bluuebunny/crossref_metadata_2025 huggingface dataset:
Promoting Cross Border Tourism in Europe. The case of Greece – Turkey.
Authors: Kalogirou Christina , Velissariou Efstathios
Published: January 2025

Greece has the particularity of being an external border of the European Union, bordering countries that do not belong to the Schengen treaty, such as Turkey. Greece belongs to the 4 most popular destinations for Turkish Travellers.
The case study showed that important factors for the development and promoting of cross-border tourism between Greece and Turkey, in addition to transportation facilities and access possibilities, are diplomatic relations and interstate agreements, fast service at the border, as well as the institutional and bureaucratic travel conditions, such as the easy granting of visas to Turkish travellers. This agreement allows Turks to visit the Greek islands for up to a week without having to apply for full access to the EU’s passport-free travel zone.
Concluding, this study highlights the importance of good political relations on a bilateral level for the development of cross-border tourism, strategic marketing tools and cooperative efforts to fully exploit the potential of cross-border tourism. In addition, the article proposes the extension of visas to other Aegean islands, but also the creation of permanent structures, such as the Cross-Border Tourism Observatory to support the sustainable development and promotion of cross-border tourism initiatives.
Generation Y female consumers’ perceived value of beauty vlogs: path analysis
Authors: Bevan-Dye Ayesha Lian
Published: January 2025

The beauty sector is widely recognised for being among the earliest adopters of social media marketing and for acknowledging the potential of social media influencers. A beauty vlogger refers to an individual who has attracted a significant number of followers on a video-based social media platform. Although academic  literature is increasingly focusing on social media influencer marketing, there is demand for additional research, particularly on YouTube vlogs, regarding their impact on beauty product consumption among Generation Y female consumers. The goal of this study was to identify the elements that contribute to Generation Y female consumers’ assessment of the perceived value of beauty vlogs on YouTube. A structured electronic questionnaire was used to gather data from a sample of 340 females, 18 years of age or older, living in South Africa. The results infer that Generation Y female consumers perceive beauty vlogs on YouTube as informative, entertaining, credible and of value. Path analysis revealed that beauty vlog informativeness, entertainment value and credibility explain 69% of the variance in Generation Y females’ perceived value of beauty vlogs on YouTube. The findings underscore the relevance of beauty product marketers collaborating with beauty product influencers on YouTube when targeting Generation Y female consumers.
Residents’ Perceptions of the Transition towards Digital Transformation in the Tourism Industry. The Case of the Chania Prefecture
Authors: Bompolaki Katerina , Apostolakis Alexandros , Kourgiantakis Markos
Published: January 2025

Crete is an archetypal summer tourism destination in the Mediterranean. It "suffers" fromstrong seasonality during the summer months, while the tourist season shrinks on an annualbasis. As a strategy to address these problems, the literature suggests digital transformationof the local tourism industry and a greater emphasis to be devoted on technology and theopportunities it offers to entrepreneurs and local communities. This study explores the viewsof the residents of the prefecture of Chania, Crete, on how they perceive concepts such astechnologically advanced tourism industry, digital transformation and transition factorstowards a technologically advanced tourism industry. Chania prefecture suffers tremendouslyfrom increased tourism activity during the summer months and technology is perceived as asolution to the resulting problems. The semi-structured interview technique was chosen tocollect information from the participants. The results of the survey revealed numerous anddiverse concerns of residents in different areas of the county. Therefore, it could be concludedthat the assumption that technological innovation is a panacea for tourism development doesnot apply equally to everyone.
A guide to selecting high-performing antibodies for Huntingtin (UniProt ID: P42858) for use in western blot, immunoprecipitation, and immunofluorescence
Authors: Fanti Rebeka , Ayoubi Riham , Alende Charles , Fotouhi Maryam , González Bolívar Sara , Chandrasekaran Renu , Southern Kathleen , Edwards Aled M. , Harding Rachel J. , Laflamme Carl ,   NeuroSGC/YCharOS/EDDU collaborative group,   ABIF consortium
Published: January 2025

Huntingtin encodes a 3144 amino acid protein, with a polyglutamine repeat tract at the N-terminus. Expansion of this repeat tract above a pathogenic threshold of 36 repeats is the causative mutation of Huntington's disease, a neurodegenerative disorder characterized by loss of striatal neurons. Here we have characterized twenty Huntingtin commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.
Alpha-guaiene isolated from patchouli oil exhibits antifungal activity against four pathogenic fungi
Authors: Nurjanah Sarifah , Alhafidz Zhaqqu , Maulani Maghfira , Rialita Tita , Lembong Elazmanawati
Published: January 2025

