Designing a library management system for Gazi Husrev-beg library using data structure and algorithm

Islamic manuscripts, documents, and religious books go way back in the early ages. These have been preserved at Balkans in the library named Gazi Husrev-beg, Library in an extensive manner. The premises are situated in the vicinity of a mosques complex called Sarajevo where the massive collection is articulated and catalogued in a brand new manner. It has a rich database in learning the Ottoman Empire and more specifically the Balkans in precision. The library was officially started in 2014 stating to be a state-of-art for the aspirers, researchers, historians, archeologists and every enthusiast as well as for general public. This research paper is devised in order to formulate a structure for library management system that can help preserve the age old assets like books, manuscripts, journals, articles, DVDs, etc. Everything is electronically managed and stored in a peculiar format. In order to keep a note on the entire system, the structure is beneficial to students, professors, librarians, public visitors etc. The process of issuing a given entity (book, or journal, or manuscript or anything from the library) and returning is kept a digital track and predefined penalty is cited to the individual if the returning of entity is late, or damaged, or misplaced. To maintain this procedure in a manual format might be confusing and tedious. To overcome the stress of maintaining this manually, a data structure is prepared, and algorithms are formed to get access of the library from multiple places of Gazi Husrev-beg Library

An Analysis of the Requirements for Efficient Protocols in WBAN

Wireless Body Area Networks (WBAN) plays a major role in the advancement of technology, particularly for diagnosising the many life threatening diseases as well as providing real-time health monitoring. The objective of this paper is to study and analyze the problems of protocols in WBAN to provide the requirements related to health care in a medical environment. The protocols need to be energy efficient and reliable as well. To date, several metrics, such as channel utilization and energy efficiencies are defined. This research provides a clear outlook on the types of routing protocols and the problems related to the losses and distribution of data in a medical environment, thus meeting energy efficiency, low delay and reliability

A survey: Issues and challenges of communication technologies in WBAN

Wireless Body Area Network (WBAN) refers to a group of small intelligent electronic devices placed on the human body to monitor its vital signals. It provides a continuous health monitoring of a patient without any constraint on his/her normal daily life activities through the health care applications. Due to the strong heterogeneous nature of the applications, data rates will vary strongly, ranging from simple data at a few Kbits/s to the video stream of several Kbits/s. Data can also be sent in bursts, which means that it is sent at a higher data rate during the bursts. This study covers the main requirements of communication technologies that are used in WBAN comprise of two major parts. The first part, which presents the short-range classification, gives a specialized outline of a few standard wireless technologies that are short-ranged. These are introduced as contenders for intra-BAN communications for communications inside a Body Area Network (BAN) and between the elements

Survey: Benefits of integrating both wireless sensors networks and cloud computing infrastructure

Cloud computing has the capabilities of powerful processing and scalable storage with the ability of offline and online data analysis and mining of the collected sensed data from body areas networks. Cloud computing can be considered as the main enabler for modern manufacturing industries. Cloud computing can efficiently serve key areas of manufacturing by aspects of the pay-as-you-go business model, scaling up and down production according to certain demands, more customized solutions, and flexible deployments. In cloud manufacturing, the distributed sensors and resources can be managed in centralized architecture that allows cloud users to request more specific product design, testing at all the stages of the product. This study covers the main points of Integrating Both Wireless Sensors Networks and Cloud Computing Infrastructure and gives a view of the various advantage and disadvantages of methods in integration

Innovative technologies of wireless sensor network: The applications of WBAN system and environment

Wireless Body Area Networks (WBAN) have risen as a key innovation for providing real-time patient health care and diagnosing many life-threatening diseases. The principle adopted by health service providers is providing convenience for patients in need of health care, allowing them comfortable with the movement and constant monitoring with a reduction in health care costs. This study presented the basic concept and general background of the main WBAN system with applications. The current models for on-body and embedded WBANs, sensor node features, and sensor schemes for information via negation are used in the WBAN

Automatic Wireless Nurse Caller

The nurse caller device is used as a special communication device between the patient and the nurse within the hospital area as a means of speeding the nurse's time response in providing immediate care to the patient. The designed wireless-based nurse caller device made installation easier and neater. The remote used a Bluetooth module MH-10 connected to the ATMega8 microcontroller as the sender and receiver. The data process using a microcontroller ATMega8 produced characters on the LCD, turned on the LED, and activated the buzzer to call the nurse. The results of the test on the device showed that the farthest distance taken by the HM-10 Bluetooth module in the open area (outdoor) was about 45 meters, and the closed area (indoor) was about 20 meters

Improving face recognition by elman neural network using curvelet transform and HSI color space

In this paper, a suggested algorithm was proposed to increase the efficiency of the Elman neural algorithm in face recognition. The proposed algorithm was studied on the images of 20 students from the Department of Computer Science, Tikrit University. First step creates dataset of faces, second step convert color space to HSI and using saturation layer, image decomposition using curvelet transform, feature extraction using Principle component analysis, and final step face recognition using Elman neural network. after applying proposed algorithm, the rate of face recognition 94%

Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set

These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about the cancer disease detection. Developing a proposed data mining model is useful to diagnose the cancer disease once the cancer detection is accomplished using data mining for the examination and classification of machine learning supervised algorithms

Clustering algorithms subjected to K-mean and gaussian mixture model on multidimensional data set

This paper explored the method of clustering. Two main categories of algorithms will be used, namely k-means and Gaussian Mixture Model clustering. We will look at algorithms within thesis categories and what types of problems they solve, as well as what methods could be used to determine the number of clusters. Finally, we will test the algorithms out using sparse multidimensional data acquired from the usage of a video games sales all around the world, we categories the sales in three main standards of high sales, medium sales and low sales, showing that a simple implementation can achieve nontrivial results. The result will be presented in the form of an evaluation of there is potential for online clustering of video games sales. We will also discuss some task specific improvements and which approach is most suitable