Digital Commons Network^™

Fixed Point Results For Almost Contraction Mappings In Fuzzy Metric Space, Raghad I. Sabri, Buthainah A. A. Ahmed

Baghdad Science Journal

In certain mathematical, computing, economic, and modeling issues, the presence of a solution to a theoretical or real-world problem is synonymous with the presence of a fixed point (Fp) for an appropriate mapping. Consequently, Fp plays an essential role in a wide variety of mathematical and scientific contexts. In its own right, the theory is a stunning amalgamation of analysis (both pure and applied), geometry, and topology. Recent years have shown the theory of Fps is a highly strong and useful tool in the study of nonlinear events. Fp theorems are concerned with mappings f of a set X into …

Biogenic Functionalized Zno/Cuo Nanocomposite Sensor For Potentiometric Determination Of Pseudoephedrine-Hcl In Pure And Commercial Products, Fadam M. Abdoon, Sarhan A. Salman, Hasan M. Hasan, Suham T. Ameen, Maha F. El-Tohamy

Baghdad Science Journal

The ultrafunctional potential of zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs) has generated a great interest in using such metal oxides as remarkable and electroactive nanocomposites in the studies on potentiometry and sensors. These nano-oxides were prepared from the extract of Leucaena leucocephala seeds as an environmentally friendly process. The development of a ZnO/CuO “core-shell nanocomposite-modified” coated copper wire film sensor was proposed as a new method for potentiometric determination of pseudoephedrine hydrochloride (PSD) in pure and pharmaceutical dosage forms. With the existence of polyvinyl chloride (PVC) as a polymer with high molecular weight and “o-nitrophenyl octyl ether …

Third-Order Differential Subordination For Generalized Struve Function Associated With Meromorphic Functions, Suha J. Hammad, Abdul Rahman S. Juma, Hassan H. Ebrahim

Baghdad Science Journal

Previously, many works dealt with the study of the order differential subordination and shortly after that other studies dealt with the order differential subordination in the unit disc. Recently the order differential subordination was presented by Antonino and Miller (2011). This paper looks at a considerably broader class of order differential inequalities and subordination. The authors define the criteria on an admissible class of operators, implying that order differentiale subordination exists. Meromorphic in is a function that is holomorphic in domain except for poles. If it simply states the function is meromorphic. Meromorphic functions in are those that may be …

Context-Aware Location Privacy Protection Method, Haohua Qing, Roliana Ibrahim, Hui Wen Nies

Baghdad Science Journal

Location privacy protection has drawn increasing attention with the popularity of location-based services. This study proposes a context-aware location privacy protection method (CA-LP). CA-LP evaluates users' location privacy needs by mining their historical trajectories and estimating the privacy leakage degree of locations. Experiments compare CA-LP with other methods on metrics like privacy protection level, quality of service, privacy leakage risk, information loss, and average anonymous time. Results demonstrate CA-LP provides better privacy protection and service quality when considering all factors. CA-LP shows extensive practical value in location sharing applications.

A Stage Structure Prey Predator Model Using Pentagonal Fuzzy Numbers And Functional Response, Vinothini P., Kavitha K.

Baghdad Science Journal

In the present study, our work is focused on a prey predator model with a stage structure for the prey. The objective of the study is to find the behavior of the model using parameter values in the presence of Pentagonal fuzzy numbers. The interaction between the species is done by using functional responses, such as the Holling type I reaction for immature prey and the Crowley Martin functional response for mature prey. Prey population categorized as immature and mature prey. The idea of the problem is to construct a fuzzy theoretical method which helps us to create a model …

Sexual Dimorphism And Reproductive Biology Of Bronze Featherback (Notopterus Notopterus, Pallas 1769) From Kelekar River, Ogan Ilir, South Sumatra, Indonesia, Muslim Muslim, Mochamad Syaifudin, Ferdinand Hukama Taqwa, Muhammad Iqbal Saputra

