bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization Of Keyhole Regime For Laser Powder Bed Fusion: From Single Track Formation To Multi Layers Volume, The Change In Laser And Matter Interaction
Authors: Guillon Maxence , Boulnat Xavier , Lambert Pauline , Lachambre Joël , Elguedj Thomas , Desrayaud Christophe
Published: October 2024

Laser Powder bed Fusion is a strong process enabling the on-demand production of components with complex geometry and high added value. Despite its strengths, there are still significant challenges to fully understanding the interaction between laser and powder. The interaction between laser and material differs significantly between single tracks and multiple tracks. In a single track, the laser only interacts with the powder. In contrast, for multiple tracks, the laser interacts also with the previously laid tracks. This underscores the inadequacy of characterizing only a single track for a comprehensive understanding of the interactions between laser and powder. Moreover, previous analyses show a focal shift that cannot be neglected on the machine used. Hence, this works aims at characterizing the melt pool during the formation of a single and multiple tracks with 316L powder material. The consequence of the focal shift is observed and measured.
A Comparative Study Of The Meaning Of Life, Academic Motivation, Learning Styles, Study Habits, And Academic Achievement Between University And College Students In Different Educational Institutions
Authors: Ahmad Laique
Published: October 2024

In the rapidly evolving landscape of education, understanding the factors that contribute to students' academic success is more critical than ever. This study aimed to conduct a comparative analysis of the meaning of life, academic motivation, learning styles, study habits, and academic achievement between university and college students across different educational institutions. Using a sample of 800 participants, equally divided between university and college students, data were collected through validated questionnaires, including the Purpose in Life Test, Academic Motivation Scale, VARK Learning Styles Questionnaire, and Study Habits Inventory. Academic achievement was assessed using students' GPA records and their most recent semester results. Descriptive statistics, independent samples t-tests, and correlation analyses were employed to analyze the data. The results indicated that university students exhibited significantly higher levels of meaning of life, academic motivation, and study habits compared to college students. Positive correlations were identified between meaning of life and academic motivation, as well as between study habits and academic achievement, suggesting that these variables are interlinked in influencing student performance. Furthermore, regression analysis demonstrated that academic motivation, learning styles, and study habits significantly predicted the meaning of life in students, accounting for 62% of the variance. The study's findings underscore the importance of fostering educational practices that enhance intrinsic motivation, promote a sense of purpose, and support effective study strategies in students. These insights are crucial for educators, policymakers, and institutions aiming to create learning environments that facilitate both academic success and personal development. Limitations of the study include its reliance on self-reported data and the relatively homogenous sample, suggesting that future research should focus on more diverse populations and longitudinal approaches to understand the long-term effects of these educational factors on student outcomes.
Blended Learning the new normal of Education
Authors: Subramanian Iyer Shankar , K. Singh Amit , Divakar G.M , Malhotra Sangeeta
Published: October 2024

Online Learning is part of Blended learning and is a learning technique in which use of both ordinary teaching and advanced modern online teaching, online learning materials are largely used.
Templenomics, The fuTure of vibranT bharaT(inDia)
Authors: Subramanian Iyer Shankar , Seetharaman A , Subramanian Raman , Maddulety K , Divakar G.M , Nair Bindu , K. Singh Amit
Published: October 2024

Templenomics presents a visionary approach to shaping the future economic landscape of Bharat (India) by leveraging its rich cultural heritage, technological advancements, and demographic dividend.
Non-Retrogression as Progress
Authors: Castagnari Aznar Valentina , Serrano Guzmán Silvia
Published: October 2024

Latin America has often led the way in protecting the right to health, particularly in regulating risk factors such as tobacco and unhealthy diets. However, some of these advancements have recently been jeopardized as governments prioritize private economic interests over health. Judicialization has thus emerged as an opportunity – perhaps the only one – to defend progress achieved. Given recent judicial rulings in Uruguay and Ecuador, we reflect on the fragility of legal interventions that threaten powerful economic interests, as well as on the opportunities offered by human rights-based litigation.
Autonomous driving decision-making control algorithm based on hierarchical reinforcement learning
Authors: Weidong Li , Caoyuan Ma , Hao Shi , Heng Cao
Published: October 2024

In the decision-making model of autonomous driving based on learning, the reinforcement learning model has the problems of slow convergence and single application scenario, while the imitation learning model has the problem of poor generalization. In order to solve this problem, a two-layer reinforcement learning framework is proposed to replace the decision layer and control layer in the autonomous driving task. The decision layer divides the driving behavior into lane keeping, left lane change and right lane change. After the decision layer selects the corresponding behavior, it completes the behavior by changing the input of the control layer. Then, a new method for training the control layer, RL_COE (Reinforcement learning combined with online experts), is proposed by combining reinforcement learning and online experts. Finally, a highway simulation environment is built in Carla to verify the proposed algorithm and compare it with the reinforcement learning baseline algorithm. The results show that this method greatly improves the convergence speed and stability of the algorithm and can better complete the driving task.
Complexity analysis of air traffic based on complex networks under TBO mode
Authors: Yating Peng , Daskin Mark , Williams Sarah , Minggong Wu
Published: October 2024

