Dr. Soobum Lee’s research group (Energy Harvesting and Design Optimization Lab.­­­­, EDLab) recently launched collaboration with Potomac Photonics for high precision prototyping of vibration energy harvester based on laser micromachining technology. The project laminates a piezoelectric energy-harvesting material onto a vibrating substrate and then stores the converted energy in a small battery. Vibrations in the real world are not fixed but rather occur randomly. In order to respond to this fluctuation, Lee’s group is prototyping substrates with sophisticated designs that require high precision structures to capture the random vibrations.

Please find the full story on the following link: http://www.potomac-laser.com/blog/potomacs-high-precision-laser-micromachining-advances-new-energy-harvesting-technique-umbc/

By Lisa Gray, Assistant Director of Student Life, Cultural and Spiritual Diversity. 

Earlier this year, Joakina Stone, then a Res Life colleague and collateral work staff with Student Life’s Mosaic Center, along with an amazing group of students, staff and faculty, helped us to co-create our new Mosaic Social Justice discussion series. We exchanged a bunch of ideas for a title – some basic and others long and academic. After ruminating far too long, I finally settled on “What’s the Tea?” Thankfully, Zach Kosinski and Jasmine Malhotra, our Graduate Coordinators, agreed and our series launched this year on October 1st.

Everything seemed to be going well with what we are calling our “pilot semester/year” for the series. It even had what we hope was an effective, context-setting description: “We all talk about how diverse UMBC is. But what does that mean in reality? How does it show up in how we communicate and interact with each other? When does celebrating diversity shift into inclusivity that creates positive social change in and outside our campus community? This new series hopes to help us grapple with these questions. Join us for a facilitated discussion of these topics. Voice your opinions and hear those of your fellow community members.”

This description, along with a co-facilitation model, guided questions, and a brief evaluation has helped us to move forward. Things were going really well, until our November 5th Cultural Appropriation discussion. During that discussion, our well-intentioned start had an unintentional stop. In my desire to get the discussion underway, I unintentionally culturally appropriated the name of the series—“What’s the Tea?”—while talking about cultural appropriation as it relates to native, indigenous peoples.

My blindness as the lead discussion facilitator set into motion what those in the social justice education and activism world would call a concrete example of “intent versus impact.” Thanks to some generous feedback and calling out by a couple of the discussion attendees, next came my PAN, “Pay Attention Now,” moment. PAN and PAN-ing is both an acronym and a practice I learned a couple of years ago during my time at the December 2012 Social Justice Training Institute.

This post is my apology to all the attendees of our November 5th Cultural Appropriation discussion and a thank you to those brave participants for their helpful feedback and “call out.” Through that experience, and all the hours I’ve spent since replaying and processing that discussion with supportive colleagues and students, I’ve learned that there are hills, valleys, starts, and stops in the often times messy yet rewarding work towards social justice. 

Now, for those of you who’ve been patiently waiting and wondering, here’s what’s up with “What’s the Tea?”: This phrase is an extended version of “What’s the T?” a phrase originating from Black Gay Ball culture. Urban Dictionary, Answers.com, and Wikipedia all offer solid definitions and/or historical information on the term and it’s origins.

“What’s the T? – It means like “Whats up?”, “Whats going on?” It’s commonly used in the LGBT Community and is commonly used for gossiping.”

“A term originated in Black Gay culture circa 1970-1989 that indicated some one was the “T”alk of the “T”own, hence the “T”. The term was often used by female impersonators to describe a fellow impersonator that did an exceptionally good job on stage in a live lip syncipated performance which was talked about in the gay circles for long periods of time. The term grew to define any memorable person whose actions were or would soon be largely talked about in the gay circles. Also a person who was popular in the gay community would be talked about may have been referred to as The “T”

It has lasted throughout the decades and can really refer to any person, place or thing.

Mary, did you see Miss thing’s Patty Labelle performance last night? She P’d on stage! She was the “T” last night!

Girlfriend, that party you threw was fabulous, the way you have your new apartment decorated is the deal and that new husband of yours is to die for! You are the T!

It mean what’s the deal! it basically mean what’s up!

It can also refer to one’s own personal business and daily dealings.

Ex: Q: Hey girl what’s T (what’s the T)?

A: No T, girl. I’m just at home answering a question on Wikianswers.”

By replacing “T” with “Tea,” we hope to reframe the definition to one that can apply to the social justice-based topics in the series. So, “Tea” represents the social justice awareness, knowledge, and cross-cultural communication skills that we’re “spilling” like tea into the community – one small group at a time. To help illuminate this more intentionally through imagery, we’re considering re-branding the series next semester.

Hopefully, this post has been helpful and informative. For more information on “What’s the Tea?” and other Mosaic Center programs, please visit our myUMBC page.

Ph.D. Dissertation Proposal

Learning Representation and Modeling Time Series

 Zhiguang Wang

10:00-12:00 Friday, 12 December 2015, ITE 325B

Most real-world data has a temporal component, whether it is measurements of natural (weather, sound) or man-made (stock market, robotics) phenomena. Analysis of time-series data has been the subject of active research for decades and is still considered to be a challenge in machine learning and data mining due to the properties of temporal data.

