Pub Date : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538425
Heba A. Fasihuddin, S. Alsolami, Seham Alzahrani, Rawan Alasiri, Afnan Sahloli
This paper presents a smart tutoring system for Arabic Sign Language (ArSL). Sign language is one of the main approaches of communication for people with hearing impairment. Many people are willing to learn sign language and support this segment of the society; however, learning this language requires some effort and assistant. Tools that are used to support sign language learners and specifically ArSL are limited and insufficient. Hence, the development of a tool that is capable of training and assessing ArSL learners becomes a necessity. We proposed a smart tutoring for ArSL based on using the leap motion’s hand tracking technology. The aim of this system is assisting non-disabled learners who want to learn the sign language, such as undergraduates specializing in hearing disabilities, parents of kids with hearing impairment or any interested subject. The system allows learners to practice ArSL in different levels and self-assess themselves. As it utilizes the recent technology of leap motion controller, it can detect and track hand and fingers movements and consequently assess the position and movement accuracy. Machine learning techniques, specifically the K- Nearest Neighbor algorithm was applied for classification and sign recognition. Preliminary prototype was developed and tested in terms of users’ acceptance. The outcomes show satisfactory and promising results. It is expected that the proposed system will contribute in enriching the learning process of ArSL and consequently support an important segment of our community.
{"title":"Smart Tutoring System for Arabic Sign Language Using Leap Motion Controller","authors":"Heba A. Fasihuddin, S. Alsolami, Seham Alzahrani, Rawan Alasiri, Afnan Sahloli","doi":"10.1109/ICSCEE.2018.8538425","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538425","url":null,"abstract":"This paper presents a smart tutoring system for Arabic Sign Language (ArSL). Sign language is one of the main approaches of communication for people with hearing impairment. Many people are willing to learn sign language and support this segment of the society; however, learning this language requires some effort and assistant. Tools that are used to support sign language learners and specifically ArSL are limited and insufficient. Hence, the development of a tool that is capable of training and assessing ArSL learners becomes a necessity. We proposed a smart tutoring for ArSL based on using the leap motion’s hand tracking technology. The aim of this system is assisting non-disabled learners who want to learn the sign language, such as undergraduates specializing in hearing disabilities, parents of kids with hearing impairment or any interested subject. The system allows learners to practice ArSL in different levels and self-assess themselves. As it utilizes the recent technology of leap motion controller, it can detect and track hand and fingers movements and consequently assess the position and movement accuracy. Machine learning techniques, specifically the K- Nearest Neighbor algorithm was applied for classification and sign recognition. Preliminary prototype was developed and tested in terms of users’ acceptance. The outcomes show satisfactory and promising results. It is expected that the proposed system will contribute in enriching the learning process of ArSL and consequently support an important segment of our community.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127308329","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538427
Dwi Astharini, Nurul Ihsan Hariz Pratama, S. Rahardjo, F. Triputra, A. Syahriar, Octarina Nur Samijayani
In this paper, design and analysis one of the proposed Optical Orthogonal Frequency Division Multiplexing (OFDM) for Visible Light Communication has been conducted. The chosen design is Generalized LED Index Modulation Orthogonal Frequency Division Multiplexing (GLIM-OFDM), with its proposed scheme that avoid Hermitian symmetry and DC bias. Thus, by utilizing the properties of complex data signal and the bipolar index with spatial modulation Multi Input Multi Output (MIMO) configuration. System generator is used to design the GLIM-OFDM. The design is targeted into Arty Board with Xilinx Artix-7 FPGA. Analysis and comparison are covering in the arithmetic option of unscaled and scaled for its effect on precision, performance, and resource usage. The designed system is proven to work according to theory of operation scheme. To verify that, the reversible design has been designed to ensure the processed data in the transmitter side with the origin data signal. The unscaled option performs slightly faster than the scaled option. Both arithmetic option has same precision of data representation. The GLIM-OFDM design used less resource in unscaled option compared with the design in scaled option.
