Surge Of Activity Research Articles

Emergency call utilization over a 10-years period: an observational study in Region Zealand, Denmark, 2013–2022

BackgroundImproving prehospital emergency care requires a comprehensive understanding of the efficiency of emergency medical services and demand fluctuations. The medical emergency call is the primary contact between citizens and the emergency medical dispatch center, serving as the gateway to accessing emergency assistance. This study aimed to characterize the emergency call population and analyze the development of emergency call utilization in Region Zealand in Denmark during a 10-years period.MethodsThis was an observational register-based study of administrative data from the emergency medical dispatch center in Region Zealand. Data was collected from 1 January 2013 to 31 December 2022. All unique emergency calls from residents to the emergency number “1-1-2” were included. Descriptive analyses were used to characterize the study population. Poisson regression models were used to calculate ratio estimates for the association between years and hospital catchment areas, using the incidence rate of emergency calls as outcome measure.ResultsA total of 641,457 emergency calls were included. A significant increase in the total number of emergency calls was found, with an increase from 58,454 annual calls to 80,819 calls over the study period. The incidence rate per 1000 residents per year increased from 71.1 to 95.2, a 35% increase. The southern part of the region had significantly more emergency calls per 1000 residents per year during the study period compared to the eastern part of the region (IRR 1.70). Demographically, males comprised 52.3% of cases, and patients aged 65 and older represented 48.2% of calls. Emergency calls were “Emergency level A” in 45.5% and “Emergency level B” in 39.1%. In 22.3% of cases, the emergency call was categorized as “Unclear problem.” The most frequent categories were “chest pain” (12.7%), “impaired consciousness” (9.6%), “breathing difficulties” (8.8%), “accidents” (7.9%), and “minor injuries” (7.6%).ConclusionsThe study revealed a significant increase in emergency calls, both in absolute numbers and per 1000 residents per year, indicating growing demand for emergency care, along with a surge in activity at the region's dispatch center. Regional disparities underscores the potential necessity for tailored developmental approaches over time.

Second hand or second generation? The performance of secondary buyouts

AbstractSecondary buyouts (SBOs) appear paradoxical because the surge in SBO activity is met with scepticism from the public and investors regarding their performance. In this paper, we undertake a comprehensive analysis of SBO performance through two distinct lenses: First, we address the prevailing notion of SBOs as “lemons”. These are perceived as opportunities that, following a successful primary buyout (PBO), seemingly leave little room for further value creation. To investigate this “negative correlation hypothesis”, we employ a unique back-to-back sample of 276 cases involving the same firm in both a PBO and an SBO. Analysing the correlation between the internal rate of returns (IRRs) of back-to-back PBO/SBOs, our results do not support the “negative correlation hypothesis”. Second, we directly compare the deal performance of the two related back-to-back buyout rounds. For our back-to-back sample, we find that PBOs display significantly higher IRRs than SBOs. However, after performing a matched comparison adjusting for size and holding period differences, which are two well-known pitfalls of IRR rank orders, our findings suggest that there is no systematic outperformance of SBOs against their PBO comparables. Finally, we analyse differences in operating performance between PBOs and SBOs. Our results do not indicate a significant difference, either based on the back-to-back sample or when comparing PBOs and SBOs against matched public peers. In the light of our findings, we advocate for a reevaluation of the current perception of SBOs. Rather than being dismissed as “second-hand” opportunities, they should be recognised as “second-generation” opportunities deserving closer consideration.

