Computer Engineering Commons^™

A Bibliometric Survey On The Diagnosis Of Plant Leaf Diseases Using Artificial Intelligence, Rutuja Rajendra Patil, Sumit Kumar Dr

Library Philosophy and Practice (e-journal)

Due to uncertain environmental conditions such as untimely rainfall, hailstorms, draught, fog the agriculture sector faces huge loss in crop yield. One of the biggest reason is plant leaf diseases. Therefore the need arises to diagnose the plant leaf diseases beforehand so that the diseases could be avoided and crop yield loss could be minimized. The paper represents the bibliometric study of plant leaf disease diagnosis using Artificial Intelligence. The study focuses on 472 scientific documents such as journals, articles, book chapters publicized in various journals. These documents are extracted from Scopus database after querying it with keywords related to …

Code Smells: A Synthetic Narrative Review, Peter Kokol Prof, Marko Kokol, Sašo Zagoranski

Library Philosophy and Practice (e-journal)

Code smells are symptoms of poor design and implementation choices, which might hinder comprehension, increase code complexity and fault-proneness and decrease maintainability of software systems. The aim of our study was to perform a triangulation of bibliometric and thematic analysis on code smell literature production. The search was performed on Scopus (Elsevier, Netherlands) database using the search string “code smells” which resulted in 442 publications. The Go-to statement was the first bad code smells identified in software engineering history in 1968. The literature production trend has been positive. The most productive countries were the United States, Italy and Brazil. Eight …

Implementation Of Uhf-Rfid Technology In An Academic Library Of Pakistan; A Case Study, Attya Shahid Ms, Naveed Sehar

Library Philosophy and Practice (e-journal)

There are numerous libraries in Pakistan that cannot afford RFID technology because of the limited budget and resources and confronted book theft, low security, and delay services. This paper base an experiment that how libraries can adopt this technology effectively and productively with a lower budget and higher outcomes. The FAST-National University of Computer and Emerging Sciences Library Karachi campuses is the principal library in Pakistan which has adopted UHF-RFID technology with the integration of ILS insignia; SIP II compliance that jointly works with library integrated system and numerous activities can be made through this. An exploratory study conducted in …

Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence, Pooja Kamat, Rekha Sugandhi Dr.

Library Philosophy and Practice (e-journal)

The new industrial revolution called Industry 4.0 is proliferating at its peak. The time is no longer away when the human race is going to witness a huge paradigm shift. Intelligent machines empowered by Artificial Intelligence (AI)will take over the presence of human workers in the industrial manufacturing sector with the target of achieving 100% automation. With the emergence of cut-throat price competition in the product market, it has become equally important to manufacture goods at minimal costs and with the highest quality. Predicting the decrease in machinery efficiency at an earlier stage to accomplish this objective helps to reduce …

Technology Safety Audit In Computer Laboratories Using Iso/Iec 17799 : 2005 (Case Study: Ftk Uin Sunan Ampel Surabaya), Muqoffi Khosyatulloh, Nurul Fariidhotun Nisaa, Ilham, M. Kom

Library Philosophy and Practice (e-journal)

Management audit is very important for assessment of their information technology management to gain efficient and effective business running process. Information technology security as an effort of internal controlling for risk and threat security minimization, is mainly considered due to all learning and lecturing administration activities use information technology. Allso, the implementation of a number of computer labs to facilitate learning processes and access to information in order to support the lectures and personal development of students To find out how secure technology information is, it is then requiring an audit to make sure everything run based on procedure. Management …

Bibliometric Survey Of Privacy Of Social Media Network Data Publishing, Rupali Gangarde Ass. Prof., Amit Sharma Dr., Ambika Pawar Dr.

Library Philosophy and Practice (e-journal)

We are witness to see exponential growth of the social media network since the year 2002. Leading social media networking sites used by people are Twitter, Snapchats, Facebook, Google, and Instagram, etc. The latest global digital report (Chaffey and Ellis-Chadwick 2019) states that there exist more than 800 million current online social media users, and the number is still exploding day by day. Users share their day to day activities such as their photos and locations etc. on social media platforms. This information gets consumed by third party users, like marketing companies, researchers, and government firms. Depending upon the purpose, …

The Art Of Selecting Phd Students: Combination Of Bibliometric And Ahp Approach, Preeti Mulay Dr., Rahul Raghvendra Joshi Prof., Sophia Gaikwad Dr.

