bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Environment-Adaptive GNSS/INS Integrated Positioning with Factor Graph Optimization
Authors: Li Zhengdao , Lee Pin-Hsun , Hung Tsz Hin Marcus , Zhang Guohao , Hsu Li-Ta
Published: January 2024

Global navigation satellite systems (GNSSs) applied to intelligent transport systems in urban areas suffer from multipath and non-line-of-sight (NLOS) effects due to the signal reflections from high-rise buildings, which seriously degrade the accuracy and reliability of vehicles in real-time applications. Accordingly, the integration between GNSS and inertial navigation systems (INSs) could be utilized to improve positioning performance. However, the fixed GNSS solution uncertainty of the conventional integration method cannot determine the fluctuating GNSS reliability in fast-changing urban environments. This weakness becomes solvable using a deep learning model for sensing the ambient environment intelligently, and it can be further mitigated using factor graph optimization (FGO), which is capable of generating robust solutions based on historical data. This paper mainly develops the adaptive GNSS/INS loosely coupled system on FGO, along with the fixed-gain Kalman filter (KF) and adaptive KF (AKF) being taken as comparisons. The adaptation is aided by a convolutional neural network (CNN), and the feasibility is verified using data from different grades of receivers. Compared with the integration using fixed-gain KF, the proposed adaptive FGO (AFGO) maintains the 100% positioning availability and reduces the overall 2D positioning error by up to 70% in the aspects of both root mean square error (RMSE) and standard deviation (STD).
Characterization of Active Riverbed Spatiotemporal Dynamics through the Definition of a Framework for Remote Sensing Procedures
Authors: Crivellaro Marta , Vitti Alfonso , Zolezzi Guido , Bertoldi Walter
Published: January 2024

The increasing availability and quality of remote sensing data are changing the methods used in fluvial geomorphology applications, allowing the observation of hydro-morpho-biodynamics processes and their spatial and temporal variations at broader and more refined scales. With the advent of cloud-based computing, it is nowadays possible to reduce data processing time and increase code sharing, facilitating the development of reproducible analyses at regional and global scales. The consolidation of Earth Observation mission data into a single repository such as Google Earth Engine (GEE) offers the opportunity to standardize various methods found in literature, in particular those related to the identification of key geomorphological parameters. This work investigates different computational techniques and timeframes (e.g., seasonal, annual) for the automatic detection of the active river channel and its multi-temporal aggregation, proposing a rational integration of remote sensing tools into river monitoring and management. In particular, we propose a quantitative analysis of different approaches to obtain a synthetic representative image of river corridors, where each pixel is computed as a percentile of the bands (or a combination of bands) of all available images in a given time span. Synthetic images have the advantage of limiting the variability of individual images, thus providing more robust results in terms of the classification of the main components of the riverine ecosystem (sediments, water, and riparian vegetation). We apply the analysis to a set of rivers with analogous bioclimatic conditions and different levels of anthropic pressure, using a combination of Landsat and Sentinel-2 data. The results show that synthetic images derived from multispectral indexes (such as NDVI and MDWI) are more accurate than synthetic images derived from single bands. In addition, different temporal reduction statistics affect the detection of the active channel, and we suggest using the 90th percentile instead of the median to improve the detection of vegetated areas. Individual representative images are then aggregated into multitemporal maps to define a systematic and easily replicable approach for extracting active river corridors and their inherent spatial and temporal dynamics. Finally, the proposed procedure has the potential to be easily implemented and automated as a tool to provide relevant data to river managers.
Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data—A Case Study of the Eastern Coast of Laizhou Bay, China
Authors: Mu Ke , Tang Cheng , Tosi Luigi , Li Yanfang , Zheng Xiangyang , Donnici Sandra , Sun Jixiang , Liu Jun , Gao Xuelu
Published: January 2024

Monitoring shoreline movements is essential for understanding the impact of anthropogenic activities and climate change on the coastal zone dynamics. The use of remote sensing allows for large-scale spatial and temporal studies to better comprehend current trends. This study used Landsat 5 (TM), Landsat 8 (OLI), and Sentinel-2 (MSI) remote sensing images, together with the Otsu algorithm, marching squares algorithm, and tidal correction algorithm, to extract and correct the coastline positions of the east coast of Laizhou Bay in China from 1984 to 2022. The results indicate that 89.63% of the extracted shoreline segments have an error less than 30 m compared to the manually drawn coastline. The total length of the coastline increased from 166.90 km to 364.20 km, throughout the observation period, with a length change intensity (LCI) of 3.11% due to the development of coastal protection and engineering structures for human activities. The anthropization led to a decrease in the natural coastline from 83.33% to 13.89% and a continuous increase in the diversity and human use of the coastline. In particular, the index of coastline diversity (ICTD) and the index of coastline utilization degree (ICUD) increased from 0.39 to 0.79, and from 153.30 to 390.37, respectively. Over 70% of the sandy beaches experienced erosional processes. The shoreline erosion calculated using the end point rate (EPR) and the linear regression rate (LRR) is 79.54% and 85.58%, respectively. The fractal dimension of the coastline shows an increasing trend and is positively correlated with human activities. Coastline changes are primarily attributed to interventions such as land reclamation, aquaculture development, and port construction resulting in the creation of 10,000.20 hectares of new coastal areas. Finally, the use of Kalman filtering for the first time made it possible to predict that approximately 84.58% of the sandy coastline will be eroded to varying degrees by 2032. The research results can provide valuable reference for the scientific planning and rational utilization of resources on the eastern coast of Laizhou Bay.
A Novel ICESat-2 Signal Photon Extraction Method Based on Convolutional Neural Network
Authors: Qin Wenjun , Song Yan , Zou Yarong , Zhu Haitian , Guan Haiyan
Published: January 2024

