Computer Sciences Commons^™

Twitter And The Magic Pony, Singapore Management University

Perspectives@SMU

London-based Magic Pony went from A.I. startup to a multimillion dollar cash-out in 18 months. Was selling to Twitter the right exit strategy?

What Do You Mean? Research In The Age Of Machines, Arthur J. Boston

Faculty & Staff Research and Creative Activity

What Do You Mean?” was an undeniable bop of its era in which Justin Bieber explores the ambiguities of romantic communication. (I pinky promise this will soon make sense for scholarly communication librarians interested in artificial intelligence [AI].) When the single hit airwaves in 2015, there was a meta-debate over what Bieber meant to add to public discourse with lyrics like “What do you mean? Oh, oh, when you nod your head yes, but you wanna say no.” It is unlikely Bieber had consent culture in mind, but the failure of his songwriting team to take into account that some …

Blended Root Finding Algorithm Outperforms Bisection And Regula Falsi Algorithms, Chaman Sabharwal

Computer Science Faculty Research & Creative Works

Finding the roots of an equation is a fundamental problem in various fields, including numerical computing, social and physical sciences. Numerical techniques are used when an analytic solution is not available. There is not a single algorithm that works best for every function. We designed and implemented a new algorithm that is a dynamic blend of the bisection and regula falsi algorithms. The implementation results validate that the new algorithm outperforms both bisection and regula falsi algorithms. It is also observed that the new algorithm outperforms the secant algorithm and the Newton-Raphson algorithm because the new algorithm requires fewer computational …

Use Cases Of Lossy Compression For Floating-Point Data In Scientific Data Sets, Franck Cappello, Sheng Di, Sihuan Li, Xin Liang, Ali Murat Gok, Dingwen Tao, For Full List Of Authors, See Publisher's Website.

Computer Science Faculty Research & Creative Works

Architectural and technological trends of systems used for scientific computing call for a significant reduction of scientific data sets that are composed mainly of floating-point data. This article surveys and presents experimental results of currently identified use cases of generic lossy compression to address the different limitations of scientific computing systems. The article shows from a collection of experiments run on parallel systems of a leadership facility that lossy data compression not only can reduce the footprint of scientific data sets on storage but also can reduce I/O and checkpoint/restart times, accelerate computation, and even allow significantly larger problems to …

Automatic Recall Of Software Lessons Learned For Software Project Managers, Tamer Mohamed Abdellatif Mohamed, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Context: Lessons learned (LL) records constitute the software organization memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often disregarded. This can lead to the repetition of previous mistakes or even missing potential opportunities. This, in turn, can negatively affect the organization’s profitability and competitiveness.

Objective: We aim to present a novel solution that provides an automatic process to recall relevant LL and to push those LL to project managers. This will dramatically …

Can We Rely On Smartphone Applications?, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Smartphones are becoming necessary tools in the daily lives of millions of users who rely on these devices and their applications. There are thousands of applications for smartphone devices such as the iPhone, Blackberry, and Android, thus their reliability has become paramount for their users. This work aims to answer two related questions: (1) Can we assess the reliability of mobile applications by using the traditional reliability models? (2) Can we model adequately the failure data collected from many users? Firstly, it has been proved that the three most used software reliability models have fallen short of the mark when …

Auditor: An R Package For Model-Agnostic Visual Validation And Diagnostics, Alicja Gosiewska, Przemysław Biecek

The R Journal

Machine learning models have successfully been applied to challenges in applied in biology, medicine, finance, physics, and other fields. With modern software it is easy to train even a complex model that fits the training data and results in high accuracy on test set. However, problems often arise when models are confronted with the real-world data. This paper describes methodology and tools for model-agnostic auditing. It provides functinos for assessing and comparing the goodness of fit and performance of models. In addition, the package may be used for analysis of the similarity of residuals and for identification of outliers and …

