Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00241
Chawanangwa Lupafya, D. Balasubramaniam
There are many aspects involved in the development and operation of a software system, including system artefacts, activities, and infrastructure. Most of these aspects are vulnerable to uncertainty, which can result in risks to system quality and performance. Thus it is important to identify, represent and manage uncertainty in software systems. We hypothesise that using an underlying conceptual framework for characterising uncertainty can facilitate these activities. This paper demonstrates the use of an extensible framework, which defines a foundation for the systematic and explicit consideration of uncertainty in software systems. A software architecture case study is used to illustrate and evaluate the framework. A discussion of potential uses for the framework and future research is also provided.
{"title":"A Framework for Considering Uncertainty in Software Systems","authors":"Chawanangwa Lupafya, D. Balasubramaniam","doi":"10.1109/COMPSAC54236.2022.00241","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00241","url":null,"abstract":"There are many aspects involved in the development and operation of a software system, including system artefacts, activities, and infrastructure. Most of these aspects are vulnerable to uncertainty, which can result in risks to system quality and performance. Thus it is important to identify, represent and manage uncertainty in software systems. We hypothesise that using an underlying conceptual framework for characterising uncertainty can facilitate these activities. This paper demonstrates the use of an extensible framework, which defines a foundation for the systematic and explicit consideration of uncertainty in software systems. A software architecture case study is used to illustrate and evaluate the framework. A discussion of potential uses for the framework and future research is also provided.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Automated driving systems(ADS) are major trend and the safety of such critical system has become one of the most important research topics. We usually use scenarios in order to define the specifications of ADS. In these scenarios, graphical diagrams are often used to represent abstractly the positioning and behavior of vehicles. However, such diagrams are not suitable for the development of high-reliability systems, because they are informal and may cause discrepancies among different engineers. In this paper, we propose a formal speci-fication language called Bounding Box Specification Language (BBSL) which allows us to write rigorous specifications of ADS. BBSL describe multiple types of objects in a driving environment, such as vehicles and pedestrians, as bounding boxes defined as two-dimensional interval, and describe positional relationships between them in mathematical notation. It is capable of strictly delineating many positional relationships while being also capable of expressing specifications that are concise enough to be read and written manually. Therefore, BBSL is suitable for describing the specification of Object and Event Detection and Response (OEDR) among the tasks of ADS. In this paper, we describe what kind of description BBSL enables, and describe its operations. Then, we show examples of specifications of ADS written in BBSL and discuss the advantages of specifications written in BBSL.
{"title":"A Formal Specification Language Based on Positional Relationship Between Objects in Automated Driving Systems","authors":"Kento Tanaka, Toshiaki Aoki, Tatsuji Kawai, Takashi Tomita, Daisuke Kawakami, Nobuo Chida","doi":"10.1109/COMPSAC54236.2022.00147","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00147","url":null,"abstract":"Automated driving systems(ADS) are major trend and the safety of such critical system has become one of the most important research topics. We usually use scenarios in order to define the specifications of ADS. In these scenarios, graphical diagrams are often used to represent abstractly the positioning and behavior of vehicles. However, such diagrams are not suitable for the development of high-reliability systems, because they are informal and may cause discrepancies among different engineers. In this paper, we propose a formal speci-fication language called Bounding Box Specification Language (BBSL) which allows us to write rigorous specifications of ADS. BBSL describe multiple types of objects in a driving environment, such as vehicles and pedestrians, as bounding boxes defined as two-dimensional interval, and describe positional relationships between them in mathematical notation. It is capable of strictly delineating many positional relationships while being also capable of expressing specifications that are concise enough to be read and written manually. Therefore, BBSL is suitable for describing the specification of Object and Event Detection and Response (OEDR) among the tasks of ADS. In this paper, we describe what kind of description BBSL enables, and describe its operations. Then, we show examples of specifications of ADS written in BBSL and discuss the advantages of specifications written in BBSL.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124586797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00070
Wook-Sung Yoo, Hwapyeong Song, Hyun-Duck Kim
Periodontitis is a chronic inflammatory disease of the tissue around the teeth. The early detection of periodontitis before it manifests undesirable irreversible destruction of periodontal tissues has been an important issue in public dental health. The clinical examination is a traditional way of the diagnosis of periodontal diseases but is often insufficient and does not provide information on the current activity of periodontitis or its progression. After intensive clinical studies in the Department of Preventive and Social Dentistry at Seoul National University (SNU) in South Korea, the salivary matrix-metalloproteinase (MMP)-9 was identified as one of the major enzymes responsible for the initiation of periodontitis. SNU developed a point-of-care (POC) kit for a lateral flow test (LFT) using MMP-9 and created a diagnostic model based on a patient's personal information for screening periodontitis. After the successful clinical studies, the Rapid Periodontitis screening Tool (RPT), a database-driven web application, was developed to measure the risk of periodontitis online with the collaboration between the School of Dentistry at SNU and the Computer Science Program at Marshall University in the United States. The web interface in RPT allows anyone to enter their personal data and the value of LFT test results to receive the screening result immediately. The RPT also provides member pages to track down the test results in the long run. Once commercialized, the RPT will help early detection of periodontitis to enhance public health. This paper describes details of the tool and future research direction.
