Search

This review article explores the transformative impact of AI and IoT in livestock management, highlighting their pivotal role in advancing Agriculture 4.0. It delves into various technologies such as robotics, nanotechnology, and gene editing, which are reshaping farming and food systems towards sustainability. The paper emphasizes the significance of digital phenotyping in poultry, particularly in enhancing productivity, animal welfare, and sustainability through innovative genomics research and health monitoring platforms. Additionally, it examines the evolution of e-agriculture in India, focusing on government initiatives and the increasing influence of mobile technology in farming. The role of Big Data in Smart Farming is also scrutinized, revealing its extensive impact beyond primary production and its potential in reshaping supply chain dynamics and business models. The review further assesses the contributions of IoT in agricultural systems, particularly in meeting the challenges of a rapidly growing global population. Through this comprehensive analysis, the paper underscores the necessity for ongoing research and development in these areas, recognizing the potential challenges and opportunities presented by these robust, sustainable, and in creating a more technologically advanced agricultural future.

This review article titled “Revolutionizing Agriculture: The Impact of AI and IoT” delves into the transformative role of Artificial Intelligence (AI) and the Internet of Things (IoT) in modern agriculture. It encapsulates the burgeoning wave of digitalization and its implications for data-driven farming practices. The paper comprehensively reviews the advancements in digital agriculture management, highlighting the integration of AI, IoT devices, machine learning, and sensor technology in enhancing farming efficiency and productivity. Emphasis is placed on the use of robotics, drones for crop monitoring, and smart irrigation systems, which leverage real-time data for optimized agricultural operations. The role of high-speed 5G networks in enabling these smart farming solutions is also discussed, particularly their impact on data transmission and connectivity in rural settings. Challenges and opportunities in implementing Smart Decision Support Systems (SDSS) in developing countries are explored, focusing on real-time soil analysis and decision-making aids for farmers. The review further discusses a proposed cloud-based system for remote farm monitoring, employing AI-based models for efficient data processing and improving farming practices. This article aims to provide a nuanced understanding of the current and future potential of AI and IoT in reshaping agricultural practices, addressing global food security challenges, and supporting sustainable development.

Electrical power systems usually suffer from instabilities because of some disturbances occurring due to environmental conditions, system failures, and loading conditions. The most frequently encountered problem is the loss of synchronization between the rotor angle and the stator magnetic angle for synchronous generators. The contribution of this study is that a nonlinear adaptive control approach called feedback error learning (FEL) is utilized to improve the small-signal stabilities of an electric power system. The power system under study is composed of a synchronous machine connected to infinite bus. Many advantages of FEL control approach makes it capable to robustly adapting with all possible operating conditions rather than using optimization algorithms for tuning the conventional power system stabilizer (CPSS) that is still unsatisfactory especially at some critical operating points. The performances of two controllers, namely the proposed FEL scheme and the conventional controller CPSS, are tested by Matlab simulations. It is found that the FEL controller can be effectively used as an alternative stabilizer for improving small-signal stabilities of the power

Background Both drug‐coated balloon (DCB) angioplasty and conventional plain balloon angioplasty (PBA) can be implemented to treat hemodialysis dysfunction. The present study aims to compare the safety and efficacy of these 2 approaches by conducting a meta‐analysis of available randomized controlled trials. Methods and Results PubMed, Cochrane Library, and Embase databases were queried from establishment to January 2021. A total of 18 randomized controlled trials including 877 and 875 patients in the DCB and PBA groups, respectively, were included in the present meta‐analysis. Target lesion primary patency, circuit patency, target lesion revascularization, and mortality were pooled. Odds ratios (ORs) were reported with 95% CIs. Publication bias was analyzed with funnel plot and Egger test. Target lesion primary patency was higher among patients who underwent DCB (OR, 2.93 [95% CI, 2.13–4.03], P

The objective of this paper is to contribute towards understanding the effects of palm oil production upon key macroeconomic variables in Malaysian economy. A dynamic general equilibrium model was employed in order to analyze the dynamic macroeconomic adjustment processes arising from palm oil production increase for Malaysian economy (the second biggest palm oil producer in world), operating under a managed float exchange rate regime. The model utilized in this paper is likely to be of interest to other palm oil-exporting economies with similar features such as that of Indonesia. Findings from this paper show that an increase in palm oil production would potentially result in an increase in private capital stock, private sector wealth, real income, public capital stock, human capital stock and non-palm oil output supply and demand. However, the revenue arising from the palm oil sector also has the potential to deteriorate the non-palm-oil trade balance through a slight loss of competitiveness from a real exchange rate appreciation.

Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Force (USPSTF) recommends anyone ages 50-75 and/or with a family history to be screened for CRC. To improve screening specificity and sensitivity, we have built an artificial neural network (ANN) trained on 12 to 14 categories of personal health data from the National Health Interview Survey (NHIS). Years 1997-2016 of the NHIS contain 583,770 respondents who had never received a diagnosis of any cancer and 1409 who had received a diagnosis of CRC within 4 years of taking the survey. The trained ANN has sensitivity of 0.57 ± 0.03, specificity of 0.89 ± 0.02, positive predictive value of 0.0075 ± 0.0003, negative predictive value of 0.999 ± 0.001, and concordance of 0.80 ± 0.05 per the guidelines of Transparent Reporting of Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) level 2a, comparable to current risk-scoring methods. To demonstrate clinical applicability, both USPSTF guidelines and the trained ANN are used to stratify respondents to the 2017 NHIS into low-, medium- and high-risk categories (TRIPOD levels 4 and 2b, respectively). The number of CRC respondents misclassified as low risk is decreased from 35% by screening guidelines to 5% by ANN (in 60 cases). The number of non-CRC respondents misclassified as high risk is decreased from 53% by screening guidelines to 6% by ANN (in 25,457 cases). Our results demonstrate a robustly-tested method of stratifying CRC risk that is non-invasive, cost-effective, and easy to implement publicly.

Lung cancer is the most common cause of cancer-related death globally. As a preventive measure, the United States Preventive Services Task Force (USPSTF) recommends annual screening of high risk individuals with low-dose computed tomography (CT). The resulting volume of CT scans from millions of people will pose a significant challenge for radiologists to interpret. To fill this gap, computer-aided detection (CAD) algorithms may prove to be the most promising solution. A crucial first step in the analysis of lung cancer screening results using CAD is the detection of pulmonary nodules, which may represent early-stage lung cancer. The objective of this work is to develop and validate a reinforcement learning model based on deep artificial neural networks for early detection of lung nodules in thoracic CT images. Inspired by the AlphaGo system, our deep learning algorithm takes a raw CT image as input and views it as a collection of states, and output a classification of whether a nodule is present or not. The dataset used to train our model is the LIDC/IDRI database hosted by the lung nodule analysis (LUNA) challenge. In total, there are 888 CT scans with annotations based on agreement from at least three out of four radiologists. As a result, there are 590 individuals having one or more nodules, and 298 having none. Our training results yielded an overall accuracy of 99.1% [sensitivity 99.2%, specificity 99.1%, positive predictive value (PPV) 99.1%, negative predictive value (NPV) 99.2%]. In our test, the results yielded an overall accuracy of 64.4% (sensitivity 58.9%, specificity 55.3%, PPV 54.2%, and NPV 60.0%). These early results show promise in solving the major issue of false positives in CT screening of lung nodules, and may help to save unnecessary follow-up tests and expenditures.

Much has been written, published, and presented about the important role and uses of technology in English language teaching (ELT) today and the effect it can have on students' learning. The present qualitative study is an intervention, which attempted to explore the integration of technology among 11 public school English language teachers in the Sultanate of Oman through the use of community of practice (CoP). As the first in the region, this qualitative study triangulated data using a focus group interview and reflective journals. Three themes emerged from the data analysis. Despite certain challenges, the findings were generally positive and encouraging, and revealed that if a CoP is effectively utilized to the fullest to integrate technology in ELT, it can facilitate policy implementation and Second Language Teacher Education (SLTE) in the Sultanate of Oman, the neighboring Gulf Cooperation Council countries, some Asian and Far Eastern countries, and beyond.

Language learning games combine a number of linguistic, psychological and social elements that have been found to have considerable advantages and powerfully impact language learning and teaching. They are incorporated into language curricula to promote interactive engaging learning. This study investigates the role of games in the Omani ELT syllabus through conducting a thorough content analysis of Basic Education System English language textbooks across all grades as well as seeking the attitudes of teachers and students of three public schools representing the three teaching cycles in the educational system. A content analysis form and a questionnaire were used to collect data. Results showed that the Omani ELT syllabi endorsed a modest number of communicative games across grades, the majority of which focus on teaching vocabulary with a very timid focus on the language skills. Moreover, students hold highly positive attitudes about the role of games in improving their language whereas teachers have moderately positive attitudes about their role. Implications of these results on the language learning and teaching context are outlined.