Baghdad Science Journal

Sexual dimorphism and reproductive biology are fundamental aspects of fish breeding studies. The aim of this research was to analyze the sexual dimorphism and reproductive biology of Notopterus notopterus. A total of 74 N. notopterus were collected from the Kelekar River in Ogan Ilir Regency, Indonesia, consisting of 38 males (TL: 18–23.6 cm; BW: 35.1–92.1 g) and 36 females (TL: 19.6-26.3 cm; BW: 49.4–133.8 g). Seventeen morphometric characters, three meristic characters, and five reproductive biological parameters were analyzed. The results showed the differences in the morphometric characteristics of male and female N. notopterus. However, there was no difference in the …

Comparison Of Physical Characteristics Of Mass And Luminosity Function Of Disk Systems In Barred And Unbarred Spiral Galaxies, Al Najm M.N., Y. E. Rashed, H. H. Al-Dahlaki

Baghdad Science Journal

Among the most important ways to investigate galaxies' distribution over cosmic time is the luminosity function LF in terms of baryonic disc mass ψ^S(Ms), magnitude Ø^B(MB). We have studied an estimate of the baryon mass density in the sample of barred and unbarred spiral-type galaxies from previous literature, which virtually involves, for each class of objects with visible baryon content, an integral over the luminosity of the product of the luminosity function (LF) and the mass-to-light ratio. The multiple regression technique used the statistical software package in our study and results, such as database analysis and graphing software (Statistics Win …

Transformer-Based Joint Learning Approach For Text Normalization In Vietnamese Automatic Speech Recognition Systems, The Viet Bui, Tho Chi Luong, Oanh Thi Tran

Research Collection School Of Computing and Information Systems

In this article, we investigate the task of normalizing transcribed texts in Vietnamese Automatic Speech Recognition (ASR) systems in order to improve user readability and the performance of downstream tasks. This task usually consists of two main sub-tasks: predicting and inserting punctuation (i.e., period, comma); and detecting and standardizing named entities (i.e., numbers, person names) from spoken forms to their appropriate written forms. To achieve these goals, we introduce a complete corpus including of 87,700 sentences and investigate conditional joint learning approaches which globally optimize two sub-tasks simultaneously. The experimental results are quite promising. Overall, the proposed architecture outperformed the …

Hisoma: A Hierarchical Multi-Agent Model Integrating Self-Organizing Neural Networks With Multi-Agent Deep Reinforcement Learning, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-agent deep reinforcement learning (MADRL) has shown remarkable advancements in the past decade. However, most current MADRL models focus on task-specific short-horizon problems involving a small number of agents, limiting their applicability to long-horizon planning in complex environments. Hierarchical multi-agent models offer a promising solution by organizing agents into different levels, effectively addressing tasks with varying planning horizons. However, these models often face constraints related to the number of agents or levels of hierarchies. This paper introduces HiSOMA, a novel hierarchical multi-agent model designed to handle long-horizon, multi-agent, multi-task decision-making problems. The top-level controller, FALCON, is modeled as a class …

Motif Graph Neural Network, Xuexin Chen, Ruicui Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao

Research Collection School Of Computing and Information Systems

Graphs can model complicated interactions between entities, which naturally emerge in many important applications. These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph representations. Graph neural networks (GNNs) are currently the most popular model in graph embedding approaches. However, standard GNNs in the neighborhood aggregation paradigm suffer from limited discriminative power in distinguishing high-order graph structures as opposed to low-order structures. To capture high-order structures, researchers have resorted to motifs and developed motif-based GNNs. However, the existing motif-based GNNs still often suffer from less discriminative power on high-order …

Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation, Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho

Research Collection School Of Computing and Information Systems

Regional information-based image emotion analysis has recently garnered significant attention. However, existing methods often focus on identifying region proposals through layered steps or merely rely on visual saliency. These approaches may lead to an underestimation of emotional categories and a lack of comprehensive interclass discrimination perception and emotional intraclass contextual mining. To address these limitations, we propose a novel approach named InterIntraIEA, which combines interclass discrimination and intraclass correlation joint learning capabilities for image emotion analysis. The proposed method not only employs category-specific dictionary learning for class adaptation, but also models intraclass contextual relationships and perceives correlations at the channel …