Sarcasm detection on social data: heuristic search and deep learning

<span lang="EN-US">Due to the significant surge in online activity, sarcasm detection (SD) has attracted major attention in social media networks. Sarcasm is a lexical item of negative sentiments or dislikes by utilizing exaggerated language constructs. SD has created a natural language processing (NLP) procedure focused on the intricate and unclear aspects of sarcasm, primarily used in sentiment analysis (SA), human-computer interaction, and various NLP applications. Concurrently, advancements in machine learning (ML) approaches facilitate the creation of effective SD systems. This manuscript presents the future search algorithm with deep learning assisted sarcasm detection and classification on social networking data (FSADL-SDCSND) approach. The major intent of the FSADL-SDCSND approach is in the effective and automated recognition of sarcastic text. In the presented FSADL-SDCSND technique, several data pre-processing stages are achieved to transform the data into a compatible format. Besides, the FSADL-SDCSND approach applies a bidirectional serial-parallel long short-term memory (BS-PLSTM) approach for SD and classification. The hyperparameter tuning process is accomplished by employing the future search algorithm for improving the recognition of the BS-PLSTM model. For superior output of the FSADL-SDCSND model, a sequence of simulations can be applied. The investigational outputs highlighted the improved solutions of the FSADL-SDCSND model with other approaches under diverse performance measures.</span>

Epilepsy in children and anesthesia

Epilepsy, also called seizure disorder, is the most common childhood brain disorder in the United States. The aetiology of epilepsy in children is multifactorial with congenital, metabolic, infective, and problems associated with prematurity being common causes. Nearly 3 million Americans have epilepsy. About 450,000 of them are under 17 years old. About 1 in 200 children (0.5%) have epilepsy, a neurological condition where children have a predisposition to recurrent, unprovoked seizures. There are many different types of epilepsy, especially in infancy, childhood and adolescence. Epilepsy can be thought of in terms of either: the site of seizure origin in the brain (generalised or focal seizures), or the underlying cause. Genetic epilepsies (formerly called idiopathic or primary epilepsies) occur in an otherwise normal person and are due to a genetic predisposition to seizures. Some epilepsies are due to an underlying abnormality of the brain structure or chemistry (formerly called symptomatic or secondary epilepsies). Other epilepsies have no known cause. Epilepsy is commonly diagnosed in children and can be confused with other conditions. An accurate diagnosis is essential. A seizure is an excessive surge of electrical activity in the brain that can cause a variety of symptoms, depending on which parts of the brain are involved. Seizures can be provoked or unprovoked. Provoked seizures, caused by fever in a young child or severe hypoglycemia, are not considered to be forms of epilepsy. Unprovoked seizures have no clear cause but can be related to genetics or brain injury. When a child has two or more unprovoked seizures, epilepsy is often the diagnosis. Despite advances in antiepileptic medication therapy, a significant number of pediatric patients with epilepsy have seizures that are not well controlled. Antiepileptic medications interact with anesthetic agents, and common anesthetics can precipitate or suppress seizure activity. There are important pharmacokinetic and pharmacodynamic interactions between AEDs and drugs commonly used in anaesthesia. These affect both drug efficacy and the risk of seizure activity intraoperatively.

Ten Years of Fashion Design Research Scientometric Analysis of Research: Research Overview, Frontiers and Evolutionary Paths

