Medical research indicated that narrowing of the retinal blood vessels might be an early indicator of cardiovascular diseases; one of them is hypertensive retinopathy. This paper proposed the new staging method of hypertensive retinopathy by measure the ratio of diameter artery and vein (AVR). The dataset used in this research is the public Messidor color fundus image dataset. The proposed method consists of image resizing using bicubic interpolation, optic disk detection, a region of interest computation, vessel diameter measuring, AVR calculation, and grading the new categories of Hypertensive Retinopathy based on Keith-Wagener-Barker categories. The experiments show that the proposed method can determine the stage of hypertensive retinopathy into new categories.

Wireless multi-hop communication is used widely today though there are many uneven issues related to the process of organizing the transmission, e.g., collisions, caused by simultaneous transmission of two objects that are equally distant toward opposite directions from the receiver, and so on. To address such cases, there are solutions, such as CSMA or NB-IoT. The point is that common solutions propose to use an arbiter (e.g. AP), which controls transmission between hops. The main benefit of the approach is the simplicity, but it lacks flexibility. In other cases, if the arbiter is absent, common methods use intense sequential access to the spectrum and queued control over the radio resource. However, these techniques have selective spectrum usage, i.e., the reserved bandwidth is used only partially. In separate cases, these may impact security and stability as well. The paper discusses a new concept: get rid of arbiter and organize an Ad-hoc network, where resources are dynamically distributed, depending on the needs. The only limitation is that the medium must be able to hold enough bandwidth to organize a set of separate carriers, we call tunnels, for parallel communication. Normally, tunnels are uniformly occupied by hops. So, the primary goal of this work is to develop a new principle for tunnel selection by two or more nodes and define the impact of its parameters onto the resulting performance. The tunnel is then used as a detached medium, shared exclusively between these nodes for communication. Thus, two regimes can be outlined: the regime of picking an appropriate tunnel and regime of communication. In the paper, we will discuss the regime of picking the tunnel, i.e., present the principle that allows doing that, study the influence of its technical parameters on its tactical parameters, and define best conditions for its operation. As a result, we proposed method of time distributed media access control for picking carrier (tunnel), which is more flexible compared to the current solutions as it does not require an arbiter and allows using tunnels simultaneously as well as change them dynamically.

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based data provided by Twitter API, Twitter places and Geocode parameters. We studied these methods to determine their accuracy and their suitability for research. The study concludes that the places method is the more accurate, but it excludes a lot of the data, while the geocode method provides us with more data, but special attention needs to be paid to outliers.

Software Defined Networking (SDN) has emerged as a new networking paradigm that is based on the decoupling between data plane and control plane providing several benefits that include flexible, manageable, and centrally controlled networks. From a security point of view, SDNs suffer from several vulnerabilities that are associated with the nature of communication between control plane and data plane. In this context, software defined networks are vulnerable to distributed denial of service attacks. In particular, the centralization of the SDN controller makes it an attractive target for these attacks because overloading the controller with huge packet volume would result in bringing the whole network down or degrade its performance. Moreover, DDoS attacks may have the objective of flooding a network segment with huge traffic volume targeting single or multiple end systems. In this paper, we propose an entropy-based mechanism for Distributed Denial of Service (DDoS) attack detection and mitigation in SDN networks. The proposed mechanism is based on the entropy values of source and destination IP addresses of flows observed by the SDN controller which are compared to a preset entropy threshold values that change in adaptive manner based on network dynamics. The proposed mechanism has been evaluated through extensive simulation experiments.

This paper utilises programming style on a source code plagiarism and collusion detection to both capture obvious attempts of such academic dishonesty (which characteristics are ignored on most detection techniques) and prioritise non-coincidental similarity to the coincidental one (as only the former can raise suspicion). The technique relies on pairwise programming style similarity to deal with the former and dishonesty probability (how significant is the programming style change between the author’s current submission and previous submissions) to deal with the latter. According to our evaluation, programming style similarity can increase precision since when a code is copied, the programming style can be unconsciously shared (especially for novice students). Dishonesty probability increases not only precision but also recall, f-score, and the resulted similarity degree of suspected pairs; the copied code commonly has different programming style in comparison with the student’s usual style (captured from previous submissions). Our detection technique is comparable to a common technique in academia except that it takes longer processing time as more hints are generated and considered.

