KEMAMPUAN NUMERASI SISWA MELALUI PEMBELAJARAN KONTEKSTUAL DENGAN BANTUAN GAME SEDERHANA
Authors: Fitri Yusliana , Juliani Siska
Published: February 2024

Tujuan dari penelitian ini adalah memperbaiki Pembelajaran yang dilakukan guru dikelas untuk meningkatkan kemampuan numerasi siswa melalui Pembelajaran kontekstual dengan bantuan game sederhana. Jenis penelitian ini adalah penelitian Tindakan kelas (action research) subjek penelitian ini siswa kelas VI SDN 1 Kuala Dua Belas dengan jumlah subjek sebanyak 8 orang. Teknik pengumpulan data yaitu tes, observasi dan wawancara. Penelitian ini dilakukan dalam dua siklus yaitu siklus I dan siklus II. Setiap siklus terdiri dari tiga tahap yaitu perecanaan, tindakan, dan evaluasi atau refleksi. Berdasarkan hasil penelitian diketahui bahwa adanya peningkatan kemampuan numerasi siswa dari siklus I ke siklus II. Pada siklus I siswa yang tuntas hanya sebesar 12.5% sedangkan pada akhir siklus II siswa yang tuntas menjad 75%. Sehingga dapat disimpulkan bahwa Pembelajaran kontekstual dengan bantuan game sederhana dapat meningkatkan kemampuan numerasi siswa kelas VI SDN 1 Kuala dua belas.
Religion, Theology, and Philosophical Skills of LLM–Powered Chatbots
Authors: Trepczyński Marcin
Published: February 2024

In this study, I demonstrate how religion and theology can be useful for testing the performance of LLMs or LLM–powered chatbots, focusing on the measurement of philosophical skills. I present the results of testing four selected chatbots: ChatGPT, Bing, Bard, and Llama2. I utilize three examples of possible sources of inspiration from religion or theology: 1) the theory of the four senses of Scripture; 2) abstract theological statements; 3) an abstract logic formula derived from a religious text, to show that these sources are good materials for tasks that can effectively measure philosophical skills such as interpretation of a given fragment, creative deductive reasoning, and identification of ontological limitations. This approach enabled sensitive testing, revealing differences among the performances of the four chatbots. I also provide an example showing how we can create a benchmark to rate and compare such skills, using the assessment criteria and simplified scales to rate each chatbot with respect to each criterion.
Olhares e percepções sobre o aprendizado no Ensino Fundamental I no período pós pandêmico em uma escola Municipal de Niterói-RJ
Authors: Pinto Rita De Cassia Martins Moreira , Quintana Luciana
Published: February 2024

O presente trabalho trata-se de uma reflexão acerca do cotidiano escolar em uma escola do município de Niterói, no Rio de Janeiro, após dois anos do retorno das aulas pós pandemia. A metodologia utilizada foi relatos de profissionais do magistério que atuam diretamente com docentes, estudantes e famílias afetadas pelos impactos causados pela Covid-19 e ratificadas pela carência de políticas públicas ou a falta de aplicação delas na educação básica municipal. Baseado em dados estatísticos e, principalmente, numa pedagogia do acolhimento, escuta e cuidado, percebeu-se a necessidade de criar ações voltadas para a recuperação da autoestima e aprendizagem de estudantes, que foram perdidas durante o período de isolamento. Embora os profissionais da educação tenham se dedicado e se articulado para minimizar os impactos deixados pela pandemia no retorno às aulas, grande parte dos estudantes pertencentes às classes populares, apresentaram carências e defasagens em leitura e escrita, associada à crescente taxa de evasão escolar. Portanto, pôde-se concluir com este trabalho, o surgimento de um desafio para os próximos quatro anos: a necessidade de políticas públicas para atender essa demanda que é mais que urgente.
GOVERNMENT DEBT INSTRUMENTS WITH EMBEDDED DERIVATIVES IN UKRAINE: RISKS ANALYSIS
Authors:   National University of Kyiv-Mohyla Academy, Tarnavskyi Oleksandr
Published: February 2024