{"title":"Design and Analysis of Generalized LED Index Modulation OFDM on FPGA","authors":"Dwi Astharini, Nurul Ihsan Hariz Pratama, S. Rahardjo, F. Triputra, A. Syahriar, Octarina Nur Samijayani","doi":"10.1109/ICSCEE.2018.8538427","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538427","url":null,"abstract":"In this paper, design and analysis one of the proposed Optical Orthogonal Frequency Division Multiplexing (OFDM) for Visible Light Communication has been conducted. The chosen design is Generalized LED Index Modulation Orthogonal Frequency Division Multiplexing (GLIM-OFDM), with its proposed scheme that avoid Hermitian symmetry and DC bias. Thus, by utilizing the properties of complex data signal and the bipolar index with spatial modulation Multi Input Multi Output (MIMO) configuration. System generator is used to design the GLIM-OFDM. The design is targeted into Arty Board with Xilinx Artix-7 FPGA. Analysis and comparison are covering in the arithmetic option of unscaled and scaled for its effect on precision, performance, and resource usage. The designed system is proven to work according to theory of operation scheme. To verify that, the reversible design has been designed to ensure the processed data in the transmitter side with the origin data signal. The unscaled option performs slightly faster than the scaled option. Both arithmetic option has same precision of data representation. The GLIM-OFDM design used less resource in unscaled option compared with the design in scaled option.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126554046","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538405
T. Teoh, G. Chiew, Y. Jaddoo, H. Michael, A. Karunakaran, Y. Goh
Recurrent Neural Networks (RNN) are a special class of deep learning algorithms using neurons or nodes, and have received much attention in the subject of data science in the recent years. In RNN, the input nodes take into consideration not only the current inputs, but the previously perceived outputs as well – hence the term recursive. In today’s context, smartphones are very much a part of almost every individual’s daily lives. The demand, development and usage of Android devices is massive. As Android devices dominate the current market share, the question of security naturally arises in our complex world. Consequently, the amount of malware data available for research is voluminous as well. This publication demonstrates the power and efficiency of RNN applied onto Android malware data. We study a procured dataset, with over 4000 entries labeled as malicious or benign. From our experiment and data analytics, we present a prediction accuracy of 0.964 using RNN.
{"title":"Applying RNN and J48 Deep Learning in Android Cyber Security Space for Threat Analysis","authors":"T. Teoh, G. Chiew, Y. Jaddoo, H. Michael, A. Karunakaran, Y. Goh","doi":"10.1109/ICSCEE.2018.8538405","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538405","url":null,"abstract":"Recurrent Neural Networks (RNN) are a special class of deep learning algorithms using neurons or nodes, and have received much attention in the subject of data science in the recent years. In RNN, the input nodes take into consideration not only the current inputs, but the previously perceived outputs as well – hence the term recursive. In today’s context, smartphones are very much a part of almost every individual’s daily lives. The demand, development and usage of Android devices is massive. As Android devices dominate the current market share, the question of security naturally arises in our complex world. Consequently, the amount of malware data available for research is voluminous as well. This publication demonstrates the power and efficiency of RNN applied onto Android malware data. We study a procured dataset, with over 4000 entries labeled as malicious or benign. From our experiment and data analytics, we present a prediction accuracy of 0.964 using RNN.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124193052","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538408
Yuan Jia
–-Tonal patterns in spoken language carry rich semantic and sentiment information. However, they may differ significantly from dialect to dialect, even within the same language. Therefore, understanding dialect-specific tonal patterns plays an important role for developing intelligent and customized speech understanding and generation technologies. The present study adopts phonetic experiments to systematically investigate the citation tone and tone sandhi patterns of Liaocheng and Tai’an dialects that belong to the Shangdong dialectal region in China. It aims to provide empirical data for the theoretical analysis and explore the diversities of tonal phenomenon within Shandong (Hereinafter, as SD) dialect. Results demonstrate that both of these two dialects have four citation tones, i.e., Tone 1(14), Tone2 (51), Tone3 (55), and Tone4 (35) in Liaocheng dialect; Tone 1(14), Tone2 (51), Tone3 (55), and Tone4 (213) in Tai’an dialect. Due to the difference of Tone4 between these two dialects, Tai’an dialect exhibits more kinds of tone sandhi patterns than Liaocheng dialect. This result lies in the devious tone4 in Tai’an dialect, which triggers more tonal variations in disyllabic sequences.
