International Journal of Information Technology and Computer Science @ijitcs
Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1227
Drugs relationship discovery using hypergraph
Статья научная
Globally, the governments are concerned for saving human life but in recent days, the cost of medicine to save the human life grows rapidly, due to the different combination of the drugs sold by the drug store and based on the drugs availability in the drug store. As a regular routine, the Clinical physicians prescribe the drug name or druggist company name for the patient, instead of prescribing the brand name. For a particular drug name, more number of brand name both generic drugs and combination drugs were available. Almost all the physicians or druggist knows these generic drugs and combination drugs along with their dosage and recommends it for the patient. Since the patients are unaware about the brand name of the medicine, they are buying the costly drug without knowledge. At the same time the patients whoever provide the review on the drug consumed, mostly gives a negative review. On the other side, Government gives approval for every drug produced year by year and those drugs getting rejected for approval where sent for new alternative extension of chemical formula, as well government bans several combinations of drugs. There should be a database for awareness; it should help physicians, druggist and end user to look for banned and unbanned drug. We have identified that the drug details and their approvals were not maintained in the database. So, the proposed work is (i) to identify and classify the exact drug, which can be used as generic or combination and (ii) to create a banned drug model representation, which was unavailable. A hypergraph-based model named Drugs Relationship Discovery using Hypergraph (DRDH) was constructed as a preliminary design representation for drugs. Here, the drugs combination was considered as a hypervertex and the combination approved for manufacturing in the particular company was considered as an edge, having weight as the price of single dose usage based on Indian government listed drug. With this proposed model as a reference, the banned drugs are listed separately, manufacturing stopped drugs are highlighted with the weight of -1 and the physician or druggist can access the model to ensure the correct drug, their production, and usage. The Time complexity has been analyzed for the hypergraph, which was constructed based on the details of relationship identified among the drugs. Using the parameters of the list of drugs used in India on fever and the common cold, comparison over time taken to identify the relationship has also been done.
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Dual Amplitude-Width PPM for Free Space Optical Systems
Статья научная
The PPM (Pulse Position Modulation) is commonly used in Free Space Optic (FSO) systems owing to its power efficiency, but it shows a rapid decline in spectral efficiency with increase in the power efficiency and moderate data rate. In order to improve these two parameters, we present a modified modulation scheme of the existing PPM, on the basis of PPM, PAM (Pulse Amplitude Modulation) and PWM (Pulse Width Modulation). This modified version called DAWPPM (Dual Amplitude-Width PPM). The average power requirements, bandwidth efficiency and normalized data rate are studied after introducing symbol structure. The proposed scheme shows an improvement in terms of data rate and bandwidth efficiency, and when in come to power efficiency it shows lower efficiency compared to PPM. We present theoretical expressions of data rate, spectral efficiency, and normalized power requirements, and we present comparison results to PPM modulation scheme.
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Dual Layer Encryption for IoT based Vehicle Systems over 5G Communication
Статья научная
In modern communication scenario of the 5G era, the service quality is the greatest concern for the users. Also, the concept of security can’t be neglected in this case. In the IoT oriented services like vehicle and VANET systems, the security in the presentation layer of the network is required. This work is over the security mechanism of the service storage and fetching the files for service. A new scheme of multi layered file and content encryption has been produced in order to strengthen the security of the file and data to maintain integrity and confidentiality of the IoT enabled services implemented in 5G. The encryption scheme is designed for the password encryption through asymmetric key cryptography (RSA) along with an enhanced concern of internal content or data security with symmetric key (AES-128) cryptography. This encryption system of double layer for a file makes the study unique and differentiable than other security schemes.
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Duration Estimation Models for Open Source Software Projects
Статья научная
For software organizations that rely on Open Source Software (OSS) to develop customer solutions and products, it is essential to accurately estimate how long it will take to deliver the expected functionalities. While OSS is supported by government policies around the world, most of the research on software project estimation has focused on conventional projects with commercial licenses. OSS effort estimation is challenging since OSS participants do not record effort data in OSS repositories. However, OSS data repositories contain dates of the participants’ contributions and these can be used for duration estimation. This study analyses historical data on WordPress and Swift projects to estimate OSS project duration using either commits or lines of code (LOC) as the independent variable. This study proposes first an improved classification of contributors based on the number of active days for each contributor in the development period of a release. For the WordPress and Swift OSS projects environments the results indicate that duration estimation models using the number of commits as the independent variable perform better than those using LOC. The estimation model for full-time contributors gives an estimate of the total duration, while the models with part-time and occasional contributors lead to better estimates of projects duration with both for the commits data and the lines of data.
