Pub Date : 2017-07-03DOI: 10.1080/13614576.2017.1368407
Dr. Vaibhav Eknath Narawade, U. Kolekar
ABSTRACT A wireless sensor network (WSN) is an application area that is valuable in various fields, such as healthcare monitoring, environmental monitoring, and so on. Application areas require WSNs with high throughput and low degree of packet loss. Due to congestion in the network, the throughput of the network is affected, which imposes the need for congestion control in the network. This article proposes a method, titled NARX Neural network-based Rate Adjustment (NNRA) for avoiding and controlling congestion in the network. Initially, congestion in the network is avoided by dropping packets and the NNRA is used to control congestion in the network when congestion is present. Performance analysis is carried out in terms of throughput, delay, size of the queue, packet loss, and the level of the congestion using two setups. The results of the proposed method are compared with the existing methods to prove the effectiveness of the proposed method. The proposed method attained a maximum throughput at a rate of 0.9585 and minimum values for delay, queue size, packet loss, and the congestion level.
{"title":"NNRA-CAC: NARX Neural Network-based Rate Adjustment for Congestion Avoidance and Control in Wireless Sensor Networks","authors":"Dr. Vaibhav Eknath Narawade, U. Kolekar","doi":"10.1080/13614576.2017.1368407","DOIUrl":"https://doi.org/10.1080/13614576.2017.1368407","url":null,"abstract":"ABSTRACT A wireless sensor network (WSN) is an application area that is valuable in various fields, such as healthcare monitoring, environmental monitoring, and so on. Application areas require WSNs with high throughput and low degree of packet loss. Due to congestion in the network, the throughput of the network is affected, which imposes the need for congestion control in the network. This article proposes a method, titled NARX Neural network-based Rate Adjustment (NNRA) for avoiding and controlling congestion in the network. Initially, congestion in the network is avoided by dropping packets and the NNRA is used to control congestion in the network when congestion is present. Performance analysis is carried out in terms of throughput, delay, size of the queue, packet loss, and the level of the congestion using two setups. The results of the proposed method are compared with the existing methods to prove the effectiveness of the proposed method. The proposed method attained a maximum throughput at a rate of 0.9585 and minimum values for delay, queue size, packet loss, and the congestion level.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"110 - 85"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1368407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48430733","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 : 2017-07-03DOI: 10.1080/13614576.2017.1368406
S. Halbhavi, D. Kulkarni, S. K. Ambekar, D. Manjunath
ABSTRACT Nowadays, the electric power networks comprise diverse renewable energy resources, with the rapid development of technologies. In this scenario, the optimal Economic Dispatch is required by the power system due to the increment of power generation cost and ever growing demand of electrical energy. Thus, the reduction of power generation cost in terms of fuel cost and emission cost has become one of the main challenges in the power system. Accordingly, this article proposes the Grey Wolf Optimization-Extended Searching (GWO-ES) algorithm to provide the excellent solution for the problems regarding Combined Economic and Emission Dispatch (CEED). It validates the robustness of the proposed algorithm in seven Hybrid Renewable Energy Systems (HRES) test bus systems, which combines the wind turbine along with the thermal power plant. Furthermore, it compares the performance of the proposed GWO-ES algorithm with conventional algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and GWO. Next, the article emulates a valuable convergence analysis and justification for the quality of CEED through the GWO-ES algorithm. Finally, the result was compared to four other conventional algorithms to assure the efficiency of the proposed algorithm in terms of fuel cost and emission cost reduction.
