2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)最新文献

A Persian speaker-independent dataset to diagnose autism infected children based on speech processing techniques 基于语音处理技术的波斯语独立数据集诊断自闭症感染儿童

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729345

Maryam Alizadeh, S. Tabibian

{"title":"A Persian speaker-independent dataset to diagnose autism infected children based on speech processing techniques","authors":"Maryam Alizadeh, S. Tabibian","doi":"10.1109/ICSPIS54653.2021.9729345","DOIUrl":"https://doi.org/10.1109/ICSPIS54653.2021.9729345","url":null,"abstract":"Autism spectrum disorder is one kind of brain developmental disorders. The easiest way to diagnose persons with autism is done through speech processing techniques. However, limited researches have been done in this field. The reason may be due to the lack of valid and suitable datasets in this field. Therefore, in this paper, while analyzing the existing datasets in this field, the process of designing, collecting and evaluating a Persian speaker-independent dataset to diagnose children with autism (PersionSIChASD dataset) using speech processing methods has been discussed. Data collection has been done under the supervision of an autism specialist. The dataset includes those phonetic units that children with autism have difficulty in saying them, correctly. The results of evaluating the proposed dataset have shown speech recognition accuracies equal to 76% and 12% for phonetic units articulated by typical and autism infected children, respectively. The significant difference between the mentioned recognition rates (about 64%) could be exploited to diagnose autism infected children.","PeriodicalId":286966,"journal":{"name":"2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)","volume":"509 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121803657","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}

引用次数: 0

Model-Free Learning Algorithms for Dynamic Transmission Control in IoT Equipment 物联网设备动态传输控制的无模型学习算法

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729333

Hanieh Malekijou, Vesal Hakami

引用次数: 0

Combination of Feature Selection and Hybrid Classifier as to Network Intrusion Detection System Adopting FA, GWO, and BAT Optimizers 基于FA、GWO和BAT优化器的网络入侵检测系统特征选择与混合分类器的结合

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729365

Mousa Alizadeh, Sadegh E Mousavi, M. Beheshti, A. Ostadi

{"title":"Combination of Feature Selection and Hybrid Classifier as to Network Intrusion Detection System Adopting FA, GWO, and BAT Optimizers","authors":"Mousa Alizadeh, Sadegh E Mousavi, M. Beheshti, A. Ostadi","doi":"10.1109/ICSPIS54653.2021.9729365","DOIUrl":"https://doi.org/10.1109/ICSPIS54653.2021.9729365","url":null,"abstract":"In terms of network topology, one of the extensively utilized technologies is the intrusion detection system (IDS). Despite applying numerous machine learning approaches (supervised and unsupervised) to enhance efficacy, reaching high-grade performance is still a challenging problem for existing intrusion detection algorithms. This study presents a new technique for IDS that focuses on various deep neural networks (DNNs) and their combination for data classification. The proposed model consists of three parts: (1) the feature selection is composed of an intersection of mutual information based on the transductive model (MIT-MIT), Anova F-value, and Genetic Algorithm (GA) methods, (2) the second section is a classifier network using a hybrid CNN-LSTM algorithm, and (3) the hyperparameter optimization module that puts to use Firefly, BAT, and Gray Wolf algorithms. In order to validate and verify the suggested model via accuracy, F1 score, recall, and precision criteria, a benchmark dataset, namely, NSL-KDD, is employed, which compares the proposed method with the highly developed classifiers. The comparison outcomes confirmed the surpassing of the presented strategy over contrast algorithms.","PeriodicalId":286966,"journal":{"name":"2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117112556","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}

引用次数: 5

RetinaMHSA: Improving in single-stage detector with self-attention 视网膜hsa:自我关注单级检测仪的改进

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729362

S. S. Fard, A. Amirkhani, M. Mosavi

引用次数: 1

Perceptually Optimized Loss Function for Image Super-Resolution 图像超分辨率感知优化损失函数

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729334

Amirhossein Arezoomand, Pooryaa Cheraaqee, Azadeh Mansouri

引用次数: 0

Wind Energy Potential Approximation with Various Metaheuristic Optimization Techniques Deployment 基于各种元启发式优化技术的风能势逼近

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729389

Mohammed Wadi, Wisam Elmasry, A. Shobole, Mehmet Rida Tur, R. Bayindir, Hossein Shahinzadeh