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Dynamic Discovery of Web Services using WSDL
Статья научная
Web service technology promises to provide a ynamic integration and interaction of heterogeneous systems, thereby to facilitate fast and efficient cooperation among the entities in cooperative environments. With the surge of Service Oriented Architecture (SOA) and Web Services, service discovery has become increasingly crucial. Web service discovery mechanism retrieves relevant web services from the internet to serve a wide range of users such as service consumers, service developers, service deployers, and service brokers. This paper demonstrates the model for discovery of web services using WSDL processing system and comparison between WSDL(Web Service Description Language) and UDDI(Universal Description Discovery and Integration) based discovery system. The solution leverages WSDL retrieval according to the requested term using horizontal and vertical search and processing WSDL to find suitable web services to satisfy the user request during run time.
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Dynamic High Level Cross Layer Security Mechanisms for Wireless Sensor Networks
Статья научная
In dynamic insensitive application specific network, WSN consists of hundred and thousands of sensor nodes densely deployed in the sensor field. Majority of sensor nodes are static having power limitations, low network throughput, message transfer delays and computation power limits that are major obstacles. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major sources of QoS degradation in WSNs. The potential applications of the WSNs typically range from those in defense, military, environmental monitoring, health monitoring and civilian surveillance applications etc. All of these applications being omnipresent in nature necessitate appropriate heavy secure mechanisms to ensure the data security and privacy. On the other hand, the WSN nodes, being extremely resource constrained, it is really challenging to devise the WSNs security protocols. So need to propose dynamic high level cross layer security mechanism for detecting various attacks and the countermeasures taken to avoid the same without comprising any network resources.
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Dynamic Resource Discovery Scheme for Vehicular Cloud Networks
Статья научная
To discover computing resources available for any application before they are allocated to requests dynamically on demand, developing effective mechanism for resource discovery in Vehicular Cloud Networks (VCN) is very important. Providing the services to the requested vehicle in time is a major concern in the VCN environment. Dynamic and intelligent resource discovery schemes are essential in VCN environment so that services are provided to the vehicles in time. Resource discovery is key characteristic of VCN. VCN requires intelligent algorithms for resource discovery. Creating a mechanism for resource management and search resources is the largest challenge in VCN. There is a need to consider for dynamic way to discover the resources in the VCN. The lack of intelligence in resource handling, less flexible for dynamic simultaneous requests, and low scalability are issues to be addressed for the resource discovery in VCN. In this paper we proposed dynamic resource discovery scheme in VCN. Proposed resource discovery scheme uses Honey Bee Optimization (HBO) technique integrated with static and mobile agents. Mobile agent collects the vehicular cloud information and static agent intelligently identifies the required resources by the vehicle. Dynamic discovery model will take into account different parameters influencing the task execution time to optimize subsequent schedule. To test the performance effectiveness of the scheme, proposed dynamic resource discovery scheme is compared with fixed time scheduling algorithm. The objective of the proposed scheme is to search the resources in VCN with a minimum delay. The simulation results of the proposed scheme is better than the existing scheme.
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Статья научная
Media Independent Handover (MIH) is a standard proposed by IEEE 802.21 working group to facilitate vertical handover support between heterogeneous networks. Currently, the implementation of the IEEE 802.21 standard supported in ns2, provided by National Institute of Standards and Technology (NIST) considers only the signal strength as a parameter to determine the destination network. Selecting a destination network using only RSS as indicator does not meet the needs of all users. For more accurate choice of destination network, vertical handoff decision should consider the values of different criteria of network as well mobile node. In this paper, we have proposed an improved handoff decision module including additional parameters which considers state of mobile node and network conditions during handoff decision in order to improve the performance. The simulation results shows that the proposed method achieves better performance in terms of throughput, handoff latency and packet drop over the basic handoff scheme. More over the proposed method helps to reduce the unnecessary handoffs by eliminating the ping-pong effect and thus increases overall system performance.