Since the complex network constructed according to the unified separation standard does not take into account the differences in the operation of aircraft types, it cannot meet the refined requirements of air traffic complexity analysis under trajectory based operation (TBO). To solve this problem, an air traffic complexity analysis model based on complex networks to distinguish different aircraft types is proposed. Firstly, a calculation model for lateral flight safety intervals of different aircraft types is established, an aircraft precise protection zone is constructed, and the basis for determining the aircraft connection in the flight conflict network is optimized. On the basis of considering information such as aircraft heading and speed, flight conflict judgment pays attention to the different performance and status of aircraft, so that the flight conflict network can be closer to the operation mode of TBO. Through experimental simulation of the TBO operation environment and verification using radar data from Gaoqi Airport, the results show that compared with the previous flight conflict network, the model can refine the horizontal separation standards between aircraft, reduce the complexity of the airspace, reduce the workload of controllers, and improve the operation efficiency of the airspace, and provide more space for aircraft to autonomously select the optimal trajectory.
Molecular spectral line data preprocessing container load grouping prediction algorithm based on EMD-LSTM
Authors: Ye Xianchen , Bayo Amelia , Hansen Freya , Zhang Yazhou , Du Xu , Li Jia , Wang Wanqiong
Published: October 2024

Unbalanced allocation of container resources in cluster environments is an urgent problem to be solved. Aiming at container load prediction and resource allocation strategy, this paper designs an astronomical data processing container load grouping prediction algorithm based on empirical mode decomposition-long short-term memory network, and proposes an adaptive recommendation value generation algorithm based on predicted load information, which can automatically allocate container computing resources according to the degree of load fluctuation. The load prediction accuracy is verified using simulated data and real astronomical observation data. The experimental results show that the algorithm proposed in this paper has higher prediction accuracy than the triple index method and the single long short-term memory network model. In the real-time preprocessing test of astronomical data, the recommendation value generation algorithm proposed in this paper can effectively improve the utilization efficiency of computing resources compared with the default strategy.
Prediction of potential conflicts between active targets in airport flight zones based on LSTM
Authors: Eagleton Michael , Smith James , Nakashima Kenichi
Published: October 2024

Aiming at the problem of constant conflicts in airport flight zones, a method based on LSTM to predict potential conflicts of active targets in airport flight zones is proposed. Firstly, based on the complex network theory, two types of active targets, aircraft and vehicles, are taken as the research objects, and the flight zone active target network is established. The network dynamic evolution model is set up, and the operation data is input to calculate multiple network characteristic indicators. The principal component analysis of the indicator time series is performed to fit the potential conflict index; then, the Keras framework is used to build a long short-term memory neural network (LSTM) model, and the indicator time series is input into LSTM for training and prediction, and compared with other prediction methods; finally, the actual operation data of Xi'an Xianyang Airport is used for experiments, and the predicted values are compared with the true values. The mean square errors of the prediction results of each indicator are respectively 1.61%、13.13%、0.72%、0.004%、0.014%; The research shows that by establishing the flight zone active target network model, the network characteristic indicators can be used to characterize potential conflicts from different angles; LSTM can effectively predict the potential conflicts of the flight zone active target network, remind relevant personnel to pay attention to preventing conflicts and reducing the probability of conflicts.
CY GNSS significant wave height inversion model based on multivariate machine learning
Authors: Zhang Yun , Xiao Sheng , Jiang Lifei , Meng Wanting , Yang Shuhu , Han Yanling
Published: October 2024

The Cyclone Global Navigation Satellite System (CYGNSS) provides high-quality Global Navigation Satellite System Reflectometry (GNSS-R) data, which can be reliably used for the inversion of Significant Wave Height (SWH). Due to the high dynamics of CYGNSS, the received signal is easily affected by environmental factors, and the complexity of the sea conditions makes it difficult for simple models to accurately invert SWH. In order to solve the above problems, this paper proposes a multivariate SWH inversion model based on machine learning. According to the formation mechanism of waves and the correlation analysis between CYGNSS parameters and SWH, relevant parameters are selected, and three training schemes of 5 parameters, 9 parameters and 17 parameters are designed. Subsequently, the inversion model was trained and validated using Random Forest (RF) and Convolutional Neural Network (CNN), and the SWH inversion results were compared with the reference values of the European Centre for Medium-range Weather Forecasts (ECMWF). The best inversion model was the 17-parameter CNN inversion model with an RMSE of = 0.1840 m.
A Novel Fault Diagnosis Method for Rolling Bearings Based on Multi-Domain Adaptation Neural Network
Authors: Keskinocak Pinar , Wilson Brian , Scott Megan
Published: October 2024

