bluuebunny/crossref_metadata_2025 huggingface dataset:
Two Factor Authentication and Synchronization of Financial Data Module between Bank and ODOO ERP Involving APIS
Authors: S. Vignesh  , R.Mahalakshmi
Published: May 2024

In this project, we aim to bolster security and streamline functionality through two key features: two-factor authentication (2FA) using the 32-bit algorithm and financial data synchronization via API integration to Odoo ERP by implementing two key features: two-factor authentication (2FA) using the 32-bit algorithm and financial data synchronization via API integration to Odoo ERP. The implementation of 2FA introduces an additional layer of security to Odoo's login processes. By leveraging the 32-bit algorithm, users will generate one-time passwords (OTPs) throughout authentication processes, significantly reducing the risk of unauthorized access and enhancing overall system security. Simultaneously, we will integrate API endpoints for one-time passwords (OTPs) throughout authentication processes, significantly reducing the risk of unauthorized access and enhancing overall system security. Subsequently, we will integrate API endpoints for one-time passwords (OTPs) throughout authentication processes, significantly reducing the risk of unauthorized access and enhancing overall system security. This synchronization ensures the accuracy and consistency of financial information, enabling real-time decision-making and improving operational efficiency.
Our methodology involves carefully selecting and implementing the 32-bit algorithm for OTP generation, ensuring robustness and efficiency in Odoo ERP's security framework. Additionally, we will develop user-friendly interfaces for financial data synchronization, facilitating seamless communication between Odoo ERP and external systems. This synchronization guarantees the accuracy and consistency of financial information, empowering stakeholders with timely insights and facilitating informed decision-making.
Integration of Secured Authentication Mechanisms to Ensure Integrity of User Identities and Assessment Data for Online Quiz Design System
Authors: R. Mohanraj  , Dr. C. Meenakshi
Published: May 2024

The integration of secure authentication mechanisms ensures the integrity of user identities and assessment data for online quiz design system is an innovative digital solution designed to revolutionize the landscape of online assessments across various educational and professional sectors. With a primary objective to provide a seamless and engaging experience, the platform incorporates a myriad of cutting-edge features. User experience takes center stage, ensuring effortless navigation through quiz creation, participation, and result analysis. Leveraging advanced algorithms and seamless data integration, the system delivers real-time updates on quiz availability and performance metrics, empowering users to make informed decisions swiftly. Robust quiz management tools cater to the needs of both quiz creators and participants, facilitating everything from quiz creation to result dissemination. The integration of secure authentication mechanisms ensures the integrity of user identities and assessment data, fostering trust and reliability. Proactive notifications keep users engaged and informed throughout the quiz-taking process, while a feedback and ratings system promotes transparency and accountability within the online assessment ecosystem. Together, these features converge to create an unparalleled platform that offers convenience, efficiency, flexibility, and growth opportunities, thereby redefining the standards of excellence in online assessments and shaping the future of learning and evaluation.
Web-Based Agricultural Machinery Rental Business Management System
Authors: Navinkumar  , Dr. S. Nagasundaram
Published: May 2024

Nowadays there are many online services which are on trend that give much benefit to user. This application named as tractor hiring application for farmers is a rental service in which the farmer arrives to request a hire of a rental unit. It is more convenient than carrying the cost of owning and maintaining the unit. There are several problems occur on farmer like they are not able to hire a tractor and equipment of agriculture for farming in nominal amount or they do not find tractor easily. In another case, sometimes farmers are unaware about the price of the tractor and other agricultural equipment; such that tractor owner misguide the farmers very easily and cheat them by taking extra money. The solution for solving such various problems occur on farmers regarding to agriculture can be overcome using this application. Therefore with this new method the process will me more efficient and safety of hiring tractor as well as equipment is secure. It is also the best way to increase the quality of agriculture management, productivity and can reduce the time constraints for farmers.
Data Embedding with Reversible Encoding
Authors: D. Surendhar  , R. Mahalakshmi
Published: May 2024

Data Embedding with Reversible Encoding (DERE) has been introduced for preserving image privacy and data embedding. DERE usually involves three parties, namely, the image provider, data hider, and receiver. On the security with key setting, there are three categories: share independent secret keys (SIK), shared one key (SOK), and share no secret keys (SNK). In SIK, the image provider and data hider must respectively and independently share secret keys with the receiver, whereas in SNK, no secret key is shared. However, the literature works proposed SNK-type schemes by using homomorphic encryption (with exorbitant computation cost). In this paper, we address the SOK setting, where only the image provider shares a secret key with the receiver, and the data hider can embed a secret message without any knowledge of this key. To realize our SOK scheme in a simple manner, we propose a new technique by using multi-secret sharing as the underlying encryption, which indeed induces a blow-up issue of the key size. For preserving the efficiency of the key size, we apply a compression by using lightweight cryptographic algorithms. Then, we demonstrate our SOK scheme based on the proposed techniques, and show effectiveness, efficiency, and security by experiments and analysis. We address shared one key (SOK) setting, where only the image provider shares a secret key with the receiver, and the data hider can embed a secret message without any knowledge of this key.
Evaluation of Fire Protection Systems in Multiple Use High-rise Buildings for Fire Safety Optimization
Authors: Pravin Tathod  , Kamlesh Mishra
Published: May 2024

