Hk comp software standards

Bayesian learning. Ensemble Methods. Deep learning. Human language technology for text and spoken language. Machine learning, syntactic parsing, semantic interpretation, and context-based approaches to machine translation, text mining, and web search. Data modeling concepts; conceptual, logical and physical design; analyzing, evaluating and improving schemas; schema documentation and maintenance; functional analysis; design tools; schema mappings; database tuning; distributed database design.

Text retrieval models, vector space model, document ranking, performance evaluation; indexing, pattern matching, relevance feedback, clustering; web search engines, authority-based ranking; enterprise data management, content creation, meta data, taxonomy, ontology; semantic web, digital libraries and knowledge management applications. This course will provide an introduction to concepts and techniques in the field of data mining. Materials include an introduction to data warehousing and OLAP, data preprocessing and the techniques used to explore the large quantities of data for the discovery of predictive models and knowledge.

The course will include techniques such as nearest neighbor, decision tress, neural networks, Bayesian networks and Naive Bayes, rule-based methods, association analysis and clustering, as well as social networks and data mining applications in business and finance applications, and other emerging data mining subareas.

Students learn the materials by attending lectures and implementing and applying different data analysis and mining techniques to large datasets throughout the semester. This course will expose students to new and practical issues of real world mining and managing big data. Data mining and management is to effectively support storage, retrieval, and extracting implicit, previously unknown, and potentially useful knowledge from data.

This course will place emphasis on two parts. The first part is big data issues such as mining and managing on distributed data, sampling on big data and using some cloud computing techniques on big data. The second part is applications of the techniques learnt on areas such as business intelligence, science and engineering, which aims to uncover facts and patterns in large volumes of data for decision support.

This course builds on basic knowledge gained in the introductory data-mining course, and explores how to more effectively mine and manage large volumes of real-world data and to tap into large quantities of data. Working on real world data sets, students will experience all steps of a data-mining and management project, beginning with problem definition and data selection, and continuing through data management, data exploration, data transformation, sampling, portioning, modeling, and assessment.

Display technologies; scan conversion; clipping; affine transformations; homogeneous coordinates and projection; viewing transformations; hidden surface removal; reflectance and shading models; ray tracing; spline curves and surfaces; hierarchical modeling; texture mapping; color models.

Introduction to image processing. Topics include image processing and analysis in spatial and frequency domains, image restoration and compression, image segmentation and registration, morphological image processing, representation and description, object recognition, related application areas and some other closely related topics. Some sophisticated image processing and analysis tools and state-of-the-art methods may also be introduced subject to the availability of time.

Color theory; digital audio, image and video fundamentals, representation, and processing; digital multimedia applications and programming. This experiential project course will provide hands-on experiences in creating music and soundtracks with a wide range of emotional characteristics for a variety of situations in computer games and videos.

The course is structured as if at an LA film school for sound designers, and contrasting in style and content from other UST courses, where the primary focus includes emotional not just technical control. This course will provide a creative outlet for applying problem-solving in a deep and engaging way to music. Whether students have music background or not, this course will provide them a chance to explore music almost like a composer.

Students will share their musical creations and learn from one another, and create music that modulates the moods of listeners. Computer game development touches on many facets of computer science, including computer graphics, artificial intelligence, algorithms, networking, human-computer interaction, music, and sound. This course will cover all of these aspects, with special emphasis on real-time graphics rendering.

Students will get hands-on experience on how to design and implement real-world computer games, which will help improve their skills in programming, teamwork, management, and communication. This course is a broad introduction to Human-Computer Interaction HCI , with an emphasis on techniques, models, theories, and applications for designing, prototyping, and evaluating current and future interactive systems for human use. HCI is an interesting and important area of study, providing the human perspective to computing.

Besides technology and innovation, it also touches on issues like ethics and social responsibilities related to technologies in the real world. This course will introduce visualization techniques for data from everyday life, social media, business, scientific computing, medical imaging, etc.

The labs and the course project will give students hands-on experience to turn their data into beautiful visualizations. Alternate code s. Deep learning has significantly advanced the performance of computer vision system from object recognition to image processing. This course covers the basics and various applications of deep learning in computer vision. Students will study the details of convolutional neural networks as well as recurrent neural networks and train deep networks with end-to-end optimization, and learn deep learning based approaches for both high-level and low-level computer vision tasks such as image recognition and image enhancement.

