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Articles 15301 - 15330 of 63040

Full-Text Articles in Computer Sciences

Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang Mar 2022

Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang

Research Collection School Of Computing and Information Systems

Recently, there is an emerging trend to apply deep reinforcement learning to solve the vehicle routing problem (VRP), where a learnt policy governs the selection of next node for visiting. However, existing methods could not handle well the pairing and precedence relationships in the pickup and delivery problem (PDP), which is a representative variant of VRP. To address this challenging issue, we leverage a novel neural network integrated with a heterogeneous attention mechanism to empower the policy in deep reinforcement learning to automatically select the nodes. In particular, the heterogeneous attention mechanism specifically prescribes attentions for each role of the …

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Jscsp: A Novel Policy-Based Xss Defense Mechanism For Browsers, Guangquan Xu, Xiaofei Xie, Shuhan Huang, Jun Zhang, Lei Pan, Wei Lou, Kaitai Liang Mar 2022

Jscsp: A Novel Policy-Based Xss Defense Mechanism For Browsers, Guangquan Xu, Xiaofei Xie, Shuhan Huang, Jun Zhang, Lei Pan, Wei Lou, Kaitai Liang

Research Collection School Of Computing and Information Systems

To mitigate cross-site scripting attacks (XSS), the W3C group recommends web service providers to employ a computer security standard called Content Security Policy (CSP). However, less than 3.7 percent of real-world websites are equipped with CSP according to Google’s survey. The low scalability of CSP is incurred by the difficulty of deployment and non-compatibility for state-of-art browsers. To explore the scalability of CSP, in this article, we propose JavaScript based CSP (JSCSP), which is able to support most of real-world browsers but also to generate security policies automatically. Specifically, JSCSP offers a novel self-defined security policy which enforces essential confinements …

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Coders Assembly: Peer Assisted Learning Model For Freshman Programming Courses, Kyong Jin Shim, Gottipati Swapna, Shankararaman, Venky Mar 2022

Coders Assembly: Peer Assisted Learning Model For Freshman Programming Courses, Kyong Jin Shim, Gottipati Swapna, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Today, computing graduates see a bright outlook thanks to the high demand for skills driven by the increasing importance of technology as the main driving force behind business transformation. As technology continues to grow exponentially over recent years, computing graduates have some of the highest starting salaries in the market. Even though universities have increased production of computing degree graduates in recent years, it is insufficient to fill the jobs available in the market. Therefore, going forward, the demand is likely to further increase. The continued demand for computing programs in universities has led to an increased intake size, thus …

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Mrim: Enabling Mixed-Resolution Imaging For Low-Power Pervasive Vision Tasks, Jiyan Wu, Vithurson Subasharan, Tuan Tran, Archan Misra Mar 2022

Mrim: Enabling Mixed-Resolution Imaging For Low-Power Pervasive Vision Tasks, Jiyan Wu, Vithurson Subasharan, Tuan Tran, Archan Misra

Research Collection School Of Computing and Information Systems

While many pervasive computing applications increasingly utilize real-time context extracted from a vision sensing infrastructure, the high energy overhead of DNN-based vision sensing pipelines remains a challenge for sustainable in-the-wild deployment. One common approach to reducing such energy overheads is the capture and transmission of lower-resolution images to an edge node (where the DNN inferencing task is executed), but this results in an accuracy-vs-energy tradeoff, as the DNN inference accuracy typically degrades with a drop in resolution. In this work, we introduce MRIM, a simple but effective framework to tackle this tradeoff. Under MRIM, the vision sensor platform first executes …

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Analyzing The Impact Of Digital Payment On Efficiency And Productivity Of Commercial Banks: A Case Study In China, Haopeng Wang, Aldy Gunawan Mar 2022

Analyzing The Impact Of Digital Payment On Efficiency And Productivity Of Commercial Banks: A Case Study In China, Haopeng Wang, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Digital payment has become one of the most popular payment methods all around the world, especially in countries that witnessed the rapid development of internet. As a traditional financial institution, commercial banks have been impacted by newly developed payment technology since third payment platforms have attracted customers to use the digital payment for daily consumption, transferring, and even investment. This paper focuses on analyzing whether and how the commercial banks in China have been affected by digital payment by using empirical methods. Systematic Generalized Method of Moments (SYS-GMM) is used to test the relationship between the productivity of commercial banks …

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The Ai Chip Race, Guansong Pang Mar 2022

The Ai Chip Race, Guansong Pang

Research Collection School Of Computing and Information Systems

The strong demand of computing power for artificial intelligence (AI) and machine learning is accelerating the race to develop cheaper and faster AI chips. The AI chip market was valued 10.6 billion in 2021 and the total revenue is expected to reach 79.8 billion by 2027. To be part of the market, tech giants from different countries have been successively joining the race, while AI chip startups attracting billions of dollars are taking off like a rocket.

