bluuebunny/crossref_metadata_2025 huggingface dataset:
AI and the Sustainability of the Signaling and Human Capital Roles of Higher Education
Authors: Alexander W. Robert J. , Belloni Raffaella
Published: September 2024

Over the last several decades there has been an arms race to acquire credentials as higher education has shifted from an elitist system to mass education. From an individual perspective, given the higher education system and labor market conditions, it is rational to pursue advanced qualifications. However, whether the education system delivers improvements in human capital or is principally a signaling mechanism is questionable. Estimates of the proportion of labor market rewards due to signaling range as high as 80%, suggesting that education is not only expensive but inefficient. In an increasingly transactional environment in which education providers are highly motivated by financial considerations, this situation is only likely to be exacerbated by the rapid developments in AI. The use of AI has the potential to make learning more effective but, given that many students see credential acquisition as transactional, it may reduce both human capital and the value of the signaling effect. If the credibility of the credentials offered is further damaged, the sustainability of the higher education sector in its present form and scale may well be unsustainable. We examine the evidence on credential inflation, returns to education and mismatch of graduates to jobs before analyzing how AI is likely to affect these trends. We then suggest possible responses of prospective students, education providers and employers to the growing adoption of AI in both education and the workplace. We conclude that the current offerings of generalist degrees, as opposed to vocational qualifications, are not sustainable and that to survive, even in a downsized form, the sector must respond to this disruptive technology by changing both the nature of its offerings and its methods of ensuring that the credentials they offer reflect genuine student learning.
Genetic Polymorphisms of Il-18 and Their Association with Infectious Diseases – an Update
Authors: Arumugam Durga , Semalaiyappan Janani , Mookiah Balamurugan , Kuttiatt Vijesh Sreedhar
Published: September 2024

Cytokines play a substantial role in the pathophysiology of infectious diseases. Consequently, genetic polymorphisms in cytokine genes can have profound effect on the susceptibility to or protection from infections and also influence the clinical manifestations, disease severity as well as outcome. The objective of this brief narrative review is to provide an update on the recent research findings on the role of genetic polymorphisms of IL-18, a recently discovered cytokine on certain infectious diseases of public health relevance. The current review suggests there is a significant impact of IL-18 polymorphisms on different infectious diseases. The presence of G and T alleles at position -656 is suggested to have a probable protective effect against VL. The −137G/−607C (GC) and −137C/−607C (CC) haplotypes in the promoter region are associated with increased susceptibility to severe malarial anemia. SNPs rs544354 and rs574429 (GC) are linked to a higher risk of P. falciparum infection and increased parasitemia. The -137 C/C genotype and -137 G allele (with G/G genotype) are associated with faster progression to AIDS. In contrast, the IL-18 genotype does not seem to affect overall HIV susceptibility but influences disease progression. The G and GG genotypes at position -137 and allele A at position -607 are likely associated with protection against HBV infection. Conversely, the C allele at position -137 is linked to increased susceptibility to HBV infections. The GG genotype of IL-18 -137 G > C variant is associated with increased susceptibility to pulmonary tuberculosis (PTB). The AC genotype of IL-18 -607A>C has been linked to PTB susceptibility, particularly in patients with co-morbid diabetes mellitus. SNPs −137G/C, 113T/G, and +127C/T are associated with susceptibility to H. pylori infection, indicating that these genetic variants may influence the risk of H. pylori-related diseases. There are conflicting results in studies conducted in different populations (e.g., genetic polymorphism, studies conducted in India and China against HBV infection) highlighting the need for further research with larger sample sizes to resolve discrepancies. Due to the variability in findings, extensive studies in diverse populations are needed to better understand the impact of IL-18 polymorphisms.
Solving the Transport Infrastructure Investment Projects Selection and Scheduling as a Multiple Knapsack Problem Using Genetic Algorithms
Authors: Ječmen Karel , Mocková Denisa , Teichmann Dušan
Published: September 2024

The development of transport infrastructure is a key element of economic growth, social connectivity, and sustainable development. Many countries have historically underinvested in transport infrastructure, necessitating more efficient strategic planning in transport infrastructure investment projects implementation. This article addresses the selecting and scheduling of transport infrastructure projects, specifically within the context of drawing available resources from pre-allocated funds within a multi-annual budget investment program. The current decision-making process is largely based on expert judgment, lacking quantitative decision support methods. The authors propose a genetic algorithm as a decision-support tool that frames the problem as an NP-hard 0-1 multiple knapsack problem. The proposed genetic algorithm is unique for its matrix-encoded chromosomes, specially designed genetic operators, and a customized repair operator, which is implemented to address the large number of invalid chromosomes generated during the GA computation. The goal is to maximize the impact of allocated funds over a seven-year programming period, while respecting constraints specified by the funding authorities. In computational experiments, proposed GA is compared to an exact solution and is proved to be efficient in terms of quality of obtained solutions and computational time, highlighting its potential for enhancing strategic decision-making in transport infrastructure development.
An Ensemble of Machine Learning Models for the Classification and Selection of Categorical Variables in Traffic Inspection Work of Importance for the Execution of Events
Authors: Đukić Aleksandar , Banjanin Milorad K. , Stojčić Mirko , Đurić Tihomir , Đekić Radenka
Published: September 2024