Proficiency in the English language has been described as central for determining Non-Native English Speaking Teachers (N-NESTs) selection for joining the profession. The Ministry of Education in the Sultanate of Oman decided to set the score of Band 6 on the International English Language Testing System (IELTS) for accepting the English Language Teaching (ELT) graduates of Sultan Qaboos University (SQU) as full-time teachers. This qualitative content analysis study hence triangulates data from interviews and the relevant literature about the different language proficiency measurement devices to determine the selection of SQU graduates to join the ELT force. The findings show that the Ministry of Education needs to rethink the decision of opting for the IELTS as a valid and reliable selection criterion. The results have important implications for setting selection criteria of becoming an English language teacher in the Sultanate of Oman and beyond.

Historically and as a developing country, the Sultanate of Oman has always been culturally dependent on Britain to plan and implement its English Language Teaching (ELT) and in-service teacher education. This dependency has negatively affected preparing English language teachers with a new global professional identity capable of introducing change to the Omani ELT system. This argument is at the heart of my response to Wyatt and Sargeant's article in this issue of "Changing English." I argue for professionalism as a political ideology capable of resisting and challenging the ELT cultural imperialism. [For Wyatt and Sargeant's article, "As an Insider, Researching English Language Teaching in Oman, You Need to Be Reflexive: A Response to Al-Issa (2019)," see EJ1302936.]

This paper examines the language planning situation in the Sultanate of Oman with emphasis on the planning of Arabic, English, French and German, and their choice and spread in serving different interests and purposes. The paper explores the historical, social, political, and ideological processes and complexities of the language policy and planning (LPP) situation in the Sultanate. The discussion attempts to show that language planning, as carried out by the elites, is top-down and ideologically oriented and motivated, as it favors certain knowledge and traditions, while marginalizing and oppressing others. A brief introductory history of Oman is followed by an account of the language profile of the country. The paper then examines the role of Language in Education Planning (LEP) in the spread of Arabic, English, French, and German in schools and higher education. It concludes that there is an ideological struggle, contest, and conflict at the LEP level resulting in a lack of strategic planning and organized effort affecting language choice, language spread, language contact, language preservation, language maintenance, and language shift. Finally, the paper recommends avenues for further research and ways forward for LPP and LEP in Oman.

The government of the Sultanate of Oman actively promotes the value of English as a global "lingua franca" to support modernization and national economic growth. This policy, however, creates difficulties for many teachers, who find themselves implementing certain practices that conflict with a vision of English language teaching (ELT) that accords with humanist values. They find themselves adopting forms of instruction that reduce English to a matter of drills and skills. This essay draws on an inquiry that I facilitated with the help of four Student Teachers during their practicum. The inquiry involved asking them to keep reflective journals in an effort to place their teaching in a critical perspective exposing the contradictory nature of their professional situation. The journals show their struggle with the ELT "status quo" at their cooperating schools, while revealing their commitment to opening up educational opportunities for their students beyond what the curriculum prescribes.

Family ownership is a special form of the known forms of ownership that is distinguished from it in that the owners are relatives who belong to one family. This is what the legislator in the Emirate approved under Family Property Law No. (9) of 2020 in more detail, and thus completed this type of ownership with the social life and Emirati customs and traditions. Therefore, the legislator in the Emirate of Dubai was keen to organize this type of ownership in an optional manner for the securities related to the allocation of this type of ownership. The study aimed to establish a comprehensive and clear legal framework for the family institution in the Emirate of Dubai, and to facilitate its transfer between successive generations easily and smoothly, and to maintain the exclusivity of ownership, the role it plays in achieving institutional economic growth in the emirate, and to maintain social prostitution, and to stay away from everything. What may increase disputes between family members. The study concluded with a number of distinguished results: Public property in both federal laws and the law of the Emirate of Dubai has a form of common ownership, and the legislator has organized its download within common ownership (compulsory common ownership), while the legislator in the Emirate of Dubai has allocated an independent law under the name of the Family Organization Law. It concluded many tips, including: The urgent need for a strong organization of commercial ownership in the Federation of Legal Contractors, similar to the legislator in the Emirate of Dubai, since this is the reason it is also in the field of family commercial companies and real estate, and therefore the UAE legislator allowed one of three celebrities to be an exception to the rule that it also requires. However, the legislator should have rejected this and not not taken it into account; because it is contrary to starting with family ownership, which is exclusive ownership between family members or the family for downloading. [ABSTRACT FROM AUTHOR]