{"title":"Adaptive Grey Wolf Optimization for Weightage-based Combined Economic Emission Dispatch in Hybrid Renewable Energy Systems","authors":"S. Halbhavi, D. Kulkarni, S. K. Ambekar, D. Manjunath","doi":"10.1080/13614576.2017.1368406","DOIUrl":"https://doi.org/10.1080/13614576.2017.1368406","url":null,"abstract":"ABSTRACT Nowadays, the electric power networks comprise diverse renewable energy resources, with the rapid development of technologies. In this scenario, the optimal Economic Dispatch is required by the power system due to the increment of power generation cost and ever growing demand of electrical energy. Thus, the reduction of power generation cost in terms of fuel cost and emission cost has become one of the main challenges in the power system. Accordingly, this article proposes the Grey Wolf Optimization-Extended Searching (GWO-ES) algorithm to provide the excellent solution for the problems regarding Combined Economic and Emission Dispatch (CEED). It validates the robustness of the proposed algorithm in seven Hybrid Renewable Energy Systems (HRES) test bus systems, which combines the wind turbine along with the thermal power plant. Furthermore, it compares the performance of the proposed GWO-ES algorithm with conventional algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and GWO. Next, the article emulates a valuable convergence analysis and justification for the quality of CEED through the GWO-ES algorithm. Finally, the result was compared to four other conventional algorithms to assure the efficiency of the proposed algorithm in terms of fuel cost and emission cost reduction.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"124 - 142"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1368406","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48526798","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 : 2017-07-03DOI: 10.1080/13614576.2017.1412146
{"title":"EOV-C2","authors":"","doi":"10.1080/13614576.2017.1412146","DOIUrl":"https://doi.org/10.1080/13614576.2017.1412146","url":null,"abstract":"","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"143 - 143"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1412146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44103952","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 : 2017-07-03DOI: 10.1080/13614576.2017.1368408
J. Gitanjali, Muhammad Rukunuddin Ghalib
ABSTRACT Human activity recognition is an effective approach for identifying the characteristics of historical data. In the past decades, different shallow classifiers and handcrafted features were used to identify the activities from the sensor data. These approaches are configured for offline processing and are not suitable for sequential data. This article proposes an adaptive framework for human activity recognition using a deep learning mechanism. This deep learning approach forms the deep belief network (DBN), which contains a visible layer and hidden layers. The processing of raw sensor data is performed by these layers and the activity is identified at the top most layers. The DBN is tested using the real time environment with the help of mobile devices that contain an accelerometer, a magnetometer, and a gyroscope. The results are analyzed with the metrics of precision, recall, and the F1-score. The results proved that the proposed method has a higher F1_score when compared to the existing approach.
{"title":"A Novel Framework for Human Activity Recognition with Time Labelled Real Time Sensor Data","authors":"J. Gitanjali, Muhammad Rukunuddin Ghalib","doi":"10.1080/13614576.2017.1368408","DOIUrl":"https://doi.org/10.1080/13614576.2017.1368408","url":null,"abstract":"ABSTRACT Human activity recognition is an effective approach for identifying the characteristics of historical data. In the past decades, different shallow classifiers and handcrafted features were used to identify the activities from the sensor data. These approaches are configured for offline processing and are not suitable for sequential data. This article proposes an adaptive framework for human activity recognition using a deep learning mechanism. This deep learning approach forms the deep belief network (DBN), which contains a visible layer and hidden layers. The processing of raw sensor data is performed by these layers and the activity is identified at the top most layers. The DBN is tested using the real time environment with the help of mobile devices that contain an accelerometer, a magnetometer, and a gyroscope. The results are analyzed with the metrics of precision, recall, and the F1-score. The results proved that the proposed method has a higher F1_score when compared to the existing approach.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"71 - 84"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1368408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42475588","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 : 2017-01-02DOI: 10.1080/13614576.2017.1297731
M. Ngoepe, S. Katuu
ABSTRACT The importance of curriculum development on archives and records management in the digital era, especially on the African continent, cannot be overemphasized. While many universities in the global hub have included studies on all aspects of archives and records management programs with many emphasizing records created in networked environments, the same cannot be said about universities on the African continent. In Africa, education and training of archives and records professionals can be traced back several decades. Archives and records practitioners in Africa’s different countries have, over the years, taken varying paths to attain their professional qualifications. This study outlines progress on an ongoing study by InterPARES Trust Africa Team that examines the curricula in different African educational institutions and investigates the extent to which they address the increasingly complex environment that includes the management of digital records in networked environments. It is hoped that the study will inform curriculum development and review in the area of digital records at the institutions of higher learning in Africa.
