Volume 9 | Issue 6

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Leadership Style, Hotels, Hospitality, Manager

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ABSTRACT Low cost, low power consumption, high operating speed, and high integration density-based electronic goods are economically requisite in business, engineering, science and technology in the present era. Single Electron tunneling based threshold phenomenon is one approach by which all the logic gates, combinational and sequential circuits can be implemented. Single Electron tunneling devices (SEDs) and Threshold Logic Gates (TLGs) have the capabilities of controlling the transport of only an electron through a tunnel junction at a time. A single electron bearing the charge is sufficient to store an information in a SED in the atmosphere of 0K. Power required in the single electron tunneling circuits is very low in comparison with the (CMOS) circuits. The speed of the processing of TLG based devices will be very near to electronic speed. The single-electron transistor (SET) and TLG both attract the scientists, technologists and researchers to design and implement their large scale circuits for small cost of the ultra-low power and its small size. All the tunneling events in the case of a TLG-based circuit happen when only a single electron tunnels from one conductor to other through the tunnel junction under the proper applied bias voltage and multiple input voltages. For implementing an up-down converter, TLG would be a best candidate to fulfill the necessities requiring for its implementation. So far as the Ultra-low noise is concerned, TLG based circuit would be a best selection for implementing the desired tunneling circuits. Different TLGs like 2- or 3- input AND and OR, RS Flip-flop and T-Flip-flop, an UP-Down counter are implemented by using linear or non-linear threshold logic gates or devices. And their corresponding truth table or simulated results are given in due places.

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up-down Counter, Electron-tunneling, Coulomb-blockade, linear threshold gate

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Brain tumors are the most frequent and severe cancer with a life expectancy of only a few months in the most advanced stages. As a result, therapy planning is an important step in improving patients' quality of life. Various image methods such as computed tomography, magnetic resonance imaging, and ultrasound images, are commonly used to examine tumors in the brain, lung, liver, and other organs. Biopsy is used to classify brain tumors. It is done before final brain surgery. Technology advancements and machine learning can assist radiologists in tumor diagnosis without the need of invasive procedures. The convolutional neural network is a machine-learning technique that has shown to be effective in image segmentation and classification. Automatic brain tumor categorization is a difficult undertaking due to the enormous geographical and structural heterogeneity of the brain tumor's surrounding environment. The use of Convolutional Neural Networks (CNN) classification for automated brain tumor detection is proposed in this paper.

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Brain Tumors; Computed Tomography; Magnetic Resonance, Convolutional Neural Networks.

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Extracting useful information from numerous records stored in medical data structures is particularly difficult. Developed primarily for use in web information systems, web semantic technologies offer efficient solutions for the management of complex and distributed data and can also be used in clinical information. The semantic web provides solutions to encode information in a meaningful way and as a result, records can be searched efficiently and created easily. Semantic web technologies can facilitate the management and sharing of information to promote linguistic competence in healthcare information systems. Technological advances in biomedical engineering and scientific health disciplines have enabled many Health Information Systems (HIS) and medical devices to generate enormous amounts of data. Hospitals produce this data daily and the data produced has diverse sources and is therefore stored in different repositories or databases resulting in limited relevance of HIS data. This article aims to provide an overview of semantic web technologies in health care.

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Health Information System, Ontologies.

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The ports are very significant in India because of economic growth of India is depends on Sea Transport and it is a principal constituent to the international trade. Indian ports met rapidly expanding traffic, handling more than a billion tonne of cargo for example 2013-14 the major ports accounted for 57.11 per cent (555.50 MT) of the cargo by volume. This underlines the importance of sustaining the growth and development of ports. Berth generally is used for handling of cargoes which are classified bulk berth, container berth, general berth, coal berth, Iron ore berth and fertilizer berth. Total number of berth is 239 in all the 12 major ports in India. The general berth depth is lowest among the other types of berth and it is between 8mtrs to 12.5mtrs. The traditional major port of Kolkata, Mumbai and Chennai are declining performance due to inadequate berth and depth of the port. So, the researcher concludes that Indian port authority should take the steps to increasing the depth of the berth for using mother vessels.

