A. M. Rajapakse, Sanura N. Sanjula, Kelum Nishantha, T. R. Bandara, Dulini, Y. Mudunkotuwa
For generations, Sri Lankans use cement bricks and clay bricks as common building materials in the construction field. This study investigates the feasibility of improving the strength while lowering the mass and thermal conductivity of bricks by adding coconut fiber or coconut fiber dust as a reinforcing material. Each reinforcing material is used in both clay and cement bricks. The mixtures are prepared according to varying volume ratios of the raw materials used. Coconut fibers are combed and cut into 4-5 cm pieces and dry coconut fiber dust is sieved using a 4 mm sieving mesh. The mixture is prepared by hand mixing and the traditional processes are replicated in making the bricks. Tests are carried out to understand the variation of mass, compressive strength, thermal conductivity, and water absorption of the reinforced bricks in comparison to bricks with no reinforced material. The cement brick reinforced with coconut fiber achieves the expected results in the compressive strength test and thermal conductivity test but underperformed when comparing masses and water absorption. Clay bricks reinforced with coconut fiber dust show impressive results in compressive tests and with the addition of dust, the appearance seems to have changed. It is observed that reinforcing cement bricks with coconut fiber could double the compressive strength along with a 5% reduction in mass. Reinforcing clay bricks with coconut fiber dust increases its compressive strength by over 70% while decreasing the mass by over 30 %. The study proves that it is feasible to use reinforced coconut fiber or coconut fiber dust to improve the properties of both clay and cement bricks, while clay bricks reinforced with coconut fiber are an exception.
{"title":"Cement and Clay Bricks Reinforced with Coconut Fiber and Fiber Dust","authors":"A. M. Rajapakse, Sanura N. Sanjula, Kelum Nishantha, T. R. Bandara, Dulini, Y. Mudunkotuwa","doi":"10.31357/ait.v2i3.6046","DOIUrl":"https://doi.org/10.31357/ait.v2i3.6046","url":null,"abstract":"For generations, Sri Lankans use cement bricks and clay bricks as common building materials in the construction field. This study investigates the feasibility of improving the strength while lowering the mass and thermal conductivity of bricks by adding coconut fiber or coconut fiber dust as a reinforcing material. Each reinforcing material is used in both clay and cement bricks. The mixtures are prepared according to varying volume ratios of the raw materials used. Coconut fibers are combed and cut into 4-5 cm pieces and dry coconut fiber dust is sieved using a 4 mm sieving mesh. The mixture is prepared by hand mixing and the traditional processes are replicated in making the bricks. Tests are carried out to understand the variation of mass, compressive strength, thermal conductivity, and water absorption of the reinforced bricks in comparison to bricks with no reinforced material. The cement brick reinforced with coconut fiber achieves the expected results in the compressive strength test and thermal conductivity test but underperformed when comparing masses and water absorption. Clay bricks reinforced with coconut fiber dust show impressive results in compressive tests and with the addition of dust, the appearance seems to have changed. It is observed that reinforcing cement bricks with coconut fiber could double the compressive strength along with a 5% reduction in mass. Reinforcing clay bricks with coconut fiber dust increases its compressive strength by over 70% while decreasing the mass by over 30 %. The study proves that it is feasible to use reinforced coconut fiber or coconut fiber dust to improve the properties of both clay and cement bricks, while clay bricks reinforced with coconut fiber are an exception.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80658379","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}
Buddhi Kodikara, Dr Lanka Undugoda, Himashi Karunarathne, R. Kandisa
Phytochemical constituents in extracts from medicinal plants have been widely used since ancient times to treat microbial infections. Coriandrum sativum and Zingiber officinale are two of the main popular ingredients in traditional medicine recipes. Currently, these extracts are used to prevent Covid-19 infections. Therefore, this review describes the antimicrobial properties of coriander and ginger and how far it is suitable to use against bacterial and viral infections occurring in the human respiratory tract. For instance, the main phytochemical available in C. sativum is linalool, followed by terpinene, pinene, cymene, decenal, and camphor. Gingerol is the main constituent in Z. officinale followed by shogaols and paradols. Moreover, many research findings revealed that the extract from coriander and ginger can be used to control respiratory tract infected pathogens due to the antiviral and antibacterial properties of available phytochemicals. Therefore, it is very effective to use coriander and ginger to boost the immune system. Furthermore, scientific evidence has proved the effective antiviral properties of compounds present in coriander and ginger that have binding affinity to the proteins in the virus, blocking the virus's receptors and boosting the immunity to face the COVID-19 situation. In fact, the effectiveness of the antimicrobial activity of mixed extract of medicinal plant parts is better than that of individuals. Therefore, this will review the therapeutic characteristics of coriander and ginger extracts due to their various phytochemical activities.