Background The major component of patchouli oil, patchouli alcohol, is used as fixative and has antimicrobial activity. The function of other components, such as α-guaiene, remains unknown. Therefore, this study reports the antifungal activity of α-guaiene isolated from patchouli oil against for pathogenic fungi: Aspergillus niger, Candida albicans ATCC 7102, Microsporum gypseum ATCC 14683, and Trichophyton mentagrophytes ATCC 16404. Methods The material from fraction (249°C-254°C) had the highest α-guaiene. Minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined using the microdilution technique to evaluate antifungal activity, with n-hexane and medium serving as negative controls, and ketoconazole and fluconazole serving as positive controls. Results The results showed that the MIC value was determined at 45%, 50% for C. albicans, 55%, 60% for A. niger, 50%, 60% for M. gypseum, and 95%, 100% for T. mentagrophytes, respectively. Positive and medium controls demonstrated no microbial growth, whereas negative and growth controls revealed the presence of microorganisms. Fungus resistance to α-guaiene T. mentagrophytes exhibited the highest MIC value. Conclusions Overall, this study reveals that α-guaiene is a promising agent effective against the studied pathogenic fungi.
Role, function, and expectations of research funding committees: Perspectives from committee members
Authors: Blatch-Jones Amanda , Boxall Cherish , Meadmore Katie
Published: January 2025

Research funding committees play an integral role in the research funding process, consisting of a range of skills, knowledge, and expertise (e.g., professional, and public contributors). Although there is some evidence that has explored the efficiency and effectiveness of funding committees in terms of the funding process, there is a lack of published evidence about the purpose, role, and function of funding committees, from the perspective of committee members. A subset of survey data from a cohort of six National Institute for Health and Care Research (NIHR) research programmes, exploring the purpose of a funding committee, and the expectations and role of a funding committee member between October 2020 to December 2021. All committee members were eligible to participate in the survey. Using an inductive approach, 50 completed responses (22.5% response rate) were analysed, focusing on the role of a funding committee member and the functions of a funding committee. Participants highlighted seven key areas for the purpose of a funding committee: prioritising and recommending what research to fund (n=36) and assessment of quality (n=24) being the most common responses. Four areas were considered important to the expectations and role of funding committee members, with reviewing, critically appraising, and discussing applications (n=44); and being fair, objective, and unbiased (n=27) being the most common responses. The findings offer a unique insight into committee members’ expectations about the role, purpose and function of a funding committee and their contribution to the funding recommendation process. There was high agreement that the purpose and role of committees and their members was to offer expert advice to make fair, impartial decisions on which research should be prioritised. Exploring the purpose, role, and function of funding committees has relevance and importance for funding organisations seeking to enhance and optimise the decision-making practice of funding committees.
Case Report: Case report: a rare case of dentigerous cyst in 1-year-old patient.
Authors: Alshehri Sami
Published: January 2025

One of the most common benign lesions is dentigerous cyst, which is commonly associated with unerupted tooth crowns. Dentigerous cysts in infants may manifest as swelling or a firm mass in the oral cavity. Such cysts arise from dental follicles, and their development can lead to dental complications such as tooth displacement, root resorption of the adjacent teeth, or infection if not treated carefully. Enucleation is the method of choice for the treatment of such lesions. In the current case report, a rare age presented with 1 a old patient was referred to oral and maxillofacial clinics. In the case of right facial swelling and pain for five days ago, intra- and extra-oral examinations were performed. Computed Tomography (CT) demonstrated a well-defined expansile lytic lesion, and parents consented and agreed to proceed with the surgery option. Enucleation was performed surgically, and the patient was followed up for up to 8 months. Significant improvement was noted, with no further complications or recorded complaints.
FXR agonist in post-liver transplantation patients: a randomized open-labeled study.
Authors: K N Anila , S Nair Saraswathy , Balakrishnan` Dinesh , G Unnikrishnan , S T Binoj , Narayana Menon Ramachandran , Varghese Christi Titus , Mallick Shweta , Nair Krishnanunni , Durairaj Madhu Srinivasan , V Guhan , Zackariah Nafiya , Rajakrishnan Haritha , Valsan Arun , Shaji Mathew Johns , Philips Cyriac Abby , Watson Christopher , O V Sudheer , S Sudhindran
Published: January 2025