In recent years, data-driven approaches have shown promise in fault diagnosis. However, in practical industrial applications, challenges such as discrepancies between source domain and target domain data distributions, coupled with limited labeled fault data, have hindered the performance of traditional domain adaptation algorithms in bearing fault diagnosis. To address this issue, this study introduces a novel method based on MDANN (Multi Domain Adaptation Neural Network) for diagnosing rolling bearing faults using unlabeled data. Initially, the raw vibration signals are preprocessed using wavelet packet decomposition and reconstruction (WPT), which helps minimize signal redundancy while preserving critical features. Following this, the multi-kernel maximum mean discrepancy (MK-MMD) algorithm is employed to compute the differences in input feature values, and the MDANN network parameters are adjusted via backpropagation, allowing the network to extract domain-invariant features. To ensure the unlabeled target domain data can be effectively used in training, a pseudo-labeling strategy is applied, where the label with the highest probability is treated as the true label, thereby enabling the model to learn from the target domain data and improve the acquisition of reliable diagnostic knowledge. The method is validated using two publicly available datasets, CWRU and PU, with experimental results demonstrating that it outperforms conventional domain adaptation techniques in terms of diagnostic accuracy. This indicates the proposed approach is highly effective in capturing transferable features and addressing the distributional differences between datasets.
Small sample composite fault diagnosis of hydraulic bearings based on improved VME algorithm and mRVM
Authors: Nocedal Jorge , Baker Matthew , King Elizabeth , Perez Joshua
Published: October 2024

The working environment of rolling bearings is complex. Once a fault occurs, various parts will affect each other and produce a compound fault. Traditional methods often use signal separation algorithms to separate different types of signals for fault diagnosis, but it is difficult to analyze specific faults efficiently and accurately. To solve this problem, this paper combines variational mode decomposition (VMD), Laplace energy index (LE) and variational mode extraction (VME) for signal extraction. Multi-class relevance vector machine (mRVM) and DS evidence theory are used for intelligent fault diagnosis, focusing on the context of small sample data. First, the VMD-LE-VME method is used to extract effective fault information from the fault signal and obtain multi-domain features. Then, the multi-domain features are input into mRVM for fault identification. Finally, the classification results are fused through DS evidence theory to obtain the final classification results. The effectiveness and superiority of this method in processing small sample data are verified by experiments.
Enhanced Speech Processing for Air Traffic Control Using an Optimized Generative Adversarial Network
Authors: Henderson Shane , Adams Kimberly , Simmons Andrew , Green Patrick
Published: October 2024

In order to improve the quality of voice calls during air traffic control, an improved SEGAN air traffic control speech enhancement algorithm is proposed. Aiming at the problem that the traditional speech enhancement algorithm based on generative adversarial network (SEGAN) is drowned under low signal-to-noise ratio conditions, a multi-stage, multi-mapping, multi-dimensional output generator and a multi-scale, multi-discriminator network model are proposed based on the SEGAN network model. First, the speech semantic features are extracted based on the deep neural network structure to complete the semantic segmentation of air traffic control speech. Secondly, multiple generators are set to further optimize the speech signal. Then, a downsampling module is added to the convolution layer to improve the model's utilization of speech information and reduce the loss of speech information. Finally, multi-scale, multiple discriminators are used to learn the distribution law and information of speech samples in multiple directions. The results show that under low signal-to-noise ratio conditions, the improved SEGAN model improves the short-term objective intelligibility (STOI) and the perceptual evaluation of speech quality (PESQ) by and respectively , which can quickly and effectively perform air traffic control speech enhancement and provide preparation for subsequent air traffic control speech recognition.
Complex system fault diagnosis based on interpretive structural model
Authors: Seepersad Carolyn Conner , Wright Nicholas , Hughes Samantha , Lee Benjamin
Published: October 2024

To realize the fault diagnosis of complex systems, a fault diagnosis method for complex systems based on the explanatory structural model is proposed. According to the fault mechanism analysis, the fault association matrix of system elements is established. The explanatory structural model is applied to transform the fault association relationship of complex systems into an intuitive hierarchical structural model through matrix transformation, so as to realize the structuring and hierarchical propagation of system faults. The PageRank algorithm is introduced to evaluate the influence and impact of system element faults. According to the influence and impact of the same-layer components and the fault transmission logic, the main cause of system fault transmission is clarified, which provides a basis for fault diagnosis. Finally, a specific application is carried out with a certain device as an example to verify the effectiveness of the method.
Dynamic model of arriving passengers based on dual value drive
Authors: Zhiwei Xing , Jun Kan , Shujie Zhu , Zishuo Liu
Published: October 2024

In order to optimize the service process of integrated transportation hubs, the dynamic characteristics of the gathering behavior of arriving passengers were analyzed, and the transformation mechanism of the gathering behavior of arriving passengers in the time dimension of inverse gamma distribution, gamma distribution and chi-square distribution was studied. It was revealed that the gathering behavior was jointly affected by the flight operation time and the utility of the transfer mode, and was converted into the time value and utility value of the arriving passengers respectively. On this basis, a dual-value-driven dynamic model of arriving passengers was established based on the three distributions, and the output was the parameter-adjustable distribution of arriving passengers. The results show that the simulation output with adjustable parameters is consistent with the real distribution, which provides a method and basis for the accurate prediction of the distribution of arriving passengers at hub airports.
Performance degradation modeling of civil aviation engines based on component characteristic map optimization
Authors: Cooper William L. , Adams Kimberly , Simmons Andrew , Green Patrick
Published: October 2024