This article identifies key risks that investors in Ukrainian dollar-linked government bonds face, namely model risk, currency risk, volatility risk, interest rate risk, time risk. Most of the open literature on the subject of Ukrainian dollar-linked government bonds concentrates on the risks to the issuer (risks to the government finance). As this instrument constitutes a significant part of state-owned banks’ portfolios, it is of high need to understand the risks from the investors’ standpoint. It is noted that other developing economies are known to issue dollar-linked debt securities, for example Brazil, which also experienced investors’ the lack of confidence in local currency. Studies concerning indexed debt securities in Ukraine and worldwide are analysed. This research points out the most important in terms of valuation and risks analysis characteristics of Ukrainian dollar-linked government bonds. Fair value of Ukrainian banks’ portfolios of dollar-linked government bonds is decomposed into the value of plain bond, intrinsic value of embedded option and time value of embedded option. Key components of model risk for investors are identified, namely input risk and assumption violation risk. Risk metrics (Greek letters) of banks’ portfolios in dollar-linked government bonds are computed and compared between investor banks based on Black-Scholes fremework. Based on risk metrics, it is concluded that Ukreximbank faces the highest time risk (relative to its regulatory capital), while Privatbank’s portfolio is the most sensitive to changes in US interest rates. It is highlighted that time risk cannot be diversified or hedged, which should be accounted for by banks. Methods for management of identified risks are proposed. Risk factors’ contributions to revaluation if dollar-linked government bonds portfolios of banks during the first year of full-scale russian invasion of Ukraine are computed and compared between banks. It is noted that for deeper analysis of investor banks’ risks one should consider banks’ open currency position and changes in the costs and volume of funding.
РОЗПІЗНАВАННЯ ТА МОНІТОРИНГ ВОДНИХ ОБ’ЄКТІВ НА ОПТИЧНИХ СУПУТНИКОВИХ ЗОБРАЖЕННЯХ ІЗ ВИКОРИСТАННЯМ МАШИННОГО НАВЧАННЯ
Authors: КАШТАН Віта , ГНАТУШЕНКО Володимир , УДОВИК Ірина , ШЕВЦОВА Ольга
Published: February 2024

Річки, озера та відкриті водойми є ключовими компонентами для розвитку навколишнього середовища, особливо в міських екосистемах. Точні карти міських поверхневих водних об’єктів на основі супутникових даних є важливою передумовою для кращого та швидшого прийняття рішень щодо моніторингу міських екосистем, впливу міських теплових островів та адаптації до зміни клімату. В роботі запропоновано інформаційну технологію розпізнавання та моніторингу водних об’єктів на оптичних супутникових зображеннях з використанням машинного навчання. Розроблена технологія складається з восьми етапів: завантаження первинних даних; геоприв’язка растрових зображень; попередня обробка даних; сегментація даних для визначення границь водних об’єктів та ділянки землі; оцифрування берегової лінії; створення бінарної маски; картографування контурів водних об’єктів з використанням топографічної карти та аналіз просторово-часових змін. Машинне навчання використовується для сегментації зображень, а метод опорних векторів (SVM) використовується для картографування контурів водних об’єктів. Це дозволяє отримати результати з субпіксельною точністю, забезпечуючи важливу інформацію для подальших досліджень та прийняття рішень. Експерименти проведено на супутникових даних Sentinel-2 для моніторингу водних об’єктів з просторовим розрізненням 10 метрів. Областю дослідження стала берегова лінії Одеської області – Національний природний парк "Тузлівські лимани". Порівняльний кількісний аналіз з існуючими методами, такими як водні індекси та K-means, підтверджує високу точність розробленої технології протягом 2016–2023 років (точність від 96.96% до 97%). Коефіцієнт Каппа, який враховує ступінь узгодженості між реальною та передбачуваною класифікацією, підтверджує високу стабільність та достовірність підходу (0.94). Технологія моніторингу водних об’єктів на оптичних супутникових зображеннях з використанням машинного навчання може бути використана для дослідження змін на прибережних територіях, прийняття рішень в галузі управління прибережними ресурсами та земельним використанням.
El Parque Estatal Cerro de la Tortuga como reservorio de la herpetofauna en la región centro-sur del estado de Morelos
Authors: Chávez-Ramírez E. A. , López-Cortes I. , Jiménez-Piedragi C. D.
Published: February 2024