Liver diseases cause nearly 2 million deaths worldwide each year, with approximately 1 million deaths from cirrhosis complications and another 1 million from viral hepatitis and liver cancer, according to WHO estimates. Liver transplantation (LT) remains the primary curative option, boasting success rates of 85% in the first year and 75% at five years post-transplant. Despite high costs, LT is considered cost-effective, especially for younger patients with active work years remaining. However, post-transplant complications, particularly intrahepatic cholestasis, present notable challenges. This complication arises from factors such as ischemia-reperfusion injury, infections, immunological rejection, and surgical complications, all contributing to impaired bile flow and liver damage. Current medical therapies for post-LT cholestasis are limited, with ursodeoxycholic acid (UDCA) frequently used, despite questionable efficacy. Obeticholic acid (OCA), a potent Farnesoid X Receptor (FXR) agonist approved by the FDA for treating primary biliary cholangitis (PBC), has shown potential benefits in reducing elevated cholestatic liver enzymes. Given its significant effects on liver health, OCA may offer therapeutic value in managing post-transplant cholestasis and improving graft survival. This randomized controlled trial (RCT) aims to evaluate OCA’s efficacy compared to UDCA in reducing cholestatic injury and enhancing graft function post-LT. The primary outcomes will focus on a 15% reduction in alkaline phosphatase and gamma-glutamyl transferase levels at 3, 6, and 12 months from baseline one month. Secondary outcomes include molecular markers, biliary complications, graft rejection, quality of life, and cost-effectiveness. Results are anticipated to demonstrate that OCA could improve graft survival, reduce complications, and enhance quality of life, potentially setting a new standard in post-LT care if found beneficial.
Antioxidant and Hepatoprotective Effects of Moringa oleifera-mediated Selenium Nanoparticles in Diabetic Rats.
Authors: Ahmad Tarmizi Anas Ahzaruddin , Nik Ramli Nik Nasihah , Abdul Mutalib Maisarah , Jasmi Nor Amira , Mokhtar Mohd Helmy , Adam Siti Hajar
Published: January 2025

Background The search for efficient treatments for type 2 diabetes mellitus (T2DM) has highlighted the potential of plant-based therapeutic compounds and eco-friendly processes for producing selenium nanoparticles. This study investigates the antidiabetic potential of Moringa oleifera-mediated biogenic selenium nanoparticles (MO-SeNPs) in diabetic rats. Methods Male Sprague-Dawley rats were induced with diabetes via a high-fat diet for 2 weeks followed by a single intraperitoneal injection of streptozotocin (STZ) at 45 mg/kg body weight (BW). The rats were divided into five groups: normal, diabetic control, metformin at 100 mg/kg/BW, and two groups treated with oral administration of MO-SeNPs at 0.25 and 0.5 mg/kg body weight for 28 days. Food and water intake as well as fasting blood glucose and body weight were measured weekly. After the treatment period, rats were sacrificed, and blood and liver samples were harvested for further analysis. Results MO-SeNPs treatment significantly reduced blood glucose levels (p < 0.05) and restored insulin resistance, with lower dose demonstrating better glycaemic control than larger dose. MO-SeNPs also increased hepatic antioxidant enzyme activity, including GSH-Px, CAT, and T-SOD, which neutralise oxidative stress. MO-SeNPs also improves cardiovascular health by raising HDL and lowering LDL. MO-SeNPs showed hepatoprotective benefits by lowering inflammatory markers such TNF-α, IL-6, IL-1β, iNOS, and AGEs, and reduced lipid peroxidation. Diabetes raises inflammatory indicators, causing liver damage and other problems. The reduction in these indicators shows MO-SeNPs reduce liver inflammation and protect the liver. The normalisation of liver enzyme levels (ALT, AST, ALP) showed improved liver function. Conclusions The findings suggest that the green synthesis of SeNPs using Moringa oleifera offers a viable alternative for diabetes treatment, highlighting its potential to enhance glycemic control and improve overall metabolic health.
A guide to selecting high-performing antibodies for Stearoyl-CoA desaturase (SCD1) (UniProt ID: O00767) for use in western blot, immunoprecipitation, and immunofluorescence
Authors: Ruíz Moleón Vera , Alende Charles , Fotouhi Maryam , González Bolívar Sara , Ayoubi Riham , Laflamme Carl ,   NeuroSGC/YCharOS/EDDU collaborative group,   ABIF consortium
Published: January 2025

The enzyme stearoyl-CoA desaturase (SCD1) is a modulator of lipid metabolism by catalyzing the biosynthesis of mono-unsaturated fatty acids from saturated fatty acids. Understanding the specific mechanisms by which SCD1 plays in health and disease can provide novel insides in therapeutic targets, a process that would be facilitated by the availability of high-quality antibodies. Here we have characterized nine SCD1 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.
Cost efficiency in commercial banking in Poland. Linear ordering approach
Authors: Niedziółka Paweł , Korzeb Zbigniew
Published: January 2025

Motivation: Previous research has primarily focused on the impact of operational efficiency on bank profitability. An in-depth review of the literature indicates that there is a lack of studies aimed at identifying the characteristics of banks with similar levels of cost efficiency.
Aim: The aim of the article is to identify clusters of banks with similar profiles, given the level of operating costs relative to the scale and profitability of operations.
Results: Operational efficiency is positively related to bank profitability, and economies of scale manifest themselves in the form of relatively higher cost efficiency of large credit institutions. The results confirm the validity of the management strategy of the abrupt reduction of operating costs in commercial banks and create premises for supervisory authorities to prepare the expected (optimal) scenario of banking sector structure evolution and adjust to it the regulatory policy.
Cancer Cachexia: Innovations in Pharmacotherapy for Terminal-Stage Patients - Review of the latest reports
Authors: Witowska Kinga , Sacher Karolina , Hosseinnejad Negar , Biskupski Mikolaj , Turemka Mariola , Mandziuk Aneta , Korotko Urszula , Zabojska Krystyna , Wojtas Aneta Klaudia , Cygnarowicz Aleksandra
Published: January 2025

