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Context The aim of the study was to develop a prognostic model using artificial intelligence for patients undergoing lumbar spine surgery for degenerative spine disease for change in pain, functional status, and patient satisfaction based on preoperative variables included in following categories—sociodemographic, clinical, and radiological. Methods and Materials A prospective cohort of 180 patients with lumbar degenerative spine disease was included and divided into three classes of management—conservative, decompressive surgery, and decompression with fixation. Preoperative variables, change in outcome measures (visual analog scale—VAS, Modified Oswestry Disability Index—MODI, and Neurogenic Claudication Outcome Score—NCOS), and type of management were assessed using Machine Learning models. These were used for creating a predictive tool for deciding the type of management that a patient should undergo to achieve the best results. Multivariate logistic regression was also used to identify prognostic factors of significance. Results The area under the curve (AUC) was calculated from the receiver-operating characteristic (ROC) analysis to evaluate the discrimination capability of various machine learning models. Random Forest Classifier gave the best ROC-AUC score in all three classes (0.863 for VAS, 0.831 for MODI, and 0.869 for NCOS), and the macroaverage AUC score was found to be 0.842 suggesting moderate discriminatory power. A graphical user interface (GUI) tool was built using the machine learning algorithm thus defined to take input details of patients and predict change in outcome measures. Conclusion This study demonstrates that machine learning can be used as a tool to help tailor the decision-making process for a patient to achieve the best outcome. The GUI tool helps to incorporate the study results into active decision-making.

Purpose: To assess the psychological impact of COVID-19 infection lockdown on the general population. Methods: From 28th April to 4th May 2020, an online survey was conducted using snowballing sampling and invitation through online social media to participate. Socio-demographic and clinical variables were col-lected. Psychological impact was assessed with the help of self designed questionnaire adapted from DSM-5 Self-Rated Level 1 CCSM-Adult scale. Results: In total, there were 568 responses from different cities / vil-lages of the country. Out of these eight responses were excluded from the study because of lack of consent and final sample size analyzed was 560 (358 male, 202 female). Half of the participants were under 35 years of age, 63.9% were male, 49% have done post graduation and 59.1% were living in nuclear family. Analysis of response revealed presence of a high prevalence of psychiatric symptoms ranging from 5.5 % to 49.3% in the participants. Anxiety symptoms (49.3%), manic symptoms (37.3%) depressive symptoms (36.1%), anger issues (28.6%), somatic symptoms (26.3%) and sleep problems (24.5%) were the most common domains of psychiatric symptomatology reported by participants. Conclusion: Our study provides early evidence of a significant psychological impact of COVID-19 infection and lockdown on common people living in the community indicating a need for quick, comprehensive and longitudinal assessment of mental health needs of the population for early diagnosis and prevention of psychiatric disorders. © 2021 KBCSM, Zagreb.

Some of the glitches in Mobile cloud computing are high latency, network bottleneck, and congestion. From a centralized to a decentralized computing scenario, Mobile Edge computing can transfer the computation to the edge, which decreases the response time for the application and increase the user experience. This paper assesses Docker as a medium for Edge Computing, a container-based technology. Docker can be seen as an open platform for designers and system managers to use Docker Engine, a portable, lightweight runtime and packaging tool to build, ship, run applications, and Docker hub. This cloud service distributes applications and mechanizing workflows. The key benefit is that, as soon as possible, Docker can get code checked and can fit into production. This paper will discuss Docker and present how this technology has overcome the earlier problems of virtualization with building and deploying large applications in two ways. We have implemented Docker of YOLO and AQM models on Jetson TX2 and compared both applications on Docker and Host OS. We can use dockers in two ways either we can use previously made dockers or build our own Docker according to our needs. In this paper, I have used the Docker image of YOLO and built my own Docker for AQM Model. These Docker containers' performance measured in this paper based on their device performance, memory consumption, boot time, and Docker performed very well.