The Cerro de la Tortuga State Park as a herpetofauna reservoir in the central region of Morelos
The Cerro de la Tortuga State Park (PECT) in the south-central region of the state of Morelos in Mexico is an important reservoir of amphibian and reptile diversity. The objective of this study is to update the inventory of amphibians and reptiles and to determine the composition, species richness, species-area relationship and similarity of the herpetofauna between reserves with different types of administration. The herpetofauna within the PECT was composed of 28 species, equivalent to 20 % of the herpetofauna of Morelos and 1.97 % of the herpetofauna of Mexico. The Squamata order was the best represented group, with 17 species (60.71 %), followed by Anura with 10 species (35.71 %) and Testudines with 1 species (3.57 %). The agreement with the analysis of the species/area relationship, REBIOSH (3 spp.) and PECT (1 spp.) harbor a greater number of species than expected with respect to CBCH (3 spp.), which harbors a lower number. of species than expected. The similarity of the herpetofaunistic composition of the PECT result is greater between the RESM (50 %) and the REBIOSH (34 %), compared to the CBCH (12 %). Our results indicate that the PECT acts as an important reservoir for the herpetofauna of the south-central region of Morelos, which could structurally be part of the so-called conservation archipelagos. However, in addition to evidence of composition and similarity between reserves, we suggest developers consider habitat quality for corridor identifiers and genetic studies that demonstrate gene flow for species shared between reserves.
Financiamiento colectivo (Crowdfunding)
Authors:   Universidad de Guadalajara, Barrera Salvador
Published: February 2024

La Ley para regular las instituciones de tecnología financiera, apareció el 9 de marzo del 2018 en el Diario Oficial de la Federación y proporciona un marco legal a las empresas Fintech1 para el financiamiento a través de un colectivo para deuda, capital, copropiedad o regalías y permite que las startups (empresas emergentes) ofrezcan servicios a través de páginas web, redes sociales y aplicaciones con el fin de facilitar y hacer más fácil su proceso de atención, logrando que un conjunto de particulares aporten para cubrir un capital a empresas típicamente innovadoras, prestamos entre particulares, proyectos comunitarios u otros como libros, películas, álbumes de música, eventos, videojuegos y productos orientados al consumidor . Este procedimiento permite hacer preordenes y compartir ganancias. En ese trabajo se estudiará su concepto, características, se analizará casos de éxito en México, en las categorías de recompensa, deuda, capital y donación. Se revisará una empresa representativa de cada categoría, como lo son: Fondify, Prestadero, Play Business y Donadora.
Analisis Du Pont System Untuk Mengukur Kinerja Keuangan Pada Industri Media Dan Hiburan Yang Terdaftar Di BEI Tahun 2017-2021
Authors: Rahmawati Tri Indah , Hurriyaturrohman Hurriyaturrohman , Rizqi Muhamad Nur
Published: February 2024

Penelitian ini bertujuan untuk mengetahui serta menganalisis kondisi kinerja keuangan pada Industri Media dan Hiburan yang terdaftar di Bursa Efek Indonesia dengan analisis Du Pont System tahun 2017-2021. Metode yang digunakan adalah analisis Du Pont System dengan pendekatan kuantitatif deskriptif dengan data sekunder berupa laporan keuangan industri media dan hiburam tahun 2017-2021 yang meliputi perhitungan Net Profit Margin (NPM), Total Assets Turnover (TATO), Return On Investment (ROI), Equity Multiplier (EM) dan Return On Equity (ROE). Berdasarkan hasil penelitian diperoleh kesimpulan bahwa kinerja keuangan 5 industri media dan hiburan memiliki nilai TATO,ROI, EM dan ROE tahun 2017-2021 rendah dibawah standar industri dengan kinerja keuangan yang kurang baik. Namun, PT. Media Nusantara Citra Tbk dan PT. Surya Citra Media Tbk mampu menghasilkan nilai NPM diatas standar industri dengan kinerja keuangan yang baik yang dimana tingkat pendapatan setiap tahunnya terus meningkat walaupun sempat menurun ditahun 2020.
Analisis Rasio Keuangan Untuk Menilai Kinerja Keuangan Pada PT. Aneka Tambang Tbk yang Terdaftar di BEI Periode 2017-2021
Authors: Adelya Ficka , Sundarta M. Imam
Published: February 2024