{"title":"Antibacterial and Antiviral Properties of Coriandrum Sativum and Zingiber Officinale against Human Respiratory Tract Related Bacterial and Viral Infections: A Review with a Focus on the Case of SARS-CoV","authors":"Buddhi Kodikara, Dr Lanka Undugoda, Himashi Karunarathne, R. Kandisa","doi":"10.31357/ait.v2i3.5598","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5598","url":null,"abstract":"Phytochemical constituents in extracts from medicinal plants have been widely used since ancient times to treat microbial infections. Coriandrum sativum and Zingiber officinale are two of the main popular ingredients in traditional medicine recipes. Currently, these extracts are used to prevent Covid-19 infections. Therefore, this review describes the antimicrobial properties of coriander and ginger and how far it is suitable to use against bacterial and viral infections occurring in the human respiratory tract. For instance, the main phytochemical available in C. sativum is linalool, followed by terpinene, pinene, cymene, decenal, and camphor. Gingerol is the main constituent in Z. officinale followed by shogaols and paradols. Moreover, many research findings revealed that the extract from coriander and ginger can be used to control respiratory tract infected pathogens due to the antiviral and antibacterial properties of available phytochemicals. Therefore, it is very effective to use coriander and ginger to boost the immune system. Furthermore, scientific evidence has proved the effective antiviral properties of compounds present in coriander and ginger that have binding affinity to the proteins in the virus, blocking the virus's receptors and boosting the immunity to face the COVID-19 situation. In fact, the effectiveness of the antimicrobial activity of mixed extract of medicinal plant parts is better than that of individuals. Therefore, this will review the therapeutic characteristics of coriander and ginger extracts due to their various phytochemical activities. ","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73875049","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}
Artificial Intelligence (AI) is now everywhere. It refers to systems that demonstrate intelligent behavior, such as the ability to analyze their environment to take action that is typically displayed by humans and animals. AI-embedded devices possess the ability to learn through example scenarios and past data presented to the system. The word AI was first introduced to the research community in 1956 at a conference at Dartmouth College in the United States [1]. With time, the AI industry expanded from data to information, then to knowledge, and ultimately to intelligence. Due to the depth and breadth of learning capacity associated with AI technologies, today it has become one of the hottest research areas, finding applications in but not limited to computer vision, marketing, industrial automation, big data, and the Internet of things (IOT).
{"title":"Artificial Intelligence for Healthcare Systems of Developing World: Opportunities and Risks","authors":"Maheshika Dissanayake","doi":"10.31357/ait.v2i3.5996","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5996","url":null,"abstract":"Artificial Intelligence (AI) is now everywhere. It refers to systems that demonstrate intelligent behavior, such as the ability to analyze their environment to take action that is typically displayed by humans and animals. AI-embedded devices possess the ability to learn through example scenarios and past data presented to the system. The word AI was first introduced to the research community in 1956 at a conference at Dartmouth College in the United States [1]. With time, the AI industry expanded from data to information, then to knowledge, and ultimately to intelligence. Due to the depth and breadth of learning capacity associated with AI technologies, today it has become one of the hottest research areas, finding applications in but not limited to computer vision, marketing, industrial automation, big data, and the Internet of things (IOT).","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81346295","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}
Kasun Thushara, Fazlun Rifaza Noordeen, Kaveesha N. Ranasinghe, Chamitha D. Alwis, Madushanka N. Dharmaweera, Bhathiya M. Pilanawithana
The agricultural sector is a major economic force in Sri Lanka, which contributes to the national economy, food security, and employment. The traditional methods practiced by farmers mainly drove the growth of the agriculture sector over the last 2500 years. However, these traditional methods have often been ineffective against pest attacks in recent years causing significant losses to farmers and threatening food security. To counter these issues, officials and researchers have started formulating novel technology-based smart solutions. This study proposes a smart, autonomous mobile robot that can help detect pests and diseases in advance and assist in crop estimation of chili plants. The model is created as such for pest and plant disease detection in small-scale chili plantations with the hope of using it in other crop types for the same purpose in the future. Thus, the proposed approach together with the developed model can be used to enhance the growth of other plants as well. Identification of the type of garden and the detection of pests and plant diseases are achieved using machine learning techniques while the identification of nutrient deficiencies is achieved using image processing techniques. This proposed mobile robot incorporates sensory inputs, machine learning, robotics, and image processing. Furthermore, a mobile application acts as the interface between the user and the robot.
{"title":"A Novel Machine Learning based Autonomous Farming Robot for Small-Scale Chili Plantations","authors":"Kasun Thushara, Fazlun Rifaza Noordeen, Kaveesha N. Ranasinghe, Chamitha D. Alwis, Madushanka N. Dharmaweera, Bhathiya M. Pilanawithana","doi":"10.31357/ait.v2i3.5461","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5461","url":null,"abstract":"The agricultural sector is a major economic force in Sri Lanka, which contributes to the national economy, food security, and employment. The traditional methods practiced by farmers mainly drove the growth of the agriculture sector over the last 2500 years. However, these traditional methods have often been ineffective against pest attacks in recent years causing significant losses to farmers and threatening food security. To counter these issues, officials and researchers have started formulating novel technology-based smart solutions. This study proposes a smart, autonomous mobile robot that can help detect pests and diseases in advance and assist in crop estimation of chili plants. The model is created as such for pest and plant disease detection in small-scale chili plantations with the hope of using it in other crop types for the same purpose in the future. Thus, the proposed approach together with the developed model can be used to enhance the growth of other plants as well. Identification of the type of garden and the detection of pests and plant diseases are achieved using machine learning techniques while the identification of nutrient deficiencies is achieved using image processing techniques. This proposed mobile robot incorporates sensory inputs, machine learning, robotics, and image processing. Furthermore, a mobile application acts as the interface between the user and the robot.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"06 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85975702","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}
Shalika Laksan Wickrama, D. Koralagama, Sandika Abeysinghe
Value-added activities, chain structures, and middlemen impact are incomprehensible in the dried fish economy. Processors have a significant impact at the initial stage of the value chain, but little control over value chain management; however vastly monopolized by intermediaries. Yet, the processors receive poor returns compared to other actors in the value chain. Value stream analysis visualizes the value additions incorporated by all the actors and agents in the value chain. Despite the literature states of different returns along the value chain, a comprehensive mapping is needed to assess the contribution by actors and agents over Value Added (VA), Necessary Value Added (NVA) and Non-Necessary Value Added activities (NNVA). This will enable fair and efficient functions in the value chain. The same scenario is common in dried fish value chains in Sri Lanka which is inadequately researched. This study aims to conduct a value stream analysis, middlemen impact assessment, and their relationship for skipjack tuna and smoothbelly sardinella dried fish value chains representing the highest per-capita consumption dried fish varieties in Sri Lanka. Hambantota, Matara, Puttalam, and Gampaha were selected to conduct the study representing the highest dried fish production districts. A quantitative data collection method was adopted employing a pre-tested structured questionnaire. A simple random sampling technique was used to draw the sample from processors, wholesalers and retailers where the sample sizes were 100, ,40, and 40 respectively. Secondary data were collected from reputed published materials. Data were analyzed mainly using descriptive techniques. The number of VA, NV,A and NNVA activities are approximately decreased through the skipjack tuna value chain as processor (VA-10, NVA-01, NNVA-02), wholesaler (VA-2, NVA-1, NNVA-4) and retailer (VA-02, NVA-01, NNVA-01) and for smoothbelly sardinella processor (VA-08, NVA-01, NNVA-02), wholesaler (VA-02, NVA-01, NNVA-02) and retailer (VA-01, NVA-01, NNVA-02) levels. Time spent for each activity is decreased through value chain for both dried fish varieties. The market margins for skipjack tuna and smoothbelly sardinella are 46.64% and 38.19% respectively. Profit margins are increased along the value chain at the processor, wholesaler and retailer levels for skipjack tuna (9.63%, 15.25%, 27.22%) and smoothbelly sardinella (12.53%, 14.23%, 20.98%) respectively. In contrast, profit gain was not fairly distributed along the value chain proportionately contribution to activities and times spent by actors. This recommended an effective mechanism for fair profit sharing for dried fish actors based on their contribution to value addition and time spent on each activity.