A number of research initiatives have recently been launched around the world regarding the conceptualization, specification, design and development principles of the future use of credit cards, storing secret information on them, while most time we use them for online payment. In addition, if it has enough money, we can pay for what we need at any time. Therefore, the goal of this proposed research is to use data mining techniques to predict credit card payment next month. Our proposed system contains five steps: (a) find the suitable database from the internet because this database is not available in Iraq, (b) pre-process the credit card database based on person correlation matrix to determine which feature is less correlated with other to remove it and reduce the time of prediction, (c) split pre-processing database into two parts training and testing dataset, (d) apply TreeNet prediction data mining techniques (TPDMT) on training dataset to test if we need payment next month or do not, find the optimal tree. TreeNet based on Boosting Machine usually makes the predictor to use Decision Trees (DTs). (e ) Finally, pass the testing dataset on the optimal tree results from TPDMT, then using the five measures related to confusion matrix to evaluate the results including “Accuracy (AC), recall or true positive rate (TP), precision (P), F-measure (considers both precision and recall) and Fb”.

The article presents mathematical model of interconnected physical processes on sintering machine during agglomeration of iron ore pellets. The mathematical model uses a system of partial differential equations. Velocity of the horizontal movement of the layer and the vertical velocity of the air movement through the layer as well as phase transition and simple chemical reactions of pellet and air components are taken into account in this model. The purpose of simulation is to determine the time dependency of sinter temperature distributed along the length and height of the layer and then define rational parameters for optimization of metallurgical process. In addition, concentration of sinter and gas components distributed along the height of the layer is computed. The numerical experiment shows that temperature front, which is lower in the layer cross-section, is sharper in comparison with the upper front, where the obtained agglomerate is cooled, as water requires a considerable amount of energy to evaporate. The obtained results are qualitatively consistent with the data in scientific literature.

Social networks have increased their demand extensively for mining texts. Opinions are used to express views and reviews are used to provide information about how a product is perceived. The reviews available online can be available in thousands, so making the right decision to select a product becomes a very tedious task. Several research works has been proposed in the past but they were limited to certain issues discussed in this paper. A dynamic system is proposed based on the features using ontology followed with classification. Classifying information from such text is highly challenging. We propose a novel method of extracting aspects using ontology and further categorizing these sentiments into positive, negative and neutral category using supervised leaning technique. Opinion Mining is a natural language processing task that mine information from various text forums and classify them on the basis of their polarity as positive, negative or neutral. In this paper, we demonstrate machine learning algorithms using WEKA tool and efficiency is evaluated using information retrieval search strategies.

Smart Antenna Systems (SAS) are largely employed in wireless networks for their capabilities to provide very high performances with respect to omnidirectional antennas. The use of adaptive array Smart Antenna could bring to enhance aspects such as energy management, especially in Mobile Ad Hoc Network (MANET), when the network performance closely depends on the battery life of the mobile nodes as well as on the routing protocol features. In this paper, we propose a new adaptive array Smart Antenna System that improves some Ad Hoc Distance Vector (AODV) network protocol features through a mechanism of energy consumption optimization. The system implements the Least Mean Square (LMS) as adaptive algorithm; for this purpose, we perform a co-simulation between Matlab, that implements the LMS algorithm and Omnet++, that provides a complete simulation environment for MANET.

The concept of knowledge potential of agents which serves as a characteristic of a certain amount of knowledge of any individual accumulated over a certain period of life is presented in the paper. The original model approach to information processes of knowledge potential dissemination based on physical analogies, namely the phenomenon of diffusion, is proposed. The redistribution process of two-component knowledge potential is described and the results of numerical experiments are given. The diffusion-like models of knowledge potential distribution in the social and communicative educational environment of the city are built. In particular, the attention is focused on the description (modeling) of knowledge potential redistribution processes within a given social and communicative community (clique), with well-established external and internal relationship between the members (agents) of educational and training processes. Solutions to the modeling problem of interaction (interference) between the knowledge potential components of different agents within a given clique are proposed, a multi-vector of knowledge potential is considered and the results of numerical experiments are given.