Through programming projects, students will implement, train, and test deep neural networks on cutting-edge computer vision research. Students would be required to study or do research in a final course project related to deep learning and computer vision and present their work by the end of the course. This course is designed to equip students, who have a particular interest in becoming practitioners, with substantial hands-on experience in solving concrete problems in a computer operating system, via programming, in a laboratory intensive course.

Students will notably experiment with many topics in the areas of operating systems and network protocols, such as: boot loaders, shell, process management, system calls, process scheduler, file system, virtual memory, network protocols and packet filtering, system modules and device drivers. Principles of application development for mobile and embedded devices. Mobile software development environments and software architectures. Features of typical mobile platforms: user-interface and user-experience design, multimedia, 2D and 3D graphics and data storage support, networking, location and mapping services.

Design patterns and application frameworks. Mobile back-end support. Web applications. Students need to design and implement a full-fledged mobile application. Analysis, synthesis and evaluation of different computer architectures. Principles of computer network architectures and communication protocols; the OSI reference model; switching and multiplexing techniques; data link, network, transport and application layers; LAN and medium access protocols; network programming.

Cryptosystems, symmetric-key and public-key cryptography, cryptanalysis, authentication, message digests, digital signatures, and random number generation. Access controls and firewalls. Applications such as certificate authorities, electronic commerce, smartcards, and digital cash. This course equips students with cybersecurity knowledge and current IT practices on security risk management. Through hands-on laboratory sessions, students will understand existing IT security issues, learn how to assess IT security risks, and conduct experiments on ethical hacking.

They will practice system attack and defense strategies using security tools, so as to gain practical experience to become a cybersecurity professional.

The course covers current security trends, industrial practices on IT security, design requirements for secure web and mobile applications, security assessment, risk analysis and risk management. Knowledge in web programming and database administration is not essential but a plus. This course is an introduction to social information network analysis and engineering.

Students will learn both mathematical and programming knowledge for analyzing the structures and dynamics of typical social information networks e. Facebook, Twitter, and MSN. They will also learn how social metrics can be used to improve computer system design as people are the networks. It will cover topics such as small world phenomenon; contagion, tipping and influence in networks; models of network formation and evolution; the web graph and PageRank; social graphs and community detection; measuring centrality; greedy routing and navigations in networks; introduction to game theory and strategic behavior; social engineering; and principles of computer system design.

Students who do not have the prerequisites but with equivalent background may seek approval from the instructor for enrollment in the course. Big data systems, including Cloud Computing and parallel data processing frameworks, emerge as enabling technologies in managing and mining the massive amount of data across hundreds or even thousands of commodity servers in datacenters.

This course exposes students to both the theory and hands-on experience of this new technology. The course will cover the following topics. By walking through a number of hands-on labs and assignments, students are expected to gain first-hand experience programming on real world clusters in production datacenters.

This course is for academic and professional development of students in the programs offered by the Department of Computer Science and Engineering.

Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Terms and conditions apply, please refer to 3Business website for details. HK Electric has recently received enquiries from customers regarding the bogus emails they received.

Please stay alert for bogus emails with false information; and do not open any attachments or hyperlinks in the bogus emails but delete them as soon as possible. With Power We Serve. Previous Banner. A quick breakdown of key reporting timelines. Briefly, the annual compliance requirements in Hong Kong are simple but attentive. People can easily find out the procedure, online forms, instructions, etc. Being one of the most desirable jurisdictions for business start-up and development, Hong Kong Government is serious about the annual compliance obligations.

You should be aware of the yearly filing to prevent unexpected penalties. Take a look at our services and see how we can help you with Hong Kong company incorporation, corporate secretary, accounting, auditing, tax filing and business advisory. Table of Contents. Content Team. Get Started. Conclusion Briefly, the annual compliance requirements in Hong Kong are simple but attentive.

Table of Contents 1. Annual Compliance Requirements in Hong Kong 1. Renewal of Company Secretary and Registered Office 1. Accounting and Auditing 1. Renewal of Hong Kong Business Registration 1. Internal Records 1.

Annual General Meetings 1. Maintenance and Update of any Changes to the Companies Registry 1.