{"title":"Value Stream Analysis and Middlemen Impact of Skipjack Tuna and Smoothbelly Sardinella Dried Fish Value Chains in Sri Lanka","authors":"Shalika Laksan Wickrama, D. Koralagama, Sandika Abeysinghe","doi":"10.31357/ait.v2i3.5661","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5661","url":null,"abstract":"Value-added activities, chain structures, and middlemen impact are incomprehensible in the dried fish economy. Processors have a significant impact at the initial stage of the value chain, but little control over value chain management; however vastly monopolized by intermediaries. Yet, the processors receive poor returns compared to other actors in the value chain. Value stream analysis visualizes the value additions incorporated by all the actors and agents in the value chain. Despite the literature states of different returns along the value chain, a comprehensive mapping is needed to assess the contribution by actors and agents over Value Added (VA), Necessary Value Added (NVA) and Non-Necessary Value Added activities (NNVA). This will enable fair and efficient functions in the value chain. The same scenario is common in dried fish value chains in Sri Lanka which is inadequately researched. This study aims to conduct a value stream analysis, middlemen impact assessment, and their relationship for skipjack tuna and smoothbelly sardinella dried fish value chains representing the highest per-capita consumption dried fish varieties in Sri Lanka. Hambantota, Matara, Puttalam, and Gampaha were selected to conduct the study representing the highest dried fish production districts. A quantitative data collection method was adopted employing a pre-tested structured questionnaire. A simple random sampling technique was used to draw the sample from processors, wholesalers and retailers where the sample sizes were 100, ,40, and 40 respectively. Secondary data were collected from reputed published materials. Data were analyzed mainly using descriptive techniques. The number of VA, NV,A and NNVA activities are approximately decreased through the skipjack tuna value chain as processor (VA-10, NVA-01, NNVA-02), wholesaler (VA-2, NVA-1, NNVA-4) and retailer (VA-02, NVA-01, NNVA-01) and for smoothbelly sardinella processor (VA-08, NVA-01, NNVA-02), wholesaler (VA-02, NVA-01, NNVA-02) and retailer (VA-01, NVA-01, NNVA-02) levels. Time spent for each activity is decreased through value chain for both dried fish varieties. The market margins for skipjack tuna and smoothbelly sardinella are 46.64% and 38.19% respectively. Profit margins are increased along the value chain at the processor, wholesaler and retailer levels for skipjack tuna (9.63%, 15.25%, 27.22%) and smoothbelly sardinella (12.53%, 14.23%, 20.98%) respectively. In contrast, profit gain was not fairly distributed along the value chain proportionately contribution to activities and times spent by actors. This recommended an effective mechanism for fair profit sharing for dried fish actors based on their contribution to value addition and time spent on each activity.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84838645","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}
Lateral movement is a pervasive threat because modern networked systems that provide access to multiple users are far more efficient than their non-networked counterparts. It is a well-known attack methodology with extensive research conducted investigating the prevention of lateral movement in enterprise systems. However, attackers use increasingly sophisticated methods to move laterally that bypass typical detection systems. This research comprehensively reviews the problems in lateral movement detection and outlines common defenses to protect modern systems from lateral movement attacks. A literature review outlines techniques for automatic detection of malicious lateral movement, explaining common attack methods utilized by advanced persistent threats and components built into the Windows operating system that can assist with discovering malicious lateral movement. Finally, a novel approach for moving laterally designed by other security researchers is reviewed and studied, an original process for detecting this method of lateral movement is proposed, and the application of the detection methodology is also expanded.
{"title":"A Novel Method for Moving Laterally and Discovering Malicious Lateral Movements in Windows Operating Systems: A Case Study","authors":"A. Mailewa, Kyle Rozendaal","doi":"10.31357/ait.v2i3.5584","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5584","url":null,"abstract":"Lateral movement is a pervasive threat because modern networked systems that provide access to multiple users are far more efficient than their non-networked counterparts. It is a well-known attack methodology with extensive research conducted investigating the prevention of lateral movement in enterprise systems. However, attackers use increasingly sophisticated methods to move laterally that bypass typical detection systems. This research comprehensively reviews the problems in lateral movement detection and outlines common defenses to protect modern systems from lateral movement attacks. A literature review outlines techniques for automatic detection of malicious lateral movement, explaining common attack methods utilized by advanced persistent threats and components built into the Windows operating system that can assist with discovering malicious lateral movement. Finally, a novel approach for moving laterally designed by other security researchers is reviewed and studied, an original process for detecting this method of lateral movement is proposed, and the application of the detection methodology is also expanded.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85622970","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}
Driving under the influence of fatigue often results in uncontrollable vehicle dynamics, which causes severe and fatal accidents. Therefore, early warning on the fatigue onset is crucial to avoid occurrences of such kind of a disaster. In this paper, the authors have investigated a novel semi-supervised convolutional variational autoencoder-based classification approach to classify the state of the driver. A convolutional variational autoencoder is a generative network. The authors have proposed a discriminative model using convolutional variational autoencoders and residual learning. This approach calculates an intermediate loss base on deep features of the network in addition to the label information in training. The loss obtained by this method helps the training to be more effective on the model and leads to better accuracy in driver fatigue classification. The trained model has managed to classify driver fatigue with higher accuracy (97%) than the other successful models taken into comparison, proving that the proposed method is more practical for computing classification loss for driver fatigue to currently available methods.