{"title":"An Empirical Study On Tonal Patterns Of Shandong Dialects","authors":"Yuan Jia","doi":"10.1109/ICSCEE.2018.8538408","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538408","url":null,"abstract":"–-Tonal patterns in spoken language carry rich semantic and sentiment information. However, they may differ significantly from dialect to dialect, even within the same language. Therefore, understanding dialect-specific tonal patterns plays an important role for developing intelligent and customized speech understanding and generation technologies. The present study adopts phonetic experiments to systematically investigate the citation tone and tone sandhi patterns of Liaocheng and Tai’an dialects that belong to the Shangdong dialectal region in China. It aims to provide empirical data for the theoretical analysis and explore the diversities of tonal phenomenon within Shandong (Hereinafter, as SD) dialect. Results demonstrate that both of these two dialects have four citation tones, i.e., Tone 1(14), Tone2 (51), Tone3 (55), and Tone4 (35) in Liaocheng dialect; Tone 1(14), Tone2 (51), Tone3 (55), and Tone4 (213) in Tai’an dialect. Due to the difference of Tone4 between these two dialects, Tai’an dialect exhibits more kinds of tone sandhi patterns than Liaocheng dialect. This result lies in the devious tone4 in Tai’an dialect, which triggers more tonal variations in disyllabic sequences.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115610909","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538375
Shadi M. S. Hilles
The aim of the research is to propose a new approach to image coding using SOFM and spatial frequency band-pass filter to investigate the Artificial Neural Network. The approach is based on SOFM which is similar to vector quantization (VQ) and it is adopted the technique to improve the image compression effectively. In the approach has been using the band-pass filter for image compression by SOFM based on vector quantization by components as the original image and the spatial frequency image component, which is derived from the adaptive to the contours of the 2D analysis and synthesis. The calculation of the computational cost is compression based on SOFM. The new approach of image coding using a band-pass filter, where is used as a first stage of proposed method of image encoding and as well as the image decoding has been presented with De-quantization with entropy coding based on arithmetic coder and high pass filter, the evaluation with jpeg format compression shows, that using 16x16 image block of pre-processing in SOFM has given the best compression ratio with small SNR. On the given experiment shows the different pixels presented by Lena.bmp, girl256.bmp and compared with a compression ratio of the Iena.jpeg file.
{"title":"Spatial Frequency Filtering Using Sofm For Image Compression","authors":"Shadi M. S. Hilles","doi":"10.1109/ICSCEE.2018.8538375","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538375","url":null,"abstract":"The aim of the research is to propose a new approach to image coding using SOFM and spatial frequency band-pass filter to investigate the Artificial Neural Network. The approach is based on SOFM which is similar to vector quantization (VQ) and it is adopted the technique to improve the image compression effectively. In the approach has been using the band-pass filter for image compression by SOFM based on vector quantization by components as the original image and the spatial frequency image component, which is derived from the adaptive to the contours of the 2D analysis and synthesis. The calculation of the computational cost is compression based on SOFM. The new approach of image coding using a band-pass filter, where is used as a first stage of proposed method of image encoding and as well as the image decoding has been presented with De-quantization with entropy coding based on arithmetic coder and high pass filter, the evaluation with jpeg format compression shows, that using 16x16 image block of pre-processing in SOFM has given the best compression ratio with small SNR. On the given experiment shows the different pixels presented by Lena.bmp, girl256.bmp and compared with a compression ratio of the Iena.jpeg file.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115307598","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538387
A. Al-Ahmad, Hasan Kahtan
Cloud computing is an on-demand network selfservice, dynamic power and virtual resources. It provide elasticity, restrictions and interactivity which introduces many new features and issues. This paper will review cloud computing common features and issues mainly in term of security. Security has been selected to be the focus of his paper due to high interest in security form both academics and inducts. This paper has categorized cloud computing feature into three categories i.e. technology, economy, and on-Technology. On the other hand this paper has categorized the cloud computing security issues into five categories i.e. infrastructure, data, access, compliance, and provider. This paper provides researchers and industry an insight about the cloud features and issues that may help them in directing their research and implementation of technologies and provide categorization for loud computing features and issues, which can be expanded while the cloud computing technology advances.