Temporal Relational Graph Convolutional Network Approach To Financial Performance Prediction, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Accurately predicting financial entity performance remains a challenge due to the dynamic nature of financial markets and vast unstructured textual data. Financial knowledge graphs (FKGs) offer a structured representation for tackling this problem by representing complex financial relationships and concepts. However, constructing a comprehensive and accurate financial knowledge graph that captures the temporal dynamics of financial entities is non-trivial. We introduce FintechKG, a comprehensive financial knowledge graph developed through a three-dimensional information extraction process that incorporates commercial entities and temporal dimensions and uses a financial concept taxonomy that ensures financial domain entity and relationship extraction. We propose a temporal and …

Enhancing Recipe Retrieval With Foundation Models: A Data Augmentation Perspective, Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang

Research Collection School Of Computing and Information Systems

Learning recipe and food image representation in common embedding space is non-trivial but crucial for cross-modal recipe retrieval. In this paper, we propose a new perspective for this problem by utilizing foundation models for data augmentation. Leveraging on the remarkable capabilities of foundation models (i.e., Llama2 and SAM), we propose to augment recipe and food image by extracting alignable information related to the counterpart. Specifically, Llama2 is employed to generate a textual description from the recipe, aiming to capture the visual cues of a food image, and SAM is used to produce image segments that correspond to key ingredients in …

Risurconv : Rotation Invariant Surface Attention-Augmented Convolutions For 3d Point Cloud Classification And Segmentation, Zhiyuan Zhang, Licheng Yang, Xiang Zhiyu

Research Collection School Of Computing and Information Systems

Despite the progress on 3D point cloud deep learning, most prior works focus on learning features that are invariant to translation and point permutation, and very limited efforts have been devoted for rotation invariant property. Several recent studies achieve rotation invariance at the cost of lower accuracies. In this work, we close this gap by proposing a novel yet effective rotation invariant architecture for 3D point cloud classification and segmentation. Instead of traditional pointwise operations, we construct local triangle surfaces to capture more detailed surface structure, based on which we can extract highly expressive rotation invariant surface properties which are …

Desk2desk : Optimization-Based Mixed Reality Workspace Integration For Remote Side-By-Side Collaboration, Ludwig Sidenmark, Tianyu Zhang, Leen Al Lababidi, Jiannan Li, Tovi Grossman

Research Collection School Of Computing and Information Systems

Mixed Reality enables hybrid workspaces where physical and virtual monitors are adaptively created and moved to suit the current environment and needs. However, in shared settings, individual users’ workspaces are rarely aligned and can vary significantly in the number of monitors, available physical space, and workspace layout, creating inconsistencies between workspaces which may cause confusion and reduce collaboration. We present Desk2Desk, an optimization-based approach for remote collaboration in which the hybrid workspaces of two collaborators are fully integrated to enable immersive side-by-side collaboration. The optimization adjusts each user’s workspace in layout and number of shared monitors and creates a mapping …

Improving Out-Of-Distribution Detection With Disentangled Foreground And Background Features, Choubo Ding, Guansong Pang

Research Collection School Of Computing and Information Systems

Detecting out-of-distribution (OOD) inputs is a principal task for ensuring the safety of deploying deep-neural-network classifiers in open-set scenarios. OOD samples can be drawn from arbitrary distributions and exhibit deviations from in-distribution (ID) data in various dimensions, such as foreground features (e.g., objects in CIFAR100 images vs. those in CIFAR10 images) and background features (e.g., textural images vs. objects in CIFAR10). Existing methods can confound foreground and background features in training, failing to utilize the background features for OOD detection. This paper considers the importance of feature disentanglement in out-of-distribution detection and proposes the simultaneous exploitation of both foreground and …

Zero-Shot Object Counting With Good Exemplars, Huilin Zhu, Jingling Yuan, Zhengwei Yang, Yu Guo, Zheng Wang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a critical challenge in current ZOC methods lies in their inability to identify high-quality exemplars effectively. This deficiency hampers scalability across diverse classes and undermines the development of strong visual associations between the identified classes and image content. To this end, we propose the Visual Association-based Zero-shot Object Counting (VA-Count) framework. VACount consists of an Exemplar Enhancement Module (EEM) and a Noise Suppression Module (NSM) that synergistically refine the process of class exemplar identification …