{"title":"Deep Residual Learning-Based Convolutional Variational Autoencoder For Driver Fatigue Classification","authors":"Sameera Adhikari, Senaka Amarakeerthi","doi":"10.31357/ait.v2i3.5545","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5545","url":null,"abstract":"Driving under the influence of fatigue often results in uncontrollable vehicle dynamics, which causes severe and fatal accidents. Therefore, early warning on the fatigue onset is crucial to avoid occurrences of such kind of a disaster. In this paper, the authors have investigated a novel semi-supervised convolutional variational autoencoder-based classification approach to classify the state of the driver. A convolutional variational autoencoder is a generative network. The authors have proposed a discriminative model using convolutional variational autoencoders and residual learning. This approach calculates an intermediate loss base on deep features of the network in addition to the label information in training. The loss obtained by this method helps the training to be more effective on the model and leads to better accuracy in driver fatigue classification. The trained model has managed to classify driver fatigue with higher accuracy (97%) than the other successful models taken into comparison, proving that the proposed method is more practical for computing classification loss for driver fatigue to currently available methods.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74318784","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}
Many businesses are interested in searching for the latest technologies to secure the tie with existing customers and to prevent potential customers from abandoning their businesses during the COVID-19 pandemic. The food industry is one of them. Therefore, this review article is an attempt to identify various e-marketing tools adopted in the business world in the pre-covid era and to underpin their applicability in the food industry in the covid era by highlighting the advantages and challenges of their adoption. Research articles, conference proceedings, book chapters, theses, and dissertations regarding the topic of applications of e-marketing published from 2000 to 2019 available in the google scholar database, were considered in the review. The final search of the literature was carried out in February 2020. The study reveals that the benefits of applying e-marketing tools in food businesses could compensate for the pitfalls of adopting them. Authors suggest that the ability to compare prices of similar products from different sellers as the most promising benefit of e-marketing, from the customer perspective. Similarly, the cost-effectiveness experienced by food suppliers compared to traditional marketing, makes the e-marketing concept attractive, for food businesses. This work discovers the ability and the inclination of people to launch, manage and organize business ventures with e-marketing approaches in the present as well as the future world.
{"title":"E-marketing Tools for Food Businesses Amidst Covid-19 Pandemic: Advantages and Challenges","authors":"P. Wanniarachchi, Supun Rajakaruna","doi":"10.31357/ait.v2i3.5663","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5663","url":null,"abstract":"Many businesses are interested in searching for the latest technologies to secure the tie with existing customers and to prevent potential customers from abandoning their businesses during the COVID-19 pandemic. The food industry is one of them. Therefore, this review article is an attempt to identify various e-marketing tools adopted in the business world in the pre-covid era and to underpin their applicability in the food industry in the covid era by highlighting the advantages and challenges of their adoption. Research articles, conference proceedings, book chapters, theses, and dissertations regarding the topic of applications of e-marketing published from 2000 to 2019 available in the google scholar database, were considered in the review. The final search of the literature was carried out in February 2020. The study reveals that the benefits of applying e-marketing tools in food businesses could compensate for the pitfalls of adopting them. Authors suggest that the ability to compare prices of similar products from different sellers as the most promising benefit of e-marketing, from the customer perspective. Similarly, the cost-effectiveness experienced by food suppliers compared to traditional marketing, makes the e-marketing concept attractive, for food businesses. This work discovers the ability and the inclination of people to launch, manage and organize business ventures with e-marketing approaches in the present as well as the future world.\u0000 ","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84213517","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}
Rapid technological advancements have aided the service sector's continued evolution, converting traditional physical service encounters managed by service professionals into self-service technologies (SSTs) controlled by customers. Despite the fact that prior studies have attempted to understand customers' technology acceptance in general, sufficient attention has not been paid to the study of self-service technologies, particularly Online based SSTs. Hence, the purpose of this study is to investigate the website aesthetics and technology playfulness of online-based SSTs leading the use of self-service technologies in the Sri Lankan commercial banking industry. A qualitative approach was undertaken, conducting 50 semi-structured interviews with banking customers who use SSTs in the Western Province, Sri Lanka with the use of a non-probabilistic purposeful sampling strategy. The method of thematic analysis was used to analyze the data. The findings revealed “Information quality and guidance”, “Innovative systems and facilities”, “Use of multiple languages”, “High interactivity” and “Visually appealing techniques” as the five themes of website aesthetics and “Enjoyment”, “Exciting”, “Entertaining”, “Creativity”, “Delight” and “Appealing features” as the six themes of technology playfulness leading towards the use of online-based SSTs in the banking sector. The findings would occupy the vacuum of existing literature on the customer use of online-based self-service technologies. Practitioners will be given direction with the understanding on how consumers could be encouraged towards the use of online-based SSTs with the integration of website aesthetics and technology playfulness to improve the delivery of self-service technologies in the commercial banking sector.