Light-Field Style Transfer, David Marvin Hart

Theses and Dissertations

For many years, light fields have been a unique way of capturing a scene. By using a particular set of optics, a light field camera is able to, in a single moment, take images of the same scene from multiple perspectives. These perspectives can be used to calculate the scene geometry and allow for effects not possible with standard photographs, such as refocus and the creation of novel views.Neural style transfer is the process of training a neural network to render photographs in the style of a particular painting or piece of art. This is a simple process for a …

Collective Representation Learning On Spatiotemporal Heterogeneous Information Networks, Dakshak Keerthi Chandra, Pengyang Wang, Jennifer Leopold, Yanjie Fu

Computer Science Faculty Research & Creative Works

Representation learning is a technique that is used to capture the underlying latent features of complex data. Representation learning on networks has been widely implemented for learning network structure and embedding it in a low dimensional vector space. In recent years, network embedding using representation learning has attracted increasing attention, and many deep architectures have been widely proposed. However, existing network embedding techniques ignore the multi-class spatial and temporal relationships that crucially reflect the complex nature among vertices and links in spatiotemporal heterogeneous information networks(SHINs).

To address this problem, in this paper, we present two types of collective representation learning …

Projektimi I Një Iot Moduli Për Monitorimin E Cilësisë Së Ujit Në Kohë Reale, Ramiz Krasniqi

Theses and Dissertations

Fillimisht falenderoj Zotin i cili më mundësoj të arrijë të mbrojë temën e diplomës së nivelit Master pranë profesorëve të nderuar të cilët gjithashtu i falendëroj për përkushtimin dhe angazhimin e tyre. Gjithsesi këtyre arritjeve të mia i bashkangjiten edhe shumë njerëz të cilët qëndrojnë prapa sukseseve të mia e për të cilët kam falendërim të veçantë. Falenderoj prindërit për përkujdesjen dhe motivimin që gjithmonë më kanë japur. Gjithë kjo punë e imja nuk do të ishte realizuar në radhë të parë pa ndihmën e mentorit tim, Dr.Zhilbert Tafës i cili ishte i gatshëm të më ofrojë ndihmën e tij …

Algortimet Kriptografike Dhe Siguria, Agnesa Krasniqi

Theses and Dissertations

Rritja e përdorimit të Internetit ka ndikuar ndjeshëm në natyrën e aplikacioneve dhe në mënyrën sesi ne komunikojmë. Siguria e të dhënave dikton përdorimin e teknikave të ndryshme kriptografike. Për këtë arsye analizojmë në detaje teknikat e ndryshme të shifrimit duke vlerësuar performancën dhe efikasitetin e tyre. Për të kuptuar rëndësinë e aplikimit të teknikave kriptografike mjafton të njohim panoramën e gjerë të aplikacioneve dhe shërbimeve ku kemi të dhëna sensitive. Ruajtja e të dhënave është një ndër kërkesat bazë vetjake por edhe operacionale në garantimin e sigurisë së suksesit në një iniciativë biznesi si bankat apo kompanitë e ndryshme. …

Siguria Dhe Privatësia Në Sektorin Bankar Që Përdorin Shërbime Të Bazuara Në Cloud: Sfidat Dhe Kontrollet, Driton Emërllahu

Theses and Dissertations

Kjo tezë e masterit diskuton çështjet e sigurisë dhe privatësisë të sektorit bankar që përdorin shërbime të bazuara në cloud, si dhe përshkruan implikimet e tij në sigurinë privatësinë e të dhënave personale, dhe implikimet në konfidencialitetin e bizneseve, ndërmarrjeve apo entitete të ndryshme. Me anë të këtij hulumtimi gjejmë se shpërndarja (sharing) e informacionit për disa informacione ose edhe për disa përdorues mund të jetë e kufizuar në disa mënyra ose dhe mund të ndikojë në statutin ose mbrojtjen e informacionit të përbashkët, dhe bankat kanë qenë tradicionalisht një industri konservatore në lidhje me adoptimin e teknologjive më të …

