Wednesday, September 30, 2020

RESEARCH ON CRO'S DILEMMA IN SAPIENS CHAIN: A GAME THEORY METHOD

Author :  Jinyu Shi

Affiliation :  Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education

Country :  China

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract

In recent years, blockchain-based techniques have been widely used in cybersecurity, owing to the decentralization, anonymity, credibility and not be tampered properties of the blockchain. As one of the decentralized framework, Sapiens Chain was proposed to protect cybersecurity by scheduling the computational resources dynamically, which were owned by Computational Resources Owners (CROs). However, when CROs in the same pool attack each other, all CROs will earn less. In this paper, we tackle the problem of prisoner’s dilemma from the perspective of CROs. We first define a game that a CRO infiltrates another pool and perform an attack. In such game, the honest CRO can control the payoffs and increase its revenue. By simulating this game, we propose to apply Zero Determinant (ZD) strategy on strategy decision, which can be categorized into cooperation and defecting. Our experimental results demonstrate the effectiveness of the proposed strategy decision method.

Keyword :  Cybersecurity, Blockchain, Game Theory, CRO's Dilemma

For More Detailshttps://airccj.org/CSCP/vol8/csit89508.pdf

Sunday, September 27, 2020

AUDIO ENCRYPTION ALGORITHM USING HYPERCHAOTIC SYSTEMS OF DIFFERENT DIMENSIONS

 Author :  S. N. Lagmiri

Affiliation :  IRSM, Higher Institute of Management Administration and Computer Engineering

Country :  Morocco

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

Data security has become an important concern for communication through an insecure channel because the information transferred across the networks has a large chance of unauthorized access. The available encryption algorithms that are primarily used for text data may not be suitable for multimedia data such as sound. Hyperchaotic systems are generally proposed as a solution to multimedia encryption, because of their random properties and the high sensitivity of initial conditions and system parameters. In this paper, audio data encryption with different dimensional hyperchaotic systems has been presented. The proposed hyperchaotic systems exhibit excellent chaotic behavior. To demonstrate its application to the processing of multimedia encryption, the three systems are applied with an algorithm based on the key generation from the initial conditions for encryption and decryption process. The results of encryption, decryption and statistical analysis of the audio data show that the proposed cryptosystem has excellent encryption performance, high sensitivity to security keys and can be applied for secure real-time encryption.

Keyword :  Audio signal, Hyperchaotic system, Encryption algorithm, Histogram, Correlation, Power spectrum.

For More Detailshttps://airccj.org/CSCP/vol8/csit89507.pdf

Saturday, September 26, 2020

AN INTELLIGENT APPROACH OF THE FISH FEEDING SYSTEM

 Author :  Mohammed M. Alammar

Affiliation :  Department of Electrical Engineering and Electronics, University of Liverpool

Country :  United Kingdom

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

Fish breeding is a promising branch of farming, so the creation of tools for automation of this area is quite relevant. Feeding on fish farms is the main component of the successful functioning of such businesses. However, this process requires an in-depth preparation, as each species of fish has a different food culture, as well as various behaviours during nutrition. Moreover, in the method of feeding fish, farmers must take into account the age, size of the fish, and other characteristics. This paper contains information on the creation of a Preference testing by images processing is considered as the most effective tool that can be used to determine the sensory behaviour of an animal, which can record the eating behaviour of fish and determine the degree of their hunger, and, finally, to feed them. Moreover, small fish are shyer, which provokes their malnutrition. A smart feeding system can solve the issue of uniform the distribution of food for all fishes.

Keyword :  Fish Feeding, Preference testing, Fish Farming, Smart Feeding System, Methods of Fish Feeding.

For More Details https://airccj.org/CSCP/vol8/csit89506.pdf

Thursday, September 24, 2020

LEARNING TRAJECTORY PATTERNS BY SEQUENTIAL PATTERN MINING FROM PROBABILISTIC DATABASES

Author :  Josky Aïzan

Affiliation :  Ecole Doctorale Sciences Exactes et Appliquées

Country :  France

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

In this paper, we use Sequential Pattern Mining from Probabilistic Databases to learn trajectory patterns. Trajectories which are a succession of points are firstly transformed into a succession of zones by grouping points to build the symbolic sequence database. For each zone we estimate a confidence level according to the amount of observations appearing during trajectory in the zone. The management of this confidence allows to reduce efficiently the volume of useful zones for the learning process. Finally, we applied a Sequential Pattern Mining algorithm on this probabilistic databases to bring out typical trajectories.