In the present scenario, the field of Information Technology(IT) is moving from physical storage to cloud storage as "cloud" providers deliver on-demand resources over the Internet. MEC's key idea is to provide an IT infrastructure system and cloud computing services at the mobile network's edge, within the RAN and close to mobile users. MEC expands the idea of cloud computing by taking the benefits of the cloud closer to consumers in the form of a network edge, resulting in less latency from end to end. It is a decentralized computing infrastructure where some applications use signal processing, storage, control and computing are distributed between the data source and the cloud in the most effective and logical way. Virtualization is the main cloud infrastructure technology used in MEC. Virtualization is accomplished by virtualizing the software or hardware resource layer. Virtualization in MEC can be done by the hypervisor, Virtual machine, Docker Container or by Kubernetes. Hypervisors and VMs are the technologies used earlier. Docker is the technology we use nowadays, and Kubernetes is the future of Virtualization. In the face of large-scale and highly scalable needs, the cloud computing infrastructure is hard to fulfil in a short time, and the conventional virtual machine-based cloud host absorbs a lot of device resources on its own hence in this paper, we will address Docker as new container technology and introduce you to how this technology has solved previous problems in Virtualization, including the creation and deployment of large applications. The purpose of this paper is to provide a detailed survey of related MEC research and technological developments where specifically relevant research and future directions are illustrated.

Background: Epilepsy is the second most common neurological disorder, and it may have a significant effect on sexual functions in epileptic patients. Materials and Methods: Sexual dysfunctions were assessed in 146 male patients suffering from generalized tonic-clonic seizure (GTCS) with a seizure-free interval of at least 1 year. Out of 146 patients enrolled, 46 patients had a psychiatric impairment and were excluded from the study, after applying the General Health questionnaire12 (GHQ12) scale and detailed psychiatric evaluation. The remaining patients were evaluated for the presence of sexual dysfunction by applying Arizona Sexual Experience scale (ASEX). Sixty-six patients scoring more than 19 as a cutoff score on the ASEX scale were further interviewed by a psychiatrist, and a diagnosis of sexual dysfunction was made as per ICD 10 Diagnostic criteria. Results: Sexual dysfunction was diagnosed in 66% (n = 66) of the patients. Erectile dysfunction was the most common sexual disorder diagnosed in 36% of the patients (n = 36) followed by premature ejaculation in 26% (n = 26) and decreased libido (hypoactive sexual desire) seen in 4% (n = 4) of the patients. In patients with sexual dysfunction, a significant association was observed with the duration of epilepsy and type of therapy (mono/polytherapy) (P value < 0.05). Erectile dysfunction and hypoactive desire were more common in patients taking polytherapy, whereas premature ejaculation was more common in patients on monotherapy. Conclusion: Significant impairment of sexual functions was observed in male epileptics with GTCS. A high index of suspicion should be kept in mind by the practicing clinician on diagnosing and treating sexual dysfunction in them.

Stemmer is a fundamental NLP tool which performs the task of normalization (i.e. to remove suffixes) of inflected word. This paper presents a stemmer, design and developed for Sindhi Language, using unsupervised approach. Suffixes are extracted using “Linguistica 5 “[22] a tool for unsupervised learning of morphology. The raw corpus of 10000 sentences of Sindhi Language is used for extraction of suffixes. Unsupervised stemmer is evaluated using Direct approach. Results are compared with existing rule-based, stemmer [32] and Lemmatizer[33], 1000 words are extracted from Sindhi Dictionary for evaluation.