Traditional approaches for modeling and representing time-series data fall into three categories. Non-data adaptive models, such as Discrete Fourier Transformation (DFT), Discrete Wavelet Transformation (DWT), and Discrete Cosine Transformation (DCT), compute the transformation with an algorithm that is invariant with respect to the data. Data adaptive approaches such as Symbolic Aggregation approXimation (SAX), Piecewise Linear Aggregation (PLA), and shapelets compute transforms that are highly dependent on the data. In model-based approaches such as AutoRegressive Moving Average models (ARMA), Linear Dynamical Systems (LDS), and Hidden Markov Models (HMMs), the underlying data is assumed to fit a specific type of model. The estimated parameters can then be used as features in, for example, a classifier.

However, more complex, high-dimensional, and noisy real-world time-series data are often difficult to model because the dynamics are either too complex or unknown. Traditional shallow methods, which contain a small number of non-linear operations, might not have the capacity to accurately model such complex systems.

We develop and verify three different approaches to represent and model time-series. Time-Warping SAX and Pooling SAX are two extensions of the vanilla SAX approach that is used as a symbolic representation of time series. Time-Warping SAX extracts linear temporal dependencies by building a time-delay embedding vector to construct more informative SAX words. Pooling SAX applies a non-parametric weighting scheme to extract significant variables. These are data adaptive models that achieve state-of-the-art accuacy on time-series classification problems.

We also propose the Gramian Angular Field (GAF) and Markov Transition Field (MTF) as two novel approaches to encode a time-series as an image. These representations not only demonstrate potential for visual inspection by humans, but when they are combined with deep learning approaches (Convolutional Network and Denoised Auto-encoders) they achieve excellent performance compared to other modern algorithms on classification and regression/imputation problems. GAF and MTF are non-data adaptive approaches that allow us to learn models and extract the abstract representations supported by model-based approaches.

Finally, we propose to model time-series by learning the representation directly from the raw data with model-based approaches. We will develop recurrent auto-encoders, in which the global optimum is ensured by a new Adaptive Risk-Averting/Seeking Criterion, to model the real/complex time series (dynamical systems) by learning the implicit data generating distribution over time. This model will be applied to tasks such as classification, regression/imputation, and anomaly detection.

Committee: Drs. Timothy Oates (Chair), James Lo (Math), Yun Peng and Matt Schmill

When discussing the concept and implementation of brave spaces, a lot of the conversation revolves around the idea that these spaces are inherently physical. We speak of transforming places into brave spaces, designating that certain locations at certain times are deemed an acceptable place to problematize and challenge the dominant power structures in society and the influence that they bear on our opinions and beliefs in conversation with others. What we never speak of is when we create these brave spaces within our own minds, grappling with these same concepts in a way that is more self-reflexive than would be in dialogue. Even though the majority of the time, these mental brave spaces do not come tethered to a specific time or location, they are still important to recognize as a valid form of creating brave spaces. The creation of these mental brave spaces are critical in that they allow people to take their individual connection to dominant power structures and problematize those relationships on their own terms. This is not to say that physical brave spaces don’t allow for the same sort of agency in choosing when to challenge oneself, but to argue that creating mental brave spaces allots for a more personal reflection on these dominant power structures at the pacing of the individual.

Before the rally and march for Justice for Eric Garner last Thursday, I was terrified. Not only for my life, but that I would not have the mental capacity to deal with facing the reality of racial injustice and police brutality. The conversation was everywhere, and I was actively engaged in it, but I did not know to what extent I was mentally and emotionally prepared to be a part of the activism in action. I was aware of the issues of police brutality and racial injustice, but I hadn’t ever been a part of something that had the potential to bring harm to me like the rally and march did. After deep and critical thought on the issue, and almost deciding that I could not bring myself to attend the rally and march, I decided to go. This was my mental brave space: challenging the conditioning that I’d had that caused me to fear the police as a black male-passing individual. The rally itself wasn’t designated a brave space, and there were no guidelines set up or enforced that would make it into one, but my complication of the effects of police brutality and racial injustice on me personally were what made me feel as though I was enacting a mental brave space.

Attending the protest is something that I will never regret, but I know that if I had chosen to stay home, if I had chosen to continue to exist in the fictional safety that society has constructed for those who remain complicit within a system, I would have always wondered. I can’t say that I would have regretted not attending, as I will never know, but I can say that I count myself lucky for having the tools to problematize my own fear and uneasiness and view them within the constructs of racial injustice and police brutality. Knowing how to operate within a physical brave space, and thus having the ability to create a mental brave space for myself, I believe that I was well-equipped to see why it was important in that moment for me to overcome my fear and attend the rally and march. Many of those present at the protest, without the knowledge and language of theory, were able to eloquently express the very same ideals that I’d been taught in my classes while seeming to have created mental brave spaces for themselves. Learning to navigate brave spaces, whether physical or mental, and whether taught through theory or self-learned, is a skill that I believe is becoming critical in this transformative time in our lives.

UMBC’s Cybersecurity Graduate Program Director Dr. Rick Forno and Homer Minnick, Director of UMBC Training Centers’ Cyber Academy, were featured in a recent Daily Record article examining how local universities support the cybersecurity education and training needs of corporate, military, and intelligence employers.

More information:

UMBC’s Graduate Cybersecurity Program

UMBC Training Centers Cyber Academy