Keyword :  Trajectory Patterns, Data Mining, Sequential Pattern Mining, Probabilistic Databases

URLhttps://airccj.org/CSCP/vol8/csit89505.pdf

Monday, September 21, 2020

DISASTER INITIAL RESPONSES MINING DAMAGES USING FEATURE EXTRACTION AND BAYESIAN OPTIMIZED SUPPORT VECTOR CLASSIFIERS

 Author :  Yasuno Takato

Affiliation :  Research Institute for Infrastructure Paradigm Shift (RIIPS), Yachiyo Engineering

Country :  Japan

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

Whenever a natural disaster occurs, it is important to quickly evaluate the damage status in high-priority locations. Frequently, owing to the restrictions imposed by the availability of disaster management resources, spatial information is predicted where the infrastructure manager makes an initial response. It is critical that an initial response be effective to mitigate social losses. In recent years, Japan has experienced several great earthquakes with magnitudes of around 6, most notably the Great East Japan earthquake of March 2011 (M9), as well as those striking Kumamoto (April 2016 (M7)), Osaka (June 2018 (M6.1), and Hokkaido (September 2018 (M6.7)). These huge earthquakes occur not only in Japan but around the world, with an earthquake and tsunami striking Indonesia as recently as October 2018. The initial response to future earthquakes is an important issue related to knowledge of natural disasters and to predict the degree of damage to infrastructure using multi-mode usable data sources. In Japan, approximately 5 million CCTV cameras are installed. The Ministry of Land, Infrastructure and Transportation uses 23,000 of these cameras to monitor the infrastructure in each region. This paper proposes a feature extraction damage classification model using disaster images with five classes of damage after the occurrence of a huge earthquake. We present a support vector damage classifier for which the inputs are the extracted damage features, such as tsunami, bridge collapses, and road damage leading to a risk of accidents, initial smoke and fire, and non-disaster damage. The total number of images is 1,117, which we collected from relevant websites that allow us to download records of huge earthquake damage that has occurred worldwide. Using ten pre-trained architectures, we have extracted the damage features and constructed a support vector classification model with a radial basis function, for which the hyper parameters optimize the resul

Keyword :  Disaster Response, Damage Mining, Feature Extraction, Support Vector classifier, Bayesian Optimization

For More Detailshttps://airccj.org/CSCP/vol8/csit89504.pdf

Sunday, September 20, 2020

ENHANCE NMF-BASED RECOMMENDATION SYSTEMS WITH SOCIAL INFORMATION IMPUTATION

Author :  Fatemah Alghamedy

Affiliation :  Department of Computer Science, University of Kentucky, Lexington, Kentucky

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

We propose an NMF (Nonnegative Matrix Factorization)-based approach in collaborative filtering based recommendation systems to improve the Cold-Start-Users predictions since Cold-Start-Users suffer from high error in the results. The proposed method utilizes the trust network information to impute a subset of the missing ratings before NMF is applied. We proposed three strategies to select the subset of missing ratings to impute in order to examine the influence of the imputation with both item groups: Cold-Start-Items and Heavy-Rated-Items; and survey if the trustees' ratings could improve the results more than the other users. We analyze two factors that may affect results of the imputation: (1) the total number of imputed ratings, and (2) the average of imputed rating values. Experiments on four different datasets are conducted to examine the proposed approach. The results show that our approach improves the predicted rating of the cold-start users and alleviates the impact of imputed ratings.

Keyword :  Collaborative filtering, recommendation system, nonnegative matrix factorization, trust, matrix, imputation

For More Detailshttps://airccj.org/CSCP/vol8/csit89503.pdf


Saturday, September 19, 2020

IMPUTING ITEM AUXILIARY INFORMATION IN NMF-BASED COLLABORATIVE FILTERING

Author :  Fatemah Alghamedy

Affiliation :  Department of Computer Science, University of Kentucky, Lexington, Kentucky

Country :  Saudi Arabia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

The cold-start items, especially the New-Items which did not receive any ratings, have negative impacts on NMF (Nonnegative Matrix Factorization)-based approaches, particularly the ones that utilize other information besides the rating matrix. We propose an NMF based approach in collaborative filtering based recommendation systems to handle the New-Items issue. The proposed approach utilizes the item auxiliary information to impute missing ratings before NMF is applied. We study two factors with the imputation: (1) the total number of the imputed ratings for each New-Item, and (2) the value and the average of the imputed ratings. To study the influence of these factors, we divide items into three groups and calculate their recommendation errors. Experiments on three different datasets are conducted to examine the proposed approach. The results show that our approach can handle the New-Item's negative impact and reduce the recommendation errors for the whole dataset.

