Physical Sciences and Mathematics Commons^™

Stable Solution To L 2,1-Based Robust Inductive Matrix Completion And Its Application In Linking Long Noncoding Rnas To Human Diseases, Ashis Kumer Biswas, Dong-Chul Kim, Mingon Kang, Chris Ding, Jean X. Gao

Computer Science Faculty Publications and Presentations

Backgrounds

A large number of long intergenic non-coding RNAs (lincRNAs) are linked to a broad spectrum of human diseases. The disease association with many other lincRNAs still remain as puzzle. Validation of such links between the two entities through biological experiments are expensive. However, a plethora lincRNA-data are available now, thanks to the High Throughput Sequencing (HTS) platforms, Genome Wide Association Studies (GWAS), etc, which opens the opportunity for cutting-edge machine learning and data mining approaches to extract meaningful relationships among lincRNAs and diseases. However, there are only a few in silico lincRNA-disease association inference tools available to date, and …

Amake: Cached Builds Of Top-Level Targets, Jim Buffenbarger

Computer Science Faculty Publications and Presentations

This paper describes a software-build tool named Amake, an extension of GNU Make. Its additional features solve important problems that have, until now, only been addressed by “high-end” build tools (e.g., ClearCase and Vesta).

With a typical build tool, if a top-level target must be updated, intermediate targets must be built from sources, and then combined to build the top-level target. The enhancements described here allow a top-level target to be fetched from a shared cache, without building, or even fetching its intermediate-target dependencies. Thus, a developer’s workspace may need only contain sources and top-level targets. This reduces build time, …

The Public’S Perception Of Humanlike Robots: Online Social Commentary Reflects An Appearance-Based Uncanny Valley, A General Fear Of A “Technology Takeover”, And The Unabashed Sexualization Of Female-Gendered Robots, Megan K. Strait, Cynthia Aguillon, Virginia Contreras, Noemi Garcia

Computer Science Faculty Publications and Presentations

Towards understanding the public’s perception of humanlike robots, we examined commentary on 24 YouTube videos depicting social robots ranging in human similarity – from Honda’s Asimo to Hiroshi Ishiguro’s Geminoids. In particular, we investigated how people have responded to the emergence of highly humanlike robots (e.g., Bina48) in contrast to those with more prototypically-“robotic” appearances (e.g., Asimo), coding the frequency at which the uncanny valley versus fears of replacement and/or a “technology takeover” arise in online discourse based on the robot’s appearance. Here we found that, consistent with Masahiro Mori’s theory of the uncanny valley, people’s commentary reflected an aversion …

On The Temporal Effects Of Mobile Blockers In Urban Millimeter-Wave Cellular Scenarios, Margarita Gapeyenko, Mikhail Gerasimenko, Andrey Samuylov, Dmitri Moltchanov, Sarabjot Singh, Mustafa Riza Akdeniz, Ehsan Aryafar, Nageen Himayat, Sergey Andreev, Yevgeni Koucheryavy

Computer Science Faculty Publications and Presentations

Millimeter-wave (mmWave) propagation is known to be severely affected by the blockage of the line-of-sight (LoS) path. In contrast to microwave systems, at shorter mmWave wavelengths such blockage can be caused by human bodies, where their mobility within environment makes wireless channel alternate between the blocked and non-blocked LoS states. Following the recent 3GPP requirements on modeling the dynamic blockage as well as the temporal consistency of the channel at mmWave frequencies, in this paper a new model for predicting the state of a user in the presence of mobile blockers for representative 3GPP scenarios is developed: urban micro cell …

Phosphoproteomics Profiling Of Nonsmall Cell Lung Cancer Cells Treated With A Novel Phosphatase Activator, Danica Wiredja, Marzieh Ayati, Sahar Mazhar, Jaya Sangodkar, Sean Maxwell, Daniela Schlatzer, Goutham Narla, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications and Presentations

