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Research ArticleOpen accessIn the abstractThe Use of Real Options Methodology to Pasturelands EvaluationA. Michailidis, F. Chatzitheodoridis, I. Mountousis, K. PapanikolaouThis study demonstrates the utility of the real options approach to pasturelands investment analysis. The main objectives are to discuss the real options theory and show how it can be adopted to model uncertainty and managerial flexibility in pasture management (enlargement plan) and investment. Secondly, we show how to calculate the option values of selected options that may be available … …American Journal of Applied Sciences, Vol. 3, Issue 8 · 31 Aug 2006 · 6,763 accessesView PDFCite
Research ArticleOpen accessIn the abstractFormation of Vegetation Cover and Soil Quality Indicators at the Mine Sites of a Gold-Bearing Deposit (the Case of Kara-Agash, Kazakhstan)Vadim Chashkov, Aliya Bugubaeva et al.At present, the processes of natural recovery, vegetation coverage, and degraded lands of several coal, iron ore, uranium, and polymetallic mines and gold-bearing deposits are well-studied. The present study aims to identify opportunities to shape the soil layer and vegetation cover on reclaimed dumps/tailings of industrial waste and degraded land via artificial restoration. For this purpose, in July 2023, studies … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 16 Sep 2024 · 4,765 accessesView PDFCite
Research ArticleOpen accessIn the abstractIn vitro Kinematics Semen Tolerance to Oxidative StressCyril Mpho PilaneInterpretation of semen kinematic parameters remain as a point of discussion in predicting semen quality following processes like cryopreservation. During cryopreservation, oxidative stress remains a challenge in promoting post-thaw semen quality. Comparison of livestock semen exposed to oxidative stress, in vitro, highlight various aspects of sperm cell movement, like kinematics, to predict their qualities. Sperm cell kinematics includes the measurement … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 3 · 13 Sep 2024 · 4,560 accessesView PDFCite
Review ArticleOpen accessIn the abstractData Mining the Adoption Trends: A Bibliometric Analysis of Online Learning in Higher Education (2000-2023)Nirmaljeet Kaur Virk, Syed Ahmed Salman, Amiya BhaumikOver the past two decades, online learning in higher education has developed dramatically, becoming a widespread phenomenon significantly influencing teaching and learning strategies. To further encourage its development, monitoring the research frontiers and gaining insights into the progress of related research is crucial. In this pursuit, the present research used VOS viewer to conduct a bibliometric study on the 661 … …Journal of Computer Science, Vol. 20, Issue 12 · 24 Oct 2024 · 4,836 accessesView PDFCite
Research ArticleOpen accessIn the abstractSales Forecasting Models: Comparison between ARIMA, LSTM and ProphetDmitry BrykinSales forecasting is crucial for business planning and resource allocation. Data-driven approaches have become popular in this field. This study compares the performance of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Prophet within the context of specific sales categories derived from acquiring data provided by a bank. This study uses a time series dataset … …Journal of Computer Science, Vol. 20, Issue 10 · 1 Aug 2024 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the abstractInnovations in Access to Justice in Uganda: Justice Users’ LensKakuru Timothy, Ssendikaddiwa Emmanuel, Kennedy Kasozi et al.Access to justice remains a global challenge and in Uganda, four in ten people have at least one legal problem every four years, yet seven in ten of the legal problems are not resolved. While innovation is critical to changing the status quo, most innovations have been mostly informed by what legislators and legal practitioners need to do their jobs … …Journal of Social Sciences, Vol. 20, Issue 1 · 29 Jul 2024 · 6,735 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Plant Disease Detection Using Graph Isomorphic Networks: Enhancing Crop Yield Through Leaf AnalysisD. Sumathi, Sreejyothsna Ankam, Pravin Prakash Adivarekar et al.The economy of Tanzania is mostly driven by agriculture. Disease is one of the reasons that contributes to the low production of staple foods like cassava and maize, alongside climate change. Loss of income and food security are the results. In order to detect the diseases early, preventative measures are required. A potential option for farmers could be the use … …Journal of Computer Science, Vol. 21, Issue 9 · 15 Oct 2025 · 3,101 accessesView PDFCite
Research ArticleOpen accessIn the abstractSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnxiety-Focused Classification Using Smartphone-Based Gait Analysis and Deep Learning ModelsMinchan Kang, Gou-Sung Degbey, Hyunhwa Lee et al.Mood disorders, such as anxiety, significantly impact individual well-being and present challenges to healthcare systems globally. Traditional screening methods, including self-administered symptom questionnaires, provide valuable insights into symptoms but may miss dynamic fluctuations. This study explores the potential of smartphone inertial sensors and deep learning models for anxiety risk classification. Using gait data from 36 participants, collected via smartphone accelerometers … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 821 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite