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Problematic Gaming Among Adolescents within a Non-Clinical Population: A Scoping Review
Gaming is a pastime activity that has been enjoyed by millions of individuals worldwide for the past few years. The adolescent is in a developmental period that involves significant bio- psychosocial changes, including rapid changes in physical and mental states that make them more vulnerable to addiction. Online Gaming could have a higher risk of developing problematic gaming. Many studies have documented video gaming addiction and not problematic video gaming. Problematic gaming is a condition different from video game addiction. Further research remains needed to synthesise the factors behind problematic video game usage. The purpose of the scoping review is to synthesise the findings related to problematic video by identifying using a search through the following database: JSTOR, ProQuest, APA Psycnet, Ebsco. The research will help detect the early symptoms of addiction and understand the mechanism behind the addictive nature. Through the study, we can provide psychological care for adolescents by educating them and preventing and being aware of problematic gaming usage and experiences. The Electrochemical Society -
Process development to synthesize plasma sprayable powders from nano alumina ceramic powders
Nano sized (?100 nm) alumina powders were converted into micron sized (30-75 mm) plasma sprayable powders by employing synthetic polymers to agglomerate them. The agglomeration process was carried out (a) in a spray dryer and (b) through systematic manual granulation procedure. The importance of process parameters that govern the plasma spray powder synthesis and thereby the characteristics were being suitable for being plasma spray coated have been brought out in this research paper. A comparative study has been made between the two synthesis methods by testing the powders synthesized under different processing conditions for their flowability characteristics. Micro-structural features related with the shape morphology and powder grain sizes were studied by Scanning Electron Microscope and the elemental composition characterization was carried out by Energy Dispersive Spectroscopy. The most suitable plasma sprayable powders were further coated onto metal substrates by using an Atmospheric Plasma Spray coating unit. The plasma sprayable powders were developed with a goal to explore their potential for their applications as wear resistant nano coatings. 2019 Elsevier Ltd. All rights reserved. -
Process Optimization Using Value Stream Mapping in PCB Manufacturing
PCB Manufacturing process is a complex process and has several processes and sub-processes. Adopting a lean manufacturing system will help to increase the efficiency of the system. This study aims to optimize the process for PCB manufacturing using value stream mapping. Observation method has been used to collect the cycle time of different processes from a PCB manufacturing plant in India. Pareto charts, why-why analysis and Ishikawa diagrams have been used to do the analysis and optimize the process and create a value stream mapping for the entire process. Standard Operating Procedures have been framed and solutions to increase the efficiency has been proposed. 2022 IEEE. -
Professional chat application based on natural language processing
There has been an emerging trend of a vast number of chat applications which are present in the recent years to help people to connect with each other across different mediums, like Hike, WhatsApp, Telegram, etc. The proposed network-based android chat application used for chatting purpose with remote clients or users connected to the internet, and it will not let the user send inappropriate messages. This paper proposes the mechanism of creating professional chat application that will not permit the user to send inappropriate or improper messages to the participants by incorporating base level implementation of natural language processing (NLP). Before sending the messages to the user, the typed message evaluated to find any inappropriate terms in the message that may include vulgar words, etc., using natural language processing. The user can build an own dictionary which contains vulgar or irrelevant terms. After pre-processing steps of removal of punctuations, numbers, conversion of text to lower case and NLP concepts of removing stop words, stemming, tokenization, named entity recognition and parts of speech tagging, it gives keywords from the user typed message. These derived keywords compared with the terms in the dictionary to analyze the sentiment of the message. If the context of the message is negative, then the user not permitted to send the message. 2018 IEEE. -
Proficient technique for satellite image enhancement using hybrid transformation with FPGA
Visual quality of images is improved by digital techniques for the improvement of photographs. The main purpose of image improvements is to process an image to make the output more desirable for a particular use than the original image. This paper proposes a new approach, which improves the picture of the satellite by the use of the SVD DWT concept, the Gaussian transformation DWT and multiwavelet transformation. This suggested approach would convert and approximate the single-colour value matrix of the low-flowing sub-band into one low-frequency and 15 high-frequency sub-bands, and then recreate the improved picture using the inverse transformation. In terms of technical criteria as PSNR, RMSE and CC, this approach can have higher quality and quantitative performance. This paper introduces strategies for improving hardware images using a programmable door array in real-time (FPGA). The suggested algorithm is implemented successfully with Xilinx ISE, MATLAB and ModelSim on different scale satellite images in Verilog HDL. In this article, these algorithms should be simulated and implemented using Verilog HDL. The Spartan-3E from Xilinx is the unit chosen here. 2021 IEEE -
Profit function Optimization for Growing Items Industry
The economy of a country depends on many industries; growing item industries are one of them. Growing items also exhibit mortality in the growth period, which creates a complex environment for the procurement decision. A practical inventory model is required to overcome this situation, which provides the optimum solution. This work describes an economics ordering quantity model for growing items with constant demand and mortality. We also take into consideration that one of the real-life management practices for businesses is the allowance of a delay in payment. There is a solution procedure with a numerical example. We have discussed analytical results to verify the concavity of the profit function. Sensitivity analysis provides us with some very useful information. . 2023 IEEE. -
Prognosis of Diabetes Mellitus Paradigm Predictive Techniques
Human life is in the era of data, when almost everything is straped on to data wellspring more- over entire esse are digitises telerecorded. That is data is generated every milli second through several means like Agriculture, Bioinformatics, Web, Cybersecurity, Smart city data, classified in- formation, pda data, flexibility evidence, medical facts, Covid related data from official state too central government portals and a number of other sources are available in todays technological con- text. There are various forms of data like structured, semi-structured, and unstructured data, text, graphics are all feasible. Every day, week, month new genre natural-world features to be resolved, machine learning adroitness have emerged as problem resolver. As a result, data management tools and analytical methodologies capable of extricate penetrated realization related specifics felicitous methodical manner ceaselessly whereby world of nature enactment rely urgently needed. The vast majority of research is focused on machine learning prediction algorithms; thus, we focus on these. Our evaluation aims to provide newbies to the field, as well as more seasoned readers, with a thorough understanding of the primary approaches and algorithms developed over the previous two decades, with an emphasis on the most notable and continuing work. We also present a new taxonomy of state of the art Model, which highlights the many conceptual and technical approaches to training with labeled and unlabeled data. Finally, we show how the fundamental assumptions underlying most machine learning methods are linked to the well-known assumptions. Grenze Scientific Society, 2023. -
Progression of Metamaterial for Microstrip Antenna Applications: A Review
This article provides an overview of the evolution of metamaterials (MTM) and all the aspects related to metamaterial development for antenna applications. It will be a useful collection of information for antenna researchers working in metamaterials applications. It gives an insight into the various metamaterial structures utilized along with miniature antenna designs. Different types of design parameters studied by the previous researchers are showcased to understand better perception of the metamaterial usage. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Prominent label identification and multi-label classification for cancer prognosis prediction
Cancer prognosis prediction improves the quality of treatment and increases the survivability of the patients. Conventional methods of cancer prediction deal with single class by limiting the prognosis prediction to one response variable. The SEER Public Use cancer database has more prominent variables that support better prediction approach. The objective of this paper is to find the prominent labels from cancer databases and use them in a multi-class environment. The implementation consist of three phases namely, pre-processing, prominent label identification and multi-label classification. Breast, Colorectal and Respiratory Cancer Data sets have been used for the experimentation. Also random samples from all three data sets are generated to form a mixed cancer data. Patient survival, number of primaries and age at diagnosis are the prominent labels identified from others using the Decision tree, Nae Bayes and KNN algorithms. The three prominent labels have been tested using multi-label RAkEL algorithm to find the relations between them. The results of the empirical study are comparatively better than the traditional way of cancer prediction. 2012 IEEE. -
Proposal of smart home resource management for waste reduction and sustainability using AI and ML
A research indicated that electricity is obliterating extra non-renewable sources for its production. In that, as per Centre for Policy Research (CPR), about 25% of the total production is diverted to meet the daily consumption in an Indian household. Not only this but also, waste management has become an important issue to deal with. According to Municipal Solid Waste (MSW) of India, waste generation in Indian urban communities extends between 200 - 870 grams per day, contingent on the localities' standard of living and the area of the city. Therefore, in this paper we propose a concept that focuses on a sustainable solution using Artificial Intelligence and Machine Learning algorithms for waste and carbon footprint reduction in a home. This concept explains a solution availed with the help of a proposed model called Home Resource Management (HoReM) that is imbibed in a Smart home. 2019 IEEE. -
Protecting Medical Research Data Using Next Gen Steganography Approach