In order to provide a theoretical basis for the degradation of the air path performance of civil aviation engines at the unit level, the CFM56-3 engine was used as the research object. First, on the basis of using the characteristic map scaling method to obtain the component characteristic equation, the selection process of the scaling reference point of the fan general characteristic map was optimized, and a surface fitting method of the characteristic map was proposed to construct an engine component-level benchmark performance model that meets specific speed conditions under steady-state conditions. Then, by introducing the fault factor to generate the fault coefficient matrix, the deviation of the engine monitoring parameters as the component efficiency decreases was calculated, and compared with the fingerprint map data of the GE training manual, it was verified that the engine steady-state performance model that integrates the fan characteristic map scaling reference point optimization and the characteristic map surface fitting method has good accuracy and use in the analysis of air path performance degradation.
Pedestrian safety behavior modeling method in human-vehicle-intelligence shared road space
Authors: Ruoma Wu , Dezhen Yang , Qi Ren , Lulu Jia
Published: October 2024

In the context of the development of autonomous vehicles sharing road resources with traditional traffic participants in the future, modeling the safe behavior of pedestrians in the shared road space between people, vehicles and intelligence is crucial for the simulation development and reliability and safety testing of autonomous vehicles. To meet this demand, the safe movement behavior of pedestrians is first analyzed, and on this basis, the traditional pedestrian social force model is improved to construct a momentum model for the interactive movement of pedestrians with other pedestrians, traditional vehicles and autonomous vehicles in the shared road space; then, the safety parameters of the model are calibrated using a data set of human-vehicle interactive movement and a genetic algorithm, and a typical shared road space scenario is built to verify the effectiveness of the model. The simulation results show that the model can simulate the real safe movement behavior of pedestrians, and has better simulation effects when used in tasks such as human-vehicle-intelligence shared road space simulation.
Vörös Imre válogatott különvéleményeinek gyűjteményéről
Authors: Kelemen Katalin
Published: October 2024

Vörös Imre, a magyar publikációs panorámában egyedülálló módon, saját bevallása szerint az utókor mérlegére kívánta tenni kilencéves alkotmánybírói tevékenységének egy "jelentős súlyú szeletét". E célból jelentette meg 2000-ben a Dixi et salvavi című kötetet, ahonnan az idézet is származik, s amely kilencéves alkotmánybírói megbízatása alatt írt tizenegy különvéleményének szövegét gyűjti össze. Egy pár oldalas, Vörös Imre által írt bevezetést követően a kiválasztott különvélemények teljes szövege található időrendi sorrendben. Vörös mindegyik különvéleményhez maga írt egy rövid felvezetőt is, amelyben címszószerűen megadja a különvélemény tárgyát, az Alkotmány hivatkozott rendelkezéseit, valamint az Alkotmánybíróság határozatának tárgyát és döntésének pár soros összefoglalását. A kötet végén tárgymutató és az Alkotmány hivatkozott rendelkezéseinek mutatója is megtalálható.
Ứng dụng phương pháp nghiền ướt để giảm kích thước tiểu phân nhằm tăng độ hòa tan cilnidipin
Authors: Nam Đào Văn , Quang Quản Duy , Hoài Trần Thị , Ánh Võ Quốc
Published: October 2024

Giảm kích thước tiểu phân (KTTP) là một biện pháp hiệu quả để cải thiện độ hòa tan của dược chất ít tan, qua đó có thể tăng sinh khả dụng của thuốc. Nghiên cứu này áp dụng kỹ thuật nghiền ướt để giảm KTTP cilnidipin, đây là thuốc hạ huyết áp thuộc nhóm chẹn kênh calcium và thuộc nhóm 2 theo phân loại BCS (thấm tốt, tan kém). Các yếu tố thời gian nghiền, tốc độ nghiền và tỉ lệ dược chất có ảnh hưởng lớn đến hiệu quả của quá trình nghiền. Tuy nhiên, chỉ có thời gian nghiền có ảnh hưởng đáng kể đến độ rộng phân bố KTTP. Qua quá trình nghiền, KTTP của cilnidipin có thể được làm nhỏ đến 0,3 µm. Phân tích DSC cho thấy có sự dịch chuyển píc nóng chảy của cinidipin về phía nhiệt độ thấp hơn, đặc biệt ở các mẫu có kích thước nanomet. Tuy nhiên, phổ XRD không có dấu hiệu dược chất đã thay đổi dạng thù hình. Độ hòa tan của cilnidipin được tăng lên đáng kể sau nghiền, đạt ~ 100% (điều kiện sink) và 60-100 % (điều kiện non-sink) tại 5 phút. Trong khi đó, mẫu nguyên liệu gần như chưa hòa tan sau 5 phút ở cả 2 điều kiện. Quy trình nghiền ướt đã xây dựng có thể được phát triển thêm nữa để giảm KTTP của cilnidipin, ứng dụng trong bào chế các dạng thuốc uống.
fabrication of wood alternative material from cassava rhizome and cassava peel pulp
Authors: Minaboon Nichapha , Khamput Prachoom , Watcharasawe Kongpop , Malai Attapole
Published: October 2024