Active vibration control using smart materials has been a subject of research for about 2 decades. In active vibration control, the controller plays an important role in attenuating vibration of the flexible structure. In the present study, a cantilever beam structure is used to study the effect of various optimal controllers using a single pair of actuator and sensor which is placed in a collocated manner at the root of the beam. Simulation and experimental studies are carried out using three optimal controllers, viz. Linear quadratic regulator (LQR), linear quadratic Gaussian (LQG) and H-infinity. The simulation study is carried out using ANSYS© and MATLAB© for all the three controllers. The experimental results are obtained using LabVIEW© programs developed by the authors. The LQR optimal control gain is calculated using state and output feedback control laws. Considering the process and measurement noises the Kalman gain is calculated and the LQG regulator is obtained further by combining the LQR and Kalman gains. The H-infinity controller is designed by considering weighting function which maintains system response and error signals within the prescribed tolerances. In the present study, H-infinity control is found to be giving robust and better performance.

The Study of word formation is called as morphology. Morphological analysis is one of the important tasks of Natural Language Processing. IR and Machine Translation are two important applications o...

This paper presents a new algorithm to construct a XOR-Free architecture of an area efficient Walsh generator. The approach completely removes the modulo-two operations required for extracting zero crossing and parity in the generation. In its place a new Transition Sequence based approach is introduced to obtain that string. The string then, becomes input to a triggered flip-flop and generate 2n Walsh sequences in dyadic ordering. The approach reduces the conventional sequential design to semi-sequential and thereby reduces the encoding/decoding cost with lesser design complexity. Results of the proposed architecture reduces the area up to 25–90% by extracting both the symmetry and state isomorphism. Further, it improves dynamic power consumption up to 3–60% with increasing sequence length as compare to conventional approach. The hardware co-simulation of the architecture is first validated and then implemented with Xilinx ZYNQ FPGA.

This paper presents a new algorithmic approach to construct a generic Nth Order Walsh Functions (WF) using Transition Sequence (TS). The TS acts as a pointer to the desired Walsh Index (WI) and produces the Sign Change string (S). This string becomes input to a triggered flip flop to generate 2n Walsh Sequences (WS). The proposed strategy totally removes the obvious use of modulo 2 adders leading to a simpler Isomorphic architecture. The FPGA implementation of the generated WS shows a superior performance for higher order WF (n) up to 9. This novel approach reduces Hardware (HW) area by 25–90% and Dynamic Power (DP) by 3–60%, with varying n from 4 to 9, as compared to pure sequential design approach. The proposed design has been tested and verified on the Xilinx Virtex-5 platform.

In recent years, real-time surveillance and monitoring system is getting importance because of security reasons. Government organizations, residential areas, commercial complexes, schools and colleges, industries, borders, and others require a dedicated surveillance system. The traditional surveillance systems do not provide real-time object identification and alerts. This paper aims to design and develop a real-time object detection and alert system (ODAS). The proposed system could be used as a surveillance and monitoring system. The object detection system uses the YOLO framework to detect objects within images and live videos. Object identity and time stamp, along with bounding box image, are marked by the detection system and stored locally. Also, the collected information is transmitted to the server in real time. At the server, the graphical user interface (GUI) application continuously gathers information from different nodes, analyzes it, and fires an alert message if the anomalies/targeted object is found. GUI also facilitates us to analyze the obtained information of an individual node or in the combination that infers the direction of movement made by a detected object and its current position. ODAS also takes the services of the real-time database to provide real-time updates of anomalies on the android phone/tablet.

Accompanying the rapid urbanization, A developing country like India, still monitoring the food grain's health using conventional methods, which detect insects at a very later stage due to which food grain get spoil. The major parameter that should be observed for maintaining the quality of grains are temperature, relative humidity, and carbon dioxide concentration. The observation of these parameters regularly can lead to early detection of the insects in the grains. This paper suggests the state of the art Internet of Things (IoT) based real-time system which observes the warehouse parameter i.e Temperature, Relative Humidity, and Carbon dioxide and predicts the type of insect activity. The hardware Device used in the experiment is designed by keeping in mind the Indian warehouse's conditions and for large scale implementation of this model. The hardware Device contains two sensors (DHT22 and CDM7160), ESP8266, and battery for power supply. DHT22 and CDM7160 sensors are adopted to detect the above parameters i.e temperature, relative humidity, and CO2. The online portal has been created for data analysis and real-time data collection from the sensor nodes. This portal can be easily integrated with the digital portal already present in most of the warehouses. The machine learning algorithm has been deployed on the online server to predict relative humidity on the basis of collected data of relative humidity at a particular temperature. The prediction of relative humidity has been done for the next five days. The predicted relative humidity is used for predicting the type of insect that could attack the stack of the warehouse in the coming future. Based on the predicted results further action will be taken for controlling the food grain quality and prevent the wastage of food grain.