Introduction and purpose
Cachexia is a complex and multifactorial syndrome, which is a current, worldwide treatment challenge, and concerns most of the patients with cancer. The issue is characterized by anorexia, skeletal muscle loss, adipose tissue wasting, involuntary weight loss, malnutrition, and poor appetite due to dysfunction of metabolism and chronic, systemic inflammation. Additionally, it impacts oncological treatment and a decline in Quality of Life. The review aims to explore the latest research, innovations, and potentials in the treatment of cachexia.
Material and methods
The review was based on research of articles published from 2019 to 2024 on the PubMed database using the following keywords: cancer cachexia, palliative care, and cachexia pharmacotherapy. 
Results
Anamorelin, a selective ghrelin receptor agonist showed effectiveness in weight gain and appetite improvement. Also, myostatin inhibitors protect muscles and promote their growth due to suppression of myostatin. Ponsegromab, a GDF-15 inhibitor, significantly and directly enhanced muscle mass, appetite, and quality of life, with good safety. Modern anti-inflammatory medications like momelotynib or tocilizumab, reduced the concentration of pro-inflammatory cytokines and improved quality of life, however, but posed immunosuppression risk. Pentoxifylline declined inflammation and chemotherapy toxicity, and improved body weight and survival. Cannabinoids alleviated chemotherapy-induced nausea but were ineffective for weight and quality of life.
Conclusions
Therapeutic approaches target various aspects of cachexia due to its complex pathophysiology. Anamorelin, ponsegromab, and myostatin inhibitors have clinical potential. Modern anti-inflammatory drugs and pentoxifylline offer supportive benefits. Further research is vital for developing effective and safe treatment guidelines for cancer cachexia.
Normalized solutions to p-Laplacian equation: Sobolev critical case
Authors: Lou Qingjun , Zhang Xiaoyan , Zhang Zhitao
Published: January 2025

This paper is devoted to the study of normalized solutions to p-Laplacian equation involving Sobolev critical exponent.
Under the focussing condition, we obtain existence of ground states in mass subcritical case, mass critical case and mass supercritical case, respectively.
Furthermore, we show some asymptotic behaviors of ground states. Meanwhile, under the defocussing condition, we prove some non-existence results.
Corrigendum and contribution to "Weakly almost periodic functions invariant means and fixed point properties in locally convex topological vector spaces" (Topol. Methods Nonlinear Anal. 60 (2022), no.1, 135-152)
Authors: Salame Khadime
Published: January 2025

This corrigendum makes a correction to K. Salame, {\em Weakly almost periodic functions invariant means and fixed point properties in locally convex topological vector spaces}, Topol. Methods Nonlinear Anal. {\bf 60} (2022), 135-152,
and brings some new contributions to this open problem.
The Use of Alternative Energy as a Driver Fishing Boat
Authors: IS Nina Paramytha , Ariyadi Tamsir
Published: January 2025

The use of outboard engines commonly used by fishing boats is considered no longer effective, considering the price of BBM (Fuel Oil) which always increases and the effects caused by the use of outboard engines are not environmentally friendly such as producing noise and air pollution caused. This research aims to overcome the problems of using outboard engines by utilizing solar panels to convert sunlight into electrical energy and DC 775 motors as boat propulsion. The use of solar panels with a tracker system to maximize solar panels in producing electrical energy which is then stored in a battery to drive a DC motor. The results of the calculation of a battery with a capacity of 20 Ah can drive the boat for 3.7 hours, where fishermen need 1 liter of fuel to run the outboard engine for 30 minutes. The maximum boat speed generated is 5.76 knots. The results of the analysis in terms of costs incurred for fuel operations are 0% because they utilize sunlight and there is no pollution and noise generated when the boat works. Future development can replace the battery with a larger capacity and add solar panels for faster battery charging. With this research, researchers hope to help fishermen in reducing operational costs and the success of catching more fish.
Designing Business Intelligence Dashboards to Support Decision-Making in a Fishery Business
Authors: Raihanto Muhammad Satya , Febrianti Melinska Ayu , Qurtubi Qurtubi , Setiawan Danang , Auliana Windi
Published: January 2025

