Miracle-dz/UniFAR-FTUs huggingface dataset:
PENCIRIAN REKABENTUK KONSEP SOFA ERGONOMIK MENGIKUT PERSEPSI PENGGUNA: KAJIAN KES DI MALAYSIA

AbstrakPembangunan rekabentuk konsep sofa ergonomik adalah melibatkan daripada pelbagai ciri-ciri dankaedah-kaedah rekabentuk. Salah satu daripada kaedah yang boleh digunakan dalam menentukankonsep rekabentuk yang paling sesuai adalah proses penambahbaikan kerusi sofa yang sediadadan menerapkan beberapa kaedah yang berkaitan ke dalam struktur pembangunan rekabentuksofa ergonomik melalui persepsi pengguna. Untuk mencapai tujuan itu, suatu kaji selidik respondenmelibatkan 30 orang pengguna dilakukan untuk mendapat maklumbalas awal terhadap rekabentuksofa yang terdapat dipasaran dan biasa digunakan dikalangan pegawai-pegawai kerajaan dan swasta.Soalan kaji selidik menitik beratkan kepada konsep sofa, ciri-ciri am sofa, asas pemilihan struktur, asaspemilihan warna, dan asas anggaran harga. Seterusnya, keperluan ini akan dikenalpasti mengikutkeutamaan dan diterjemahkan kedalam pembangunan rekabentuk sofa ergonomik dengan menerapkandata antropometrik dalam pembangunan tersebut. Berdasarkan keputusan data analisis menunjukkanrekabentuk konsep sofa ergonomik telah mempengaruhi kesan fizikal kepada manusia. Kaji selidik iniamat penting dalam melihat persepsi pengguna selain dapat mengkaji penerapan unsur-unsur sainsfizikal kedalam proses rekabentuk konsep sofa ergonomik. Kajian ini memberi satu implikasi yangbesar dalam pembangunan rekabentuk konsep sofa ergonomik bagi meningkatkan mutu produktivitidalam industri perabut di Malaysia. Abstract The development of Conceptual Ergonomics Sofa Design involved variety of features and methods. Oneof methods that can be used in determining the most appropriate design is the process of upgrading theexisting sofa chair and applying some methods in related to the structural development of the designconcept through user perceptions. To achieve this goal, a survey study was conducted involving 30respondents to obtain user feedback on the sofa design whereas the commonly used sofa available in themarket and at the government office as well as at the private sector. Survey questioniore was emphasizedon the concept sofa, sofa general characteristics, the basic structure of the selection, basic color selection,and price estimation basis. Further, these requirements will be identified and prioritized to be translatedinto the development of ergonomic design sofa by applying anthropometric data in this development.Based on the results of data analysis showed conceptual design sofa has affected the physical effect onman. The survey is very important in the perception of consumers in addition to reviewing the applicationof the elements of physical science concepts into the design process ergonomic sofa. This study providesa major implications in the development of conceptual design for ergonomic sofa improve productivity inthe furniture industry in Malaysia.
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges

This paper describes the third Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022. The 3rd ABAW Competition is a continuation of the Competitions held at ICCV 2021, IEEE FG 2020 and IEEE CVPR 2017 Conferences, and aims at automatically analyzing affect. This year the Competition encompasses four Challenges: i) uni-task Valence-Arousal Estimation, ii) uni-task Expression Classification, iii) uni-task Action Unit Detection, and iv) MultiTask-Learning. All the Challenges are based on a common benchmark database, Aff-Wild2, which is a large scale in-the-wild database and the first one to be annotated in terms of valence-arousal, expressions and action units. In this paper, we present the four Challenges, with the utilized Competition corpora, we outline the evaluation metrics and present both the baseline systems and the top performing teams’ per Challenge. Finally we illustrate the obtained results of the baseline systems and of all participating teams. More information regarding the Competition and the leaderboard for each Challenge can be found in the competition’s website: http://ibug.doc. ic.ac. uk/resources/cvpr-2022-3rd-abaw.
Fast Semantic-Assisted Outlier Removal for Large-scale Point Cloud Registration

