2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第4页

Predicting Hospital Length of Stay of Neonates Admitted to the NICU Using Data Mining Techniques 利用数据挖掘技术预测新生儿入住NICU的住院时间

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303666

Ardeshir Mansouri, M. Noei, M. S. Abadeh

{"title":"Predicting Hospital Length of Stay of Neonates Admitted to the NICU Using Data Mining Techniques","authors":"Ardeshir Mansouri, M. Noei, M. S. Abadeh","doi":"10.1109/ICCKE50421.2020.9303666","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303666","url":null,"abstract":"Hospitals face many pressures, including limited budgets and resources. The Intensive Care Unit (ICU) mostly includes patients who are in critical condition and require costly sources of treatment and has attracted much attention from the medical community. The ability to predict the length of stay for newborns in the Neonatal Intensive Care Unit (NICU) can assist the health care system in allocating needed resources and also has clinical value as an indicator of newborn’s health status. This research utilized the Medical Information Mart for Intensive Care III database (MIMIC III), and the performance of different machine learning models on NICU patients was discussed. Data was filtered, extracted, and preprocessed from the database, and the preprocessing step included a vast amount of feature engineering. The performance of various regression models for predicting hospital length of stay for NICU patients was discussed and compared. Finally, high performing results with a high R2 score of 0.78 by exploiting only patients’ diagnoses data and demographics obtained at the first 24 hours of the admission was achieved.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129503799","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

Speed Control of Brushless DC motor using Fractional Order Fuzzy PI Controller Optimized via WOA 基于WOA优化分数阶模糊PI控制器的无刷直流电动机速度控制

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303634

Mohammad Ali Labbaf Khaniki, Sadegh Esfandiari, M. Manthouri

引用次数: 7

Show, Attend to Everything, and Tell: Image Captioning with More Thorough Image Understanding 展示，关注一切，并告诉:图像标题与更彻底的图像理解

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303609

Zahra Karimpour, Amirm. Sarfi, Nader Asadi, Fahimeh Ghasemian

{"title":"Show, Attend to Everything, and Tell: Image Captioning with More Thorough Image Understanding","authors":"Zahra Karimpour, Amirm. Sarfi, Nader Asadi, Fahimeh Ghasemian","doi":"10.1109/ICCKE50421.2020.9303609","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303609","url":null,"abstract":"Image captioning is one of the most important cross-modal tasks in machine learning. Attention-based encoder-decoder frameworks have been utilized for this task, abundantly. For visual understanding of an image, via the encoder, most of these networks use the last convolutional layer of a network designed for some computer vision tasks. There are several downsides to that. First, these models are specialized to detect certain objects from the image. Thus, when we get deeper into the network, the network focuses on these objects, becoming almost blind to the rest of the image. These blindspots of the encoder sometimes are where the next word in the caption lies. Moreover, many words in the caption are not included in the target classes of these tasks, such as \"snow\".having this observation in mind, in order to reduce the blind spots of the last convolutional layer of the encoder, we propose a novel method to reuse other convolutional layers of the encoder. Doing so provides us diverse features of the image while not neglecting almost any part of the image and hence, we \"attend to everything\" in the image. Using the flickr30k [1] dataset, we evaluate our method and demonstrate comparable results with the state-of-the-art, even with simple attention mechanisms.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122145126","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: 1

A Warning System Design for Camel-Vehicle Collisions Mitigation 骆驼车辆碰撞预警系统设计

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303617

Yaser Dorrazehi, M. Mehrjoo, M. Kazeminia

{"title":"A Warning System Design for Camel-Vehicle Collisions Mitigation","authors":"Yaser Dorrazehi, M. Mehrjoo, M. Kazeminia","doi":"10.1109/ICCKE50421.2020.9303617","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303617","url":null,"abstract":"In this paper, we propose a warning system to reduce camel-vehicle collision (CVC) in accident-prone roads of Sistan and Baluchestan province of Iran. The system consists of recording cameras, cellular network handsets, and a camel’s movement simulator unit. The position of camels, detected by infrared cameras installed on some passing vehicles through the road, is transmitted to a central processing unit via cellular network. The processing unit simulates the random process of camel movement, finds the probability of the camel presence in the neighbourhood over time, and broadcasts it to the passing vehicles periodically. To this end, we conduct a field measurement to collect traces of the camels’ movement. Then, we present a model of camel’s movement using hidden Markov model (HMM). To evaluate the warning system, we simulate the collisions occurrences in Iranshahr-Zehkalot road. Simulation results show that if all the passing vehicles are equipped with night vision cameras and the drivers use their mobile phones to receive warning messages and adapt their speed properly, the accidents are reduced by 92%.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122418418","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: 3

A Concurrent BIST Architecture for Combinational Logic Circuits 一种用于组合逻辑电路的并行BIST结构

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303669

Ahmad Menbari, H. Jahanirad

引用次数: 3

DroidTKM: Detection of Trojan Families using the KNN Classifier Based on Manhattan Distance Metric DroidTKM:基于曼哈顿距离度量的KNN分类器检测木马家族