Traffic Inspection (TI) work in this article is positioned as a specific module of road traffic with its primary function oriented towards monitoring and controlling safe traffic and the execution of significant events within a particular geographic area. Exploratory research on the significance of event execution in simple, complicated and complex traffic flow and process situations is related to the activities of monitoring and controlling functional states and performance of categorical variables, which include objects and locations of road infrastructure, communication infrastructure and networks of traffic inspection resources. It is emphasized that the words “work” and “traffic” have the semantic status as synonyms (in one world language), which is explained in the design of the Agent-based model of the complexity of content and contextual structure of TI work at the singular and plural level with 12 points of interest (POI) in the thematic research. An Event Execution Log (EEL) was created for on-site data collection with eight variables, seven of which are independent (event type, activities, objects, locations, host, duration-period and periodicity of the event) and one dependent (significance of the event) variable. The structured data set includes 10,994 input-output vectors in 970 categories collected in the EEL created by 32 human agents (traffic inspectors) over a 30-day period. An algorithmic presentation of the methodological research procedure for preprocessing and final data processing in the ensemble of machine learning models for classification and selection of TI tasks is given. Data cleaning was performed on the available dataset to increase data consistency for further processing. Vector elimination was carried out based on the Location variable, such that the total number of vectors equals the number of unique categories of this variable, which is 636. The main result of this research is the Classification modeling of the significance of events in TI work based on machine learning techniques and the Stacking ensemble. The created machine learning models for event significance classification modeling have high accuracy values. To evaluate the performance metrics of the Stacking ensemble of models, the confusion matrix, Precision, Recall, ND F1-score are used.
Factors Associated with the Occurrence and Complications of Arterial Hypertension at the Sangmélima Referral Hospital – Cameroon
Authors: Biwoele Tarcisse , Ndoumba Annick , Aguinaga-Ontoso Ines , Ngo'o Servais , Ndongo Séraphine Clarisse Meyeñe , Ambomo Sylvie Miryam , Guillen-Grima Francisco , Onambele Luc
Published: September 2024

Summary: Hypertension is a public health problem with serious social, economic, and health consequences. The World Health Organisation (WHO) estimates that 1 in 3 adults worldwide suffers from hypertension. In Cameroon, the prevalence of hypertension is estimated at 35%, with nearly 17,000 deaths recorded each year. This study aimed to determine the factors associated with the occurrence and complications of hypertension at the Sangmélima Referral Hospital (HRS). A total of 528 patients treated in the cardiology department of the HRS were identified between January and December 2023. The data were analyzed using SPSS 28 software. Binary logistic regression determined the odds ratios and 95% confidence intervals associated with each variable. Differences were statistically significant for a p-value < 0.05. At the HRS, the annual incidence of hypertension was 16.13%. Hypertension was present in 78.8% of patients. The factors associated with the occurrence and complications of hypertension were age (OR=1.028; p=0.003 ), level of education (OR=15.49; p=0.023), marital status (OR=3.859; p=0.04), hypercholesterolemia (OR=2.856; p=0.01), monthly income (OR=0.882; p=0.026), number of dependents (OR=1.231; p=0.025), food security (OR=16.666; p<0.001), tobacco consumption (OR=8.592; p=0.041), fruit and vegetable consumption (OR=0.027; p=0.031), salt/sugar consumption (OR=8.129; p<0.001), place of residence (OR=4.794; p=0.005), access to essential technologies (OR=8.851; p=0.002), and use of traditional care (OR=3.137; np=0.032). HTA at the HRS is associated with several factors. In order to limit the impact of hypertension, it is crucial to emphasize improving socioeconomic and health conditions.
Networks Based on Graphs of Transient Intensities and Product Theorems in Their Modelling
Authors: Tsitsiashvili Gurami Shalvovich
Published: September 2024

The paper considers two models of queuing with a varying structure based on the introduction of additional transient intensities into known models or their combinations, which create stationary distributions convenient for calculation. In the first model, it is a probabilistic mixture of known stationary distributions with given weights. In the second model, this uniform distribution is repeatedly used in physical statistics. Both models are based on the selection of states, between which additional transient intensities are introduced. The algorithms used in the paper for introducing new transient intensities are closely related to the concept of flow in a deterministic transport network. The introduced controls are selected so that the marginal distribution of the combined system is a mixture of the marginal distributions of the combined systems with different weights determined by the introduced transient intensities. As a result, the process of functioning of the combined system is obtained by switching processes corresponding to different combined systems at certain points in time.
Development of a New Treatment for Interstitial Lung Disease and COPD with Platinum-Palladium - In Relation to Improvement Examples and Research Examples
Authors: Kawakami Satoshi , Shirakawa Taro , Wajima Shoichi , Segawa Yusuke , Fukuzawa Yoshitaka , Sakabe Kou
Published: September 2024