{"title":"Provision of Records Created in Networked Environments in the Curricula of Institutions of Higher Learning in Africa","authors":"M. Ngoepe, S. Katuu","doi":"10.1080/13614576.2017.1297731","DOIUrl":"https://doi.org/10.1080/13614576.2017.1297731","url":null,"abstract":"ABSTRACT The importance of curriculum development on archives and records management in the digital era, especially on the African continent, cannot be overemphasized. While many universities in the global hub have included studies on all aspects of archives and records management programs with many emphasizing records created in networked environments, the same cannot be said about universities on the African continent. In Africa, education and training of archives and records professionals can be traced back several decades. Archives and records practitioners in Africa’s different countries have, over the years, taken varying paths to attain their professional qualifications. This study outlines progress on an ongoing study by InterPARES Trust Africa Team that examines the curricula in different African educational institutions and investigates the extent to which they address the increasingly complex environment that includes the management of digital records in networked environments. It is hoped that the study will inform curriculum development and review in the area of digital records at the institutions of higher learning in Africa.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"1 - 12"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1297731","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43106113","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 : 2017-01-02DOI: 10.1080/13614576.2017.1297733
Suvarna S. Pawar, Y. Prasanth
ABSTRACT Nowadays, the web service has become the emerging communication technology where the interaction of each user is performed through the World Wide Web. However, the performance of the web service mechanism is degraded due to security flaws that occur throughout the Internet.. The user or service requester may not attain the relevant web service for their requirement. To overcome this problem, the newly developed multi-objective based Cuckoo Search (MCS) algorithm is proposed in this article. Initially, the input query model was built by the query keyword that is provided by the service requester. Then, the given query is matched with the database that hosts the web services that relates to input query. Among the various services, the user has to select the appropriate web service using the proposed algorithm. The MCS algorithm is newly designed by combining the Cuckoo Search algorithm and the QoS parameter based multiple objectives. Additionally, the new mathematical model of fitness is evaluated by the multi-objective parameters. Finally, the proposed algorithm exploits the fitness value to select the relevant web service for the user query. The experimental results are validated and performance is analyzed by the parameters of precision, recall, and F-measure. Thus, 86.6% of precision value was obtained by the proposed method, which ensured provision of the appropriate web service.
{"title":"Multi-Objective Optimization Model for QoS-Enabled Web Service Selection in Service-Based Systems","authors":"Suvarna S. Pawar, Y. Prasanth","doi":"10.1080/13614576.2017.1297733","DOIUrl":"https://doi.org/10.1080/13614576.2017.1297733","url":null,"abstract":"ABSTRACT Nowadays, the web service has become the emerging communication technology where the interaction of each user is performed through the World Wide Web. However, the performance of the web service mechanism is degraded due to security flaws that occur throughout the Internet.. The user or service requester may not attain the relevant web service for their requirement. To overcome this problem, the newly developed multi-objective based Cuckoo Search (MCS) algorithm is proposed in this article. Initially, the input query model was built by the query keyword that is provided by the service requester. Then, the given query is matched with the database that hosts the web services that relates to input query. Among the various services, the user has to select the appropriate web service using the proposed algorithm. The MCS algorithm is newly designed by combining the Cuckoo Search algorithm and the QoS parameter based multiple objectives. Additionally, the new mathematical model of fitness is evaluated by the multi-objective parameters. Finally, the proposed algorithm exploits the fitness value to select the relevant web service for the user query. The experimental results are validated and performance is analyzed by the parameters of precision, recall, and F-measure. Thus, 86.6% of precision value was obtained by the proposed method, which ensured provision of the appropriate web service.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"34 - 53"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1297733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44380109","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 : 2017-01-02DOI: 10.1080/13614576.2017.1297732
S. B. Vinay Kumar, P. Rao
ABSTRACT One of the most familiar stochastic heuristic search algorithm is Particle swarm optimization (PSO), which is motivated by social behavior of animals like birds, fishes, and so forth. The significant advantages of PSO algorithm are simple structure and limited parameters to be used. Among the parameters, inertia weight is considered as the most crucial one in PSO which brings trade-off between the characteristics of exploitation and exploration. A novel Interactive Self-Improvement based Adaptive PSO (ISI-APSO) method that traits better searching efficiency and accuracy than the traditional particle swarm optimization is proposed. More precisely, it can achieve faster convergence speed while on global search over the entire search space. The simulation results show that the performance of our proposed ISI-APSO is substantially improved than other heuristic algorithms in terms of the search efficiency and convergence speed.