Library Philosophy and Practice (e-journal)

For the PhD guide or the advisor selecting the accurate PhD scholar is the most elephantine task. It actually requires an art for the perfect selection; as the length, breadth, depth and volume of PhD work is spread across the years and this relationship between the scholar and the guide should start and flourish positively for the immense experience throughout the PhD process. Hence it was essential to understand bibliometric details including how many researchers have already published their contributions in the form of papers and patents, in the Scopus database. In addition to the bibliometric details, in this study, …

Personality Prediction Through Curriculam Vitae Analysis Involving Password Encryption And Prediction Analysis, Gagandeep Kaur, Shruti Maheshwari

Library Philosophy and Practice (e-journal)

A recruitment process requires an eligibility check, an aptitude evaluation and a psychometric analysis of prospective candidates. The work puts forward an application where the system allows employers to post new job offerings and registered candidates can apply. The application estimates applicant’s emotional aptitude through a psychometric analysis based on a test whereas the professional standard is verified via a technical aptitude test. OCEAN Model is used to assess emotional quotient and predict the personality traits. Machine learning techniques such as Logistic Regression are used for modelling the personality predictor. The details of the candidates are kept secure by using …

Global Research Trend On Cyber Security: A Scientometric Analysis, Somesh Rai, Kunwar Singh Dr, Akhilesh Kumar Varma

Library Philosophy and Practice (e-journal)

Scientometrics is a quantitative analysis of scholarly literature related to a particular subject or area (well defined by some limits, scope and coverage), which helps to understand different aspects about the scholarly literature’s growth in various dimensions of knowledge. Similarly, this study is a quantitative analysis of the Global research trends in cyber security. Some works related to scientometrics of ‘deception, counter-deception in cyberspace’ had been published in 2011, but we have focused on ‘cyber security’ as the topic of research. For analysis we have utilised the published data available in Scopus database, which is directly related to ‘cyber security’. …

Bibliometric Survey On Incremental Clustering Algorithms, Archana Chaudhari, Rahul Raghvendra Joshi, Preeti Mulay, Ketan Kotecha, Parag Kulkarni

Library Philosophy and Practice (e-journal)

For clustering accuracy, on influx of data, the parameter-free incremental clustering research is essential. The sole purpose of this bibliometric analysis is to understand the reach and utility of incremental clustering algorithms. This paper shows incremental clustering for time series dataset was first explored in 2000 and continued thereafter till date. This Bibliometric analysis is done using Scopus, Google Scholar, Research Gate, and the tools like Gephi, Table2Net, and GPS Visualizer etc. The survey revealed that maximum publications of incremental clustering algorithms are from conference and journals, affiliated to Computer Science, Chinese lead publications followed by India then United States. …

Recent Trends, Current Research In Cyberpsychology: A Literature Review, Amarjit Kumar Singh, Pawan Kumar Singh

Library Philosophy and Practice (e-journal)

Cyberpsychology refers to the study of the mind and behavior in the context of interactions with technology. It is an emerging branch, which has focused on the psychological aspects connected to the increasing presence and usages of technology in modern lives. This paper traces recent advancement and trends of Cyberpsychology is an emerging domain of knowledge and goes on the give a literature review of the same. An analysis of the recent research and literature covering 300 most relevant research papers from the period of 2012 to 15, August 2019 was conducted to determine and shape the research pattern based …

Tutorial: Are You My Neighbor?: Bringing Order To Neighbor Computing Problems, David Anastasiu, Huzefa Rangwala, Andrea Tagarelli

Faculty Publications

Finding nearest neighbors is an important topic that has attracted much attention over the years and has applications in many fields, such as market basket analysis, plagiarism and anomaly detection, community detection, ligand-based virtual screening, etc. As data are easier and easier to collect, finding neighbors has become a potential bottleneck in analysis pipelines. Performing pairwise comparisons given the massive datasets of today is no longer feasible. The high computational complexity of the task has led researchers to develop approximate methods, which find many but not all of the nearest neighbors. Yet, for some types of data, efficient exact solutions …

Personality And Technology: Big Five Personality Traits As Descriptors Of Universal Acceptance And Usage Of Technology Utaut., Shohar Bano, Ubaid Ullah Shah, Dr. Sabha Ali

Library Philosophy and Practice (e-journal)

Presently, information professionals are progressively dependent on information and communication technologies to complete their everyday tasks. As, result dependence on PC frameworks, programming and data innovation-related technologies are increasing for better working and providing quality services. Therefore, to understand, analyze and evaluate the acceptance and use of this technology several models of technology acceptance and use have been formulated in information science literature. Using eight such models, Venkatesh, Morris, Davis and Davis proposed a unified model called the Unified Theory of Acceptance and Use of Technology or (UTAUT) model. The UTAUT model has been studied and analyzed in various spheres …

The Scientific Information Exchange General Model At Digital Library Context: Internet Of Things, Nayere Soleimanzade, Asefeh Asemi, Mozafar Cheshmehsohrabi, Ahmad Shabani

Library Philosophy and Practice (e-journal)

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model.

Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is …

Influence Propagation For Social Graph-Based Recommendations, Avni Gulati, Magdalini Eirinaki

Faculty Publications

Social networking is an inevitable behavior of humans living in a society. In recent years, and with the rise of online social networks, personalized recommendations that leverage the social aspect have become a very intriguing domain for researchers. In this work, we explore how influence propagation and the decay in the cascading effect of influence from influential users can be leveraged to generate social graph-based recommendations. Understanding how influence propagates within a social network is itself a challenging problem. Few researchers have considered influence propagation and even fewer have considered decay in the cascading effect of influence in a social …

Accessibility And Decay Of Web Citations In Computer Science Journals, Mohsen Jalali

Library Philosophy and Practice (e-journal)

The aim of this research is to scrutiny the accessibility and decay of web citations (URLs) used in refereed articles published by 27 Computer Science open access journals as indexed by Scopus. To do this, at first, we downloaded 1000 articles of Computer Science open access journals from 2009 to 2018. After acquiring articles, their web citations are extracted and analyzed from the accessibility and decay point of view. Moreover, for initially missed web citations complementary pathways such as using Google search engine are employed. Then, data collected are analyzed using descriptive statistical methods. Research findings indicated that 80.7% of …

A Building Permit System For Smart Cities: A Cloud-Based Framework, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur, Adwait Kaley, Arpit Patel, Akshar Joshi, Dhvani Shah

Faculty Publications

In this paper we propose a novel, cloud-based framework to support citizens and city officials in the building permit process. The proposed framework is efficient, user-friendly, and transparent with a quick turn-around time for homeowners. Compared to existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of both the end user experience and the permitting and urban planning processes. This is enabled through a data mining-powered permit recommendation engine as well as a data analytics process that allow a gleaning of key …

A Neuromorphic Quadratic, Integrate, And Fire Silicon Neuron With Adaptive Gain, David Parent, Eric Basham

Faculty Publications

An integrated circuit implementation of a silicon neuron was designed, manufactured, and tested. The circuit was designed using the Quadratic, Integrate, and Fire (QIF) neuron model in 0.5 µm silicon technology. The neuron implementation was optimized for low current consumption, drawing only 1.56 mA per QIF circuit and utilized hysteretic reset, non-inverting integrator, and voltage-squarer circuits. The final area of each circuit in silicon was 268 µm height × 400 µm width. This design is the first IC of its kind for this neuron model and is successfully able to output true spiking that follows the behaviors of bistability, monotonic, …

Enabling Autonomous Navigation For Affordable Scooters, Kaikai Liu, Rajathswaroop Mulky

Faculty Publications

Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping those in need navigate to their destinations in a hassle-free manner. In this paper, we propose to improve the safety and autonomy of navigation by designing a cutting-edge autonomous scooter, thus allowing people with mobility challenges to ambulate independently and safely in possibly unfamiliar surroundings. We focus on indoor navigation scenarios for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. To achieve semi-LiDAR functionality, we leverage the gyros-based pose data to compensate …

The 2018 Nvidia Ai City Challenge, Milind Naphade, Ming-Ching Chang, Anuj Sharma, David Anastasiu, Vamsi Jagarlamudi, Pranamesh Chakraborty, Tingting Huang, Shuo Wang, Ming-Yu Liu, Rama Chellappa, Jenq-Neng Hwang, Siwei Lyu

Faculty Publications

The NVIDIA AI City Challenge has been created to accelerate intelligent video analysis that helps make cities smarter and safer. With millions of traffic video cameras acting as sensors around the world, there is a significant opportunity for real-time and batch analysis of these videos to provide actionable insights. These insights will benefit a wide variety of agencies, from traffic control to public safety. The second edition of the NVIDIA AI City Challenge, being organized as a CVPR workshop, provided a forum to more than 70 academic and industrial research teams to compete and solve real-world problems using traffic camera …