Among the several types of occupancies, a multiple use Highrise building presents a more challenge to fire protection due to its functionality, complexity and financial value. The key objective of the present paper was to examine the situation of physical (as opposed to non-physical) fire protection systems in fourteen randomly selected commercial high-rise buildings in the Indore city for fire safety optimization. Methods used include; physical observations, document review and interviews. A multi- attribute evaluation model/approach was applied to establish sufficiency and/or suitability of fire protection systems in the light of the national regulations and approved standards. The study findings show that, save for the facilities of the disabled and the firefighting/evacuation lifts, other fire protection systems are mainly provided in the buildings. However, insufficient maintenance and/or unsuitable elements render their safety performance low. The results of the analysis showed that portable fire extinguishers had the highest performance with 77.57% of the buildings sufficiently and suitably in terms of number, locations, servicing etc., while few % of the building was sufficiently and/or suitably installed with a sprinkler system i.e. they all exhibited some deficiency in terms of coverage and maintenance issues. This could be associated with the cost factor. The results of other systems were as follows: Fire detection and alarm (14.29%); Escape route (50%); Emergency lighting (64.29%); Smoke control System (50.00%); Compartmentation (64.29%), Riser mains, hose reels and hydrants (64.29%); Fire Brigade access and facilities (64.29%); Safety signs and notices (7.14%); Portable fire extinguishers and Fire assembly points (28.57%). In view of the findings, it’s recommended that increased efforts in inspection and maintenance of fire protection systems are considered to address the identified shortfalls throughout the project life. Provision for firefighting/evacuation lifts and facilities for the disabled persons should be considered during design of the commercial high-rise buildings.
Formulation and Evaluation Herbal Soap
Authors: Mr. Rushikesh B. Shendage  , Mr. Pramod B. Chikkodi
Published: May 2024

This study presents the formulation and benefits of an herbal soap riched with extracts from mango, teak, almond, and neem leaves. These ingredients were selected for their well-functioning, antimicrobial, antioxidant, and skin-nourishing properties. Mango leaves are contributing to skin protection and healing. Teak leaves are known for their antibacterial and anti-inflammatory effects. Almond leaves are for moisturizing benefits, while neem leaves are for antiseptic and antifungal properties. The combination of these extracts creates a soap Skin health, promoting a clear, hydrated, skin
Study on Leachate Management and Design of Experimental Setup for Treatment of Leachate using Bio-absorbent
Authors: Manohar P  , Ganesh H  , V Aun Kumar  , Mallikarjuna T  , Ashok Kumar V  , Kavya K
Published: May 2024

The management of leachate, a complex and environmentally hazardous effluent generated from solid waste landfill sites, poses significant challenges to environmental engineers and policymakers worldwide. In this study, we present a comprehensive investigation into leachate management strategies with a focus on the design and implementation of an experimental setup for its treatment by using the method of Treatment unit Initially, we conducted a thorough review of existing literature to understand the composition, characteristics, and environmental impact of leachate. This literature review informed the development of effective treatment strategies targeting key contaminants such as heavy metals, organic pollutants, and pathogens present in leachate. Subsequently, we designed and constructed an experimental treatment setup tailored to address the specific challenges associated with leachate treatment. The experimental setup integrates various treatment processes including physical, chemical, and biological methods to achieve comprehensive removal of contaminants.
To evaluate the efficacy of the experimental setup, we conducted a series of laboratory-scale experiments using synthetic leachate samples. The sample treated by MSV LABORATORY such Parameters are turbidity, biological oxygen demand (BOD), NPK, heavy metal concentrations throughout the treatment process.
Preliminary results indicate promising outcomes in terms of contaminant removal and it is found that promising results are seen with peanut shell as the bio-absorbent, with significant reductions observed in BOD 2050 mg/l (from 7301mg/l), and heavy metal (Lead as Pb 0.11 mg/l), (Cadmium as Cd 0.2mg/l), Turbidity (49 mg/l) is concentrations. Additionally, microbial analysis revealed a substantial reduction in pathogenic microorganisms following treatment. In conclusion, this study contributes to the advancement of leachate management practices by offering insights into effective treatment strategies and the design of experimental setups for practical implementation. The sample treated to yield the best results in peanut shell bio absorbent is now being utilized in irrigation fields and gardening applications.
Evaluating Health Services and Operations among Barangay Health Offices: Basis for Document Digitalization with Text Classification Algorithm and Machine Learning
Authors: Jaspergen D. Dahilan  , Riah E. Encarnacion
Published: May 2024

Barangay Health Offices (BHOs) plays an important role in delivering primary healthcare services to local communities. However, many of its operations still rely on outdated manual systems for document reporting and analysis. The process of digitalizing document reporting and analysis presents an opportunity to streamline processes, enhance efficiency, accuracy, and accessibility of health-related information, and enable better data-driven decision-making at the barangay level. It is for this reason that the researchers intend to address the problem within the Barangay Health Offices (BHOs) of Surigao City. By analyzing the needs of the 20 female BHO workers and utilizing a mixed-methods approach, various aspects of health service provision and operational transactions were evaluated. The findings revealed positive perceptions among respondents, particularly in Health Services Provision (WM = 4.2), resource availability (WM = 3.85), data security (WM = 3.05), and infrastructure (WM = 2.53). However, infrastructure challenges such as internet speed and computer availability were highlighted as areas needing improvement. Data security measures were also identified as requiring enhancement through encryption and regular audits. The survey results will be essential in creating the proposed digitalization framework aimed at enhancing the efficiency, accuracy, and accessibility of health-related information using text classification algorithm and machine learning. This research exploration hasalso contributed valuable insights for policymakers and health administrators seeking to optimize health services provision at the grassroots level. The proposed digitalization framework will be a pathway towards improved healthcare delivery and operational effectiveness
Depression Detection by Analyzing Social Media Post of User: A Review
Authors: Aditya Ghodke  , Sahil Kadam  , Shubhum Jadhav  , Parikshit Jadhav  , Aditi Bhosale
Published: May 2024