With current trends in sensors (cheaper, more volume of data) and applications (increasing affordability for new tasks, new ideas in what 3D data could be useful for); there is corresponding increasing interest in the ability to automatically, reliably, and cheaply, register together individual point clouds. The volume of data to handle, and still elusive need to have the registration occur fully reliably and fully automatically, mean there is a need to innovate further. One largely untapped area of innovation is that of exploiting the {\em semantic information} of the points in question. Points on a tree should match points on a tree, for example, and not points on car. Moreover, such a natural restriction is clearly human-like - a human would generally quickly eliminate candidate regions for matching based on semantics. Employing semantic information is not only efficient but natural. It is also timely - due to the recent advances in semantic classification capabilities. This paper advances this theme by demonstrating that state of the art registration techniques, in particular ones that rely on"preservation of length under rigid motion"as an underlying matching consistency constraint, can be augmented with semantic information. Semantic identity is of course also preserved under rigid-motion, but also under wider motions present in a scene. We demonstrate that not only the potential obstacle of cost of semantic segmentation, and the potential obstacle of the unreliability of semantic segmentation; are both no impediment to achieving both speed and accuracy in fully automatic registration of large scale point clouds.
Emergence of splits and collective turns in pigeon flocks under predation

Complex patterns of collective behaviour may emerge through self-organization, from local interactions among individuals in a group. To understand what behavioural rules underlie these patterns, computational models are often necessary. These rules have not yet been systematically studied for bird flocks under predation. Here, we study airborne flocks of homing pigeons attacked by a robotic falcon, combining empirical data with a species-specific computational model of collective escape. By analysing GPS trajectories of flocking individuals, we identify two new patterns of collective escape: early splits and collective turns, occurring even at large distances from the predator. To examine their formation, we extend an agent-based model of pigeons with a ‘discrete’ escape manoeuvre by a single initiator, namely a sudden turn interrupting the continuous coordinated motion of the group. Both splits and collective turns emerge from this rule. Their relative frequency depends on the angular velocity and position of the initiator in the flock: sharp turns by individuals at the periphery lead to more splits than collective turns. We confirm this association in the empirical data. Our study highlights the importance of discrete and uncoordinated manoeuvres in the collective escape of bird flocks and advocates the systematic study of their patterns across species.
Undefining life's biochemistry: implications for abiogenesis

In the mid-twentieth century, multiple Nobel Prizes rewarded discoveries of a seemingly universal set of molecules and interactions that collectively defined the chemical basis for life. Twenty-first-century science knows that every detail of this Central Dogma of Molecular Biology can vary through either biological evolution, human engineering (synthetic biology) or both. Clearly the material, molecular basis of replicating, evolving entities can be different. There is far less clarity yet for what constitutes this set of possibilities. One approach to better understand the limits and scope of moving beyond life's central dogma comes from those who study life's origins. RNA, proteins and the genetic code that binds them each look like products of natural selection. This raises the question of what step(s) preceded these particular components? Answers here will clarify whether any discrete point in time or biochemical evolution will objectively merit the label of life's origin, or whether life unfolds seamlessly from the non-living universe.
Mixed Reality in Architecture

Nowadays, strong influence of technology development in all areas of science and arts (architecture) can be observed. Therefore, it is not surprising that some of the contemporary topics in architectural discourse (particularly in the context of cutting edge technologies) are closely related to technology. For example, new mixed reality devices coming to the commercial market belong to the area of research that is working with mixed realities and virtual spaces. Advantage of this technology is that it enables more dynamic and realistic perception of the computer designed world. Recent development and better accessibility of MR hardware has brought higher attention of designers to this problematic. Together with technology of games engines, the new powerful designing tool is emerging. The existence of this technology has an ability to transform design processes in the field of architecture.
The Effect of Program Cost on Minority Student Virtual Computing Outreach Participation

A Historically Black College or University (HBCU) hosted a virtual supplemental learning program to expose underrepresented minority and low-income youth to game development via Construct 3: Game Making Software. The program implemented a hybrid need-based admissions model that compared paid, subsidized, and free virtual outreach participation among underrepresented minority (URM) and low-income adolescents. Due to the program's unique distinctions: a virtual learning environment amid COVID-19, African American undergraduate instructors, and its need-based admissions model, it is unclear which factors directly affected student participation. Future directions include investigating what factors contributed to participation rates, obtaining student and parent feedback, and comparing this program to summer programs for underrepresented students.
Integrated Data Science for Secondary Schools: Design and Assessment of a Curriculum

We propose that secondary-school data-science curricula should be based on four key ingredients: two are technical (programming and statistics, with visualization sitting at their intersection), while two are human-facing (meaningful domains, and civic responsibility). We describe their relationship and argue for their importance. Based on this, we then present the Bootstrap:Data Science curriculum, designed for integration into multiple disciplines and settings. It achieves this by (a) being designed as a set of remix-able lessons, and (b) letting classes and students choose personally meaningful datasets. We also initiate the process of evaluating this curriculum. We create two assessment instruments, one focused on learning and the other on personalization and engagement. We provide very preliminary data gathered from students and teachers.
Scratch and Sense: Using Real-Time Sensor Data to Motivate Students Learning Scratch

