bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Decompression and Rasterization of Massive Point Clouds
Authors: Goel Rahul , Schütz Markus , Narayanan P. J. , Kerbl Bernhard
Published: August 2024

Large-scale capturing of real-world scenes as 3D point clouds (e.g., using LIDAR scanning) generates billions of points that are challenging to visualize. High storage requirements prevent the quick and easy inspection of captured datasets on user-grade hardware. The fastest real-time rendering methods are limited by the available GPU memory and render only around 1 billion points interactively. We show that we can achieve state-of-the-art in both while simultaneously supporting datasets that surpass the capabilities of other methods. We present an on-the-fly point cloud decompression scheme that tightly integrates with software rasterization to reduce on-chip memory requirements by more than 4×. Our method compresses geometry losslessly and provides high visual quality at real-time framerates. We use a GPU-friendly, clipped Huffman encoding for compression. Point clouds are divided into equal-sized batches, which are Huffman-encoded independently. Batches are further subdivided to form easy-to-consume streams of data for massively parallel execution. The compressed point clouds are stored in an access-aware manner to achieve coherent GPU memory access and a high L1 cache hit rate at render time. Our approach can decompress and rasterize up to 120 million Huffman-encoded points per millisecond on-the-fly. We evaluate the quality and performance of our approach on various large datasets against the fastest competing methods. Our approach renders massive 3D point clouds at competitive frame rates and visual quality while consuming significantly less memory, thus unlocking unprecedented performance for the visualization of challenging datasets on commodity GPUs.
Photon-Driven Manifold Sampling
Authors: Lee Fei , Jhang Jia-Wun , Chang Chun-Fa
Published: August 2024

Complex lighting phenomenon such as the caustics often arises from specular chains of varying lengths. Thanks to recent advancement in specular light transport, we are able to address most effects caused by shorter specular chains using root-finding techniques. However, finding longer chains of valid specular interaction still remains problematic due to the curse of dimensionality. This creates a difficulty for methods that depend on random sampling to navigate the path space.

In this paper, we present Photon-Driven Manifold Sampling (PMS), an unbiased method designed for sampling multi-bounce caustics, derived from Specular Manifold Sampling (SMS). We achieve efficient caustic rending through the combination of photon mapping and path space manifold exploration. Our method, inspired by recent advancements in path reusing techniques, caches multi-bounce caustic photons with the aim of reusing their vertices to seed local exploration via manifold walk. This eliminates the necessity for additional random sampling in seed path sampling as seen in alternative methods that took the guiding approach. Our results highlight a notable decrease in variance compared to other state-of-the-art techniques and demonstrate the adaptability to intricate specular chains.
Aliasing Detection in Rendered Images via a Multi-Task Learning
Authors: Fan Shu-Ho , Hsiao Kai-Wen , Tan Kai Yi , Yao Chih-Yuan , Chu Hung-Kuo
Published: August 2024

As technology advances from simple 2D designs to intricate 3D environments, the demand for high-quality visuals in video games and interactive media necessitates robust image quality assessment (IQA) techniques. Traditional methods like PSNR and SSIM, reliant on reference images, struggle with the unique challenges of 3D rendered content, highlighting the need for specialized non-reference IQA approaches. This paper introduces a novel multi-task learning architecture that corrects and predicts aliasing artifacts simultaneously, enhancing predictive accuracy without reference images. It also incorporates temporal information to improve visual coherence and smoothness. An automated labeling pipeline developed using Unity ensures a stable and unbiased dataset for model training and evaluation. Our experiments demonstrate that this approach reliably detects aliasing across various complexities, achieving state-of-the-art performance. By addressing specific challenges in rendered image assessment and leveraging innovative learning techniques, our work advances IQA for video games and simulations, ensuring high visual quality.
DGF: A Dense, Hardware-Friendly Geometry Format for Lossily Compressing Meshlets with Arbitrary Topologies
Authors: Barczak Joshua , Benthin Carsten , McAllister David
Published: August 2024

The widespread availability of hardware accelerated ray tracing solutions is driving a gradual sea-change in the real-time graphics space. The major graphics APIs now offer standardized support for accelerated ray tracing. In the same time frame, rasterization-based systems such as Nanite [Karis et al. 2021] have significantly raised geometric complexity in games. The state of the art in raster graphics now enables lossy compressed geometry representations that are decoded on the-fly during rendering. This trend conflicts with current ray tracing interfaces, which require opaque acceleration structures to be built from uncompressed input data. This paper seeks to close the gap by defining a block-compressed geometry format that is designed for arbitrary geometry topologies and can be directly consumed by future fixed-function hardware.
Succinct Opacity Micromaps
Authors: Waldemarson Gustaf , Doggett Michael
Published: August 2024