In this paper our main aim is to protect medical research information, when data either images or information shared via internet or stored on hard drive 3rd person cant access without authentication. As needs be, there has been an expanded enthusiasm for ongoing years to upgrade the secrecy of patients data. For this we combined different techniques to provide more security. Our approach is a combination of cryptography, Steganography & digital watermarking we named this technique as Next Gen. We used cryptography for encrypting the patients information even if they find image is stegonized and digital watermarking for authenticity and for Steganography we used most popular least significant bit algorithm (LSB). The experimental outcomes with various inputs show that the proposed technique gives a decent tradeoff between security, implanting limit and visual nature of the stego pictures. 2020, Springer Nature Switzerland AG. -
Protection Against SIM Swap Attacks on OTP System
One-time password-based authentication stands out to be the most effective in the cluster of password-less authentication systems. It is possible to use it as an authentication factor for login rather than an account recovery mechanism. Recent studies show that attacks like SIM swap and device theft raise a significant threat for the system. In this paper, a new security system is proposed to prevent attacks like SIM swap on OTP systems, the system contains a risk engine made up of supervised and unsupervised machine learning model blocks trained using genuine user data space, and the final decision of the system is subject to a decision block that works on the principles of voting and logic of an AND gate. The proposed system performed well in detecting fraud users, proving the systems significance in solving the problems faced by an OTP system. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Protection offered by thermal barrier coatings to Al-Si alloys at high temperatures - A microstructural investigation
Thermal barrier coatings, with ~50 mm thick Nickel-Aluminide bond coat and ~250 mm thick Yttria-Stabilized zirconia ceramic top coats were synthesized by Air Plasma Spray coating process on flat plates machined from Al-11Si alloy diesel engine pistons. Coating process parameters and qualifications that were followed were based on previous studies made on the same substrates. The ceramic coatings were subjected to various thermal treatments such as (a) thermal shock cycling tests and (b) continuous heating in a furnace. Uncoated Al-Si samples were simultaneously subjected to the same thermal treatments and used as reference to study the protection offered by the coatings to the base metal substrates. Thermal shock cycles tests involved subjecting the coated and uncoated Al-Si plates to oxy-acetylene flame to allow the ceramic surface to be maintained at 500 C for 1000 cycles (one cycle comprised of heating for 60 s, withdrawal from flame and forced cooling in ambient air for 60 s) and similar thermal shock cycles in an electric furnace. The specimen were also heated in a furnace at 300 C for 1000 continuous hours. Stresses induced during thermal shock cycles and oxidation of bond coat-ceramic coat interface during the exposure to heat are the main reasons for the coating's failure. Details of an investigation on the microstructural changes and oxidation behaviour of the substrate and the ability of the coatings to protect the metal substrates from oxidation are presented. Microstructural studies were carried out by employing a Scanning Electron Microscope attached with Energy Dispersive X-ray spectroscopy facility. The findings were compared on (a) uncoated Al-Si alloy and (b) thermal barrier coated Al-Si alloy with a goal to understand the capability of the coatings to protect the metal from the influences of thermal treatments, at temperatures lower than the melting point of the Al-Si alloy. 2019 Elsevier Ltd. All rights reserved. -
PSA-MP: Path Selection Algorithm for MANET depends on Mobility Prediction to Enhance Link Stability
Link failure is a much crucial issue to be addressed for improving the stability of the routing. Selection of a stable path is an important task since nodes are mobile. The instability of a link leads to frequent link failure, which further causes to link re-establishment. In this paper, a Path Selection Algorithm based on Mobility Prediction (PSA-MP) is proposed that uses Mobility, Direction and Link Expiration Time (LET) as metrics to evaluate the link stability. In the existing algorithm, if any link gets fails during the link-establishment phase, it informs the previous node for selecting alternate link. But, in PSA-MP the alternate link is selected before a link fails by predicting Mobility, Direction and LET of nodes. As a result, it reduces link re-establishment delay. Ultimately, PSA-MP reduces E2Edelay, which in turn boosts Packet Delivery Ratio (PDR). Eventually, link stability is enhanced in MANETs, which is the focus of this paper. Published under licence by IOP Publishing Ltd. -
Pseudo Color Region Features for Plant Disease Detection
This study reports a novel pseudo color region features for a computer vision system for the identification of diseases in Tomato Plants. The HSV based algorithm identifies eccentric and non- eccentric dots, spots, patches and region of different pseudo colors. Proposed method uses region properties and creates an enhanced and effective feature vector for plant disease detection. The features are more intuitive for humans to understand and help in tuning the underlying Artificial Intelligence Model better. The algorithm uses a scalable data structure to store regions counts using a hash function. It has wide application in the Computer Vision domain. 2020 IEEE. -
Pulse Shaper Design for UWB-Based Medical Imaging Applications