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Port, Berth, Vessel, International trade, and Depth

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The proposed paper discusses on the possibilities of transmitting power wirelessly over certain small distances for a load of 50W (maximum 75W). The system consists of mainly five blocks namely: AC-DC rectifier, DC-AC high frequency inverter, resonating circuits, DC-AC high frequency rectifier and a closed loop buck converter. This particular system is designed to operate in the radio frequency bandwidth of 25kHz to 150kHz. The system is designed keeping in mind applications such as very low power electric cycle and laptop chargers. This concept can be extended for mid-range WPT systems mainly wireless EV charging by changing few devices.

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WPT, PTC, DC-AC High Frequency Inverter, Buck Converter, Wireless EV Charging

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: In Ayurveda Various Acharyas give explanation about Prameha. The description in Ayurveda text shows marked similarity of Prameha Rupa and type 2 Diabetes Mellitus. It is characterized by polyurea, burning sensation in palm, polyuria, unexplained weight gain, polydipsia. According to Ayurveda it is a Tridoshajavyadhi (mainly kapha Pradhan) and Meda, Sweda is the main Dushya. The general prevalence of type 2 diabetes mellitus (pre diabetes) is 11.8%. A 50 years old male having chronicity of 10 years for type 2 diabetes mellitus came for consultation in OPD of Ayurved hospital For complaints of Karpaddaha, Atiswedpravrutti, Shlathangatwam, Pipasativridhi since last 1 month. The line of treatment given to the patient includes Dipan, Amapachak, Kaphanashak, Guru Apatarpanjanya. The Ayurved classics i.e. Bruhat Nighantu Ratnakar has advised Abhrakadi Yoga for management of Prameha. Good result was observed on Karapaddaha (70%), Shlathangatwam (65%), Atisweda (60%) Bharvridhi (10%). by the treatment regimen FBS was 180mg/dl which was reduced by 113mg/dl, PPBS was 230mg/dl which was reduced by 164 mg/dl after 45days of treatment and urine sugar became nil which was in traces before the treatment. Significant result was noted on subjective and objective parameters by Abhrakadi Yoga and Pathyapalana. This approach may be taken into consideration for further treatment and Research work of Prameha.

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Prameha, type 2 diabetes mellitus, Abhrakadi Yoga.

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294 Ashirwad R.K.Extension Stand road sangli , maharashtra

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CAD, Catia, GUI, Macros, Design, Parametric modeling, two stage spur gearbox

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E-learning has transformed the education sector in a drastic way. With the sudden shift away from the traditional classroom due to the pandemic, there is a dire need to implement e-learning for the benefit of both the learner and the educator. Keeping in mind the vast scope of e-learning, the paper will be an attempt to redefine the role of the educator and the learner in e-learning, the usage of the terminology, the fundamental perspectives while also highlighting the advantages and the disadvantages particularly in reference to the state of Nagaland.

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E-learning, Education, Learning, Teaching, Technology

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Smart Traffic Monitoring and Controlling Using IOT and Cloud is a cornerstone of a Smart city. In the current problems of the world, urban mobility is one of the major problems, especially in metropolitan cities. ... An algorithm is used to predicts the traffic density for future to minimize the traffic congestion.

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Hardware nd Software

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This paper establishes a forecasting framework to predict the prices of stocks. The project seek to utilise Deep Learning Models, Long-Short Term Memory (LSTM), Neural Network Algorithm to predict stock prices.

