Pub Date : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161436
Jovan Milojković, V. Ciric, D. Rancic
In a new era of technology, reducing process execution time using multiple hardware components is a trend. In order to reduce cycle time in software delivery smarter deployment pipeline strategies should be considered, as well as parallel builds and parallel testing strategies. In this paper we propose a system that parallelizes software testing within the deployment pipeline. The proposed system increases hardware used for the process execution and reduces time needed for testing of a developed software product. Docker will be used for the system implementation. Parallelization will be achieved at process and container levels. Furthermore, in this paper we show how parallelization using containers and processes affects time needed for test execution of a developed software product.
{"title":"Design and Implementation of Cluster Based Parallel System for Software Testing","authors":"Jovan Milojković, V. Ciric, D. Rancic","doi":"10.1109/ZINC50678.2020.9161436","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161436","url":null,"abstract":"In a new era of technology, reducing process execution time using multiple hardware components is a trend. In order to reduce cycle time in software delivery smarter deployment pipeline strategies should be considered, as well as parallel builds and parallel testing strategies. In this paper we propose a system that parallelizes software testing within the deployment pipeline. The proposed system increases hardware used for the process execution and reduces time needed for testing of a developed software product. Docker will be used for the system implementation. Parallelization will be achieved at process and container levels. Furthermore, in this paper we show how parallelization using containers and processes affects time needed for test execution of a developed software product.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"100 1","pages":"276-279"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90954707","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161787
S. Cejka
Energy communities, as recently introduced by the European Union’s ’Clean Energy for All Europeans Package’ need to be transformed into the national laws of the member states until Mid of 2021. By integrating local energy producers and consumers, they aim for an improvement of energy efficiency, increasing integration of renewable energy sources, and a reduction of greenhouse gas emissions on a local level. Individuals will be enabled to take over an active part in the energy transition. While a number of remaining open issues were identified, this paper especially deals with profitability aspects for local energy producers and consumers, as well as for the community itself. As this topic will have a significant impact on the participation, the applicability and acceptance of energy communities will also be affected.
{"title":"Legal measures to aid profitability for energy communities and their participants","authors":"S. Cejka","doi":"10.1109/ZINC50678.2020.9161787","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161787","url":null,"abstract":"Energy communities, as recently introduced by the European Union’s ’Clean Energy for All Europeans Package’ need to be transformed into the national laws of the member states until Mid of 2021. By integrating local energy producers and consumers, they aim for an improvement of energy efficiency, increasing integration of renewable energy sources, and a reduction of greenhouse gas emissions on a local level. Individuals will be enabled to take over an active part in the energy transition. While a number of remaining open issues were identified, this paper especially deals with profitability aspects for local energy producers and consumers, as well as for the community itself. As this topic will have a significant impact on the participation, the applicability and acceptance of energy communities will also be affected.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"59 1","pages":"248-250"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87506988","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161798
Huy Nguyen-Quoc, Vinh Truong Hoang
Face matching is an active research topic in the last decade due to various applications in pattern recognition. Rather than using a single feature type, the fusion of many distinct features might decrease the error rate of facial recognition systems. This also increases the time processing and data storage. In this paper, we first employ feature fusion extracted from HOG and GIST descriptor from facial image and use Canonical Correlation Analysis (CCA) to combine into a single feature. Then, a feature selection approach based on Fisher ranking is considered to remove irrelevant and noisy features. The experiment is evaluated on three common datasets (AR, Georgia Tech and MUCT) which have been shown the improvement of the proposed approach.