{"title":"Collaborative Research on Rapid Periodontitis Test","authors":"Wook-Sung Yoo, Hwapyeong Song, Hyun-Duck Kim","doi":"10.1109/COMPSAC54236.2022.00070","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00070","url":null,"abstract":"Periodontitis is a chronic inflammatory disease of the tissue around the teeth. The early detection of periodontitis before it manifests undesirable irreversible destruction of periodontal tissues has been an important issue in public dental health. The clinical examination is a traditional way of the diagnosis of periodontal diseases but is often insufficient and does not provide information on the current activity of periodontitis or its progression. After intensive clinical studies in the Department of Preventive and Social Dentistry at Seoul National University (SNU) in South Korea, the salivary matrix-metalloproteinase (MMP)-9 was identified as one of the major enzymes responsible for the initiation of periodontitis. SNU developed a point-of-care (POC) kit for a lateral flow test (LFT) using MMP-9 and created a diagnostic model based on a patient's personal information for screening periodontitis. After the successful clinical studies, the Rapid Periodontitis screening Tool (RPT), a database-driven web application, was developed to measure the risk of periodontitis online with the collaboration between the School of Dentistry at SNU and the Computer Science Program at Marshall University in the United States. The web interface in RPT allows anyone to enter their personal data and the value of LFT test results to receive the screening result immediately. The RPT also provides member pages to track down the test results in the long run. Once commercialized, the RPT will help early detection of periodontitis to enhance public health. This paper describes details of the tool and future research direction.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128304616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00217
Andreas Mäkilä, A. Friebe, Leif Enblom, P. Strandberg, T. Seceleanu
Many hardware solutions for Power over Ethernet (PoE) Power Sourcing Equipment (PSE) exist, with slightly varying feature sets. A software solution is needed for interaction with the PSEs, and for managing a power budget across several PSEs. A generic interface is desirable, as well as generic software components that can be used in support of several PSE solutions. In this paper we present a union of features and real-time requirements for three hardware solutions, and the development of a generic software architecture.
{"title":"A Generic Software Architecture for PoE Power Sourcing Equipment","authors":"Andreas Mäkilä, A. Friebe, Leif Enblom, P. Strandberg, T. Seceleanu","doi":"10.1109/COMPSAC54236.2022.00217","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00217","url":null,"abstract":"Many hardware solutions for Power over Ethernet (PoE) Power Sourcing Equipment (PSE) exist, with slightly varying feature sets. A software solution is needed for interaction with the PSEs, and for managing a power budget across several PSEs. A generic interface is desirable, as well as generic software components that can be used in support of several PSE solutions. In this paper we present a union of features and real-time requirements for three hardware solutions, and the development of a generic software architecture.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127035034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00114
Zhengxin Li, Sikai Tao, Ruixun Zhang, Hongpeng Wang
Medical segmentation of cochlear images aims to identify the area of the cochlea in a set of CT slices. The shape of cochlea will vary a quite in different CT slicing levels, and the relevant dataset has a higher labeling cost. This will lead to segmentation results with edge discontinuity when we implement supervised algorithm under few samples. In order to solve the problem of a small number of labeled images, this paper proposes a semi-supervised model called GSDNet which is based on GAN, which captures the features of the cochlear image without labels, so as to achieve high performance for processing fewer sampled data. To further improve the generalization of the model, we adopt a training method that allows the model to gradually distinguish between real images and fake images. In addition, in order to solve the problem of local noise interference and discontinuous segmentation results, we introduce a label discrimination network to force the distribution of generated results from segmentation network to align with the true label distribution, so that the edges of the segmentation results are continuous and the shape is more accurate. Finally, we conduct a segmentation experiment of the cochlear region containing 30 slices about cochlea data, and compare different cutting-edge methods. The method proposed in this paper achieves higher performance on the dice index.
