175 10 3575 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mingsiritham, Kemmanat Chanyawudhiwan, Gan Paiwithayasiritham, Chaiyos Date A point or period of time associated with an event in the lifecycle of the resource 2020-12-11 Description An account of the resource This research aimed to study factor analysis of smart social media technology to promote professional learning communities for teachers.   The sample included 900 teachers in basic education, selected by Simple   Random Sampling method. The sample group was divided for exploratory   factor analysis (EFA) and confirmatory factor analysis (CFA), 450 each. Research tool was a questionnaire with 5 levels of rating scale. Data were analyzed by exploratory factor analysis and confirmatory factor analysis. The results of the study revealed that: 1. Exploratory factor analysis of smart social media technology to promote professional learning communities for teachers consisted of 7 components: 1) professional learning communities for teacher, 2) cloud technology, 3) augmented reality, 4) internet of thing, 5) social  technology, 6) data analytics technology, and 7) mobile technology and 2. Confirmatory factor analysis of smart social media technology to promote  professional learning communities for teachers (SMPLC) found that the model was consistent with the empirical data ( =6.17, df=6, p=0.405). Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17253 10.3991/ijim.v14i20.17253 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17253/8371 Rights Information about rights held in and over the resource Copyright (c) 2020 kemmanat Mingsiritham, Gan Chanyawudhiwan, Chaiyos Paiwithayasiritham Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 20 (2020); pp. 165-173 1865-7923 Subject The topic of the resource Smart technology Social media Professional learning communities Title A name given to the resource Factor Analysis of Smart Social Media Technology to Promote Professional Learning Communities for Teachers Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Puttinaovarat, Supattra Sriklin, Teerawad Dangtia, Sompop Khaimook, Kanit Date A point or period of time associated with an event in the lifecycle of the resource 2020-12-11 Description An account of the resource Every flood causes damages to many lives and properties. Moreover, it affects the economy and lifestyle of people in the society in a short period and a long period. In consequence, this research would demonstrate techniques and flood detection analyzed through digital images and web application development for receiving reports and inspection of flood situation in every area. The process requires crowdsource data and uses 3S technology so it will receive the accurate and real-time data for making a decision in the flood management and aids to the people in the disastrous area. In this research, Convolutional neural network was applied for flood detection and classification using digital images and data from people or the victims. According to the study, it was found that convolutional neural network for flood classification has accuracy of data at the high level or 95.50%, 93.00%, 97.89%, and 0.91 which are the results of accuracy, producer accuracy, user accuracy, and kappa statistics, respectively. Besides, the use of this technique saves cost, time, and labors. Furthermore, the method could be applied to other disasters such as landslide, earthquake, and fire. It is able to monitor the incident in each type of disasters and also examines the damaged site after the incident. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17243 10.3991/ijim.v14i20.17243 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17243/8373 Rights Information about rights held in and over the resource Copyright (c) 2020 Supattra Puttinaovarat, Teerawad Sriklin, Sompop Dangtia, Kanit Khaimook Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 20 (2020); pp. 117-134 1865-7923 Subject The topic of the resource Flood Identification CNN Crowdsource Data GIS Title A name given to the resource Flood Disaster Identification and Decision Support System using Crowdsource Data Based on Convolutional Neural Network and 3S Technology Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Enaya, Yaser Ali Jawad Mohammed, Mohammed Bilal, Ghassan Abdulhussein Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource This study introduces a novel authentication methodology; it is based on pattern recognition of fingers size and pressure when users touch smartphone screen. By analyzing diagrams of these touches and applying data mining for the first time as an authentication technique, this paper presents three new approaches. First, an exact-range evaluation approach has been verified that size is more recognition consistency than pressure. Second, a pattern-range is a new technique reliance on size frequency position. At last, using a size-range has been facilitated the login. The association rules have been modified to work on finger touchscreen data files. To login, 94.1111% of 18 authorized users are succeeded and 98.9% of 20 unauthorized users are failed. Android device and Android studio are used. Size and pressure are normalized to 1; a training set is applied; the password is not considered. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17239 10.3991/ijim.v14i19.17239 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17239/8229 Rights Information about rights held in and over the resource Copyright (c) 2020 Yaser Ali Enaya, Yaser Ali Enaya, Mohammed jawad Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 163-179 1865-7923 Subject The topic of the resource data trace support factor confidence factor training set exact-range size-range pattern-range Title A name given to the resource Password-free Authentication for Smartphone Touchscreen Based on Finger Size Pattern Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Alotaibi, Reem Ali, Ahlam Alharthi, Haya Almehamdi, Renad Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource Chatbots have gained increasing importance in today research with a lot of available applications. They are flexible and can be applied in many application domains.  