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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Jabbar, Mays Kareem</text>
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                <text>Trabelsi, Hafedh</text>
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                <text>The Vehicular Ad-hoc Network (VANET) represents a new future for dynamic information dissemination between societies. VANET has a wide range of applications in a variety of aspects, including Intelligent Transportation Systems (ITS). VANET has some characteristics, like highly dynamic topology and intermittent connections. These characteristics lead to untrustworthy information transmission in VANET. Vehicle clustering is an efficient approach to improve the scalability of the network and connection reliability. The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms. The most notable clustering algorithms introduced between 1999 and 2021 are reviewed. A complete survey on clustering in VANETs is provided based upon the clustering process. The clustering process in most algorithms is explored in the aspects of CH selection metrics, cluster formation, and cluster maintenance. The clustering techniques based on some parameters like stability, convergence, overhead, and latency are compared. Some of the most common problems, as well as the approaches employed to solve them, are also discussed. Also, the performance parameters which evaluate the clustering approaches are summarized.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29973</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29973/11343</text>
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                <text>Copyright (c) 2022 mays kareem jabbar, Hafedh  Trabelsi</text>
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                <text>https://creativecommons.org/licenses/by/4.0</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 25-48</text>
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                <text>1865-7923</text>
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                <text>VANET, Clustering Algorithms, Performance Parameters</text>
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                <text>Clustering Review in Vehicular Ad hoc Networks:  Algorithms, Comparisons, Challenges and Solutions</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Echoukairi, Hassan</text>
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                <text>Idrissi, Abdellah</text>
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                <text>Omary, Fouzia</text>
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                <text>The operation time of LEACH protocol is divided into several frames. Each frame consists of a number of equal time slots where the selection of cluster heads and the re-establishment of clusters are periodic. Each member of the cluster exploits its own time slot to transmit the data, then it turns off its radio to reduce energy consumption. Here, the clusters generated are not uniformly distributed and the time slots of the dead member nodes are not allocated. We propose an improved version, which is based simultaneously on the integration of the clustering approach K-Means and the exploitation of the free time slot in favor of cluster head in the transmission phase. The results show that the proposed protocol allowed us to achieve increased throughput, improved reliability of the packet delivery ratio, low routing load and an effective reduction in energy consumption for low node density in WSNs.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29863</text>
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                <text>10.3991/ijim.v16i08.29863</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29863/11179</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="48022">
                <text>Copyright (c) 2022 Hassan ECHOUKAIRI, Pr A.Idrissi, Pr F.Omary</text>
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                <text>https://creativecommons.org/licenses/by/4.0</text>
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              <elementText elementTextId="48024">
                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 08 (2022); pp. 165-181</text>
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              <elementText elementTextId="48025">
                <text>1865-7923</text>
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            <description>The topic of the resource</description>
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              <elementText elementTextId="48026">
                <text>wireless sensor networks</text>
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                <text>hierarchical protocols</text>
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                <text>leach</text>
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                <text>k-means</text>
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                <text>throughput</text>
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            <name>Title</name>
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              <elementText elementTextId="48034">
                <text>New Hierarchical Routing Protocol Based on K-Means Clustering with Exploiting Free Time Slot for Wireless Sensor Networks</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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              <elementText elementTextId="47992">
                <text>Hussein, Karim Qassim</text>
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                <text>Al-Bayati, Maha A.</text>
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                <text>This research aims at developing an e- spelling system supported by effective multimedia technique of sign language and finger spelling. However the aimed system should enhance the hearing disability for the Deaf student so he can enter his desired paragraph then the spelling process&amp;nbsp; could be accomplished in two stages, the fist stage&amp;nbsp; is the word spelling which translates each word into the corresponding sign language video clip (MPEG video cut). Then stopping message appears asking the Deaf student to move to the second&amp;nbsp; stage of translating. The second stage is the letter spelling which translates the current translated word (in sign language) into finger spelling letter by letter in sequence. Both stages of spelling are controlled by the Deaf student. After completing translation of that word into alphabets finger spelling, the next word would &amp;nbsp;be translated into the corresponding sign language video clip. Real run-out forms (8 screens) have been displayed to describe the tracing process of translating and spelling via this e-spelling system. The system has been showed/tried by some experts to get the valuable feedback from them. As final result it is expected that Deaf students can improve their skills in English reading when they practice, drill and repeat the translating and spelling process of various English sentences and words. One hand ASL (American Sign Language) alphabets are used for letter spelling and Indian Sign Language Dictionary is used for word spelling. Visual programming coding source and its multimedia control components/techniques with database have been used in developing this system</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29831</text>
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                <text>10.3991/ijim.v16i10.29831</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29831/11347</text>
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                <text>Copyright (c) 2022 Karim Qassim Hussein</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 67-78</text>
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                <text>1865-7923</text>
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                <text>e-Learning Modules  , Deaf    , ASL one-hand American alphabets finger spelling., sign Language , Reading Skills ,visual multimedia</text>
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                <text>Multi-Mode e-Learning System of Reading Skills for Deaf Students Based on Visual Multimedia</text>
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              <elementText elementTextId="47968">
                <text>Cabanillas-Carbonell, Michael</text>
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                <text>Paucarcaja-Ochoa , Harold</text>
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                <text>Martos-Olazabal , Jhanery</text>