Social Recommendations For Personalized Fitness Assistance, Saumil Dharia, Magdalini Eirinaki, Vijesh Jain, Jvalant Patel, Iraklis Varlamis, Jainikkumar Vora, Rizen Yamauchi

Faculty Publications

Wearable technology allows users to monitor their activity and pursue a healthy lifestyle through the use of embedded sensors. Such wearables usually connect to a mobile application that allows them to set their profile and keep track of their goals. However, due to the relatively “high maintenance” of such applications, where a significant amount of user feedback is expected, users who are very busy, or not as self-motivated, stop using them after a while. It has been shown that accountability improves commitment to an exercise routine. In this work, we present the PRO-Fit framework, a personalized fitness assistant aiming at …

Artificial Intelligence(Ai) Application In Library Systems In Iran: A Taxonomy Study, Asefeh Asemi, Adeleh Asemi

Library Philosophy and Practice (e-journal)

With introducing and developing AI logic, this science as a branch of computer science could impact and improve all sciences which used computer systems. LIS also could get benefit from AI in many areas. This paper survey applications of AI in library and information science and introduce the potential of library system to apply AI techniques. Intelligent systems have contributed for many librarian purposes like cataloging, indexing, information retrieval, reference, and other purposes. We applied Exploratory Factor Analysis (EFA) as a primer method for identification of the most applicable AI techniques categories in LIS. ESs are the most usable intelligent …

Recommender Systems For Large-Scale Social Networks: A Review Of Challenges And Solutions, Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, Konstantinos Tserpes

Faculty Publications

Social networks have become very important for networking, communications, and content sharing. Social networking applications generate a huge amount of data on a daily basis and social networks constitute a growing field of research, because of the heterogeneity of data and structures formed in them, and their size and dynamics. When this wealth of data is leveraged by recommender systems, the resulting coupling can help address interesting problems related to social engagement, member recruitment, and friend recommendations.In this work we review the various facets of large-scale social recommender systems, summarizing the challenges and interesting problems and discussing some of the …

A Data-Driven Approach For Detecting Autism Spectrum Disorders, Manika Kapoor, David Anastasiu

Faculty Publications

No abstract provided.

Patient Friendly Kidney Function Screening, Ragwa El Sayed, Rathna Ramesh, Alessandro Bellofiore, David Anastasiu, Melinda Simon

Faculty Publications

No abstract provided.

Teaching With Jupyter In-Class Activities: Lessons Learned And Next Steps, David Anastasiu

Faculty Publications

No abstract provided.

Parallel Cosine Nearest Neighbor Graph Construction, David Anastasiu, George Karypis

Faculty Publications

The nearest neighbor graph is an important structure in many data mining methods for clustering, advertising, recommender systems, and outlier detection. Constructing the graph requires computing up to n2 similarities for a set of n objects. This high complexity has led researchers to seek approximate methods, which find many but not all of the nearest neighbors. In contrast, we leverage shared memory parallelism and recent advances in similarity joins to solve the problem exactly. Our method considers all pairs of potential neighbors but quickly filters pairs that could not be a part of the nearest neighbor graph, based on similarity …

Document Clustering, David Anastasiu, Andrea Tagarelli

Faculty Publications

In a world flooded with information, document clustering is an important tool that can help categorize and extract insight from text collections. It works by grouping similar documents, while simultaneously discriminating between groups. In this article, we provide a brief overview of the principal techniques used to cluster documents, and introduce a series of novel deep-learning based methods recently designed for the document clustering task. In our overview, we point the reader to salient works that can provide a deeper understanding of the topics discussed.

Efficient Identification Of Tanimoto Nearest Neighbors; All Pairs Similarity Search Using The Extended Jaccard Coefficient, David Anastasiu, George Karypis

Faculty Publications

Tanimoto, or extended Jaccard, is an important similarity measure which has seen prominent use in fields such as data mining and chemoinformatics. Many of the existing state-of-the-art methods for market basket analysis, plagiarism and anomaly detection, compound database search, and ligand-based virtual screening rely heavily on identifying Tanimoto nearest neighbors. Given the rapidly increasing size of data that must be analyzed, new algorithms are needed that can speed up nearest neighbor search, while at the same time providing reliable results. While many search algorithms address the complexity of the task by retrieving only some of the nearest neighbors, we propose …

A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco

Faculty Publications

Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and …