The increasing demand for wood alternative material in construction and furniture. Corresponds to global efforts to reduce pressure on forests, necessitating the exploration of alternative materials to wood. The agricultural industry can not only supply raw materials from non-wood plants but also waste material and byproducts. The aim of this research was to explore and manufacture wood alternatives using cassava rhizomes and cassava peels, thereby valorizing agricultural waste. The research methodology involved blending milled rhizomes and cassava peels with urea-formaldehyde resin followed by a hot-pressing process to form the final product. The samples size for this study was 450x450x10 mm were made using 6-10 percent urea-formaldehyde resin by weight of the composite materials aiming to achieve a sheet density about 600 kg/cu-m. Three distinct ratios of Cassava rhizome to cassava peel pulp were examined as potential wood substitutes. All test results of sample were compared with the industrial standards outlined in Thai Industrial Standard. The study found that wood substitutes created from Cassava rhizome and Cassava peel pulp combined with urea-formaldehyde resin could meet the set standards. Cassava rhizome improves important properties like density, moisture content, thickness swelling, formaldehyde content, modulus of rupture, and modulus of elasticity according to TIS 876-2547 standards. However, adding peel pulp tends to reduce these qualities. There is no significant change in the density of the wood-alternative materials. However, a 10% urea formaldehyde content improves the mechanical properties. The study found that wood substitutes created from Cassava rhizome and Cassava peel pulp combined with urea-formaldehyde resin could meet the set standards. Moreover, the production cost of these wood substitute materials was lower than the prevailing market prices. This study disseminates knowledge from research that utilizes cassava rhizomes and peels to create sheet like wood substitute materials. Using modern methods and appropriate technologies, cassava rhizomes and peels can be transformed into a diverse range of wood substitute products, and capable of effectively competing with wood and other materials in the future.
Perancangan Sistem Informasi Perpustakaan Berbasis Web Pada UPT SMP Negeri 34 Gresik
Authors: Muhammad Al Amin  , Farhanna Mar’i
Published: October 2024

Technical advances in computer applications have led to the creation of these library information systems, which are anticipated to support and facilitate the human workforce. It is anticipated that this technology will help with daily tasks in an effective and efficient manner as well. The subject of this study is the library system. There are obstacles in UPT Library SMP 34 GRESIK, and one of them is that the library still uses its service manual procedures, indicating the need innovation and change in the form of a cohesive system to accompany and prepare children in the classroom The library service information system provided by this network-based library information system should make it easier for students to find information and check out books, as well as for librarians to manage information about books and student loans. The waterfall approach was used by the author. To create this internet-based library resource system. The process of implementing this library information system begins with soft requirement analysis, prioritizing the process of borrowing books. Waterfall design techniques are used throughout the design stage, which involves creating a database with MySQL and building a user interface. Relationships are built in the database architecture using Entity Relationship Diagrams and Logic Relationship database (Database) structures.
Representasi Perempuan Dalam Sinetron Suara Hati Istri
Authors: Aqila Mindani
Published: October 2024

This research aims to determine the representation of women in the Suara Hati Istri series using semiotic analysis from a gender perspective. This research was conducted using a narrative descriptive qualitative research method. The data in this research is the episode of “Beratnya Punya Suami Yang Ingin Istrinya Cantik Seperti Model” using data collection techniques browsing by the vidio.com site, documentation, and literature studies. This research uses Charles Sanders Peirce's semiotic analysis. The results of the research show that in the series of Suara Hati Istri: Beratnya Punya Suami Yang Ingin Istrinya Cantik Seperti Model women are represented based on the role of a wife, namely macak, masak, and manak in the patriarchal system of Javanese society. The character Nana is represented as a housewife who has complete responsibility for taking care of all the needs of the house, husband, and children. Her husband, Fendy, also demands that Nana continue to look beautiful. Apart from that, Fendy also considers that looking after and caring for children is a wife's responsibility so she is not allowed to have a baby sitter.
Analisis Sentimen Web Novel Menggunakan Metode Latent Dirichlet Allocation (LDA)
Authors: Dewi Rosmala  , Ryan Cahyadi N
Published: October 2024

Web novels have gained popularity in recent years as a form of literature that is published and consumed online via specialized platforms. User generated comments and reviews play an important role in the web novel platform, providing valuable insight into reader sentiment and feedback. Manually analyzing sentiment from a large number ofcomments would be very time consuming, an efficient automated approach was required. This study uses the Latent Dirichlet Allocation (LDA) method to identify sentiment patterns (positive, negative, neutral) in user comments on web novels and analyze their distribution as a whole. LDA, originally designed for topic modeling, has proven effective in sentiment analysis, helping to group comments into relevant topics and uncover general sentiments related to each topic. This study aims to use the LDA method to identify sentiment patterns (positive, negative, or neutral) in user comments on web novels and analyze the distribution of sentiment as a whole. The results show the effectiveness of LDA in sentiment analysis, achieving quite good results, with 72% accuracy, 80% precision, 72% recall, and 65% F1 score.
Penerapan ERP untuk Sistem Informasi Kepegawaian pada BKPSDM Kota Solok
Authors: Denny Rinaldi  , Jhon Veri
Published: October 2024