When it comes to the application of the photon data gathered by the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), accurately removing noise is crucial. In particular, conventional denoising algorithms based on local density are susceptible to missing some signal photons when there is uneven signal density distribution, as well as being susceptible to misclassifying noise photons near the signal photons; the application of deep learning remains untapped in this domain as well. To solve these problems, a method for extracting signal photons based on a GoogLeNet model fused with a Convolutional Block Attention Module (CBAM) is proposed. The network model can make good use of the distribution information of each photon’s neighborhood, and simultaneously extract signal photons with different photon densities to avoid misclassification of noise photons. The CBAM enhances the network to focus more on learning the crucial features and improves its discriminative ability. In the experiments, simulation photon data in different signal-to-noise ratios (SNR) levels are utilized to demonstrate the superiority and accuracy of the proposed method. The results from signal extraction using the proposed method in four experimental areas outperform the conventional methods, with overall accuracy exceeding 98%. In the real validation experiments, reference data from four experimental areas are collected, and the elevation of signal photons extracted by the proposed method is proven to be consistent with the reference elevation, with R2 exceeding 0.87. Both simulation and real validation experiments demonstrate that the proposed method is effective and accurate for extracting signal photons.
Correction: Yang et al. Spatial Diffusion Waves of Human Activities: Evidence from Harmonized Nighttime Light Data during 1992–2018 in 234 Cities of China. Remote Sens. 2023, 15, 1426
Authors: Yang Jianxin , Yuan Man , Yang Shengbing , Zhang Danxia , Wang Yingge , Song Daiyi , Dai Yunze , Gao Yan , Gong Jian
Published: January 2024

In the original publication [...]
Design, Analysis, and Development of Low-Cost State-of-the-Art Magnetorheological-Based Microprocessor Prosthetic Knee
Authors: Qadir Muhammad Usman , Haq Izhar Ul , Khan Muhammad Awais , Shah Kamran , Chouikhi Houssam , Ismail Mohamed A.
Published: January 2024

For amputees, amputation is a devastating experience. Transfemoral amputees require an artificial lower limb prosthesis as a replacement for regaining their gait functions after amputation. Microprocessor-based transfemoral prosthesis has gained significant importance in the last two decades for the rehabilitation of lower limb amputees by assisting them in performing activities of daily living. Commercially available microprocessor-based knee joints have the needed features but are costly, making them beyond the reach of most amputees. The excessive cost of these devices can be attributed to custom sensing and actuating mechanisms, which require significant development cost, making them beyond the reach of most amputees. This research contributes to developing a cost-effective microprocessor-based transfemoral prosthesis by integrating off-the-shelf sensing and actuating mechanisms. Accordingly, a three-level control architecture consisting of top, middle, and low-level controllers was developed for the proposed prosthesis. The top-level controller is responsible for identifying the amputee intent and mode of activity. The mid-level controller determines distinct phases in the activity mode, and the low-level controller was designed to modulate the damping across distinct phases. The developed prosthesis was evaluated on unilateral transfemoral amputees. Since off-the-shelf sensors and actuators are used in i-Inspire, various trials were conducted to evaluate the repeatability of the sensory data. Accordingly, the mean coefficients of correlation for knee angle, force, and inclination were computed at slow and medium walking speeds. The obtained values were, respectively, 0.982 and 0.946 for knee angle, 0.942 and 0.928 for knee force, and 0.825 and 0.758 for knee inclination. These results confirmed that the data are highly correlated with minimum covariance. Accordingly, the sensors provide reliable and repeatable data to the controller for mode detection and intent recognition. Furthermore, the knee angles at self-selected walking speeds were recorded, and it was observed that the i-Inspire Knee maintains a maximum flexion angle between 50° and 60°, which is in accordance with state-of-the-art microprocessor-based transfemoral prosthesis.
Exponential Fusion of Interpolated Frames Network (EFIF-Net): Advancing Multi-Frame Image Super-Resolution with Convolutional Neural Networks
Authors: Elwarfalli Hamed , Flaute Dylan , Hardie Russell C.
Published: January 2024

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel accuracy using an affine motion model to capture the camera platform motion. The frames are externally upsampled using single-image interpolation. The interpolated frames are then fused with the custom EWF layer, employing subpixel registration information to give more weight to pixels with less interpolation error. Realistic image acquisition conditions are simulated to generate training and testing datasets with corresponding ground truths. The observation model captures optical degradation from diffraction and detector integration from the sensor. The experimental results demonstrate the efficacy of EFIF-Net using both simulated and real camera data. The real camera results use authentic, unaltered camera data without artificial downsampling or degradation.
Multi-Frame Content-Aware Mapping Network for Standard-Dynamic-Range to High-Dynamic-Range Television Artifact Removal
Authors: Wang Zheng , He Gang
Published: January 2024