Application Of Intelligent Data Analysis In Medicine, Diellëza Xhokli

Theses and Dissertations

Përmes këtij punimi të temës së diplomës është paraqitur një punë e cila ka të bëjë me Aplikimin e analizes intelegjente të të dhënave në mjekësi ku do të diskutohet në vazhdim, kjo temë do të trajtojë sasinë e të dhënave të mëdha, ruajtjen e atyre të dhënave në bazën e të dhënave mjekësore e cila kërkon zhvillimin e mjeteve të specializuara për ruajtjen në këto të dhëna. Ky punim ka për qëllim kryesor hulumtimet online të cilat bazohen në njohjen e zhvillimit të intelegjencës së të dhënave aktuale si dhe nevojën për analizen intelegjente të të dhënave në mjekësi …

Krahasimi I Teknikave Të Multipleksimit (Fdma, Tdma, Dhe Cdma), Bardhyl Sopjani

Theses and Dissertations

Kërkesa për lloje të ndryshme të komunikimeve të tilla si zëri, imazhet, videot dhe të dhënat tjera, rrisin kërkesën për shpejtësi më të mëdha të transmetimit. Nevoja për kapacitete më të mëdha, ka shtyrë më tutje zhvillimin e teknologjisë, e ku multipleksimi gjen zbatim të rëndësishëm në këtë drejtim.

Multipleksimi ka evoluar me kalimin e viteve. Kjo është filluar me metodën e Emile Baudot për të transmetuar gjashtë sinjale telegrafi njëkohësisht përmes një kablli në sistemet e komunikimit me sinjal të përzier me shpejtësi të lartë, që tani janë të zakonshme. Evolucioni filloi me burime identike të shumëfishta informacioni, siç …

Search Engines Arkitektura Dhe Krahasimi I Platformave Ekzistuese, Valbonë Hajrizi

Theses and Dissertations

Në këtë punim të diplomës master, është shtjelluar puna dhe funksionaliteti i makinave të kërkimit (ang. Search Engine) në ueb, dhe arkitektura dhe krahasimi i platformave aktuale, duke bërë krahasimin e tyre si për nga aspekti i vetive, dizajnit, funksionalitetit, shpejtësisë në gjetjen dhe kthimin e informacioneve të kërkuara, saktësisë në gjetjen e informacioneve të duhura, si dhe përdorimit të tyre nga shfrytëzuesit.

Sot, të hapësh një shfletues në Internet dhe mos hapësh një makinë kërkuese në ueb, është pothuajse e pamundur, kjo për arsye se tani Interneti është një grumbull shumë i madh i të dhënave, sa që, për …

Krahasimi I Algoritmeve Për Kërkimin E Paternës Brenda Dokumentit, Vionë Hasani

Theses and Dissertations

Problemet në kohë reale në botë kanë nevojë për algoritëm të shpejtë dhe me gabim minimal. Në ditët e sotme ka shumë aplikacione që janë përdorur për të kërkuar rezultate në internet. Ka shumë algoritme të cilat përdoren për kërkimin e rezultateve. Metoda e përputhjes së paternës është njëra prej tyre. Në aplikacionin në internet njerëzit merren me llojet e ndryshme të të dhënave, për shembull kërkimi i tekstit, kërkimi i figurave, kërkimi audio dhe kërkimi i videos. Çdo search engine përdorë algoritme të ndryshme të kërkimit për trajtimin e tipeve të ndryshme të të dhënave.

Pasi që ekzistojnë algoritme …

Menaxhimi I Mikroserviseve Me Anë Të Kubernetes, Ilir Koci

Theses and Dissertations

Ky punim diplome analizon menaxhimin e një aplikacioni të ndarë në mikroservise me anë të Kubernetes si orchestration platformë dhe Docker si containerization platformë. Pasi që Cloud po shkon drejt mikroserviseve atëherë do të ishte ide e mirë qe kjo temë të mirrej me këtë problem. Pasi që aplikacionet monolithic janë vështirë të menaxhueshme dhe kanë vështirësi të shkallëzohen kur ka kërkesë të madhe për atë aplikacion atëherë ndarja e tij në mikroservise dhe orkestrimi i tij me anë të Kubernetes e lehtëson punën për System Admin (DevOps Engineer).