{"title":"Face recognition based on selection approach via Canonical Correlation Analysis feature fusion","authors":"Huy Nguyen-Quoc, Vinh Truong Hoang","doi":"10.1109/ZINC50678.2020.9161798","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161798","url":null,"abstract":"Face matching is an active research topic in the last decade due to various applications in pattern recognition. Rather than using a single feature type, the fusion of many distinct features might decrease the error rate of facial recognition systems. This also increases the time processing and data storage. In this paper, we first employ feature fusion extracted from HOG and GIST descriptor from facial image and use Canonical Correlation Analysis (CCA) to combine into a single feature. Then, a feature selection approach based on Fisher ranking is considered to remove irrelevant and noisy features. The experiment is evaluated on three common datasets (AR, Georgia Tech and MUCT) which have been shown the improvement of the proposed approach.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"44 1","pages":"54-57"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73531294","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161785
Nur Aisyah Syafinaz Suarin, K. Chia, Fathen Nasohah Kosmani
Even though both farm and wild raw honeys are better than processed honey in terms of nutritional value and quality, wild honey is more expensive than farm honey due to its scarcity, nutrition, and quality. However, there is a challenge for consumer to differentiate both farm and wild raw honey due to the complexity of raw honey. Although near infrared (NIR) spectroscopy is promising to assist consumers to differentiate types of honeys, the financial barrier to have a NIR spectroscopy is needed to be addressed. Thus, this research aims to evaluate the performance of a low cost NIR light acquisition alternative in classifying stingless bee honeys using artificial neural network (ANN). First, 164 honey samples of two different types of raw honeys were prepared. Next, NIR light LEDs of five different wavelengths i.e. 850, 860, 870, 890, and 950 nm with light sensors were used to acquire the transmitted NIR absorbance from raw honey sample. ANN with different number of hidden neurons were used to analyze the data, and six datasets were used to investigate the best distance between NIR light source and light sensors. Results indicate that the acquired NIR light coupled with ANN by using eight hidden neurons and an average distance of 40 mm from light source to light sensor were able to produce the best result with the best true positive (TP) correct classification percentage accuracy and cross entropy (CE) value of 96.0% and 1.14, respectively.
{"title":"Stingless Bee Honey Classification Using Near Infrared Light Coupled With Artificial Neural Network","authors":"Nur Aisyah Syafinaz Suarin, K. Chia, Fathen Nasohah Kosmani","doi":"10.1109/ZINC50678.2020.9161785","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161785","url":null,"abstract":"Even though both farm and wild raw honeys are better than processed honey in terms of nutritional value and quality, wild honey is more expensive than farm honey due to its scarcity, nutrition, and quality. However, there is a challenge for consumer to differentiate both farm and wild raw honey due to the complexity of raw honey. Although near infrared (NIR) spectroscopy is promising to assist consumers to differentiate types of honeys, the financial barrier to have a NIR spectroscopy is needed to be addressed. Thus, this research aims to evaluate the performance of a low cost NIR light acquisition alternative in classifying stingless bee honeys using artificial neural network (ANN). First, 164 honey samples of two different types of raw honeys were prepared. Next, NIR light LEDs of five different wavelengths i.e. 850, 860, 870, 890, and 950 nm with light sensors were used to acquire the transmitted NIR absorbance from raw honey sample. ANN with different number of hidden neurons were used to analyze the data, and six datasets were used to investigate the best distance between NIR light source and light sensors. Results indicate that the acquired NIR light coupled with ANN by using eight hidden neurons and an average distance of 40 mm from light source to light sensor were able to produce the best result with the best true positive (TP) correct classification percentage accuracy and cross entropy (CE) value of 96.0% and 1.14, respectively.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"45 1","pages":"99-102"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76553198","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161803
C. Schirru, L. Billeci, Francesco Sansone, Raffaele Conte, A. Tonacci
Attention tests are among the most widely used for characterizing one of the most important human cognitive domains. However, their link with emotional processes and physiological reactions is not fully clear and often debated. To this extent, in this pilot we used commercially available tools for administering a validated attentional test and, at the same time, to unobtrusively record physiological parameters related to the autonomic nervous system activity in a small cohort of young, healthy individuals. Preliminary results demonstrated the feasibility of this approach and suggested that the methodology employed was somewhat sensitive to detect changes related to the task administered in the cohort studied. Such results would probably pave the way for a future exploitation of integrated hardware/software systems tailored at detecting psychophysiological changes eventually occurring during cognitive testing administration.
