NewSociRank: Recognizing and Ranking Frequent News Topics Using Social Media Factors

Mass media sources such as news media used to inform us of daily events before. Now a day, unlike news media, social media services like Twitter provide a huge amount of user-generated data, which contain informative news-related content. For these resources to be useful, we need to find a way to filter the noise and capture only the content based on its similarity to the news media. However, even after noise is removed, information overload may still exist in the remaining data-hence, it is convenient to prioritize it for consumption. To achieve prioritization, the information must be ranked in order of estimated importance considering three factors. First, the media focus(MF) of a topic, the temporal prevalence of a particular topic in the news media. Second, user attention (UA), the temporal prevalence of the topic in social media. Last, the interaction between the social media users who mention this topic indicates the strength of the community discussing it, and can be regarded as the user interaction (UI) toward the topic. We propose an unsupervised framework�NewSociRank�which recognizes the news topics prevalent(common) in both social media and the news media, and then ranks them by relevance(popularity) using their degrees of MF, UA, and UI

Home Away from Home

The implementation of this application is important because people are facing problems to give rent to the tenants and even the tenants are also not able to find the houses which will suit to their needs. If we talk about the owners, they are unable to provide the information about their house like number of rooms, facilities available, in which area it is, what is the rent and all. They are not finding the right people to give the house for rent. Similarly, to find a house for their needs, tenants has to go all around in the area where they want to live. It takes so much time, even if they find also by seeing the features and all, tenants may not satisfy with this. It is a time-wasting process. To overcome all these disadvantages and to provide the services for both owner and tenant, a application should be proposed so that both people requirements will be satisfied. To implement the above idea, an E-commerce web application should be designed so that It brings both the people meet at one place and find the related information to solve their problems. For using this application owner has to register and he can post the information regarding his house details, he can upload his profile, he will be having a facility to upload the files, images, to view the feedback given by the tenant etc. Similarly, renter/tenant can able to browse or search the information, he can find the information about the houses for rent in the area he needs, he can view the profile of the owner, view the services and facilities present in the house, he can view the rent, he can contact the owner through the site, he can pay the amount, he can book the house, he can give the feedback of the house etc. All these services should provide to the tenant. Another user of the application is Site administrator, who must manage the owner accounts, properties of the owner, vacationer accounts and to resolve any sort of issues had in between them. Owner and Tenant can have the enquiry about each other with the administrator. Both side communication will be had with the Admin. All the existing applications are providing the details of sites, houses available for rent, but they are not giving the right information of the owner, facilities available, correct rental, feedback, payment options etc. in the other sites admin is not responsible for any sort of work. Here, he is establishing the relationship with both the persons

Statistical convergence in strong topology of probabilistic normed spaces

Following the concept of statistical convergence, we define and study statistical analog concepts of convergence and Cauchy's sequence on a probabilistic normed space that is endowed with a strong topology. Some important properties of statistical convergence have been extended in this new setting

Implementation of a high performance network node for a control oriented local area network

TASKMASTER is an experimental microcontroller node of a real-time control oriented network which was proposed by James H. Herzog and Tinggui Zhang to demonstrate the feasibility of a task oriented control structure in performing distributed control actions. This study is a continuation of research involving the TASKMASTER network. A high performance microcontroller the 32-bit Motorola MC68332 has been used in this study to implement a node of the TASKMASTER network. Use of the MC68332 with its powerful peripheral subsystems offers significant scope for improvement of the overall performance of the network in addition to strengthening its control processing capabilities. An 8-bit microcontroller the Intel 8052 has also been used to implement a node of the network. A high-level language C has been used for coding of the operating system of the network which previously has been coded in assembly. In addition to being more readable, use of a high-level language offers other significant advantages such as portability, smaller code development time and code debugging time and the ability to compare different microcontrollers on a common basis. A performance analysis and comparison between the two microcontrollers used and the language used in coding them was also performed using performance measures designed as part of this study

Concerns and confidences expressed by teaching staff about the shift of medical education to online mode in South India during the COVID 19 pandemic

Background: Online education is prevalent in the country since the beginning of the 21st century. The outbreak of COVID-19, the government declared lockdown, and subsequent closing of institutions was unexpected, and it forced medical colleges to launch online programs for undergraduate courses. Due to the sudden shifting to online mode, most teaching staff members face the challenges of lacking online teaching experience, early preparation, or support from educational technology teams. This institution was in touch with the teachers and students through online mode, enquiring about their welfare and wellness. The present study focuses on concerns and confidences presented by the medical teaching staff on online medical education.  Method: This study was conducted at Jubilee Mission Medical College & Research Institute, a medical college in central Kerala in south India. This institution conducted online classes for undergraduate (UG) medical students through Google classroom and YouTube platforms. There was 186 teaching staff from 21 departments involved in undergraduate (MBBS) teaching in this Institute. In this study, we collected information from the teaching staff about the online classes that they handled. A 27-point survey form was designed using a Google survey and mailed to them. The responses were collected in a week. The data collected was analyzed. Result: Fifty-one members responded. All responding teachers preferred regular classroom teaching due to the provision for better teacher-student interaction. However, one-third of respondents wanted the continuation of online classes, even after resuming classroom teaching. Out of 51 responses, 24 teachers graded the success of the programs more than 90%. The major suggestions received for further improvement of the program were that the departments provided their hardware and software, centralized online sessions for practical purposes, and collected regular feedback from students. Conclusion: The successes of our online teaching programs were limited to didactic teaching only. It could not replace the actual patient examination in a clinical setting, which involves communication skills and emotional relationships. This adversary must be converted into an opportunity to develop e-learning programs. This pandemic should open our eyes, so we learn from it and be better prepared for the future