Today, the problem of early diagnosis of depression is one of the most important problems in psychology. Mental health problems are often one of the most important health problems in the world, with depression alone currently affecting more than 300 million people. As social media platforms create more male or female user accounts, researchers are increasingly using evidence-based data to determine whether content can be used to spread mental health issues in users. Scientists around the world say that depression is a disease that causes serious problems in our lives and is still a cause for concern. With the advent of all-inclusive devices such as smartphones, predicting depression remains an open question. Social testing is often used to solve this problem. This paper aims to use a depression assessment and suicidal ideation detection system to predict the level of depression supporting suicidal behavior. The purpose of this system is to provide the best tools to understand the process by which a man or woman is depicted through words as being in a relationship that may be disturbing. For this purpose, experts and productive people are used to determine whether the person is depressed or not by using their ability to do physical work at work. They were trained to use similar equipment and divided into different levels of depression on a scale of 0-100%. It also collects the logs in the report and sorts them by whether it's the best tweet you've ever sent. Whether you suffer from depression or not, using cutting- edge technology is a method for early detection of depression or mental illness. The main purpose of this evaluation is to investigate relevant resources and their impact on determining depression levels. The aim of this review is to understand the criteria used to classify people with depression by looking at some of the cases discovered by postgraduate studies examining the education of men and women. With the ability to combine all tag groups, you can create periodic reports that can be used to identify customers suffering from depression. This article shows that there is variability in reporting patterns between depressed and non- depressed individuals, as evidenced by the association of reporting groups. This study used cognitive tools to create data collected from consumer social media posts. Natural Language Processing (NLP) has been classified using the BERT code set to represent depression in a simpler and more understandable way
Varietal Classification of Selected Green Coffee Beans (Coffea arabica L. and Coffea canephora Pierre ex A.Froehner) Using Image Processing Software
Authors:   University of the Philippines Los Baños, Lumagui Katrina Nicole , Manuel Luther John , Quilloy Erwin , Yaptenco Kevin
Published: May 2024

The study created a classification model that sorts green coffee beans based on its variety, primarily ‘Arabica’ and ‘Robusta’ to address coffee adulteration. A total of 1500 green coffee beans were obtained from Cavite, Philippines, allotting 70% and 30% of it for training and testing dataset, respectively. These were then captured through the fabricated image acquisition setup. Image processing techniques were performed to extract the features of the beans namely color, size, shape, and crack using ImageJ software. Fourier analysis was mainly performed for the extraction of the bean shape information. After performing t-test, 3, 4, and 7 parameters of color, size, and shape features were found to be significant, respectively. The 14 features were used in creating 7 classifications setups of different feature combinations through discriminant analysis. The model that yielded the highest accuracy (99%) is the combination of color and size features. This exceeded the subjective varietal classification accuracy (98%) performed by a coffee expert. Thus, the variety of green coffee beans were feasibly classified through image analysis and the created model had surpassed the traditional performance of sorting green coffee beans.
Impact of Perceived Usefulness on ICT Adoption by SMEs Bread Baking Industry in Zamfara State
Authors: Sabur HASSAN, Abdul , Benson Ikebuaso
Published: May 2024

The study explore the relationship between perceived usefulness on ICT adoption of SMEs bakery firms in Zamfara State. The objective is to assess the impact of perceived usefulness on ICT adoption by SMEs bread baking industry. The study was anchored on Technology Acceptance Model (TAM) theory. The study used a quantitative and survey research design. The dependent variable is SMEs ICT adoption while the independent variable is Perceived Usefulness (improved job performance, Enhanced job effectiveness and Enhanced productivity). This study used a saturated sample, from 95 questionnaires collected, the data obtained were then analyzed using SEM (Structural Equation Modeling) PLS-4. The results showed that there is a significant positive relationship between SMEs ICT adoption and enhancement of job effectiveness in bread baking industry in Zamfara state. Equally there is a significant positive relationship between SMEs ICT adoption and enhanced firm Productivity of bread baking industry in Zamfara state. Further more the findings shows that there is a significant positive relationship between SMEs ICT adoption and Improved Performance of bread baking industry in Zamfara state. Therefore the study concludes that technology utilization promotes job effectiveness, firm Productivity and Improved Performance in the business and these can enhanced competitive advantage in the market. The study recommends that bread baking industry should key into the ICT adoption behavior, firms that are yet to adopt modern technology in their production processes should do so. And bread baking firms that have adopted this modern technology should ensure periodic up-grade and review their level of utilization in meeting market demand.
Psikolojik Esneklik Ölçeği Türkçe Formu: Geçerlik ve Güvenirlik Çalışması
Authors: Çakır Yasemin , Balcı Çelik Seher
Published: May 2024