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Ispray: Reducing Urban Air Pollution With Intelligent Water Spraying, Yun Cheng, Zimu Zhou, Lothar Thiele Mar 2022

Ispray: Reducing Urban Air Pollution With Intelligent Water Spraying, Yun Cheng, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Despite regulations and policies to improve city-level air quality in the long run, there lack precise control measures to protect critical urban spots from heavy air pollution. In this work, we propose iSpray, the first-of-its-kind data analytics engine for fine-grained PM2.5 and PM10 control at key urban areas via cost-effective water spraying. iSpray combines domain knowledge with machine learning to profile and model how water spraying affects PM25 and PM10 concentrations in time and space. It also utilizes predictions of pollution propagation paths to schedule a minimal number of sprayers to keep the pollution concentrations at key spots under control. …

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Innovative Human Motion Sensing With Earbuds, Dong Ma, Andrea Ferlini, Cecilia Mascolo Mar 2022

Innovative Human Motion Sensing With Earbuds, Dong Ma, Andrea Ferlini, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

Earbuds, ear-worn wearables, have attracted growing attention from both industry and academia. This trend has witnessed manufacturers embedding multiple sensors on earbuds to enrich their functionalities. For example, Apple AirPods, Sony WF-1000XM3, and Bose QuietControl 30, have been equipped with accelerometers for tapping interaction or multiple microphones for noise cancellation. On the other hand, the research community regards earbuds as a powerful personal-scale human sensing and computing platform. By integrating sensors like PPG, barometer, and ultrasonic sensors, researchers have been devising a plethora of earable sensing applications, such as blood pressure monitoring [1], facial expression recognition [2], and authentication [3].

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Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim Mar 2022

Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/7680/. Developing automatic Math Word Problem (MWP) solvers has been an interest of NLP researchers since the 1960s. Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs. However, most existing methods are benchmarked solely on one or two datasets, varying in different configurations, which leads to a lack of unified, standardized, fair, and comprehensive comparison between methods. This paper presents MWPToolkit, the first open-source framework for solving MWPs. In MWPToolkit, we decompose the procedure of existing MWP solvers into multiple core components and decouple …

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Deconfounded Visual Grounding, Jianqiang Huang, Yu Qin, Jiaxin Qi, Qianru Sun, Hanwang Zhang Mar 2022

Deconfounded Visual Grounding, Jianqiang Huang, Yu Qin, Jiaxin Qi, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

We focus on the confounding bias between language and location in the visual grounding pipeline, where we find that the bias is the major visual reasoning bottleneck. For example, the grounding process is usually a trivial languagelocation association without visual reasoning, e.g., grounding any language query containing sheep to the nearly central regions, due to that most queries about sheep have groundtruth locations at the image center. First, we frame the visual grounding pipeline into a causal graph, which shows the causalities among image, query, target location and underlying confounder. Through the causal graph, we know how to break the …

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Learning Program Semantics With Code Representations: An Empirical Study, Jing Kai Siow, Shangqing Liu, Xiaofei Xie, Guozhu Meng, Yang Liu Mar 2022

Learning Program Semantics With Code Representations: An Empirical Study, Jing Kai Siow, Shangqing Liu, Xiaofei Xie, Guozhu Meng, Yang Liu

Research Collection School Of Computing and Information Systems

Program semantics learning is the core and fundamental for various code intelligent tasks e.g., vulnerability detection, clone detection. A considerable amount of existing works propose diverse approaches to learn the program semantics for different tasks and these works have achieved state-of-the-art performance. However, currently, a comprehensive and systematic study on evaluating different program representation techniques across diverse tasks is still missed. From this starting point, in this paper, we conduct an empirical study to evaluate different program representation techniques. Specifically, we categorize current mainstream code representation techniques into four categories i.e., Feature-based, Sequence-based, Tree-based, and Graph-based program representation technique and …