{"title":"GSDNet: An Anti-interference Cochlea Segmentation Model Based on GAN","authors":"Zhengxin Li, Sikai Tao, Ruixun Zhang, Hongpeng Wang","doi":"10.1109/COMPSAC54236.2022.00114","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00114","url":null,"abstract":"Medical segmentation of cochlear images aims to identify the area of the cochlea in a set of CT slices. The shape of cochlea will vary a quite in different CT slicing levels, and the relevant dataset has a higher labeling cost. This will lead to segmentation results with edge discontinuity when we implement supervised algorithm under few samples. In order to solve the problem of a small number of labeled images, this paper proposes a semi-supervised model called GSDNet which is based on GAN, which captures the features of the cochlear image without labels, so as to achieve high performance for processing fewer sampled data. To further improve the generalization of the model, we adopt a training method that allows the model to gradually distinguish between real images and fake images. In addition, in order to solve the problem of local noise interference and discontinuous segmentation results, we introduce a label discrimination network to force the distribution of generated results from segmentation network to align with the true label distribution, so that the edges of the segmentation results are continuous and the shape is more accurate. Finally, we conduct a segmentation experiment of the cochlear region containing 30 slices about cochlea data, and compare different cutting-edge methods. The method proposed in this paper achieves higher performance on the dice index.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114418992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00212
Luca Barbierato, Daniele Salvatore Schiera, R. Scoccia, Alessandro Margara, Lorenzo Bottaccioli, E. Patti
The ongoing energy transition to reduce carbon emissions presents some of the most formidable challenges the energy sector has ever experienced, requiring a paradigm change that involves diverse players and heterogeneous concerns, including regulations, economic drivers, societal, and environmental aspects. Central to this transition is the adoption of integrated Multi-Energy Systems (MES) to efficiently produce, distribute, store, and convert energy among different vectors. A deep understanding of MES is fundamental to harness the potential for energy savings and foster energy transition towards a low carbon future. Unfortunately, the inherent complexity of MES makes them extremely difficult to analyze, understand, design and optimize. This work proposes a digital twin co-simulation platform that provides a structured basis to design, develop and validate novel solutions and technologies for multi-energy system. The platform will enable the definition of a virtual representation of the real-world (digital twin) as a composition of models (co-simulation) that analyze the environment from multiple viewpoints and at different spatio-temporal scales.
{"title":"COMET: Co-simulation of Multi-Energy Systems for Energy Transition","authors":"Luca Barbierato, Daniele Salvatore Schiera, R. Scoccia, Alessandro Margara, Lorenzo Bottaccioli, E. Patti","doi":"10.1109/COMPSAC54236.2022.00212","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00212","url":null,"abstract":"The ongoing energy transition to reduce carbon emissions presents some of the most formidable challenges the energy sector has ever experienced, requiring a paradigm change that involves diverse players and heterogeneous concerns, including regulations, economic drivers, societal, and environmental aspects. Central to this transition is the adoption of integrated Multi-Energy Systems (MES) to efficiently produce, distribute, store, and convert energy among different vectors. A deep understanding of MES is fundamental to harness the potential for energy savings and foster energy transition towards a low carbon future. Unfortunately, the inherent complexity of MES makes them extremely difficult to analyze, understand, design and optimize. This work proposes a digital twin co-simulation platform that provides a structured basis to design, develop and validate novel solutions and technologies for multi-energy system. The platform will enable the definition of a virtual representation of the real-world (digital twin) as a composition of models (co-simulation) that analyze the environment from multiple viewpoints and at different spatio-temporal scales.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130057703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00201
You Liang, A. Thavaneswaran, Alex Paseka, W. Qiao, M. Ghahramani, Sulalitha Bowala
Pairs trading strategies are constructed based on exploiting mean reversion in security prices, which have been demonstrated to perform well for stocks. However, their performance is not widely studied for cryptocurrencies, which are usually discerned as inefficient and unpredictable. One significant advantage of pairs trading is that potential profits can be generated regardless of the overall market movement. The pairs trading has the potential to be profitable for cryptocurrencies in bear markets and with intraday data. Kalman filter (KF) algorithms are popular for pairs trading to update the hedge ratio dynamically. They reduce the arbitrariness in parameter optimization by putting constraints on the parameter space. However, a major drawback is that the innovation volatility estimate calculated by using a KF algorithm is always affected by the initial values and outliers. An effective resilient filtering approach to estimate the innovation volatility is presented in this paper for cryptocurrencies. This paper presents rolling regression pairs trading strategies, traditional KF pairs trading strategies and resilient filter pairs trading strategies. The proposed trading strategies have been evaluated through some experiments on hourly Bitcoin USD and Ethereum USD prices and it is shown that the proposed resilient filter trading strategy is much more stable to initial values than the traditional KF trading strategy.