{"title":"Wind Energy Potential Approximation with Various Metaheuristic Optimization Techniques Deployment","authors":"Mohammed Wadi, Wisam Elmasry, A. Shobole, Mehmet Rida Tur, R. Bayindir, Hossein Shahinzadeh","doi":"10.1109/ICSPIS54653.2021.9729389","DOIUrl":"https://doi.org/10.1109/ICSPIS54653.2021.9729389","url":null,"abstract":"This paper presents a comprehensive empirical study of five different distribution functions to analysis the wind energy potential, namely, Rayleigh, Gamma, Extreme Value, Logistic, and T Location-Scale. In addition, three metaheuristics optimization methods, Grey Wolf Optimization, Marine Predators Algorithm, and Multi-Verse Optimizer are utilized to determine the optimal parameter values of each distribution. To test the accuracy of the introduced distributions and optimization methods, five error measures are investigated and compared such as mean absolute error, root mean square error, regression coefficient, correlation coefficient, and net fitness. To conduct this analysis, the Catalca site in the Marmara region in Istanbul, Republic of Turkey is selected to be the case study. The experimental results confirm that all introduced distributions based on optimization methods are efficient to model wind speed distribution in the selected site. Rayleigh distribution achieved the best matching while Extreme Value distribution provided the worst matching. Finally, many valuable observations drawn from this study are also discussed. MATLAB 2020b and Excel 365 were used to perform this study.","PeriodicalId":286966,"journal":{"name":"2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114810915","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}

引用次数: 4

Bone Fracture Detection and Localization on MURA Database Using Faster-RCNN 基于Faster-RCNN的MURA数据库骨折检测与定位

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729393

Shaghayegh Shahiri Tabarestani, A. Aghagolzadeh, M. Ezoji

引用次数: 1

AoI-Aware Status Update Control for an Energy Harvesting Source over an Uplink mmWave Channel 在上行毫米波信道上能量收集源的aoi感知状态更新控制

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729335

Marzieh Sheikhi, Vesal Hakami

{"title":"AoI-Aware Status Update Control for an Energy Harvesting Source over an Uplink mmWave Channel","authors":"Marzieh Sheikhi, Vesal Hakami","doi":"10.1109/ICSPIS54653.2021.9729335","DOIUrl":"https://doi.org/10.1109/ICSPIS54653.2021.9729335","url":null,"abstract":"In the new generation networks, the freshness of the data plays a prominent role in real-time systems. The novel metric of the age of information (AoI) measures the elapsed time since the generation of the latest received data. This paper considers a real-time scenario where a source node samples and forwards the measurements to a monitoring center over a millimeter-wave (mmWave) channel. The source node is also equipped with a finite rechargeable battery to harvest energy from the environment. We propose a remote monitoring problem that considers the tradeoff between the minimization of long-term average AoI and the energy usage of the source node. We formulate the problem as an MDP model, and as a model-free reinforcement learning approach, we utilize the Q-learning algorithm to obtain the optimal policy that minimizes the long-term average AoI. Our evaluations investigate the convergence property as well as the impact of changing the problem parameters on the average AoI and average energy consumption. Simulation results show that compared to two other baselines (i.e., random and greedy (myopic) policy), the proposed Q-Learning based algorithm is able to keep the data fresh and consumes less energy by considering the possible future system states.","PeriodicalId":286966,"journal":{"name":"2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128876214","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}

引用次数: 2

Anomaly Detection and Resilience-Oriented Countermeasures against Cyberattacks in Smart Grids 智能电网异常检测与面向弹性的网络攻击对策

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729386

Hossein Shahinzadeh, Arezou Mahmoudi, Jalal Moradi, H. Nafisi, E. Kabalci, Mohamed Benbouzid

{"title":"Anomaly Detection and Resilience-Oriented Countermeasures against Cyberattacks in Smart Grids","authors":"Hossein Shahinzadeh, Arezou Mahmoudi, Jalal Moradi, H. Nafisi, E. Kabalci, Mohamed Benbouzid","doi":"10.1109/ICSPIS54653.2021.9729386","DOIUrl":"https://doi.org/10.1109/ICSPIS54653.2021.9729386","url":null,"abstract":"Security in smart grids has been investigated by many scholars so far. Among the existing security issues, False Data Injection (FDI) attacks in energy, computers, and communication domains are still an ongoing challenge. These attacks have the ability to sabotage the grid through causing misfunctioning of measurements devices as well as changing the state estimation appraisal so that these changes, known as false data, cannot be easily recognized and identified using conventional approaches. In this paper, the degree of network resilience against FDI attacks is analyzed by simulating a randomly generated sample FDI attack, in which the false data vector has different intensity and different quantity. A steady-state AC power flow in accordance with the outage model is employed to simulate and predict the power system response after the incidence of an FDI attack, and the ability of this attack for blackout and shutting down the transmission network has been investigated. In the proposed model, the transmission line outage, load shedding, as well as voltage instability metrics are tested and analyzed on the IEEE 300- bus test network. Given that FDI attacks are considered a serious threat to power systems, the preliminary results imply that the targeted electricity grid is resilient against these attacks in terms of the probability of outage and chain blackouts, but the transient voltage stability can be affected.","PeriodicalId":286966,"journal":{"name":"2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS)","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116371918","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}

引用次数: 9

Fraud Detection System in Online Ride-Hailing Services 网约车服务欺诈检测系统

2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS) Pub Date : 2021-12-29 DOI: 10.1109/ICSPIS54653.2021.9729379

Kosar Bakhshi, B. Bahrak, H. Mahini

引用次数: 0