Recently, advancements in image sensor technology have paved the way for the proliferation of high-dynamic-range television (HDRTV). Consequently, there has been a surge in demand for the conversion of standard-dynamic-range television (SDRTV) to HDRTV, especially due to the dearth of native HDRTV content. However, since SDRTV often comes with video encoding artifacts, SDRTV to HDRTV conversion often amplifies these encoding artifacts, thereby reducing the visual quality of the output video. To solve this problem, this paper proposes a multi-frame content-aware mapping network (MCMN), aiming to improve the performance of conversion from low-quality SDRTV to high-quality HDRTV. Specifically, we utilize the temporal spatial characteristics of videos to design a content-aware temporal spatial alignment module for the initial alignment of video features. In the feature prior extraction stage, we innovatively propose a hybrid prior extraction module, including cross-temporal priors, local spatial priors, and global spatial prior extraction. Finally, we design a temporal spatial transformation module to generate an improved tone mapping result. From time to space, from local to global, our method makes full use of multi-frame information to perform inverse tone mapping of single-frame images, while it is also able to better repair coding artifacts.
A Study on E-Nose System in Terms of the Learning Efficiency and Accuracy of Boosting Approaches
Authors: Chang Il-Sik , Byun Sung-Woo , Lim Tae-Beom , Park Goo-Man
Published: January 2024

With the development of the field of e-nose research, the potential for application is increasing in various fields, such as leak measurement, environmental monitoring, and virtual reality. In this study, we characterize electronic nose data as structured data and investigate and analyze the learning efficiency and accuracy of deep learning models that use unstructured data. For this purpose, we use the MOX sensor dataset collected in a wind tunnel, which is one of the most popular public datasets in electronic nose research. Additionally, a gas detection platform was constructed using commercial sensors and embedded boards, and experimental data were collected in a hood environment such as used in chemical experiments. We investigated the accuracy and learning efficiency of deep learning models such as deep learning networks, convolutional neural networks, and long short-term memory, as well as boosting models, which are robust models on structured data, using both public and specially collected datasets. The results showed that the boosting models had a faster and more robust performance than deep learning series models.
Novel Framework for Quality Control in Vibration Monitoring of CNC Machining
Authors: Apostolou Georgia , Ntemi Myrsini , Paraschos Spyridon , Gialampoukidis Ilias , Rizzi Angelo , Vrochidis Stefanos , Kompatsiaris Ioannis
Published: January 2024

Vibrations are a common issue in the machining and metal-cutting sector, in which the spindle vibration is primarily responsible for the poor surface quality of workpieces. The consequences range from the need to manually finish the metal surfaces, resulting in time-consuming and costly operations, to high scrap rates, with the corresponding waste of time and resources. The main problem of conventional solutions is that they address the suppression of machine vibrations separately from the quality control process. In this novel proposed framework, we combine advanced vibration-monitoring methods with the AI-driven prediction of the quality indicators to address this problem, increasing the quality, productivity, and efficiency of the process. The evaluation shows that the number of rejected parts, time devoted to reworking and manual finishing, and costs are reduced considerably. The framework adopts a generalized methodology to tackle the condition monitoring and quality control processes. This allows for a broader adaptation of the solutions in different CNC machines with unique setups and configurations, a challenge that other data-driven approaches in the literature have found difficult to overcome.
Whether Socioeconomic Status Matters in Accessing Residential College: Role of RC in Addressing Academic Achievement Gaps to Ensure Sustainable Education
Authors: Gui Pingping , Alam Gazi Mahabubul , Hassan Aminuddin Bin
Published: January 2024

Following the fourth objective of the United Nations’ Sustainable Development Goals (SDGs), education disparities are one of the most serious issues holding back national development. Despite efforts being made to tackle this discrepancy, it has long been a source of concern for many communities. It is important to note that residential colleges (RCs) have evolved and contributed to higher education for several decades now, aiming to provide an equal and inclusive living and learning environment. Having said that, while disparity is still one of the most challenging issues in this system, it has not been fully examined. Using stratified random sampling on RC students’ data from undergraduate universities piloting RC programs up to 2018 in different parts of China, this study examines the effects of socioeconomic status (SES) on RC access. The study further explores the difference in academic achievement among RC students from diverse SES backgrounds and comprehensively analyzes the impact of RC on sustainable education. The study finds that disparities exist in accessing RC for individuals from varied SES backgrounds. However, RC mitigates the influence of SES on academic achievement to curtail these differences. The findings imply that ensuring access to RC for individuals from underprivileged SES backgrounds should be prioritized to address education-disparity-related challenges.
Statistical Analysis of Climate Trends and Impacts on Groundwater Sustainability in the Lower Indus Basin
Authors: Ahmed Waqas , Ahmed Suhail , Punthakey Jehangir F. , Dars Ghulam Hussain , Ejaz Muhammad Shafqat , Qureshi Abdul Latif , Mitchell Michael
Published: January 2024