An Investigating of the Impact of Bed Flume Discordance on the Weir-Gate Hydraulic Structure

Discordance and concordance play a significant role in the hydraulic response for the flume, open channel, hydraulic structure, and flow field measurement. Bed discordance and bed concordance are regarded as common problems in open channels. Discordance is the dominant one, which could have an effect on the hydraulic structure that is constructed inside the channel. This paper deals with the impact of bed flume discordance on hydraulic flow characteristics at the weir-gate downstream hydraulic regime. Four configurations with different lengths and heights of the bed flume discordance are adopted here to investigate the impact of these configurations on the hydraulic characteristics. In addition, one configuration of the bed flume concordance is adopted to compare with the other four configurations. At downstream, the average water depth becomes dimensionless by dividing by upstream water depth, vertical distance between weir and gate, length of downstream, length of concordance, and length of discordance in order to evaluate the inequality in the distribution of Froude number. On one hand, certain results appear strongly between Reynolds number and Froude number at downstream, actual discharge and flow velocity at downstream, flow area past the gate and Froude number at downstream. On the other hand, there was a complex dramatic relation between the weir-gate discharge coefficient and Froude number at downstream. Overall, the study shows that there is a good relationship between specific energy, water depth, and flow speed. Doi: 10.28991/HIJ-2022-03-03-09 Full Text: PD

CAPABLE AND SECURE DATA ACCESS TO THE INTERNET SUPPORTED OBJECTS IN THE SMART SYSTEM

Under the current plan, when the user exits the user group, the manager of the audience only cancels the group's secret key, which means that the private user key associated with the attribute remains valid. Our plan is suitable for devices with limited resources. If someone within the group intentionally discovers the public's confidential response to the revoked user, they can perform the understandings through their own key. To demonstrate this attack, a specific instance is presented. We have demonstrated our safety in our plan under the assumption of Daffier-Hellman (DCDH) for the divisible account. Unfortunately, the ABE plan requires high arithmetic expenses while performing encryption and understanding of files. This defect becomes more severe for lightweight devices due to restricted computing sources. Within this system, we focused on designing the Club-ping-ABE plan with efficient user revocation of the cloud storage system. The result of our experience shows that the cost of computing for local devices is relatively low and can be fixed. We tried to design the attack model for collusion by users who were removed and who were collaborating with existing users. In addition, we built the penguin-ABE Club plan to cancel the eligible user by increasing the current plan and proving that our plan is safe for cost-per-acquisition under the selective model

An Alternative Proposed Method for Solution of Assignment Problem

The assignment problem is a particular type of linear programming problem. In this paper, we analyzed the standard and existing proposed methods.  After studying these methods, we proposed a new alternative method for solving the assignment problem. We examined the newly proposed method by a couple of numerical examples and compare this result with the standard method. The main characteristic of this newly proposed method is that it constructed a very easy logical and arithmetical algorithm. Here we point out some advantages and limitations of the new proposed method. Programming code for the newly proposed method has been added in this paper

Single-trial extraction of event-related potentials (ERPs) and classification of visual stimuli by ensemble use of discrete wavelet transform with Huffman coding and machine learning techniques

BackgroundPresentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task.MethodsEEG single trials are decomposed with discrete wavelet transform (DWT) up to the level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects.ResultsThe proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60, sensitivities 93.55, specificities 94.85, precisions 92.50, and area under the curve (AUC) 0.93 using SVM and k-NN machine learning classifiers.ConclusionThe proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds

To Study the Viscosity Index of SN500 and SN150 Base Oil with Vegetable Oil and Selective Polymers as Additives

Viscosity index is one of the most important parameter for the lubricating oils performance. The effect of additives on the viscosity index for mineral lubricating oils SN500 and SN150 have been studied by adding castor oil, olive oil, corn oil, sunflower oil in addition to Glue Adhesive and poly isotridecanol ethoxylated used by North Oil Refineries Company for comparison the results. The viscosity has been measured at 40°C and 100°C according to ASTM D445 and viscosity index calculated according to ASTM D2270. It has been found that corn oil has the best effect of the vegetable oils in improving the viscosity index of the mineral base oils. The influence of additives on the pour point was also evaluated, castor oil showed the best result of all vegetable oil in depressing the pour point of the Base oil