{"title":"Cloud Computing Review: Features And Issues","authors":"A. Al-Ahmad, Hasan Kahtan","doi":"10.1109/ICSCEE.2018.8538387","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538387","url":null,"abstract":"Cloud computing is an on-demand network selfservice, dynamic power and virtual resources. It provide elasticity, restrictions and interactivity which introduces many new features and issues. This paper will review cloud computing common features and issues mainly in term of security. Security has been selected to be the focus of his paper due to high interest in security form both academics and inducts. This paper has categorized cloud computing feature into three categories i.e. technology, economy, and on-Technology. On the other hand this paper has categorized the cloud computing security issues into five categories i.e. infrastructure, data, access, compliance, and provider. This paper provides researchers and industry an insight about the cloud features and issues that may help them in directing their research and implementation of technologies and provide categorization for loud computing features and issues, which can be expanded while the cloud computing technology advances.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129654313","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538423
Rishi Gupta, Sandeep Kumar, Pradeep Yadav, Sumit K. Shrivastava
There has been a developing enthusiasm for programmed human statistic estimation i.e., Age, sexual orientation scare, marks, tattoos and race from unconstrained facial pictures because of an assortment of potential applications in law requirement, security control, and human-PC cooperation. Bounteous writing has explored the issue of computerized age, sexual orientation, and race acknowledgement from unconstrained facial pictures. Nonetheless, in spite of the concurrence of this component, a large portion of the investigations have tended to them independently, next to no consideration has been given to their connections. Programmed statistic estimation remains a testing issue since people having a place with a similar statistic gathering can be tremendously unique in their facial appearances because of natural and extraneous elements. This paper shows a non-exclusive system for the programmed statistic (age. sexual orientation and race) estimation. The proposed approach comprises of the accompanying three principal stages. Preprocessing, Highlight Extraction and Prediction given a face picture. To start with it preprocesses the facial picture next concentrate statistic useful highlights and afterwards, it gauges age, sexual orientation, and race. Tests are directed on two open databases (MORPH II and LFW)[I] MORPH (Craniofacial Longitudinal Morphological Face Database) [1] is one amongst the most important in public accessible longitudinal face databases, The tagged Faces within the Wild (LFW 4) [10] may be an information of faces that contains 13000 pictures of 1680 celebrities tagged with gender, demonstrate that the proposed approach has better execution analyzed than the cutting edge. The proposed method is evaluated based on evaluation measurement precision, recall, accuracy, and MAE. The proposed work gives stable and good results.
