International Journal of Advanced Networking and Applications

4263-4269

Authors: Koffka Khan, Wayne Goodridge

Stochastic Dynamic Programming (SDP) is an important class of optimization which has recently been used in the area of dynamic adaptive streaming over HTTP (DASH). Though DASH is very popular method of video delivery in recent years it is plagued with problems when multiple players share a bottleneck link. Thus, this area has become a very active area of research. Two works which implement SDP in DASH are selected and their performances compared against the Conventional DASH player. It is shown that SDP works well for various network conditions.

4277-4282

Authors: Francisco Ángel Luna Hernández; Mayra Hernández Oramas; Victor Manuel Arias Peregrino

Nowadays there are serious global problems, among them, the bad air quality in urban zones stands out, and also the lack of healthy food to guarantee quality feeding. According with some information of the United Nations Organization for agriculture and feeding, the global population is expected to increase to reach 8300 millions, and for that reason objectives for the sustainable development were fixed in the 2030 Agenda. In Mexico, the 2013-2018 Development Plan in the goal National IV Mexico Prospero is looking to guarantee the security in feeding, that is why an opportunity area has been identified in which we can set innovations and new technology. The main objective of this project was to develop an Autonomous Urban Garden, which allows to plant and care for different daily consumption foods on the roofs or roofs of houses or buildings through the Arduino platform and various sensors (soil moisture, rain, humidity and temperature), they can convert a large part of the carbon dioxide into oxygen, they will provide food to a family, ensuring that they are consumable since they themselves would be in charge of planting and harvesting.

4289-4293

Authors: Ayax Israel Isidro Alvarado; Victor Manuel Arias Peregrino; Dulce María León de la O; Alejandro Hernández Cadena; Jose Ángel Jesus Magaña

Visual disability is a condition that affects 285 million people around the world, this sector of the society has a lot of tools for displacement, since a simple white cane that is the first thing that comes to our mind talking about visual disability to some technologic devices that assists them, nevertheless, these devices attack different difficulties, such as the detection of objects in front or the reading of signs in the public thoroughfare. However, there is a difficulty that has not been addressed; the detection of cavities or subsidence in the ground, this section must be taken into account as it can cause very serious accidents and for this reason a device designed to overcome this need is designed.

4298-4304

Authors: Amira Hassan Abed; Mona Nasr; Walaa Saber

Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.

4309-4320

Authors: Sanaa Abou Elhamayed; Samah Osama M. Kamel

Spam Email messages have a big problem either for users or for the Internet service providers. The content of such messages may contain viruses and bad information. The spam messages also occupy a huge amount of space on the mail boxes. So, the process of Emails' classification is very important to be analyzed and discussed. This research work aims at classifying the email messages into either spam or non-spam. The E-mail messages or a dataset can be represented in a matrix form. The rows of the matrix are representing the instances (messages) while the columns are representing the features of such instances. K-Nearest Neighbor (KNN) and Naïve Bayes (NB) are two classifiers where they are used to classify the email messages. The proposed approach based on partitioning the dataset into segment and compared with the adopted approach. Moreover, feature selection methods are adopted to choose the significant features and eliminate the others to avoid processing overheads. The choice of the relevant features plays an important role of the classification accuracy. In this work, some feature selection methods are adopted, analyzed, and operated. The performance of such methods is compared. Moreover, a feature selection method is proposed and discussed. The performance of the proposed feature selection method is compared with the adopted ones. This work is operated on a chosen dataset taken from the Internet. The dataset contains about four-thousand messages with fifty-eight features. Moreover, the dataset is supported with a target feature representing the class labels. From the practical experiments it is shown that the performance of the proposed method is better than the adopted ones. It is also expected that the proposed method is applicable to other datasets for other application domains.