Accurate assessment and thorough analysis of managerial performance are essential in obtaining enhanced business performance. A real-time monitoring system is necessary to support the decision-making process. This study aims to design a business intelligence dashboard containing real-time monitoring of water quality to support the decision-making of the management team of an agribusiness company. Four steps were used in designing the business intelligence (BI) dashboard: (1) scope and plan, (2) analyze and define, (3) architect and design, and (4) build, test, and refine. The study started with determining the scope and plan for developing the BI dashboard to monitor the water pond’s quality in real time. The requirements of system input and output were identified in the analyze and define phase. The data warehouse model and design visualization regarding the BI dashboard were determined in the architect and design step. The system's architecture was analyzed in the final step, build and test. Three months of data collection and interviews with the management team of the fishery company were performed to support each step in BI design. This study’s outcome is a BI dashboard providing real-time monitoring that supports the management team's decision-making process. This study still considers two water quality measures; therefore, future research can be conducted using other measures. Future research can also be performed on another agribusiness company to support the decision-making process and increase competitiveness.
Toward an Advanced Gas Composition Measurement Device for Chemical Reaction Analysis
Authors: Gonibala Fajriansya , Jamilatun Siti , Amelia Shinta , Ma’arif Alfian , Setiawan Muhammad Haryo
Published: January 2025

The research details the development of a reactor-based monitoring system designed to identify and monitor gases generated within industrial chemical reactors. Consisting of nine MQ and DHT11 sensors, this reactor design allows for simultaneous measurement of temperature and humidity within the sample. Using a sensor array methodology, this research utilizes multiple sensors to collect and process analog signals to improve the accuracy of gas identification within samples. These analog signals obtained from the sensors are processed by an Arduino Mega 2560 microcontroller using the Arduino IDE software. The research, conducted on ten different samples, shows methane (CH4), hydrogen (H2), and alcohol (C2H6O) as the most concentrated gases. Notably, certain samples such as batik waste, honey, Robusta coffee, and sambal have a significant impact on methane gas concentrations. In addition, substances such as Robusta Coffee, Sprite, Syrup, and Oyster Sauce have a significant effect on hydrogen gas concentrations, while Robusta Coffee, Sambal, Arabica Coffee, and Pepper have a significant effect on alcohol gas concentrations. In addition, of the nine MQ sensors used, the MQ3, MQ4, and MQ8 are particularly effective at detecting alcohol, methane, and hydrogen gases, respectively, in the samples tested.
Simple Simulation of Perturb and Observe MPPT Algorithm on Synchronous Buck Converter
Authors: Abuzairi Tomy , Rachmad Ralfi Wibowo
Published: January 2025

The efficiency of the PV system can be improved by operating the solar panel on its Maximum Power Point (MPP). However, ariations in irradiance and temperature will lead to the shifting of solar panel MPP. To continuously operate the solar panel near its MPP, a tracking algorithm is needed. In this research, a model consisting of a synchronous buck converter and a Maximum Power Point Tracking (MPPT) algorithm will be designed as aMATLAB/Simulink model. Perturb and Observe technique will be used to implement the algorithm into the synchronous buck converter, which will control a 10 W solar panel load so it will operate near its MPP. Results show that the PV system model can track the Solar Panel MPP in various simulated irradiance.
Advancing UAV Path Planning System: A Software Pattern Language for Dynamic Environments
Authors: Airlangga Gregorius
Published: January 2025

In the rapidly advancing domain of Unmanned Aerial Vehicle (UAV) technologies, the capability to navigate dynamic and unpredictable environments is paramount. To this end, we present a novel design pattern framework for real-time UAV path planning, derived from the established Pattern Language of Program Community (PLOP). This framework integrates a suite of software patterns, each selected for its role in enhancing UAV operational adaptability, environmental awareness, and resource management. Our proposed framework capitalizes on a blend of behavioral, structural, and creational patterns, which work in concert to refine the UAV's decision-making processes in response to changing environmental conditions. For instance, the Observer pattern is employed to maintain real-time environmental awareness, while the Strategy pattern allows for dynamic adaptability in the UAV's path planning algorithm. Theoretical analysis and conceptual evaluations form the backbone of this research, eschewing empirical experiments for a detailed exploration of the design's potential. By offering a systematic and standardized approach, this research contributes to the UAV field by providing a robust theoretical foundation for future empirical studies and practical implementations, aiming to elevate the efficiency and safety of UAV operations in dynamic environments.
Adaptive Cyber-Defense for Unmanned Aerial Vehicles: A Modular Simulation Model with Dynamic Performance Management
Authors: Airlangga Gregorius
Published: January 2025

In light of escalating cyber threats, this study tackles the cybersecurity challenges in UAV systems, underscoring the limitations of static defense mechanisms. Traditional security approaches fall short against the sophisticated and evolving nature of cyber-attacks, particularly for UAVs that depend on real-time autonomy. Addressing this deficiency, we introduce an adaptive modular security system tailored for UAVs, enhancing resilience through real-time defensive adaptability. This system integrates scalable, modular components and employs machine learning techniques—specifically, neural networks and anomaly detection algorithm to improve threat prediction and response. Our approach marks a significant leap in UAV cybersecurity, departing from static defenses to a dynamic, context-aware strategy. By employing this system, UAV stakeholders gain the flexibility needed to counteract multifaceted cyber risks in diverse operational scenarios. The paper delves into the system's design and operational efficacy, juxtaposing it with conventional strategies. Experimental evaluations, using varied UAV scenarios, measure defense success rates, computational efficiency, and resource utilization. Findings reveal that our system surpasses traditional models in defense success and computational speed, albeit with a slight increase in resource usage a consideration for deployment in resource-constrained contexts. In closing, this research underscores the imperative for dynamic, adaptable cybersecurity solutions in UAV operations, presenting an innovative and proactive defense framework. It not only illustrates the immediate benefits of such adaptive systems but also paves the way for ongoing enhancements in UAV cyber defense mechanisms.
Development of the Design and Control of a Hexapod Robot for Uneven Terrain
Authors: Putra Prasetya Murdaka , Widodo Nuryono Satya
Published: January 2025