Onerestore : A Universal Restoration Framework For Composite Degradation, Yu Guo, Yuan Gao, Yuxu Lu, Huilin Zhu, Ryan Wen Liu, Shengfeng He

Research Collection School Of Computing and Information Systems

In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite this reality, existing restoration methods typically target isolated degradation types, thereby falling short in environments where multiple degrading factors coexist. To bridge this gap, our study proposes a versatile imaging model that consolidates four physical corruption paradigms to accurately represent complex, composite degradation scenarios. In this context, we propose OneRestore, a novel transformer-based framework designed for adaptive, controllable scene restoration. The proposed framework leverages a unique cross-attention mechanism, merging degraded scene descriptors with image features, …

Latent Representation Learning For Geospatial Entities, Ween Jiann Lee, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Representation learning has been instrumental in the success of machine learning, offering compact and performant data representations for diverse downstream tasks. In the spatial domain, it has been pivotal in extracting latent patterns from various data types, including points, polylines, polygons, and networked structures. However, existing approaches often fall short of explicitly capturing both semantic and spatial information, relying on proxies and synthetic features. This article presents GeoNN, a novel graph neural network-based model designed to learn spatially-aware embeddings for geospatial entities. GeoNN leverages edge features generated from geodesic functions, dynamically selecting relevant features based on relative locations. It introduces …

An Empirical Study Of Automatic Program Repair Techniques For Injection Vulnerabilities, Tingwei Zhu, Tongtong Xu, Kui Liu, Jiayuan Zhou, Xing Hu, Xin Xia, Tian Zhang, David Lo

Research Collection School Of Computing and Information Systems

Injection vulnerabilities are among the most serious and dangerous security defects, as they can be exploited by attackers to inject malicious inputs and carry out cybercrimes. Timely fixing of injection vulnerabilities is crucial. However, manual repairs of injection vulnerabilities often require specialized knowledge and are prone to errors, posing a challenge and a heavy burden on developers. In recent years, Automated Program Repair (APR) techniques have shown promising momentum in automatically fixing general defects. Yet, there has been no research on how APR techniques perform in repairing injection vulnerabilities. Therefore, in this paper, we conduct an empirical study. We first …

Gradualreality : Enhancing Physical Object Interaction In Virtual Reality Via Interaction State-Aware Blending, Hyuna Seo, Juheon Yi, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

We present GradualReality, a novel interface enabling a Cross Reality experience that includes gradual interaction with physical objects in a virtual environment and supports both presence and usability. Daily Cross Reality interaction is challenging as the user’s physical object interaction state is continuously changing over time, causing their attention to frequently shift between the virtual and physical worlds. As such, presence in the virtual environment and seamless usability for interacting with physical objects should be maintained at a high level. To address this issue, we present an Interaction State-Aware Blending approach that (i) balances immersion and interaction capability and (ii) …

Graph Continual Learning With Debiased Lossless Memory Replay, Chaoxi Niu, Guansong Pang, Ling Chen

Research Collection School Of Computing and Information Systems

Real-life graph data often expands continually, rendering the learning of graph neural networks (GNNs) on static graph data impractical. Graph continual learning (GCL) tackles this problem by continually adapting GNNs to the expanded graph of the current task while maintaining the performance over the graph of previous tasks. Memory replay-based methods, which aim to replay data of previous tasks when learning new tasks, have been explored as one principled approach to mitigate the forgetting of the knowledge learned from the previous tasks. In this paper we extend this methodology with a novel framework, called Debiased Lossless Memory replay (DeLoMe). Unlike …

A Fresh Look At Judicial Remedies In Eu Equality Law And Beyond: The Untapped Possibility Of Structural Injunctions., Daniel H. Halberstam, Sina Van Den Bogaert