The increasingly rapid development of information technology currently encourages organizations to implement connected information systems with one database, so that it becomes easier for several organizational devices to share data, and it is also easier to communicate. The obstacles faced when still using paper as a document medium are spending a lot of time completing documents, not being efficient in completing reports that have time limits, so that the information needed is slow and what is obtained is less than optimal. This research method is qualitative by explaining in detail about the Personnel System in personnel services in the implementation of Enterprise Resource Planning (ERP). Then the data analysis techniques used in this research are qualitative descriptive analysis, observation, interviews and documentation. In implementing this ERP, it was concluded that the personnel service application could improve human resource management thereby improving services from various areas of the organization
Perancangan Sistem Penerimaan Siswa Baru SMK Swasta Yapim Biru-Biru Berbasis Web
Authors: Sri Putri Balqis  , Tegar Ardiansyah  , Ahmad Taufik Al Afkari Siahaan
Published: October 2024

The aim of this research is to design a web-based new student admission system at Yapim Biru - Biru Deli Serdang Private Vocational School which can make registration easier so that you don't have to queue at school anymore. With this new system, the service system can be simplified and can print the data of accepted students and registered students, so that the data of accepted students is arranged more neatly and is easier to access. The rapid development of information technology among all fields, especially in the field of school education, uses information technology to facilitate school performance, especially in accepting new students. The system design methodology used in preparing the final report of this practical work uses a descriptive method, namely by conducting research based on the data that has been collected. One of the developments in information technology applications is information systems. Information systems function as collecting, processing, storing, analyzing and disseminating information designed for specific purposes.
Perancangan Ui / Ux Aplikasi Penjualan Alat Bulu Tangkis Berbasis Mobile Menggunakan Metode Activity Centered Design (ACD)
Authors: Muhamad Dipa Maulana  , Meriska Defriani  , Muhamad Rafi Muttaqin
Published: October 2024

Perancangan UI/UX sebelum memulai pengembangan aplikasi adalah langkah strategis yang krusial. UI/UX yang baik tidak hanya meningkatkan kepuasan dan retensi pengguna tetapi juga mengurangi biaya dan waktu pengembangan, serta membantu membangun brand yang kuat. Pada pembuatan aplikasi mobile perlu dibuatkannya UI/UX, UI/UX merupakan salah satu hal utama dalam pembuatan sebuah aplikasi yang menjadi faktor penentu dalam menaikan traffic penjualan. Activity Centered Design (ACD) merupakan pendekatan yang berpusat pada aktivitas yang menganggap aktivitas sebagai tujuan tingkat tertinggi dan memandang motivasi untuk berpartisipasi dalam suatu aktivitas dan hasil yang diinginkan dari berpartisipasi dalam aktivitas itu adalah sama. Proses ACD memiliki empat tahapan yaitu requirement, desain, implementasi dan evaluasi. Salah satu metode yang digunakan dalam perancangan antarmuka yaitu metode Activity Centered Design, metode ini dikenal sebagai suatu metode yang fokus pada aktivitas pengguna produk Setelah dilakukan hasil pengujian SUS dari 15 responden maka diperoleh dari nilai rata-rata atau SUS Score sebanyak 84,16. Penelitian ini menghasilkan rancangan interface prototype aplikasi mobile penjualan alat bulutangkis GOR Siti Sofiah dengan menggunakan metode Activity Centered Design dengam fitur yang telah disesuaikan dengan kebutuhan pengguna dan telah dilakukan pengujian menggunakan metode System Usability Scale (SUS). Berdasarkan pengujian usability dengan perhitungan System Usability Scale (SUS) diperoleh nilai rata-rata SUS sebesar 84,16 Berdasarkan hasil perhitungan tersebut menunjukkan bahwa rancangan prototype yang dibuat sudah memenuhi kebutuhan pengguna.
Rancang Bangun Monitoring Alat Pemantau Curah Hujan Berbasis Mikrokontroller dengan Data Real-Time Via Telegram
Authors: Sujon Sujon  , Siti Sufaidah  , Lailatul Nur Hidayah
Published: October 2024

Rainfall monitoring is an important aspect of meteorology and water resources management. The development of a microcontroller-based rainfall monitoring device that can transmit data in real-time through the Telegram application offers an effective and efficient solution to overcome the constraints of manual monitoring. This research aims to design and build a rainfall monitoring system that uses a microcontroller as the main controller and the Twilio platform as a data transmission service via Telegram. This tool is designed to measure rainfall intensity using a hall effect sensor, which is then processed by a microcontroller. The rainfall data obtained will be sent to the user's device via Telegram message. This system is expected to provide accurate and timely information to users, so that it can be used in various applications such as agriculture, flood monitoring, and water resource management. The test results show that this rainfall monitoring tool is able to send data quickly, this tool is expected to increase efficiency and effectiveness in rainfall monitoring and make a significant contribution in the field of meteorology and environmental management.
Membangun Model Prediksi Churn Pelanggan yang Akurat
Authors: Andy Hermawan  , Nila Rusiardi Jayanti  , Zia Tabaruk  , Faizal Lutfi Yoga Triadi  , Aji Saputra  , M.Rahmat Hidayat Syachrudin
Published: October 2024