This study aims to determine and assess financial performance using liquidity ratios, solvency ratios, and profitability ratios at PT. Aneka Tambang Tbk. The data collection method in this study is to use secondary data, namely financial reports from 2017-2021. This study analyzed data using descriptive methods with a qualitative approach. Based on the results of the research, it shows that the average value of the liquidity ratio in 2017-2021 is in an illiquid state because it is below the industry standard, which means that the company has not been able to manage its assets optimally, so that the company's short-term debt is greater than the company's current assets. The solvency ratio shows that the average value in 2017-2021 is in a solvable state because it is below the industry standard, which means the company is capable of meeting its debts. And the profitability ratio shows that in 2017-2021 it is not profitable because it is below industry standards, which means that the company's ability to generate good profits from sales, total assets and total equity of the company is still not good because the cost of goods sold continues to increase.
Making Visible: The Diorama, the Double and the (Gothic) Subject
Authors: Thomas Sophie
Published: February 2024

Of the pictures opening at the Diorama in Regent's Park in 1830, The Times made the following note:

The views at the Diorama are again changed, and France and Switzerland are once more placed before our eyes without our encountering the nausea of crossing the Channel, the roguery of continental innkeepers, and all the other innumerable and indescribable miseries of foreign travel. Thanks to the contrivances of modern ingenuity, the "long drawn aisles and fretted vaults" of the Cathedral at Rheims are now fixed snugly in the Regent's-park, and the rocks of Mont St. Gothard, torn from their old foundations, are reposing quietly in the same vicinity. All this is owing to the magic pencil of Messrs. Daguerre and Bouton, who, if they have not given us the realities of these magnificent objects, have at least given us imitations of them so wonderfully minute and vivid, as to appear more like the illusions of enchantment than the mere creations of art. (22 April 1830)

The continued appeal of the London Diorama, after seven years in business, is neatly conveyed here: questions of convenience aside, the Diorama as a form of popular visual entertainment retained an impressive power to create and control the field of the visible, and to produce illusions so convincingly "real" that they appeared to be the result of magic rather than the "mere" work of art.
The Effect of Mol of Rice Water Waste and Kepok Banana Peel to The Growth of Brassica rapa chinensis
Authors: Yuliana Meta , Dewi Belia Murni , Teristiandi Novin
Published: February 2024

MOL merupakan larutan fermentasi oleh mikroba dan bersumber dari bahan organik seperti kulit pisang. MOL berguna dalam mendorong penguraian bahan organik dan dapat digunakan sebagai pupuk organik cair karena mengandung NPK. Penelitian ini bertujuan untuk pengaruh fermentasi campuran air cucian beras putih dan kulit pisang kepok terhadap pertumbuhan tanaman pakcoy (Brassica rapa chinensis) dan untuk mengetahui konsentrasi terbaik MOL dari kulit pisang kepok yang diberikan. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) dengan 5 perlakuan dan 5 ulangan. Perlakuan pada penelitian ini adalah P0 (kontrol), P1 (10%), P2 (20%), P3 (30%), dan P4 (40%). Data dianalisis menggunakan analisis varians (ANOVA) yang dilanjutkan dengan Uji Duncan pada taraf signifikansi 5%. Hasil penelitian menunjukkan bahwa MOL kulit pisang kepok berpengaruh terhadap pertumbuhan tanaman pakcoy pada beberapa parameter yaitu berat basah, berat kering dan panjang akar tanaman namun tidak terhadap tinggi dan jumlah daun tanaman pakcoy. Perlakuan P2 (20%) menunjukkan hasil terbaik.
Multi-objective Colliding Bodies Optimization Algorithm for the Obnoxious p-median Problems
Authors: Kaveh Ali , Mahdavi Vahid Reza
Published: February 2024

The obnoxious p-median problem consists of locating p facilities among a set of sites such that the sum distance from any demand to its nearest facility and the dispersion among facilities are maximized. In this paper, the multi-objective colliding bodies optimization algorithm (MOCBO) is utilized to obtain the trade-off curve of the obnoxious p-median problems. The performance of the developed optimization method is investigated for locating obnoxious facilities through two case studies to maximize the two conflicting objectives. The performance of the MOCBO algorithm is further compared with those of the MPSO and NSGA-II algorithms representative of the state of the art in the field of multi-objective optimization. In this study, the MOCBO algorithm showed suitable convergence performance and generalization abilities compared to the MPSO and NSGA-II algorithms.
السلوك الجازم وعلاقته بمستوى الطموح لدى لاعبات كرة القدم صالات نادي فتاة اربيل الرياضي
Authors: Teacher .Dr. Bekhal is forgiving and honorable
Published: February 2024

