MEALS2SHARE Neighborhood Home Cooked Food Sharing Web Application

The goal of this project is to develop a web application which will provide users a platform to share home cooked food. Today in fast pace busy life, it is nearly impossible to get started in meal preparation after returning home from work. Many a times we are away from our homes travelling or staying away for different reasons. Having food that is inferior to home food and compromising on fast food or restaurant food have resulted in diseases that were rare few decades back. Increasing obesity, diabetes or other metabolic diseases could be significantly controlled with good and healthy food habits. Therefore, to provide quality and healthy food as if it was from one’s own kitchen, this web application provides an easy solution where the healthy home food seeker “foodie” could interact with home food provider “cook”. This application is built in ASP.NET framework using MVC (Model View Controller) development model and requires SQL Server. This application brings an easy to use interface so that the provider user could share the food they have prepared in their kitchen with the price they want to sell it and the service receiver user could search the food they would like to eat and locate the cook in geographical proximity. Both users - cook and foodie have their dedicated user accounts to keep track of their food listings, order history and transactions. This web application brings its own advantage to both users- foodie and cook and thus will provides immense business opportunity to the service provider launching this ecommerce web application

Signaling Security in LTE Roaming

LTE (Long Term Evolution) also known as 4G, is highly in demand for its incomparable levels of experience like high data rates, low latency, good Quality of Services(QoS) and roaming features. LTE uses Diameter protocol, which makes LTE an all IP network, connecting multiple network providers, providing flexibility in adding nodes and flexible mobility management while roaming. Which in turn makes LTE network more vulnerable to malicious actors. Diameter protocol architecture includes many nodes and the communication between the nodes is done through request and answer messages. Diameter manages the control session. Control session includes the signaling traffic which consists of messages to manage the user session. Roaming signaling traffic arises due to subscribers movement out of the geographical range of their home network to any other network. This signaling traffic moves over the roaming interconnection called S9 roaming interface. This thesis project aims to interfere and manipulate traffic from both user-to-network and network-to-network interfaces in order to identify possible security vulnerabilities in LTE roaming. A fake base-station is installed to establish a connection to a subscriber through the air interface. The IMSI (International Mobile Subscription Identity) is captured using this fake station. To explore the network-to-network communication an emulator based LTE testbed is used. The author has investigated how Diameter messages can be manipulated over the S9 interface to perform a fraud or DoS attack using the IMSI number. The consequences of such attacks are discussed and the countermeasures that can be considered by the MNOs (Mobile Network Operators) and Standardization Committees

Music therapy: Structural music modulation on reducing symptoms of generalized anxiety disorder.

The present study examines whether modulating musical structural elements in therapeutic treatment reduces the severity of symptoms among individuals diagnosed with generalized anxiety disorder. Music therapy has recently become a more utilized non-traditional treatment modality for anxiety. However, the specific elements of music that trigger relaxation responses alongside prevent rumination spirals has not received significant attention in literature thus far. This study aims to assess what type of music allows for the most effective treatment in reducing anxiety. Using a 2 (tempo: adagio, allegro) x 2 (timbre: string instrumental, vocal) x 2 (key: C major, D minor) between participants experimental design, participants diagnosed with generalized anxiety disorder will be assigned to one of eight conditions manipulating structural elements of music. Over a 10 week study period, participants will attend a CBT talk therapy session and music therapy session once a week. At the end of the study, participants will reassess the severity of GAD symptoms. It is hypothesized that music therapy involving adagio tempo, string instrumental timbre, and the key of C major music will demonstrate larger symptom reduction levels than that of allegro tempo, vocal timbre, the key of D minor music. Additionally, a supersize effect would demonstrate larger significant reductions in symptoms using a combination of adagio, string instrumental and C major key music. This study may allow the increased use of music therapy alongside traditional treatment modalities to provide greater accessibility, immediate relief, and more efficacy within the modality by understanding what elements are most impactful to reduce symptoms

Prediction of Corporate Bankruptcy using Financial Ratios and News

A corporate’s insolvency can have catastrophic effects on not only the corporate but also on the returns of its lenders and investors. Predicting bankruptcy has been one of the most sought-after areas for researchers for many decades. This study involves predicting the bankruptcy of the United States corporates using financial ratios and news data. The financial ratios of the companies were extracted from yearly financial reports of the companies, and the news data of the companies was scrapped from online newspapers, reports and articles using Google News. The news data was analyzed for negative and positive sentiments. The sentiment scores, along with the financial ratios of the companies, were given as features to the machine learning models. Various models were analyzed for their results such as Random Forest, Logistic Regression and Support Vector Machines (SVM). The study finds the best results from the random forest model with an accuracy of 90%. Moreover, the significant feature importance of the sentiment score given by the model proves that unstructured data, such as news, can play a crucial part in predicting bankruptcy in conjunction with the structured data, such as financial ratios

High Density Impulse Noise Detection using Fuzzy C-means Algorithm

A new technique for detecting the high density impulse noise from corrupted images using Fuzzy C-means algorithm is proposed. The algorithm is iterative in nature and preserves more image details in high noise environment. Fuzzy C-means is initially used to cluster the image data. The application of Fuzzy C-means algorithm in the detection phase provides an optimum classification of noisy data and uncorrupted image data so that the pictorial information remains well preserved. Experimental results show that the proposed algorithm significantly outperforms existing well-known techniques. Results show that with the increase in percentage of noise density, the performance of the algorithm is not degraded. Furthermore, the varying window size in the two detection stages provides more efficient results in terms of low false alarm rate and miss detection rate. The simple structure of the algorithm to detect impulse noise makes it useful for various applications like satellite imaging, remote sensing, medical imaging diagnosis and military survillance. After the efficient detection of noise, the existing filtering techniques can be used for the removal of noise.