Interstitial pneumonia is a general term for diseases in which inflammation occurs mainly in the interstitium of the lung. It is also pointed out that interstitial pneumonia reduces alveolar function and makes it difficult to take in oxygen through inspiration, causing symptoms such as dyspnea and coughing, which may eventually lead to respiratory failure. At present, there is no effective treatment and only conservative treatment exists. This time, we report that the therapeutic effect was confirmed in patients with interstitial pneumonia who took platinum-palladium. In this case, improvement tendencies were observed in patients with Idiopathic pulmonary fibrosis (IPF), but improvement tendencies were also observed in many other lung diseases. In order to explore the mechanism, AMPK was measured at the in vitro level, and blood KL-6 and hydrogen peroxide levels in the patient were measured at the in vivo level. AMPK values were significantly elevated by more than 800%, KL-6 and hydrogen peroxide levels were also significantly decreased by drinking platinum-palladium. Platinum-palladium exhibits a strong antioxidant effect and is the only substance in the world that can approach all four types of active oxygen. In addition, when it was actually administered to patients, there were cases of dramatic improvement, and it was confirmed that KL-6, a parameter of lung function, decreased in 16 out of 32 patients As the number of cases is expected to increase in the future, the substance is expected to be effective as a drug, although it is currently classified as a soft drink.
Enhanced Vehicle Logo Detection Method Using Mamba Structure for Electric Vehicle Application
Authors: Yang Shuo , Liu Yisu , Liu Ziyue , Xu Changhua , Du Xueting
Published: September 2024

Vehicle logo detection plays a crucial role in various computer vision applications, such as vehicle classification and detection. In this research, we propose an improved vehicle logo detection method leveraging the MAMBA structure. The MAMBA structure integrates multiple attention mechanisms and bidirectional feature aggregation to enhance the discriminative power of the detection model. Specifically, we introduce the Multi-Head Attention for Multi-Scale Feature Fusion (MHAMFF) module to capture multi-scale contextual information effectively. Moreover, we incorporate the Bidirectional Aggregation Mechanism (BAM) to facilitate information exchange between different layers of the detection network. Experimental results on a benchmark dataset (VLD-45 dataset) demonstrate that our proposed method outperforms baseline models in terms of both detection accuracy and efficiency. Furthermore, extensive ablation studies validate the effectiveness of each component in the MAMBA structure. Overall, the proposed MAMBA-based vehicle logo detection approach shows promising potential for real-world applications in intelligent transportation systems.
Innovative Surface Plasmon Resonance Aptasensor for Detecting Cocaine in Human Urine
Authors: KEKLIK ŞAH Gül , ISBIR TURAN Aybüke A.
Published: September 2024

This study describes the development of an optical-based surface plasmon resonance (SPR) aptasensor for the detection of cocaine. The aptasensor was prepared by first attaching gold nanoparticles to a clean SPR chip surface, followed by the addition of an aptamer to create a modified surface. This surface was characterized using Contact Angle and Atomic Force Microscopy, revealing surface roughness values of 0.28 nm and 28.12 nm for the blank and modified surfaces, respectively. The detection of cocaine was carried out in the concentration range of 1 ng/mL to 1000 ng/mL, with a detection time of approximately 8 minutes and a cocaine limit of detection (LOD) of 0.43 ng/mL. Repeatability studies were conducted, and the stability of the signal response was examined at a concentration of 200 ng/mL. Adsorption isotherm models, including Scatchard, Langmuir, and Freundlich, were calculated to assess the surface homogeneity of the SPR aptasensor chip, with the results indicating compatibility with the Langmuir isotherm model.
Tracing the EoL-Tyre Management Chain in Togo with Focus of Implementing a Tyre Recycling Plant
Authors: Narra Mona-Maria , Gbiete Djangbadjoa , Agboka Komi , Narra Satyanarayana , Nelles Michael
Published: September 2024

To evaluate the used and End-of-Life tyre management chains, both direct observation and interviews with approximately 200 used-tyre dealers were conducted. The study revealed that while the used tyre business is well-organized, End-of-Life tyre treatment is nearly non-existent, often involving dumping, open burning for metal recovery, or use in meat processing, causing environmental and health risks. To address these challenges, an 8 t/hr capacity tyre recycling plant is planned, based on estimated tyre availability and development opportunities for sustainable recycling in Togo.
Inflammatory bowel diseases in children: diagnostic algorithms and modern therapy strategies
Authors:   Research Clinical Institute of Childhood, Ministry of Health of the Moscow Region, Moscow, Russian Federation, Khavkin A.I. ,   N.I.Pirogov Russian National Research Medical University, Moscow, Russian Federation,   Belgorod State University, Belgorod, Russian Federation, Nalyotov A.V. ,   M.Gorky Donetsk State Medical University, Donetsk, Russian Federation, Fedulova E.N. ,   Privolzhsky Research Medical University, Nizhniy Novgorod, Russian Federation, Marchenko N.A. ,   M.Gorky Donetsk State Medical University, Donetsk, Russian Federation
Published: September 2024