Alpha masked geometry such as foliage has long been one of the trickier things to render efficiently, both for rasterization based approaches and for hardware accelerated ray-tracing. Recently, a new type of primitive was introduced to the Vulkan® and DirectX® ray-tracing APIs that promises to alleviate this issue: Opacity Micromaps, a structure that uses a bit of extra memory as hints to the pipeline when it should actually call the AnyHit-shader. In this paper, we extend this primitive with a novel compression method that uses the concept of succinct 4-way trees to reduce the memory footprint by up to 110 times, including an algorithm for looking up micromap values directly from this compressed form. Further, we perform a comprehensive analysis of the generated micromaps to demonstrate their performance in terms of both memory footprint and frame render time compared to a number of similar structures. Finally, we highlight some aspects of the extension that developers and artists should be aware of to make the most out of it.
GigaVoxels DP: Starvation-Less Render and Production for Large and Detailed Volumetric Worlds Walkthrough
Authors: Richermoz Antoine , Neyret Fabrice
Published: August 2024

Using voxel hierarchies as a generic 3D scene representation makes ray marching, antialiasing, and LOD easy. The drawback is the huge amount of memory required to store voxels, even with empty space compression. Still, GigaVoxels [Crassin et al. 2009] showed that by using a ray-guided cache to produce and store only visible voxels bricks on demand, it is possible to walk through very large and detailed worlds with real-time performance in bounded GPU memory. However, on-demand production of data during rendering is still challenging in terms of synchronization and starvation of GPU cores. We propose a new GPU-driven algorithm using dynamic parallelism (DP) to minimize these, and a "GPU-cores timeline" profiling tool to analyze them. We validate our model with timings (2× gain) and we illustrate it on various scenes.
GPU-friendly Stroke Expansion
Authors: Levien Raph , Uguray Arman
Published: August 2024

Vector graphics includes both filled and stroked paths as the main primitives. While there are many techniques for rendering filled paths on GPU, stroked paths have proved more elusive. This paper presents a technique for performing stroke expansion, namely the generation of the outline representing the stroke of the given input path. Stroke expansion is a global problem, with challenging constraints on continuity and correctness. Nonetheless, we implement it using a fully parallel algorithm suitable for execution in a GPU compute shader, with minimal preprocessing. The output of our method can be either line or circular arc segments, both of which are well suited to GPU rendering, and the number of segments is minimal. We introduce several novel techniques, including an encoding of vector graphics primitives suitable for parallel processing, and an Euler spiral based method for computing approximations to parallel curves and evolutes.
SAH-Optimized k-DOP Hierarchies for Ray Tracing
Authors: Káčerik Martin , Bittner Jiří
Published: August 2024

We revisit the idea of using hierarchies of k-sided discrete orientation polytopes (k-DOPs) for ray tracing. We propose a method for building a k-DOP-based bounding volume hierarchy while optimizing its topology using the surface area heuristic. The key component of our method is a fast and exact algorithm for evaluating the surface area of a 14-DOP combined with the parallel locally ordered clustering algorithm (PLOC). Our k-DOP PLOC builder has about 40% longer build times than AABB PLOC, but for scenes with oblong slanted objects, the resulting BVH provides up to 2.5x ray tracing speedup over AABB BVH. We also show that k-DOPs can be used in combination with other techniques, such as oriented bounding boxes (OBBs). Transforming k-DOP BVH into OBB BVH is straightforward and provides up to 12% better trace times than the transformation from AABB to OBB BVH.
The Ecosystem Ecology of Coral Reefs Revisited
Authors: Allgeier Jacob E.
Published: August 2024

Early studies in coral reefs showed that simple measurements of ecosystem metabolism (primary production and ecosystem respiration) were useful for understanding complex reef dynamics at an ecosystem scale. These studies also helped establish the field of ecosystem ecology, but contemporary coral reef ecology has shifted away from these origins. In this manuscript, I describe the historical development of a theory of ecosystem metabolism that was foundational for the discipline of ecosystem ecology, and I update this theory to fully incorporate dynamics on coral reefs (and all ecosystems). I use this updated theory to (a) identify important controls on coral reef processes and (b) provide a rationale for patterns of coral reef carbon dynamics that allow me to generate hypotheses of coral reef ecosystem production. I then use existing data to broadly evaluate these hypotheses. My findings emphasize the importance of integrating measurements of ecosystem metabolism with current approaches to improve the development of theory and the efficacy of conservation and management of coral reefs.
Methanobactins: Structures, Biosynthesis, and Microbial Diversity
Authors: Reyes Reyvin M. , Rosenzweig Amy C.
Published: August 2024

Methanobactins (Mbns) are ribosomally synthesized and posttranslationally modified peptide natural products released by methanotrophic bacteria under conditions of copper scarcity. Mbns bind Cu(I) with high affinity via nitrogen-containing heterocycles and thioamide groups installed on a precursor peptide, MbnA, by a core biosynthetic enzyme complex, MbnBC. Additional stabilizing modifications are enacted by other, less universal biosynthetic enzymes. Copper-loaded Mbn is imported into the cell by TonB-dependent transporters called MbnTs, and copper is mobilized by an unknown mechanism. The machinery to biosynthesize and transport Mbn is encoded in operons that are also found in the genomes of nonmethanotrophic bacteria. In this review, we provide an update on the state of the Mbn field, highlighting recent discoveries regarding Mbn structure, biosynthesis, and handling as well as the emerging roles of Mbns in the environment and their potential use as therapeutics.
Bonded Bipolar Plate-Graphite Felt Components for Redox Flow Batteries Manufactured via Thermal Fusion by Electro-Welding
Authors: Germer Wiebke , Satola Barbara , Schillert Leif-Arvid , Gupta Gaurav , Uhlig Lisa M. , N. Nambi Krishnan
Published: August 2024

