Access to Computer Science (CS) education in the United States remains uneven, with disparities linked to geography, income, and demographics. While state dashboards report enrollment and disparities, they rarely show how local community factors shape access and participation. This project presents an interactive dashboard combining Georgia Department of Education enrollment data with National Center for Education Statistics attributes and U.S. Census Bureau data. By linking school-level participation with demographic, socioeconomic, and geographic context, the dashboard reveals differences in representation and resources across communities and highlights how these factors influence opportunities for CS participation. This integration of school- and community-level data provides a more nuanced view of disparities than standard state reports alone.

Abstract query languages such as Domain Relational Calculus (DRC), Datalog (DLOG), and Relational Algebra (RA) are covered in an introductory database course. Unlike SQL queries, which can be executed, queries in these abstract languages usually are not executable due to the unavailability of query processors. In this paper, we present both backend query processors for these abstract query languages as well as an interactive Web-based expression tree visualizer for queries. The interactive tool allows teachers and students to visualize expression trees for these queries and interact with them to view values at sub-expression nodes. Since DRC, DLOG, and RA form a hierarchy of languages with DRC being purely declarative, DLOG being partly declarative and partly procedural, and RA being fully procedural, users can view translations of DRC expressions into DLOG and DLOG expressions into RA. Besides, since the system eventually translates all queries into SQL, the users can also view SQL equivalents of sub-expressions in any of the three languages.

Parameter-efficient fine-tuning (PEFT) significantly reduces computational and memory costs by updating only a small subset of the model’s parameters, enabling faster adaptation to new tasks with minimal loss in performance. Previous studies have introduced PEFTs tailored for point cloud data, as general approaches are suboptimal. To further reduce the number of trainable parameters, we propose a point-cloud-specific PEFT, termed Graph Features Tuning (GFT), which learns a dynamic graph from initial tokenized inputs of the transformer using a lightweight graph convolution network and passes these graph features to deeper layers via skip connections and efficient cross-attention modules. Extensive experiments on object classification and segmentation tasks show that GFT operates in the same domain, rivalling existing methods, while reducing the trainable parameters. Code is available at https://github.com/manishdhakal/GFT.

Unmanned Aerial Vehicles (UAVs), equipped with cameras, are employed in numerous applications, including aerial photography, surveillance, and agriculture. In these applications, robust object detection and tracking are essential for the effective deployment of UAVs. However, existing benchmarks for UAV applications are mainly designed for traditional 2D perception tasks, restricting thedevelopment of real-world applications that require a 3D understanding of the environment. Furthermore, despite recent advancements in single-UAV perception, limited views of a single UAV platform significantly constrain its perception capabilities over long distances or in occluded areas. To address these challenges, we introduce UAV3D – a benchmark designed to advance research in both 3D andcollaborative 3D perception tasks with UAVs. UAV3D comprises 1,000 scenes, each of which has 20 frames with fully annotated 3D bounding boxes on vehicles. We provide the benchmark for four 3D perception tasks: single-UAV 3D object detection, single-UAV object tracking, collaborative-UAV 3D object detection, and collaborative-UAV object tracking. Our dataset and code are available athttps://huiyegit.github.io/UAV3D_Benchmark/.

The eXtreme Multi-label text Classification (XMC) refers to training a classifier that assigns a text sample with relevant labels from an extremely large-scale label set (e.g., millions of labels). We propose MatchXML, an efficient textlabel matching framework for XMC. We observe that the label embeddings generated from the sparse Term Frequency-Inverse Document Frequency (TF–IDF) features have several limitations. We thus propose label2vec to effectively train the semantic dense label embeddings by the Skip-gram model. The dense label embeddings are then used to build a Hierarchical Label Tree by clustering. In fine-tuning the pre-trained encoder Transformer, we formulate the multi-label text classification as a text-label matching problem in a bipartite graph. We then extract the dense text representations from the fine-tuned Transformer. Besides the fine-tuned dense text embeddings, we also extract the static dense sentence embeddings from a pre-trained Sentence Transformer. Finally, a linear ranker is trained by utilizing the sparse TF–IDF features, the fine-tuned dense text representations, and static dense sentence features. Experimental results demonstrate that MatchXML achieves the state-of-the-art accuracies on five out of six datasets. As for the training speed, MatchXML outperforms the competing methods on all the six datasets. Our source code is publicly available athttps://github.com/huiyegit/MatchXML.