Generally, Pollution estimations are performed utilizing costly hardware at settled areas or committed portable hardware research centers. This is a coarse-grained and costly approach to estimate pollution. In this paper, we present a portable approach for estimating fine-grained air quality continuously. We propose practical information acquisition model for indoor and outdoor air quality monitoring which can be carried anywhere as a portable device. It consists of gas detection circuitry for CO, CO2, PM2.5, PM10 and humidity sensor. Array of gas sensors are connected to microcontroller after signal conditioning circuit. This data is sent to a cloud service platform which provides facility of accessing the data in the form of real-time graph. An android app has been developed for the easy access of the air quality data on mobile phones. Data can be collected from many such Active Queue Management (AQM) blocks. We present fundamental models and examine its execution challenges.

The emergence of the Internet of things (IoT) facilitates us to connect all the devices available at home. Also, we can control and access devices and appliances remotely in real time. This article, by taking the advantages of IoT, proposes an IoT-based affordable air quality monitoring with smart home system that brings controlling and monitoring of devices and appliances, and monitoring of home environment together in real time. The system uses the combination of wireless communication and cloud networking, to remote control various appliances (like fans, TV), also getting a glimpse of air quality. In order to monitor the home environment, we develop a practical information acquisition model, a network for indoor and outdoor air quality monitoring which can be carried anywhere as a portable device. The portable nodes can sense pollutants like CO, CO2, PM 2.5, PM 10 with temperature and humidity and monitor the air quality. The collected data are sent to a cloud service platform like things speak and Firebase for real-time visualization and appropriate forecasting and prediction analytics. Also, a user-friendly Android app and web portal increase the usability of this system. Moreover, when critical conditions occur, an alert is reflected on the android app and on web portal in real time. Also, the system starts sending a warning ring on registered mobile.

Stemming is one of the important tasks of Natural Language Processing Applications, such as in Information retrieval and Machine Translation. In this research paper, we focused on Derivational Stemmer for resource-poor language Sindhi, in Devanagari Script by using suffix Stripping approach. A dictionary of frequent words is added to reduce over and under stemming error. This is our first attempt to develop a Rule-based Derivational Stemmer in Sindhi Devanagari Script. We compared the results of this derivational stemmer with inflectional stemmer of Sindhi Devanagari Script, previously developed by us.

The emergence of the internet of things (IoT) facilitates us to connect all the devices available at home. Also, we can control and access devices and appliances remotely in real time. This article, by taking the advantages of IoT proposes an intelligent home with air quality monitoring (AQM) system that brings controlling and monitoring of devices and appliances, and monitoring of home environment together in real time. The system uses the combination of wireless communication and cloud networking, to remote control various appliances (like Fans, TV), also getting a glimpse of air quality. In order to obtain accurate, stable values for long period, industrial class sensors are used by the system for home environment monitoring. A user-friendly Android app and web portal also increase the usability of this system. Moreover, when undesirable conditions occur, the same is reflected by an android app or web portal. Eventually, home environment data analysis is done.

Now a day’s web is multilingual and equipped with lot of information. In order to access information in different language we require some Language processing tools such as Stemmer, Part of Speech Tagger etc. Although plenty of different language processing tools are available for some languages, still some of the languages are not getting attention of research and community. Sindhi Language is one of them. This research paper we have proposed a Light weight Inflectional Stemmer using affix stripping approach, for Sindhi Devanagari Script.

