Comparing machine learning and ensemble learning in the field of football

Football has been one of the most popular and loved sports since its birth on November 6th, 1869. The main reason for this is because it is highly unpredictable in nature. Predicting football matches results seems like the perfect problem for machine learning models. But there are various caveats such as picking the right features from an enormous number of available features.  There have been many models which have been applied to various football-related datasets. This paper aims to compare Support Vector Machines a machine learning model and XGBoost an Ensemble learning model and how Ensemble Learning can greatly improve the accuracy of the predictions

Enhanced encryption technique for secure iot data transmission

Internet of things is the latest booming innovation in the current period, which lets the physical entity to process and intervene with the virtual entities. As all the entities are connected with each other, it generates load of data, which lacks proper security and privacy standards. Cryptography is one of the domains of Network Security, which is one such mechanism that helps the data transmission process to be secure enough over the wireless or wired channel and along with that, it provides authenticity, confidentiality, integrity of data and prevents repudiation. In this paper, we have proposed an alternate enhanced cryptographic solution combing the characteristic of symmetric, asymmetric encryption algorithms and Public Key Server. Here, the key pairs of end points (User’s Device and IoT device) are generated using Elliptic Curve Cryptography and the respective public keys are registered in Public Key Server along with their unique MAC address. Thereafter, both the ends will agree on one common private secret key, which will be the base for further cryptographic process using AES algorithm. This model can be called as multi-phase protection mechanism. It will make the process of data transmission secure enough that no intermediate can tamper the data

Hybrid Cryptography security in public cloud using TwoFish and ECC algorithm

Cloud computing is a structure for rendering service to the user for free or paid basis through internet facility where we can access to a bulk of shared resources which results in saving managing cost and time for large companies, The data which are stored in the data center may incur various security, damage and threat issues which may result in data leakage, insecure interface and inside attacks. This paper will demonstrate the implementation of hybrid cryptography security in public cloud by a combination of Elliptical Curve Cryptography and Twofish algorithm, which provides an innovative solution to enhance the security features of the cloud so that we can improve the service thus results in increasing the trust over the technology.   

Remote Monitoring of Heart Patients Using Robotic Process Automation (RPA)

After the age of 60 years or older many people are diagnosed with heart related issues to follow up older patients, bedridden, who needs maximum care at their homes implementation of phone monitoring becomes necessary. According to study many heart patients are supposed to have a regular check up to keep a track on their physiological data. Health care is a ground that is rapidly developing in services and technology. A recent development in this region is remote monitoring of patients which has many benefits in a fast-aging world population with increasing health complications. Sensors are used to monitor essentials or vital requirements such as heartbeat, blood pressure, temperature, blood glucose level and many more. Remote monitoring varies for every age group and every aspect. During pandemic times its difficult for many of them to move around, thus remote monitoring of patients helps to have a safer and efficient way to monitor them and also saves time. These new technologies can make a contact-less and monitor illness based on the sensor values. To make remote monitoring more efficient automation places a vital role. In health sector, to make any process automated RPA (Robotic process automation) is used. Using the established application software robots automate the process originally performed by human beings. This paper focuses on easy way to monitor patients who are in a distant place, have a regular check-up without visiting the doctor regularly and in case of emergency contact the doctor within no time

Extraction of Handwritten Text using Word Beam Search Algorithm and Language Modeling

The challenge of recognizing handwriting in mortgage records is covered in this article. Businesses trying to digitize huge numbers of hand-marked scanned documents or reports have a significant challenge: offline handwritten text recognition from images. In order to translate a picture into a series of characters that match to the text that is contained in the image, this research suggests an innovative language model in combination with a deep convolutional network and a recurrent encoder-decoder network. Using the principles of Deep Learning and Word Beam Search, the complete model is trained as an end-to-end replacement for conventional handwriting recognition techniques. When the Connectionist Temporal Classification (CTC) loss function is trained on the digital form, an RNN is the result. Character probabilities are contained in this matrix for each discrete time step. By translating the character probabilities, a CTC decoding algorithm maps the final text. The token passing mechanism is used to create the recognized text from a list of dictionary words. We offer a novel and highly efficient method for developing restrictive models for classification which might associate entity names in accordance with the data contained in the article on entity types. A benchmark dataset predicated on the Mortgage domain is included. This Mortgage domain is evaluated in the presented model. We tested the model provided below using a set of benchmark mortgage datasets, which are published. The experimental outcomes were compared to the IAM and RIMES datasets, two openly accessible datasets. On the evaluation set of both datasets, word level precision at the cutting edge by 2.5% & 1.3%, respectively

Role of Information Tools in Teaching and Learning

Human capabilities are not wholly adequate to the demands of the modern teaching and learning enterprise. Here is where we aid the information tools as a facilitator. The impression of visual and audio tools are far greater is learners in registering the learning outcomes in their memory than the passive teaching of lecturing. Dramatic changes in technology have increased the variety and accessibility of information tools. Online Google Apps, Presentation software’s, desktops and palm devices, course management tools, clickers and lecture capture tools, even flipping the classrooms are some of the latest information tools. Students are made to understand, communicate, associate and create by using the tools. This facilitates the transformation of knowledge & skills into products and solutions. Knowledge stored in the short term memory is transformed into long term memory by using the tools. Modern tools improve learning outcomes by the use of improved methodologies and better evaluation. Advantages of using the tools are better presentation by the teachers and proper understanding of the learners. Information tools facilitate interactive classes resulting in an enjoyable experience. Plenty of credible and resourceful websites makes the learners’ accessibility easier. Slow learners are able to learn at their own pace, away from classrooms. Limited involvement of teachers in using information tools is a challenge. Resource limitation and knowledge and skills of the teachers are barriers. But these are attended by proper approaches to solve the issues. Research report by ‘Institute of Multimedia Education’ in Japan proves that use of Information tools has significant and possible impact on student achievement in terms of knowledge accumulation, practice skill and presentation skill

Dynamic ways of using DAS with reduced call drops and hands-off

In today’s digital era people are controlled by digital gadgets, Cellular Systems are the backbone of these gadgets or cellular systems. Current technologies are offering more facilities to their users and also have a few challenges.  In a cellular system, call dropping is one of the challenging problems, which is faced by a mobile user in a network due to many reasons like availability of free channels, low level of system configuration, high traffic rate, etc. In this research study, among various failures handover failure is one of the major reasons for call drops. A dropped call happens when your phone gets disconnected somehow from the cellular network. Usually, this happens because of poor cell signal wherever you are that causes the call to drop. When a handover failure exists, a call drop occurs. Many different techniques are proposed and introduced to remove the call drop problem. In this research proposed a proper load balancing for cellular signals using networking for efficient call drop-down solutions with the concept of the distributed antenna system