Computer Science and Information Technologies

Journal Information
ISSN / EISSN : 2722-323X / 2722-3221
Current Publisher: Institute of Advanced Engineering and Science (10.11591)
Total articles ≅ 11

Latest articles in this journal

Merlin Florrence Joseph, Ravi Lourdusamy
Computer Science and Information Technologies, Volume 1, pp 61-77; doi:10.11591/csit.v1i2.p61-77

Visualization is a technique of creating images, graphs or animations to share knowledge. Different kinds of visualization methods and tools are available to envision the data in an efficient way. The visualization tools and techniques enable the user to understand the knowledge in an easy manner. Nowadays most of the information is presented semantically which provides knowledge based retrieval of the information. Knowledge based visualization tools are required to visualize semantic concepts. This article analyses the existing semantic based visualization tools and plug-ins. The features and characteristics of these tools and plug-ins are analyzed and tabulated.
Shrutika Khobragade, Rohini Bhosale, Rahul Jiwane
Computer Science and Information Technologies, Volume 1, pp 78-83; doi:10.11591/csit.v1i2.p78-83

Cloud Computing makes immense use of internet to store a huge amount of data. Cloud computing provides high quality service with low cost and scalability with less requirement of hardware and software management. Security plays a vital role in cloud as data is handled by third party hence security is the biggest concern to matter. This proposed mechanism focuses on the security issues on the cloud. As the file is stored at a particular location which might get affected due to attack and will lost the data. So, in this proposed work instead of storing a complete file at a particular location, the file is divided into fragments and each fragment is stored at various locations. Fragments are more secured by providing the hash key to each fragment. This mechanism will not reveal all the information regarding a particular file even after successful attack. Here, the replication of fragments is also generated with strong authentication process using key generation. The auto update of a fragment or any file is also done here. The concept of auto update of filles is done where a file or a fragment can be updated online. Instead of downloading the whole file, a fragment can be downloaded to update. More time is saved using this methodology.
Sridhar Iyer
Computer Science and Information Technologies, Volume 1, pp 54-60; doi:10.11591/csit.v1i2.p54-60

In the current work, for Space Division Multiplexing based Optical Networks (SDM-b-OTNs), we investigate the performance of various switching methods with a variation in traffic evolution over different time frame periods. Initially, comparison of the existing methods viz., independent switching (InSw), frequency switching (FqSw), and space switching (SpSw) demonstrates that (i) over longer periods of time frame, FqSw provisions low network usage, and (ii) SpSw offers low network usage for shorter periods of time frame; however, as time frame increases to longer periods, SpSw starts to outperform InSw. Next, we investigate a hybrid switching (HySw) method which begins by implementing InSw and then shifts to the use of SpSw after the activation of specific numbers of space channels. HySw is observed to provision substantial savings on the costs incurred for switching, and with lower space channel values it also offers a balance in the trade-off which occurs between the costs associated for activating the space channels and that incurred for switching. Lastly, a comparison of InSw, SpSw, and HySw considering mixed line rate (MLR) demands shows that the space channels assigned in the ‘in-between’ periods of time frame can be reduced by shifting from InSw to SpSw in the starting periods of time frame.Overall, from the results it is inferred that the network performance only slightly depends on the MLR traffic, and over longer periods of time frame, in comparison to InSw, the significant benefits of SpSw and HySw remains conserved.
Mohamed Maher Ben Ismail
Computer Science and Information Technologies, Volume 1, pp 84-92; doi:10.11591/csit.v1i2.p84-92

Recently, deep learning has been coupled with notice- able advances in Natural Language Processing related research. In this work, we propose a general framework to detect verbal offense in social networks comments. We introduce a partitional CNN-LSTM architecture in order to automatically recognize ver- bal offense patterns in social network comments. Specifically, we use a partitional CNN along with a LSTM model to map the social network comments into two predefined classes. In particular, rather than considering a whole document/comments as input as performed using typical CNN, we partition the comments into parts in order to capture and weight the locally relevant information in each partition. The resulting local information is then sequentially exploited across partitions using LSTM for verbal offense detection. The combination of the partitional CNN and LSTM yields the integration of the local within comments information and the long distance correlation across comments. The proposed approach was assessed using real dataset, and the obtained results proved that our solution outperforms existing relevant solutions.
Arpita Shah, Narendra Patel
Computer Science and Information Technologies, Volume 1, pp 39-46; doi:10.11591/csit.v1i2.p39-46

