Transcript: Obvious things....... plus..... Build relationships Make time to have a coffee with someone you don't know Help everyone you can Use a recruiter Keep Linkedin profile up to date Apply to lots of positions (have a plan B) Change your name on facebook Dematic Bluescope research Ways to secure a job - Hints and Tips Thesis - Robot Wall Climber IBM Memcor Graduate IT Specialist Business Intelligence Specialist Mechanical Design and Control System Deloitte - Decision Science and Analytics Servian Cochlear UNSW Andrew's Journey
Transcript: Cameron Un UNSW Quadrangle Strategy Summary Summary The UNSW Quadrangle Strategy intends to conceive a public space that is recognisable by the community and improve connections to transport whilst exploring how the precinct functions as a whole. The UNSW Quadrangle Strategy will play an important role in increasing the liveliness of the precinct by incorporating an interactive design to attract students, staff and visitors. The strategy intends to reduce congestion in the Quadrangle which will provide a smoother path to public transport options. To improve the quality of the precinct, the strategy’s objectives are too: • Analyse which features of the Quadrangle are favourable and those that are inappropriate in its design. • Identify current issues which restrict the transformation of the Quadrangle. • Suggest several options to improve both the liveliness and access to public transportation of the Quadrangle. Strategy Objectives Objectives Precinct Context Precinct Context The UNSW Quadrangle is an important point of interchange between the upper and lower campus as well as public transport options. It is also a place where students can relax, gather to work on group projects or work individually. UNSW Quadrangle UNSW Campus Key Challenges There were a number of obstacles which restricted a satisfactory design of the Quadrangle which included: Lengthy and conflicting paths Makes it difficult for pedestrians to navigate around the Quadrangle without conflict. Path restriction by vehicular activity Occasionally trucks operate on the road parallel between High Street and the Quadrangle which causes congestion. Key Challenges Congestion Hot Routes Cold Routes Point of Congestion Timelapse Design Approach Design Approach Small Bridge & Ring Path Pedestrians are forced to conflict when using the crossroad style path. A small bridge over the intersection would allow pedestrians to cross on and under the bridge without conflict. The ring path will help pedestrians to manuever smoothly and create extra walking space. Multiple Entrances/Exits to High Street Many pedestrians are forced to funnel through one route which is also occasionally interrupted by construction efforts. To resolve this, more paths should be created.
Transcript: Ensemble Classifier Design and Performance Evaluation for Intrusion Detection Using UNSW-NB15 Dataset Zeinab Zoghi The University of Toledo Computer Science Research Project for Master of Science in Computer Science Engineering Special Thanks to My Advisor Dr. Gursel Serpen Reference References  Kumar, Vikash, Ayan Kumar Das, and Ditipriya Sinha. "UIDS: a unified intrusion detection system for IoT environment." Evolutionary Intelligence (2019): 1-13.  Kanimozhi, V., and Prem Jacob. "UNSW-NB15 Dataset Feature Selection and Network Intrusion Detection using Deep Learning."  Tama, Bayu Adhi, and Kyung-Hyune Rhee. "An in-depth experimental study of anomaly detection using gradient boosted machine." Neural Computing and Applications 31.4 (2019): 955-965.  Raman, MR Gauthama, et al. "An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm." Artificial Intelligence Review (2019): 1-32.  Sharma, Jivitesh, et al. "Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation." EURASIP Journal on Information Security 2019.1 (2019): 15.  Papamartzivanos, Dimitrios, Félix Gómez Mármol, and Georgios Kambourakis. "Dendron: Genetic trees driven rule induction for network intrusion detection systems." Future Generation Computer Systems 79 (2018): 558-574.  Kumar, Vikash, et al. "An integrated rule based intrusion detection system: analysis on UNSW-NB15 data set and the real time online dataset." Cluster Computing (2019): 1-22. Conclusion Conclusion The UNSW—NB15 has two major issues, namely class imbalance and class overlap, which need to be addressed prior to being employed for model development. Class imbalance and overlap, if not addressed, are likely to hinder the attack detection and identification performance of intrusion detection systems. We designed an ensemble IDS model and proposed two algorithms in order to shrink the number of false negative rate seen in UNSW-NB15 due to the class imbalance and class overlap The combination of the ensemble model and the algorithms outperformed seven models currently proposed in the literature Result and Discussion Results Binary Classification: 790 attack records are misclassified among the entire 45,332 attack records less than 2% of the overall attacks are misclassified as non-attack or Normal (0.017 missed alarm rate) 1022 of 37,000 Normal records are incorrectly classified as attacks (less than 3% false alarm rate) Multiclass Classification: 4.14% of the 28% overall missed alarm rate is the attack classes misclassified as Normal 3% of 4.14% are Shellcode, Fuzzers, and Analysis misclassified as Normal 23.86% missed alarm rate is associated with misclassification among attack classes 19.20% of Analysis, 6.69% of Backdoor, 4.35% of DoS, 