Background and Aim: Fashion design is a highly creative, interdisciplinary field that covers many aspects such as clothing, accessories, and textiles. Through creative design, material selection, process technology, etc., provide people with unique, beautiful, and practical fashion products and services. There has been a significant surge in research activity in the field of fashion design over the past decade, and by reviewing the data it was found that there is an academic gap in the bibliometrics of Fashion Design. The purpose of this study is 1) To study the research overview of Fashion Design. 2) To analyze the research frontiers of Fashion Design. 3) To analyze the evolution Path of Research Frontiers of Fashion Design. Materials and Methods: The key steps in retrieval: (1) Select database; (2) Enter "Topic"; (3) Select Document Type; (4) Select Document Language; (5) Enter Document Release Time Scope. Enter Topic="Fashion Design". Document types are article, proceeding paper, and English review from 2014-01-01 to 2022-12-31 for recent research. Book Citation Index-Science and Book Citation Index-Social Science & Humanities were excluded, leaving 1,049 documents. Common scientometric software includes CiteSpace, HistCite, Loet Tools, SciMAT, and VOSviewer. This study uses VOSviewer (version 1.6.19) for visualizing and analyzing scientific literature, helping researchers identify patterns, trends, and relationships in data. Results: The result of this research is that there are many prolific authors, Countries, and Publishers in this research field. There are three research fronts: "Impact", "Consumption" and "Industry". The evolution path of the research fronts starts from "Clothing Design" in 2014-2018. and "Arts", to "Innovation" in 2018-2019, to "Creativity" in 2019-2020, then to "Technology" and "Sustainability" in 2020-2021. Conclusion: The quality of articles in the "Fashion Design" research field is generally higher, with more research and very active. Research Frontiers: There are three research fronts: "Impact", "Consumption" and "Industry" The fashion design field’s focus on influence, consumption, and industry reflects its increasing emphasis on business and social impact. Evolution Path of Research Frontiers: The evolutionary path of the research frontier ranges from “Costume Design” and “art” in 2014-2018, to “Innovation” in 2018-2019, to “Creativity” in 2019-2020, and then to “technology” in 2020-2021 and “Sustainable development”. After 2021, it will be "Impact ", "Consumption" and "Industry". The evolution path of the research frontier reflects the shift in the development direction of the field of fashion design from single design and art to more design and art: diversification and comprehensiveness. From focusing on innovative ideas to technology and sustainable development to market, consumer, and industry development, it reveals the changes and evolution in the field of fashion design in the pursuit of excellence, sustainable development, and social impact.

MODERN TRANSFORMATIONS OF NATIONAL ECONOMIES IN RESPONSE TO THE GLOBALIZATION OF FINANCE AND CREDIT

The study's relevance is determined by the fact that the global economy is a chaotic system composed of millions of interconnected elements (economies of individual countries). In this context, it is emphasized that each national economy experiences periods of growth and decline. These cycles have an irregular nature and can be triggered by intermittenсies in the finance and credit sectors in globalized economies, specifically phenomena of sudden, unpredictable surges in activity or volatility that cause their transformation, while in periods of relative stability, they ensure their sustainability. Thus, the article's aim is a comprehensive analysis of typical transformations of national economies as a response to the globalization of the finance and credit. The study emphasizes that the globalization of the finance and credit creates a highly dynamic and complex environment where the economies of various countries are closely interconnected. As a result of globalization, financial crises, technological innovations, and geopolitical events can rapidly spread across the globe, triggering significant changes in the economies of different nations. These processes are quite chaotic, but they exhibit certain recurring patterns. The transformations of national economies, driven by core intermittent events, manifest in the liberalization of financial markets, the development of financial innovations, the strengthening of central banks, and the reinforcement of international cooperation. Most countries have liberalized their financial markets by lowering barriers for foreign investors and expanding access to financial services. National economies are actively developing financial innovations such as fintech, blockchain, and cryptocurrencies to adapt to the new conditions of global competition. Central banks are playing an increasingly important role in stabilizing financial systems and mitigating the effects of financial crises. Countries are collaborating internationally to develop common rules and standards in the financial and credit sectors, aiming to minimize the risks of global financial crises. The transformations of national economies affect developed and developing countries, bringing about positive and negative consequences.

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate harmful content, execute phishing schemes, and orchestrate various cyber attacks. As these threats evolve, detecting malicious URLs (MURLs) has become crucial for safeguarding internet users and ensuring a secure online environment. In response to this urgent need, we propose a novel machine learning-driven framework designed to identify known and unknown MURLs effectively. Our approach leverages a comprehensive dataset encompassing various labels—including benign, phishing, defacement, and malware—to engineer a robust set of features validated through extensive statistical analyses. The resulting malicious URL detection system (MUDS) combines supervised machine learning techniques, tree-based algorithms, and advanced data preprocessing, achieving a high detection accuracy of 96.83% for known MURLs. For unknown MURLs, the proposed framework utilizes CL_K-means, a modified k-means clustering algorithm, alongside two additional biased classifiers, achieving 92.54% accuracy on simulated zero-day datasets. With an average processing time of under 14 milliseconds per instance, MUDS is optimized for real-time integration into network endpoint systems. These outcomes highlight the efficacy and efficiency of the proposed MUDS in fortifying online security by identifying and mitigating MURLs, thereby reinforcing the digital landscape against cyber threats.