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State Graph Reasoning For Multimodal Conversational Recommendation, Yuxia Wu, Lizi Liao, Gangyi Zhang, Wenqiang Lei, Guoshuai Zhao, Xueming Qian, Tat-Seng Chua Mar 2022

State Graph Reasoning For Multimodal Conversational Recommendation, Yuxia Wu, Lizi Liao, Gangyi Zhang, Wenqiang Lei, Guoshuai Zhao, Xueming Qian, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational recommendation system (CRS) attracts increasing attention in various application domains such as retail and travel. It offers an effective way to capture users’ dynamic preferences with multi-turn conversations. However, most current studies center on the recommendation aspect while over-simplifying the conversation process. The negligence of complexity in data structure and conversation flow hinders their practicality and utility. In reality, there exist various relationships among slots and values, while users’ requirements may dynamically adjust or change. Moreover, the conversation often involves visual modality to facilitate the conversation. These actually call for a more advanced internal state representation of the dialogue …

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On The Influence Of Biases In Bug Localization: Evaluation And Benchmark, Ratnadira Widyasari, Stefanus Agus Haryono, Ferdian Thung, Jieke Shi, Constance Tan, Fiona Wee, Jack Phan, David Lo Mar 2022

On The Influence Of Biases In Bug Localization: Evaluation And Benchmark, Ratnadira Widyasari, Stefanus Agus Haryono, Ferdian Thung, Jieke Shi, Constance Tan, Fiona Wee, Jack Phan, David Lo

Research Collection School Of Computing and Information Systems

Bug localization is the task of identifying parts of thesource code that needs to be changed to resolve a bug report.As this task is difficult, automatic bug localization tools havebeen proposed. The development and evaluation of these toolsrely on the availability of high-quality bug report datasets. In2014, Kochhar et al. identified three biases in datasets used toevaluate bug localization techniques: (1) misclassified bug report,(2) already localized bug report, and (3) incorrect ground truthfile in a bug report. They reported that already localized bugreports statistically significantly and substantially impact buglocalization results, and thus should be removed. However, theirevaluation is still limited, …

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Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim Mar 2022

Mwptoolkit: An Open-Source Framework For Deep Learning-Based Math Word Problem Solvers, Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

While Math Word Problem (MWP) solving has emerged as a popular field of study and made great progress in recent years, most existing methods are benchmarked solely on one or two datasets and implemented with different configurations. In this paper, we introduce the first open-source library for solving MWPs called MWPToolkit, which provides a unified, comprehensive, and extensible framework for the research purpose. Specifically, we deploy 17 deep learning-based MWP solvers and 6 MWP datasets in our toolkit. These MWP solvers are advanced models for MWP solving, covering the categories of Seq2seq, Seq2Tree, Graph2Tree, and Pre-trained Language Models. And these …

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Efficient Search Of Live-Coding Screencasts From Online Videos, Chengran Yang, Ferdian Thung, David Lo Mar 2022

Efficient Search Of Live-Coding Screencasts From Online Videos, Chengran Yang, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Programming videos on the Internet are valuable resources for learning programming skills. To find relevant videos, developers typically search online video platforms (e.g., YouTube) with keywords on topics they wish to learn. Developers often look for live-coding screencasts, in which the videos’ authors perform live coding. Yet, not all programming videos are livecoding screencasts. In this work, we develop a tool named PSFinder to identify live-coding screencasts. PSFinder leverages a classifier to identify whether a video frame contains an IDE window. It uses a sampling strategy to pick a number of frames from an input video, runs the classifer on …

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Can Identifier Splitting Improve Open-Vocabulary Language Model Of Code?, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, David Lo Mar 2022

Can Identifier Splitting Improve Open-Vocabulary Language Model Of Code?, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, David Lo

Research Collection School Of Computing and Information Systems

Statistical language models on source code have successfully assisted software engineering tasks. However, developers can create or pick arbitrary identifiers when writing source code. Freely chosen identifiers lead to the notorious out-of-vocabulary (OOV) problem that negatively affects model performance. Recently, Karampatsis et al. showed that using the Byte Pair Encoding (BPE) algorithm to address the OOV problem can improve the language models’ predictive performance on source code. However, a drawback of BPE is that it cannot split the identifiers in a way that preserves the meaningful semantics. Prior researchers also show that splitting compound identifiers into sub-words that reflect the …