A recent 2017 study from HigherEd.com, shows that roughly 35% of students transfer colleges during their academic career. While much research has focused on the impact of undergraduate student success factors such as flipped classrooms, hybrid learning, and technology usage, we found no studies comparing transfer students versus non-transfer (native). In our research, we measure impact based on CS course load per semester related to pass/fail rates and contrast student status of transfer versus non-transfer (native). We show that transfer students tend to enroll in more CS courses per semester, beyond the department's recommended two. We also show that their performance is consistently different than that of native students, namely higher CS course fail rates and lower CS GPA scores. The detrimental effects and realization in this study is reason for further investigation. More features will be gathered to be used in our continued analysis and we see the need to examine the difficulty of CS courses taken to indicate why one cohort performs poorly and one does not. We conjecture that most transfer students tend to complete their core classes and are left with only CS courses to complete upon transfer. This results in the transfer students taking a heavier CS load and thus impacting their performance negatively, as compared to native students. Considering that many transfer students start their path way in 2-year institutions, it is imperative that better advising strategies are developed to enable the students to succeed upon their transition.

BACKGROUND: The Epi-Info software suite, built and maintained by the Centers for Disease Control and Prevention (CDC), is widely used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks such as Ebola and Zika. As it exists today, Epi-Info Desktop runs only on the Windows platform, and the larger Epi-Info Suite of products consists of separate codebases for several different devices and use-cases. Software portability has become increasingly important over the past few years as it offers a number of obvious benefits. These include reduced development time, reduced cost, and simplified system architecture. Thus, there is a blatant need for continued research. Specifically, it is critical to fully understand any underlying negative performance issues which arise from platform-agnostic systems. Such understanding should allow for improved design, and thus result in substantial mitigation of reduced performance. In this paper, we present a viable cross-platform architecture for Epi-Info which solves many of these problems. RESULTS: We have successfully generated executables for Linux, Mac, and Windows from a single code-base, and we have shown that performance need not be completely sacrificed when building a cross-platform application. This has been accomplished by using Electron as a wrapper for an AngularJS app, a Python analytics module, and a local, browser-based NoSQL database. CONCLUSIONS: Promising results warrant future research. Specifically, the design allows for cross-platform form-design, data-collection, offline/online modes, scalable storage, automatic local-to-remote data sync, and fast analytics which rival more traditional approaches.

The wide popularity of graphs in areas such as Semantic Web and Social Network has necessitated the need to develop efficient methods to store and process graph data. However, the unique structure of graphs render traditional data handling methods and storage structures inefficient when dealing with large volumes of data. Existing graph storage structures either compromise scalability by adopting an in-memory approach or compromise on performance by relying heavily on disk access. In this paper, we propose a novel graph data storage format that reduces latency due to disk access by using a hybrid storage strategy. We also introduce an adaptive caching technique that makes the structure scalable to accommodate large scale graphs.

We review several feature selection methods: Recursive Feature Elimination, Select K Best, and Random Forests, as elements of a processing chain for feature selection in a text mining task. The text mining task is a multi-label classification problem of label assignment; metadata that is usually applied to published scientific papers by expert curators. In the formulation of this classification task, a feature space that is dramatically larger than the available training data occurs naturally and inevitably. We explore ways to reduce the dimension of the feature space, and show that sequential feature selection does substantially improve performance for this complex type of data.

The treatment of abstract query languages such as Relational Algebra, Relational Calculus, and Datalog in introductory database courses varies considerably across the various computer science departments around the world. We propose an integrated approach in which students learn how to express a natural language query in Domain Relational Calculus (DRC), apply a query-transforming algorithm to the DRC expression tree to produce Datalog Rules (DLG), and finally apply another query-transforming algorithm to the DLG rules to produce an equivalent Relational Algebra (RA) expression. This systematic approach works very well for "forall-queries" in which the forall-quantifier is necessary in the DRC expression. To make this approach even more effective, the students are required to use DRC, DLG, and RA interpreters that allow them to execute query expressions as well as produce equivalent expressions. The students are also involved in implementing these interpreters to get a deeper understanding of querying in relational systems.

Routing in Disruption Tolerant Networks (DTNs) is a challenging problem due to the intermittent connectivity between the nodes. Researchers have proposed many routing protocols that adapt to the temporary connections of DTNs. One classification of routing protocols makes use of historical information to predict future contact patterns for any pair of nodes. However, most existing protocols focus on the probability of a path from the source to the destination without considering the information in a packet which includes the source, destination, size, TTL (Time-To-Live) and limited resources such as available buffer size and bandwidth. In this paper, we propose a new prediction-based routing algorithm that takes into account packet information under the conditions of limited transmission opportunities. The goal of this protocol is to increase the overall delivery ratio through scheduling packets at each node. Meanwhile, this protocol may sacrifice some messages' delivery delay time to some extent. Extensive simulation results with real traces show that our protocol with packet scheduling has better performance than the pure probabilistic routing algorithms in term of delivery ratio. Our protocol's performance advantage is more obvious for nodes with higher packet intensity and shorter TTL in packets.