In the Indonesian Search and Rescue Robot Contest in 2021 and 2022, the robot still cannot work well when passing through uneven obstacles. The change in uneven terrain from the previous year was a difficulty for the robot in passing it. This research was conducted to develop mechanical design and movement control design for the robot, so that the robot can be more optimal when moving through uneven terrain. The design of the hexapod robot is done by reducing the dimensions of the existing robot and determining the Center of Gravity point. The movement of the robot is also designed by determining the angular position of the AX-18A servo with respect to the terrain the robot travels through. The movement algorithm applied to the robot is the tripod gait algorithm. The robot control on the debris field and irregular floor is done by applying a proximity sensor to minimise the robot from hitting the wall on the field. The robot also has an IMU sensor that will work in measuring the slope on the up-and-down floor terrain (slope), so that the movement of the robot can be adjusted when passing through the terrain with the slope read by the sensor. The results of the research conducted show that the robot can be redesigned through 3D design through solidworks by determining the Center of Gravity (CoG) point. The robot has been able to pass through 3 objects tested, namely debris terrain, irregular floor terrain, and up and down floor terrain. The success rate of the robot when passing through debris terrain and irregular floor terrain is 100% with an average time of 9.7 seconds and 10.1 seconds. The success rate of the robot when passing through the up-and-down floor terrain is 80% with an average time of 22.9 seconds.
The Use of Clustering Methods in Memory-Based Collaborative Filtering for Ranking-Based Recommendation Systems
Authors: Wiyono Slamet , Rais Rais
Published: January 2025

This research explores the application of clustering techniques and frequency normalization in collaborative filtering to enhance the performance of ranking-based recommendation systems. Collaborative filtering is a popular approach in recommendation systems that relies on user-item interaction data. In ranking-based recommendation systems, the goal is to provide users with a personalized list of items, sorted by their predicted relevance. In this study, we propose a novel approach that combines clustering and frequency normalization techniques. Clustering, in the context of data analysis, is a technique used to organize and group together users or items that share similar characteristics or features. This method proves beneficial in enhancing recommendation accuracy by uncovering hidden patterns within the data. Additionally, frequency normalization is utilized to mitigate potential biases in user-item interaction data, ensuring fair and unbiased recommendations. The research methodology involves data preprocessing, clustering algorithm selection, frequency normalization techniques, and evaluation metrics. Experimental results demonstrate that the proposed method outperforms traditional collaborative filtering approaches in terms of ranking accuracy and recommendation quality. This approach has the potential to enhance recommendation systems across various domains, including e-commerce, content recommendation, and personalized advertising.
Comparative Analysis of MLP, CNN, and RNN Models in Automatic Speech Recognition: Dissecting Performance Metric
Authors: Lenson Abraham K. S. , Airlangga Gregorius
Published: January 2025

This study conducts a comparative analysis of three prominent machine learning models: Multi-Layer Perceptrons (MLP), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM) in the field of automatic speech recognition (ASR). This research is distinct in its use of the LibriSpeech 'test-clean' dataset, selected for its diversity in speaker accents and varied recording conditions, establishing it as a robust benchmark for ASR performance evaluation. Our approach involved preprocessing the audio data to ensure consistency and extracting Mel-Frequency Cepstral Coefficients (MFCCs) as the primary features, crucial for capturing the nuances of human speech. The models were meticulously configured with specific architectural details and hyperparameters. The MLP and CNN models were designed to maximize their pattern recognition capabilities, while the RNN (LSTM) was optimized for processing temporal data. To assess their performance, we employed metrics such as precision, recall, and F1-score. The MLP and CNN models demonstrated exceptional accuracy, with scores of 0.98 across these metrics, indicating their effectiveness in feature extraction and pattern recognition. In contrast, the LSTM variant of RNN showed lower efficacy, with scores below 0.60, highlighting the challenges in handling sequential speech data. The results of this study shed light on the differing capabilities of these models in ASR. While the high accuracy of MLP and CNN suggests potential overfitting, the underperformance of LSTM underscores the necessity for further refinement in sequential data processing. This research contributes to the understanding of various machine learning approaches in ASR and paves the way for future investigations. We propose exploring hybrid model architectures and enhancing feature extraction methods to develop more sophisticated, real-world ASR systems. Additionally, our findings underscore the importance of considering model-specific strengths and limitations in ASR applications, guiding the direction of future research in this rapidly evolving field.
Hybrid System Prototype for Dam Water Level Control System to Irrigating Rice Fields
Authors: Hidayat Agung Wahyu , Sulistiyowati Indah , Wicaksono Arief , Syahrorini Syamsudduha
Published: January 2025