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Hermes: Using Commit-Issue Linking To Detect Vulnerability-Fixing Commits, Truong Giang Nguyen, Hong Jin Kang, David Lo, Abhishek Sharma, Andrew E. Santosa, Asankhaya Sharma, Ming Yi Ang Mar 2022

Hermes: Using Commit-Issue Linking To Detect Vulnerability-Fixing Commits, Truong Giang Nguyen, Hong Jin Kang, David Lo, Abhishek Sharma, Andrew E. Santosa, Asankhaya Sharma, Ming Yi Ang

Research Collection School Of Computing and Information Systems

Software projects today rely on many third-party libraries, and therefore, are exposed to vulnerabilities in these libraries. When a library vulnerability is fixed, users are notified and advised to upgrade to a new version of the library. However, not all vulnerabilities are publicly disclosed, and users may not be aware of vulnerabilities that may affect their applications. Due to the above challenges, there is a need for techniques which can identify and alert users to silent fixes in libraries; commits that fix bugs with security implications that are not officially disclosed. We propose a machine learning approach to automatically identify …

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Learning User Interface Semantics From Heterogeneous Networks With Multi-Modal And Positional Attributes, Gary Ang, Ee-Peng Lim Mar 2022

Learning User Interface Semantics From Heterogeneous Networks With Multi-Modal And Positional Attributes, Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

User interfaces (UI) of desktop, web, and mobile applications involve a hierarchy of objects (e.g. applications, screens, view class, and other types of design objects) with multimodal (e.g. textual, visual) and positional (e.g. spatial location, sequence order and hierarchy level) attributes. We can therefore represent a set of application UIs as a heterogeneous network with multimodal and positional attributes. Such a network not only represents how users understand the visual layout of UIs, but also influences how users would interact with applications through these UIs. To model the UI semantics well for different UI annotation, search, and evaluation tasks, this …

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Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan Misra, Nirmalya Roy Mar 2022

Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan Misra, Nirmalya Roy

Research Collection School Of Computing and Information Systems

We tackle the problem of domain adaptation for inertial sensing-based human activity recognition (HAR) applications -i.e., in developing mechanisms that allow a classifier trained on sensor samples collected under a certain narrow context to continue to achieve high activity recognition accuracy even when applied to other contexts. This is a problem of high practical importance as the current requirement of labeled training data for adapting such classifiers to every new individual, device, or on-body location is a major roadblock to community-scale adoption of HAR-based applications. We particularly investigate the possibility of ensuring robust classifier operation, without requiring any new labeled …

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Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin Pu, Ying Zhang, Li-Chen Chou Mar 2022

Estimating Financial Information Asymmetry In Real Estate Transactions In China: An Application Of Two-Tier Frontier Model, Ganlin Pu, Ying Zhang, Li-Chen Chou

Research Collection School Of Computing and Information Systems

This study applies the two-tier stochastic frontier model to estimate the distribution of housing transaction information in Hangzhou, Wenzhou, Ningbo, and Jinhua (four cities in Zhejiang Province, China) during the year 2018, to analyze the difference in the price information acquired by the buyers and sellers in the transaction, and the effect of information asymmetry on the transaction price. The empirical results show that in each city, during the housing transaction process, the supplier has more complete information about house prices than consumers, and can therefore implement price discrimination strategies in setting service prices. Due to the disadvantage in acquired …

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The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo Mar 2022

The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo

Research Collection School Of Computing and Information Systems

We study the role of ride-hailing surge factors on the allocative efficiency of taxis by combining a reduced-form estimation with structural analyses using machine-learning-based demand predictions. Where other research study the effect of entry on incumbent taxis, we use higher frequency granular data to study how location-time-specific surge factors affect taxi bookings to bound the effect of customer decisions while accounting for various confounding variables. We find that even in a unique market like Singapore, where incumbent taxi companies have app-based booking systems similar to those from ride-hailing companies like Uber, the estimated upper bound on the cross-platform substitution between …

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Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu Mar 2022

Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu

Research Collection School Of Computing and Information Systems

This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …

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Gender Influence On Communication Initiated Within Student Teams, Rita Garcia, Chieh-Ju Trinity Liao, Ariane Pearce, Christoph Treude Mar 2022

Gender Influence On Communication Initiated Within Student Teams, Rita Garcia, Chieh-Ju Trinity Liao, Ariane Pearce, Christoph Treude

