iosr-JCE   Volume-25 ~ Issue-6 ~ Nov. - Dec. 2023

Abstract: With the rapid advancement from the hardware age to the software age and now to the internet age, we find ourselves in a pivotal era where everyone is connected to internet the inter-relationships of data hold immense significance. In today's landscape, Education - one of the pillars of growth for human civilization has become accessible to one and all. Now days every person got equal opportunities to learn about something new from internet. This platform of internet has become the largest library for knowledge in today's world. With advancement of time we had also seen growth in new industries related to Internet + Education, these new ways to teach and learn had pave the way for many who have difficulty for finding the right system and path to learn and get a chance to move forward in their life.

Key Word: Smart search and sorting, Platform based interaction, Security mechanism , Content provider

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Abstract: Background: Advances in information and communications technology have aided government agencies at all levels in expanding and improving their ability to provide citizens with information and services online. E-services have the potential to benefit both governments and citizens by lowering service costs while increasing service accessibility. The objective of this study was to determine how e-Government initiatives contribute to Good Governance among Public Sector Organizations in Developing Countries. The specific areas under focus were; efficiency and Effectiveness, transparency and accountability and consistency with the rule of law. The study was anchored.....

Key Word: Accountability, e-Government, Good Governance, Efficiency, Effectiveness Rule of Law,

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Abstract: By introducing new methods of teaching and learning, the Internet of Things (IoT) has the potential to change the educational sector. By giving students real-time data and individualized learning opportunities, Internet of Things can improve the educational experience. Internet of Things system implementation in education, however, is fraught with difficulties related to cost, security, and privacy. The purpose of this research study is to examine Internet of Things applications in education and the difficulties in putting Internet of Things systems into practice. A literature review and a technique involving interviews with technology specialists and educators will both be part of the study. The results of the study will offer perceptions into the possible advantages of putting Internet of Things technologies in education and offer suggestions for resolving the difficulties

[1]. Abuhelaleh, M., Al-Ayyoub, M., Al-Betar, M. A., Alwesabie, A., & Al-Betar, M. A. (2017). Internet Of Things Applications: A Systematic Review. Journal Of Network And Computer Applications, 97, 23-32.
[2]. Agrawal, M., & Yadav, H. (2020). Impact Of Internet Of Things On Education And Its Future Prospects. International Journal Of Scientific & Technology Research, 9(1), 1-5.
[3]. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet Of Things: A Survey On Enabling Technologies, Protocols, And Applications. IEEE Communications Surveys & Tutorials, 17(4), 2347-2376.
[4]. Chen, N., Liu, X., &Xie, H. (2019). Applications Of The Internet Of Things (Internet Of Things) In Education: A Review. Journal Of Educational Technology Development And Exchange, 12(1), 1-17.
[5]. Gosavi, R., & Jadhav, V. (2017). Internet Of Things In Education: A Review Of The Literature. In Proceedings Of The 2017 3rd International Conference On Computing For Sustainable Global Development (Indiacom) (Pp. 694-698).

Abstract: The subject of activity recognition by humans or anyone has undergone a revolution because of recent advances in deep learning, which enable models to learn intricate representations and hierarchies from unprocessed data, improving recognition accuracy. Because they require a lot of feature engineering and data preparation, the traditional way by many machine learning techniques like the support vector machines models (SVM) and histogram of gradients (HOG) with k-nearest neighbor classifiers have lost some of their appeal. In order to increase the robustness and predictive accuracy of human activity recognition from raw image data, this research focuses on developing an efficient and robust model by utilizing the strengths of convolutional neural networks (CNN), Vgg16, Inception model, and......

Keywords: HOG, Deep Learning, VGG16, ResNet50, Inception, Xception and HAR

[1]. Al-Qaness MA, Helmi AM, Dahou A, Elaziz MA. The Applications Of Metaheuristics For Human Activity Recognition And Fall Detection Using Wearable Sensors: A Comprehensive Analysis. Biosensors. 2022 Oct 3;12(10):821.
[2]. Lara OD, Labrador MA. A Survey On Human Activity Recognition Using Wearable Sensors. IEEE Communications Surveys & Tutorials. 2012 Nov 29;15(3):1192-209
[3]. Ranieri, Caetano Mazzoni, Scott Macleod, Mauro Dragone, Patricia Amancio Vargas, And Roseli Aparecida Francelin Romero. "Activity Recognition For Ambient Assisted Living With Videos, Inertial Units And Ambient Sensors." Sensors 21, No. 3 (2021): 768.
[4]. Moshiri PF, Shahbazian R, Nabati M, Ghorashi SA. A CSI-Based Human Activity Recognition Using Deep Learning. Sensors. 2021 Oct 30;21(21):7225.
[5]. Anguita D, Ghio A, Oneto L, Parra X, Reyes-Ortiz JL. A Public Domain Dataset For Human Activity Recognition Using Smartphones. Inesann 2013 Apr 24 (Vol. 3, P. 3)