Naturally, one of the causes of crop failure in agriculture is flooding brought on by unchecked water overflow, particularly during the rainy season. Crop failure is a common source of complaints from farmers because, in addition to making it harder for them to sell their harvests, it decreases the price at which rice is sold to customers, which reduces the amount of people who purchase rice. This project aims to develop a hybrid dam water level control system prototype for paddy field irrigation. In this instance, the innovative flood monitoring and control system integrates Blynk as a user interface that can be accessible via software, along with an ESP 32 monitoring unit and a NodeMCU 8266 controller. like smartphone devices. The ESP 32 controls servo motor 1 to open the dam door in the event of flooding. In addition, the ESP 32 monitors the dam's water level using the I2C LCD and alerts the user with a bell. The NodeMCU 8266 functions as a link to the ultrasonic sensor to relay the water level data to the ESP 32. Through the Blynk application, the user can manually control Servo motor 2 to open and close the dam door with configurable water level limitations. The results of the studies indicate that this system functions flawlessly, from setting up a warning system to connecting tools. The system may be manually operated by making use of microcontroller technology.
Implementation of GPS as a Validation System for Computer Laboratory Practicum Attendance
Authors: Prasetya Anang Nur , Supriyanto Supriyanto
Published: January 2025

The attendance system is a data management system for tracking individual or institutional attendance automatically, catering to personal or organizational management needs. Its primary objective is to serve as evidence of participation in activities, particularly in educational settings, where it validates attendance during the teaching and learning process, making attendance crucial. Manual attendance-taking in the Informatics Engineering Practicum at Ahmad Dahlan University is prone to difficulties in calculation, as well as risks of torn, wet, or lost attendance sheets, leading to prolonged processing times. The development of the Reglab application aims to enhance efficiency by securely managing attendance data, replacing manual processes. Additionally, it will integrate GPS technology to validate that practical activities occur within the laboratory. The Agile methodology guides the development of Reglab, leveraging existing systems while ensuring that resources are allocated effectively to accommodate the increasing volume of student and practicum schedule data. Student data will only be utilized for practicum registration, scheduling, and attendance purposes. The Agile approach ensures that the product output meets usability and user experience standards. System evaluation involves Blackbox testing and addressing user complaints received by the laboratory, with results aligning with expectations and a reduction in reported issues.
Implementation of Digital Feedback Control with Change Rate Limiter in Regulating Water Flow Rate Using Arduino
Authors: Sitompul Erwin , Putra Ridha Muhlita , Tarigan Hendra , Silitonga Arthur , Bukhori Iksan
Published: January 2025

Water flow rate control is crucial in applications where it determines operational efficiency in applications such as agriculture, hydroponics, industrial processes, and hydrology. This research presents two algorithms for a simple and reliable digital water flow control: Error-Sign-based Control (ESC) and Error-Value-based Control (EVC). These algorithms are equipped with a change rate limiter to avoid excessive control output increase. They were compared qualitatively with the conventional digital PID controller. Subsequently, they were implemented and tested in a water circulation system. The control loop consisted of a microcontroller, water flow rate sensor, and submersible DC water pump with a supporting motor driver. The controllers were given a control task to follow a 150-second reference trajectory with a changing set point every 30 seconds. The performance measures of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were utilized to assess the performance of the control algorithms. EVC with a change rate limiter of 10% delivered the best performance with an MAE of 0.40 and RMSE of 0.97. EVC provides simple and reliable control of the water flow rate system due to its easy tuning, quick tracking response to set point changes, and solid regulating performance. Further work in the implementation of the control scheme in other applications is encouraged.
Improving Power Quality in High-Rise Buildings with a Single-Tone Passive Filter and Capacitor Bank
Authors: Kasbi Ahmad Aminul , Ruliyanta Ruliyanta , Keraf Adhyathta
Published: January 2025

Total harmonic distortion and a low power factor are critical issues affecting power quality in modern high-rise buildings. Non-linear loads generated by highly efficient electrical equipment cause total harmonic distortion. On the other hand, low power factor is caused by induction machines, excessively long cables, and inefficient equipment. This research aims to design a single-tunable filter and capacitor bank to address power quality issues. Our method involves utilizing a single-line building design diagram and conducting load simulations using ETAP 19.0.1 software. Our method is a harmonic load flow analysis. We use this method to calculate the harmonic distribution at various points within the electrical network. Harmonic flow analysis aids in identifying the harmonic contributions from various non-linear loads within the system. For research, we implemented a single-tuned passive filter and capacitor bank in the building's electrical system. We initiate the study by analyzing the transformer's total harmonic distortion (THD) and then make iterative adjustments to parameter values until we achieve compliance with the IEEE 519-2014 standard. As a result, the study recommends the installation of two single-tuned filters for orders 5 and 7, as well as the inclusion of a capacitor bank with a capacity of XXX. This reduces the system's THDi value from 21.77% to 4.45% and 22.63% to 4.45%, respectively. The power factor increased from 85.78% to 99.69% and 88.68% to 99.41%, respectively.
Automatic Satay Grill Using 5 Volt Stepper Motor for Home Business
Authors: Prayoga Dimas Dwi , Anshory Izza , Wicaksono Arief , Syahrorini Syamsudduha
Published: January 2025