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease including Crohn's disease and ulcerative colitis. In about 10% of cases, the disease manifests itself in childhood. The clinical picture of IBD with rectal bleeding or perianal inflammation requires immediate endoscopic examination. In the absence of red-flag symptoms, a combination of patient history, blood and stool biomarkers may help differentiate IBD from other causes of abdominal pain or diarrhea. Treatment of IBD in children is carried out taking into account predictors of adverse outcome, which justifies the preliminary use of anti-tumor necrosis factor therapy for patients with a high risk of developing complications of the disease. In the treatment of patients with IBD, biochemical or endoscopic remission, rather than clinical remission, is the therapeutic goal because intestinal inflammation often persists despite resolution of abdominal symptoms. In pediatric practice, IBD is associated with additional problems, such as impaired growth and physical development, delayed puberty and mental maturation in adolescents. Even after remission has been achieved, many patients with IBD continue to experience nonspecific symptoms like abdominal pain and fatigue. Transfer to adult care is a well-recognized risk for disease relapse, which highlights patient vulnerability and the need for a transition program that is continued by the adult-oriented IBD team. The general pediatrician is an invaluable link in integrating these challenges in the clinical care of patients with IBD and optimizing their outcomes. This state-of-the-art review aims to provide general pediatricians with an update on pediatric IBD to facilitate interactions with pediatric gastrointestinal specialists. Key words: inflammatory bowel diseases, Crohn's disease, ulcerative colitis, children, diagnosis, treatment
Practical aspects of the choice of vitamin and mineral complexes in children from 1 to 3 years
Authors:   Privolzhsky Research Medical University, Nizhny Novgorod, Russian Federation, Skochilova T.V. , Fedulova E.N. ,   Privolzhsky Research Medical University, Nizhny Novgorod, Russian Federation, Khavkin A.I. ,   Research Clinical Institute of Childhood of the Ministry of Health of the Moscow Region, Moscow, Russian Federation,   Belgorod National Research University, Belgorod, Russian Federation, Zastelo E.S. ,   Privolzhsky Research Medical University, Nizhny Novgorod, Russian Federation
Published: September 2024

In the period of early childhood, adequate provision of the body with energy, functional components of food, vitamins and minerals is required. The emerging taste habits of a child at this age may affect the further provision of micronutrients. This period often coincides with the stage of adaptation to preschool institutions, and the presence of hypovitaminosis can adversely affect it. It is necessary to pay timely attention to the medical and nutritional aspects of preparing a child to attend organized children's groups. Prevention of micronutrient insufficiency at an early age can be carried out in various ways, including through the use of vitamin and mineral complexes (VMC). At the age of 1 to 3 years, there are certain features of the choice and appointment of VMC, the article presents various IUD drugs recommended for prevention and treatment. New forms of vitamins and minerals are of interest not only among the medical community, but also among parents of children preparing for the adaptation period. Key words: vitamins, minerals, trace elements, prevention, deficiency, children, early age, adaptation
Role of specialized food products in dietary treatment for obesity
Authors:   Federal Research Centre of Nutrition, Biotechnology and Food Safety, Moscow, Russian Federation, Gapparova K.M. , Chekhonina Yu.G. ,   Federal Research Centre of Nutrition, Biotechnology and Food Safety, Moscow, Russian Federation,   N.I.Pirogov Russian National Research Medical University, Moscow, Russian Federation
Published: September 2024

Enhancing dietary patterns in the population of Russia is an extremely urgent task due to the need to improve the quality of life and reduce the risk of alimentary-dependent diseases, which are currently the most important medical and social problem. The epidemic of obesity observed in recent decades requires the development of new approaches to the diagnosis, treatment and prevention of this disease and its numerous complications. An essential factor in the recovery of this category of patients is adequate diet therapy, providing the right balance of the main macro- and micronutrients and enriched with several biologically active compounds that affect the adaptation and recovery capabilities of the body. To increase the effectiveness of nutritional support and to solve all the tasks set to normalize the metabolic status, it is advisable to include in the diet of this category of patients a wide range of specialized food products for therapeutic and preventive nutrition, sources of protein, polyunsaturated fatty acids, dietary fiber, vitamins and minerals, including antioxidants, bioactive compounds from plant origin and others. Key words: alimentary-dependent diseases, diet therapy, obesity, nutritional status, specialized food products
Gut microbiota and obesity
Authors:   Research Clinical Institute of Childhood, Ministry of Health of the Moscow Region, Moscow, Russian Federation, Khavkin A.I. ,   Belgorod State Research University, Belgorod, Russian Federation, Shrainer E.V. ,   Institute of Chemical Biology and Fundamental Medicine Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation,   Group of companies “Center for new medical technologies”, Novosibirsk, Russian Federation,   “Soloways” laboratory, Novosibirsk, Russian Federation, Nikolaichuk K.M. ,   Novosibirsk State University, Novosibirsk, Russian Federation, Pak I.A. ,   Group of companies “Center for new medical technologies”, Novosibirsk, Russian Federation,   “Soloways” laboratory, Novosibirsk, Russian Federation, Dudurich V.V. ,   Federal State Autonomous Educational Institution of Higher Education “ITMO National Research University”, Saint Petersburg, Russian Federation,   “Сerbalab” laboratory, Saint Petersburg, Russian Federation, Ponomarenko A.V. ,   Institute of Chemical Biology and Fundamental Medicine Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation,   Group of companies “Center for new medical technologies”, Novosibirsk, Russian Federation,   “Soloways” laboratory, Novosibirsk, Russian Federation, Yakovets E.А. ,   Novosibirsk State University, Novosibirsk, Russian Federation, Pokushalov E.A. ,   Group of companies “Center for new medical technologies”, Novosibirsk, Russian Federation,   “Soloways” laboratory, Novosibirsk, Russian Federation
Published: September 2024