Objective To test the hypothesis that, in the initial evaluation of patients with suspected coronary artery disease (CAD), stress myocardial perfusion imaging (MPI) would result in less downstream testing than coronary computed tomographic angiography (CCTA). Methods In this international, randomized trial, mildly symptomatic patients with an intermediate likelihood of having CAD, and asymptomatic patients at intermediate risk of cardiac events, underwent either initial stress-rest MPI or CCTA. The primary outcome was downstream noninvasive or invasive testing at 6 months. Secondary outcomes included cumulative effective radiation dose (ERD) and costs at 12 months. Results We recruited 303 patients (151 MPI and 152 CTA) from 6 centers in 6 countries. The initial MPI was abnormal in 29% (41/143) and CCTA in 56% (79/141) of patients. Fewer patients undergoing initial stress-rest MPI had further downstream testing at 6 months (adjusted OR 0.51, 95% CI 0.28-0.91, P = 0.023). There was a small increase in the median cumulative ERD with MPI (9.6 vs. 8.8 mSv, P = 0.04), but no difference in costs between the two strategies at 12 months. Conclusion In the management of patients with suspected CAD, a strategy of initial stress MPI is substantially less likely to require further downstream testing than initial testing with CCTA. Trial registration: clinicaltrials.gov identification number NCT01368770.

This letter presents a new algorithm to construct an XOR-Free architecture of a power efficient Convolutional Encoder. Optimization of XOR operators is the main concern while implementing polynomials over GF(2), which consumes a significant amount of dynamic power. The proposed approach completely removes the XOR-processing operation of a chosen nonsystematic, feed-forward generator polynomial and reduces the logical operators, thereby the encoding cost. Hardware (HW) implementation of the proposed design uses Read-only memory (ROM) with a preprocessed addressing operations to reduce ROM size by nearly 50%. The results of the new architecture reduce the dynamic power up to 21.4% and HW cost up to 15% with lesser design complexity as compared to conventional method. The Hardware cosimulation of the architecture is first validated and then implemented with Xilinx Virtex-V FPGA.

Coronavirus disease (COVID), also known as COVID-19, has brought the immense challenges for the health-care system globally. All the branches of medicine are equally involved in managing these patients. During this pandemic, care of obstetric patients in terms of obstetric analgesia becomes crucial. Hence, the purpose of this review was to draft a basic model of strategies related to the provision of safe obstetric analgesia during this coronavirus pandemic, which will assist the health-care providers across the developing countries to formulate their own protocols depending upon the resource availability. All research articles related to obstetric analgesia during the COVID-19 pandemic from January 2020 to December 01, 2020 available on PubMed, Cochrane, Google scholar, and Embase are included in this study. The keywords used for data search were "obstetric analgesia during COVID-19," "coronavirus pandemic," "Labor pain," "obstetric pain management guidelines," and "regional anesthesia during COVID-19." Eventually, our review yielded the most recentmodel for the provision of safe and effective obstetric analgesia practices during the COVID-19 pandemic across the developing countries.

Background and Aims: There is a wide variation in the anatomical relationship of the Internal Jugular Vein (IJV) to the Common Carotid Artery (CCA). This makes landmark based techniques of IJV cannulation and head rotation questionable and may lead to accidental arterial puncture. We conducted this study to determine the anatomical relation of the IJV to the CCA using (USG) in patients undergoing IJV cannulation for central venous access, and to analyse the effect of head rotation on this relationship. Material and Methods: A prospective observational study was conducted on 100 patients requiring central venous access, in the operation theatre or the intensive care unit. Anatomical relationship of the IJV to CCA at the level of the cricoid cartilage was analysed by noting the segment position (1-12) around the CCA using a high frequency linear USG probe on patients in neutral head position, on both sides and also with the head rotated to the contra lateral side by 15° and 45°. Results: Antero-lateral segments 1 and 2 were the most common positions (50% on the right and 73% on the left side). Change in segment causing increase in overlap of IJV and CCA with 15° head rotation was seen in 44% subjects on the right and 39% on the left. Statistically, a higher number of subjects showed overlap with 45° rotation (99% on right and 97% on left, P < 0.05). Conclusion: There is a wide variation in anatomical location of the IJV in relation to the CCA as seen by USG. Excessive head rotation causes overlap of IJV over CCA which may cause inadvertent arterial puncture, even under USG guidance. Thus, it is preferable to cannulate the IJV in neutral or near neutral head and neck position.

