Journal of Science & Technology (JST)
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THE FIRST GEOLOGISTS OF HUMANKIND WERE THE ANCIENT ISRAELITES WHO MADE THEIER WAY FROM EGYPT TO THE LAND OF ISRAEL
Get PDFThe biblical book of Genesis contains a description of the creation of the world, which is similar in large measure to the order of Creation known to science today. This article offers an explanation as to how those who wrote the Old Testament could have known the quite accurate order of Creation they set down in writing. In fact, the group of people from amongst the tribes of Israel who made their way from Egypt to the Land of Israel might actually be considered humankind’s first geologists, predating the Greek and Roman philosophers and thinkers by more than a thousand years.
 
A Design and Analysis of Two Plate Injection Mould Tool For Wi-Fi RouterThermoplastic Product
Get PDF: This A Wi-Fi router is a device that performs the function of a wireless access point, it is used to provide access to the internet or a private computer. It is the hardware device that provide basic infrastructure for a home or small office network.Proposed to make a single impression semi-automatic family mould to design top and bottom cover for Wi-Fi router to make it more aesthetic, to reduce material cost, better heat dissipation, and to reduce the tooling cost, to make the product more competitive in the market.It is proposed select the suitable plastic material, to modify the existing plastic product design and to develop a suitable two plate family mould of one impression each using SIEMENS NX software. It is also proposed to make detailing of mould parts and its assembly for manufacturing using SIEMENS NX software. The analysis was done in AUTODESK MOLDFLOW. The mould cost, raw material cost and processing cost per component are to be estimated to find the cost per component and to compare it with the existing component part
Application of High Level Programming Language (Visual Basic): A Review
Get PDFVisual Basic is a one type of high-level Object Oriented Programming Language. It is developed by the Microsoft.NET Framework. It has finally become a fully-generated Object Oriented Programming Language with all the associated features one would come to expect. It allows programmers to handle much larger applications, through improved scalability and reusability with all features than any other programming language. Various VB Tools are used in this program. This article discusses the new features using .Net code examples to real applications in Computer Technology
Eplontersen Therapy: Bridging Cardiac Health and Neuropathy Relief in Hereditary ATTR Amyloidosis
Get PDFAmyloidosis, Transthyretin, Transthyretin is generated mostly in the helix, and it is necessary for transferringretinol and thyroxine. When misfolded TTR polyneuropathy (ATTR-PN) aggregates to create amyloid fibrils, itcauses TTRamyloidosis, which results in organ failure. If left untreated, familial transthyretin cardiomyopathy(FAP), an amyloid polyneuropathy connected to mutations like the V30M variant, generates increasing sensoryand autonomic neuropathy with a dismal prognosis
Vehicle to Grid Technology in a Micro Grid Using DC Fast Charging Architecture
Get PDFBatteries from electric vehicles (EVs) have the potential to be used in microgrids as energy storage devices. By storing energy when there is excess (Grid-to-Vehicle, or G2V) and returning it to the grid (Vehicle-to-Grid, or V2G) when needed, they may aid in micro-grid energy management. The development of appropriate control systems and infrastructure is necessary to make this idea a reality. This study presents an architecture for establishing a V2G-G2V system in a micro-grid employing level-3 rapid charging of EVs. An EV interface is provided via a dc rapid charging station in a modeled micro-grid test system. V2G-G2V power transmission is shown via simulation research. According to test findings, EV batteries are actively regulating power in the microgrid via G2V-V2G modes of operation. The controller provides excellent dynamic performance in terms of dc bus voltage stability, and the charging station design assures low harmonic distortion of grid injected current
Proposing Decentralized Algorithm for Minimization of Transmission Power and Improving System Performance in Radio Network
Get PDFThe minimization of transmission power is a critical issue in radio networks due to its impact on network coverage, energy efficiency, and signal quality. In this paper, we propose a decentralized algorithm for the minimization of transmission power in radio networks. The proposed algorithm allows each node in the network to independently adjust its transmission power based on its local information, without the need for centralized coordination. We evaluate the performance of the proposed algorithm through extensive simulations, comparing it to other centralized and decentralized algorithms in terms of transmission power, network coverage, and signal quality. Our results show that the proposed algorithm outperforms existing decentralized algorithms and can approach the performance of centralized algorithms. Furthermore, the proposed algorithm offers improved scalability and robustness to node failures, making it an attractive solution for large-scale wireless networks. Overall, our study demonstrates the potential of decentralized algorithms for power optimization in radio networks and provides insights into the design and implementation of such algorithms
SMART GRID USING MACHINE LEARNING