Activation of protein phosphatase 2A (PP2A) is a promising anti-cancer therapeutic strategy, as this tumor suppressor has the ability to coordinately downregulate multiple pathways involved in the regulation of cellular growth and proliferation. In order to understand the systems-level perturbations mediated by PP2A activation, we carried out mass spectrometry-based phosphoproteomic analysis of two KRAS mutated non-small cell lung cancer (NSCLC) cell lines (A549 and H358) treated with a novel Small Molecule Activator of PP2A (SMAP). Overall, this permitted quantification of differential signaling across over 1,600 phosphoproteins and 3,000 phosphosites. Kinase activity assessment and pathway enrichment implicated collective downregulation of RAS …

Understanding The Uncanny: Both Atypical Features And Category Ambiguity Provoke Aversion Toward Humanlike Robots, Megan K. Strait, Victoria A. Floerke, Wendy Ju, Keith Maddox, Jessica D. Remedios, Malte F. Jung, Heather L. Urry

Computer Science Faculty Publications and Presentations

Robots intended for social contexts are often designed with explicit humanlike attributes in order to facilitate their reception by (and communication with) people. However, observation of an “uncanny valley”—a phenomenon in which highly humanlike entities provoke aversion in human observers—has lead some to caution against this practice. Both of these contrasting perspectives on the anthropomorphic design of social robots find some support in empirical investigations to date. Yet, owing to outstanding empirical limitations and theoretical disputes, the uncanny valley and its implications for human-robot interaction remains poorly understood. We thus explored the relationship between human similarity and people's aversion toward …

Fatrec Workshop On Responsible Recommendation Proceedings, Michael Ekstrand, Amit Sharma

Computer Science Faculty Publications and Presentations

We sought with this workshop, to foster a discussion of various topics that fall under the general umbrella of responsible recommendation: ethical considerations in recommendation, bias and discrimination in recommender systems, transparency and accountability, social impact of recommenders, user privacy, and other related concerns. Our goal was to encourage the community to think about how we build and study recommender systems in a socially-responsible manner.

Recommendation systems are increasingly impacting people's decisions in different walks of life including commerce, employment, dating, health, education and governance. As the impact and scope of recommendations increase, developing systems that tackle issues of …

Analyzing The Relationship Between Human Behavior And Indoor Air Quality, Beiyu Lin, Yibo Huangfu, Nathan Lima, Bertram Jobson, Max Kirk, Patrick O’Keeffe, Shelley N. Pressley, Von Walden, Brian Lamb, Diane J. Cook

Computer Science Faculty Publications and Presentations

In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany population growth and aging, we examine the relationship between home occupant behavior and indoor air quality. To do this, we collect both sensor-based behavior data and chemical indoor air quality measurements in smart home environments. We introduce a novel machine learning-based approach to quantify the correlation between smart home features and chemical measurements of air quality, and …

Multispectral Image Analysis Using Decision Trees, Arun D. Kulkarni, Anmol Shrestha

Computer Science Faculty Publications and Presentations

Many machine learning algorithms have been used to classify pixels in Landsat imagery. The maximum likelihood classifier is the widely-accepted classifier. Non-parametric methods of classification include neural networks and decision trees. In this research work, we implemented decision trees using the C4.5 algorithm to classify pixels of a scene from Juneau, Alaska area obtained with Landsat 8, Operation Land Imager (OLI). One of the concerns with decision trees is that they are often over fitted with training set data, which yields less accuracy in classifying unknown data. To study the effect of overfitting, we have considered noisy training set data …

Spatial-Semantic Image Search By Visual Feature Synthesis, Mai Long, Hailin Jin, Chen Fang, Feng Liu

Computer Science Faculty Publications and Presentations

The performance of image retrieval has been improved tremendously in recent years through the use of deep feature representations. Most existing methods, however, aim to retrieve images that are visually similar or semantically relevant to the query, irrespective of spatial configuration. In this paper, we develop a spatial-semantic image search technology that enables users to search for images with both semantic and spatial constraints by manipulating concept text-boxes on a 2D query canvas. We train a convolutional neural network to synthesize appropriate visual features that captures the spatial-semantic constraints from the user canvas query. We directly optimize the retrieval performance …

The Necst Program - Networking And Engaging In Computer Science And Information Technology Program, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

In this paper, we describe the NECST Program and its innovative mentorship structure for transitioning graduate students in computer science whose undergraduate experiences may be in other disciplines. NECST employs several activities that provide the additional scaffolding to support students as they make this transition. While we believe these activities may be suited for other situations, the program helps address the unique challenges northern New Jersey faces with relation to graduate studies in computing fields.