{"title":"A Novel Optimal Profit Resilient Filter Pairs Trading Strategy for Cryptocurrencies","authors":"You Liang, A. Thavaneswaran, Alex Paseka, W. Qiao, M. Ghahramani, Sulalitha Bowala","doi":"10.1109/COMPSAC54236.2022.00201","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00201","url":null,"abstract":"Pairs trading strategies are constructed based on exploiting mean reversion in security prices, which have been demonstrated to perform well for stocks. However, their performance is not widely studied for cryptocurrencies, which are usually discerned as inefficient and unpredictable. One significant advantage of pairs trading is that potential profits can be generated regardless of the overall market movement. The pairs trading has the potential to be profitable for cryptocurrencies in bear markets and with intraday data. Kalman filter (KF) algorithms are popular for pairs trading to update the hedge ratio dynamically. They reduce the arbitrariness in parameter optimization by putting constraints on the parameter space. However, a major drawback is that the innovation volatility estimate calculated by using a KF algorithm is always affected by the initial values and outliers. An effective resilient filtering approach to estimate the innovation volatility is presented in this paper for cryptocurrencies. This paper presents rolling regression pairs trading strategies, traditional KF pairs trading strategies and resilient filter pairs trading strategies. The proposed trading strategies have been evaluated through some experiments on hourly Bitcoin USD and Ethereum USD prices and it is shown that the proposed resilient filter trading strategy is much more stable to initial values than the traditional KF trading strategy.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126648924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00240
Lili Xiao, Huibiao Zhu, Mengda He, S. Qin
The C++11 standard introduced a language level weak memory model (i.e., the C++11 memory model) to improve the performance of the execution of C/C++ programs. Algebra is well-suited for direct use by engineers in symbolic calculation of parameters. It is a challenge to investigate the algebraic semantics for the C++11 memory model. Inspired by the promising semantics, in this paper, we explore the algebraic laws for the C++11 memory model, including a set of sequential and parallel expansion laws. We introduce the concept of guarded choice, and every program under the C++11 memory model can be converted into the head normal form of guarded choice. In addition, the proposed algebraic laws are implemented in the rewriting engine Maude.
c++ 11标准引入了一种语言级弱内存模型(即c++ 11内存模型)，以提高C/ c++程序的执行性能。代数非常适合工程师在参数的符号计算中直接使用。研究c++ 11内存模型的代数语义是一个挑战。受这一前景语义的启发，本文探讨了c++ 11内存模型的代数定律，包括一组顺序和并行展开定律。引入了保护选择的概念，c++ 11内存模型下的每个程序都可以转换为保护选择的头部范式。此外，所提出的代数定律在重写引擎Maude中实现。
{"title":"Algebraic Semantics for C++11 Memory Model","authors":"Lili Xiao, Huibiao Zhu, Mengda He, S. Qin","doi":"10.1109/COMPSAC54236.2022.00240","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00240","url":null,"abstract":"The C++11 standard introduced a language level weak memory model (i.e., the C++11 memory model) to improve the performance of the execution of C/C++ programs. Algebra is well-suited for direct use by engineers in symbolic calculation of parameters. It is a challenge to investigate the algebraic semantics for the C++11 memory model. Inspired by the promising semantics, in this paper, we explore the algebraic laws for the C++11 memory model, including a set of sequential and parallel expansion laws. We introduce the concept of guarded choice, and every program under the C++11 memory model can be converted into the head normal form of guarded choice. In addition, the proposed algebraic laws are implemented in the rewriting engine Maude.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127165144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Credit risk assessment, which aims at identifying high-risk users, plays a critical role in financial institutions. A common method is to use the greedy strategy to generate an interpretable rule set to classify all the users into high-risk or non-risk users. During each iteration, the greedy strategy utilizes a pre-defined indicator function to evaluate which rule is the best and then adds it to the rule set. However, in reality, the indicator function is designed manually and requires much domain knowledge and expert experience. Worse still, we need to design a suitable indicator for every situation, which is tedious and time-consuming work. This motivates us to propose a self-adaptive indicator that can be adapted to different situations without too much human intervention. In this paper, we see the indicator as a weighted sum of several sub-indicators. By tuning the weights, the indicator can be adapted to different situations automatically. That is, we transform this indicator selection problem into a weights tuning problem. To find the best weight of self-adaptive indicators, machine learning methods and black-box optimization are utilized. The experimental results demonstrated that our self-adaptive indicator can select a better rule set to identify more high-risk users compared to the human-defined indicator.