{"title":"Identification of Age, Gender, & Race SMT (Scare, Marks, Tattoos) from Unconstrained Facial Images Using Statistical Techniques","authors":"Rishi Gupta, Sandeep Kumar, Pradeep Yadav, Sumit K. Shrivastava","doi":"10.1109/ICSCEE.2018.8538423","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538423","url":null,"abstract":"There has been a developing enthusiasm for programmed human statistic estimation i.e., Age, sexual orientation scare, marks, tattoos and race from unconstrained facial pictures because of an assortment of potential applications in law requirement, security control, and human-PC cooperation. Bounteous writing has explored the issue of computerized age, sexual orientation, and race acknowledgement from unconstrained facial pictures. Nonetheless, in spite of the concurrence of this component, a large portion of the investigations have tended to them independently, next to no consideration has been given to their connections. Programmed statistic estimation remains a testing issue since people having a place with a similar statistic gathering can be tremendously unique in their facial appearances because of natural and extraneous elements. This paper shows a non-exclusive system for the programmed statistic (age. sexual orientation and race) estimation. The proposed approach comprises of the accompanying three principal stages. Preprocessing, Highlight Extraction and Prediction given a face picture. To start with it preprocesses the facial picture next concentrate statistic useful highlights and afterwards, it gauges age, sexual orientation, and race. Tests are directed on two open databases (MORPH II and LFW)[I] MORPH (Craniofacial Longitudinal Morphological Face Database) [1] is one amongst the most important in public accessible longitudinal face databases, The tagged Faces within the Wild (LFW 4) [10] may be an information of faces that contains 13000 pictures of 1680 celebrities tagged with gender, demonstrate that the proposed approach has better execution analyzed than the cutting edge. The proposed method is evaluated based on evaluation measurement precision, recall, accuracy, and MAE. The proposed work gives stable and good results.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130195729","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538380
Nouf S. Aldahwan, M. Saleh
The adoption of cloud computing technology in higher education institutions and universities to fulfill their evolving computing needs is an emerging research field. Saudi Arabia is the largest economy in the Gulf region, which makes KSA a potential market for cloud computing technologies. In addition, KSA’s higher institutions differ from other institutions around the world as they have uniquely separated campuses of males and females. Cloud computing has its own advantages since it can often decrease infrastructure and maintenance costs, improve operational efficiency by allowing various computing devices to complete tasks, and increase the user’s ability to access resources, applications, and data anytime, anywhere. However, there is a lack of tools to help the decision makers at higher education institutions analyze and evaluate the best cost-effective manner to adopt cloud services. Thus, there is a need for a cost-benefit computing tool that is based on a comprehensive multilayer framework to evaluate the costs different cloud service providers such as Amazon, Google, and Microsoft. In this study, an attempt has been made to develop the computing tool and its accompanying framework for cost-benefit analysis to study the suitability of different cloud computing deployment models for the higher education environment. The proposed tool will support decision makers at institutions to assess the various tangible benefits of adopting cloud services versus inhouse services, while taking into consideration the various intangible benefits. The developed tool has been evaluated by experts through interviews. The results showed that the framework can analyze the costs and benefits through comparison between different cloud models, which saves time and effort for decision makers to find the optimal solutions.
{"title":"Developing a Framework for Cost-Benefit Analysis of Cloud Computing Adoption by Higher Education Institutions in Saudi Arabia","authors":"Nouf S. Aldahwan, M. Saleh","doi":"10.1109/ICSCEE.2018.8538380","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538380","url":null,"abstract":"The adoption of cloud computing technology in higher education institutions and universities to fulfill their evolving computing needs is an emerging research field. Saudi Arabia is the largest economy in the Gulf region, which makes KSA a potential market for cloud computing technologies. In addition, KSA’s higher institutions differ from other institutions around the world as they have uniquely separated campuses of males and females. Cloud computing has its own advantages since it can often decrease infrastructure and maintenance costs, improve operational efficiency by allowing various computing devices to complete tasks, and increase the user’s ability to access resources, applications, and data anytime, anywhere. However, there is a lack of tools to help the decision makers at higher education institutions analyze and evaluate the best cost-effective manner to adopt cloud services. Thus, there is a need for a cost-benefit computing tool that is based on a comprehensive multilayer framework to evaluate the costs different cloud service providers such as Amazon, Google, and Microsoft. In this study, an attempt has been made to develop the computing tool and its accompanying framework for cost-benefit analysis to study the suitability of different cloud computing deployment models for the higher education environment. The proposed tool will support decision makers at institutions to assess the various tangible benefits of adopting cloud services versus inhouse services, while taking into consideration the various intangible benefits. The developed tool has been evaluated by experts through interviews. The results showed that the framework can analyze the costs and benefits through comparison between different cloud models, which saves time and effort for decision makers to find the optimal solutions.