{"title":"Website Aesthetics and Technology Playfulness in Encouraging Customer Use of Online based Self-Service Technologies: Special Reference to Commercial Banks in Sri Lanka","authors":"Sandamali Galdolage, Samudrika Rasanjalee","doi":"10.31357/ait.v2i3.5500","DOIUrl":"https://doi.org/10.31357/ait.v2i3.5500","url":null,"abstract":"Rapid technological advancements have aided the service sector's continued evolution, converting traditional physical service encounters managed by service professionals into self-service technologies (SSTs) controlled by customers. Despite the fact that prior studies have attempted to understand customers' technology acceptance in general, sufficient attention has not been paid to the study of self-service technologies, particularly Online based SSTs. Hence, the purpose of this study is to investigate the website aesthetics and technology playfulness of online-based SSTs leading the use of self-service technologies in the Sri Lankan commercial banking industry. A qualitative approach was undertaken, conducting 50 semi-structured interviews with banking customers who use SSTs in the Western Province, Sri Lanka with the use of a non-probabilistic purposeful sampling strategy. The method of thematic analysis was used to analyze the data. The findings revealed “Information quality and guidance”, “Innovative systems and facilities”, “Use of multiple languages”, “High interactivity” and “Visually appealing techniques” as the five themes of website aesthetics and “Enjoyment”, “Exciting”, “Entertaining”, “Creativity”, “Delight” and “Appealing features” as the six themes of technology playfulness leading towards the use of online-based SSTs in the banking sector. The findings would occupy the vacuum of existing literature on the customer use of online-based self-service technologies. Practitioners will be given direction with the understanding on how consumers could be encouraged towards the use of online-based SSTs with the integration of website aesthetics and technology playfulness to improve the delivery of self-service technologies in the commercial banking sector.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81560291","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}
For decades, researchers have investigated how to recognize facial images. This study reviews the development of different face recognition (FR) methods, namely, holistic learning, handcrafted local feature learning, shallow learning, and deep learning (DL). With the development of methods, the accuracy of recognizing faces in the labeled faces in the wild (LFW) database has been increased. The accuracy of holistic learning is 60%, that of handcrafted local feature learning increases to 70%, and that of shallow learning is 86%. Finally, DL achieves human-level performance (97% accuracy). This enhanced accuracy is caused by large datasets and graphics processing units (GPUs) with massively parallel processing capabilities. Furthermore, FR challenges and current research studies are discussed to understand future research directions. The results of this study show that presently the database of labeled faces in the wild has reached 99.85% accuracy.
{"title":"Learning Representations for Face Recognition: A Review from Holistic to Deep Learning","authors":"Fabian Barreto, J. Sarvaiya, S. Patnaik","doi":"10.46604/aiti.2022.8308","DOIUrl":"https://doi.org/10.46604/aiti.2022.8308","url":null,"abstract":"For decades, researchers have investigated how to recognize facial images. This study reviews the development of different face recognition (FR) methods, namely, holistic learning, handcrafted local feature learning, shallow learning, and deep learning (DL). With the development of methods, the accuracy of recognizing faces in the labeled faces in the wild (LFW) database has been increased. The accuracy of holistic learning is 60%, that of handcrafted local feature learning increases to 70%, and that of shallow learning is 86%. Finally, DL achieves human-level performance (97% accuracy). This enhanced accuracy is caused by large datasets and graphics processing units (GPUs) with massively parallel processing capabilities. Furthermore, FR challenges and current research studies are discussed to understand future research directions. The results of this study show that presently the database of labeled faces in the wild has reached 99.85% accuracy.","PeriodicalId":52314,"journal":{"name":"Advances in Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49634565","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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