Bipolar plates and graphite felt electrodes were thermally fused to one single component via a newly developed electro-welding process. A dropwise arrangement of the polymeric binder led to mechanically stable bonding and was documented by X-ray micro-computed tomography. Electrical conductivity of the fused components was achieved without any conductive filler and electro-welded samples show lower resistance values than unbonded ones at the same graphite felt electrode compression of 5% in ex situ electrical conductivity measurements. Applicability was demonstrated in situ in a 2-cell vanadium redox flow battery stack operated at a graphite felt electrode compression rate of 5% only. Obtained energy efficiencies of the battery are at least equal or even higher compared to state of the art vanadium redox flow battery with unbonded components at 20% graphite felt electrode compression. Composite components will simplify stack assembly and their increased electrode porosity during operation is expected to reduce pressure drop and to increase overall system efficiency.
An Expanded hp‐Method for Solving Nonsmooth Time Delay Optimal Control Problems
Authors: Hedayati M. , Ahsani Tehrani H. , Fakharzadeh J. A. , Noori Skandari M. H.
Published: August 2024

In this research, we present an expanded hp‐method for solving time delay optimal control (TDOC) problems, applicable to issues with both smooth and nonsmooth solutions. The method discretizes the time domain using an adaptive grid with unknown switch points. Subsequently, we use the operational integration matrix to approximate the problem’s state variable derivative. Next, we approximate the state and control variables using the Legendre–Gauss–Lobatto points and Legendre spectral collocation. This formulation transforms the original problem into a nonlinear programming problem, solvable using relevant techniques. To demonstrate the efficacy of the proposed method, we solve numerical examples and compare the obtained results with those of several exiting methods.
Succession Planning and Leadership Development in Nursing: A Bibliometric Analysis (2000–2023)
Authors: Al Hajri Azza K.
Published: August 2024

Succession planning is a commonly employed term in business strategy, referring to the systematic process of transferring leadership responsibilities to another employee to ensure the seamless continuity of an organization’s operations. Today, this concept has acquired importance in various industries, including healthcare, with a specific focus on nursing. Several factors led nurse managers to consider preparing potential leaders for primary leadership roles due to the shortage of nurses, significantly impacting healthcare services and patient safety. Because of the importance of this topic, this present bibliometric analysis aims to analyze research studies conducted on succession planning and leadership development in nursing from 2000 to 2023 to identify research trends, key themes, and the evolution of research during this period. The Elsevier Scopus database was utilized for this analysis. This methodology identified (n = 326) journal studies based on the predefined keywords and timeframe. The data derived from this bibliometric analysis offers a robust foundation for conducting a systematic review, enabling a comprehensive synthesis and evaluation of the evidence in this significant field of study.
Machine Learning‐Based Prediction of Parking Space Availability in IoT‐Enabled Smart Parking Management Systems
Authors: Dahiya Anchal , Mittal Pooja , Sharma Yogesh Kumar , Lilhore Umesh Kumar , Simaiya Sarita , Ghith Ehab , Tlija Mehdi
Published: August 2024

Parking space management has become a critical challenge in urban areas due to increasing vehicle numbers and limited parking infrastructure. This paper presents a comprehensive study of machine learning (ML) models in IoT‐enabled environments focusing on proposing an ML‐based model for predicting available parking space. The study evaluates the performance of various models including K‐nearest neighbors (KNNs), support vector machines (SVMs), random forest (RF), decision tree (DT), logistic regression (LR), and Naïve Bayes (NB) based on “precision, recall, accuracy, and F1‐score performance metrics”. The results obtained by implementing ML models on the data with 65% and 85% threshold values are compared to draw meaningful conclusions regarding their performance in predicting parking space availability. Among the evaluated models, random forest (RF) demonstrates superior performance with high precision, recall, accuracy, and F1‐score values. It showcases its effectiveness in accurately predicting parking space availability in the IoT‐enabled environment. On the other hand, models such as K‐nearest neighbors (KNNs), decision tree (DT), logistic regression (LR), and Naïve Bayes (NB) show relatively lower performance in complex parking scenarios. The paper concludes that the use of advanced predictive models, particularly random forest, significantly enhances the accuracy and reliability of IoT‐enabled parking management systems and also reduces the waiting time of the vehicles, leading to more efficient resource utilization, reduced traffic congestion in real‐time scenarios, and better user satisfaction in the IoT‐enabled environment.
A Hospital‐Based Nursing Study on Intention to Leave Job and Nurse‐Physician Collaboration
Authors: Mercan Baspinar Melike , Birer Zerafet , Demiray Sevgi , Basar Hakan , Adas Gokhan Tolga
Published: August 2024