(Cautiously) Embracing pro-Palestinian activism in Singapore: civil society in illiberal regimes

ABSTRACT This paper explores the rise of pro-Palestine activism in Singapore. In illiberal regimes like the city–state, the political opportunities for activists to assert themselves are limited, though not non-existent. It is thus instructive to witness how the new surge of pro-Palestine activism in the country, and indeed, worldwide, has been dealt with by the government. I make the following claims. First, while the overall thrusts of Singapore’s foreign and domestic policies remain the same with regard to the Israel–Palestine conflict, especially on Singapore’s special relationship with Israel, the People’s Action Party (PAP) government has given clear concessions to the pro-Palestinian camp. Second, this balancing act is done with domestic electoral and political goals in mind. The issue has special resonance among younger Singaporeans and the Muslim community, and the government is well-aware of that. Politically, if not dealt with properly, the matter could also be a potential racial-religious fault-line, which is why political sophistication was needed to appease the various sides in society. The implication is that even in less democratic polities like Singapore, activists can make significant gains in the realm of both public opinion and policy. This study is situated within the literature on civil society-state relations.

Do political elite endorsements influence online mobilization? A study of Twitter behavior in Narendra Modi’s 2019 election campaigns

ABSTRACT Modern campaigns increasingly rely on social media to influence voters, with Twitter offering affordances that enable direct communication between politicians and the public. However, scholars remain divided over the effectiveness of engaging ordinary Twitter users for mobilizing support online. This article seeks to address this issue by examining whether endorsements from political elites influence the tweeting behavior of ordinary users. Using a quasi-experimental design, we analyze an original dataset of tweets made by users who were mentioned (N = 27,634; 36.62 million tweets) and not mentioned (N = 27,672; 16.30 million tweets) by Indian Prime Minister Narendra Modi on 16th March 2019, during his national election campaign. Our analysis reveals that, on average, users mentioned by Modi exhibited a greater increase in tweet activity compared to those not mentioned. However, this surge in activity proved to be only temporary, suggesting that mentions by political elites facilitate immediate mobilization but are not necessarily self-sustaining. Furthermore, no evidence was found of a differential effect based on users’ pre-existing engagement levels. Our findings offer important insights into political leaders’ strategic use of Twitter in campaigns and contribute to the theoretical understanding of Twitter's role in mobilization and interactivity by bringing in diverse perspectives from the Global South.

Effects of ketamine on GABAergic and glutamatergic activity in the mPFC: biphasic recruitment of GABA function in antidepressant-like responses.

Major depressive disorder (MDD) is associated with disruptions in glutamatergic and GABAergic activity in the medial prefrontal cortex (mPFC), leading to altered synaptic formation and function. Low doses of ketamine rapidly rescue these deficits, inducing fast and sustained antidepressant effects. While it is suggested that ketamine produces a rapid glutamatergic enhancement in the mPFC, the temporal dynamics and the involvement of GABA interneurons in its sustained effects remain unclear. Using simultaneous photometry recordings of calcium activity in mPFC pyramidal and GABA neurons, as well as chemogenetic approaches in Gad1-Cre mice, we explored the hypothesis that initial effects of ketamine on glutamate signaling trigger subsequent enhancement of GABAergic responses, contributing to its sustained antidepressant responses. Calcium recordings revealed a biphasic effect of ketamine on activity of mPFC GABA neurons, characterized by an initial transient decrease (phase 1, <30 min) followed by an increase (phase 2, >60 min), in parallel with a transient increase in excitation/inhibition levels (10 min) and lasting enhancement of glutamatergic activity (30-120 min). Previous administration of ketamine enhanced GABA neuron activity during the sucrose splash test (SUST) and novelty suppressed feeding test (NSFT), 24 h and 72 h post-treatment, respectively. Chemogenetic inhibition of GABA interneurons during the surge of GABAergic activity (phase 2), or immediately before the SUST or NSFT, occluded ketamine's behavioral actions. These results indicate that time-dependent modulation of GABAergic activity is required for the sustained antidepressant-like responses induced by ketamine, suggesting that approaches to enhance GABAergic plasticity and function are promising therapeutic targets for antidepressant development.