Customer churn prediction models have become an important tool in the telecommunications industry to reduce churn rates and improve customer retention. This research focuses on building an accurate customer churn prediction model using machine learning algorithms for TELCO Company. By applying diverse feature engineering techniques and prediction models such as RandomForestClassifier, DecisionTreeClassifier, and XGBoost, this study showcases a significant improvement in prediction accuracy compared to previously implemented rule-based methods. The findings of this research allow TELCO Company to identify high-risk customers more effectively and implement targeted retention strategies. Results show that the resulting model can identify customers at risk of churn more effectively, enabling more targeted retention actions..
Peningkatan Literasi Teknologi IoT untuk Mendukung Implementasi Smart City di Masyarakat Perkotaan
Authors: Apri Affandi
Published: October 2024

The implementation of Internet of Things (IoT) technology in the smart city concept has become an important innovation that plays a major role in improving the quality of life of urban communities. IoT enables the integration of various interconnected devices and systems to optimize the management of city resources such as energy, transportation and security. This research aims to encourage the influence of IoT technology on the implementation of smart cities in several cities in Indonesia. Using qualitative and quantitative methods, this research collects data through interviews with city stakeholders as well as secondary data analysis from related reports and publications. The research results show that the application of IoT in smart cities has a significant impact on increasing operational efficiency, better environmental management, and improving public services. However, this research also found a number of challenges, such as limited infrastructure, data security problems, and low digital literacy among the public. In conclusion, although IoT has great potential in accelerating the implementation of smart cities, policies are needed that support and increase society's capacity to reach the full potential of this technology.
Inimputabilidade do Ezquisofrênico
Authors: Cesar Oliveira Fonseca Roberto , Paranhos Menezes Matheus , Martins Santos Mateus Henrique , Oliveira Santos Gonçalves Erica
Published: October 2024

A inimputabilidade é um conceito jurídico que isenta a responsabilidade criminal de indivíduos incapazes de compreender o caráter ilícito de seus atos devido a condições específicas, como menoridade, doenças mentais, ou outros distúrbios, como a esquizofrenia. No caso da esquizofrenia, que afeta a percepção da realidade e o pensamento, o reconhecimento da inimputabilidade é essencial para assegurar que essas pessoas recebam tratamento médico adequado, em vez de serem punidas criminalmente. A jurisprudência brasileira adota o sistema biopsicológico, avaliando tanto a condição mental quanto a capacidade do agente no momento do delito. Para menores de 18 anos, aplica-se o sistema biológico, presumindo a inimputabilidade absoluta. O tratamento da esquizofrenia envolve medicação e psicoterapia, e seu diagnóstico depende de avaliações psiquiátricas rigorosas. A jurisprudência exige que a incapacidade seja comprovada por laudos médicos no momento da ação. O objetivo não é apenas proteger o indivíduo, mas também reduzir o estigma e garantir a segurança pública ao proporcionar tratamento adequado.
O PERFIL DO CRIMINOSO NOS CRIMES CIBERNÉTICOS: COMPORTAMENTOS, MOTIVAÇÕES E TÁTICAS
Authors: Gomes Domingos Thaís , Jacob Alexandre
Published: October 2024

O presente artigo tem como objetivo realizar um estudo sobre os comportamentos, motivações e táticas dos cibercriminoso. A metodologia utilizada baseou-se em pesquisas teóricas e documentais, com consultas à doutrina, jurisprudências, teses, dissertações, além de fontes confiáveis, tanto governamentais quanto não governamentais. O estudo busca responder ao seguinte questionamento como a identificação dos tipos de perfil dos criminosos cibernéticos pode contribuir para o combate, prevenção e criação/aperfeiçoamento da legislação brasileira atual? O presente artigo tem como objetivos estudar sobre a parte histórica da internet e suas subdivisões, além de analisar o modus operandi dos criminosos digitais, assim como compreender a legislação brasileira sobre o tema e entender o perfil dos cibercriminoso. Os crimes cibernéticos estão se tornando uma ameaça crescente no ambiente digital, afetando empresas, governos e indivíduos em escala global. Com o avanço da tecnologia, os métodos utilizados pelos infratores virtuais se tornam mais sofisticados e difíceis de combater.
SEGURANÇA DA INFORMAÇÃO PARA EMPRESAS NO BRASIL
Authors: Ribeiro Machado Kalleb , Oliveira Cata Preta Kaio , Mendel Pungirum João César
Published: October 2024