Aim. To explore factors influencing Turkish nurses’ intention to leave job, including nurse‐physician collaboration level, workplace’s environment issues, job satisfaction components, and the effects of the COVID‐19 pandemic. Methods. A cross‐sectional hospital‐based nursing study was conducted between 1 April and 1 May 2022. The data were gathered using a self‐administered questionnaire including sociodemographic variables, region of childhood, priorities on job expectations, self‐score of job satisfaction level (0–10 points), intention to leave scale score, and nurse‐physician collaboration scale score. The E‐PICOS statistic program was used for descriptive and correlation analyses exploring data. Results. A total of 325 nurses were enrolled with an average age of 29.71 ± 6.39 and work experience of 7.88 ± 7.15 years. Female (73.5%) and male (26.5%) nurses had similar levels of intention to leave (p = 0.078). The most frequent priorities on job expectations were high salary (40.3%) and well‐planned working hours (26.8%), respectively. Priority rate on job expectations about academic advancement opportunities was seen in 17.5% of all. Participating in joint doctor‐nurse visits more than nurse‐nurse working and work experience time significantly impacted satisfaction (p = 0.012; p = 0.027, respectively). Job satisfaction has a positive relationship with a high level of socioeconomic and physical environment in workplace’s environment characteristics (p = 0.035; r = 0.117) and a negative relationship with intention to leave the job (p < 0.001; r = −0.502). No correlation was found between an increased intention to leave and poorer collaboration between nurses and physicians (p = 0.370; r = −0.050). Despite the lack of significance, nurses who prioritize organizational culture and brand in their workplace expectations and who work in COVID‐19 areas reported higher job satisfaction than others (p = 0.133; p = 0.133, respectively). Furthermore, nurses who grew up in the Aegean Region, a highly developed part of the country, displayed the highest intention to leave and the lowest job satisfaction (p = 0.214, p = 0.359, respectively). Conclusions. Nurses’ intention to leave job negatively correlates with job satisfaction, regardless of level of nurse‐physician collaboration. Additionally, variations in the intention to leave based on regions of upbringing highlight the importance of human resources based on geographical and cultural development levels.
KRAS-Driven Tumorigenesis and KRAS-Driven Therapy in Pancreatic Adenocarcinoma
Authors: Than Minh T. , O’Hara Mark , Stanger Ben Z. , Reiss Kim A.
Published: August 2024

Pancreatic ductal adenocarcinoma (PDAC) is associated with significant morbidity and mortality and is projected to be the second leading cause of cancer-related deaths by 2030. Mutations in KRAS are found in the vast majority of PDAC cases and plays an important role in the development of the disease. KRAS drives tumor cell proliferation and survival through activating the MAPK pathway to drive cell cycle progression and to lead to MYC-driven cellular programs. Moreover, activated KRAS promotes a protumorigenic microenvironment through forming a desmoplastic stroma and by impairing antitumor immunity. Secretion of granulocyte-macrophage colony-stimulating factor and recruitment of myeloid-derived suppressor cells and protumorigenic macrophages results in an immunosuppressive environment while secretion of secrete sonic hedgehog and TGFβ drive fibroblastic features characteristic of PDAC. Recent development of several small molecules to directly target KRAS marks an important milestone in precision medicine. Many molecules show promise in preclinical models of PDAC and in early phase clinical trials. In this review, we discuss the underlying cell intrinsic and extrinsic roles of KRAS in PDAC tumorigenesis, the pharmacologic development of KRAS inhibition, and therapeutic strategies to target KRAS in PDAC.
Table S7 from p53R172H and p53R245W Hotspot Mutations Drive Distinct Transcriptomes in Mouse Mammary Tumors Through a Convergent Transcriptional Mediator
Authors: McDaniel Joy M. , Morrissey Rhiannon L. , Dibra Denada , Patel Lalit R. , Xiong Shunbin , Zhang Yun , Chau Gilda P. , Su Xiaoping , Qi Yuan , El-Naggar Adel K. , Lozano Guillermina
Published: August 2024

FIMO results summarizing Nr5a2 motif occurrences upstream of p53R245W target gene(s) promoters.
Supplementary Fig. 5 from Tumor Vessel Normalization via PFKFB3 Inhibition Alleviates Hypoxia and Increases Tumor Necrosis in Rectal Cancer upon Radiotherapy
Authors: Edelmann Marcus , Fan Shuang , De Oliveira Tiago , Goldhardt Tina , Sartorius Dorothée , Midelashvili Teona , Conrads Karly , Paul Niels B. , Beißbarth Tim , Fleischer Johannes R. , Blume Moritz L. , Bohnenberger Hanibal , Josipovic Natasa , Papantonis Argyris , Linnebacher Michael , Dröge Leif H. , Ghadimi Michael , Rieken Stefan , Conradi Lena-Christin
Published: August 2024

Supplementary Fig. 5
Table 1 from p53R172H and p53R245W Hotspot Mutations Drive Distinct Transcriptomes in Mouse Mammary Tumors Through a Convergent Transcriptional Mediator
Authors: McDaniel Joy M. , Morrissey Rhiannon L. , Dibra Denada , Patel Lalit R. , Xiong Shunbin , Zhang Yun , Chau Gilda P. , Su Xiaoping , Qi Yuan , El-Naggar Adel K. , Lozano Guillermina
Published: August 2024