Agricultural intensification is increasing global demand for water, with groundwater especially susceptible given its year-round reliability. Climate change impacts on groundwater recharge exacerbate uncertainties for future access and use, especially for large aquifers across alluvial plains such as the Indus Basin of Pakistan. To generate better understanding of climate change impacts on groundwater balances in such contexts, we used MODFLOW 2005 to quantify the groundwater budget of the Northern Rohri Canal Command Area under RCP 4.5 and 8.5 climatic scenarios, while also taking climatic regionalisation into account. Under a baseline scenario, total annual pumping in the northern Rohri command was estimated to be 3.619 billion cubic metres (BCM), and the total net loss in storage over the simulation period from October 2010 to April 2014 was estimated at 1.244 BCM per year. By 2047, net decline in storage is projected to more than double to 2.185 per year under RCP 4.5 scenario and 2.214 under RCP 8.5. Our estimates suggest that a sustainable yield across the command area should be managed at approximately 3 ± 0.3 BCM per year to ensure sufficient adaptive reserves of groundwater for access during times of drought and inadequate surface supply, while also reducing waterlogging impacts from high watertables. This first-time estimate of sustainable yield provides irrigation system managers with an overall guide from which divisional-scale measures to achieve the goal can be identified through stakeholder engagement.
Blockchain Architectures for the Digital Economy: Trends and Opportunities
Authors: Pineda Magda , Jabba Daladier , Nieto-Bernal Wilson
Published: January 2024

The digital economy, driven by information and communication technologies (ICT), has profoundly transformed in recent decades. The digitalization of society has given rise to an economic environment in which information, connectivity, and innovation play fundamental roles. In this context, a technology that has emerged as a fundamental pillar of the digital economy is the chain of blocks, commonly known as blockchain. Blockchain is a technology that has revolutionized the way online data and transactions are managed and shared. Through its ability to create secure, transparent, and decentralized ledgers, blockchain has paved the way for the digital economy, facilitating trust in digital transactions and enabling various applications ranging from cryptocurrencies to supply chain management and intellectual property. This study will delve into blockchain and its influence on the digital economy. It will explore how this technology has reshaped how companies interact, how consumers access services, and how new business models are developed in a constantly evolving digital environment. Additionally, the challenges and opportunities that blockchain presents in the context of the digital economy will be analyzed, and how it is helping to shape the future of business and society in general. As the exploration of blockchain and its impact on the digital economy progresses, it becomes evident how these two forces converge, generating a promising digital landscape full of significant opportunities and transformations. This phenomenon is consistently supported by a growing body of research and analysis, which underlines the growing influence of blockchain on the global economy. The dynamic interplay between these two spheres, blockchain and the digital economy, is constantly evolving and offers an exciting glimpse into the future regarding innovation and disruption across a wide range of sectors. As a result, significant opportunities are looming for those seeking to understand and capitalize on these emerging trends. Throughout this study, the current trends and most intriguing perspectives that shape this landscape will be broken down, offering a deeper insight into how blockchain and the digital economy are shaping an extraordinary digital future.
Progressing from Science Communication to Engagement: Community Voices on Water Quality and Access in Makhanda
Authors: Khumalo Linda , Mickelsson Martin , Fogel Ronen , Mutingwende Nhamo , Madikiza Lwazikazi , Limson Janice
Published: January 2024

The EU’s Responsible Research and Innovation framework advocates for engagement between communities and scientists, creating opportunities for scientific research and processes to be informed and shaped by community voices. To date, few examples in the literature explore this in practice. Hence, key questions remain as to the role that communities play in this framework and the nature of and extent to which community voices and localised perspectives inform research and innovation. This paper explores how a collaborative community engagement process, facilitated at the outset, could meaningfully inform the establishment of a water quality testing facility. In Makhanda, a water-scarce region of South Africa, focus group discussions as well as site visits/observations integrated community and researcher knowledges to shape the community-engaged water testing facility. This study details how the daily assessment of water by the community provided valuable insights to the researchers on the nature and extent of factors affecting water quality and informed the sites and timing of water testing in subsequent scientific measurements of the same. Furthermore, it opened pathways to sustained, longer-term engagement between scientists and communities around water quality, highlighting the need for a multi-stakeholder focus to support community agency around access to safe water.
Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System
Authors: Yao Zhengyi , Tan Liang , Yi Junhao , Fu Luxia , Zhang Zhuang , Tan Xinghong , Xie Jingxue , She Kun , Yang Peng , Wu Wanjing , Ye Danlian , Yu Ziyuan
Published: January 2024

An intelligent logistics system is a production system based on the Internet of Things (IoT), and the logistics information of humans has a high degree of privacy. However, the current intelligent logistics system only protects the privacy of shippers and consignees, without any privacy protection for carriers, which will not only cause carriers’ privacy leakage but also indirectly or directly affect the logistics efficiency. It is particularly worth noting that solving this problem requires one to consider the balance between privacy protection and operational visibility. So, the local privacy protection algorithm ϵ-L_LDP for carriers’ multidimensional numerical sensitive data and ϵ-LT_LDP for carrier location sensitive data are proposed. For ϵ-L_LDP, firstly, a personalized and locally differentiated privacy budgeting approach is used. Then, the multidimensional data personalization perturbation mechanism algorithm L-PM is designed. Finally, the multidimensional data are perturbed using L-PM. For ϵ-LT_LDP, firstly, the location area is matrix-partitioned and quadtree indexed, and the location data are indexed according to the quadtree to obtain the geographic location code in which it is located. Secondly, the personalized random response perturbation algorithm L-RR for location trajectory data is also designed. Finally, the L-RR algorithm is used to implement the perturbation of geolocation-encoded data. Experiments are conducted using real and simulated datasets, the results show that the ϵ-L_LDP algorithm and ϵ-LT_LDP algorithm can better protect the privacy information of carriers and ensure the availability of carrier data during the logistics process. This effectively meets the balance between the privacy protection and operational visibility of the intelligent logistics system.
Significance of Volatile Organic Compounds to Secondary Pollution Formation and Health Risks Observed during a Summer Campaign in an Industrial Urban Area
Authors: Cao Li , Men Qihui , Zhang Zihao , Yue Hao , Cui Shijie , Huang Xiangpeng , Zhang Yunjiang , Wang Junfeng , Chen Mindong , Li Haiwei
Published: January 2024