Abstract: Background: This study carried out in the city of Douala aims to assess the impact of the effluent of the Cameroonian Soap Manufacturing Company (CCC) on the zooplankton communities of the main tributary of the Mgoua watercourse in order to establish strategies for the sustainable management of aquatic ecosystems in Cameroon. Materials and Methods: Sampling for physicochemical and biological analysis was done on monthly basis from March to July 2013 at 2 stations (MG1 and MG2) respectively located upstream and downstream of the point of discharge of the effluent into the watercourse. Two samples of the raw effluent were also collected in April and July 2013. All the samples were taken to the Hydrobiology and Environment Laboratory of the University of Yaounde I for analysis......

Keywords:Tributary of MGOUA, zooplankton communities, CCC effluent, physicochemical, Douala.

[1]. Fofana M N, N’doua Etile R, Goore Bi G. Répartition Saisonnière Du Zooplancton En Relation Avec Les Caractéristiques Environnementales Dans Le Lac Kaby (Bongouanou, Côte D’ivoire). Journal Des Biosciences Appliquées. 2019 ; 140 : 14245-14255.
[2]. Nzieleu Tchapgnouo J G, Njiné T, Zébazé Togouet S H, Djutso Segnou S C, Et Al. Diversité Spécifique Et Abondance Des Communautés De Copépodes, Cladocères Et Rotifères Des Lacs Du Complexe Ossa (Dizangué, Cameroun). Physio-Géo. 2012 ; 6 : 71-93.
[3]. Kengni L, Tematio P, Filali Rharrassi, Tepoule Ngueke J, Tsafack E I, Mboumi T L, Mounier S. Pollution Des Eaux Superficielles Et Des Nappes En Milieu Urbain : Cas De La Zone Industielle De Douala-Bassa (Cameroun). International Journal Of Biological And Chemical Sciences. 2012; 6(4): 1838-1853.
[4]. Onana Fils M, Zébazé Togouet S H, Dassié B S, Nna S Et Al. Impact De L’effluent Du Complexe Chimique Cameounais (CCC) Sur La Structure Et Le Peuplement Des Macroinvertébrés Benthiques D’un Cours d’Eau Tropical Urbain (Douala, Cameroun). European Journal Of Scientific Research. 2014 ; 121(3) : 298-390.
[5]. Zambou Sogboum D. Rôle De L’évaluation Environnementale Dans L’aménagement Urbain, Cas De La Périphérie Est De Douala. Les Correspondants Du Sifée. Novembre 2020

Abstract: One-class classification (OCC) is a special kind of classification problem in machine learning in which during training only the data points of one class is present. It has applications in many domains as it is difficult to collect the data of abnormal class. Many OCC algorithms have been proposed. In this paper, we will discuss many OCC algorithms. We will also discuss the performance measures used for OCC algorithms. Application domains of OCC algorithms will also be discussed.

Keywords:OCC algorithms; Performance measures; Binary classification

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Abstract: The study examined upper primary school science teachers' curriculum knowledge, attitude, and their classroom instructional practices in the implementation of the Standards-Based curriculum in the Krachi-East Municipality in the Oti Region of Ghana. A mixed method concurrent triangulation research design was used for the study. A total of 251 upper primary school Science teachers were purposively selected from different schools to participate in the study. Convenient sampling was used to select 10 participants for qualitative phase. Data were collected through a survey questionnaire, classroom observation guide and a semi structured interview guide. The descriptive....

