2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)最新文献

Imam: Word Embedding Model for Islamic Arabic NLP 伊玛目:伊斯兰阿拉伯语NLP的词嵌入模型

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257931

Ali M. Alargrami, Maged M. Eljazzar

{"title":"Imam: Word Embedding Model for Islamic Arabic NLP","authors":"Ali M. Alargrami, Maged M. Eljazzar","doi":"10.1109/NILES50944.2020.9257931","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257931","url":null,"abstract":"This paper can be considered one of the first works to introduce an efficient distributed word representation model for different NLP tasks in the islamic domain. The Word Embedding Model and the algorithm on top of it is implemented in Imam application where user can ask the application to search for any data related to Isalmic domain and get an answer. The data is gathered from different resources (Maliks muwataa, Musnad Ahmad Ibn-hanbal, Sahih Muslim ahadith, Sahih Al-bukhari, Sunan Al-darimi, and more). The amount of records gathered was more than ninety thousand documents (Text Blocks) from 10 different books.After several sequential pipeline processes of Data cleaning, preprocessing and Normalization, Skip-gram technique was used to built the word2vec model and then At last tested with different methods, first by using the K-means clustering and then nonlinear dimensionality reduction technique to represent the data in 2D dimension, secondly by using word similarity to test model ability to understand the Quranic language. The tests clearly show that the model can be used effectively in different NLP Arabic Islamic tasks.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124460773","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

An Artificial Intelligence Based Technique for COVID-19 Diagnosis from Chest X-Ray 基于人工智能的胸部x线诊断新冠肺炎技术

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257930

Saddam Bekhet, M. Hassaballah, Mourad A. Kenk, Mohamed Abdel Hameed

{"title":"An Artificial Intelligence Based Technique for COVID-19 Diagnosis from Chest X-Ray","authors":"Saddam Bekhet, M. Hassaballah, Mourad A. Kenk, Mohamed Abdel Hameed","doi":"10.1109/NILES50944.2020.9257930","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257930","url":null,"abstract":"The COVID-19 pandemic had a catastrophic impact on world health and economic. This is attributed to the unavoidable delay in the diagnosis process, due to limitation of COVID-19 test kits. Thus, it is urgently required to establish more cheap and affordable diagnostic approaches. Chest X-ray is an important initial step towards a successful COVID-19 diagnose, where it is easily to detect any chest abnormalities (e.g., lung inflammation). Furthermore, majority of hospitals have X-ray devices that can be used in early COVID-19 diagnosis. However, the shortage of radiologists is a key factor that limits early COVID-19 diagnosis and negatively affects the treatment process. This paper presents an artificial intelligence based technique for early COVID-19 diagnosis from chest X-ray images using medical knowledge and deep Convolutional Neural Networks (CNNs). To this end, a deep learning model is built carefully and fine-tuned to achieve the maximum performance in COVID-19 detection. Experimental results on recent benchmark datasets demonstrate the superior performance of the proposed technique in identifying COVID-19 with 96% accuracy.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117064085","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: 23

Energy-Efficient Computation Offloading for Indoor Localization Based on Game Theory 基于博弈论的室内定位节能计算卸载

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257948

Marwa Zamzam, T. el-Shabrawy, M. Ashour

{"title":"Energy-Efficient Computation Offloading for Indoor Localization Based on Game Theory","authors":"Marwa Zamzam, T. el-Shabrawy, M. Ashour","doi":"10.1109/NILES50944.2020.9257948","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257948","url":null,"abstract":"The topic of localization within indoor environments has recently received significant attention as localization has become an essential component of many Internet of Things applications such as object tracking and health care management. One of the promising approach to provide accurate localization while minimizing energy consumption is to use computational offloading under mobile edge computing system. Thus, the aim of this paper is to minimize the total energy consumption of multiple users by using computation offloading technique between users, mobile edge computing servers and cloud server. The offloading technique that is proposed in this paper should take in consideration users’ accuracy, latency requirements and the maximum capacity of each server. The paper presents the network model and the computation model of the proposed system. Then, the problem formulation is introduced to minimize the total energy consumption which is the sum of all energy consumed by the users in the local devices and the offloaded servers. In order to provide a distributed implementation that is more suitable for the users within localization environment, the paper formulates the proposed problem as a potential game and the existence of Nash Equilibrium is proved where all users have satisfied offloading decision. The paper obtains the optimal solution to act as a reference for the proposed potential game algorithm. Finally, the paper presents and analyzes the results of the potential game distributed computational offloading algorithm by comparing it to local computing, random offloading and the optimal solution techniques.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127367208","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

Trans-Compiler based Mobile Applications code converter: swift to java 基于转换编译器的移动应用程序代码转换器:swift到java

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257928

A. A. Muhammad, Amira T. Mahmoud, Shaymaa S. Elkalyouby, Rameez B. Hamza, A. Yousef

引用次数: 6

Insilico Codon Bias Correction for Transgenic Biological Protein Sequences for Vaccine Production 用于疫苗生产的转基因生物蛋白序列的Insilico密码子偏差校正