Në këtë temë ceken se si funksionojnë platformat e containerization si …

Improving Structure Evaluation Through Automatic Hierarchy Expansion, Brian Mcfee, Katherine M. Kinnaird

Computer Science: Faculty Publications

Structural segmentation is the task of partitioning a recording into non-overlapping time intervals, and labeling each segment with an identifying marker such as A, B, or verse. Hierarchical structure annotation expands this idea to allow an annotator to segment a song with multiple levels of granularity. While there has been recent progress in developing evaluation criteria for comparing two hierarchical annotations of the same recording, the existing methods have known deficiencies when dealing with inexact label matchings and sequential label repetition. In this article, we investigate methods for automatically enhancing structural annotations by inferring (and expanding) hierarchical information from the …

Fog Computing Enabling Industrial Internet Of Things: State-Of-The-Art And Research Challenges, Rabeea Basir, Saad Qaisar, Mudassar Ali, Monther Aldwairi, Muhammad Ikram Ashraf, Aamir Mahmood, Mikael Gidlund

All Works

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a …

Resource Characterisation Of Personal-Scale Sensing Models On Edge Accelerators, Mattia Antonini, Tran Huy Vu, Chulhong Min, Alessandro Montanari, Akhil Mathur, Fahim Kawsar

Student Publications

Edge accelerator is a class of brand-new purpose-built System On a Chip (SoC) for running deep learning models efficiently on edge devices. These accelerators offer various benefits such as ultra-low latency, sensitive data protection, and high availability due to their locality and are opening up interminable opportunities for building sensory systems in the real world. Naturally, in the context of sensory awareness systems, e.g., IoT, wearables, and other sensory devices, the emergence of edge accelerators is pushing us to rethink how we design these systems at a personal-scale. To this end, in this paper we take a closer look at …

An Optimal Hybrid Learning Approach For Attack Detection In Linear Networked Control Systems, Haifeng Niu, Avimanyu Sahoo, Chandreyee Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel learning-based attack detection and estimation scheme is proposed for linear networked control systems NCS, wherein the attacks on the communication network in the feedback loop are expected to increase network induced delays and packet losses, thus changing the physical system dynamics. First, the network traffic flow is modeled as a linear system with uncertain state matrix and an optimal Q-learning based control scheme over finite-horizon is utilized to stabilize the flow. Next, an adaptive observer is proposed to generate the detection residual, which is subsequently used to determine the onset of an attack when it exceeds a predefined …

Vireo-Eurecom @ Trecvid 2019: Ad-Hoc Video Search (Avs), Phuong Anh Nguyen, Jiaxin Wu, Chong-Wah Ngo, Francis Danny, Benoit Huet

Research Collection School Of Computing and Information Systems

In this paper, we describe the systems developed for Ad-hoc Video Search (AVS) task at TRECVID 2019[1] and the achieved results.

View-Dependent Data Prefetching For Interactive Visualization Of Large-Scale 3d Scientific Data, Jin Wang

School of Computing: Dissertations, Theses, and Student Research

One of the most significant challenges for today's interactive visualization is the efficient analysis and visualization of large-scale data, and I/O becomes a significant performance bottleneck. This thesis proposes a new data management policy to support interactive large-scale visual analytics. Our method can characterize user's data access patterns according to their data-dependent and view-dependent visualization operations, and leverage application knowledge to derive a novel scheme to predict data access during the interactive operations. Based on the prediction results, we develop a data replacement policy to exploit data locality and minimize data movement across multiple levels of a memory hierarchy. We …