The chemical complexity and toxicity of volatile organic compounds (VOCs) are primarily encountered through intensive anthropogenic emissions in suburban areas. Here, pollution characteristics, impacts on secondary pollution formation, and health risks were investigated through continuous in-field measurements from 1–30 June 2020 in suburban Nanjing, adjacent to national petrochemical industrial parks in China. On average, the total VOCs concentration was 34.47 ± 16.08 ppb, which was comprised mostly by alkanes (41.8%) and halogenated hydrocarbons (29.4%). In contrast, aromatics (17.4%) dominated the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) with 59.6% and 58.3%, respectively. Approximately 63.5% of VOCs were emitted from the petrochemical industry and from solvent usage based on source apportionment results, followed by biogenic emissions of 22.3% and vehicle emissions of 14.2%. Of the observed 46 VOC species, hexachlorobutadiene, dibromoethane, butadiene, tetrachloroethane, and vinyl chloride contributed as high as 98.8% of total carcinogenic risk, a large fraction of which was ascribed to the high-level emissions during ozone pollution episodes and nighttime. Therefore, the mitigation of VOC emissions from petrochemical industries would be an effective way to reduce secondary pollution and potential health risks in conurbation areas.
The Impact of Underground Structures on Urban Flood Models
Authors: Hauser Martina , Reinstaller Stefan , Oberascher Martin , Muschalla Dirk , Kleidorfer Manfred
Published: January 2024

Owing to climate change, heavy rainfall events have increased in recent years, often resulting in urban flooding. Urban flood models usually consider buildings to be closed obstacles, which is not the case in reality. To address this research gap, an existing 1D/2D model was extended with underground structures. The underground structures were located using site visits, Google Earth, and information provided by the city administration. Control strategies were used to represent partially open doors or tilted windows. The model was simulated with three measured rainfall events in three different scenarios. Scenarios with underground structures resulted in small storage volumes in the structures and a slightly less flooded area on the surface. The assumptions made were analysed using sensitivity analysis. Varying the number and location of underground structures resulted in small variations in the stored volume and surface flood volume. The sensitivity analysis also showed that the thresholds for height and velocity had a large impact, whereas the opening percentage did not influence the number of buildings affected. The conclusion of the study is that the inclusion of underground structures has little effect on the predicted flooded areas but can be useful in quantifying the water depth in potentially vulnerable buildings.
International Perspectives in Education and Communication
Authors: Kefalaki Margarita , Diamantidaki Fotini
Published: January 2024

Rapid technological development, the increasing need for sustainability standards and actions, combined with the constant rise of artificial intelligence (AI), impact all industries and workplaces, including the education sector (Tettamanzi et al., 2023). Our ‘new normal’, after the COVID-19 pandemic, precipitated educators to implement changes to their teaching in order to help them provide an effective educational learning experience (Tettamanzi et al., 2023), hence making it crucial to redefine our approaches, plan, innovate and readjust to all the novel needs. The four research papers of this issue discuss ways in which education professionals and beyond innovate and adapt to a ‘new normal’.
Lost In Space
Authors: Altamirano Michael Anibal
Published: January 2024

College enrollment in the United States has continued to decrease since the pandemic. For colleges and universities, the students who are enrolling face unprecedented challenges, which many university leaders need help understanding and managing. The explorative nature of this study is to examine the traumatic environment of the pandemic on high school students, examining how this trauma has led to the suggested rampant arrested emotional development among said students. Arrested emotional development is attributed to rising cases of immaturity, anger, confusion, and suffering among high school students. Furthermore, the study will examine a connection between underdevelopment and the quality of students currently entering higher education. This investigation endeavors to understand the mindset of future university students and to help leaders of these institutions identify and serve future admits. This research methodology will be a principally qualitative approach consisting of primary information gathered from a culturally diverse sample of interviewed parents, teachers, administrators, and social workers based on their observations. Secondary information illustrates a broader and more global view of this problem. The evidence offered within this study explores an emerging issue that is currently under-researched, with the optimism of proposing opportunities for further exploration.
Perancangan Buku Foto Esai Benteng Kedungcowek Surabaya
Authors: Nugroho Yulius Widi , Magh'firoh Restu Hendriyani , Gerungan Charles Adam
Published: January 2024