A Graphical Digital Personal Assistant That Grounds And Learns Autonomously, Casey Kennington, Aprajita Shukla

Computer Science Faculty Publications and Presentations

We present a speech-driven digital personal assistant that is robust despite little or no training data and autonomously improves as it interacts with users. The system is able to establish and build common ground between itself and users by signaling understanding and by learning a mapping via interaction between the words that users actually speak and the system actions. We evaluated our system with real users and found an overall positive response. We further show through objective measures that autonomous learning improves performance in a simple itinerary filling task.

Temporal Alignment Using The Incremental Unit Framework, Casey Kennington, Ting Han, David Schlangen

Computer Science Faculty Publications and Presentations

We propose a method for temporal alignments--a precondition of meaningful fusions--of multimodal systems, using the incremental unit dialogue system framework, which gives the system flexibility in how it handles alignment: either by delaying a modality for a specified amount of time, or by revoking (i.e., backtracking) processed information so multiple information sources can be processed jointly. We evaluate our approach in an offline experiment with multimodal data and find that using the incremental framework is flexible and shows promise as a solution to the problem of temporal alignment in multimodal systems.

Edos: Edge Assisted Offloading System For Mobile Devices, Hank H. Harvey, Ying Mao, Yantian Hou, Bo Sheng

Computer Science Faculty Publications and Presentations

Offloading resource-intensive jobs to the cloud and nearby users is a promising approach to enhance mobile devices. This paper investigates a hybrid offloading system that takes both infrastructure-based networks and Ad-hoc networks into the scope. Specifically, we propose EDOS, an edge assisted offloading system that consists of two major components, an Edge Assistant (EA) and Offload Agent (OA). EA runs on the routers/towers to manage registered remote cloud servers and local service providers and OA operates on the users’ devices to discover the services in proximity. We present the system with a suite of protocols to collect the potential service …

Silence, Please!: Interrupting In-Car Phone Conversations, Soledad López Gambino, Casey Kennington, David Schlangen

Computer Science Faculty Publications and Presentations

Holding phone conversations while driving is dangerous not only because it occupies the hands, but also because it requires attention. Where driver and passenger can adapt their conversational behavior to the demands of the situation, and e.g. interrupt themselves when more attention is needed, an interlocutor on the phone cannot adjust as easily. We present a dialogue assistant which acts as 'bystander' in phone conversations between a driver and an interlocutor, interrupting them and temporarily cutting the line during potentially dangerous situations. The assistant also informs both conversation partners when the line has been cut, as well as when it …

Analysis On The Security And Use Of Password Managers, Carlos Luevanos, John Elizarraras, Khai Hirschi, Jyh-Haw Yeh

Computer Science Faculty Publications and Presentations

Cybersecurity has become one of the largest growing fields in computer science and the technology industry. Faulty security has cost the global economy immense losses. Oftentimes, the pitfall in such financial loss is due to the security of passwords. Companies and regular people alike do not do enough to enforce strict password guidelines like the NIST (National Institute of Standard Technology) recommends. When big security breaches happen, thousands to millions of passwords can be exposed and stored into files, meaning people are susceptible to dictionary and rainbow table attacks. Those are only two examples of attacks that are used to …

Panel: Influencing Culture And Curriculum Via Revolution, Amit Jain

Computer Science Faculty Publications and Presentations

The goal of this panel session is to introduce audience members to the challenges and successes of significant cultural and curricular change as enacted by awardees in the NSF program Revolutionizing Engineering and Computer Science Departments (RED). This panel will explore how organizations go about the process of cultural investigation and how they embark on culture change, using RED awardees of 2016 as the featured panelists (the second cohort). These teams are engaged in high-risk, high-trust-required activities focused on both the organizational and operational structure of their departments, and on re-envisioning engineering and computer science curricula to create professionals able …

Development Of An Intelligent Equipment Lock Management System With Rfid Technology, Yeh-Cheng Chen, C. N. Chu, H. M. Sun, Jyh-Haw Yeh, Ruey-Shun Chen, Chorng-Shiuh Koong

Computer Science Faculty Publications and Presentations

The equipment lock has been an important tool for the power company to protect the electricity metering equipment. however, the conventional equipment lock has two potential problems: vandalism and counterfeiting. To fulfill the control and track the potential illegal behavior, the human labor and paper are required to proceed with related operations, resulting in the consumption of a large amount of human resources and maintenance costs.