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Статья научная
Electronic Commerce (E-Commerce) has a growing potential in Saudi Arabia, due to widespread use of the internet and the maturity of the Information Technology (IT) infrastructure. The purpose of this paper is to assess the quality of E-Commerce websites in Saudi Arabia, using a proposed evaluation instrument. To achieve this aim, six E-Commerce websites were selected for evaluation and then categorized into three categories: domestic, regional and international. Each category consisted of two E-Commerce websites, with the international website category considered as a benchmark. The six websites were evaluated by sixty participants (n=60) with good web design experience, following a set of guidelines offered by the evaluation instrument. The evaluation instrument described six key evaluation factors: appearance, content, organization, interaction, customer-focus and assurance. Each factor was evaluated by several indicators using a five-point scale ranging from not applicable (0) to very strong (4). To unify the views of all evaluators, a technique was introduced which would show the way in which each indicator was assessed based on several checklists (questions). The results therein revealed that international websites were of higher quality than regional and domestic websites with regard to all aspects of web evaluation. In addition, the quality of regional websites outweighed that of domestic websites with regard to appearance, content, organization, customer-focus and assurance, but not interaction.
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E-learning to m-learning: framework for data protection and security in cloud infrastructure
Статья научная
In recent years, the advancement in internet technologies has greatly altered the learning landscape, thus, a shift from traditional methods of learning to internet based learning platforms. E-learning, m-learning and cloud are some of the most powerful responses to these growing technological shift by the education sectors. Their impact and benefits cannot be over-emphasized with regard to making learning accessible, affordable, available and convenient. In addition, the use of cloud technology has made the world of education more integrated, networked and composite. This makes e-learning and m-learning as highly effective as the conventional method of learning delivery. However, despite these advantages, the security and the protection of learners’ data on this cloud platform have been some of the major challenges to m-learning effective implementation and use. This paper discusses the various benefits of the using m-learning platform and cloud infrastructure in higher education. It also examines the vulnerabilities of the platform as well as other security and privacy challenges regarding the effective implementation of m-learning in cloud infrastructure environment. Finally, it proposes a detailed data protection and security framework that is needed for addressing these issues. It is expected that the proposed framework when fully implemented, will bring about necessary solution to issues relating to the security and data protection of m-learners in cloud computing environment, increase trust in the use of the system as well as enhance the m-learning platforms.
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ECADS: An Efficient Approach for Accessing Data and Query Workload
Статья научная
In current scenario a huge amount of data is introduced over the web, because data introduced by the various sources, that data contains heterogeneity in na-ture. Data extraction is one of the major tasks in data mining. In various techniques for data extraction have been proposed from the past, which provides functionali-ty to extract data like Collaborative Adaptive Data Shar-ing (CADS), pay-as-you-go etc. The drawbacks associat-ed with these techniques is that, it is not able to provide global solution for the user. Through these techniques to get accurate search result user need to know all the de-tails whatever he want to search. In this paper we have proposed a new searching technique "Enhanced Collaborative Adaptive Data Sharing Platform (ECADS)" in which predefined queries are provided to the user to search data. In this technique some key words are provided to user related with the domain, for efficient data extraction task. These keywords are useful to user to write proper queries to search data in efficient way. In this way it provides an accurate, time efficient and a global search technique to search data. A comparison analysis for the existing and proposed technique is pre-sented in result and analysis section. That shows, pro-posed technique provide better than the existing tech-nique.
