An IoT based Tele-Health WBAN Model for Elderly People – A Review

The Tele-Health WBAN (Wireless Body Area Network) Model for patients required more attention especially old age people’s healthcare services in Low-cost Internet of Things (IoT) Devices. The advancements in telemedicine have increased drastically towards wearable sensor devices and mobile phone-based applications in the last few years. The study presents the integration of IoT and wearable sensor devices in the Tele - Health system developed for tracking heart patients among the elderly people and also to prevent them from stroke. In order to meet the demand for old age people healthcare services, it is very much essential to provide assistance in cardiac disease diagnosis and suggest medication in their home with comfortable environment. Hence, they can avoid frequent visit to hospitals and long stays.

Emerging Aspects of Artificial Intelligence for Smart Life

Nowadays Artificial intelligence makes our life easy and comfortable that is hard to imagine that to survive our life without AI technology. We all know that Artificial Intelligence (AI) is a precious gift to human being. Recently it is used in robotics, education, agriculture, computer vision, cyber security, face recognition, speech recognition, self driving cars, medical image processing, biometrics, bioinformatics, satellite control, disease detection, drugs development, network developments, manufacturing, business, healthcare and medicine. In the digital era AI provides the best results in all most all the domains. This article helps to understand the emerging aspects of AI in various fields.

Virtual Crime Scene Investigation and Evidence Protection

This paper presents the recreation of crime scenes through Virtual Reality for crime investigation and evidence storage. 3D image capturing and processing techniques are used to render fully-immersive Virtual Reality environment for investigators to work with. Cloud database and Blockchain technology for evidence storage are explained. The different levels of views on such virtual crime scenes and evidence storage are also expounded.

Big Data on Machine Learning – A Review

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over big data analytics.

Evading Signature Validation in Digitally Signed PDF

Carefully marked Portable Document Formats (PDFs) are utilized in agreements, contracts, bills, proposals, and arrangements to ensure the genuineness and trustworthiness of their material. A normal client would accept that carefully marked PDF records are conclusive and cannot be additionally altered. Be that as it may, different changes like adding comments to a marked PDF or rounding out structure fields are permitted and do not nullify PDF marks. In this paper, we show that this adaptability permits attackers to totally change a record’s substance while keeping the first signature approval status immaculate.

Analysis of a Parabolic Fin via Matrix Method

Heat is not lost equally by each element of the fin but is lost mostly near the base of the fin. Thus there would be wastage of the material if a uniform fin is used. Due to this reason fins of varying cross-sections like hyperbolic fins or parabolic fins are constructed. The parabolic fin of varying cross-section is usually analyzed by ordinary calculus approach. The paper analyses parabolic fin of varying cross-section to find the rate of conduction of heat through it via the application of matrix method. The matrix method has been applied successfully in science and engineering problems and also comes out to be very effective tool to find the temperature distribution and rate of conduction of heat through a parabolic fin.

Cretaceous Geology, Age-Differences and Economic Geology of Gidan Alfarma Environ, Northwestern Nigeria

In this present study, the geology and economic aspect of lithological units of Sokoto Basin, sheet 4 South West Sokoto, part of Nigerian Sedimentary Basins were studied. It is bounded by latitudes N 13° 36' 30"- N 13° 40' 45" and longitudes E 05° 38' 00"- E 05° 40' 44"to gently undulating plain which was mapped on the scale of 1:25,000. The methodology adopted was mainly primary data which involved reconnaissance survey and actual or full field survey. The economic deposits include clays/ shale, lateritic ironstones, limestone, phosphate and gypsum, which are mined by the local artisanal miners.

Iodine Status of School Age Children 6-12 Years in Umuahia South LGA of Abia State, Nigeria

Background: Iodine deficiency disorders have continued to be a significant health problem in some Nigerian communities despite universal salt iodization. Objective: This study was designed to assess the iodine status of school age children (6-12 years) in Umuahia South LGA of Abia State, Nigeria. Methods: A total of 414 school children were studied. Urine samples were obtained from 84 school children, 30 males and 54 females. The background and socio-economic information, food habit and dietary intake of the respondents were determined using validated questionnaires. Urinary iodine concentration analysis, using Sandell-Kolthoff reaction was used to determine the iodine status of the children. Chi-square was used to determine the relationship between urinary iodine status of the children and the socio-economic characteristics of their parents. Results: More than half (58.7%) of the children were females while 40.5% were males. About a quarter of the children (40.1%) were 9-10 years, 23.4% were 11-12 years while 36.5% were 6-8 years. Most of the respondents (72.2%) were aware of iodized salt; 14.3% heard about iodized salt from friends, 41.8% heard from the media while 13% heard about iodized salt from the market. Majority of the respondents (94.4%) claimed they consume iodized salt while 4.9% said they use salts that were measured in cups which was not iodized salt. The study revealed that 54.3% of the school children had optimal iodine status while 35.7% had mild iodine deficiency which was higher in males (46.7%) than in females (29.6%). About 5.6% of the respondents had grade 1 goiter. There was a significant association (p< 0.05) between urinary iodine status of the school children and educational status of their fathers’, mothers’, parents’ occupation and income level of fathers. Conclusion: Nutrition education should be aimed at mothers, caregivers, and school children to promote consumption of iodine rich foods.

The Role of Artificial Intelligence in Human Resource Management

This paper deals with the Role of Artificial Intelligence (AI) in Human Resource Management (HRM). We can see in the present globalized world, the customary methods of how business is directed are being tested. There could be not, at this point just nearby firms as contenders, yet associations need to contend continually on a worldwide level as innovation is making the world more modest. This infers that for an association to keep awake to date and maintain an upper hand and accepting these new mechanical advancements is critical. HRM includes a wide range of viewpoints, like preparing workers, enrollment, representative relations, and the advancement of the association. People fill in as a wellspring of information and ability which each association can and should draw on. Hence, obtaining and holding these kinds of workers through enrollment assume a major part today. Because of the significance Human Resource (HR) has for the association, the enrollment interaction by which all this asset is acquired is the way to progress. The enlistment cycle used to be longer and take a lot of time and suggest a lot of administrative works for the spotters, anyway this has as of now gradually began to change with online enrollment getting normal. This paper deals with the various applications and the advantages of implementing Artificial Intelligence in Human Resource management.

A Novel Multi-Criteria Decision Sorting Approach based on Chebyshev's Theorem for Supplier Classification Problem

One of the interesting features of Multi-Criteria Decision Making/ Multiple Attribute Decision Making (MCDM/ MADM) is that a number of techniques that can be used to solve the same problem. In general, three common categories of decision problems are choice problem, ranking problem, and sorting problem. While, the issue of choice and ranking problems is more emphasized in MCDM/ MADM, but the literature weakly consider sorting problems. Several solutions for the above problem are suggested (i.e., Flow sort, AHP-Sort, ELECTRE Tri, etc.). Theoretically, there is no reason to be limited to these techniques. Hence, in this paper we propose a novel multi-criteria sorting method that is based on Chebyshev’s theorem. More specifically, different from other studies on MCDM sorting problems, which put more emphasis on the extension of new models, this work attempts to present a general framework using the Chebyshev’s inequality, to transform the results of conventional MCDM models from ranking format to sort mode. Finally, the proposed approach is compared with three existed models. Compared results show that the proposed method is efficient and the results are stable.