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303720

Diyana Tehrany Dehkordy, A. Rasoolzadegan

{"title":"DroidTKM: Detection of Trojan Families using the KNN Classifier Based on Manhattan Distance Metric","authors":"Diyana Tehrany Dehkordy, A. Rasoolzadegan","doi":"10.1109/ICCKE50421.2020.9303720","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303720","url":null,"abstract":"Currently, the speed of Android malware publications has increased dramatically. The rapid rise of malware has made malware detection and family classification to become an important challenge; because attackers can publish more malware with minor changes in existing android applications. These minor changes in the application lead to the creation of multiple families of malware. So far, many methods have been proposed to detect malware applications and classify them. However, few methods focus on detecting malware families. In this paper, a detection method is proposed to identify Trojan families in order to improve accuracy and reduce error rates. To achieve these purposes, static and dynamic analysis are used to extract the required features of the applications. The k- means method has also been used to preprocess the obtained dataset. Then, a detection model is developed to identify families using the classifiers of K-Nearest Neighbor (KNN), Support Vector Machine, and Iterative Dichotomiser 3. The accuracy of KNN is also measured according to different distance metrics which has not yet been studied among malware detection methods. The proposed method is able to detect a variety of Trojans using KNN based on Manhattan metric with an accuracy of 97.83% and False Positive Rate (FPR) of 0.06%. The comparison between the performance of the proposed method and the other methods shows a 4.83% and 0.94% improvement in terms of accuracy and FPR, respectively.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129190048","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: 7

New generation of metaheuristics by inspiration from ancient 新一代的元启发式灵感来自古代

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303653

Sasan Harifi, Madjid Khalilian, J. Mohammadzadeh, S. Ebrahimnejad

{"title":"New generation of metaheuristics by inspiration from ancient","authors":"Sasan Harifi, Madjid Khalilian, J. Mohammadzadeh, S. Ebrahimnejad","doi":"10.1109/ICCKE50421.2020.9303653","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303653","url":null,"abstract":"Recently, the development of new metaheuristic algorithms has become very expansive. This expansion is especially evident in the category of nature-inspired algorithms. Nature is indeed the source of the solution in many problems, but the developed algorithms in this category used almost the same procedure for optimization. Before the development of nature-inspired algorithms, evolutionary-based algorithms were introduced. It seems that there is a need for some kind of change in this area. This change can be found in the new generation of algorithm development inspired by the ancient era. Ancient inspiration brings together all the positive aspects of nature and evolution. This paper discusses some applications of the ancient-inspired Giza Pyramids Construction (GPC) algorithm compared to the nature-inspired Emperor Penguins Colony (EPC) algorithm. Applications discussed in this paper include improving k-means clustering and optimizing the neuro-fuzzy system. Results from experiments show that the ancient-inspired GPC algorithm performed superior and more efficiently than algorithms inspired by other sources of inspiration.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131062061","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: 3

Using OWA Approach to Solve Cold-Start Problem of Recommender Systems 用OWA方法解决推荐系统冷启动问题

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303692

Mohammad Soleymannejad, Alireza Basiri

引用次数: 1

A Novel Compact Rule Extractor Based on Genetic-Fuzzy Algorithm 一种新的基于遗传模糊算法的紧凑规则提取器

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303613

F. Ahouz, Amin Golabpour

{"title":"A Novel Compact Rule Extractor Based on Genetic-Fuzzy Algorithm","authors":"F. Ahouz, Amin Golabpour","doi":"10.1109/ICCKE50421.2020.9303613","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303613","url":null,"abstract":"Extracting effective rules in medical data with two indicators of accuracy and high interpretability is essential in increasing the accuracy and speed of diagnosis by specialists. As a result, the production of decision support systems that are able to detect data-driven rules play a vital role in the early detection of disease, even in areas where there is no access to a specialist. In this paper, a novel automatic rule extractor is presented using a hybrid model consisting of fuzzy logic and evolutionary algorithm. Fuzzy systems are suitable for making diagnostic models due to the high interpretability of their rules. The genetic algorithm is used to automatically generate these rules. To evaluate the proposed method, Pima Diabetes dataset including 768 records and 9 variables was used. The accuracy of the proposed model on the PIMA dataset was 77.12%. This is achieved by 7 fuzzy rules with an average length of 2.1, using three linguistic variables that represent low, normal and high values of each of the independent variables. All membership functions are the same width. According to the three criteria of low number of rules, short rule length and symmetric membership functions with the same width, the proposed method is quite suitable for extraction of compact rule base with high accuracy and interpretability in medical data.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129398250","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: 1

A new memoryless online routing algorithm for Delaunay triangulations Delaunay三角剖分的一种新的无内存在线路由算法

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303695

Ashkan Rezazadeh, Mostafa Nouri-Baygi

{"title":"A new memoryless online routing algorithm for Delaunay triangulations","authors":"Ashkan Rezazadeh, Mostafa Nouri-Baygi","doi":"10.1109/ICCKE50421.2020.9303695","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303695","url":null,"abstract":"We consider 1-local online routing on a special class of geometric graphs called Delaunay triangulations (DTs). A geometric graph G = (V, E) of a point set consists of a set of points in the plane and edges between them, where each edge weighs as the Euclidean distance between it’s end-points. DTs are one of the useful classes of these graphs because of some good properties which can help during the navigation process, therefore over the years DTs have been widely proposed as network topologies for several times.In this paper, we present a new memoryless online routing (MOR) algorithm for DTs which is simple, elegant, and easy to implement, while having an acceptable performance.The set of MOR algorithms are suitable for cases where we want to find a path using only local information, our proposed algorithm is memoryless or 1-local, in k-local routing, we find a path between a source vertex s to a destination vertex t while our knowledge at each step is limited to the locations of s and t, the location of current vertex and it’s k-neighborhood vertices.We also evaluate and compare the perforamnce of our prpopsed algorithm with existing MOR algorithms. Our experimental results implied that our proposed algorithm has an acceptable performance in both Euclidean and link metrics and it outperforms all of the existing MOR algorithms in Euclidean metric, and some of them in the link metric as well. Finally, we pose two open problems to solve in the future.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115912657","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