The global prevalence of obesity has almost tripled since the end of the last century. Excess body weight is responsible for nearly 2.8 million deaths each year due to complications. Many studies support both a genetic predisposition and the role of the gut microbiome in obesity’s development. The review is highlight recent scientific advances in understanding the relationships between the gut microbiome, obesity, and comorbidities for cause-and-effect relationships. It examines impact of gut microbiota composition and changes in metabolite profile on the obesity pathogenesis and related metabolic disorders. The article also discusses such therapeutic microbiota’s agents as antibiotics, pre-, auto- and probiotics, as well as fecotransplantation. Key words: obesity, microbiota, metabolites, children, short-chain fatty acids
Perancangan Aplikasi Manajemen Perangkat Mikrotik Dengan Memanfaatkan Application Programming Interface RouterOS Menggunakan Metode Waterfall
Authors: Hartono Rudi , Rafid Adhitya Pratama Dzulfiqar , Purnomo Fendi Aji
Published: September 2024

Abstrak 

Penelitian ini mengembangkan aplikasi manajemen perangkat MikroTik menggunakan Application Programming Interface (API) RouterOS dengan metode waterfall. Aplikasi ini bertujuan untuk memudahkan pengelolaan dan konfigurasi perangkat jaringan MikroTik, dengan fitur-fitur utama seperti konfigurasi perangkat, pemantauan perangkat, dan manajemen pengguna, serta fitur tambahan seperti pengelolaan log, manajemen firewall, dan manajemen hotspot. Proses pengembangan dimulai dengan analisis kebutuhan yang melibatkan identifikasi kebutuhan pengguna dan fitur yang diperlukan. Desain sistem mencakup perancangan arsitektur sistem, database, dan antarmuka pengguna. Implementasi melibatkan pengembangan kode program, integrasi dengan API RouterOS, dan pengujian menyeluruh menggunakan metode black box untuk memastikan semua fungsi berjalan sesuai kebutuhan fungsional. Hasil pengujian menunjukkan bahwa aplikasi ini berfungsi dengan baik dan dapat memenuhi kebutuhan pengguna. Dengan demikian, aplikasi ini diharapkan dapat membantu organisasi dan bisnis dalam mengelola perangkat MikroTik secara lebih efisien dan efektif.

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Abstract

This study presents the development of a MikroTik device management application using the RouterOS Application Programming Interface (API) and the waterfall methodology. The primary goal of the application is to facilitate the management and configuration of MikroTik network devices. It features essential functionalities such as device configuration, device monitoring, and user management, along with additional features like log management, firewall management, and hotspot management. The development process commenced with a needs analysis, identifying user requirements and necessary features. The system design phase included the architectural design, database design, and user interface design. Implementation involved coding, integration with the RouterOS API, and comprehensive testing using the black box method to ensure all functions met the specified requirements. The testing results demonstrated that the application functions effectively and meets user needs. Consequently, this application is expected to assist organizations and businesses in managing MikroTik devices more efficiently and effectively.
Prototipe Sistem Pemantauan dan Penyiraman Tauge Berbasis IoT Menggunakan Wemos dan Firebase
Authors: Ramadhan Dimas Agih , Susanto Rudi , Lestari Wiji
Published: September 2024

Abstrak 

Dalam penanaman tauge supaya hasil tauge menjadi bagus perlu memperhatikan beberapa hal. Sekarang ini penyiraman masih dilakukan manual dan perlu waktu yang lama jika dilakukan pada budidaya besar dengan jumlah tenaga sedikit, akibatnya pemantauan kondisi pertumbuhan tauge juga tidak optimal. Dibutuhkan sistem penyiraman sekaligus pemantauan yang pada penelitian ini terintegrasi dengan smartphone, memanfaatkan Internet of Things dengan Wemos D1 Mini dan Firebase. Metode prototype digunakan untuk pengembangan sistemnya dan framework Flutter digunakan dalam pembuatan aplikasi antarmuka di Android. Untuk pengujian sistem dilakukan pengujian fungsional terhadap perangkat keras dan black box testing terhadap perangkat lunak. Hasil pengembangan sistem ialah perangkat IoT penyiraman terjadwal serta pemantauan suhu, kelembaban, dan tingkat cahaya yang dapat dipantau secara real time maupun terdokumentasi. Hasil penanaman tauge menggunakan alat ini mencapai panjang lebih dari 10 cm dalam 3 ½ hari waktu tanam dan kurang dari 10 cm dengan waktu tanam 2 ½ hari.