Tumors Used in Study
Figure 2 from Tumor Vessel Normalization via PFKFB3 Inhibition Alleviates Hypoxia and Increases Tumor Necrosis in Rectal Cancer upon Radiotherapy
Authors: Edelmann Marcus , Fan Shuang , De Oliveira Tiago , Goldhardt Tina , Sartorius Dorothée , Midelashvili Teona , Conrads Karly , Paul Niels B. , Beißbarth Tim , Fleischer Johannes R. , Blume Moritz L. , Bohnenberger Hanibal , Josipovic Natasa , Papantonis Argyris , Linnebacher Michael , Dröge Leif H. , Ghadimi Michael , Rieken Stefan , Conradi Lena-Christin
Published: August 2024

3PO reduces colorectal cancer cell invasion and endothelial cell sprouting capabilities. A, Invasion assay performed with HCT-116, HT-29, SW-1463, and SW-837 cancer cells. Cells were plated in a Boyden multi-well chamber and treated with 10 µmol/L 3PO for a period of 96 hours. Data are displayed as means SD, n = 3. ∗∗, P < 0.01; ∗∗∗∗, P < 0.0001; Student t test. B, Representative pictures of migration assay performed with SW-837 treated with 10 and 25 µmol/L 3PO; 0 and 30 hours after removing culture inserts. C, Cell migration assay quantification of SW-837 treated with different concentrations of 3PO for 48 hours. Data are displayed as means ± SD, n = 3. D, Relative mRNA expression levels of PAXILLIN, CDC42, and WASF-1 in SW-837 cells treated with different concentrations of 3PO after 72 hours. Data are displayed as means SD, ∗, P < 0.05; ∗∗, P < 0.01; one-way ANOVA. E, Representative pictures of cell sprouting assay performed with HUVECs treated with 10 and 20 µmol/L 3PO after 0 and 24 hours. F and G, Sprouting assay quantification of HUVECs upon PFKFB3 inhibition. Sprouting length, vessel number, and EC proliferation analyzed upon treatment with 10 and 20 µmol/L 3PO for a period of 24 hours. H, Sprouting length quantification upon 24 hours of 3PO treatment on already established spheroids. Data are displayed as means SD, n = 3. ∗∗∗, P < 0,001; ∗∗∗∗, P < 00,001; one-way ANOVA.
Data from p53R172H and p53R245W Hotspot Mutations Drive Distinct Transcriptomes in Mouse Mammary Tumors Through a Convergent Transcriptional Mediator
Authors: McDaniel Joy M. , Morrissey Rhiannon L. , Dibra Denada , Patel Lalit R. , Xiong Shunbin , Zhang Yun , Chau Gilda P. , Su Xiaoping , Qi Yuan , El-Naggar Adel K. , Lozano Guillermina
Published: August 2024

Abstract
Aggressive breast cancers harbor TP53 missense mutations. Tumor cells with TP53 missense mutations exhibit enhanced growth and survival through transcriptional rewiring. To delineate how TP53 mutations in breast cancer contribute to tumorigenesis and progression in vivo, we created a somatic mouse model driven by mammary epithelial cell-specific expression of Trp53 mutations. Mice developed primary mammary tumors reflecting the human molecular subtypes of luminal A, luminal B, HER2-enriched, and triple-negative breast cancer with metastases. Transcriptomic analyses comparing MaPR172H/− or MaPR245W/− mammary tumors to MaP−/− tumors revealed (1) differences in cancer-associated pathways activated in both p53 mutants and (2) Nr5a2 as a novel transcriptional mediator of distinct pathways in p53 mutants. Meta-analyses of human breast tumors corroborated these results. In vitro assays demonstrate mutant p53 upregulates specific target genes that are enriched for Nr5a2 response elements in their promoters. Co-immunoprecipitation studies revealed p53R172H and p53R245W interact with Nr5a2. These findings implicate NR5A2 as a novel mediator of mutant p53 transcriptional activity in breast cancer.
Significance:
Our findings implicate NR5A2 as a novel mediator of mutant p53 transcriptional activity in breast cancer. NR5A2 may be an important therapeutic target in hard-to-treat breast cancers such as endocrine-resistant tumors and metastatic triple-negative breast cancers harboring TP53 missense mutations.
Comparison of proposed electricity billing mechanism for residential clients of Maharashtra
Authors: Belge Archana Talhar , Bodkhe Sanjay , Alegavi Sujata , Ravankar Arpit , Kasturiwale Hemant , Ranjan Alok
Published: August 2024

The comparison of three modified electricity billing mechanisms (model I, model II, and model III) for low tension (LT-I) residential consumers of Maharashtra, India, is presented in this paper. Models I and II are presented in detail along with the results in the previous version of this paper in the year 2020 and year 2022. In continuation of this work, model III is presented in this paper in the year 2023. The main components of this mechanism are traditional billing, time-of-day billing, and an optional facility to use renewable energy by implementing net metering. The combination of these elements generates three distinct billing mechanisms. These have several advantages, like the profits of the existing mechanism, renewable integration, grid stability, demand management, cost saving, environmental benefits, and customer empowerment. The projected billing mechanism is developed and implemented in MATLAB software, and a real-time application is created. The comparison between these three mechanisms helps in giving the best mechanism with respect to residential consumers. Lastly, the philosophy for the future extension to this work is presented which is based on the concept of overseas billing mechanism i.e., seasonal time of day tariff of Sacramento Municipal Utility District and Arizona Public Service.
Simulation of losses in a three-phase bank of transformers in the presence of harmonic distortion
Authors: Grau-Merconchin Frank , Hernández Areu Orestes , Nuñez Alvarez José Ricardo , Montenegro-Romero Michael , Quintero-Ospino Oscar
Published: August 2024