Articles

This article proposes a shift in thinking about judicial remedies (or “sanctions”), from anti-discrimination law to equal pay and beyond.We suggest the currently preferred remedies – one-off declarations, compensation, fines, and simple orders to obey the law – may be insufficient when confronting a recalcitrant institution, complex violations, and broad, ongoing harm. In such cases, we suggest considering a remedy long overlooked in Europe: a “structural injunction”, i.e. ordering changes to an offending organization’s structure, processes, or rules. We argue that under certain circumstances, an injunction, including a structural injunction, may be appropriate or required under EU law to remedy …

The Origins Of The Major Questions Doctrine, Rachel Rothschild

Articles

In a series of recent cases, the Supreme Court has invoked the newly named “major questions doctrine” to strike down agency regulations that protect public health and the environment. Several Justices have argued that while the name “major questions” may be new, these decisions are simply the latest iteration in a longstanding effort of the courts to curtail the explosive growth of the administrative state since 1970. The first paradigmatic example of this line of cases is the 1980 “Benzene” case, in which the Supreme Court set aside the Occupational Safety and Health Administration (OSHA)’s new workplace standards for the …

Cal Poly Humboldt Library Digest, October 2024, Cal Poly Humboldt Library

Library Publications

No abstract provided.

Check Out The Library, 2024 Fall Issue, Cal Poly Humboldt Library

Library Publications

No abstract provided.

Response To Letter To The Editor Concerning The Article "The Clinical And Economic Impact Of Extended Battery Longevity Of A Substernal Extravascular Implantable Cardioverter Defibrillator"., Bradley P Knight, Nicolas Clémenty, Anish Amin, Ulrika Maria Birgersdotter-Green, Henri Roukoz, Reece Holbrook, Jaimie Manlucu

Heart and Vascular Articles

No abstract provided.

Impact Of Functional Recovery On Patients Having Heart Surgery., Richard J Snow, Lauren Mckown, Geoffrey Blossom, Karen Vogel, Amy Creighton, Jason Shriver, Linda Will, Katie Lentz, Elizabeth Snow, Teresa Caulin-Glaser

Heart and Vascular Articles

OBJECTIVE: To describe the results of a program developed to manage institutional postacute care (IPAC) (postacute skilled nursing, inpatient rehabilitation facility, and long-term acute care) in a CMS Bundled Payments for Care Improvement (BPCI) project for coronary artery bypass graft (CABG) surgery.

STUDY DESIGN: We compared pre- and postutilization patterns during a 3-year period by evaluating risk-adjusted national, state, and other BPCI participant comparisons using a difference-in-differences (DID) analysis in a large urban community tertiary center with a CABG surgery program. Included in the analysis were all Medicare patients receiving CABG surgery at the institution (n = 504), across the …

New Ways Of Teaching Adat (Customary) Law At Indonesian Law Schools, Tody S.J. Utama, Rikardo Simarmata, Jacqueline A.C. Vel, Adriaan W. Bedner

The Indonesian Journal of Socio-Legal Studies

While customary law typically is not the sole legal system regulating people's daily lives, it still plays a big role in shaping the behavior of countless individuals worldwide. For this reason, law schools in many countries teach customary law courses, but these courses often present customary law as a sterile set of principles and norms detached from studying social reality. This approach associates customary law with traditional communities whose members live in relative isolation from the world, ignoring the fact that customary law operates in a legally pluralistic universe, interacting with religious and state law systems, and that it adapts …

Innovation Challenges In The Air Force Sbir Program: From The Small Businesses’ Perspective, Hart J. Holt, Amy M. Cox, Scott Drylie, David S. Long, Alfred E. Thal Jr., R. David Fass

Faculty Publications

Every year the United States invests $3.2 billion in the Small Business Innovation Research (SBIR) program to promote innovation among the nation’s small businesses. Half of this investment is from the DoD. This research considers the challenges faced by small businesses innovating with the DoD, particularly those awarded SBIR contracts with the United States Air Force. The authors surveyed 286 unique small businesses that were previously awarded an Air Force SBIR contract. By asking the survey respondents open-ended questions and categorizing their responses, they pinpoint unaddressed challenges from the small business perspective. By categorizing survey responses through Qualitative Content Analysis, …