Volume 8 Issue 8 by INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGIES AND MANAGEMENT RESEARCH I J E T M R JOURNAL
International Journal of Engineering Technologies and Management Research, 2021
In this study, land use capabilities, land types and other soil properties of Kırşehir province w... more In this study, land use capabilities, land types and other soil properties of Kırşehir province were classified and analyzed. In the study, 1/25.000 scale digital soil maps obtained from the Ministry of Agriculture and Forestry (Turkey) were used. Numerical data were classified using Arc GIS 10.3.1 software, which is one of the GIS software. As a result of the research; In general, It was observed that IV. class lands were formed in the Kirsehir province IV.class lands were found to be 1658.3 km 2 and it was determined that they cover 25% of the total area. It is seen that soil insufficiency is high in Kırşehir province due to slope and erosion damage. Soil insufficiency due to slope and erosion damage was found to be 3520.7 km 2 and it was determined that 54% of the total area was exposed to this effect. It has been observed that the land type is generally composed of steppe, bare rocks and rubble. It was determined that the area formed by bare, rocks and debris is 1128.5 km 2. It has been determined that the stony soil areas are 1094.2 km 2. As a result of the study, classified map outputs related to land uses and some soil properties were obtained. It will be inevitable that this research will provide important database bases for other studies to be carried out in this region in the future.
International Journal of Engineering Technologies and Management Research, 2021
The concept of Pascal's triangle has fascinated mathematicians for several centuries. Similarly, ... more The concept of Pascal's triangle has fascinated mathematicians for several centuries. Similarly, the idea of Pythagorean triples prevailing for more than two millennia continue to surprise even today with its abundant properties and generalizations. In this paper, I have demonstrated ways through four theorems to determine Pythagorean triples using entries from Pascal's triangle.
International Journal of Engineering Technologies and Management Research, 2021
Motivation/Background: The purpose of this paper is to shed light on leadership and decision-maki... more Motivation/Background: The purpose of this paper is to shed light on leadership and decision-making in situations of uncertainty and risks-the coronavirus (COVID-19) crisis, as well as to give a systematic framework as a guide for leaders to deal with the COVID-19 and other sudden crises. Method: This paper is based on theoretical analytical methodology, where questions of the study are built, and then data were collected from previous research about study concepts. This helps in extracting lessons and principles that help researchers to answer study questions and build the methodological framework. Results: The current COVID-19 is a global sudden crisis that differs from previous crises in terms of its strength, effects, and speed. It struck all health, economic, social and psychological aspects of life. It caused a challenge of supply chains to governments and organizations, accelerated transformation to virtual work, and brought cultural change at all levels. All this forced leaders to take quick and bold decisions in the absence of complete information and lack of transparency. Conclusions: The originality of this study stems from studying the new COVID-19 crisis that suddenly struck the world and confused the most powerful countries and institutions, as leaders stood unable to deal with this crisis and its destructive effects in various aspects of life. Research on dealing with this crisis is still incomplete and subject to modification and change. Therefore, studying this and coming up with a systematic framework increases originality and novelty of this study.
International Journal of Engineering Technologies and Management Research, 2021
Aiming at the problems in hyperspectral image classification, such as high dimension, small sampl... more Aiming at the problems in hyperspectral image classification, such as high dimension, small sample and large computation time, this paper proposes a band selection method based on subspace clustering, and applies it to hyperspectral image land cover classification. This method considers each band image as a feature vector, clustering band images using subspace clustering method. After that, a representative band is selected from each cluster. Finally feature vector is formed on behalf of the representative bands, which completes the dimension reduction of hyperspectral data. SVM classifier is used to classify the new generated sample points. Experimental data show that compared with other methods, the new method effectively improves the accuracy of land cover recognition.
International Journal of Engineering Technologies and Management Research, 2021
Polyethylene terephthalate is one of the important synthetic ester polymeric material used in wid... more Polyethylene terephthalate is one of the important synthetic ester polymeric material used in widespread areas. In textile industry, this fibrous material finds use in most of the garment and apparel applications due to its ease of handling, maintenance, and drying and competes with cotton materials. However, due to the maximum hydrophobic behavior, this textile material gives number of issues like accumulation of statics, negligible moisture content, poor comfort and aesthetic characters. Hence, in order to use this polyester material in the general textile industries particularly for garment and apparel productions, it is necessary to increase to some extent of its hydrophilic character by the application of some suitable chemicals like polyvinyl alcohol. In these context, in this work an attempt is made to treat the polyethylene terephthalate fabric with sodium hydroxide followed by polyvinyl alcohol so as to increase the aesthetic properties. The output received after the polyvinyl alcohol treatment on this fabric gives the good results expected for the garment applications.