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                <text>The pandemic is currently forcing several countries to take certain restrictions on public transportation to prevent the spread of the virus, Peru is in the aforementioned phase, so many users who continue to use public transportation on a daily basis to get to work, home, supermarkets, among other activities, must stay informed to comply with these requirements. In this context, the mobile application was developed to help the proper management of information of the sanitary measures of the Covid-19 in the area of public transport for the city of Lima, and this is compatible with Android and iOS; likewise, the Mobile-D methodology, helped to make such mobile application and to know the phases to proceed with the implementation, which has an impact on time, information management and user satisfaction. The results of the present document show that the level of user satisfaction increased to 67.5% of a sample of 200 people as the experimental group. It was concluded that the application made it possible to automate the management of information on Covid-19 sanitary measures in the field of public transportation.</text>
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                <text>1865-7923</text>
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            <description>Information about rights held in and over the resource</description>
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                <text>Copyright (c) 2022 Dr. Binar Kurnia Prahani, M.Pd., Mohd Zaidi Bin Amiruddin, Prof. Dr. Budi Jatmiko, M.Pd., Assoc. Prof. Nadi Suprapto, Ph.D., Tan Amelia, S.Kom., M.MT.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 08 (2022); pp. 18-33</text>
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                <text>1865-7923</text>
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                <text>Bibliometric</text>
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                <text>Reno Renaldi</text>
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                <text>In order to to support physical distancing activities in the teaching and learning process during the Covid-19 pandemic, an appropriate and effective learning model to fit the learning objectives must be developed. The CBE (Contextual Based on E-learning) learning model, developed from the Contextual Teaching Learning (CTL) model, was integrated with e-learning. This CTL learning model was chosen because this model is an innovative learning model where the process can assist students to connect learning with the context of their lives. This study aims to describe the model's effectiveness which was measured based on three aspects, namely: a) significant difference between students’ achievement in CBE model compared to that in traditional model; b) The effectiveness of CBE syntax in learning; c) Students’ perception on the new CBE model. This study is quantitative research with quasi experimental method. The results of the CBE model showed that the CBE model is significantly effective in improving students' abilities. Therefore, it can be concluded that the CBE model is proven to be effective to be implemented as new teaching model in online learning. The implication of this research is to contribute to new existing knowledge for education, and computer science and to add references to new online-based models. The limitation of this research is the effectiveness of this model  described the cognitive knowledge trough students’ learning outcomes.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29787</text>
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                <text>Copyright (c) 2022 Reno Renaldi, Aldiga Rienarti Abidin, Yuda Irawan, Abdurrahman Hamid, Rizky Ema Wulansari</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 11 (2022); pp. 39-50</text>
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                <text>1865-7923</text>
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                <text>Contextual Learning</text>
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                <text>Contextual Based E-learning (CBE): A New Model for Online Teaching in Public Health Department for Learning During the Covid-19 Pandemic</text>
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                <text>Herrera Salazar, José Luis</text>
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                <text>Fruit consumption is related to the enjoyment of good health and the reduction of the occurrence of diseases such as obesity. At present, in the markets the process of determining the state of maturity of fruits is carried out by employees using only their criteria, since this method is very broad and tedious when carried out, for this the present investigation was developed, in improving the process of determining the state of maturity of fruits. The article exposes the development of a mobile application with Arduino, based on Scrum, to improve the determination of the state of maturity of fruits in markets.&amp;nbsp; Resorting to the use of pure experimental design with a sample of 30 data for each indicator. The results indicate that the margin of error when determining the resistances of the fruit with the application with respect to the multimeter was 4.73 percent and in determining the color of the fruit with respect to the sensor was 6.09 percent. It was concluded that the prototype fulfills its function of determining the state of maturity of the fruit by means of these 2 sensors implemented in the Arduino, having a minimum margin of error.</text>
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                <text>Copyright (c) 2022 Victor Cespedes-Lluque, Miguel Yucra-Calla, Michael Cabanillas-Carbonell, José Luis Herrera Salazar</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 14 (2022); pp. 63-77</text>
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                <text>1865-7923</text>
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                <text>Copyright (c) 2022 Anton Komaini</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 05 (2022); pp. 207-215</text>
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                <text>1865-7923</text>
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              <elementText elementTextId="47855">
                <text>Copyright (c) 2022 Michael Cabanillas-Carbonell, Piero Cusi-Ruiz, Daniela Prudencio-Galvez, José Luis Herrera Salazar</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 11 (2022); pp. 51-64</text>
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                <text>1865-7923</text>
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                <text>Akintola, Abimbola Ganiyat</text>
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                <text>Balogun, Abdullateef</text>
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                <text>Usman-Hamza, Fatima</text>
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                <text>Due to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for identifying and categorising malware apps was created. Conventional ML methods are concerned with increasing classification accuracy. However, the standard classification method performs poorly in recognising malware applications due to the unbalanced real-world datasets. In this study, an empirical analysis of the detection performance of ML methods in the presence of class imbalance is conducted. Specifically, eleven (11) ML methods with diverse computational complexities were investigated. Also, a synthetic minority oversampling technique (SMOTE) and random undersampling (RUS) are deployed to address the class imbalance in the Android malware datasets. The experimented ML methods are tested using the Malgenome and Drebin Android malware datasets that contain features gathered from both static and dynamic malware approaches. According to the experimental findings, the performance of each experimented ML method varies across the datasets. Moreover, the presence of class imbalance deteriorated the performance of the ML methods as their performances were amplified with the deployment of data sampling methods (SMOTE and RUS) used to alleviate the class imbalance problem. Besides, ML models with SMOTE technique are superior to other experimented methods. It is therefore recommended to address the inherent class imbalance problem in Android Malware detection.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/29687</text>
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              <elementText elementTextId="47831">
                <text>Copyright (c) 2022 Abdullateef Balogun, Abimbola Ganiyat Akintola, Hammed Adeleke Mojeed, Fatima Usman-Hamza, Shakirat Aderonke Salihu, Ghaniyyat Bolanale Balogun, Peter Ogirima Sadiku, Kayode Sakariyau  Adewole</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 140-162</text>
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                <text>1865-7923</text>
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                <text>Android</text>
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                <text>Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection</text>
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