Bu çalışmanın amacı Ben-Itzhak, Bluvstein ve Maor (2014) tarafından geliştirilen Psikolojik Esneklik Ölçeği’nin Türkçeye uyarlanmasıdır. Araştırmaya 2021-2022 eğitim-öğretim yılında üniversite 1., 2., 3. ve 4. Sınıf düzeyinde öğrenim görmekte olan toplam 337 üniversite öğrencisi katılmıştır. Katılımcıların 204’ü kadın; 133’ü erkektir. Psikolojik Esneklik Ölçeği’nin orijinal ölçek formunda olduğu gibi beş faktörlü modeli “Olumlu Değişim Algısı”, “Kendini Esnek Biri Olarak Görme”, “Kendini Açık ve Yenilikçi Biri Olarak Görme”, “Dinamik ve Değişen Bir Gerçeklik Algısı” ve Çok Yönlü Bir Gerçeklik Algısı” sergileyip sergilemediğini tespit edebilmek amacı ile doğrulayıcı faktör analizi yapılmıştır. DFA sonucuna göre program tarafından üretilen değişiklik önerileri incelenmiştir. Aynı alt ölçekte yer alan maddeler incelenerek benzer içeriğe sahip olan maddelere dair hata kovaryansları önerilen biçimde modele eklenerek analizler tekrar yapılmıştır. Ayrıca aynı anda birden fazla faktöre yüklenerek ölçeğin faktör yapısı üzerinde olumsuz etkide bulunan maddeler ölçek formundan çıkarılmıştır. Psikolojik Esneklik Ölçeği’nin ölçüt geçerliğini tespit edebilmek amacıyla Kabul ve Eylem Formu II Ölçeği ile arasındaki korelasyona bakılmıştır. Korelasyon analizleri sonucunda ulaşılan değerler de ölçek formunun uyum geçerliğinin sağlandığını ortaya koymaktadır. Ölçeğin güvenirliği Cronbach alfa iç tutarlılık katsayısı ve test tekrar yöntemleri ile analiz edilmiştir. Araştırma bulguları psikolojik esneklik ölçeğinin geçerli ve güvenilir bir ölçme aracı olduğunu göstermektedir.
Um Exu do Brasil
Authors: Kalunga José da , Angola João de
Published: May 2024

ste livro conta a história de uma entidade trabalhadora da luz e transcreve sua história desde o período em que estava imersa em ilusões, até se tornar o ser que é hoje: um Exu. Uma história emocionante de um filho de Deus que havia se perdido e que conheceu a verdade na energia mais pura, o amor incondicional. Se reencontrando e também o caminho para a casa do Pai Maior. A cada capítulo, a narrativa detalha aspectos de sua vida e também a relação do personagem principal com outras entidades da Umbanda, principalmente as entidades da esquerda, destacando a seriedade, a força e a luz de seus trabalhos, desfazendo preconceitos antigos difusos no imaginário popular. Você, caro irmão ou irmã aprendiz do amor fraterno, fique atento aos sábios ensinamentos ofertados neste livro e faça uma boa viagem evolutiva!
ANÁLISE MICROBIOLÓGICA COMPARATIVA DAS FASES PRÉ E PÓS-PROCESSAMENTOS INDUSTRIAIS DE AMÊNDOAS DE CACAU
Authors: Santos Carolina Souza Almeida , Andrade Mariana Moreira
Published: May 2024

O cacau é um fruto muito antigo que é proveniente do cacaueiro. Suas sementes são ricas em muitas propriedades como lipídeos, proteínas, amido e células polifenólicas, se tornando importantes para o consumo, logo que possuem conteúdo anti-inflamatório e antioxidante atuando em diversos tipos de doenças como câncer e doenças cardiovasculares. Esse fruto é muito utilizado para a produção de vários produtos como o chocolate, manteiga de cacau, liquor de cacau e entre outros. Apesar de seus benefícios, quando fabricados podem ser sujeitos a contaminação que podem levar a diversos prejuízos como econômicos e a saúde da população. Portanto, o objetivo desse trabalho é analisar microbiologicamente as amêndoas de cacau antes e após o processamento na indústria, afim de averiguar se ocorreu a sua esterilização de forma correta, e para essas análises serão comparados os resultados para psicotróficos aeróbios e mofo, bolores e leveduras. Seus resultados serão computados através do método de Contagem Padrão em Placas (UFC/g) de acordo com a ANVISA.
Towards semantic enrichment of Earth Observation data: The LEODS framework
Authors: Milon-Flores Daniela F. , Bernard Camille , Gensel Jérôme , Giuliani Gregory , Chatenoux Bruno , Dao Hy
Published: May 2024

Abstract. The Earth’s ecosystem is facing serious threats due to the depletion of natural resources and environmental pollution. To promote sustainable practices and formulate effective policies that address these issues, both experts and non-expert stakeholders require access to meaningful Open Data. Current Earth monitoring programs provide a large volume of open Earth Observation (EO) data typically organized and managed in EO Data Cubes (EODCs). From these datasets, satellite-derived indices can be calculated for assessing various environmental aspects in areas of interest over time. However, current EOs lack semantics and are isolated from significant Web resources, greatly hindering their comprehension and limiting their use to specialized users. To enhance EO data with semantic richness and ensure their understanding by a wider audience, it is pertinent to adopt a Linked Open Data (LOD) approach. In this paper, we present the Linked Earth Observation Data Series (LEODS) framework designed to publish aggregated EO data in the LOD Cloud. LEODS provides a processing chain that converts EO data into EO-RDF data cubes based on a spatio-temporal modeling approach that ensures integration and future semantic enrichment of EO data while preserving the advantages of traditional EODCs and following the FAIR principles (i.e., findable, accessible, interoperable, and reusable). To highlight the advantages of our proposal, we explore through SPARQL queries and visualizations, the results of implementing LEODS with study areas located in Switzerland and France.
Construction of a walkability quality dataset in GIS: the case study of Berlin
Authors: Gaglione Federica
Published: May 2024