In tourism, Chatbots can recommend sights, hotels, activities, or even full travel plans. Usually, users are required to visit plenty of websites and install different Apps into their mobile phones in order to navigate the city and planning for the trip which is inconvenient and time-consuming. To address this issue, this paper proposes “Smart Guidance”, an AI text-based chatbot that is developed as a mobile application. It simulates a chat with users in a natural language, it also provides a two-way interaction and it is a single point of contact for all user communications. We provide a use case in the city of Jeddah, Saudi Arabia. Jeddah is the second largest city in Saudi Arabia and tourists have various choices when it comes to moving around the city. The final evaluation of the chatbot showed that the bot could understand meanings and users’ requests. Moreover, users found that the interaction is effective, and the responses are provided immediately. Users were satisfied and like the idea that they could express their needs in their natural language. Furthermore, users enjoyed the interaction and felt engaged. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17201 10.3991/ijim.v14i19.17201 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17201/8211 Rights Information about rights held in and over the resource Copyright (c) 2020 Reem Alotaibi, Ahlam Ali, Haya Alharthi, Renad Almehamdi Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 18-30 1865-7923 Subject The topic of the resource Tourism Chatbot Natural Language Processing Machine learning Jeddah Title A name given to the resource AI Chatbot for Tourist Recommendations: A Case Study in the City of Jeddah, Saudi Arabia Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Saleh Hussein, Ameer Salah Khairy, Rihab Mohamed Najeeb, Shaima Miqdad Alrikabi, Haider Th.Salim Date A point or period of time associated with an event in the lifecycle of the resource 2021-03-16 Description An account of the resource The global online communication channel made possible with the internet has increased credit card fraud leading to huge loss of monetary fund in their billions annually for consumers and financial institutions. The fraudsters constantly devise new strategy to perpetrate illegal transactions. As such, innovative detection systems in combating fraud are imperative to curb these losses. This paper presents the combination of multiple classifiers through stacking ensemble technique for credit card fraud detection. The fuzzy-rough nearest neighbor (FRNN) and sequential minimal optimization (SMO) are employed as base classifiers. Their combined prediction becomes data input for the meta-classifier, which is logistic regression (LR) resulting in a final predictive outcome for improved detection. Simulation results compared with seven other algorithms affirms that ensemble model can adequately detect credit card fraud with detection rates of 84.90% and 76.30%. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17173 10.3991/ijim.v15i05.17173 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17173/8827 Rights Information about rights held in and over the resource Copyright (c) 2021 Haider Th.Salim Alrikabi, Ameer Saleh Hussein, Rihab Salah Khairy Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 05 (2021); pp. 24-42 1865-7923 Subject The topic of the resource Fraud detection Credit card Ensemble technique Stacking Machine learning Title A name given to the resource Credit Card Fraud Detection Using Fuzzy Rough Nearest Neighbor and Sequential Minimal Optimization with Logistic Regression Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Fuada, Syifaul Rabbani, Raihan Fakhri Majid, Nuur Wachid Abdul Prasetiyo, Prasetiyo Muttaqin, Rahmat Adiono, Trio Islam, Shorful Date A point or period of time associated with an event in the lifecycle of the resource 2021-04-09 Description An account of the resource In this short paper, we prove that smartphones connected to Wi-Fi can be detected (scanned) easily with a Raspberry Pi help. According to the observation, the smartphone eventually broadcasts some packets of data containing MAC layers data. The period of broadcasting data depends on the smartphone’s state (active scanning/sleep). Besides MAC layers data, we also detect/capture other parameters, i.e., wireless signature data transmitted by smartphone (RSSI) and Time-stamp. The RSSI value measured in this test has a range from –30 dBm to –80 dBm. The result proves that different smartphones give different RSSI values (each smartphone emits different power strength). The RSSI value has more significant changes in a short-range (in this test result, 1 to 10 meters) and less significant change in a long-distance (above 20 meters). MAC address, time-stamp, and RSSI scanned/captured successfully through Raspberry Pi from the smartphones can be used as a reference for various purposes/applications in future work, such as Wi-Fi scanning/tracking system. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17169 10.3991/ijim.v15i07.17169 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17169/9075 Rights Information about rights held in and over the resource Copyright (c) 2021 Syifaul Fuada, Raihan Fakhri Rabbani, Nuur Wachid Abdul Majid Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 07 (2021); pp. 176-184 1865-7923 Subject The topic of the resource MAC layer data Time-stamp RSSI Smartphone Wi-Fi tracking system Title A name given to the resource Your MAC Address Can be Detected Easily When Your Smartphone Connected to the Wi-Fi Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mingsiritham, Kemmanat Koraneekij, Prakob Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource The purpose of this research was to study the using results of OER mobile application to enhance 21st century skills in information media and technology skills for humanities and social sciences learners. The sample included 33 students who studied in an autonomous university in the Humanities and Social Sciences field. Research instruments consisted of self-assessment form before and after studying, behavior observation form, and assignment evaluation form. Data were analyzed by using mean, standard deviation, dependent t-test, and one way repeated measure.The results showed that information, media and technology skills had average scores after studying higher than before studying with statistical significance at the level of .05 (t = 17.382, p = .000). Students had learning behavior with OER mobile application at very high level (M = 4.52, SD = .26). The analysis of one way repeated measure of assignment evaluation in each period (week 2, week 4, week 6) showed statistically significant at the .05 level. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17105 10.3991/ijim.v14i19.17105 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17105/8233 Rights Information about rights held in and over the resource Copyright (c) 2020 kemmanat Mingsiritham, Prakob Koraneekij Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 197-203 1865-7923 Subject The topic of the resource Application Open Smart Classroom Open learning Information Media and Technology skills Title A name given to the resource The Using Results of OER Mobile Application to Enhance 21st Century Skills in Information Media and Technology Skills for Humanities and Social Sciences Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Wohllebe, Atilla Ross, Florian Podruzsik, Szilárd Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-24 Description An account of the resource Mobile apps have become massively more important in the retail sector in recent years. A central challenge for retailers is the acquisition of new users for their mobile apps. A potentially interesting target group for this can be a company's existing, satisfied customer base, whereby customer satisfaction is often measured by the willingness to recommend the app or the Net Promoter Score. This paper investigates the influence of the willingness to recommend a retailer by consumers on their willingness to install a mobile app from this retailer. The influence of usage habits is also examined. The analysis of a survey of 105 consumers on a total of five retailers can confirm the hypotheses regarding the willingness to recommend a retailer and the Net Promoter Score (NPS) in particular: With the willingness to recommend, the willingness to install a retailer's app also increases. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17027 10.3991/ijim.v14i19.17027 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17027/8225 Rights Information about rights held in and over the resource Copyright (c) 2020 Atilla Wohllebe Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 19 (2020); pp. 124-139 1865-7923 Subject The topic of the resource Mobile App Net Promoter Score Smartphone App Likelihood To Recommend Title A name given to the resource Influence of the Net Promoter Score of Retailers on the Willingness of Consumers to Install Their Mobile App Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource AlKhunzain, Abdulmohsin Suliman Khan, Raja Muhammad Ishtiaq Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-26 Description An account of the resource The life of the common to the students have changed due to spread of COVID-19 9 all around the globe. All the educational institutions were also set to be functioned remotely following the global instructions to meet the challenges to combat the COVID-19. The of current inquiry is the explore the male and female learners on the use of mobile phones for Blackboard learn. The Study survey method to collect the data. 68 participants of the medical majors of the CFY formed the sample for the present study. The findings of the study indicate that learners preferred to use M-blackboard. The results also indicated that backboard which is a form of e-learning can be beneficial if it is used with the traditional classroom teaching to get the potential benefits of the software. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/17003 10.3991/ijim.v15i02.17003 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/17003/8633 Rights Information about rights held in and over the resource Copyright (c) 2021 Abdulmohsin Suliman Alkhunzain Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 02 (2021); pp. 4-17 1865-7923 Subject The topic of the resource Blackboard M-learning Perceptions E-learning Title A name given to the resource The Use of M-Learning: A Perspective of Learners’ Perceptions on M-Blackboard Learn Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Gadebe, Moses Lesiba Kogeda, Okuthe Paul Date A point or period of time associated with an event in the lifecycle of the resource 2020-11-10 Description An account of the resource The availability of Smartphones has increased the possibility of self-monitoring to increase physical activity and behavior change to prevent obesity. However self-monitoring on a Smartphtone comes with some challenges such as unavailability of lightweight classification algorithm, personalized dataset to completely capture bodily postures, subject sensitivity, limited storage and computational power. However, most classification algorithms such as Support Vector Machines, C4.5, Naïve Bayes and K Neighbor relies on larger dataset to accurately predict human activities. In this paper, we present top-k of compressed small personalized dataset to reduce computational cost with increased accuracy. We collected top-k personalized dataset from 13 recruited subjects. After benchmarking our collected dataset we found that the dataset is suitable for tree-oriented algorithm, especially the Random Forest, C4.5 and Boosted tree with accuracy and precision of 100% except for KNN, Support Vector and Naïve Bayes. Further, our top-k personalized dataset improves pruning and overfitting of tree-oriented algorithms. Moreover, the linear consistence of static human activities reveals the potential of our top-k dataset to be replicated to multiple-subject to close subject sensitivity challenge. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/16965 10.3991/ijim.v14i18.16965 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/16965/8129 Rights Information about rights held in and over the resource Copyright (c) 2020 Moses Lesiba Gadebe, Okuthe Paul Kogeda Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 18 (2020); pp. 68-86 1865-7923 Subject The topic of the resource top-k personalized dataset gravimeter filtering technique tree oriented Title A name given to the resource Top-K Human Activity Recognition Dataset Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article