هدف البحث هو التعرف على العلاقة بين السلوك الجازم ومستوى الطموح لدى لاعبات كرة القدم صالات نادي فتاة اربيل الرياضي ،حيث استخدمت الباحثة المنهج الوصفي باسلوب العلاقات المتبادلة لكونه يسعى الى جمع البيانات من أفراد المجتمع ومحاولة تحديد الحالة الراهنة للمجتمع في متغيرات معينة من خلال استخدام كل من مقاييس السلوك الجازم ومستوى الطموح لدى لاعبات كرة القدم صالات نادي فتاة اربيل  ، ﺘﻡ ﺍﺴﺘﺨﺩﺍﻡ المقاييس كأدوات للبحث ، واستخدمت الباحثة عدد من الوسائل الاحصائية لمعالجة النتائج التي حصلت عليها مثل الوسط الحسابي والانحراف المعياري ومعامل الارتباط البسيط (بيرسون). وتم إختيار عينة البحث من مجتمع البحث المكون من لاعبات كرة القدم للصالات والبالغ عددهن  (  20 )  لاعبة  ،وبعد عرض النتائج ومناقشتها توصلت الباحثة الى وجود علاقة معنوية  طردية قوية  بين السوك الجازم  ومستوى الطموح الرياضي للاعبات كرة القدم صالات نادي أربيل .  وفي ضوء ما تم التوصل إليه من الإستنتاجات الإستفادة  وضرورة الاهتمام بالنساء في كل جوانب الحياة وفي جميع الالعاب ، وخاصة الجانب النفسي ، حيث اصبح إدراج أخصائي نفسي في فرق كرة القدم النسوي اكثر من ضروري . كما يجب على المدرب والادارية الاهتمام والتركيز بالجهد المبذولة من قبل اللاعبة وليس النتيجة ، والعمل على زيادة الثقة لدى لاعبة القدم في المواقف التنافسية والتدريبية .وإجراء دراسات لوضع برامج تدريبية لتعزيز السلوك الجازم  في مختلف الرياضات التنافسية .وتنمية سمة مستوى الطموح لدى اللاعبات مما يتفق مع الواقع الرياضي والاجتماعي بما يخدم نجاحاتهم المستقبلية والعمل على الحيلولة دون وقوعهم في اليأس والإحباط .
Perlindungan Terhadap Pengetahuan Tradisional Makanan Khas “Gulai Ikan Mungkus” Sebagai Kekayaan Intelektual Komunal Kabupaten Kaur
Authors: Winata Nugraha Pandu , Susetyanto Joko , Ganefi  , Hamdani
Published: February 2024

Tujuan penelitian ini adalah untuk mengetahui : 1). Bagaimana bentuk upaya perlindungan Pengetahuan Tradisional makanan khas Gulai Ikan Mungkus yang dilakukan oleh pemerintah Daerah Kabupaten Kaur, Pelaku usaha rumah Makan tradisional Kabupaten Kaur dan Masyarakat Kabupaten Kaur, dan 2). Bagaimana Peran Pemerintah Kabupaten Kaur Untuk Melakukan Pendaftaran Makanan Khas Gulai Ikan Mungkus Sebagai Pengetahuan Tradisional Kabupaten Kaur, Penelitian ini merupakan  penelitian hukum empiris, dengan  menggunakan pendekatan yuridis sosiologis. Pengumpulan Data dilakukan dengan wawancara kepada respoden / sample yang terpilih, observasi,  dan studi dokumen. Pengolahan data dimulai dari coding dan dan dilanjutkan dengan editing data. Setelah semua data yang relevan lengkap dan tidak ada kesalahan, dilanjutkan dengan analisis data dengan menggunakan analisis kualitatif. Untuk selanjutnya dideskripsikan dalam rangka menjawab tujuan penelitian. Hasil penelitian menunjukkan bahwa : 1). bentuk upaya perlindungan Pengetahuan Tradisional makanan khas Gulai Ikan Mungkus yang dilakukan oleh Pemerintah Daerah Kabupaten Kaur adalah dengan cara : melakukan  pendataan para pelaku rumah makan yang menjual makanan khas Gulai Ikan Mungkus untuk selanjutnya diikut sertakan dalam acara festival yang diadakan oleh Pemerintah Kabupaten Kaur, menghimbau kepada semua elemen masyarakat untuk melakukan pendaftaran makanan khas Gulai Ikan Mungkus ke Dinas Pendidikan dan Kebudayaan, pembudidayaan ikan Mungkus, serta memperkenalkan makanan khas Gulai Ikan Mungkus ini kepada wisatawan luar yang datang berkunjung ke Kabupaten Kaur. Bentuk upaya perlindungan pelaku usaha rumah makan tradisional dengan tetap menjaga nilai luhur dan cita rasa makanan tradisional Gulai Ikan Mungkus, 2). Pemerintah Kabupaten Kaur belum berperan dalam melakukan pendaftaran makanan khas Gulai Ikan Mungkus.
Penegakan Hukum Tindak Pidana Korupsi Penyimpangan Penjualan Aset Tanah Milik Pemerintah Daerah Kota Bengkulu
Authors: Junaidi Fery , Herlambang  , Karo Lidia Br
Published: February 2024