The load losses of the transformers increase considerably with the presence of harmonic distortion in the currents. Its increase can be determined using an analytical method based on ANSI/IEEE Standard C57.110. On the other hand, when it comes to three-phase banks with transformers of different capacities, delta connections, or incomplete connections, the analytical method does not allow the losses to be accurately estimated, which is why digital simulation is necessary. This work presents an adjusted model to determine the load losses in a three-phase bank of three single-phase transformers with different connection schemes. The model allows for determining load and electrical losses and calculating total additional losses. It is also possible to decide on the load capacity of the bank's transformers, the power factor, and the efficiency with which they operate under these conditions.
Effect of Na-EDTA on electrical characteristics NaCl electrolyte battery charging solar panels
Authors: Maizana Dina , Mungkin Moranain , Satria Habib , Syafii Syafii , Siregar Muhammad Fadlan
Published: August 2024

This research investigates the problem of Cu-Zn electrode batteries with NaCl electrolyte. Previous studies have indicated problems with the electrolyte and electrodes after charging, such as turbidity and deposits in the electrolyte, as well as corrosion on the electrodes. Consequently, the battery can only be used once due to a decline in its electrical characteristics after the initial charging. Through this research, improvements were made to the electrical characteristics of the battery by adding Na-EDTA to enhance usage efficiency. The research method involved mixing NaCl solution with the highest electrical conductivity, using six pairs of Cu-Zn electrodes arranged in series. The physical conditions of the electrolyte and electrodes were observed, and electrical characteristics were measured. The research results indicate that the use of NaCl+Na-EDTA electrolyte produces a battery voltage of 4.20 volts with a current of 2 Ah and can be used twice. Charging with solar panels can be done in 1 hour, but the frequency is limited to two times.
Design of a high-speed 7.2 Gbps/lane receiver for MIPI D-PHY interface utilizing 18 nm FinFET technology
Authors: Hoang Trang , Ha Anh Nam
Published: August 2024

This study presents an advanced design for a high-speed receiver tailored for the MIPI D-PHY Interface, capable of handling data rates up to 7.2 Gbps per lane. The design is developed using 18 nm fin field-effect transistor (FinFET) technology and is rigorously simulated under varying process, voltage, and temperature conditions (PVTs) to ensure robustness. The architecture of the receiver integrates several key components: differential pair sensing, a folded cascode continuous time linear equalization (CTLE), a single-ended operational amplifier, and a cross-coupled stage. Operating at a supply voltage of 0.72 V in the worst-case scenario, our CTLE achieves a peaking gain of 17.77 dB at 4.26 GHz. The design demonstrates a maximum jitter of 19.63 ps at an offset voltage of ±2 mV. Notably, the power efficiency of our receiver is optimized to 0.85 mW/Gb/s, totaling 6.1 mW, with dual supply voltages of 1.98 and 0.88 V. This work contributes to the field by offering a highly efficient solution for fast data transmission with reduced power consumption and enhanced signal integrity.
Improvement of Philips MOS model 9 radio frequency performance with circuit level parasitic compensation
Authors: Gadige Aswini Kumar , Paremesha Paremesha
Published: August 2024

The two circuit-level parasitic compensation techniques for the Philips metal oxide semiconductor (MOS) model 9 metal oxide semiconductor field effect transistor (MOSFET) at high frequencies (in the GHz range) are presented in this paper. The first method involves connecting the series resonant LC circuit in parallel to the drain and grounded source/bulk of the MM9; the second method involves connecting two of these MM9s in parallel to increase the drain current at higher frequencies along with parasitic compensation. Using these compensatory techniques, it is possible to reduce the impact of drain-source parasitic capacitance on MOS model 9 by preventing the short circuit of MOSFET terminals at high frequencies. After adjustment, improvements were seen in a number of metrics, including output impedance, S-parameters, output power and stability. Finally, using a 10 dBm source power, these parasitic compensation techniques are applied to a single and two stage basic class-E power amplifier and simulated at 1.7 and 1.1 GHz, respectively. Improvements are noted in multiple performance parameters, including power Gain (16.5 dB), drain Efficiency (83%), power added efficiency (85.82%), output power (26 dBm), good Stability (K=2.23, B>0), and S-parameters (S11=-9.22 dB, S12=-39.78 dB, S21=16.38 dB, and S22=1.41 dB) in two-stage cascade power amplifier.
Integrating hetero-core fiber optics sensor in intelligent technological textiles
Authors: Arif Noor Azie Azura Mohd , Jiun Chong Chee , Sen Yong Wei , Ehsan Abang Annuar
Published: August 2024