Benteng Kedungcowek adalah salah satu bangunan bersejarah yang menjadi saksi bisu peristiwa penting masa lampau di Kota Surabaya. Bangunan ini merupakan peninggalan Hindia Belanda dan digunakan sebagai tempat penyimpanan peluru pada masa penjajahan. Namun sayangnya Benteng Kedungcowek ini sedikit masyarakat yang tau keberadaannya. Untuk memperkenalkan Benteng Kedungcowek kepada remaja usia 18-35 tahun, sebuah buku foto esai dirancang dengan tujuan menyampaikan pesan dan edukasi tentang sejarah bangunan ini secara jelas. Penelitian ini menggunakan metode kualitatif untuk menganalisis dan menggambarkan fenomena di Benteng Kedungcowek. Metode ini melibatkan pengumpulan data melalui wawancara dan pengamatan langsung di lokasi tersebut. Metode perancangan yang digunakan yaitu perencanaan, dengan mengumpulkan data tentang jenis bangunan dan jumlahnya, survei tempat, untuk memastikan izin pemotretan di lokasi yang ditargetkan, pemotretan di beberapa lokasi dalam benteng secara bersamaan, pemilihan foto terbaik untuk dimasukkan ke dalam buku foto esai, pembuatan buku dengan proses editing foto, layouting, dan menulis teks penjelas peristiwa-peristiwa yang ada. Hasil perancangan ini berupa Buku Foto Esai dengan judul Benteng Kedungcowek “Bangunan bersejarah di Surabaya”. Buku memiliki 68 halaman dan berisi foto-foto dari bangunan yang ada dengan penjelasan sejarah, fungsi, dan kegunaan dari bangunan pada saat penjajahan, kemudian dilanjutkan dengan foto pesisir sekitaran benteng, dan yang terakhir ditutup dengan kegiatan masyarakat sekitar yang menjadi kegiatan sehari-sehari masyarakat sekitaran. Selain itu juga terdapat media pendukung yaitu Poster, Notebook, Totebag, Social Media (Instagram), Mug, Keychain, Pin, T-Shirt, X-Banner, dan Topi.
Perancangan Board Game Sebagai Media Pengenalan Tujuh Presiden Indonesia Untuk Anak Usia 10-12 Tahun
Authors: Bangsawan Arjuna , Magh'firoh Restu Hendriyani , Lee Nicolaus Alexander
Published: January 2024

Indonesia dipimpin oleh presiden sebagai kepala negara sekaligus kepala pemerintahan. Sebagai kepala negara, presiden adalah simbol resmi negara Indonesia. Sementara itu, sebagai kepala pemerintahan, presiden dibantu oleh wakil presiden dan menteri-menteri dalam kabinet, memegang kekuasaan eksekutif untuk melaksanakan tugas-tugas pemerintah sehari-hari. Indonesia hingga saat ini telah dipimpin oleh tujuh presiden, dan memiliki pencapaian serta latar belakang yang berbeda-beda. Hal tersebut dapat dijadikan sebagai media pembelajaran kepada anak usia 10-12 tahun guna menanamkan wawasan kebangsaan dan membangun rasa nasionalisme. Dengan membangun rasa nasionalisme pada anak-anak, kita dapat menciptakan generasi yang memiliki koneksi emosional dan tanggung jawab terhadap negara mereka, yang pada gilirannya dapat berkontribusi pada pembangunan masyarakat yang kuat dan berkelanjutan. Perlu adanya media pembelajaran untuk memperkenalkan tujuh presiden Indonesia dengan media yang menyenangkan sehingga dapat menjadi sarana edukasi untuk memperkenalkan tujuh presiden Indonesia. Perancangan ini menggunakan metode penelitian kualitatif, dengan sumber data dari buku, jurnal dan internet. Selain itu melakukan studi komparator dengan board game yang sejenis untuk menggali data melalui analisis SWOT. Tahapan perancangan meliputi pemilihan tema, pemilihan konsep, tahap desain, tahap prototype, hingga tahap akhir. Perancangan ini menghasilkan board game roll and move dengan nama “7 PRESIDEN INDONESIA” yang memiliki komponen board, tujuh pion akrilik, 140 kartu kuis, 28 kartu kesempatan, 28 kartu penyerang, tujuh kartu biografi, 28 token reward, lencana juara pertama, panduan, dadu, dan packaging. Media pendukung yang digunakan berupa stiker, stiker nama, gantungan kunci, pembatas buku, notebook, kaos, totebag, magnet bergambar, x-banner, dan feed instagram. Hasil uji coba yang didapat memberikan hasil bahwa anak mendapatkan edukasi mengenai tujuh presiden Indonesia melalui permainan yang unik disertai dengan presaingan untuk menyelesaikan kuis secepat mungkin dengan bantuan seperti kartu kesempatan dan kartu penyerang.
Application of Fuzzy Tsukamoto Method to Rainfall Prediction in Sleman Regency
Authors: Panuntun Rizky Diar , Hermawan Arief
Published: January 2024