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Abstract

In growing bean sprouts, several things need to be considered in order to obtain good results. Currently, watering is still done manually and takes a long time when done on a large cultivation scale with limited labor, resulting in suboptimal monitoring of the growth conditions of the bean sprouts. An irrigation system and monitoring system integrated with a smartphone are needed, utilizing the Internet of Things with Wemos D1 Mini and Firebase. The prototype method is used for system development and the Flutter framework is used in creating the Android interface application. For system testing, functional testing is conducted on the hardware and black box testing on the software. The result of the system development is a scheduled IoT watering device and real-time or documented monitoring of temperature, humidity, and light levels. The result of growing bean sprouts using this tool achieves a length of more than 10 cm in 3 ½ days of planting time and less than 10 cm with 2 ½ days of planting time.
Digitalisasi Sistem Perpustakaan Sebagai Upaya Pengembangan Literasi Siswa Di SMA Negeri 1 Kayen Kabupaten Pati
Authors: Mustaqim Fakhrizal , Maryam Maryam
Published: September 2024

Abstrak

Literasi digital bertujuan untuk meningkatkan keterampilan yang diperlukan untuk menerima, menganalisis, dan mengevaluasi berbagai bentuk informasi dari kegiatan membaca. Proses peminjaman yang dilakukan secara manual menyebabkan peminjaman buku membutuhkan waktu lama, sehingga memerlukan keterlibatan teknologi informasi yang berfungsi untuk menginformasikan buku perpustakaan serta memudahkan peminjam yang dibatasi oleh jarak dan waktu. Aplikasi digitalisasi sistem perpustakaan digunakan sebagai upaya pengembangan literasi pada siswa di SMA Negeri 1 Kayen Kabupaten Pati. Sistem ini dapat memberitahukan informasi buku, ketersediaan buku, menampilkan video pembelajaran, melakukan transaksi peminjaman online melalui website menggunakan barcode yang berisi kode reservasi, memudahkan petugas memonitoring peminjam, membuat laporan, dan dapat mengingatkan peminjam untuk masa peminjaman akan berakhir melalui fitur notifikasi. Metode yang digunakan membangun aplikasi ini menggunakan metode waterfall, yaitu: analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Keunggulan dari penelitian ini berupa fungsi untuk reservasi buku yang diimplementasikan dalam teknologi barcode. Selain itu, untuk mengantisipasi keterlambatan pengembalian buku, fitur notifikasi dibuat dan akan muncul pada halaman riwayat peminjaman. Sistem ini mampu mengelola data pustaka, data transaksi, mengakses video pembelajaran, dan laporan.

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Abstract

Digital literacy aims to improve the skills needed to receive, analyze and evaluate various forms of information from reading activities. The process of borrowing that is done manually causes borrowing books to take a long time, so it requires the involvement of information technology which functions to inform library books and make it easier for borrowers who are limited by distance and time. The application of digitizing the library system is used as an effort to develop literacy in students at SMA Negeri 1 Kayen, Pati Regency. This system can notify book information, book availability, display learning videos, make online loan transactions via the website using a barcode that contains a reservation code, make it easier for officers to monitor borrowers, make reports, and can remind borrowers that the loan period will end through the notification feature. The method used to build this application uses the waterfall method, namely: requirements analysis, system design, implementation, testing, and maintenance. The advantage of this research is the book reservation function implemented in barcode technology. In addition, to anticipate delays in returning books, a notification feature is made and will appear on the borrowing history page. This system is capable of managing library data, transaction data, accessing learning videos, and reports.
Peringkasan Teks Berita Berbahasa Indonesia Menggunakan LSTM dan Transformer
Authors: Ardyanti Christina Prilla Rosaria , Wibisono Yudi , Megasari Rani
Published: September 2024

Abstrak

Pertumbuhan informasi di internet membuat volume data tekstual semakin besar. Hal ini membuat manusia kesulitan dalam mengolah informasi dengan cepat. Peringkasan teks dapat membantu manusia untuk memahami informasi dalam jumlah yang banyak dengan cepat. Pada penelitian ini, arsitektur encoder-decoder akan diimplementasikan pada dataset Indosum menggunakan Long Short Term Memory (LSTM) dengan tambahan  mekanisme atensi dan Transformer. Ujicoba juga dilakukan menggunakan  fine-tuning pada pre-trained model T5-Small dan BART-Small. Eksperimen juga dilakukan dengan membandingkan dataset yang menggunakan praproses dan tanpa praproses. Berdasarkan eksperimen, model LSTM-Atensi memiliki kinerja rendah  dengan nilai ROUGE-L sebesar 13.0 pada dataset yang menggunakan praproses. Sedangkan nilai ROUGE-tertinggi didapatkan dari hasil fine-tuning T5-Small dengan nilai sebesar 66.2.