In the context of the emerging Industry 4.0 paradigm, smart fabric sensors have been representing a novel addition to the textile industry. The proposed sensors utilize macro-bending techniques with varying fiber optic core sizes. The study involved the construction and testing of macro-bending sensors using single-mode (9 μm) and hetero-core (50–9–50 μm) fibers, configured into seven sinusoidal loops. The experiment was further extended to different types of elastic textiles. Spandex demonstrated superior linearity compared with jersey and rubber bands. The integration with the DOIT ESP32 DevKit facilitated real-time monitoring of respiratory rates. The results from the experiment indicated that the macro-bending sensor, fabricated using hetero-core optical fiber, exhibited superior sensitivity in comparison to the sensor assembled from single-mode optical fiber, with respective sensitivity values of 1.72 and 1.30 dB/cm. The designed sensors displayed closely aligned behavior during forward and reverse loading, indicating the reversibility of the fiber optic sensor. Given its simplistic design and low fabrication cost, the proposed sensor holds significant potential for practical applications.
Model predictive control with finite constant set for five-level neutral-point clamped inverter fed interior permanent magnet synchronous motor drive of electric vehicle
Authors: Cuong Tran Hung , Anh An Thi Hoai Thu
Published: August 2024

This paper uses the five-level neutral-point clamped (NPC) inverter to feed an electric vehicle's traction motor-interior permanent magnet synchronous motor (IPMSM). The model predictive control method controls the energy conversion process according to the model with two prediction steps. The advantage of this method is its fast response, which increases the ability to operate the converter with good voltage quality. Model predictive control (MPC) control is a closed-loop strategy with much potential when integrating multiple control objectives; the calculation process is compact without complex modulation. Within the scope of this article, the MPC strategy will be implemented with two control goals for NPC, including output load current and capacitor voltage balance with low switching frequency. The simulation results on MATLAB/Simulink software were performed to verify the proposed algorithm's effectiveness in minimizing the grid current's harmonics and ensuring an uninterrupted power supply.
Advancements in ammonia gas detection: a comparative study of sensor technologies
Authors: Hadi Amran Abdul , Shaipuzaman Nurulain Nadhirah , Aspar Mohd Amir Shahlan Mohd , Salim Mohd Rashidi , Manap Hadi
Published: August 2024

Ammonia gas is a colorless gas that is known for its pungent odor. It is commonly used in various industries, such as agriculture, refrigeration, and chemical manufacturing. This paper provides a comprehensive overview of various technologies employed in ammonia gas sensors. The objective is to compare and identify the optimum method to detect ammonia gas. The review encompasses catalytic gas sensors, metal oxide gas sensors, polymer conductivity gas sensors, optical gas sensors, and indirect gas sensors, detailing their respective operational principles. Additionally, the advantages and disadvantages of each technology for ammonia gas detection are outlined. All these technologies have been used for many applications and some of them have been commercialized. Some sensor characteristics suggestions are also stated in order to develop an improved optical ammonia sensor for industrial applications.
Optimal control design of the COVID-19 model based on Lyapunov function and genetic algorithm
Authors: Sa'adah Aminatus , Saragih Roberd , Handayani Dewi
Published: August 2024

Millions of people died worldwide as a result of the coronavirus disease 2019 (COVID-19) pandemic that started in early 2020. Examining the COVID-19 susceptible-exposed-infected-recovery (SEIR) mathematical model is one approach to developing the best control scenario for this disease. The study utilized two control variables, vaccination, and therapy, to construct a control function that relied on the quadratic Lyapunov function. The control objective was to lower the number of COVID-19 infections while maintaining system stability. A genetic algorithm (GA) is used as a novel method to estimate controller parameter value to replace the previously used parameter tuning procedure. Then, a numerical simulation was carried out implementing three control scenarios, namely vaccination control only, treatment control only, and vaccination and treatment control simultaneously. Based on the results, scenario 3 (vaccination and treatment simultaneously) showed the most significant decrease: the average decrease in the exposed human population was 98.29%, and the infected human population was 98.18%.
Neural network control of a nonlinear dynamic plant with a predictive model
Authors: Siddikov Isamidin , Khalmatov Davronbek , Khushnazarova Dilnoza , Khujanazarov Ulugbek
Published: August 2024

The paper considered the possibilities of applications of neural network technologies to control a dynamic plant with nonlinear properties. To give the control system the desired dynamic property, the use of a neural network predictive controller is proposed. The model of the control plant is in the form of a multilayer forward-directional neural network, which allows us to construct a controller using generalized equation methods with prediction. A neural network control algorithm with prediction based on minimizing the quadratic quality functional is proposed. The algorithm makes it possible to minimize the root mean square error of regulation and the control signal rate of change. To determine the sequences of optimal control impacts, the application of the Newton-Raphson method is proposed. To reduce computational costs when receiving control signals, the decomposition of the original matrix, represented as a Hess matrix, is carried out. To predict the behavior of a control plant, a formula is proposed for calculating the gradient of a neural network, discrepant by the possibility of its use in the real-time mode of the control. The proposed algorithm of the neural network control with predictive allows higher quality control of complex nonlinear dynamic plants in the real-time mode.
The comparison of several cryptosystems using the elliptic curve: a report
Authors: Trung Mai Manh , Do Le Phe , Tuan Do Trung , Trieu Thu Thuy , Tanh Nguyen Van , Tri Ngo Quang , Cong Bui Van
Published: August 2024