Research Collection School Of Computing and Information Systems

Collaboration is important during software development, but related work has found gender differences can influence the collaboration process, creating inequality in the team’s dynamics. In this paper, we present a gender analysis study that involved 39 students, examining their teams’ online collaborations while contributing to a large open-source software project. Eight teams of 4-6 Software Engineering (SE) students communicated over an online messaging platform, Slack, to complete an eight-week project. The goal of this study is to identify gender differences emerging from team collaboration. A mixed-methods approach was used to collect students’ teamwork experiences and analyse their collaboration. Our research …

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Analysing Tweets On Covid-19 Vaccine : A Text Mining Approach, Swetha Gottipati, Debashis Guha Mar 2022

Analysing Tweets On Covid-19 Vaccine : A Text Mining Approach, Swetha Gottipati, Debashis Guha

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused large scale health, economic, and social crisis. Scientists throughout the globe have been working on producing effective vaccines to combat this pandemic. COVID-19 vaccine release started in 2020, and low take-up rates among the public have been observed initially. There has been a soar in social media data on vaccines. This paper presents a comprehensive analysis of COVID-19 vaccine-related tweets. Sentiments shared by people through tweets and common topics have been extracted using classification and sentiment analysis. Our results showed a higher negative sentiment when the pandemic was declared, and it gradually changed to positive …

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Patterns Of Academic Help-Seeking In Undergraduate Computing Students, Augie Doebling Mar 2022

Patterns Of Academic Help-Seeking In Undergraduate Computing Students, Augie Doebling

Master's Theses

Knowing when and how to seek academic help is crucial to the success of undergraduate computing students. While individual help-seeking resources have been studied, little is understood about the factors influencing students to use or avoid certain re- sources. Understanding students’ patterns of help-seeking can help identify factors contributing to utilization or avoidance of help resources by different groups, an important step toward improving the quality and accessibility of resources. We present a mixed-methods study investigating the help-seeking behavior of undergraduate computing students. We collected survey data (n = 138) about students’ frequency of using several resources followed by one-on-one …

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Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry Mar 2022

Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry

Theses and Dissertations

The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.

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Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim Mar 2022

Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

As the insulated gate bipolar transistor (IGBT) modules have their own specific characteristic switching forms, their turn-on and turn-off times are changed according to practical applications. For the conventional gate drives, gate resistors are used to adjust the turn-on and turn-off times which change switching losses that have a significant amount in total losses. Collector current rate of change, $di_{C}/ dt$ and collector-emitter rate of change, $dv_{CE}/ dt$ are dependent on each other and they affect operating parameters in high power converters. Relations between current and voltages during the switching transitions are given and effects of the changes in electrical …

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Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu Mar 2022

Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Centroid based clustering approaches, such as k-means, are relatively fast but inaccurate for arbitrary shape clusters. Fuzzy c-means with Mahalanobis distance can accurately identify clusters if data set can be modelled by a mixture of Gaussian distributions. However, they require number of clusters apriori and a bad initialization can cause poor results. Density based clustering methods, such as DBSCAN, overcome these disadvantages. However, they may perform poorly when the dataset is imbalanced. This paper proposes a clustering method, named clustering with density initialization and Bhattacharyya based merging based on the fuzzy clustering. The initialization is carried out by density estimation …

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Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli Mar 2022

Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli

Turkish Journal of Electrical Engineering and Computer Sciences

Optical time-domain reflectometers (OTDR) are photonic systems that consist of an interrogator, a receiver and a fiber optical cable and have applications in telecommunications, security, environmental monitoring, distributed temperature and strain sensing. Since OTDR systems are bulk optical setups that consume multiple Watts of power, have large mass and volume footprint and are vulnerable to thermal drift, deployment of OTDR systems in the field is expensive, complicated and may not necessarily yield accurate sensing results. Thus, a compact, low-power, inexpensive and thermal drift-free OTDR system needs to be developed for improving the accuracy and the viability of OTDR in the …

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Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng Mar 2022

Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng

Turkish Journal of Electrical Engineering and Computer Sciences

With the popularization, in-depth development and application of the Internet, microblogs have become a mainstream social network platform. Several studies on social networks have conducted researches, and user influence evaluation is an important research hotspot. Most of the existing studies calculate user influence by improving PageRank and have achieved certain results. However, these studies ignored the fusion of users' interest theme similarity and information dissemination ability, and the analysis of interaction behaviors among users is not comprehensive. To address these issues, we propose a new microblog user influence algorithm called microblog user influence based on interest similarity and information dissemination …

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