Keywords: Curriculum knowledge, implementation, Standard-Based Curriculum classroom Instructional Practice

[1]. Adu, E. O. & Ngibe, N. C. P (2014). Continuous Change In Curriculum: South African Teachers' Perceptions. Mediterranean Journal Of Social Sciences (MJSS), 5, 23, 983-989.
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Abstract: Detecting toxic speech is a valuable tool for addressing the proliferation of harmful content, particularly on social media platforms. Many methods, including recent deep learning-based approaches, have been developed for this task. Various datasets have also been created to illustrate different aspects of the toxic speech detection problem. In this study, we conduct a comprehensive empirical comparison of deep and shallow toxic speech detection methods using three commonly utilized datasets. Our primary aim is to offer insights into the field's progress and highlight both strengths and weaknesses of current state-of-the-art techniques. Our analysis focuses on practical performance metrics such as detection accuracy, computational efficiency, the capability to utilize pre-trained models, and domain adaptability. Through this research, we aim to provide practical guidance for toxic speech detection applications, assess the current state-of-the-art, and pinpoint potential avenues for future research.

Key Word: Toxic, deep-learning, detection accuracy, computational efficiency

[1]. d'Sa, A. G., Illina, I., & Fohr, D. (2019). Towards Non-Toxic Landscapes: Automatic Toxic Comment Detection Using DNN. Arxiv Preprint Arxiv:1911.08395.
[2]. Abderrouaf, C., & Oussalah, M. (2019, December). On Online Hate Speech Detection. Effects Of Negated Data Construction. In 2019 IEEE International Conference On Big Data (Big Data) (Pp. 5595-5602). IEEE.
[3]. Arango, A., Pérez, J., & Poblete, B. (2019, July). Hate Speech Detection Is Not As Easy As You May Think: A Closer Look At Model Validation. In Proceedings Of The 42nd International Acm Sigir Conference On Research And Development In Information Retrieval (Pp. 45-54).
[4]. Nguyen, L. T., Van Nguyen, K., & Nguyen, N. L. T. (2021). Constructive And Toxic Speech Detection For Open-Domain Social Media Comments In Vietnamese. In Advances And Trends In Artificial Intelligence. Artificial Intelligence Practices: 34th International Conference On Industrial, Engineering And Other Applications Of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26–29, 2021, Proceedings, Part I 34 (Pp. 572-583). Springer International Publishing.
[5]. Wei, B., Li, J., Gupta, A., Umair, H., Vovor, A., & Durzynski, N. (2021). Offensive Language And Hate Speech Detection With Deep Learning And Transfer Learning. Arxiv Preprint Arxiv:2108.03305

Abstract: The global demand for Green Hydrogen is expected to reach 130 MT by 2030. Green Hydrogen is steadily emerging as an alternative energy source because it generates high enthalpy required for powering energy-intensive industrial processes, without emitting greenhouse gasses. Green hydrogen has the enormous potential to decarbonize heavy industries. This paper aims to understand the ecosystem of Green Hydrogen, the challenges around it, the ideas and technological innovations related to it, and how it can emerge as a leading technology to drive the world to a net-zero carbon status and aid in decarbonization while reducing demands of fossil fuels from various sectors

Key Word: Green Hydrogen, Renewable energy source, Decarbonization, Net-zero status

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Abstract: Sorting is a method of arranging the elements in an order. There are different sorting algorithms available to sort the elements. In this article bubble sort, selection sort and merge sort algorithm is explained. The working process, the algorithm, and the C program version of these 3 sorting techniques are explained. Bubble sort technique sorts the elements by comparing each pair of adjacent elements from left to right. Swapping of elements is done if the elements are not in order. Selection......

Key Word: Sorting, C Program for Bubble sort, C Program for Selection sort, C Program for Merge sort, Algorithm for Bubble sort, Algorithm for Selection sort, Algorithm for Merge sort

[1]. Srikanth S. Data Structures Using C, Skyward Publishers , 2021
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Abstract: Android, being an open source operating system, offers a compr ehensive understanding of its architecture. To build mobile devices (smartphones, smartwatches, and smart glasses) under various brand names, including as Google Pixel, Motorola, Samsung, and Sony, numerous manufacturers are using this OS. This widespread adoption has significantly increased the Android user base. However, some unscrupulous individuals develop malware for personal gain, recognition, or other nefarious purposes. To combat Android malware, researchers have proposed different techniques. Among these techniques, ML based methods that utilize static features of apps as input vectors have demonstrated clear advantages in terms of code coverage, operational efficiency, and the ability to detect a large number of samples. In this study, we examined.....

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