Surge in Eye Drop Safety Concerns and Interest in Alternative Dry Eye Disease Therapy Following Eye Drop Recalls: A Cross-Sectional Google Trends Analysis.

Beginning in January 2023, numerous eye drops were recalled following reports of contamination. To investigate hesitancy in topical therapies for dry eye disease (DED), we analyzed trends in Internet search traffic for alternative DED therapies and eye drop safety concerns following initial recalls. Google Trends (GT) was used to measure the popularity of specific search terms during a given time period. The main GT output metric for gauging interest in a search term is the Search Volume Index (SVI). We collected worldwide SVI data for terms "dry eye vitamin," "are eye drops safe," "stop eye drops," "lipiflow," "ilux treatment," "dry eye mask," "dry eye warm compress," "omega-3 for dry eyes," "dry eye plugs," "dry eye humidifier," "itear," and "IPL dry eye" from April 24, 2022, to October 29, 2023. Statistical analysis was performed with Microsoft Excel v.16.77.1, and comparisons between groups were performed using paired t tests. A significant increase in SVI was observed for most keywords. When comparing the 40-week period before and after the initial recall, 7/10 alternative DED therapies demonstrated a statistically significant surge in Internet search traffic after recall (P < 0.05). Furthermore, 2/2 keywords pertaining to eye drop safety concerns demonstrated an increase in SVI (P < 0.0001). We identified a significant surge in Internet search activity for eye drop safety and alternative DED therapies following eye drop recalls. Public health agencies and physicians may find this information valuable while attempting to address safety concerns and navigating noncompliance of routine eye drop therapy.

Behavioral patterns in elderly single-person households

The global rise in the aging population and the increase in older adults living alone have raised concerns about health-related behaviors, particularly sedentary lifestyles and reduced daily activities. These behaviors are linked to higher risks of physical and cognitive conditions. While many global studies have explored these patterns, research within the Chilean context remains limited. This work presents a analysis of behavioral patterns in elderly individuals living alone in Chile, offering valuable insights into this population. Using clustering techniques, we identified two distinct activity patterns among the participants. The first pattern is characterized by a gradual increase in activity during the day, peaking around midday and followed by a decline, likely associated with meal preparation and rest. The second pattern demonstrates a more dynamic lifestyle, with a rapid surge in activity after waking and sustained levels throughout the day, suggesting a potentially healthier approach to aging. These findings align with previous studies indicating high levels of sedentary behavior in older adults, reinforcing the need for interventions tailored to diversify daily routines and promote physical activity. This study is the first to explore these patterns in the Chilean context, contributing to a more comprehensive understanding of elderly care and informing future strategies for improving the well-being of older adults living alone.

Digital Warfare: Exploring Cyber Criminality Amidst Armed Conflict in Southwest Region of Cameroon

This research investigates the alarming rise of cyber criminality in the Southwest region of Cameroon, a trend significantly influenced by the ongoing armed conflict that has engulfed the area. Employing a doctrinal research methodology, the study conducts a rigorous content analysis of both primary sources such as case law, treaties, legislative texts, direct observations, and policy documents and secondary sources, including scholarly textbooks, journal articles, comprehensive reports, and various online materials. The analysis utilizes diverse legal reasoning methods, including deductive, inductive, and analogical reasoning. Findings reveal a troubling surge in cyber-criminal activities since the onset of the armed conflict in English-speaking Cameroon, driven by interrelated factors such as rampant unemployment, pervasive economic hardship, widespread illiteracy, and the displacement of individuals. In light of these findings, it is crucial for the Cameroonian government to devise and implement effective strategies that not only combat cyber-crime but also address the socio-economic challenges exacerbated by the conflict. Such comprehensive measures are vital for restoring stability and security in the Southwest region and for fostering a resilient society capable of overcoming the dual impacts of cybercrime and armed conflict.