Penegakan hukum tindak pidana korupsi penyimpangan penjualan aset tanah milik pemerintah daerah Kota Bengkulu belum maksimal, karena penanganan perkara oleh aparat penegak hukum dilakukan penuntutan secara terpisah terhadap para terdakwa dan sanksi pidana yang diputus oleh majelis hakim lebih ringan dari tuntutan jaksa penuntut umum. Tujuan penelitian ini: (1) Untuk mengetahui dan menganalisis penegakan hukum tindak pidana korupsi penyimpangan penjualan aset tanah milik pemerintah daerah Kota Bengkulu. (2) Untuk mengetahui dan menganalisis hambatan penegakan hukum tindak pidana korupsi penyimpangan penjualan aset tanah milik pemerintah daerah Kota Bengkulu. (3) Untuk mengetahui dan menganalisis upaya menanggulangi hambatan penegakan hukum tindak pidana korupsi penyimpangan penjualan aset tanah milik pemerintah daerah Kota Bengkulu. Penelitian hukum ini termasuk penelitian hukum empiris. Hasil penelitian bahwa: (1). Penegakan Hukum Tindak Pidana Korupsi Penyimpangan Penjualan Aset Tanah Milik Pemerintah Daerah Kota Bengkulu, diawali dengan menerima laporan masyarakat dilanjutkan dengan proses penyelidikan dan penyidikan oleh penyidik Kejaksaan Negeri Bengkulu, selanjutnya diterbitkan surat bahwa berkas perkara tersebut dinyatakan lengkap (P-21) oleh Kejaksaan Negeri Bengkulu, dan selanjutnya Hakim Pengadilan Negeri/PHI/Tipikor Bengkulu Kelas IA memeriksa terdakwa dan barang bukti, serta saksi-saksi yang dihadirkan oleh jaksa penuntut umum. (2). Hambatan Penegakan Hukum Tindak Pidana Korupsi Penyimpangan Penjualan Aset Tanah Milik Pemerintah Daerah Kota Bengkulu yaitu; minimnya sarana dan prasarana penyidikan, terbatasnya jumlah penyidik Tipikor Kejaksaan Negeri Bengkulu, Jaksa peneliti mempunyai kewenangan terbatas dalam menetapkan tersangka lain dan Hakim tidak menetapkan tersangka lain. (3).Upaya Menanggulangi Hambatan Penegakan Hukum Tindak Pidana Korupsi Penyimpangan Penjualan Aset Tanah Milik Pemerintah Daerah Kota Bengkulu yaitu; meningkatkan sarana dan prasarana serta anggaran penyidikan, menambah jumlah penyidik Tipikor Kejaksaan Negeri Bengkulu, jaksa peneliti melakukan tindakan tegas pengembalian berkas perkara untuk dilengkapi oleh penyidik. Jika tidak dipenuhi jangan di P21 dan berkas dikembalikan, dan hakim dapat menerapkan prinsip ultra petita dalam putusan penetapan tersangka.