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Abstract

The proliferation of information on the internet has led to an increasing volume of textual data. This presents a challenge for humans in processing information rapidly. Text summarization can aid humans in quickly comprehending large amounts of information. In this research, an encoder-decoder architecture will be implemented on the Indosum dataset using Long Short-Term Memory (LSTM) along with attention mechanisms and Transformer. Experiments will also involve fine-tuning pre-trained models T5-Small and BART-Small. The influence of preprocessing will also be studied through experiments. Based on the experiments, the LSTM-Attention model demonstrates poor performance with an ROUGE-L score of 13.0 on the preprocessed dataset. Conversely, the highest ROUGE score was achieved through fine-tuning T5-Small, scoring 66.2.
Deteksi Dini Gejala Stres pada Mahasiswa Berdasarkan Faktor-Faktor Penyebabnya Menggunakan Metode Logistic Regression
Authors: Hakim Auliya Afifah Adnan , Saputra Rizal Adi , Statiswaty Statiswaty
Published: September 2024

Abstrak

Di era saat ini, kesehatan mental seringkali diabaikan dibandingkan dengan kesehatan fisik. Hal ini sangat berlaku bagi mahasiswa yang berjuang dengan tekanan yang meningkat dalam kehidupan kuliah. Oleh karena itu, ada kebutuhan mendesak untuk solusi yang dapat mendukung kesehatan mental, salah satunya adalah metode Logistic Regression. Penelitian ini menegaskan efektivitas metode Logistic Regression dalam memprediksi dan mendeteksi dini gejala stres berdasarkan faktor penyebabnya. Eksplorasi fitur dan parameter mengungkap variasi tingkat akurasi, mencapai puncak 95%, diikuti oleh 88% dan 61%. Menganalisis hasil menggunakan Counseling_Service_Use sebagai output menunjukkan keahlian model dalam memprediksi hasil positif, meskipun dengan kecenderungan untuk memprediksi data negatif sebagai positif, dan sebaliknya. Sementara itu, model yang menggunakan Chronic_Illness dan Stress_Level sebagai output menunjukkan kinerja luar biasa dalam memprediksi semua kelas. Secara keseluruhan, penelitian ini memberikan dukungan kuat untuk efektivitas Logistic Regression dalam memprediksi gejala stres, memperkaya pemahaman tentang penerapannya dalam konteks kesehatan mental. Ini menunjukkan bahwa metode ini dapat digunakan sebagai alat yang efektif untuk deteksi dini gejala stres.

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Abstract

In the current era, mental health often takes a backseat compared to physical health. This is particularly true for students who are grappling with the increasing pressures of college life. Therefore, there is an urgent need for solutions that can support mental health, one of which is the Logistic Regression method. This study affirms the effectiveness of the Logistic Regression method in predicting and early detecting symptoms of stress based on their causative factors. Exploration of features and parameters revealed variations in accuracy rates, reaching a peak of 95%, followed by 88% and 61%. Analyzing results using Counseling_Service_Use as the output demonstrated the model’s proficiency in predicting positive outcomes, albeit with a tendency to predict negative data as positive, and vice versa. Meanwhile, models employing Chronic_Illness and Stress_Level as outputs exhibited outstanding performance in predicting all classes. Overall, this research provides robust support for the effectiveness of Logistic Regression in predicting stress symptoms, enriching the understanding of its application in the context of mental health. This shows that this method can be used as an effective tool for early detection of stress symptoms.
Analysis of Factors Affecting the Use of Digital Paylater Transactions Using the Hedonic-Motivation System Adoption Model (HMSAM)
Authors: Muhammad Zahwan Latif  , Utomo Rio Guntur
Published: September 2024

The use of paylater digital transaction methods is a major trend in the current era of digitalization. This study aims to analyze the factors of Continuance Intention of paylater digital transactions. Employing a quantitative approach with Partial Least Square Structural Equation Modeling (SEM-PLS), the research focuses on individuals aged 18 and above who have made digital paylater transactions. The sampling technique chosen was a purposive sampling technique, while data collection was conducted through questionnaires. This research proposes a modified Hedonic-Motivation System Adoption Model (HMSAM) and formulates hypotheses to test the relationship between variables. Data analysis was conducted by measuring the validity and reliability of the model and applying SEM-PLS to analyze variable relationships and test hypotheses. This model integrates elements from HMSAM developed by previous researchers. The six main variables include perceived ease of use, curiosity, joy, control, satisfaction, and Continuance Intention. The results revealed that the hypothesis testing conducted for 6 from 7 hypotheses shows the value of T-Statistics> 1.96, the value of P-Values <0.05, and the value of R-Square in low and moderate indicates moderate and small classification of the influence of Factors Affecting the Use of Digital Paylater Transactions Using the Hedonic-Motivation System Adoption Model (HMSAM).
Movie Recommendation System Based on Synopsis Using Content-Based Filtering with TF-IDF and Cosine Similarity
Authors: Juni Permana Armadhani Hiro Juni Permana , Agung Toto Wibowo
Published: September 2024

Recommendation systems have become an interesting topic in the field of artificial intelligence and data analysis. In the current era of technological advancement, the entertainment industry is rapidly growing, particularly the film industry, which is highly popular among the public due to their enthusiasm for watching movies. The increasing number and variety of films with various genres and titles have made it challenging for users to choose a film. To assist them in selecting movies, the presence of a recommendation system is necessary to provide information or film recommendations based on user interests and preferences. In this research, the development of the recommendation system will utilize the content-based filtering method, employing the TF-IDF algorithm and cosine similarity. The dataset used in this study is derived from publicly available data (MovieLens). The results of this research demonstrate that the TF-IDF and cosine similarity algorithms provide recommendations that align with the viewers' interests, as measured by precision, recall, and f1-score calculations.
Sentiment Analysis on Acute Kidney Syrup Videos Using CNN and LSTM Algorithms
Authors: Tamara Guido , Kemas Muslim L
Published: September 2024