In this paper, a pulse shaping filter is designed to shape the higher-order derivatives of the basic UWB Gaussian pulse for efficient pulse transmission through human tissues for medical imaging applications. The shaped pulse for the desired center frequency fits the FCC mask and power spectral density (PSD) specifications with higher spectral efficiency being achieved. It is observed that the ringing effect of Gaussian pulse is reduced by using the proposed bandpass FIR shaping filter. The low ringing effect observed in the shaped pulse ensures better antenna power distribution and improved location accuracy which is critical factor for medical imaging applications. The pulses synthesized are highly orthogonal which aids in multi-access communication, improved bit error rate (BER) performance and short duration UWB pulses leading to higher data rate transmission. The drooping frequency response characteristics of the synthesized pulse have reduced clutter hence tightly focused image obtained for imaging applications. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Python Driven Keyword Analysis for SEO Optimization
Every word or string of words a user types into a search engine has meaning. For example, a user might search for a 'hotel' or a 'hotel in New York City.' Keywords are the standard focus of search engine optimization (SEO), which offers a useful method of gauging demand for specific queries and aiding in a better understanding of how users look for goods, services, businesses, and, eventually, solutions. Any effective SEO strategy must include keyword research, and Python is a strong language that can be used to automate and accelerate the process. This project presents a Python-based keyword research tool that works on real-time data to identify the top searches over a user-specified domain to identify trends and customer needs. It does this by utilizing multiple Python libraries and Google Autocomplete. The Google Autocomplete results for the user-specified domain are first parsed by the tool before it can function. After that, unnecessary keywords are eliminated by filtering and cleaning the results. Subsequently, the remaining keywords are arranged for search volume and domain relevancy. The tool looks for trends by comparing the current keyword rankings with previous data. Thanks to this, users can see which keywords are growing in popularity. By identifying the most commonly asked questions and issues, the tool also offers insights into the needs of its users. The tool is simple and adaptable to each user's unique requirements. It can be used to create keyword lists for content marketing, SEO, and product development, among other uses. 2024 IEEE. -
QSAR Approach for Drug Discovery Targeting the Glucagon Receptor Using Machine Learning
Metabolic disorders like type 2 diabetes are increasing day by day so the study focusing drug discovery of glucagon receptor has become important.One of the method to study the binding strength between chemical compounds is Quantitative Structure-Activity Relationship (QSAR) which is discussed in this paper.We gathered a curated dataset of glucagon receptor ligands from the ChEMBL bio activity dataset and studied the physical and chemical properties of the molecules using factors like molecular weight and logarithm of the partition coefficient.Then Random forest regression model was applied for prediction of the binding strength of ligands. The efficiency information of ligand was extracted which contributed to study of the molecular features concerning the activity of glucagon receptor in a much easier manner. These findings highlight the potential of QSAR in elucidating the key determinants of ligated-receptor interactions and guiding the rational design of novel glucagon receptor modulators. The integration of computational approaches with experimental validation holds promise for accelerating the development of effective therapies for metabolic disorders, addressing unmet clinical needs in this field. 2023 IEEE. -
Qualitative and quantitative test of digital micromirror device for next generation UV multi-object spectroscopy
The coming decade in astronomy focuses on large wide field imaging and spectroscopic surveys. No wide field imaging facility extends to the UV region, which represents an important window into a wide variety of astrophysical problems. Also, spectroscopy would be essential to understand the physical and chemical properties of several stars, star forming regions and galaxies. Multi object spectroscopy (MOS) would be an efficient way to obtain these parameters for a large number of objects at a much shorter timescale. Digital Micromirror Device (DMD) acts as a programmable slit mask and can be used to achieve this goal in an MOS. This paper discusses different ground tests conducted on DMD to be used for the above said application. Numerical simulations for the diffraction effects on DMD is also carried out and the results are shared in this paper. 2020 SPIE -
Quality and Security Assurance Workload Scheduling in Heterogeneous Cloud Environment
The adoption of cloud computing has transformed how businesses manage their workloads, offering flexibility and efficiency. This study introduces a novel model that leverages trust mechanisms to ensure secure workload execution within heterogeneous cloud environments. The primary objective of this research was to enhance efficiency by reducing both time and energy consumption associated with executing workloads. The proposed model's efficacy was assessed through the examination of Montage and Inspiral workloads. The evaluation encompassed two smaller tasks from both Montage and Inspiral workloads, in addition to one larger task. To gauge performance, a comparative analysis was conducted between the proposed model and established models such as Energy Minimized Scheduling (EMS), Efficient Replanning (ERP), and Evolutionary Computing Workload Scheduling (EC-WSC). The findings reveal that the proposed model outperforms the existing models in terms of mitigating both time and energy expenditure for the considered workloads. 2023 IEEE.