This study focused on the design of RFID technology applied to the traditional equipment lock, which, through the mobile and electronic technology, strengthens the management/operating convenience of the lock and provides the solutions for …

Capia: Cloud Assisted Privacy-Preserving Image Annotation, Yifan Tian, Yantian Hou, Jiawei Yuan

Computer Science Faculty Publications and Presentations

Using public cloud for image storage has become a prevalent trend with the rapidly increasing number of pictures generated by various devices. For example, today's most smartphones and tablets synchronize photo albums with cloud storage platforms. However, as many images contain sensitive information, such as personal identities and financial data, it is concerning to upload images to cloud storage. To eliminate such privacy concerns in cloud storage while keeping decent data management and search features, a spectrum of keywords-based searchable encryption (SE) schemes have been proposed in the past decade. Unfortunately, there is a fundamental gap remains open for their …

Kidrec: Children & Recommender Systems: Workshop Co-Located With Acm Conference On Recommender Systems (Recsys 2017), Jerry Alan Fails, Maria Soledad Pera, Franca Garzotto, Mirko Gelsomini

Computer Science Faculty Publications and Presentations

The 1^st Workshop on Children and Recommender Systems (KidRec) is taking place in Como, Italy August 27^th, 2017 in conjunction with the ACM RecSys 2017 conference. The goals of the workshop are threefold: (1) discuss and identify issues related to recommender systems used by children including specific challenges and limitations, (2) discuss possible solutions to the identified challenges and plan for future research, and (3) build a community to directly work on these important issues.

Coms: Customer Oriented Migration Service, Kai Huang, Xing Gao, Fengwei Zhang, Jidong Xiao

Computer Science Faculty Publications and Presentations

Virtual machine live migration has been studied for more than a decade, and this technique has been implemented in various commercial hypervisors. However, currently in the cloud environment, virtual machine migration is initiated by system administrators. Cloud customers have no say on this: They can not initiate a migration, and they do not even know whether or not their virtual machines have been migrated. In this paper, we propose the COMS framework, which is short for "Customer Oriented Migration Service". COMS gives more control to cloud customers so that migration becomes a service option and customers are more aware of …

Grace's Inheritance, James Noble, Andrew P. Black, Kim B. Bruce, Michael Homer, Timothy Jones

Computer Science Faculty Publications and Presentations

This article is an apologia for the design of inheritance in the Grace educational programming language: it explains how the design of Grace’s inheritance draws from inheritance mechanisms in predecessor languages, and defends that design as the best of the available alternatives. For simplicity, Grace objects are generated from object constructors, like those of Emerald, Lua, and Javascript; for familiarity, the language also provides classes and inheritance, like Simula, Smalltalk and Java. The design question we address is whether or not object constructors can provide an inheritance semantics similar to classes.

Universal Shape Replicators Via Self-Assembly With Attractive And Repulsive Forces, Cameron Chalk, Erik D. Demaine, Martin L. Demaine, Eric Martinez, Robert Schweller, Luis Vega, Tim Wylie

Computer Science Faculty Publications and Presentations

We show how to design a universal shape replicator in a self- assembly system with both attractive and repulsive forces. More precisely, we show that there is a universal set of constant-size objects that, when added to any unknown holefree polyomino shape, produces an unbounded number of copies of that shape (plus constant-size garbage objects). The constant-size objects can be easily constructed from a constant number of individual tile types using a constant number of preprocessing self-assembly steps. Our construction uses the well-studied 2-Handed Assembly Model (2HAM) of tile self-assembly, in the simple model where glues interact only with identical …