Increased consumer demand for satay dishes as one of the traditional culinary demands innovation in the manufacturing process to improve efficiency and consistency. This research aims to design and implement a dc stepper motor-based automatic satay grill system as a solution for small businesses. This system uses a DC stepper motor as the main component, using an Arduino UNO microcontroller programmed to regulate the temperature and automatic rotation of the satay. The measurement uses a built-in LM35 temperature sensor to monitor the temperature during grilling to ensure optimal doneness. In addition, the system is equipped with an interface using an LCD screen connected to the Arduino UNO microcontroller to monitor the temperature and condition of the satay grill, allowing the user to easily set the grilling parameters according to preference. During testing of the prototype, results showed that this automatic satay grill system is capable of producing satay with uniform doneness and meeting quality standards. In addition, time and labor efficiency improved, making a positive contribution to the productivity of small and medium enterprises. Overall, this development provides an innovative and effective solution in improving the satay production process, positively impacting traditional culinary businesses.
Random Multi-Augmentation to Improve TensorFlow-Based Vehicle Plate Detection
Authors: Kirana Kartika Candra , Abdulrahman Salah Abdullah Khalil
Published: January 2025

In the development of the "Machine Learning" education kit, vehicle plate recognition was created using TensorFlow with SSD MobileNetV2. The detection failure rate in the training process with varying distances and lighting from the camera is high if the training data is insufficient. Addressing that notable gap in research, we proposed Random Multi-Augmentation to Improve TensorFlow-Based Vehicle Plate Detection. Augmentation techniques are expected to train data that is manipulated at varying lighting and distance. The proposed method consists of two combining augmentation approaches, namely: position augmentation and lighting augmentation. Position augmentation which consists of Flip, Crop, Rotate, Shift, and Crop is used to enrich the visualization of distance and viewing angle, while Lighting augmentation which consists of Greyscale, Hue, Saturation, Brightness, Exposure, and Blur is used to enrich the visualization of lighting. Variations in values were determined randomly based on variations in values from several previous studies. The comparison of TensorFlow SSD MobileNetV2 and Augmentation were tested using one video Roboflow. TensorFlow without augmentation exhibited an accuracy of 60%, precision of 100%, recall of 60%, and an F1 score of 75%, whereas TensorFlow within augmentation achieved a higher accuracy of 70%, precision of 100%, recall of 70%, and an F1 score of 82.3%. Based on precision measurement, Tensorflow can be claimed to prevent false positives, which indicates that the algorithm did not detect non-plate objects as vehicle plates. Furthermore, a comparison of the use of augmentation shows an increase in plate detection capabilities when using augmentation as Tensorflow preprocessing, which is indicated by an increase in recall and accuracy values. These results emphasize that augmentation is the pre-processing optimizer for vehicle number plate systems.
Tracking Ball Using YOLOv8 Method on Wheeled Soccer Robot with Omnidirectional Camera
Authors: Julianda Refli Rezka , Puriyanto Riky Dwi
Published: January 2025

Object detection is very we often find in everyday life that facilitates every activities in the object recognition process, for example in the military field, intelligent transportation, face detection, robotics, and others. Detection target detection is one of the hotspots of research in the field of computer vision. The location and category of the target can be determined by using target detection. Currently, target detection has been applied in many fields, one of which includes image segmentation.You only look once (YOLO) is an algorithm that can perform object detection in realtime, YOLO itself always gets development and improvement from previous versions. YOLOv8 is a type of YOLO from the latest version. YOLOv8 is a new implementation of Deep Learning that connects the input (original image) with the output. This type of YOLOv8 algorithm uses A deep dive architecture, assisted by CNN and a new backbone which uses convolutional layers for pixels which when described will be shaped like a pyramid. YOLOv8 is a stable object detection processing method with 80% higher than the previous version of YOLO, which makes YOLOv8 a type of YOLO that is better at processing object data faster and more efficiently in Real-Time.The camera with omnidirectional system is able to detect spherical objects and other objects using the YOLOV8 model used. In performance testing with 320×320 and 416×416 frames, because it fits the grid structure of the YOLO architecture. YOLOv8 has a higher mAP value with a value of 95,5% compared to previous versions of YOLO. In the detection test, YOLOv8 has a better average object detection than the previous version of YOLO which is indicated by the number of objects detected more stable.