Of late Multitenant model with In-Memory database has become prominent area for research. The paper has used advantages of multitenancy to reduce the cost for hardware, labor and make availability of storage by sharing database memory and file execution. The purpose of this paper is to give overview of proposed Supple architecture for implementing in-memory database backend and multitenancy, applicable in public and private cloud settings. Backend in-memory database uses column-oriented approach with dictionary based compression technique. We used dedicated sample benchmark for the workload processing and also adopt the SLA penalty model. In particular, we present two approximation algorithms, Multi-tenant placement (MTP) and Best-fit Greedy to show the quality of tenant placement. The experimental results show that Multi-tenant placement (MTP) algorithm is scalable and efficient in comparison with Best-fit Greedy Algorithm over proposed architecture.
Merlin Florrence
Computer Science and Information Technologies, Volume 1, pp 47-53; doi:10.11591/csit.v1i2.p47-53

Ontologies are emerging technology in building knowledge based information retrieval systems. It is used to conceptualize the information in human understandable manner. Knowledge based information retrieval are widely used in the domain like Education, Artificial Intelligence, Healthcare and so on. It is important to provide multilingual information of those domains to facilitate multi-language users. In this paper, we propose a MOnto (Multilingual Ontology) methodology to develop multilingual ontology applications for education domain. New algorithms are proposed for merging and mapping multilingual ontologies.
Noureddine Maouhoub, Khalid Rais
Computer Science and Information Technologies, Volume 1, pp 26-31; doi:10.11591/csit.v1i1.p26-31

Series resistance and mobility attenuation parameter are parasitic phenomena that limit the scaling of advanced MOSFETs. In this work, an iterative method is proposed to extract the series resistance and mobility degradation parameter in short channel MOSFETs. It also allows us to extract the surface roughness amplitude. The principle of this method is based on the exponential model of effective mobility and the least squares methods. From these, two analytical equations are obtained to determine the series resistance and the low field mobility as function of the mobility degradation. The mobility attenuation parameter is extracted using an iterative procedure to minimize the root means squared error (RMSE) value. The results obtained by this technique for a single short channel device have shown the good agreement with measurements data at strong inversion.
Veera Boopathy E
Computer Science and Information Technologies, Volume 1, pp 13-16; doi:10.11591/csit.v1i1.p13-16

Traffic in urban areas is increasing day by day which leads to most critical issues of traffic management this paper proposes a smart and fully automatic traffic control system that will detect and control the congestion in real time, detect a stolen vehicle and also passes emergency vehicles smoothly with the use of passive RFID device. This effectively reduces travel delays and relieves congestion, it is necessary to control lane merge behaviors of freeway. Depending upon the count of vehicles green passage will be set dynamically and the proposed system provides special privileges for emergency vehicles like police vehicle, ambulance, VIP vehicles, etc.
Harya Gusdevi, Ade Setya P, Puji Handini Zulaeha
Computer Science and Information Technologies, Volume 1, pp 32-38; doi:10.11591/csit.v1i1.p32-38

The conversion of kerosene use in household to gas, in addition to the decision of the Republic of Indonesia minister in relation to the movement of kerosene to gas, gas also given an affordable price, how to use it more effectively. But the public is also expected to be careful about how to use it, because the gas is explosive and leaking causing unpleasant odor (gas leak) even a more dangerous side effect is the explosion of gas cylinders. To evercome these problems then need a tool that can detect gas leakage, in order to prevent gas leakage early. Therefore the authors designed a device that can detect gas leakage by using Sensor Mq-2 and will issue sound gas alarm warning leak by Modul ISD 1760, and will stop the gas flow from the tube to the stove using a Solenoid Valve. There is also a Flame Sensor’s hardware to detect a fire if there is a spark emerging and spraying water into spots that are likely to spark fire. All hardware will be in if using ATMega 328microcontroller.Monitoring can use android smartphone, with the application that can send a warning to the mobile phone.
Priyanka Verma, Anjali Goyal, Yogita Gigras
Computer Science and Information Technologies, Volume 1, pp 1-12; doi:10.11591/csit.v1i1.p1-12

Phishing is networked theft in which the main motive of phishers is to steal any person’s private information, its financial details like account number, credit card details, login information, payment mode information by creating and developing a fake page or a fake web site, which look completely authentic and genuine. Nowadays email phishing has become a big threat to all, and is increasing day by day. Moreover detection of phishing emails have been considered an important research issue as phishing emails have been increasing day by day. Various techniques have been introduced and applied to deal with such a big issue. The major objective of this research paper is giving a detailed description on the classification of phishing emails using the natural language processing concepts. NLP (natural language processing) concepts have been applied for the classification of emails, along with that accuracy rate of various classifiers have been calculated. The paper is presented in four sections. An introduction about phishing its types, its history, statistics, life cycle, motivation for phishers and working of email phishing have been discussed in the first section. The second section covers various technologies of phishing- email phishing and also description of evaluation metrics. An overview of the various proposed solutions and work done by researchers in this field in form of literature review has been presented in the third section. The solution approach and the obtained results have been defined in the fourth section giving a detailed description about NLP concepts and working procedure.
Back to Top Top