{"title":"Autonomic correlates of attention tests delivered by commercial tools","authors":"C. Schirru, L. Billeci, Francesco Sansone, Raffaele Conte, A. Tonacci","doi":"10.1109/ZINC50678.2020.9161803","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161803","url":null,"abstract":"Attention tests are among the most widely used for characterizing one of the most important human cognitive domains. However, their link with emotional processes and physiological reactions is not fully clear and often debated. To this extent, in this pilot we used commercially available tools for administering a validated attentional test and, at the same time, to unobtrusively record physiological parameters related to the autonomic nervous system activity in a small cohort of young, healthy individuals. Preliminary results demonstrated the feasibility of this approach and suggested that the methodology employed was somewhat sensitive to detect changes related to the task administered in the cohort studied. Such results would probably pave the way for a future exploitation of integrated hardware/software systems tailored at detecting psychophysiological changes eventually occurring during cognitive testing administration.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"9 1","pages":"213-215"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89944613","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161778
Arju Aman, Aryan Singh, Ayush Raj, S. Raj
In recent years, consumer electronics for providing better customer service has sought a significant growth. For production, storage and supply of goods to consumers, it is essential to have correct information, recognize and store the information efficiently in computers. Therefore, it is essential to have an efficient and handy bar code recognition system. This paper presents an efficient method for bar code and QR code recognition together. The method automatically detects the Bar code QR code and displays the complete information of the product. The method is developed in python environment using OpenCV library. However, OpenCV does not have any dedicated modules that can be used to read and decode Bar codes and QR codes. The database is developed at the authors’ Institute where bar codes and QR codes are separately assigned to more than 100 items such as books, sofa, tables and chairs. The image of the bar code or QR code is captured in real-time and further processed using the proposed method. The code is being decoded, compared with the Data frame of the stored product and finally, displays the result i.e, the complete information about the product. The execution time of the proposed method is 0.25 seconds. The proposed method can be further prototyped on micro-controllers to develop an efficient bar code recognition system.
{"title":"An Efficient Bar/QR Code Recognition System for Consumer Service Applications","authors":"Arju Aman, Aryan Singh, Ayush Raj, S. Raj","doi":"10.1109/ZINC50678.2020.9161778","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161778","url":null,"abstract":"In recent years, consumer electronics for providing better customer service has sought a significant growth. For production, storage and supply of goods to consumers, it is essential to have correct information, recognize and store the information efficiently in computers. Therefore, it is essential to have an efficient and handy bar code recognition system. This paper presents an efficient method for bar code and QR code recognition together. The method automatically detects the Bar code QR code and displays the complete information of the product. The method is developed in python environment using OpenCV library. However, OpenCV does not have any dedicated modules that can be used to read and decode Bar codes and QR codes. The database is developed at the authors’ Institute where bar codes and QR codes are separately assigned to more than 100 items such as books, sofa, tables and chairs. The image of the bar code or QR code is captured in real-time and further processed using the proposed method. The code is being decoded, compared with the Data frame of the stored product and finally, displays the result i.e, the complete information about the product. The execution time of the proposed method is 0.25 seconds. The proposed method can be further prototyped on micro-controllers to develop an efficient bar code recognition system.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"17 1","pages":"127-131"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88883882","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161823
A. Arora, Arvinder Pal Singh Gagneja
Human behavior and deeds occupy center stage in every major environmental problem confronting humankind. Environmental degradation seems to be related to a hypercompetitive economic system, consumerism, population growth, urbanization, intensification of agriculture, and luxurious lifestyle, which supports ‘self-indulgence into desires’ and not ‘needs-based life.’ This article describes how two key factors, hyper-competitiveness, and consumerism, are associated with evil motives, selfishness, and unethical behavior among individuals and contributing to environmental and social degradation. In a nutshell, consumerism seems to be a slow societal suicide. Hyper-competitiveness articulates greed, and such people are not only manipulative but also adopt vicious and conspicuous methods in besting others. It is inferred from our study that adverse psychological health effects of consumerism and hyper-competitiveness are contributing towards environmental and social degradation.