Get PDF- In today‟s world, wastage of energy has become more frequent which leads to build a system which will take another way to maintain power generation and make proper distribution of energy and that system is called as SMART GRID.In this paper we will be making a Smart Grid which will overcome these issues by using Machine Learning. We will be using solar data power generation prediction by machine learning. This paper will help production or utility company to get knowledge of how much they have generate and distribute. By his paper blackout and energy wastage can be reduced.we developed the application which shows energy generation and user log
Detection Of Cyber Attack In Network Using Machine Learning Techniques
Get PDFImprovements in computer and communication technologies have produced significant developments that are standing put from the past. Utilising new technologies offers governments, associations, and people incredible benefits, but some people are opposed to them. For instance, the security of designated data stages, the availability of data, and the assurance of important information. Dependent on these problems, advanced anxiety-based abuse may be the current big problem. Computerised dread, which caused many problems for foundations and individuals, has manifested at a level where it might be used to undermine national and open security by a variety of social entities, such as criminal association, intelligent people, and skilled activists. In order to maintain a crucial distance from sophisticated attacks, intrusion detection systems (IDS) have been developed. Learning to reinforce support is now taking place with accuracy rates pf 97.80% and 69.79%, respectively, vector machine (SVM) estimations were developed independently to recognise port compass attempts based on the new CICID2017 dataset. Perhaps instead of SVM, we can present some alternative calculations like CNN, ANN, and Random Forest 99.33, and ANN 99.11. To disrupt, disable, damage, or maliciously control a computing environment or infrastructure, to compromise the integrity of data, or to steal controlled information, a cyber-attack attacks an enterprise’s usage of cyberspace’s via cyberspace. Cyberspace’s current state foretells uncertainty for the internet’s future and its rising user base. With big data obtained by gadget sensors disclosing enormous amounts of information, new paradigms because they might be exploited for targeted attacks. Cyber security is currently dealing with new difficulties as a result of the expansion of cloud services, the rise in users of web applications, and changes to the network infrastructure that links devices with different operating systems. So by detecting the cyberattacks we can solve this proble
Vibration Analysis in Industry 4.0: Machine Learning, Energy Harvesting, and Bibliometric Analysis
Get PDFThis research investigates the significance of bibliometric analysis, energy harvesting, and machine learning and diagnostic techniques to machine vibration analysis within the context of Industry 4.0. The study highlights the importance of early detection of machine defects and issues in reducing the likelihood of downtime and costly repairs and ensuring the optimal performance of industrial operations. Energy harvesting systems, machine learning, and diagnostic procedures are only some of the technologies used in the research of machine vibration analysis. Using these methods, it has been demonstrated that vibration patterns in machines can be analyses and predicted, that mechanical vibration energy can be converted into electrical energy, and that energy costs can be lowered. The study also includes a bibliometric analysis of the literature based on VOSviewer. Linear vibration, non-linear vibration, and vibration analysis are some of the topics it explores as it surveys the literature on vibration analysis of machines. Future research directions are proposed, and new perspectives on the current status of the field's study are provided. Practical implications for academics, professionals, and decision-makers in engineering and technology domains are derived from the study's findings, which call attention to the necessity for further study and improvement of machine vibration monitoring in Industry 4.0. This research contributes to the existing literature by providing valuable insight into the potential impacts of energy harvesting, machine learning, and bibliometric analysis on business processes
PRESERVING PRIVACY IN THE ERA OF BIG DATA: A MACHINE LEARNING-BASED ANONYMIZATION FRAMEWORK FOR SPATIOTEMPORAL TRAJECTORY DATASETS
Get PDFPublishing datasets plays an essential role in open data research and promoting transparency of government agencies. However, such data publication might reveal users’ private information. One of the most sensitive sources of data is spatiotemporal trajectory datasets. Unfortunately, merely removing unique identifiers cannot preserve the privacy of users. Adversaries may know parts of the trajectories or be able to link the published dataset to other sources for the purpose of user identification. Therefore, it is crucial to apply privacy preserving techniques before the publication of spatiotemporal trajectory datasets. In this paper, we propose a robust framework for the anonymization of spatiotemporal trajectory datasets termed as machine learning based anonymization (MLA). By introducing a new formulation of the problem, we are able to apply machine learning algorithms for clustering the trajectories and propose to use k-means algorithm for this purpose. A variation of k-means algorithm is also proposed to preserve the privacy in overly sensitive datasets. Moreover, we improve the alignment process by considering multiple sequence alignment as part of the MLA. The framework and all the proposed algorithms are applied to T-Drive, Geolife, and Gowalla location datasets. The experimental results indicate a significantly higher utility of datasets by anonymization based on MLA framework