The main purpose of the study is to identify whether the "glass ceiling" is created or not in the organisation and also to identify how gender stereotypes affect the performance of the employees. Exploratory as well as descriptive research is conducted in which data is collected through observation, face to face interaction, and questionnaire and also from previous study done on the topics related to gender stereotypes. In which researcher attempt to find out the gap created because of gender stereotypes at workplace, at last it is concluded that gender stereotypes is a vast concept, gender stereotypes may vary from organisation to organisation because it is not necessary that it will create a barrier in every organisation, according to the data it does not show any negative affect on any employees both male and female that they are facing any problem because of gender stereotypes Dr Gaurav Purohit "Gender Stereotypes at Workplace" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd15668.pdf

High Speed Data Transfers is a typical requirement of data intensive applications like image and video processing. Speed efficiency can be ensured by handling the data transfers at both Hardware and Software level. A complete system has been developed by implementing the hardware architecture on FPGA and writing corresponding Software device driver to perform the speedy data transfers from endpoint to a root complex device using PCIe interface. This paper describes the approach to design and verify this system. The speed of data transfer achieved practically for PCIe (2.0) x4 is 4Gib/s. The developed hardware architecture is resource constrained and low power. The hardware is implemented on Xilinx Zynq device. This work has a good potential in the field of image and video processing and can be used to perform large data transfer operations at high speed.

This paper deals with the design of different optimal controllers for attenuating the vibration of beams supported at both ends, viz. fixed-fixed and fixed-roller beams which form multiple input and multiple output (MIMO) system. The beam structure consists an array of sensors and actuators, mounted in a collacated manner at the root of the beam, coupled with a controller. Finite element model of the beam is obtained using ANSYS©, and through the modal analysis eigen values and eigen vectors are extracted. The state space matrices of the beam structures are obtained by mathematical modelling which is done in MATLAB©. The simulation study is performed using three optimal controllers, viz. Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG), and H- ∞ , governed by state feedback and output feedback control laws. To reduce the computational time, the significantly contributing modes are considered. LQR controller gain is determined by considering the quadratic cost function. LQG regulator is obtain by combining the LQR gain and Kalman gain. H- ∞ controllers maintains the stability and robustness of the system within prescribed limits. The simulation results of these three optimal controllers are further compared and the significant finding are reported in the paper.

Noise and vibration causes many problems in most of the industrial applications and they have grown in recent years. Active methods of controlling vibration has been of great interest for applications requiring low weight, lower energy consumption, ease of handling, safer operation due to reduced inertia, and high speed applications. Active control involves the use of sensors to sense the vibratory motion of the structure, a controller to generate a control signal, an amplifier to amplify the control signal, and an actuator for applying controlling force on the structure to control the vibrations. The present work deals with the controlling the vibration of a cantilever beam actively using piezoelectric transducers. An experimental setup is made, consisting of the aluminum (Al) cantilever beam with the Lead Zirconate Titanate (PZT) transducers bonded in the collocated manner at the root of the beam. H-infinity controller is designed in LabVIEW© to generate the required control signal. Experiments are performed for the active control of vibration, and it is observed that there is significant reduction in the settling time. H-infinity controller the stability and robustness of linear system within prescribed limits.