{"title":"Interactive Self Improvement Based Adaptive Particle Swarm Optimization","authors":"S. B. Vinay Kumar, P. Rao","doi":"10.1080/13614576.2017.1297732","DOIUrl":"https://doi.org/10.1080/13614576.2017.1297732","url":null,"abstract":"ABSTRACT One of the most familiar stochastic heuristic search algorithm is Particle swarm optimization (PSO), which is motivated by social behavior of animals like birds, fishes, and so forth. The significant advantages of PSO algorithm are simple structure and limited parameters to be used. Among the parameters, inertia weight is considered as the most crucial one in PSO which brings trade-off between the characteristics of exploitation and exploration. A novel Interactive Self-Improvement based Adaptive PSO (ISI-APSO) method that traits better searching efficiency and accuracy than the traditional particle swarm optimization is proposed. More precisely, it can achieve faster convergence speed while on global search over the entire search space. The simulation results show that the performance of our proposed ISI-APSO is substantially improved than other heuristic algorithms in terms of the search efficiency and convergence speed.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"13 - 33"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1297732","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42343098","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 : 2017-01-02DOI: 10.1080/13614576.2017.1297734
M. Praveen, K. Vishnuvardhan Reddy, R. Babu
ABSTRACT Recently, Internet of Things (IoT) devices are highly utilized in diverse fields such as environmental monitoring, industries, and smart home, among others. Under such instances, a cluster head is selected among the diverse IoT devices of wireless sensor network (WSN) based IoT network to maintain a reliable network with efficient data transmission. This article proposed a novel method with the combination of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. This method considers the distance, energy, delay, load, and temperature of the IoT devices during the operation of the cluster head selection process. Furthermore, the performance of the proposed method is analyzed by comparing with conventional methods such as Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GSO algorithms. The analysis related to the existence of the number of alive nodes, convergence estimation, and performance in terms of normalized energy, load, and temperature of the IoT devices are determined. Thus the analysis of our implementation reveals the superior performance of the proposed method.
{"title":"Energy Efficient Cluster Head Selection for Internet of Things","authors":"M. Praveen, K. Vishnuvardhan Reddy, R. Babu","doi":"10.1080/13614576.2017.1297734","DOIUrl":"https://doi.org/10.1080/13614576.2017.1297734","url":null,"abstract":"ABSTRACT Recently, Internet of Things (IoT) devices are highly utilized in diverse fields such as environmental monitoring, industries, and smart home, among others. Under such instances, a cluster head is selected among the diverse IoT devices of wireless sensor network (WSN) based IoT network to maintain a reliable network with efficient data transmission. This article proposed a novel method with the combination of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. This method considers the distance, energy, delay, load, and temperature of the IoT devices during the operation of the cluster head selection process. Furthermore, the performance of the proposed method is analyzed by comparing with conventional methods such as Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GSO algorithms. The analysis related to the existence of the number of alive nodes, convergence estimation, and performance in terms of normalized energy, load, and temperature of the IoT devices are determined. Thus the analysis of our implementation reveals the superior performance of the proposed method.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"22 1","pages":"54 - 70"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2017.1297734","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48612835","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 : 2016-08-01DOI: 10.1080/13614576.2019.1608571
Sidney Netshakhuma, M. Ngoepe
ABSTRACT Despite the availability of guidelines, standards, and software developed by national archives, professional associations, research groups and commercial organizations, digital records are still a challenge to manage, especially in Africa. A number of digitization projects undertaken by archival organizations in Africa failed to realize their goals of ensuring preservation and access of records. This is partially due to lack of strategies to migrate from analog to digital records. This study explored the strategies adopted by the African National Congress (ANC) in digitizing its liberation archives with the aim of capturing lessons learnt. Qualitative data were collected through interviews with purposively selected employees of the ANC, MultiChoice, Africa Media Online, and the Nelson Mandela Foundation as they were involved in the digitization project of the liberation archives. The results revealed that the ANC established an archives management committee to lead the implementation of digitization of the liberation archives. Furthermore, the ANC relied heavily on the companies MultiChoice and Africa Media Online, as its archivists were not trained for the digitization of archives. A number of lessons learnt with regard to the digitization of liberations archives are captured. The study concludes by demonstrating the importance of having a strategy in digitizing archival holdings. It is recommended that this study should be extended to other liberation movements in eastern and southern Africa. Furthermore, a study on determining the authenticity of digitized liberation archives is recommended.