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Ear Biometric System using GLCM Algorithm
Статья научная
Biometric verification is a mean by which a person can be uniquely authenticated by evaluating some distinguishing biological traits. Fingerprinting is the ancient and the most widely used biometric authentication system today which is succeeded by other identifiers such as hand geometry, earlobe geometry, retina and iris patterns, voice waves and signature. Out of these verification methods, earlobe geometry proved to be most efficient and reliable option to be used either along with existing security system or alone for one level of security. However in previous work, the pre-processing was done manually and algorithms have not necessarily handled problems caused by hair and earing. In this paper, we present a more systematic, coherent and methodical way for ear identification using GLCM algorithm which has overcome the limitations of other successful algorithms like ICP and PCA. GLCM elucidates the texture of an image through a matrix formed by considering the number of occurrences of two pixels which are horizontally adjacent to each other in row and column. Pre-processing techniques and algorithms will be discussed and a step-by-step procedure to implement the system will be stated.
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Ear Biometrics in Human Identification System
Статья научная
Biometrics is physical or behavior characteristics that can be used for human identification. We propose the ear as a biometric and investigate it with both 2D and 3D data. The ICP-based algorithm also demonstrates good scalability with size of dataset. These results are encouraging in that they suggest a strong potential for 3D ear shape as a biometric. Multi-biometric 2D and 3D ear recognition are also explored. The proposed automatic ear detection method will integrate with the current system, and the performance will be evaluated with the original one. The investigation of ear recognition under less controlled conditions will focus on the robustness and variability of ear biometrics. Multi-modal biometrics using 3D ear images will be explored, and the performance will be compared to existing biometrics experimental results.
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Early Detection and Classification of Melanoma Skin Cancer
Статья научная
Melanoma is a form of cancer that begins in melanocytes (cells that make the pigment melanin). It can affect the skin only, or it may spread to the organs and bones. It is less common, but more serious and aggressive than other types of skin cancer. Melanoma can be of benign or malignant. Malignant melanoma is the dangerous condition, while benign is not. In order to reduce the death rate due to malignant melanoma skin cancer, it is necessary to diagnose it at an early stage. In this paper, a detection system has been designed for diagnosing melanoma in early stages by using digital image processing techniques. The system consists of two phases: the first phase detects whether the pigmented skin lesion is malignant or benign; the second phase recognizes malignant melanoma skin cancer types. Both first and second phases have several stages. The experimental results are acceptable.
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Early Formalization of AI-tools Usage in Software Engineering in Europe: Study of 2023
Статья научная
This scientific article presents the results of a study focused on the current practices and future prospects of AI-tools usage, specifically large language models (LLMs), in software development (SD) processes within European IT companies. The Pan-European study covers 35 SD teams from all regions of Europe and consists of three sections: the first section explores the current adoption of AI-tools in software production, the second section addresses common challenges in LLMs implementation, and the third section provides a forecast of the tech future in AI-tools development for SD. The study reveals that AI-tools, particularly LLMs, have gained popularity and approbation in European IT companies for tasks related to software design and construction, coding, and software documentation. However, their usage for business and system analysis remains limited. Nevertheless, challenges such as resource constraints and organizational resistance are evident. The article also highlights the potential of AI-tools in the software development process, such as automating routine operations, speeding up work processes, and enhancing software product excellence. Moreover, the research examines the transformation of IT paradigms driven by AI-tools, leading to changes in the skill sets of software developers. Although the impact of LLMs on the software development industry is perceived as modest, experts anticipate significant changes in the next 10 years, including AI-tools integration into advanced IDEs, software project management systems, and product management tools. Ethical concerns about data ownership, information security and legal aspects of AI-tools usage are also discussed, with experts emphasizing the need for legal formalization and regulation in the AI domain. Overall, the study highlights the growing importance and potential of AI-tools in software development, as well as the need for careful consideration of challenges and ethical implications to fully leverage their benefits.
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Early Stage Disease Diagnosis System Using Human Nail Image Processing
Статья научная
Human's hand nail is analyzed to identify many diseases at early stage of diagnosis. Study of person hand nail color helps in identification of particular disease in healthcare domain. The proposed system guides in such scenario to take decision in disease diagnosis. The input to the proposed system is person nail image. The system will process an image of nail and extract features of nail which is used for disease diagnosis. Human nail consist of various features, out of which proposed system uses nail color changes for disease diagnosis. Here, first training set data is prepared using Weka tool from nail images of patients of specific diseases. A feature extracted from input nail image is compared with the training data set to get result. In this experiment we found that using color feature of nail image average 65% results are correctly matched with training set data during three tests conducted.