International Journal of Engineering Technologies and Management Research, 2021
The Internet of Things (IoT) is a network of wireless, interconnected, and networked digital dev... more The Internet of Things (IoT) is a network of wireless, interconnected, and networked digital devices that can gather, send, and store data without the need for human or computer interaction. The Internet of Things has a lot of promise for expediting and improving health care delivery by proactively predicting health issues and diagnosing, treating, and monitoring patients both in and out of the hospital. Understanding how established and emerging IoT technologies may help health systems deliver safe and effective treatment is becoming increasingly critical. The purpose of this viewpoint paper is to present an overview of existing IoT technology in health care, as well as to describe how IoT devices are improving health service delivery and how IoT technology can alter and disrupt global healthcare in the next decade. The promise of IoT-based health care is explored further to theorize how IoT can increase access to preventative public health services and help us migrate from our existing secondary and tertiary health care systems to a more proactive, continuous, and integrated approach. The intersection of the Internet of Medical Things (IoMT) for patient monitoring and chronic care management and the use of Artificial Intelligence (AI) is becoming more promising than ever as the adoption of telemedicine continues to grow dramatically. Connected devices generate huge volumes of data based on real-time measurements of patient vitals, which is delivered to cloud-based applications that are monitored by medical specialists in virtual contact centres. The policy is applied per-patient, and healthcare providers receive warnings and messages when a patient's heart rate, oxygen level, glucose level, blood pressure, or other measurement reaches a set threshold. Depending on the sort of telemedicine and telehealth platforms in use, this data is tracked and acted upon by specialists who monitor many patients for many different practices, and in other circumstances, this data is sent directly to the provider. AI in healthcare, as well as other crucial technologies are essential for resolving the issue and producing future prosperity.
International Journal of Engineering Technologies and Management Research, 2021
Lichens are universally distributed organism occurring in varied climatic condition ranging from ... more Lichens are universally distributed organism occurring in varied climatic condition ranging from the poles to the tropics in earth. The study of lichen remains quite frowzy throughout the world. Though the importance of lichen in an ecosystem is very high in its own way. Lichens are just like miniature sponges that take up everything that comes their path, including air pollution Fleishner TL. (1994). They synthesise many useful secondary metabolites. Among the synthesised metabolites, many of them have antiviral and antibacterial activity. To keep this view in mind the present study has done to to evaluate the antibacterial activity of two different crustose lichen species collected from Kalyani University Campus, WB. Since this is the first time study of antimicrobial activity of Cryptothecia striata and Cryptothecia scripta.
International Journal of Engineering Technologies and Management Research, 2021
Stroke is one of the foremost common disorders among the elderly. Early detection of stroke from ... more Stroke is one of the foremost common disorders among the elderly. Early detection of stroke from Magnetic Resonance Imaging (MRI) is typically based on the representation method of these images. Representing MRI slices in two dimensional structures (matrices) implies ignoring the dependencies between these slices. Additionally, to combine all features exist in these slices requires more computations and time. However, this results in inexact diagnosis. In this paper, we propose a new tensor-based approach for stroke detection from MRI. The proposed methodology has two phases. In first phase, each patient's MRI are represented as a tensor. Tensor representations are powerful because they capture the dependencies in highdimensional data, MRI of patient, which gives more reliable and accurate results. Also, tensor factorization is used as a method for feature extraction and reduction, which improves the performance and accuracy of classifiers. In second phase, these extracted features are used to train support vector machine (SVM) and XGBoost classifiers to classify MRI images into normal and abnormal. The proposed method is assessed with MRI dataset, and the conducted experiments illustrate the efficiency of this approach. It achieves classification accuracy of 98%.
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Volume 8 Issue 8 by INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGIES AND MANAGEMENT RESEARCH I J E T M R JOURNAL