尽管国家档案馆、专业协会、研究小组和商业组织开发了指导方针、标准和软件，但数字记录管理仍然是一个挑战，特别是在非洲。非洲档案组织开展的一些数字化项目未能实现其确保保存和获取记录的目标。这部分是由于缺乏从模拟记录向数字记录迁移的策略。本研究探讨了非洲人国民大会(ANC)在将其解放档案数字化方面采取的策略，目的是获取经验教训。定性数据是通过对参与解放档案数字化项目的非国大、多选择、非洲媒体在线和纳尔逊·曼德拉基金会的员工进行访谈收集的。结果显示，ANC成立了档案管理委员会，领导实施解放档案的数字化。此外，ANC严重依赖MultiChoice和Africa Media Online公司，因为它的档案保管员没有接受过档案数字化方面的培训。在解放档案的数字化方面吸取了一些经验教训。该研究的结论是证明了在档案馆藏数字化方面制定战略的重要性。兹建议将这项研究扩大到东部和南部非洲的其他解放运动。此外，还建议对数字化解放档案的真实性进行研究。
{"title":"An Exploration of the Digitisation Strategies of the Liberation Archives of the African National Congress in South Africa","authors":"Sidney Netshakhuma, M. Ngoepe","doi":"10.1080/13614576.2019.1608571","DOIUrl":"https://doi.org/10.1080/13614576.2019.1608571","url":null,"abstract":"ABSTRACT Despite the availability of guidelines, standards, and software developed by national archives, professional associations, research groups and commercial organizations, digital records are still a challenge to manage, especially in Africa. A number of digitization projects undertaken by archival organizations in Africa failed to realize their goals of ensuring preservation and access of records. This is partially due to lack of strategies to migrate from analog to digital records. This study explored the strategies adopted by the African National Congress (ANC) in digitizing its liberation archives with the aim of capturing lessons learnt. Qualitative data were collected through interviews with purposively selected employees of the ANC, MultiChoice, Africa Media Online, and the Nelson Mandela Foundation as they were involved in the digitization project of the liberation archives. The results revealed that the ANC established an archives management committee to lead the implementation of digitization of the liberation archives. Furthermore, the ANC relied heavily on the companies MultiChoice and Africa Media Online, as its archivists were not trained for the digitization of archives. A number of lessons learnt with regard to the digitization of liberations archives are captured. The study concludes by demonstrating the importance of having a strategy in digitizing archival holdings. It is recommended that this study should be extended to other liberation movements in eastern and southern Africa. Furthermore, a study on determining the authenticity of digitized liberation archives is recommended.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"26 1","pages":"12 - 32"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60362669","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 : 2016-07-02DOI: 10.1080/13614576.2016.1257326
{"title":"EOV Ed board","authors":"","doi":"10.1080/13614576.2016.1257326","DOIUrl":"https://doi.org/10.1080/13614576.2016.1257326","url":null,"abstract":"","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":"21 1","pages":"ebi - ebi"},"PeriodicalIF":0.0,"publicationDate":"2016-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614576.2016.1257326","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60362105","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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