Computer Engineering Commons^™

Icts For Surveillance And Suppression: The Case Of The Indian Emergency 1975-1977, Ramesh Subramanian

Journal of International Technology and Information Management

Information and Communications technologies (ICT) pervade society. The Internet, wireless communication, and social media are ubiquitous in and indispensable in society today. As they continue to grow and mushroom, there are new and increased calls from various segments of the society such as technologists, activists, sociologists, and legal experts, who issue warnings on the more nefarious and undesirable uses of ICTs, especially by governments. In fact, government control and surveillance using ICTs is not a new phenomenon. By looking at history, we are able to see several instances when ICTs have been used by governments to control, surveil, and infringe …

How Digital Leadership Competences And It Capabilities Affect An Organization's Ability To Digitally Transform And Adopt New Technologies, Melissa Brunner, Gabriel Gonzalez-Castañé, Pascal Ravesteijn

Journal of International Technology and Information Management

Although much research has been done into the importance of IT Capabilities (ITC), Digital Leadership (DL) and Digital Transformation (DT) with regard to organizations’ firm performance and ability to thrive in the current digital market, there is little research on qualifying which specific ITC and DL competences affect the success of an organization's DT and ultimately impact their ability to adopt newly emerging technologies. This research aims to address the influence of DL and ITC on DT as well as which specific DL competences and ITC might ultimately affect an organization’s ability to successfully adopt newly emerging digital technologies. Quantitative …

Innovativeness To Enlarge Digital Readiness - How To Avoid Digital Inertia?, Paul Morsch

Journal of International Technology and Information Management

Technological developments go fast and are interrelated and multi-interpretable. As consumer needs change, the technological possibilities to meet those needs are constantly evolving and new technology providers introduce new disruptive business models. This makes it difficult to predict what the world of tomorrow will look like for an organization and that makes the risks for organizations substantial. In this context, it is difficult for organizations to determine what constitutes a good strategy to adopt digital developments.

This paper describes a first step of a study with the objective to design a method for organizations to formulate a future-proof strategy in …

Analyzing Social Media Implementation In Hospitals In The U.S. Midwest Region, Dalsang Chung, C. Christopher Lee, David Hwang

Journal of International Technology and Information Management

The purpose of this research is to explore to what scale hospitals are adopting social media and implementing it in accordance with hospital characteristics. We reviewed hospitals’ social media activities on social networking sites such Facebook, Twitter, Instagram, and YouTube. We studied the 912 hospitals in the Midwest region reported in the 2015 American Hospital Association Annual Survey dataset. We reviewed each hospital’s social-networking page to understand the scale of social media adoption relative to the hospital’s characteristics such as bed count, state, ownership type (control), and specialty (service). We also considered whether the hospital is in a network and …

Exploring The Behavioral Intention To Use Collaborative Commerce: A Case Of Uber, C. Christopher Lee, Sinéad Ruane, Hyoun Sook Lim, Ruoquing Zhang, Heechang Shin

Journal of International Technology and Information Management

The goal of our research study is to develop a hybrid instrument built on the revised Unified Theory of Acceptance and Use of Technology (UTAUT2) framework, which is reliable in predicting the behavioral intention to use the Uber ridesharing app. It focuses on extending the UTAUT2 in collaborative consumption, particularly from a consumer and ridesharing-app perspective. Our proposed framework, UTAUT-CC, preserves existing UTAUT2 constructs – performance expectancy, effort expectancy, social expectancy, and facilitating conditions. It also retains demographic moderating variables of age and gender, while maintaining some of the key integral relationships depicted in those models. We integrated three new …

Distributed Cross-Community Collaboration For The Cloud-Based Energy Management Service, Yu-Wen Chen, J. Morris Chang

Publications and Research

Customers’ participation is a critical factor for inte-grating the distributed energy resources via demand response and demand-side management programs, especially when customers become prosumers. Incentives need to be delivered by the energy management service to attract prosumers to operate their distributed energy resources and electricity loads grid-friendly actively. The cloud-based energy management service enables virtual trading for customers within the same community to minimize cost and smooth the fluctuation. With the potential fast-growing number of service providers and customers, the needs exist for efficiently collaborating across multiple service providers and customers. This paper proposes the distributed cross-community collaboration (XCC) for …

Table Of Contents Jitim Vol 30 Issue 1, 2021

Journal of International Technology and Information Management

Table of Content

Conference Proceedings Of The 32nd Annual Iima Conference

Journal of International Technology and Information Management

Conference Proceedings of the 32nd Annual IIMA Conference

Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel

Theses

The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention …

Significant Contribution Of Mobile Apps To The Development Of Tourism In Uzbekistan, Alimjon Dadamuhamedov Irgashevich

The Light of Islam

Recently, Uzbekistan has taken comprehensive measures to develop tourism as one of the strategic sectors that contribute to the rapid development of regions, increase incomes and living standards of the population, as well as increase investment attractiveness. Modern information technologies make a signifcant contribution to the development of pilgrimage tourism. Advertising of online travel services in pilgrimage tourism currently does not allow you to automate the work of a travel Agency without creating an effective website. This article is devoted to the analysis of Internet technologies aimed at improving the tourism industry. The practical signifcance of the article lies in …

A Supporting Tool For Requirements Prioritization Process In Agile Software Development, Ramdan Mowad, Khaled Abdelazim Muhammad, Essam Elfakharany

Future Computing and Informatics Journal

Requirements engineering is a crucial phase of software engineering, and requirements prioritization is an essential stage of requirements engineering particularly in agile software development. Requirements prioritization goals at eliciting which requirements of software need to be covered in a particular release. The key point is which requirement will be selected in the next iteration and which one will be delayed to other iterations for minimizing risk during development and meeting stakeholders’ needs. There are many existing techniques for requirement prioritization, but most of these techniques do not cover continuous growth, change of requirements, and requirements dependencies. The prioritization techniques need …

A Bibliographic Survey On Detection Of Covid-19 Patients Using Various Sensors In The Field Of Iot, Rutuja Patil, Akshay Sharma, Divya Bhatia, Mugdha Kulkarni, Yashika Patl

Library Philosophy and Practice (e-journal)

Due to a pandemic situation arising from the past few decades and the covid -19 patients are increasing at the rapid rate. Looking in the near future an IOT model is build which can be useful for people in coming years and allows rapid testing and efficient testing methodologies using various sensors such as Temperature, Respiration, RFID etc which takes various parameters. The study focuses around 412 scientific documents such as Journals, articles, book chapters and Patents in various papers. These documents are extracted from the scopus databases after querying with the keywords related to covid patients and IOT. The …

The Ftc And Ai Governance: A Regulatory Proposal, Michael Spiro

Seattle Journal of Technology, Environmental, & Innovation Law

No abstract provided.

Docs_On_Blocks – A Defense In Depth Strategy For E-Healthcare, Saad Mohammed

Electronic Theses, Projects, and Dissertations

With the increase in the data breaches and cyber hacks, organizations have come to realize that cyber security alone would not help as the attacks are becoming more sophisticated and complex than ever. E-Healthcare industry has shown a promising improvement in terms of security over the past, but the threat remains. Thus, the E-Healthcare industries are aiming towards a Defense in Depth Strategy approach.

The project here describes how a Defense in Depth Strategy for E-Healthcare system can provide an environment for better security of the data and peer-to-peer interaction with stakeholders. The legacy systems have at some point failed …

Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani

Knowledge Engineering and Data Science

Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are …

Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat

Knowledge Engineering and Data Science

Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast Region Based Convolutional Neural Networks (RCNN), Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was …

Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski

Knowledge Engineering and Data Science

Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created …

Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman

Knowledge Engineering and Data Science

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one …

A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad

Knowledge Engineering and Data Science

Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new …

Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari

Knowledge Engineering and Data Science

Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is …

The Effect Of Information Technology Audit For E-Health Of Indonesia Using Itil Framework V.3 Domain Service Design, Eva Mufidah, Ilham M, Anis Eliyana, Tanti Handriana, Indrianawati Usman

Library Philosophy and Practice (e-journal)

This study explain about E-Health Surabaya is a web-based health service technology application that is used to help people register as patients in hospitals and health centers. Although its function is very useful, there are also people who still do not understand how to use this application, there are also some shortcomings that cause inconvenience in its use. So that research is conducted in which the application uses ITIL V.3 framework with Domain Service Design to conduct an audit of the maturity level of this E-Health Surabaya Web Application. ITIL (Information Technology Infrastructure Technology) is a framework used to manage …

Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle

Computer Science ETDs

Existing communication protocols in security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing visual imagers and microwave sensor information. These data types are ubiquitous in perimeter security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm …

Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang

Research Collection School Of Computing and Information Systems

In a cloud data storage system, symmetric key encryption is usually used to encrypt files due to its high efficiency. In order allow the untrusted/semi-trusted cloud storage server to perform searching over encrypted data while maintaining data confidentiality, searchable symmetric encryption (SSE) has been proposed. In a typical SSE scheme, a users stores encrypted files on a cloud storage server and later can retrieve the encrypted files containing specific keywords. The basic security requirement of SSE is that the cloud server learns no information about the files or the keywords during the searching process. Some SSE schemes also offer additional …

Dbknot: A Transparent And Seamless, Pluggable Tamper Evident Database, Islam Khalil

Theses and Dissertations

Database integrity is crucial to organizations that rely on databases of important data. They suffer from the vulnerability to internal fraud. Database tampering by internal malicious employees with high technical authorization to their infrastructure or even compromised by externals is one of the important attack vectors.

This thesis addresses such challenge in a class of problems where data is appended only and is immutable. Examples of operations where data does not change is a) financial institutions (banks, accounting systems, stock market, etc., b) registries and notary systems where important data is kept but is never subject to change, and c) …

Supply Chain Analysis To Determine E-Commerce Distribution Center Locations, Fatima Chebchoub

Masters Theses & Specialist Projects

Supply chain management is the key success for each business. Having a robust supply chain will help the business to improve service, quality, reduce the costs, improve the speed, and be more flexible. Organizations need to look at data and deploy plans to move the product from operation to logistics to manage a global chain. In this paper we will use E-Comm shipment data to identify the best locations to build a new distribution center (DC).

A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.

Branch Mathematics and Statistics Faculty and Staff Publications

With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a …

Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao

Research Collection School Of Computing and Information Systems

Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …

Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet

Research Collection School Of Computing and Information Systems

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on …

Tech Policy And Legal Theory Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Technology has changed dramatically over the last couple of decades. Currently, virtually all business industries are powered by large quantities of data. The potential as well as actual uses of business data, which oftentimes includes personal user data, raise complex issues of informed consent and data protection. This course will explore many of these complex issues, with the goal of guiding students into thinking about tech policy from a broad ethical perspective as well as preparing students to responsibly conduct themselves in different areas and industries in a world growingly dominated by technology.

Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance of sequential modeling heavily depends on the scale and quality of historical behaviors. However, the number of user behaviors inherently follows a long-tailed distribution, which has been seldom explored. In this work, we argue that focusing on tail users could bring more benefits and address the long tails issue by learning transferrable parameters from both optimization and feature perspectives. Specifically, we propose a gradient alignment optimizer and adopt an adversarial training scheme to facilitate knowledge transfer …