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128741661","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538386
S. Rahmatia, Ali Akbar Tanjung, Octarina Nur Samijayani, W. N. Tanjung
Long Term Evolution (LTE) is newest technology for mobile telecommunication, it has some advantages that are high data rates, low Iatency and using all Internet Protocols (IP) network architecture. The implementation of LTE requires high cost and takes a long time therefore we need network planning to reduce the risks, some calculations, simulations and optimization is done in network planning. We use software named Atoll as tool for network planning and use Taguchi’s Method (TM) as optimization technique. The objective of this paper is to obtain the optimal parameters value of azimuth, mechanical downtilt, antenna gain and antenna height. The result is the responses that determine the most influential factors due to result depending on their delta value. From this paper, the most influential factor based on SN ratio is antenna height which have delta value 9.47. Then we implement the optimized LTE radio transmitter parameters into LTE network design. The result gave more 12.2% coverage area by signal level, increase average signal received power by 0.69 dBm and increase the coverage area by throughput downlink by 1.5%.
{"title":"Network Planning optimization of Long Term Evolution Radio Transmitter Using Taguchi’s Method","authors":"S. Rahmatia, Ali Akbar Tanjung, Octarina Nur Samijayani, W. N. Tanjung","doi":"10.1109/ICSCEE.2018.8538386","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538386","url":null,"abstract":"Long Term Evolution (LTE) is newest technology for mobile telecommunication, it has some advantages that are high data rates, low Iatency and using all Internet Protocols (IP) network architecture. The implementation of LTE requires high cost and takes a long time therefore we need network planning to reduce the risks, some calculations, simulations and optimization is done in network planning. We use software named Atoll as tool for network planning and use Taguchi’s Method (TM) as optimization technique. The objective of this paper is to obtain the optimal parameters value of azimuth, mechanical downtilt, antenna gain and antenna height. The result is the responses that determine the most influential factors due to result depending on their delta value. From this paper, the most influential factor based on SN ratio is antenna height which have delta value 9.47. Then we implement the optimized LTE radio transmitter parameters into LTE network design. The result gave more 12.2% coverage area by signal level, increase average signal received power by 0.69 dBm and increase the coverage area by throughput downlink by 1.5%.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126211408","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 : 2018-07-01DOI: 10.1109/ICSCEE.2018.8538368
Naresh Pal, Aravind Kilaru, Y. Savaria, A. Lakhssassi
The basic symptom of a human body for any sort of diseases or problems is pain. Pain can be termed as a message from the injured or diseased body part sent to the brain since ancient ages physicians have used pain as a symptom or benchmark to know the severity of a disease or the condition of the human body. Measuring or quantifying the pain can immensely help the physicians to diagnose the patient and to track the healing process of the patient. In the 21st century, Infrared thermography has become one of the best ways to diagnosis human body pain using the skin temperature. This article introduces various ways of quantifying the pain by using thermal or non-thermal methods.
{"title":"Thermal image processing to Recognize and Quantify Pain in Human Body","authors":"Naresh Pal, Aravind Kilaru, Y. Savaria, A. Lakhssassi","doi":"10.1109/ICSCEE.2018.8538368","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538368","url":null,"abstract":"The basic symptom of a human body for any sort of diseases or problems is pain. Pain can be termed as a message from the injured or diseased body part sent to the brain since ancient ages physicians have used pain as a symptom or benchmark to know the severity of a disease or the condition of the human body. Measuring or quantifying the pain can immensely help the physicians to diagnose the patient and to track the healing process of the patient. In the 21st century, Infrared thermography has become one of the best ways to diagnosis human body pain using the skin temperature. This article introduces various ways of quantifying the pain by using thermal or non-thermal methods.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130632845","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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