The context of this research is that erratic rainfall can disrupt community activities, especially for traders who want to make sales. In addition, information about rainfall is also needed by farmers in determining planting patterns in order to get maximum yields. The purpose of this research is to be able to help farmers predict rainfall to get maximum crop yields. One method to be able to predict rainfall is Fuzzy Logic. This research will use the Tsukamoto Fuzzy method. In the research conducted this time, the author conducted monthly rainfall forecasting in Sleman Regency. Rainfall data in Sleman Regency from 2015 to 2022 will be used in this research. This research succeeded in getting a MAPE value of 49.31%. The result of this research is the highest monthly rainfall prediction in November, with a rainfall of 713.78 mm. At the same time, the lowest occurred in August, which amounted to 36.47 mm. This research only gets a MAPE value of 49.31%. So it can be concluded that the Tsukamoto fuzzy method cannot predict rainfall well.
Retinoblastoma and its adverse events experienced
Authors: Chee Variant Nee Vern , Chan Li Yen , Ismail Fazliana Binti , Rahmat Jamalia
Published: January 2024

Background: Retinoblastoma management has seen a paradigm shift with intra-arterial chemotherapy (IAC). Using IAC as primary management in this paediatric cancer is becoming more widespread in developing countries such as Malaysia. Considerable evidence shows that IAC has a more beneficial globe salvage rate thanintravenous chemotherapy (IVC).

Case presentation: This case report describes a successful globe salvage in Group D retinoblastoma with primary IAC and the complications experienced with this mode of treatment, especially the vascular events seen which could possibly contribute to persistent poor vision despite a completely regressed tumour.

Conclusion: Despite the remarkable tumour regression and globe preservation, the patient’s vision did not improve in the treated eye. We wish to explore the possibilities resulting in those complications and methods to reduce them in the future.
Sosialisasi dan Pelatihan Secure Computer dalam Meningkatan Kesadaran Siswa terhadap Keamanan Data
Authors: Sapriadi Sopi , Eko Syaputra Aldo , Septi Eirlangga Yofhanda , Hariani Manurung Kiki , Hayati Nova
Published: January 2024

Meningkatnya jumlah kejahatan cyber yang terjadi dan makin berkembangnya teknik-teknik dan tools serta produk perangkat lunak yang dikembangkan untuk mengotomatisasi tindakan kejahatan cyber (virus, malware, trojan, dll) mengindikasikan bahwa perlu adanya tindakan optimal dari user dalam menjaga keamanan komputer dan informasi dari para pengguna teknologi. Sosialisasi terhadap bahaya kejahatan cyber dan pentingnya menjaga keamanan data dan informasi harus dilakukan terhadap seluruh kalangan pengguna teknologi sedini mungkin. Dalam prakteknya penggunaan teknologi semakin pesat, terutama dikalangan anak muda yang baru duduk dibangku sekolah. Hal ini timbul dikarenakan saat proses belajar mengajar interaksi guru dengan siswa cenderung melibatkan teknologi dalam penyampaian informasi dan berbagi ilmu teknologi diera sekarang. Dari pertimbangan tersebut, maka timbul sebuah gagasan untuk memberikan sosialisasi computer secure user kepada siswa siswi jurusan Multimedia dan Teknik Komputer Jaringan di SMK Negeri 1 Gunung Talang. Tujuan dari program sosialisasi secure computer user ini adalah untuk memberikan para siswa-siswi pengetahuan dan keterampilan yang diperlukan untuk melindungi aset informasinya dengan membenamkan siswa ke lingkungan interaktif dimana mereka akan memperoleh pemahaman mendasar tentang berbagai ancaman keamanan komputer dan jaringan. Hasil sosialisasi ini berupa demonstrasi cara mengamankan komputer dan informasi yang dimiliki oleh siswa yang mampu mencegah penyalahgunaan informasi yang dimiliki oleh siswa dan siswi jurusan Multimedia dan Teknik Komputer Jaringan Pada SMK 1 Gunung Talang.
Perancangan Artbook Kisah Pangeran Diponegoro untuk Anak Usia 9-10 Tahun
Authors: Keytimu Jovancha , Siswo Martono  , Evi Farsiah Utami
Published: January 2024

Pahlawan Nasional merupakan sebuah gelar penghargaan yang diberikan kepada rakyat, sebagai tanda penghormatan untuk mengenang jasa mereka yang telah rela berkorban demi Tanah Air Indonesia. Salah satu Pahlawan Nasional yang telah berjasa untuk Negara Indonesia adalah Pangeran Diponegoro. Pangeran Diponegoro merupakan salah satu Tokoh Pahlawan Nasional yang berasal dari Yogyakarta. Akan tetapi, hampir 65% anak usia 9-10 tahun tidak mengenal Pangeran Diponegoro dan 70% anak-anak tidak mengetahui kisah dari Pangeran Diponegoro. Bahkan, mereka lebih menyukai buku- buku yang berjenis cerita bergambar, komik, ilustrasi, dongeng dan anime. Ditambah karakter pahlawan yang mereka idolakan seperti Captain America, Superman, Batman, Iron Man, Aquaman, Wonder Woman dan Hulk. Agar anak-anak usia 9-10 tahun dapatmengenal Pangeran Diponegoro, maka dirancanglah sebuah artbook dengan teknik digital painting. Metode yang digunakan adalah metode kualitatif. Dimana teknik pengumpulan data yang dilakukan dengan cara observasi, wawancara, angket dan dokumentasi. Sehingga, menghasilkan konsep karya excitement yang memberikan arti semangat, antusias, rasa gembira dan rasa tertarik. Konsep excitement ini diimplementasikan dalam alur cerita, elemen desain, layout, tipografi dan warna. Perancangan artbook dengan teknik digital painting ini berisi kumpulan-kumpulan gambar ilustrasi, yang menceritakan lahirnya Pangeran Diponegoro hingga terjadinya Perang Jawa. Dengan adanya artbook ini, dapat menambah pengetahuan, meningkatkan minat baca dan memberikan pesan moral bagi anak-anak.
Analisis Desain Permainan Generate the Game of Energy Choices
Authors: Elizabeth Susanti  , Paul Martin
Published: January 2024