3.04% of Exploits, 0.33% of Generic, 0.88% of Reconnaissance, 2.38% of Shellcode, and 4.55% of Worms attack records are confused with Normal records Binary Classification Binary Classification Multiclass Classification Multiclass Classification Comparative Performance Evaluation Comparative Binary Classification: Multiclass Classification: Data Analysis Analysis Data analysis in order to find if there is any data imbalance and data overlap issue Class Distribution Class Distribution Between-Class Imbalance Data Points Within-Class Imbalance Data Points Analyzing both data imbalance and data overlap with 3D scatter plot Class Overlap T-SNE and PCA PCA: mathematical dimensionality reduction method T-SNE (T- distributed Stochastic Neighbor Embedding): probabilistic dimensionality reduction method. Minimize Kullback-Leibler divergence using gradient descent method T-SNE KMeans Intercluster Distance Map displays the distance of a cluster center to other centers in 2-dimensions The clusters are sized by the number of instances that belong to each center K-mean Table Table Between-Class Imbalance Majority Classes: Normal, Exploits, Generic Minority Classes: Analysis, Backdoor, Shellcode, Worms Methods Methods Feature Selection: choose the smallest subset of features to simplify the subsequent analysis and improve the performance of machine learning algorithms Normalization: transform features to be on a similar scale to improves the performance and training stability of the model Classification: the process of assigning a class label to a particular instance Evaluation Metrics: capable to evaluate the performance of the machine learning Feature Selection Sequential Feature Selection (SFS): naive wrapper feature selection algorithm that starts with a null set and then adds one feature as the first step which depicts the highest value for the objective function. Elastic Net: select one feature among the highly correlated features in each iteration Feature Selection Schematic Diagram Schematic Diagram Diagram Data Cleaning Training: Data Transformation Elastic Net SFS Training Balanced Bagging,
Transcript: huddle Mrs. Rossi huddle to crowd together crowd huddle separate
Transcript: A Few Things I’ve Learned from Casual Teaching Work on the content and appearance of your CV and take the time to tailor it to each school Arrive early and take a crash course in your school’s setup Bring Resources Don’t go in guns blazing! Offer to help Leave a detailed note Make friends with the head teacher: admin as well as your colleagues Try to find a school that fits you Best of luck!
Transcript: Join Us Learn More http://www.facebook.com/study.at.australia What Students Say Recognized & Reputed Career @ UNSW
Transcript: Nobody knows babies like we do! Quality products . Good Customer service. Every Kid really loves this store.. BABYLOU ABOUT US About Us BabyLou was established in 2004. It has been more than a decade since we started, where we have ensured to take care of every need and want of every child and infant under one roof, true to the caption “NO BODY KNOWS BABIES LIKE WE DO”. Our benchmark is to provide 100% customer service and satisfaction and continue to deliver the same with a wide range of toys, garments and Baby Products. Play and Create We Are Best 01 02 03 Block games Building Blocks help Kids to use their brain. PLAY TO LEARN in Crusing Adventures Our Discoveries Enjoy a sunny vacation aboard a luxury yacht with the LEGO® Creator 3in1 31083 Cruising Adventures set. This ship has all the comforts you need, including a well-equipped cabin and a toilet. Sail away to a sunny bay and take the cool water scooter to the beach. Build a sandcastle, enjoy a picnic, go surfing or check out the cute sea creatures before you head back to the yacht for a spot of fishing. Escape into the mountains Disney Little Princes in Also available for your Babies..... Also... Out of The World… Our reponsibility BABYLOU…. Our Responsibility All children have the right to fun, creative and engaging play experiences. Play is essential because when children play, they learn. As a provider of play experiences, we must ensure that our behaviour and actions are responsible towards all children and towards our stakeholders, society and the environment. We are committed to continue earning the trust our stakeholders place in us, and we are always inspired by children to be the best we can be. Innovate for children We aim to inspire children through our unique playful learning experiences and to play an active role in making a global difference on product safety while being dedicated promoters of responsibility towards children.
Transcript: Google site and project. My project Hi!Nice to meet you! UNSW PELE The adventure of Jingxiong Liu My name is Jingxiong Liu. I come from China,Jiangsu Province. I like traveling,doing execises and reading. And my favorite sport is jogging. Thank you! I am a foodie~ (1) Practice makes perfect (2)Success belong to the persevering. （3）One takes on the attributes of one's associates. My google site helps me a lot in recording my progress or my stories. But I didn't use it properly ,and I need to to log more things on my log book. TO BE CONTINUED.... What I have learned. My project is designed for reading skills. And I have learned a lot from it. The project isn't perfect,but I'll keep improving it. My main resources are <WSJ>,<Economists>,<NYT>,Qura,and everything worth reading for me.
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