Abstract. This work aims to define and build a pedestrian network database by exploiting the information and potential of Google Street View. Compared to existing data such as Open Street Map, this dataset offers more detailed information on the quality of the street from a walker's point of view, also including urban context and safety characteristics in addition to those related to the geometry of a route. The research work is experimentation on the Berlin case study. The construction of the database allows, in turn, to obtain thematic maps of network classification as a result, providing a first element for local decision makers on where to implement possible improving solutions.
A methodological inquiry for anchoring pan-scalar maps
Authors: Gruget Maïeul , Touya Guillaume , Potié Quentin , Muehlenhaus Ian
Published: May 2024

Abstract. This paper reports two experiments for the design of anchored pan-scalar maps. Anchoring pan-scalar maps means improving the saliency and memorability of some cartographic elements, i.e. the pan-scalar anchors, to enhance the navigational cues that can be used for self-localization during or after a zoom in a map. Within this article, concrete examples illustrate the process of adding anchors at different locations in the map, or how map designers can extend the scale range where anchors are salient. The paper concludes by highlighting the practical implications of this research for mapping professionals, offering a clear path for the creation of more effective anchored pan-scalar maps.
Constructing Spatio-temporal Disaster Knowledge Graph from Social Media
Authors: Liu Yen-Ching , Kuo Chiao-Ling
Published: May 2024

Abstract. Social media enables the disclosure of real-time crowd situations and provides high accessibility to the public. Thus, social media has emerged as a promising resource for discovering and managing disasters. This study aims to realize an effective process of constructing a spatio-temporal disaster knowledge graph (ST-DKG) from social media for disaster semantic interpretation and achieving an effective solution for disaster management. ST-DKG is constructed using PTT, one of Taiwan’s most popular social network platforms, and natural language processing with artificial intelligence (AI) models based on Bidirectional Encoder Representations from Transformers (BERT). ST-DKG addresses issues such as ellipsis and coreference resolution, entity recognition, relation extraction, and the identification of subject-predicate-object triples. Our method not only enhances the access efficiency and interoperability of social awareness information, but also provides bottom-up spatio-temporal disaster relevant knowledge for disaster management.
Smoothing the Ride: A Surface Roughness-Centric Approach to Bicycle Routing
Authors: Löw Pablo S. , Krisp Jukka M.
Published: May 2024

Abstract. This study addresses the impact of surface roughness on bicycle route planning, emphasizing the combination of vertical acceleration and speed. The approach introduces an index derived from surface roughness that is used as an impedance in existing routing algorithms. The study evaluates bike routes based on real and modified edge lengths, revealing differences in surface roughness. Challenges, including bike variability and accelerometer limitations, are discussed. The method effectively captures regions with higher surface roughness, offering valuable information for bike route planning. Its reliance on smartphone accelerometer data makes a step towards widespread applicability.
DGGSTools: An Open Source Python Package for the Manipulation of Vector and Raster Datasets in the rHEALPix Discrete Global Grid System
Authors: Martin-Segura Sergio , Béjar Rubén , Zarazaga-Soria F. Javier
Published: May 2024

Abstract. DGGSTools is a Python package and command-line application to process geospatial datasets within the spatial reference provided by the rHEALPix Discrete Global Grid System (DGGS). Its main objective is to provide the tools necessary to transform geospatial datasets to equivalent ones following the rHEALPix DGGS, and to allow its users to work with both raster and vector versions of those datasets as preferred. Once these equivalent datasets have been produced with DGGSTools, the users can obtain the benefits of working with a DGGS, intended to facilitate the efficient integration and retrieval of heterogenous global data, while using their preferred GIS tools and workflows for the analysis of those datasets. This short paper describes the main characteristics of the first public version of DGGSTools. Although a small part of its code had already been used in some geospatial research experiments, this is the first version which is publicly available. It includes a good,number of automatic tests, it is properly packaged as a Python wheel to facilitate its installation, and offers a command-line application so the package can be used without writing a single line of code.
Artificial intelligence for greater transparency in housing price estimation
Authors: Mueller-Kett Christian
Published: May 2024

Abstract. This paper investigates the use of machine learning (ML) models to predict housing prices. A well-performing housing price model was trained, which can seamlessly be integrated into public sector processes to increase market transparency and is based on modern ML and feature engineering methods. For these models, particular consideration was given to the spatial component. The research uses the Design Science Research approach, with a case study carried out in the city of Duisburg, Germany. The ML models developed showed better performance than traditional models. The models were embedded in official processes using Shapley values to increase interpretability. The study concludes that ML models can contribute to increased market transparency in the real estate sector.
Assessment of bicycle accessibility to mobility hubs under different criteria for cycling network quality
Authors: van der Meer Lucas , Werner Christian , Loidl Martin
Published: May 2024

Abstract. The criteria used to delineate the cycling network have large implications on computed levels of bicycle accessibility to mobility hubs. We present an approach to bicycle accessibility assessment that gives insights into these implications. First, we compute a bicycle suitability index for each street segment in the proximity of a hub. Then, we compute how many households have access to the hub using only streets with a bicycle suitability above a given index threshold, while not accepting a detour from the shortest path beyond a given detour threshold. We repeat this for different combinations of threshold values that reflect varying quality standards for the cycling network. The results are presented by means of graphs and maps that show how computed levels of bicycle accessibility vary under different criteria.
Knowledge-Based Identification of Urban Green Spaces: Allotments
Authors: Ismayilova Irada , Timpf Sabine
Published: May 2024