{"title":"A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment","authors":"Yongfeng Gu, Yue Ning, Hao Ding, Kecai Gu, Daohong Jian, Zhou Xu, Hua Wu, Jun Zhou","doi":"10.1109/COMPSAC54236.2022.00249","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00249","url":null,"abstract":"Credit risk assessment, which aims at identifying high-risk users, plays a critical role in financial institutions. A common method is to use the greedy strategy to generate an interpretable rule set to classify all the users into high-risk or non-risk users. During each iteration, the greedy strategy utilizes a pre-defined indicator function to evaluate which rule is the best and then adds it to the rule set. However, in reality, the indicator function is designed manually and requires much domain knowledge and expert experience. Worse still, we need to design a suitable indicator for every situation, which is tedious and time-consuming work. This motivates us to propose a self-adaptive indicator that can be adapted to different situations without too much human intervention. In this paper, we see the indicator as a weighted sum of several sub-indicators. By tuning the weights, the indicator can be adapted to different situations automatically. That is, we transform this indicator selection problem into a weights tuning problem. To find the best weight of self-adaptive indicators, machine learning methods and black-box optimization are utilized. The experimental results demonstrated that our self-adaptive indicator can select a better rule set to identify more high-risk users compared to the human-defined indicator.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131438804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1109/COMPSAC54236.2022.00133
Xiaocao Hu, Haibo Wang
Android has recently become one of the leading operating systems for mobile app development. The permission- based mechanism in Android forces app developers to determine permissions required by apps besides implementing the functionality, which increases the burden on developers. App permission recommendation becomes necessary and meaningful to assist developers determine appropriate needed permissions. Existing approaches for app permission recommendation have various limitations, such as suffering from the cold-start problem, needing to learn both of the app and permission embedding matrices. To address these issues, we define a sparse matrix factorization model, in which API categories are utilized as latent factors, app-API calls are applied for app representation, and only one sparse matrix is to be learned for permission representation. We further present an efficient approach by utilizing the Alternating Direction Method of Multipliers to solve the optimization problem. We conduct a comprehensive set of experiments on a real-world dataset, which show that our approach outperforms the state-of-the-art approaches in terms of four well-known metrics.
{"title":"Category-Aware App Permission Recommendation based on Sparse Linear Model","authors":"Xiaocao Hu, Haibo Wang","doi":"10.1109/COMPSAC54236.2022.00133","DOIUrl":"https://doi.org/10.1109/COMPSAC54236.2022.00133","url":null,"abstract":"Android has recently become one of the leading operating systems for mobile app development. The permission- based mechanism in Android forces app developers to determine permissions required by apps besides implementing the functionality, which increases the burden on developers. App permission recommendation becomes necessary and meaningful to assist developers determine appropriate needed permissions. Existing approaches for app permission recommendation have various limitations, such as suffering from the cold-start problem, needing to learn both of the app and permission embedding matrices. To address these issues, we define a sparse matrix factorization model, in which API categories are utilized as latent factors, app-API calls are applied for app representation, and only one sparse matrix is to be learned for permission representation. We further present an efficient approach by utilizing the Alternating Direction Method of Multipliers to solve the optimization problem. We conduct a comprehensive set of experiments on a real-world dataset, which show that our approach outperforms the state-of-the-art approaches in terms of four well-known metrics.","PeriodicalId":330838,"journal":{"name":"2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"51 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114014409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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