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Deep Learning Models, LSTM, Neural Network Algorithm

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COVID-19 is an infectious disease caused by a newly discovered corona virus. The pandemic has become the cause for a dramatic loss of human life. Though there are various vaccines that are being manufactured for coronavirus, lakhs of cases are still arising worldwide. So, to prevent the spread of the pandemic, quick and effective testing is necessary. Many researches have recently shown that chest x-rays are found to be highly predictive of COVID-19. Though the chest X-Rays cannot solely be used for determining COVID-19, the persons with positive results could be quickly isolated due to the instantaneous nature of the chest X-Ray testing. In this work, we are trying to predict whether a person has COVID-19 from their chest X-Ray image by image classification using Convolutional Neural Networks learning.

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Chest X-Ray, COVID-19, Corona Virus, Convolutional Neural Networks, Machine Learning, Deep Learning

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India has an estimated 77 million people with diabetes, which makes it second most affected in the world, after China. The number is projected to grow by 2045 to become 134 million by the International Diabetes Federation. Diabetic Retinopathy is one of the many side effects of Diabetes. Up to 21% patients with the type 2 Diabetes have retinopathy at the time of first diagnosis of Diabetes, and most develop some degree of retinopathy over time. Diabetic Retinopathy is a complication of Diabetes that affects the eyes. It is caused by the damage of the blood vessels in the tissue at the back of the eye(retina). It is generally observed, especially in the rural areas, that people consult the doctor only after their vision become blurred and they start to experience blindness, which is the third or fourth stage. At this stage, it becomes difficult to treat the patient after the retina has fully damages. This paper will provide all the guidelines for detecting DR of any fundus image.

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Diabetic Retinopathy, Microaneurysms, Hemorrhages, Exudates, Support Vector Machine.

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Key words: MGNREGA, Education, Rural migration, Performance, India

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The eye is the most important sense organ which enables us to see the world. Ocular eye diseases are some of the major problems for vision. In this ocular eye disease comes the most common disease, Cataract. Cataract is a misty form that affects the vision of the eye which causes blurriness. It is mostly found in elderly people due to their age. Computer-aided diagnosis is a bit complicated task for the detection of ocular eye diseases. In the present paperwork, we predict the ocular eye diseases based on Machine Learning algorithms which include Convolution Neural Networks (CNN) and image pre-processing. The accuracy of the outcome is displayed through the confusion matrix.

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Cataract; Detection; Convolution Neural Networks (CNN); Image pre- processing; Confusion matrix

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Data mining consists of various applications in financial and medical. Data Mining perform various tasks.Classification is one of the main task in data mining. In this paper classification is integrated in Cloud computing.Whenever the user created data in offload that can be encrypted and sent to the cloud.This paper uses classification technique for security in cloud. This paper implements KNN classification and prove its efficiency.

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Security, Classification ,KNN classifier, encryption, Security

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Attendance, Curriculum, Semester

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Machine Learning has been exponentially growing in the past with applications in almost every field of science and engineering. It is a very useful and efficient technique to make sensible interpretations of the vast amount of data which is very difficult to carry out but the human mind. There are many fields in science where huge amounts of experimental data are systematically developed over several decades. It can be utilized to make new interpretations and understandings with the help of machine learning, which was otherwise not possible. This article reports advancements made in the fields of genetics, material science, and agriculture with the successful use of machine learning.

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Machine Learning, Material science, Genetics, Agriculture

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COVID-19 pandemic is the deadliest crisis the entire world is going through. There are many active cases and deaths that have been brought about by the infection. The main symptoms of the disease include fever, dry cough, sore throat, tiredness and difficulty in breathing. To prevent the spread of disease, infected people should maintain hygiene and to be kept in isolation. Masks, sanitiser, and physical distance are to be maintained to control the spread of disease. This disease mainly affects the respiratory system thereby affecting the oxygen intake which is essential for human survival. In the present paperwork, we estimated the probability of a patient being affected with COVID-19 and estimated whether they need oxygen or should be hospitalized or if home quarantine is enough based on the given patient's details.

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Logistic Regression, Django, Python, COVID-19, Symptoms, SPO2, Hospitalization

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Women domestic help, development, socio and economic conditions, exploitation.

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