Keyword :  Collaborative filtering, recommendation system, nonnegative matrix factorization, item auxiliary information, imputation

For More Details https://airccj.org/CSCP/vol8/csit89502.pdf

Thursday, September 17, 2020

COMPARISON OF FOUR ALGORITHMS FOR ONLINE CLUSTERING

Author :  Xinchun Yang

Affiliation :  1Department of Computer Engineering, Centrale Supélec, Pari

Country :  France

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 15, February, 2018

Abstract :

This paper concludes and analyses four widely-used algorithms in the field of online clustering: sequential K-means, basic sequential algorithmic scheme, online inverse weighted K-means and online K-harmonic means. All algorithms are applied to the same set of self-generated data in 2-dimension plane with and without noise separately. The performance of different algorithms is compared by means of velocity, accuracy, purity, and robustness. Results show that the basic sequential K-means online performs better on data without noise, and the K-harmonic means online performs is the best choice when noise interferes with the data.

Keyword :  Sequential Clustering, online clustering, K-means, time-series clustering

For More Details https://airccj.org/CSCP/vol8/csit89501.pdf

Wednesday, September 16, 2020

ANALYSIS OF MOBILE PAYMENT INFLUENCING FACTORS

Author :  Sitalakshmi Venkatraman

Affiliation :  School of Engineering, Construction and Design (IT), Melbourne Polytechnic

Country :  Australia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

With the exponential proliferation of mobile devices in the consumer market, wireless e-business is emerging as a key area to revolutionise industries. In the past few years, industry has witnessed an increase in the adoption of mobile payment and billing methods that leverage on wireless technologies. Yet, the success of mobile payments in businesses much depends on many factors such as, type of wireless technologies used, security options available, the players involved and their influencing m-business models. This paper examines mobile payments in both technical as well as business perspectives. It identifies and analyses the influencing factors from multi-dimensions that would be useful for adopting mobile payments.

Keyword :  Mobile payments, Wireless technologies, Business models. M-commerce

For More Details https://airccj.org/CSCP/vol8/csit88315.pdf


Thursday, September 10, 2020

IMPROVED HANDOVER ALGORITHM FOR PROXY MIPv6 BASED ON AAA SERVER

Author :  PMIPv6; AAA; handover; fast handover

Affiliation :  School of Computer Science & Engineering, South China University of Technology, Guang Zhou

Country :  China

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Keyword :  Hewei Yu

Abstract :

This paper proposes an improved handover algorithm which does not need authenticating again if Mobile Node moves within the same Proxy MIPv6 domain. When MN enters PMIPv6 domain at the first time, it needs to make an AAA authentication. But when MN moves between MAGs in the same domain, it can perform handover procedure without the second times of AAA authentication, and speed the handover process. We built a structure of PMIPv6 including AAA server on NS-2, and proposed an improved handover algorithm for PMIPv6 based on AAA authentication. The simulation results show that the new scheme can effectively reduce the handover latency and ratio of packet loss, and improve network performance.

For More Details https://airccj.org/CSCP/vol8/csit88314.pdf

Wednesday, September 9, 2020

THE WEB-BASED EDUCATION JOURNEY: A CONSTANT LIFELINE

Author :  Vidhu Mitha

Affiliation :  Department of Information Technology, SRM University

Country :  India

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

E-learning has revolutionized our realm in more than just a listable number of ways. But it took a paradigm shift when it entered the threshold of the varsity system. With the prevailing spoonfeeding era, are the students really ¬industry ready? We answer that by confirming a fact: webbased learning has become the oxygen of freshers in the IT Industry instead of the traditional learning done through graduation. Furthermore, are university enforced e-learning assessment systems a true representation of a student's proficiency? This paper is a peep into what webbased e-learning systems are to a student of today's world, by giving an overview of universitylevel e-learning in India deploying an example from SRM University's organizational framework. It assesses a key e-learning trend, the implementation of which bridges the gap between universities and the industry. It is proposed to provide constructive feedback to the elearning community and shine some light on areas of scope for future developments.

Keyword :  web-based learning, e-learning, university

For More Detailshttps://airccj.org/CSCP/vol8/csit88313.pdf

Tuesday, September 8, 2020

IMAGE QUALITY ASSESSMENT- A SURVEY OF RECENT APPROACHES

Author :  Noor Al Madeed

Affiliation :  College of Computer Science and Engineering, Qatar University

Country :  Qatar

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

Image Quality Assessment (IQA) is the process of quantifying degradation in image quality. With the increasedimage-basedapplicationsIQAdeservesextensiveresearch.Inthis paper we have presented popular IQA methods for the three types namely, Full Reference (FR), No Reference (NR) and Reduced Reference (RR). The paper gives comparison of the approaches in terms of the database used, the performance metric and the methods used.