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257881

Mohamed Abuelanin, Mohamed Fares, M. El-Hadidi

{"title":"Insilico Codon Bias Correction for Transgenic Biological Protein Sequences for Vaccine Production","authors":"Mohamed Abuelanin, Mohamed Fares, M. El-Hadidi","doi":"10.1109/NILES50944.2020.9257881","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257881","url":null,"abstract":"Codon optimization is primarily used in enhancing the levels of protein expression in the host species. Each species has its own codon usage bias, which represents the codons abundance frequency in that species. Using the host usage profile contributes to personalize the synthesis of the DNA vaccines that can achieve highly active vectors the host cells. For optimizing protein expression levels in a particular host, the genetic code sequence needs correction of codon frequency bias to match the expression of host codon landscape rather than the donating organism profile. In this work, we have applied two approaches for optimizing codon usage in protein-coding sequences. The first approach adopts a substitution-based method to replace less frequent codons with differentially higher frequency codons at the specific codon usage bias tables. The second approach finds and replaces the maximal exact protein matches between the unoptimized sequence and the host proteome. We evaluated our work by optimizing the Avian Influenza H1N1 virus’s HA gene to maximize the protein expression before synthesizing the DNA vaccine. Our method produced optimized sequences with higher GC content by 17%, which is similar to eukaryotic sequence profiles than the viral usage profiles, allowing for better expression in avian host cells.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115250428","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

Enhancement of Integrated Navigation System for high-speed flying vehicles' Navigation Applications 高速飞行器导航应用中集成导航系统的增强

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257982

Ahmed W. Ebrahim, I. Arafa, H. Hendy, Y. Elhalwagy

引用次数: 0

Forecasting of COVID-19 in Egypt and Oman using Modified SEIR and Logistic Growth Models 基于改进SEIR和Logistic增长模型的埃及和阿曼COVID-19预测

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257959

Touka M. A. Mahmoud, Mohamed S. A. Abu-Tafesh, Norhan Mohsen ElOcla, A. Mohamed

引用次数: 4

Comparative Study of Hardware Accelerated Convolution Neural Network on PYNQ Board PYNQ板上硬件加速卷积神经网络的比较研究

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257899

Alaa M. Salman, Ahmed S. Tulan, Rana Y. Mohamed, Michael H. Zakhari, H. Mostafa

{"title":"Comparative Study of Hardware Accelerated Convolution Neural Network on PYNQ Board","authors":"Alaa M. Salman, Ahmed S. Tulan, Rana Y. Mohamed, Michael H. Zakhari, H. Mostafa","doi":"10.1109/NILES50944.2020.9257899","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257899","url":null,"abstract":"In recent years convolutional neural networks (CNNs) have been remarkably used in many applications, and they are the heart of many intelligent systems. The advancements in both new electronic design automation (EDA) tools and in new hardware development boards such as Python Productivity for Zynq (PYNQ) have significantly decreased the development time of CNNs. However, the short time-to-market is at the cost of implementation area, performance and power consumption. Over the last period, CNNs’ energy consumption needs have skyrocketed dramatically. Thus, In this work, the authors conduct a comprehensive study on the power consumption of hardware accelerated CNN whether implemented using new EDAs High Level Synthesis (HLS) or the basic design abstraction of Register Transfer Level (RTL). Both methods are implemented on modern development boards from Xilinx (as PYNQ). Modern EDAs flow such as HLS does not represent the best environment for a good power consumption. The power consumption of the HLS implementation is six times more power than the RTL one. It is concluded that the new EDAs method have a deficiency to deliver highly efficient CNNs but it has the ability to deliver sufficient results within a very short period of time.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130643461","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

NILES 2020 Index NILES 2020指数

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/niles50944.2020.9257943

引用次数: 0

Low power and area SHA-256 hardware accelerator on Virtex-7 FPGA 基于Virtex-7 FPGA的低功耗和面积SHA-256硬件加速器

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257922

Ali H. Gad, Seif Eldeen E. Abdalazeem, Omar A. Abdelmegid, H. Mostafa

{"title":"Low power and area SHA-256 hardware accelerator on Virtex-7 FPGA","authors":"Ali H. Gad, Seif Eldeen E. Abdalazeem, Omar A. Abdelmegid, H. Mostafa","doi":"10.1109/NILES50944.2020.9257922","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257922","url":null,"abstract":"Lately, there have been many technological developments in communication especially in online transactions, so the demand for highly secure systems and cryptographic algorithms has increased. Cryptographic hash functions are used to protect and authenticate information and transactions. SHA-256 (Secure Hash Algorithm-256) is a one-way hash function characterized by being highly secure and fast while having a high collision resistance. This paper presents a new hardware architecture of SHA-256 with low power consumption and area based on a sequential computation of the message scheduler and the working variables of SHA-256. The hardware was described in HDL and implemented on Virtex-7 FPGA which offers high efficiency and speed. Different optimization techniques were used to further reduce the power and area such as gated clock conversion, arithmetic resource sharing, and structural modeling of small building blocks. The proposed design ran with a maximum frequency of 83.33 MHz. The implementation reports indicated a dynamic power consumption of 13 mW and area utilization of 275 slices while maintaining a good throughput of 0.637 Gbits/s and a relatively high efficiency of 2.32 Mbits/s per slice. Such design with low power and area can be used to hash messages on a portable device opening a whole new area for different applications and opportunities.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114532412","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