This Supplement includes a selection of papers presented at the 7th International Symposium on Bioinformatics Research and Application (ISBRA), which was held on May 27-29, 2011 at Central South University in Changsha, China.The technical program of the symposium included 36 extended abstracts presented orally and published in volume 6674 of Springer Verlag's Lecture Notes in Bioinformatics series.Additionally, the program included 38 short abstracts presented either orally or as posters.Authors of both extended and short abstracts presented at the symposium were invited to submit full versions of their work to this Supplement.Following a rigorous review process, 19 of the 40 full papers submitted were selected for publication.Selected papers cover a broad range of bioinformatics topics, ranging from algorithms for structural biology to phylogenetics and biological networks.The first two papers of the Supplement address two important problems in structural biology.Improved methods for predicting protein-protein and protein-DNA binding and identification of binding sites are critical components of rational drug design and functional annotation pipelines.The paper by Guo and Wang proposes an efficient algorithm for finding similar binding sites on the protein surfaces based on sequence alignment, protein surface detection, and 3D structure comparison.Validation experiments show significantly improved average recall and precision values compared with existing approaches.Szabóová et al. propose methods for predicting protein-DNA binding propensity from spatial structure information without the use of evolutionary information.Such methods are particularly useful for optimizing DNA-binding of engineered proteins, for which evolutionary information is not available.Unlike previous approaches that rely on ad-hoc sets of physicochemical

The data of Semantic Web exist in machine readable format called RDF, in order to promote data exchange on the web based on their semantics. As an expressive knowledge representation language for the Semantic Web, Web Ontology Language (OWL) plays an important role in modeling information in a semantic way. However, due to the nature of knowledge bases, ontologies tend to be very large, distributed, and interconnected. Thus, maintaining constraints and enforcing data consistency for a group of ontologies become very challenging. In addition, frequent updates on ontologies necessitate an automatic approach to checking for potential constraint violations before any change takes place. In this study, we conducted a pioneer study and presented a framework for checking global constraints and ensuring integrity on data that span multiple ontologies. As an update is issued to a single site, global constraints that can be potentially violated are broken down into sub constraints that only involve a very small subset of ontologies. The checking of sub-constraints runs effectively in parallel and returns results about each subset. The collection of these results determines the violation of global constraints.

The five papers in this special section were presented at the Fourth International Symposium on Bioinformatics Research and Application (ISBRA), held at Georgia State University in Atlanta, GA, on 6-9 May 2008.

This paper proposes a graph data model that can represent the Biochemical Network. In the data model, the Node class and extended Node subclasses are used to represent the Biochemical Entities and Interactions, and the Edge class is used to describe the relationships between nodes. Furthermore, the Path and Hyper-Path classes are proposed to represent various processes and pathways. The study presented in this paper also proposes a Query Language bcnQL that empowers users to query entities, interactions, processes and pathways with arbitrary conditions. In addition, new graphs can be composed with hyper-paths using supported graph functions. The language employs node formula, edge formula, path formula, hyper-path formula and graph formula to construct a collection of node objects, edge objects, path objects, hyper-path objects and graph objects respectively. Some query examples are presented to demonstrate the applicability of the language for this specific domain. Finally, we provide a prototype implementation for the query language.

Global semantic integrity constraints ensure integrity and consistency of data spanning multiple databases. In this paper, we take initial steps towards representing global semantic integrity constraints for XML databases. We also provide a general framework for checking global semantic integrity constraints for XML databases. Furthermore, we set forth an efficient algorithm for checking global semantic integrity constraints across multiple XML databases. Our algorithm is efficient for three reasons: (1) the algorithm does not require the update statement to be executed before the constraint check is carried out; hence, we avoid any potential problems associated with rollbacks, (2) sub constraint checks are executed in parallel, and (3) most of the processing of algorithm could happen at compile time; hence, we save time spent at run-time. As a proof of concept, we present a prototype of the system implementing the ideas discussed in this paper.