Deformable Part Models For Automatically Georeferencing Historical Map Images, Nicholas Howe, Jerod Weinman, John Gouwar, Aabid Shamji

Computer Science: Faculty Publications

Libraries are digitizing their collections of maps from all eras, generating increasingly large online collections of historical cartographic resources. Aligning such maps to a modern geographic coordinate system greatly increases their utility. This work presents a method for such automatic georeferencing, matching raster image content to GIS vector coordinate data. Given an approximate initial alignment that has already been projected from a spherical geographic coordinate system to a Cartesian map coordinate system, a probabilistic shape-matching scheme determines an optimized match between the GIS contours and ink in the binarized map image. Using an evaluation set of 20 historical maps from …

A Deep Learning Approach For Tweet Classification And Rescue Scheduling For Effective Disaster Management, Md. Yasin Kabir, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

Every activity in disaster management demands accurate and up-todate information to allow a quick, easy, and cost-efective response to reduce the possible loss of lives and properties. It is a challenging and complex task to acquire information from diferent regions of a disaster-afected area in a timely fashion. The extensive spread and reach of social media and networks such as Twitter allow people to share information in real-time. However, gathering of valuable information requires a series of operations such as (1) processing each tweet for the text classiication, (2) possible location determination of people needing help based on tweets, and …

An Extensible Geospatial Data Framework (Geoedf) For Fair Science, Carol Song, Rajesh Kalyanam, Lan Zhao

Purdue GIS Day

The growing urgency in dealing with the 21st century’s grand challenges associated with increasing population, food and water security, frequently occurring natural disasters, and changing climate demands innovative, collaborative, and multidisciplinary solutions for sustainability and resilience. However, scientific data, especially geospatial data, presents significant barriers to the effective access, use and sharing of data as they come in large volumes, from different sources, and with widely varying formats, resolutions, or annotation schemas that can differ among disciplines or even research groups. This presentation describes a recently funded NSF CSSI project to develop an open source, extensible geospatial data framework (GeoEDF), …

Characterizing Instructional Leader Interactions In A Social Learning Management System Using Social Network Analysis, Orven E. Llantos, Ma. Regina Justina E. Estuar

Department of Information Systems & Computer Science Faculty Publications

Online learning environments are designed with specific users and respective roles in mind. However, for social systems that thrive on the interaction between and among users, important features are developed based on relationships that evolve over time. Typical learning management systems are designed with the teacher and the student as primary users of the system. my.eskwela is a social learning management system that has been designed for use in public schools in the Philippines with the inclusion of an additional user, the school administrator. Although administrators influence on student learning through mediated effects of instructional leadership, pieces of literature are …

Medtruth: A Semi-Supervised Approach To Discovering Knowledge Condition Information From Multi-Source Medical Data, Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei

Research Collection School Of Computing and Information Systems

Knowledge Graph (KG) contains entities and the relations between entities. Due to its representation ability, KG has been successfully applied to support many medical/healthcare tasks. However, in the medical domain, knowledge holds under certain conditions. Such conditions for medical knowledge are crucial for decisionmaking in various medical applications, which is missing in existing medical KGs. In this paper, we aim to discovery medical knowledge conditions from texts to enrich KGs. Electronic Medical Records (EMRs) are systematized collection of clinical data and contain detailed information about patients, thus EMRs can be a good resource to discover medical knowledge conditions. Unfortunately, the …

An Online Wideband Acoustic Immittance (Wai) Database Andcorresponding Website: Resource Review, Susan E. Voss

Engineering: Faculty Publications

Wideband acoustic immittance (WAI) measures, which include absorbance, power reflectance, impedance, and other related quantities, offer an objective, noninvasive diagnostic tool for some middle-ear pathologies. An online database for normative adult WAI measures has been designed and implemented in MySQL, with the goal of enabling researchers to share and analyze data across studies.

Access database through ScholarWorks here: https://scholarworks.smith.edu/dds_data/6

Or directly here: http://www.science.smith.edu/wai-database/

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’. …