The issue of acute kidney failure, particularly caused by the consumption of cough syrup, was circulating around October 2022 and has become a serious public health concern. This issue has drawn extensive attention and sparked various reactions on social media. In this digital era, public opinion expressed in comments on social media platforms like YouTube significantly impacts societal perceptions. Therefore, in the context of the aforementioned issue, sentiment analysis on YouTube video comments can provide valuable insights into societal perceptions and people’s reactions. Therefore, this study focuses on the sentiment analysis of public opinions expressed in YouTube comments related to this matter. The methods employed for this analysis include Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) with Word2Vec feature extraction. The findings of this study indicate that both these methods produce good performance results with an oversampling dataset with a 90:10 data proportion. In the performance comparison, CNN yielded the highest accuracy, at 0.92, while LSTM was at 0.90.
Performance Analysis of Facial Image Feature Extraction Algorithm for Smart Home Security System Detection
Authors: Adly Muhammad Ihsan , Mandala Satria
Published: September 2024

Alongside the development of technology to facilitate multi-family security, security tools are also being developed. Smart home security is one of the very popular security tools in Indonesian home construction. The tool works automatically in real time and has no restrictions on environmental conditions. However, currently available tools still lack consistent accuracy and consistent performance. To solve this problem, the author proposes a smart home security system with an Arduino UNO-connected camera, two relay modules, a magnetic lock, and connecting to a home Internet of Things system. The methods used in the research for this thesis project were: 1. Literature review of ongoing Smart Home Security using facial image feature extraction algorithm research; 2. Deployment of Arduino UNO, 2 Relay Module, and Solenoid Lock; 3. The feature extraction algorithm used is Wavelet. The proposed method is expected to achieve an accuracy of 80% or more. The experimental results showed that the proposed prototype of this experiment achieved the accuracy of 85.7%. In addition to accuracy, there is also precision rate at 87.94%, recall rate at 87.56%, and f1-score rate at 87.28%
Hoax Detection of Covid-19 News on Social Media using Convolutional Neural Network (CNN) and Support Vector Machine (SVM)
Authors: Cahyani Arvia Dwi , Ramdani Andi Kholik
Published: September 2024

It is undeniable that nowadays news spreads very quickly on social media. The ease of getting news on social media has resulted in some users using and spreading news without knowing the authenticity of the news. Twitter (X) users play an important role in spreading news on social media. In early 2020, cases of Covid-19 started to occur in Indonesia and some people spread news about Covid-19 without knowing the real information. The news is increasingly spreading through Twitter media which is shared by irresponsible people. This research builds a system that can detect hoax news on social media. The stages in this study started from crawling data, data preprocessing, word embedding, data separation, modeling process, and model evaluation. The methods used are Convolutional Neural Network (CNN) and Support Vector Machine (SVM). The dataset used is news of Covid-19 in X Social media. The experiment showt that the use of the N-Gram Unigram + Bigram + Trigram combination on CNN produces an accuracy value of 75.8%, meanwhile in the SVM modeling produces 77.9%. It can be concluded that SVM has better performance than CNN in detecting hoax news,
Space Technology and Its Military Application: Options for Pakistan
Authors: Amir Shamaila , Rehman Nazia Abdul
Published: September 2024

Space technology has aided military operations and has established its place in national defense. There is a dire need for Pakistan to exploit this military tool for the balance of power in the region. Space technology is changing the face of military warfare and the contest for dominance in space has increased its pace. The same has been a neglected part of the national policy of Pakistan and has not received its prioritization yet despite having an early start on this front. This article focuses mainly on the current performance comparison of Pakistani-leased satellites with Indian indigenous developed satellites. If Pakistan does not plan to keep pace with India’s fast-growing space technology, it may result in disastrous results in the future, keeping in mind the history of wars between the two countries. The authors suggest that an inclusive, steady, and strong national space policy on the part of Pakistan should be articulated and executed.
Pulmonary embolism in a young patient with nephrotic syndrome: a case report.
Authors: Dulcetti A , Bruscia C , Malena D M. , Murante G , Angelino A , March M Rocchietti , Mariani B , Alfei B , Martocchia A , Sesti G
Published: September 2024

Introduction
Nephrotic syndrome (NS) is characterized by the presence of proteinuria of ≥ 3 g/24 h, hypoalbuminemia < 2.5 g/dl, peripheral edema, and severe hyperlipidaemia. NS is associated with increased risk of deep venous thrombosis (DVT), and, consequently, pulmonary embolism (PE) .
Case presentation
We report a case of a severe PE in a young patient with NS, admitted to the Emergency Medicine Department of the University Hospital Sant’Andrea of Rome.
Conclusions
The aim of this report is to allow a more comprehensive knowledge of the SN and its related EP highlighting both the risk of underdiagnosis and the need of a multidisciplinary approach by a team of different specialists. We also reviewed pathophysiology of hypercoagulability in NS characterized by the imbalance of prothrombotic and antithrombotic factors, and by impaired thrombolytic activities. A more complete knowledge of the clinical and laboratory features of NS and its related PE appears to be crucial for the early diagnosis and treatment.