Abstract. Urban Green Spaces (UGS) play a crucial role in enhancing the quality of life in cities by providing numerous environmental, social, and health benefits. Among these green spaces, allotment gardens stand out as a unique type that contributes to ecological services, preservation of biodiversity, and the overall well-being of urban dwellers. Unfortunately, the significance of allotment gardens as a specific type of UGS is still disregarded and they are not recognized as a separate category in land use / land cover maps or city maps of green spaces. This is mainly due to the mixed use of allotment areas, their small size and absence of tailored identification or mapping workflows. In this research, we address the latter one by proposing an approach that utilizes various semantic characteristics of allotment gardens to create distinctive spatial representations. The semantic characteristics we consider include the presence, density, and height of garden huts, proximity to water bodies and railroads, as well as the presence of pathways within the allotment gardens. Allotments are delineated using a three-step procedure. This involves utilizing a Random Forest machine learning classifier to create maps of the distribution of green spaces, extracting garden huts employing a threshold, and demarcating the area using a density based clustering technique. Furthermore, we repeat the same workflow in a new study area to assess the applicability of the proposed workflow. With the established workflow, we are able to accurately identify 78% of allotments in Augsburg and 88% in Wuerzburg respectively. Our results demonstrate that the proposed workflow can be a useful approach to validate and extend existing land use and land cover data sets while remaining time and cost effective.
A regional analysis of paraglacial landslide activation in southern coastal Alaska
Authors: Walden Jane , Jacquemart Mylène , Higman Bretwood , Hugonnet Romain , Manconi Andrea , Farinotti Daniel
Published: May 2024

Abstract. Glaciers worldwide are retreating rapidly due to anthropogenic climate change. One consequence of glacier mass loss is the destabilization of valley walls as the support provided by the glacier changes and eventually vanishes, a process known as ''debuttressing.'' In this work, we examine the evolution of eight large, active instabilities in southern coastal Alaska, a region experiencing some of the fastest glacier retreat worldwide. At half of the sites, the glacier is still in contact with the landslide, while in the other four cases, the terminus retreated past the landslide in recent decades. One site has experienced catastrophic failure; the others have not. We use automatic and manual feature tracking on optical imagery to derive slope movement from the 1980s to present and compare this with glacier terminus retreat and thinning, precipitation, and seismic energy. We find that the majority of sites underwent a pulse of accelerated landslide motion (up to 17 times higher compared to the five years preceding the acceleration) during the studied time period and that the subsequent deformation was independent of the initial activation. In two cases, the acceleration occurred after a particularly rainy month and/or a marked increase (around two times higher than the 1960–2000 average) in glacier thinning. At two further sites, no distinct activation could be detected, though both landslides are known to be moving at velocities below the detection threshold of the methods employed here. In four cases, landslide activation coincided with the rapid retreat (up to 12 times the long term average) of a lake- or marine- terminating glacier past the instability. Our results suggest that landslides adjacent to lake- or marine- terminating glaciers may be especially susceptible to sudden activation, which we hypothesize is due to the faster retreat rates of water-terminating glaciers as well as mechanical and hydrological changes resulting from the replacement of ice with water at the landslide toe. This work shows that glacier retreat can be associated with increasing landslide hazards in various glaciological settings in Alaska, which has implications for the assessment of hazards in a warming world.
A Unified System for Evaluating, Ranking and Clustering in Diverse Scientific Domains
Authors: Hu Zengyun , Chen Xi , Chen Deliang , Zhang Zhuo , Zhou Qiming , Li Qingxiang
Published: May 2024

Abstract. Evaluating, ranking, and clustering (ERC) stand as fundamental tasks in scientific research, each requiring a mathematical foundation. This study presents an ERC system anchored in the CCHZ-DISO (Chen, Chen, Hu, and Zhou-Distance between Indices of Simulation and Observation) system. Previous research underscores the optimality achieved by the CCHZ-DISO system (Hu et al., 2022). Since the inception of CCHZ- DISO-series research by Hu et al. (2019), DISO has found extensive applications across various domains including geography, hydrology, and economics. Analogous to the CCHZ-DISO system's construction, the ERC system employs the Euclidean distance to perform evaluating, ranking, and clustering tasks. Furthermore, illustrative examples are provided to elucidate the application of the ERC system. In fact, the ERC system unified the evaluating, ranking, and clustering tasks in one simple equation which is more flexible and simpler than the present system. It will have a more widely application than CCHZ-DISO in diverse scientific domains.
Neonikotinoid İnsektisitlerin Bombus (Bombus terrestris L.) Arısı Bireylerinde Hafıza ve Öğrenme Davranışına Etkisi
Authors: Buluş İsmail Yaşhan , Gösterit Ayhan , Timuroğlu Selcan
Published: May 2024

