reference stringlengths 141 444k | target stringlengths 31 68k |
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A survey of power management techniques in mobile computing operating systems <s> I <s> Recent advances in hardware and communication technology have made mobile computing possible. It is expected, [BIV92], that in the near future, tens of millions of users will carry a portable computer with a wireless connection to a... | The motivation behind searching for and exploiting unique organization and access methods stems from the potential savings in power resulting from being able to wait for expected incoming data while in a "doze" mode BIB001 . When the mobile computer is receiving, it (its CPU) must be in the "active" mode. As was argued... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> INTRODUCTION <s> Discover BIM: A better way to build better buildings. Building Information Modeling (BIM) is a new approach to design, construction, and facility management in which a dig... | Building Information Modelling (BIM) has received much attention in academia and architecture/engineering construction sector BIB001 . BIM is defined by the US National BIM Standard as "A digital representation of physical and functional characteristics BIB001 Permission to make digital or hard copies of all or part of... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Integration Methods <s> Only very few constructed facilities today have a complete record of as-built information. Despite the growing use of Building Information Modelling and the improve... | This part is about how BIM can be integrated with sensor technology and mainly discussed three subthemes: what kind of sensor should be chosen; how the sensors should be arranged and distributed in the building; and how to integrate BIM with data collected from sensors, which includes data processing, analysis and pres... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Sustainable Building <s> Evaluating a building's performance usually requires a high number of sensors especially if individual rooms are analyzed. This paper introduces a simple and scala... | This theme is concerned with two parts: energy consumption and environment protection. Building energy consumption research focuses on energy monitoring and the establishment of a method to improve energy performance or save energy, while environmental protection research concerns about saving resources and carbon emis... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Site Management <s> Abstract Tower crane operators often operate a tower crane with blind spots. To solve this problem, video camera systems and anti-collision systems are often deployed. ... | This theme includes many aspects, such as operation of site equipment, monitoring site environment, site security management and construction quality management. Various types of sensor are used in site management because it involves many aspects. Alizadehsalehia and Yitmen conducted a survey of construction companies... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Operation and Maintenance <s> This paper presents results of the first phase of the research project ''Serious Human Rescue Game'' at Technische Universitat Darmstadt. It presents a new se... | This direction includes many aspects, such as indoor environment monitoring and conditioning, user experience optimisation, emergency management and facility management. Marzouk and Abdelaty BIB002 used WSN to collect PM10, PM2.5, temperature and humidity data and proposed a global ranking system integrated with BIM to... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Structural Health Monitoring <s> AbstractBuilding information modelling (BIM) represents the process of development and use of a computer generated model to simulate the planning, design, ... | This theme is concerned about the monitoring of mechanics situation of structures and the discovery of structure defects. Structural defect can be divided into two types: structural partial defect, such as crack and over deflection of concrete elements, and structural integral defect, such as poor verticality and flatn... |
Integration of Building Information Modelling (BIM) and Sensor Technology: A Review of Current Developments and Future Outlooks <s> Positioning and Tracing <s> The purposes of this research are to develop and evaluate a framework that utilizes the integration of commercially-available Radio Frequency Identification (RF... | This direction is to develop a method to locate or trace facilities or people inside a building by using sensors. Positioning and tracing can be applied in many occasions, such as emergency management, site security management, user experience optimization and facility management. Costin et al. BIB001 put forward that ... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Methodological Background <s> This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehe... | In this section, we introduce the basics of stream clustering. Most importantly, we describe how data streams are typically aggregated and how algorithms adapt to changes over time. For a consistent notation, we denote vectors by boldface symbols and formally define a data stream as an infinite sequence X = (x 1 , x 1 ... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Time Window Models <s> Consider the problem of monitoring tens of thousands of time series data streams in an online fashion and making decisions based on them. In addition to single stream statistics such as average and stan... | As shown in our eye tracking example, the underlying distribution of the stream will often change over time. This is also known as drift or concept-shift. To handle this, algorithms can employ time window models. This approach aims to 'forget' older data to avoid that historic data is biasing the analysis to outdated p... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Clustering Feature <s> Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely studied problems in this area is the identification of clusters, or densely populated r... | BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) BIB001 BIB002 is one of the earliest algorithms applicable to stream clustering. It reduces the information maintained about a cluster to only a few summary statistics stored in a so called Clustering Feature (CF). The CF consists of three components:... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Extended Clustering Feature <s> Recently, the continuously arriving and evolving data stream has become a common phenomenon in many fields, such as sensor networks, web click stream and internet traffic flow. One of the most ... | CluStream ] extends the CF from BIRCH which allows to perform clustering over different time-horizons rather than the entire data stream. The extended CF is defined as (LS, SS, LS (t) , SS (t) , n), where LS (t) and SS (t) are the linear and squared sum of all timestamps of a cluster. The online algorithm is initializ... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Time-Faded Clustering Feature <s> Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for cluste... | DenStream ] presents a temporal extension of the CFs from BIRCH. It maintains two types of clusters: Potential core micro-clusters are stable structures that are denoted using a time-faded CF LS (ω) , SS (ω) , n (ω) . The superscript (ω) denotes that each entry of the CF is decayed over time using a decay function ω(∆... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> E-Stream <s> Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited. Clustering has to be performed... | HUE-Stream BIB003 is an extension of E-Stream which also supports categorical data and can also handle uncertain data streams. To model uncertainty, each observation is assumed to follow a probability distribution. In this case, the vectors of linear and squared sum become the sum of expectation, faded over time. ClusT... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Medoids <s> The k-means method is a widely used clustering technique that seeks to minimize the average squared distance between points in the same cluster. Although it offers no accuracy guarantees, its simplicity and speed ... | An alternative to storing Clustering Features is to maintain medoids of clusters, i.e., representatives. RepStream BIB002 BIB003 , for example, incrementally updates a graph of nearest neighbors to identify suitable cluster representatives. New observations are inserted as a new node in the graph and edges are inserted... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Centroids <s> Streaming data analysis has recently attracted attention in numerous applications including telephone records, Web documents and click streams. For such analysis, single-pass algorithms that consume a small amou... | A simpler approach to maintain clusters is to store their centroids directly. However, this makes it generally more difficult to update clusters over time. As an example, STREAM BIB001 BIB002 ] only stores the centroids of k clusters. Its core idea is to treat the k-Median clustering problem as a facility planning prob... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Competitive Learning <s> Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algo... | More recently, algorithms also use competitive learning strategies in order to adapt the centroids of clusters over time. This is inspired by Self-Organizing Maps (SOMs) BIB002 where clusters compete to represent an observation, typically by moving cluster centers towards new observations based on their proximity. SOSt... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Summary <s> This work contains a theoretical study and computer simulations of a new self-organizing process. The principal discovery is that in a simple network of adaptive physical elements which receives signals from a pri... | Distance-based algorithms are by far the most common and popular approaches in stream clustering. They allow to create accurate summaries of the entire stream with rather simple insertion rules. Since it is infeasible to store all observations within the clusters, distance-based algorithms usually summarize the observa... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> D-Stream <s> In the field of data stream analysis,conventional methods seem not quite useful.Because neither they can adapt to the dynamic environment of data stream,nor the mining models and results can meet users' needs.A g... | In BIB002 , the authors extended their concept by a measure of attraction that incorporates positional information of data within a grid-cell. This variant only merges neighboring cells if they share many points at the cell border. BIB001 ] is a small extension on how to handle points that lie exactly on the grid bound... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> DD-Stream <s> Clustering is a widely used knowledge discovery technique. It helps uncovering structures in data that were not previously known. The clustering of large data sets has received a lot of attention in recent years... | ExCC BIB002 (Exclusive and Complete Clustering) constructs a grid where the number of cells and grid boundaries are chosen by the user. This allows to handle categorical data, where the number of cells is chosen to be equal to the number of attribute levels. Clusters are identified as neighboring dense cells. Cells of... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Recursive Partitioning <s> A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to this reason, most algorithms for data streams sacrifice the correctness of their results... | Stats-Grid BIB001 is an early algorithm which recursively partitions grid-cells. The algorithm begins by splitting the data into grid-cells of fixed size. Each cell maintains its density, mean and standard deviation. The algorithm then recursively partitions grid-cells until cells become sufficiently small unit cells. ... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Hybrid Grid-Approaches <s> Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering al... | HDCStream (hybrid density-based clustering for data stream) first combined grid-based algorithms with the concept of distancebased algorithms. In particular, it maintains a grid where dense cells can be promoted to become micro-clusters as known from distanced-based algorithms (see Section 4). Each observation in the ... |
Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms <s> Projected Approaches <s> Many clustering algorithms tend to break down in high-dimensional feature spaces, because the clusters often exist only in specific subspaces (attribute subsets) of the original feature space. Therefo... | A special category of stream clustering algorithms deals with high dimensional data streams. These types of algorithms address the curse of dimensionality , i.e., the problem that almost all points have an equal distance in very high dimensional space. In such scenarios, clusters are defined Offline Clustering HPStrea... |
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YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Dataset
- split_survey_df: The split version of SciReviewGen, which aims to generate literature review chapters
- original_survey_df: The original version of SciReviewGen, which aims to generate the entire text of literature reviews
- summarization_csv: CSV files suitable for summarization task.
Data format
split_survey_df & original_survey_df
- Row:
- literature review chapter or the entire text of literature review
- Column:
- paper_id: paper_id used in S2ORC
- title: title of the literature review
- abstract: abstract of the literature review
- section: chapter title
- text: body text of literature review chapter or literature review paper
- n_bibs: number of the cited papers that can be used as inputs
- n_nonbibs: number of the cited papers that cannot be used as inputs
- bib_titles: titles of the cited papers
- bib_abstracts: abstracts of the cited papers
- bib_citing_sentences: citing sentences that cite the cited papers
- split: train/val/test split
summarization_csv
- Row:
- literature review chapter
- Column:
- reference:
literature review title <s> chapter title <s> abstract of cited paper 1 <s> BIB001 </s> literature review title <s> chapter title <s> abstract of cited paper 2 <s> BIB002 </s> ... - target: literature review chapter
- reference:
Data construction
Use make_summarization_csv.py to convert df to csv
Reference
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