Effect of storage time on antioxidant content in seeds of agricultural plants

This study investigated the impact of storage time on the prooxidant-antioxidant balance (PAB) in seed tissues of 12 agricultural plant species, including both monocots and dicots. We measured superoxide generation, TBA-active products, and the activity of enzymatic antioxidants (superoxide dismutase, catalase, and cytochrome oxidase) and non-enzymatic antioxidants (ascorbic acid and glutathione). Biochemical parameters were recorded monthly for one year. Our results demonstrated that the activity of enzymatic antioxidants and the content of non-enzymatic antioxidants decreased with increased seed storage time. Conversely, both the generation of reactive oxygen species and the level of free radical damage to biomolecules increased. The percentage change in free radical peroxidation and antioxidant protection depended on the initial PAB status of the seeds. Monocots exhibited a greater overall increase in prooxidant activity during storage, while dicots showed a less pronounced decrease in antioxidant content. A notable surge in prooxidant activity and a corresponding decline in antioxidant activity occurred at 9-10 months of storage for dicots and 6-7 months for monocots. These findings highlight the importance of considering storage time and species-specific differences to optimize planting strategies and seed care, as well as the use of appropriate plant foods.

Green momentum? An age-period-cohort analysis of support for the environmental movement in 24 countries

Over the past decade, the climate movement and especially action groups like Fridays for Future have been effective in raising awareness of environmental issues and mobilizing protesters, especially among younger age groups. However, it remains unclear whether this recent surge in activism reflects a broader societal shift or if this trend is primarily driven by younger generations. Using data from 24 countries that participated in waves three and four of the International Social Survey Programme Environment Module, this study employs, for the first time, an Age-Period-Cohort (APC) analysis of environmental Public-Sphere Behavior in an international comparative context. Based on Bayesian negative binominal multilevel models, the results provide empirical evidence for a period effect: PSB have indeed increased across generational cohorts and age groups.

Active dosimetry for VHEE FLASH radiotherapy using beam profile monitors and charge measurements

The discovery of the FLASH effect has revealed a high potential for treating cancer more efficiently by sparing healthy tissue. The surge in related medical research activities over the last couple of years has triggered a demand for technology with the capability of generating and measuring ionizing radiation at ultra-high dose-rates (UHDR). A reliable dosimetry system is an integral part of a radiotherapy machine. Because existing active dosimetry methods are unable to handle the dose-rates required for FLASH, UHDR dosimetry has emerged as an important area of research. In this paper we present an active dosimetry method based on a scintillating screen and an integrating current transformer. This method provides a simultaneous measurement of the absolute dose delivery as well as the 2D dose distribution. The measurements have been correlated with corresponding readings from radiochromic films (RCFs), and a procedure for image processing has been established. Moreover, different methods of calibrating the active dosimetry system against RCFs have been introduced and evaluated. Lastly, we present results which demonstrate that an agreement with RCFs of better than 5% can be realistically expected if camera parameters are carefully optimized.