Summary form only given. We have earlier proposed a general framework of an agent based constraint checker for checking global integrity constraints. The constraint checker consists of: update parser, metadatabase extractor, constraint planner, constraint optimizer and constraint executor. One of the important steps in checking for global constraints is to generate sub constraints from global integrity constraints. These sub constraints can be locally executed on remote sites. The constraint planner devises an effective plan for generating such sub constraints from each of the global constraints. In this paper, we focus on the constraint planner module. We propose an efficient algorithm that takes as input an update statement and the list of all global constraints and outputs sub constraints to be executed on remote sites. Our algorithm is efficient since the algorithm does not require the update statement to be executed before the constraint check is carried out. In this way, we save lot of time and resources avoiding any potential rollbacks. Our vision for implementation exploits parallelism by virtue of employing mobile agents.

This paper describes the advantages of SyD (System on Mobile Devices), a middleware technology for mobile devices and e-services, in terms of technology and programming. Features of SyD are illustrated here through our prototype application, a complex communication system for a trucking fleet that operates an automated package delivery system. The fleet system has been implemented in three ways, with SOAP, with JDBC, and with SyD. Our implementation experience shows that SyD greatly simplifies coding by allowing heterogeneous devices, peer-to-peer communications, group transactions based on triggering events, and mobility support through proxies and directory service.

Data mining has a lot of e-commerce applications. The key problem is how to find useful hidden patterns for better business applications. For these problems, granular fuzzy Web intelligence techniques are used to implement the granular fuzzy Web data mining system for available historical data of the credit company customers. Fuzzy computing and granular computing are used to design the Web fuzzy-interval data mining system that can do fuzzy-interval data clustering under uncertainty.

We present a prototype of a Web querying interface which is capable of searching and querying unified Web sources of data that have sufficient hidden relational structure. The system converts query-related parts of Web pages into relational data and provides for SQL-like or QBE-like querying capability. The relational query is parsed for relevant information such as selection conditions and table names. This information is then used in conjunction with a knowledge base containing the network locations of HTML documents at the unified Web source to retrieve only the relevant documents for conversion to relational form. The system is being developed using Oracle 8.0 and Oracle Application Server 4.0 (JWeb Cartridge).

The well-founded model is one of the most popular models of general logic programs, i.e. logic programs with negation in the bodies of clauses. We present a method for constructing this model for general deductive databases, which are logic programs without any function symbols. The method adopts paraconsistent relations as the semantic objects associated with the predicate symbols of the database. Paraconsistent relations are a generalization of ordinary relations in that they allow manipulation of incomplete as well as inconsistent information. The first step in the model construction method is to transform the database clauses into paraconsistent relation definitions involving these operators. The second step is to build the well-founded model iteratively. Algorithms for both steps are presented and their termination and correctness is also established.

A generalized relational model which is capable of representing and manipulating disjunctive and maybe kinds of information is presented. A data structure, called M-table, is defined, and the information contained in the M-table is precisely stated. Redundant information in M-tables is characterized, and an operator to remove this redundant information is presented. The relational algebra is suitably generalized to deal with M-tables. Additional operators, R-projection and merge, are presented. Queries can be expressed as a combination of the various generalized relational algebraic operators. The M-table accurately models the two bounds on the external interpretation of a query. The sure component of an M-table corresponds to one of the bounds which is the set of objects which belong to the external interpretation of the query. The maybe component of an M-table corresponds to the other bound which is the set of objects for which the possibility of belonging to the external interpretation of the query cannot be ruled out.>

The authors present a generalization of the relational model to represent indefinite and maybe kinds of incomplete information. They introduce a data structure called M-table which is capable of representing disjunctive/indefinite and maybe facts. The notion of redundancy in the context of indefinite and maybe information is studied. The information content of an M-table is precisely defined. The relational algebra is then generalized in a semantically correct manner to operate on M-tables. Queries are posed in the same manner as in the conventional relational algebra; however, the user may now expect indefinite as well as maybe answers.>

This paper extends the relational model to represent indefinite and maybe kinds of incomplete information. A data structure, called an I-table, which is capable of representing indefinite and maybe facts, is introduced. The information content of I-tables is precisely defined, and an operator to remove redundant facts is presented. The relational algebra is then extended in a semantically correct way to operate on I-tables. Queries are posed in the same way as in conventional relational algebra; however, the user may now expect indefinite as well as maybe answers.

An extension is presented of the relational model to present indefinite and maybe kinds of incomplete information. A data structure, called an I-table, is introduced, which is capable of representing indefinite and maybe facts. The information content of the I-table is defined and an operator to remove redundant facts is presented. The relational algebra is then extended, in a semantically correct way, to operate on I-tables. Queries are posed in the same way as in conventional relational algebra, but the user may expect indefinite as well as maybe answers.>