Global warming/pemanasan global merupakan fenomena alam yang terjadi oleh akibat meningkatnya konsentrasi gas rumah kaca dalam atmosfer bumi yang diakibatkan oleh aktivitas manusia. Dalam mendesain permainan papan penggabungan beberapa elemen tersebut harus dirancang dengan matang, karena selain memiliki fokus untuk dapat menampilkan estetika dari permainan papan tersebut, tetapi desain harus dapat membantu pemain dalam mengidentifikasi karakter dan bagian-bagian aset dari permainan tersebut.Dalam penelitian ini akan diterapkan metode penelitian kualitatif, dengan melakukan penelitian dari beberapa artikel desain game, artikel psikologi desain dan game, dan lain sebagainya. Tentunya dengan mempelajari artikel-artikel dan beberapa kasus. Hasil dari penelitian yang telah dilakukan pada artikel akan disampaikan ulang dengan metode analisis naratif. Pada hasil penelitian ini desain dari permainan Generate akan menjadi pembahasan utama, desain akan dibahas mulai dari desain permainan itu sendiri hingga beberapa alternatif desain yang sekiranya dapat diaplikasikan ke dalam permainan ini. Mulai dengan skenario biaya terendah hingga penggunaan emisi karbon terendah. Hal ini memberikan kesimpulan baru, bahwa desain selain berkembang dikarenakan kebutuhan estetika, desain juga berkembang oleh karena perkembangan teknologi dan jaman.Kesimpulan dari artikel ini, permainan papan Generate memiliki sistem permainan yang cukup mumpuni, namun tidak dengan desainnya. Beberapa eksplorasi desain yang dapat dilakukan di antaranya, ada perombakan aset-aset dari papan board game biasa yang menggunakan kartu dan angka-angka tertulis biasa sebagai bagian permainan, dapat dirubah menjadi aset dengan 3D. Dengan desain yang menarik juga, diharapkan banyak yang tertarik pada permainan, sehingga kampanye energi terbarukan yang tersirat dalam permainan ini pun dapat tersampaikan dengan baik.
Strategi Penyediaan Fasilitas Ruang Publik Inklusif di Kota Lama Semarang Berdasarkan Persepsi dan Preferensi Lansia
Authors: Pradana Valian Aulia , Suwandono Djoko , Nurini Nurini
Published: January 2024

A good public space must be friendly and accommodating to everyone, including the elderly. Elderly is a group that has limitations when they are in public spaces because of their different needs. To find out the needs of the elderly in public spaces, it is necessary to understand their perceptions and preferences for the facilities provided so that the elderly do not need to adapt. The purpose of this study is to determine the perceptions and preferences of the elderly in the provision of inclusive public spaces in Kota Lama Semarang. Analysis of the perceptions and preferences of the elderly was carried out on three aspects, namely accessibility, comfort and safety. Data collection was carried out through filling out questionnaires by 60 elderly in Kota Lama Semarang area. This study uses Likert scale as measuring tool for the perceptions and preferences of the elderly. The conclusion from the three aspects studied, the perception of the elderly in the condition of public space facilities shows that there are advantages and disadvantages. While the preferences of the elderly in the provision of public space facilities show that the elderly agree if procurement, additions, or improvements to facilities related to the three aspects studied. The strategy for providing inclusive public space facilities can follow the standards or best practices in other cities or countries, but does not leave the classic nuance which is the identity of the Kota Lama Semarang.
Menakar Peran Persepsi Harga dalam Penciptaan Keputusan Pembelian Jasa Wisata
Authors: Kurniawati Emaya , Santoso Aprih
Published: January 2024

This research located in Mangkang Zoo. The aim of the research is to evaluate services that influence the decision to purchase tourism services at the Mangkang Zoo, Semarang, by considering perceptions of price as a moderating factor. This research shows that service quality has an impact on purchasing decisions at the Mangkang Zoo, Semarang. Meanwhile, other findings, namely price perception, show that service quality has an influence on purchasing decisions, with price as a mediating variable at the Mangkang Zoo, Semarang. This illustrates that management has succeeded in implementing an appropriate pricing policy, including in terms of price levels, special price offers, payment processes, payment terms, all of which are in line with the quality of the services provided. The population studied was visitors who decided to use tourist services at the Mangkang Zoo, Semarang, with an unspecified number. The sampling method was carried out by chance and involved 100 respondents. The research results are that service quality has an impact on the decision to purchase tourism services at the Mangkang Zoo, Semarang. Furthermore, perceptions of price also have a positive and significant influence in strengthening the correlation between service quality and purchasing decisions for tourism services at the Mangkang Zoo, Semarang.