Keyword :  Full reference, image quality assessment, no reference, reduced reference

For More Detailshttps://airccj.org/CSCP/vol8/csit88312.pdf

Sunday, September 6, 2020

IMPLEMENTING UHF RFID READER ON SMARTPHONE PLATFORM FOR IOT SENSING

Author :  Douglas Lautner

Affiliation :  Department of Computer Science, Illinois Institute of Technology

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

As a core component of the Internet of Things technology (IoT), Radio Frequency Identification (RFID) tagged items will add billions, perhaps trillions, of objects to the Internet. As a result, uses of Ultra High Frequency (UHF) RFID sensing become massive ranging from logistics, retail and healthcare to homes and even entire smart cities. Under this trend, mobile UHF RFID scanners also need to evolve. Consumers will interact with their surroundings via tagged RFID items taking full advantage of the advancing IoT. For mainstream consumer smartphones, unfortunately, UHF RFID connectivity has yet to be fully integrated. The major challenges are: 1) the compatibility of an RFID reader module to the host platform, 2) Radio Frequency (RF) signal coexistence interference between the RFID reader and other sensor/RF technologies, and 3) the unacceptable high current drain caused by RFID active scanning. In this paper, we present a design and implementation of a novel modular UHF RFID scanning subsystem, the UHF RFID reader module, on a Motorola Moto-Z smartphone. This module is fully integrated with an Android 7.0 Operating System (OS) and directly interconnects with the low-level smartphone hardware and software framework. With the new antenna design and the signal spectrum analysis, we guarantee the RF isolation of the Mod with the smartphone’s other native wireless components and sensors. Our design and implementation also address the current drain issue and extends the battery life of Moto-Z smartphone up to 30.4 hours with IoT RFID scanning.

Keyword :  UHF RFID, Smartphone design, mobile system architecture, mobile sensing

For More Detailshttps://airccj.org/CSCP/vol8/csit88311.pdf

Friday, September 4, 2020

PREDICTING PLAYERS' PERFORMANCE IN ONE DAY INTERNATIONAL CRICKET MATCHES USING MACHINE LEARNING

Author :  Kalpdrum Passi

Affiliation :  Department of Mathematics and Computer Science, Laurentian University

Country :  Canada

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

Player selection is one the most important tasks for any sport and cricket is no exception. The performance of the players depends on various factors such as the opposition team, the venue, his current form etc. The team management, the coach and the captain select 11 players for each match from a squad of 15 to 20 players. They analyze different characteristics and the statistics of the players to select the best playing 11 for each match. Each batsman contributes by scoring maximum runs possible and each bowler contributes by taking maximum wickets and conceding minimum runs. This paper attempts to predict the performance of players as how many runs will each batsman score and how many wickets will each bowler take for both the teams. Both the problems are targeted as classification problems where number of runs and number of wickets are classified in different ranges. We used naïve bayes, random forest, multiclass SVM and decision tree classifiers to generate the prediction models for both the problems. Random Forest classifier was found to be the most accurate for both the problems.

Keyword :  Naïve Bayes, Random Forest, Multiclass SVM, Decision Trees, Cricket

URLhttps://airccj.org/CSCP/vol8/csit88310.pdf

Tuesday, September 1, 2020

COMPARISON OF BANKRUPTCY PREDICTION MODELS WITH PUBLIC RECORDS AND FIRMOGRAPHICS

Author :  Lili Zhang

Affiliation :  Kennesaw State University

Country :  USA

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 3, February, 2018

Abstract :

Many business operations and strategies rely on bankruptcy prediction. In this paper, we aim to study the impacts of public records and firmographics and predict the bankruptcy in a 12- month-ahead period with using different classification models and adding values to traditionally used financial ratios. Univariate analysis shows the statistical association and significance of public records and firmographics indicators with the bankruptcy. Further, seven statistical models and machine learning methods were developed, including Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and Neural Network. The performance of models were evaluated and compared based on classification accuracy, Type I error, Type II error, and ROC curves on the hold-out dataset. Moreover, an experiment was set up to show the importance of oversampling for rare event prediction. The result also shows that Bayesian Network is comparatively more robust than other models without oversampling.

Keyword :  Bankruptcy Prediction, Public Records, Firmographics, Classification, Oversampling

URLhttps://airccj.org/CSCP/vol8/csit88309.pdf