Recognition of Malicious URLs Using Machine Learning

The surge in online activities has heightened the risk of cyber-attacks, with phishing emerging as a notably widespread threat. Conventional phishing detection methods, such as blacklists and heuristic analysis, fall short when it comes to identifying novel and complex phishing schemes. To tackle this issue, we propose a machine learning-based solution for detecting phishing websites. Our model utilizes a combination of features—such as URL structure, domain attributes, and content characteristics—to categorize websites as either phishing or legitimate. The model's outstanding overall accuracy of 96.9% underscores the need to evaluate both precision and recall when determining the effectiveness of machine learning models. The results of this study are significant for developing robust URL classification models and advancing the field of cybersecurity. Future research could aim to improve the model's performance by integrating more features, developing real-time phishing detection systems, and exploring new attributes that can be derived from URLs. Keywords: Phishing, URL, Machine Learning, Classification, Detection

Low acaricide resistance levels in citrus orchards field populations of the invasive spider mite Eutetranychus orientalis (Acari: Tetranychidae) collected from southern Türkiye

The citrus brown mite Eutetranychus orientalis (Klein), is known as one of the most significant pests in citrus growing areas worldwide. It has recently caused outbreaks in the Mediterranean region of Türkiye. This study aimed to determine the resistance levels of E. orientalis populations between 2020 and 2021 collected from 9 commercial citrus orchards in Adana province against 5 different acaricides, in order to determine whether the observed population outbreak was due to acaricide resistance. The resistance ratios were changed between 1.67 and 2.50, 1.00–2.53, 1.85–3.68, 1.30–2.65, and 1.93–3.13-fold for abamectin, etoxazole, fenbutatin oxide, pyridaben, and spirodiclofen, respectively. The enzyme activity levels of carboxylesterase, glutathione S-transferase, and cytochrome P450 monooxygenase ranged between 1.00 and 1.13, 1.02–1.52, and 0.94–1.72-fold, respectively. As a result of the resistance study carried out for the first time on this species in Türkiye, the resistance ratios were determined to be low for E. orientalis against acaricides. Although the current resistance rates were low, certain populations exhibited a noteworthy surge in enzyme activities when compared to the susceptible population. Based on these findings, it was concluded that by implementing an appropriate resistance management strategy using acaricides with different modes of action, it is possible to prevent potential resistance development and use these acaricides effectively on this spider mite species for many years through rotation.

Identifikasi Fungsi dan Kriteria Estetika Taman Kota Pasif di Kota Semarang

As population and human activity surge, Green Open Space (RTH) in cities is increasingly being pushed, changing its function to housing and infrastructure. In fact, green open space and city governance play an important role in creating comfortable housing. Urbanparks, as a type of green open space, come in two types: active and passive. In Semarang, the construction of passive urban parks is being promoted. This research identifies the functions and aesthetic criteria of passive urban parks in Semarang. A qualitative descriptive method with triangulation of theory, sources and methods is used to analyze the data. The research results show that passive urban parks in Semarang have aesthetic functions, specifically: beautifying the visual environment and supporting city planning; Increase productivity, creativity and architectural beauty; and displaying regional characteristics through monuments or directional signs. Meanwhile, the aesthetic criteria for passive urban parks in Semarang include: unity and consistency of design elements; balance between garden elements; variations in plant height and color; selection of contrasting plant colors; repetition of elements or patterns; beautiful garden shape; strategic location in the middle of the city, main roads or road islands. It is hoped that these findings can be a guide in developing passive urban parks in Semarang so that they suit their intended purpose and maximize their benefits for the community.

Analyzing COVID-19 Sentiments on Twitter: An Effective Machine Learning Approach

The COVID-19 pandemic has brought about a surge in online discussions and social media activity, making it crucial to analyze public sentiment towards the virus and related topics. This thesis focuses on Sentiment Analysis of COVID-19 data on Twitter, employing Multinomial Logistic Regression as the primary classification algorithm. This research explores Sentiment Analysis of COVID-19 data on Twitter using Multinomial Logistic Regression. It constructs a tweet dataset reflecting various sentiments—positive, negative, and neutral. The data undergoes preprocessing, and a Sentiment Analysis model is built, with 70% of data for training and 30% for testing. The model uses Count-Vectorizer, Tf-idf for feature extraction, and Multinomial Logistic Regression to classify tweets. The study achieves state-of-the-art results with a high accuracy of 95.14%, demonstrating the effectiveness of this approach. The results offer valuable insights into public sentiment during crises, aiding in decision-making and communication strategies.