{"title":"The association of Hyper-Competitiveness and Consumerism with Ecological and Social degradation: A need for a Holistic and Responsible Approach for Environmental and Psychosocial Rehabilitation","authors":"A. Arora, Arvinder Pal Singh Gagneja","doi":"10.1109/ZINC50678.2020.9161823","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161823","url":null,"abstract":"Human behavior and deeds occupy center stage in every major environmental problem confronting humankind. Environmental degradation seems to be related to a hypercompetitive economic system, consumerism, population growth, urbanization, intensification of agriculture, and luxurious lifestyle, which supports ‘self-indulgence into desires’ and not ‘needs-based life.’ This article describes how two key factors, hyper-competitiveness, and consumerism, are associated with evil motives, selfishness, and unethical behavior among individuals and contributing to environmental and social degradation. In a nutshell, consumerism seems to be a slow societal suicide. Hyper-competitiveness articulates greed, and such people are not only manipulative but also adopt vicious and conspicuous methods in besting others. It is inferred from our study that adverse psychological health effects of consumerism and hyper-competitiveness are contributing towards environmental and social degradation.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"41 1","pages":"327-332"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81535774","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161432
GS Pavan, N. Kumar, Krishna Karthik N, J. Manikandan
Modern systems such as consumer electronics, automotive electronics, domestic appliances, music systems, air conditioners, televisions are becoming smarter with built-in voice controlled features, enabling hands-free operation. Real-time speech recognition is heart of such systems and research is in progress towards enhancing these systems to be functional in Indian languages too. Design and evaluation of a real-time speech recognition system using Convolution neural networks for Kannada language is proposed here. Performance of proposed system is evaluated using samples recorded in the lab, as standard speech datasets for this language are not available. A maximum recognition accuracy of 99.60% is obtained on using the proposed system and details pertaining to steps followed to enhance recognition accuracy of proposed system are also reported. The proposed system can be easily extended to other Indian and foreign languages.
{"title":"Design of a Real-Time Speech Recognition System using CNN for Consumer Electronics","authors":"GS Pavan, N. Kumar, Krishna Karthik N, J. Manikandan","doi":"10.1109/ZINC50678.2020.9161432","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161432","url":null,"abstract":"Modern systems such as consumer electronics, automotive electronics, domestic appliances, music systems, air conditioners, televisions are becoming smarter with built-in voice controlled features, enabling hands-free operation. Real-time speech recognition is heart of such systems and research is in progress towards enhancing these systems to be functional in Indian languages too. Design and evaluation of a real-time speech recognition system using Convolution neural networks for Kannada language is proposed here. Performance of proposed system is evaluated using samples recorded in the lab, as standard speech datasets for this language are not available. A maximum recognition accuracy of 99.60% is obtained on using the proposed system and details pertaining to steps followed to enhance recognition accuracy of proposed system are also reported. The proposed system can be easily extended to other Indian and foreign languages.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"19 1","pages":"5-10"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76920639","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 : 2020-05-01DOI: 10.1109/ZINC50678.2020.9161806
P. Asthana, G. Khanna
The features of microelectromechanical systems have been improved by advancements in manufacturing technology and growing rates of integration. The development of small structures or micro systems has created the” Internet of Things” revolution, thereby providing a significant portion of a digitized automated and interconnected environment around smart manufacturing, infrastructure, health and other areas of society. Frequent maintenance and battery refurbishment are not desirable in micro-systems, which require very low power $( mu W mW )$ to operate. Therefore, the most challenging field of micro-scale harvesting research is battery-less activity. Low-frequency ambient vibrations are abundantly available sources of energy that can be used in electrical power conversion. In this study, a low-frequency wideband energy harvester is proposed and simulated.
由于制造技术的进步和集成速度的提高，微机电系统的特性得到了改善。小型结构或微系统的发展引发了“物联网”革命，从而为智能制造、基础设施、健康和其他社会领域提供了数字化、自动化和互联环境的重要组成部分。在微系统中，频繁的维护和电池翻新是不可取的，因为微系统需要非常低的功率(mu W mW)来运行。因此，最具挑战性的微尺度采集研究领域是无电池活动。低频环境振动是丰富的能量来源，可用于电力转换。本文提出并仿真了一种低频宽带能量采集器。
{"title":"A wideband zinc oxide energy harvester for IoT based sensor*","authors":"P. Asthana, G. Khanna","doi":"10.1109/ZINC50678.2020.9161806","DOIUrl":"https://doi.org/10.1109/ZINC50678.2020.9161806","url":null,"abstract":"The features of microelectromechanical systems have been improved by advancements in manufacturing technology and growing rates of integration. The development of small structures or micro systems has created the” Internet of Things” revolution, thereby providing a significant portion of a digitized automated and interconnected environment around smart manufacturing, infrastructure, health and other areas of society. Frequent maintenance and battery refurbishment are not desirable in micro-systems, which require very low power $( mu W mW )$ to operate. Therefore, the most challenging field of micro-scale harvesting research is battery-less activity. Low-frequency ambient vibrations are abundantly available sources of energy that can be used in electrical power conversion. In this study, a low-frequency wideband energy harvester is proposed and simulated.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"108 1","pages":"251-252"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73703844","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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