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Early and Accurate Diagnosis of a Neurological Disorder Epilepsy Using Machine Learning Techniques
Статья научная
An epileptic seizure is a type of seizure induced by aberrant brain activity caused by an epileptic condition, which is a brain Central Nervous System disorder (CNS). CNSs are relatively prevalent and include a wide range of symptoms, including loss of awareness, and strange behaviour. These symptoms frequently result in injuries as a result of walking imbalance, tongue biting, and hearing loss. For many researchers, detecting a prospective seizure in advance has been a difficult undertaking. In this research work we have used non-imaging data and applied supervised learning algorithms to determine the classification of epilepsy and try to improve the efficiency of the model, compared to the existing ones. Random Forest algorithm was found to have highest accuracy compared to other machine learning models. The paper can be helpful in diagnosing high-risk brain diseases and predicting diseases such as Alzheimer's with symptoms challenging to predict and diseases with overlapping symptoms and overlapping symptoms and attribute values. The scope of the research work can be further extended to determine at which stage the epilepsy is present in a patient, in order to provide a correct diagnosis and medical treatment.
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Educational data mining: a case study perspectives from primary to university education in Australia
Статья научная
At present there is an increasing emphasis on both data mining and educational systems, making educational data mining a novel emerging field of research. Educational data mining (EDM) is an attractive interdisciplinary research domain that deals with the development of methods to utilise data originating in an educational context. EDM uses computational methodologies to evaluate educational data in order to study educational questions. The first part of this paper introduces EDM, describes the different types of educational data environments, diverse phases of EDM, the applications and goals of EDM, and some of the most promising future lines of research. Using EDM, the second part of this paper tracks students in Australia from primary school Year 1 through to successful completion of high school, and, thereafter, enrolment in university. The paper makes an assessment of the role of student gender on successive rates of educational completion in Australia. Implications for future lines of enquiry are discussed.
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Статья научная
Project management information systems have their proven position as an effective tool for achieving project management success in terms of the successful realization of the project regarding time, cost and quality. Recent research results have indicated that quality of project management information system output information is positively and significantly related to project management information system application and project management factors and revealed the empirical support. However, getting the reporting quality of the project status report, monthly generated from the project management information system based on the information timely maintained by the project managers, responsible for ERP implementation up to the satisfactory level at any time, can be problematic without having a systematic approach implemented. This article is to discuss how the continuous quality improvement based on the plan-do-check-act cycle was conducted on the reporting quality of the project status report from project management information system generated by the project managers, for achieving project management success in ERP projects implemented by a solution provider for their customers in the various industries in Japan. The results of the study indicate that the continuous improvement on the reporting quality of project management information system was found to be effective in achieving quality of project management information system output information to help managers in decision making, planning, organizing and controlling the project. It was also found to be effective in positively influencing achievement of project management success in terms of respecting the time, cost and quality.
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Effective use of lessons learned to conduct the project review for ERP implementation
Статья научная
According to a recent study, it has been said that “lessons learned” is one of the most important and “value added” aspects of the project management lifecycle. However, it has been reported that it is often the most ignored part of finishing a project. Various reasons have been offered for this phenomenon. This article describes the systematic approach to initiate the project review on the specific project identified for requiring the formal quality audit based on the use of project management information system for having the execution date fixed by the independent quality reviewer with the project manager. Then, the project review process is started by retrieving the lessons learned data from the lessons learned repository, which were collected from the previous project reviews for the relevant ERP implementation projects, for the preparation of conducting the project document review and project stakeholder interviews. A case study methodology was applied to the historical lessons learned data of the ERP implementation projects conducted by the solution provider for their customers in the various industries in Japan, which were retrieved for a period of four years from 2014 to 2017 to analyze how the lessons learned collected from the project reviews of the earlier projects were reused in those of the succeeding projects conducted during the period. Use of lessons learned based on the past project review results was found to be effective in focusing on the specific areas projected for improvement during the processes of conducting the project document review and project stakeholder interviews, as well as putting together the practical recommendations for the findings to finalize the results of the project review, which were to be formally presented and submitted to the customer as the results of the quality audit.
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