Gerek polinasyon amacıyla tarımsal üretimde kullanıldığında gerekse doğal yaşam alanlarında çeşitli insektisitlere farklı şekil ve düzeyde maruz kalan arılar beslenme reflekslerini, yön bulma becerilerini kaybedebilir vehatta ölebilirler. İnsektisitlerden neonikotinoid grubunda yer alan Acetamiprid etken maddeli insektisitler tıpkı diğer neonikotinoler gibi arıların yön bulma, öğrenme ve hafıza becerilerini olumsuz etkilemektedir. Bombus terrestris koloni bireyleri (ana, işçi ve erkek arı) koloni yaşam döngüsünün belirli dönemlerinde besin toplama veya çiftleşme gibi farklı amaçlar için koloniden ayrılmakta ve insektisitlere maruz kalabilmektedir. Bu çalışmada, B. terrestris koloni bireylerinden oluşan 5 grup (Grup 1: Çiftleşmemiş genç ana arı grubu, Grup 2: Çiftleşmiş, diyapoz dönemini tamamlamış, ancak yumurtlamamış ana arı grubu, Grup 3: Çiftleşmiş, diyapoz dönemini tamamlamış ve yumurtlamış ana arı grubu, Grup 4: İşçi arı grubu, Grup 5: Erkek arı grubu) Acetamiprid etken maddeli insektisitin (Hekplan®, HEKTAŞ) tavsiye edilen dozunun 5 farklı oranına (0 (kontrol), 1/1000, 1/100, 1/10, 1/1) maruz bırakılmıştır. İnsektisite maruz kalan arıların öğrenme ve hafıza davranışları klasik koşullandırma yöntemi ile belirlenmiştir. Her maruziyet uygulaması için 20 adet olmak üzere toplam 500 adet (5 grup x 5 doz x 20 arı) ergin birey kullanılmıştır. Sonuçlara göre klasik koşullandırma yöntemi uygulanan 3 ana arı grubundaki bireylerin işçi ve erkek arı gruplarındaki bireylere göre hem daha geç öğrenmeye başladığı hem de daha az sayıda bireyin dil çıkarma davranışı sergilediği belirlenmiştir. Hafıza çalışmalarındaki ölçümler öğrenme çalışmasından sonra 1., 2., 6. ve 12. saatlerde yapılmıştır. İnsektisitten en çok etkilenen grupların ana arı grupları olduğu belirlenmiştir. Sonuçlar, Acetamiprid etken maddeli neonikotinoid insektisitin bombus arısı bireylerinin öğrenme ve hafıza yeteneklerini farklı düzeylerde etkilediğini ortaya koymuştur.
Pengembangan SDM Untuk Meningkatkan Nilai Produk Ikan Jaring Terapung
Authors: Rohendi A , Iskandar Iis , Handayani Nining , Budiarti Tresna , Hidayat Fanny Agustina
Published: May 2024

Pengelolaan sumber daya perikanan di Indonesia menjadi fokus pemerintah, terutama Departemen Kelautan dan Perikanan, untuk mencari strategi yang sesuai. Kabupaten Bandung Barat, khususnya Cililin, merupakan pusat budidaya ikan jaring terapung. Tim dari Program Studi Magister Manajemen Universitas Adhirajasa Reswara Sanjaya berusaha meningkatkan produktivitas dan kesejahteraan peternak melalui pelatihan dan strategi. Dalam penelitian ini, diteliti cara mengembangkan sumber daya manusia untuk meningkatkan nilai tambah produk ikan. Hasil menunjukkan usaha peternakan ikan jaring terapung di Cililin dapat berkembang lebih lanjut dengan strategi yang tepat, berpotensi memberikan manfaat ekonomi bagi masyarakat setempat. Dengan pengembangan yang baik, diharapkan kualitas hidup peternak dan kesejahteraan masyarakat dapat meningkat secara signifikan.
Pengenalan Digital Marketing Bagi Pelaku Usaha UMKM Kelurahan Kebonbaru Kecamatan Kejaksan
Authors: Yusuff Andinna Ananda , Fardhoni Fardhoni , Permana Indra Surya , Herawati Tuti , Nuraeni Iin Indra
Published: May 2024

Perubahan perilaku pemasaran dari konvensional ke digital tidak diimbangi oleh keberadaan pelaku UMKM dalam menggunakan digital marketing, padahal UMKM dipercaya mampu memacu perekonomian Indonesia. Pemanfaatan konsep pemasaran berbasis teknologi digital menjadi harapan bagi UMKM untuk berkembang menjadi pusat kekuatan ekonomi. Media promosi digital marketing diharapkan menjadi pilihan yang efektif bagi pelaku UMKM dalam mengembangkan bisnis dan menjangkau pasar nasional maupun internasional. Media promosi konvensional yang banyak membutuhkan biaya dan jauh lebih rumit, dengan sendirinya, tidak lagi menjadi perhatian utama bagi pelaku UMKM karena adanya digital marketing. Kegiatan ini bertujuan untuk: (1) mengintegrasikan penggunaan media sosial dalam strategi pemasaran UMKM, (2) meningkatkan pemahaman mengenai signifikansi pemasaran digital untuk peningkatan visibilitas produk, dan (3) mendorong inovasi dalam strategi pemasaran guna mencapai segmentasi pasar yang lebih luas. Setelah sesi teori dan praktik dilaksanakan peserta dapat mengetahui platform digital pengembangan bisnis dan membuat serta mengelola akun media sosial untuk keperluan bisnis. Peserta pelatihan membutuhkan adanya kontinuitas dalam pendampingan, setelah kegiatan ini.
PEMETAAN KEBERLANGSUNGAN HIDUP UMKM GUNA OPTIMALISASI BANTUAN KREDIT MENGGUNAKAN ALGORITMA FUZZY C-MEANS
Authors: Dauni Popon , Pratiwi Pratiwi , Prasetio Rizki Tri
Published: May 2024