Este artigo discute a importância da segurança da informação para as empresas no Brasil. À medida que os processos se tornam cada vez mais digitais e as ameaças cibernéticas aumentam, a proteção de dados tornou-se essencial para a sobrevivência e credibilidade das organizações. O estudo examina os desafios enfrentados pelas empresas brasileiras em relação à segurança da informação, incluindo ameaças, vulnerabilidades e o impacto potencial de ataques cibernéticos. Também analisa as principais estratégias e práticas que as organizações utilizam para gerenciar esses riscos, como políticas de segurança, tecnologias de proteção, conscientização dos funcionários e conformidade com regulamentações como a LGPD (Lei Geral de Proteção de Dados). Por meio de uma revisão bibliográfica, o artigo oferece insights e recomendações para ajudar as empresas brasileiras a fortalecer sua segurança da informação, proteger seus dados e garantir a continuidade dos negócios em um cenário digital cada vez mais complexo.
Palavras-chave: Informação, segurança, dados
RELAÇÃO DA FORÇA MUSCULAR PERIFÉRICA COM O DESMAME DA VENTILAÇÃO MECÂNICA
Authors: Rillary Duarte Filho Débora , Schultz Malagute Gabriella , Ferreira Rihs Luciana , Corrêa Cavalcanti Priscila
Published: October 2024

A ventilação mecânica invasiva representa um método de suporte respiratório que busca manter o paciente até que ele esteja apto a respirar autonomamente, sendo que processo de desmame consiste na gradativa retirada do suporte ventilatório. O objetivo do presente trabalho foi discutir a relação da força muscular periférica com o desmame da ventilação mecânica, destacando a importância do fisioterapeuta nesse contexto. A força muscular periférica está relacionada ao desmame da ventilação mecânica em pacientes em UTI. A fraqueza muscular adquirida durante a hospitalização intensiva pode dificultar o processo de desmame, prolongando a necessidade de suporte ventilatório e isso ocorre porque a fraqueza muscular compromete a capacidade do paciente de realizar os esforços respiratórios necessários para respirar espontaneamente, contribuindo para complicações como a incapacidade de tossir eficazmente e manter uma ventilação adequada. O treinamento da musculatura inspiratória aumenta a pressão máxima inspiratória, melhorando as taxas de sucesso no desmame e reduzindo o tempo necessário para retirada completa da ventilação. Usado de forma segura e supervisionada, o treinamento oferece benefícios como a redução do tempo de internação. Avaliações clínicas podem identificar pacientes com maior potencial de melhoria, especialmente aqueles com falhas anteriores no desmame. Outras estratégias, como eletroestimulação funcional abdominal e redução precoce do suporte pressórico, também mostraram resultados positivos, mas não há consenso sobre os métodos mais eficazes. A reabilitação muscular, incluindo a fisioterapia e a mobilização precoce, podem contribuir para recuperação da força muscular periférica, melhorando as chances de sucesso no desmame da ventilação mecânica e recuperação geral do paciente.
Metodología de ahorro de consumo de combustible en embarcaciones mediante variables de programación dinámica
Authors: Rizzo David , De la Rosa Yusnier , Chafuelán Ariel
Published: October 2024

El enrutamiento meteorológico del barco se define como un seguimiento óptimo de la ruta del barco con una velocidad y potencia del motor óptimas para un viaje por mar en función de los pronósticos meteorológicos en ruta y las características del barco. En este trabajo de titulación se utilizó el método de programación dinámica para optimizar la ruta, el cual se basa en el principio de optimalidad de Bellman, y compararlo con el método MEPC de la OMI, con el objetivo directo de minimizar el consumo de combustible del viaje en una embarcación, mientras que los movimientos del barco y el tiempo de llegada se gestionan a través de restricciones: por lo tanto, se utilizó una metodología de optimización de un solo objetivo para minimizar una función de costo (el consumo total de combustible). Como resultado se obtuvo que el método de programación dinámica permite un ahorro entre 4,5 y 6 % de combustible en condiciones meteorológicas previsibles con configuraciones de velocidad
Diseño y construcción de una planta piloto para la obtención de biocombustible a partir del cultivo microalgas como una fuente de energía renovable
Authors: Azua-Alvia Jouber Antonio , Roldan-Hernández Jhonsy Joel
Published: October 2024

Ante los problemas que representa el calentamiento global debido a los gases de efecto invernadero y un futuro muy cercano en el que las principales reservas de petróleo del mundo se agotan, el uso de energías renovables y respetuosas con el medio ambiente se hace imprescindible. Gracias a los avances tecnológicos que tenemos en la actualidad es posible explorar nuevos desafíos en cuanto a la producción de energía, por lo que se ha considerado realizar la investigación sobre el uso de microalgas como biomasa para la producción de biopetróleo. Estas microalgas se desarrollan con el consumo de dióxido de carbono y determinados componentes de las aguas residuales ayudando a la mitigación de la contaminación ambiental. Durante el desarrollo del estudio, para la obtención de la materia prima se cultivaron las microalgas en condiciones autótrofas. El concentrado húmedo que se obtuvo por filtración del medio acuoso de las microalgas, se sometió a un proceso de licuefacción hidrotérmica a presión de 250 bar y 350 °C para la obtención de biocarbón, biogás, compuestos orgánicos disueltos en agua y biopetróleo. Se evidenció que el aumento de presión tiene un impacto en la calidad de los productos.