The elliptic curve cryptosystem (ECC) has several applications in Information Security, especially in cryptography with two main activities including encrypting and decrypting. There were several solutions of different research teams which propose various forms of the elliptic curve cryptosystem on cryptographic sector. In the paper, we proposed a solution for applying the elliptic curve on cryptography which is based on these proposals as well as basic idea about the elliptic curve cryptosystem. We also make comparison between our proposal and other listed solution in the same application of the elliptic curve for designing encryption and decryption algorithms. The comparison results are based on parameters such as time consumption (t), RAM consumption (MB), source code size (Bytes), and computational complexity.
Smart fuzzy incubator for free-range chicken on internet of things
Authors: Islamiyah Mufidatul , Arifin Samsul
Published: August 2024

This paper presents the design of an artificial incubator for free-range chicken eggs. The incubator is designed to maintain optimal conditions and humidity for embryo development and this incubator is equipped with an egg turning mechanism. This incubator is designed using NodeMCU 8266 hardware which is used as a control that connects to the database server, and this incubator is built using multiplex, exhaust fan, mist maker, motor tuning, DS18B20, DHT-11 and real-time clock (RTC) DS3231. The temperature and humidity conditions in the incubator are maintained within the desired range and the egg changing mechanism works effectively. The results of this research show that this artificial incubator can be a reliable and effective tool for hatching free-range chicken eggs. This incubator is very easy to use and maintain and very affordable for local free-range chicken farming. This future research will focus on determining the conditions under which the incubator will provide the best results in terms of hatching efficiency for free-range chickens.
Enhancing the resistance of password hashing using binary randomization through logical gates
Authors: Anbari Muhamad Zaki , Sugiantoro Bambang
Published: August 2024

Digitalization in various sectors makes information security issues very crucial. Information security follows the authentication, authorization, and accounting (AAA) principle, where one of the most important parts is authentication. The most widely used authentication method is username-password. The best method to secure a user-pass is to convert the plaintext using a hash so that the converted plaintext cannot be recovered. However, with higher technology, hackers can crack the ciphertext using brute force. This research proposes a username-password scrambling algorithm before it is fed into the hash function to improve resilience from attacks. This algorithm is named logical gates (LG). It works by converting the user pass into binary form, adding salt, and scrambling it with certain logical gates before inserting it into the hash function. Testing is divided into two: time of execution and attack resistance. Time of execution results show that LG takes 0.0443432033 s, while without LG takes 0.01403197646 s. The resistance of attack results show that the plaintext of the hash amplified by LG cannot be cracked at all and increases the attack time by 321.3% at prefix and 161.3% at postfix, while without LG, the plain text can be found for a certain duration of time.
Utilizing digital elevation models and geographic information systems for hydrological analysis and fire prevention in Khuan Kreng peat swamp forest, Southern Thailand
Authors: Wanthong Uraiwun , Ruang-On Somporn , Limchoowong Nunticha , Sricharoen Phitchan , Musik Panjit
Published: August 2024

The objectives of this research were to create a topographic model using Mathematica and hydrologic model using ArcGIS for water management aimed at preventing forest fires in the Khuan Kreng peat swamp forest. Pan basin area in Kreng Sub-district, characterized by low mountains, where the Cha-Uat canal intersects the krajood forest, was revealed by the hydrographic model. Kreng Sub-district was traversed by three main streams: Khuan canal, Hua Pluak Chang canal, and Laem canal. Additionally, several tributary canals that interconnect, ultimately converging into the Cha-Uat Phraek Muang canal were identified. During the dry period, the water from these canals flowed into the Cha-Uat Phraek Muang canal. To mitigate the risk of fires, it was essential to install water table measuring devices and underground barrier gates at the drain points. This ensured the return of water from the Cha-Uat Phraek Muang canal to the Khuan Kreng peat swamp forest. Maintaining sufficient water table level was crucial, as the occurrence of fires was more likely when the water table dropped below the soil surface. When the swamp forest was adequately hydrated, wildfires were confined to a narrow area since they could only burn on the forest surface, which was easier to extinguish.
Development of a decision-making module in the field of real estate rental using machine learning methods
Authors: Mukhanova Ayagoz , Baitemirov Madiyar , Ignatovich Artyom , Bayegizova Aigulim , Tanirbergenov Adilbek , Tynykulova Assemgul , Bapiyev Ideyat , Mukhamedrakhimova Galiya
Published: August 2024

The research is aimed at developing a prototype of a decision support information system for managers of a company operating in the real estate rental industry. The system provides tools for data analysis, the use of mathematical models and expert knowledge to solve complex problems. The work analyzes the practical aspects of the design and use of decision support systems and formulates the requirements for the functionality of the system being developed. The Python programming language was used for implementation. The prototype includes machine learning models, expert systems, user interface and reports. Linear regression, data clustering density-based spatial clustering of applications with noise (DBSCAN) and backpropagation methods were implemented to train the classifying perceptron. The developed tool represents a significant contribution to the field of decision support, providing unique analysis and forecasting capabilities in the dynamic real estate rental environment. This prototype is an innovative solution that promotes effective management and strategic decision making in complex real estate business scenarios.