Dinamika perekonomian Indonesia mengalami kontraksi semenjak pandemi Coronavirus Disease (COVID-19) mulai menyebar awal tahun 2020. Pembatasan sosial dan terbatasnya kegiatan masyarakat serta larangan beroperasinya usaha yang dapat menimbulkan kerumunan menyebabkan melemahnya ekonomi usaha mikro, kecil dan menengah (UMKM) bahkan hingga terancam menutup usahanya. Padahal UMKM merupakan penyumbang produk domestik bruto (PDB) nasional terbesar. Pemerintah melalui kementerian terkait telah meluncurkan berbagai program bantuan guna menyelamatkan UMKM dari krisis permodalan. Dalam upaya optimalisasi program pemerintah, maka diperlukan sebuah kelompok atau tingkatan yang dapat digunakan untuk menentukan prioritas bantuan pemerintah bagi UMKM agar program bantuan tersebut tepat sasaran. Untuk mengelompokan UMKM digunakan teknik data mining yakni, clustering. Partitive clustering digunakan sebagai pendekatan karena dinilai cocok dengan masalah yang dihadapi karena dapat mengelompokan berdasarkan kemiripan atau kedekatan antar data, sesuai dengan tujuan untuk mengelompokan UMKM berdasarkan kesamaan kondisi yang saat ini sedang dihadapi. Algoritma partitive clustering akan digunakan pada penelitian ini yakni algoritma fuzzy-c-means. Metode penelitian yang digunakan adalah cross industry standard process for data mining (CRISP-DM) yang merupakan standar model penelitian lintas industri untuk pemrosesan data yang memiliki enam tahapan penelitian diantaranya, pemahaman bisnis, pemahaman, penyiapan, pemodelan, evaluasi hingga implementasi. Penelitian ini menghasilkan 2 kelompok tingkatan UMKM yaitu kelompok keberlangsungan hidup kuat dan lemah. UMKM kuat memiliki kriteria omset yang besar dengan perbandingan jumlah karyawan terhadap omsetnya seimbang, sementara UMKM lemah memiliki kriteria omset yang relatif besar namun dengan perbandingan jumlah karyawan terhadap omsetnya tidak seimbang. Kualitas pengelompokan yang dihasilkan pun cukup baik ditandai dengan nilai Davies-Bouldin Index sebesar 0.75.
APLIKASI PENCATATAN KEUANGAN PENJUALAN KREDIT PADA CV. ERTEHA KARYA JAYA BOGOR
Authors: Ningsih Rahayu , Purmawati Shinta , Wardani Rizka
Published: May 2024

Transformasi Digital di Indonesia saat ini tentu membuat perkembangan teknologi informasi menjadi semakin pesat di segala bidang kehidupan, terutama dalam sektor usaha atau bisnis. Berdasarkan data pertumbuhan ecommerce dari  Lembaga riset Merchant Machine asal inggris, Negara Indonesia tercatat dengan pertumbuhan 78%. CV Erteha Karya Jaya Bogor merupakan perusahaan swasta yang bergerak dalam bidang distributor buku,Supplier percetakan dan ATK. Saat ini, dalam pencatatannya belum menggunakan sistem informasi yang baik, dimana semua transaksi dicatat kedalam aplikasi pengolah angka yaitu microsoft excel, termasuk laporan keuangan sehingga menyebabkan terjadinya kekeliruan dalam pembuatan laporan keuangan. Berdasarkan masalah tersebut maka penulis melakukan penelitian untuk membangun sebuah aplikasi pencatatan keuangan penjualan secara kredit. Sistem ini dibuat dengan menggunakan metode SDLC (Software Development Life Cycle) Waterfall, dengan menggunakan bahasa pemrograman PHP dan database mySQL yang memungkinkan pengguna dapat input data, edit data, pencarian data dengan cepat, serta menjadi solusi dalam penyimpanan data. Data transaksi keuangan perusahaan tersimpan dengan aman dan proses bisnis dari mulai membuat penawaran hingga laporan sesuai kebutuhan dapat dikelola dengan lebih mudah, cepat dan tepat.
IMPLEMENTASI METODE SIMPLE ADDITIVE WEIGHT PADA SISTEM PEMILIHAN PENERIMA BEASISWA
Authors: Sulistyowati Daning Nur , Sari Risma Purnama
Published: May 2024

Beasiswa merupakan bentuk bantuan atau pemberian yang diberikan kepada pelajar untuk mendukung pembiayaan pendidikan. Tujuan utama dari beasiswa adalah untuk menciptakan kesempatan yang lebih adil dan merata dalam akses pendidikan. Namun, masih terdapat banyak pemberian beasiswa yang tidak tepat, sehingga menyebabkan ketidakadilan dalam sistem pendidikan. Penelitian ini bertujuan untuk mengatasi masalah tersebut dengan menciptakan sistem penunjang keputusan pemilihan penerimaan beasiswa menggunakan metode Simple Additive Weighting (SAW) dengan alternatif yang digunakan berupa rata-rata rapor, penghasilan ayah, penghasilan ibu, semester, kelas, jumlah saudara kandung, jumlah saudara yang sudah menikah, jumlah organisasi, jumlah prestasi, dan jumlah uang jajan perhari sebagai input untuk menentukan penerimaan beasiswa. Hasil dari pengolahan dan analisis data menggunakan metode SAW menunjukkan bahwa penghasilan orang tua memiliki bobot tertinggi dengan nilai 0,20, diikuti rata-rata rapor yaitu 0,15, penghasilan ibu 0,10, Jumlah saudara kandung 0,10, jumlah organisasi 0,10, jumlah prestasi 0,10, kelas 0,10, semester 0,05, jumlah saudara yang menikah 0,05, jumlah uang jajan perhari 0,05. Dengan demikian, penghasilan orang tua menjadi faktor penentu utama dalam pemilihan penerimaan beasiswa.