Knowledge, attitude and practices regarding smoking amongst young females

Background: Smoking amongst women is increasing in the developing countries like India. There is paucity of data on the knowledge, attitude and practices of smoking amongst females in India. Hence a study was planned to assess the same.Methods: It was a qualitative research using descriptive questionnaire, prepared using the basic protocols available as per WHO Global Adult Tobacco Survey, conducted by self-reporting, from February to March, 2018 in the University Institute of Applied Management Sciences, Panjab University, Chandigarh. It was administered to 111 females aged 18 to 35 years, residing in Chandigarh.Results: Total22.5% of the female respondents were current smokers. Majority of them belonged to the age group of 26-35years; were either employed or were studying and felt that females resorted to smoking for gaining pleasure and relieving stress. Most of them were aware of passive smoking. Majority felt that people who smoke should quit for their own health and for their families and street plays, public awareness camps, television and cinema halls are important mediums for helping to quit. Will power be found to be most important to help smokers quit. Some quoted the role of nicotine replacement therapy, exercise, individual counseling etc also. Majority of the females started smoking early, at an age of 16-25years, consuming 1-10cigarettes per day and had been smoking since more than a year when interviewed. Smoking was primarily introduced by peers. All the smokers were aware of different types of smoking hazards, most commonly reported as cancer and asthma. 16/25 smokers wanted to quit and 14/16 had tried in the past but were unsuccessful.Conclusions: This study gives an indication of rising smoking trend in females. Smoking cessation measures need to be made more gender-sensitive, targeting females in their early ages

Effect of barley malt, chickpea and peanut on quality of Barley based beverage

The present investigation had been done to optimize the effect of barley malt on production of barley based beverage. Malting of barley was carried out by steeping the cleaned and bold grains in tap water at 16°C for 2-3 days. The steeped grains were also germinated at 16°C for 2-3 days and the grains showing optimum growth were sorted out and kilning was done at 60°C for 1 day. Different levels of malted grain (i.e. 0, 1, 2, and 4 %) in barley extract were optimized. It was found that addition of 4 g malt to the extract was found to be effective in decreasing the viscosity and avoiding the formation of gruel like structure. There was non significant sensory change found on addition of roasted malt grain. Amylase activity of malt significantly increased on increasing time and no reducing sugars resulted at 90°C. Nutritive value of malted beverage was improved over control. Total soluble solids (TSS), viscosity, protein, fat, reducing sugar and total sugar of malted beverage was significantly increased as compared to control. Malted beverage was more organoleptically acceptable than control. Final beverage was made with 4 g malt, 25 g bengal gram and 15 g peanut per extract from 100 g barley with addition of sugar to 17°brix and homogenizing for proper mixing was autoclaved. Thus, malting could be an appropriate food-based strategy

CoMEt: x86 Cost Model Explanation Framework

ML-based program cost models have been shown to yield highly accurate predictions. They have the capability to replace heavily-engineered analytical program cost models in mainstream compilers, but their black-box nature discourages their adoption. In this work, we propose the first method for obtaining faithful and intuitive explanations for the throughput predictions made by ML-based cost models. We demonstrate our explanations for the state-of-the-art ML-based cost model, Ithemal. We compare the explanations for Ithemal with the explanations for a hand-crafted, accurate analytical model, uiCA. Our empirical findings show that high similarity between explanations for Ithemal and uiCA usually corresponds to high similarity between their predictions

A new indication for elective induction of labor COVID-19 pandemic effect

Background: Induction of labour is performed in certain circumstances which involve greater risks of waiting for the onset of spontaneous labour than the risks due to shortening the duration of pregnancy by induction. The objective of this study was to evaluate the maternal and fetal outcome in patients undergoing elective induction during COVID-19 pandemic.Methods: This prospective observational study was conducted on 60 ANC patients with singleton pregnancy and POG >39 weeks coming to OPD with negative COVID-19 RT-PCR report. To avoid the burden of repeat testing after one week and risk of exposure to COVID-19 virus from community, patients were induced. All the data was recorded and analyzed.Results: Most of the patients were in age group of 20-25 years (50%) and only 6.7% of the patients were older than 30 years. 32 (53.3%) patients were multiparous and 50% of the patients were having Bishop score between 2-5 and only 8.3% had bishop score of more than 5. 47 patients (78.3%) underwent normal vagina delivery whereas 12 patients (20%) underwent LSCS. Failure of Induction was the indication for LSCS in 5 patients (41.7%).Conclusions: Elective induction was found to be better option in COVID-19 negative patients. All pregnant women should be monitored for development of symptoms and signs of COVID-19 particularly if they have had close contact with a confirmed case. Pregnancy and childbirth generally do not increase the risk for acquiring SARS-CoV-2 infection but may worsen the clinical course of COVID-19 compared with nonpregnant individuals of the same age.

MICROFLUIDIC DEVICES AS A TOOL FOR DRUG DELIVERY AND DIAGNOSIS: A REVIEW

Microfluidic devices are a good example of the collaboration of chemical, biological, and engineering sciences. Microfluidic devices emerge as an in fluent technology which provides an alternative to conventional laboratory methods. These devices are employed for the precise handling and transport precise quantities of drugs without toxicity. This system is emerging as a promising platform for designing advanced drug delivery systems and analysis of biological phenomena on miniature devices for easy diagnosis. Microfluidics enables the fabrication of drug carriers with controlled geometry and specific target sites. Microfluidic devices are also used for the diagnosis of cancer circulating tumor cells. In the current review, different microfluidic drug delivery systems and diagnostic devices have described