Block-based programming environments are a popular way to introduce programming as they provide helpful visual cues and remove the complexities of syntax, allowing learners to focus on being creative. However, input to programs in block-based environments is often limited to the keyboard and mouse, meaning programs respond only to the direct actions of the user. Allowing programs to respond to changes in the physical environment may influence the types of programs students create and their motivation and interest towards learning programming. We explore this idea by integrating real-time sensor data into Scratch. With our platform, students simply connect a sensor to their computer via USB and use custom blocks, alongside conventional Scratch code, to read and react to the sensor data in real-time. We evaluated this approach using a field study involving 25 students with limited prior experience in Scratch. We found students were highly motivated by the sensors and expressed a strong desire to use them in future projects. Analysis of the created programs revealed that, compared to using standard input sources, students explored a wider variety of Scratch blocks when controlling sprites using the sensors.
Path-sensitive and alias-aware typestate analysis for detecting OS bugs

Operating system (OS) is the cornerstone for modern computer systems. It manages devices and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve reliability and security of computer systems. Static typestate analysis is a common technique for detecting different types of bugs, but it is often inaccurate or unscalable for large-size OS code, due to imprecision of identifying alias relationships as well as high costs of typestate tracking and path-feasibility validation. In this paper, we present PATA, a novel path-sensitive and aliasaware typestate analysis framework to detect OS bugs. To improve the precision of identifying alias relationships in OS code, PATA performs a path-based alias analysis based on control-flow paths and access paths. With these alias relationships, PATA reduces the costs of typestate tracking and path-feasibility validation, to boost the efficiency of path-sensitive typestate analysis for bug detection. We have evaluated PATA on the Linux kernel and three popular IoT OSes (Zephyr, RIOT and TencentOS-tiny) to detect three common types of bugs (null-pointer dereferences, uninitialized variable accesses and memory leaks). PATA finds 574 real bugs with a false positive rate of 28%. 206 of these bugs have been confirmed by the developers of the four OSes.We also compare PATA to seven state-of-the-art static approaches (Cppcheck, Coccinelle, Smatch,CSA, Infer, Saber and SVF). PATA finds many real bugs missed by them, with a lower false positive rate.
A one-for-all and o(v log(v ))-cost solution for parallel merge style operations on sorted key-value arrays

The processing of sorted key-value arrays using a “merge style operation (MSO)” is a very basic and important problem in domains like scientific computing, deep learning, database, graph analysis, sorting, set-operation etc. MSOs dominate the execution time in some important applications like SpGEMM and graph mining. For example, sparse vector addition as an MSO takes up to 98% execution time in SpGEMM in our experiment. For this reason, accelerating MSOs on CPU, GPU, and accelerators using parallel execution has been extensively studied but the solutions in prior work have three major limitations. (1) They treat different MSOs as isolated problems using incompatible methods and an unified solution is still lacking. (2) They do not have the flexibility to support variable key/value sizes and value calculations in the runtime given a fixed hardware design. (3) They require a quadratic hardware cost (O(V2)) for given parallelism V in most cases. To address above three limitations, we make the following efforts. (1) We present a one-for-all solution to support all interested MSOs based on a unified abstraction model “restricted zip machine (RZM)”. (2) We propose a set of composable and parallel primitives for RZM to provide the flexibility to support variable key/value sizes and value calculations. (3) We provide the hardware design to implement the proposed primitives using only O(Vlog(V)) resource. With the above techniques, a flexible and efficient solution for MSOs has been built. Our design can be used either as a drop-in replacement of the merge unit in prior accelerators to reduce the cost from O(V2) to O(Vlog(V)), or as an extension to the SIMD ISA of CPU and GPU. In our evaluation on CPU, when V=16 (512-bit SIMD, 32-bit element), we achieve significant speedup on a range of representative kernels including set operations (8.4×), database joins (7.3×), sparse vector/matrix/tensor addition/multiplication on real/complex numbers (6.5×), merge sort (8.0× over scalar, 3.4× over the state-of-the-art SIMD), and SpGEMM (4.4× over the best one in the baseline collection).
TMO: transparent memory offloading in datacenters

The unrelenting growth of the memory needs of emerging datacenter applications, along with ever increasing cost and volatility of DRAM prices, has led to DRAM being a major infrastructure expense. Alternative technologies, such as NVMe SSDs and upcoming NVM devices, offer higher capacity than DRAM at a fraction of the cost and power. One promising approach is to transparently offload colder memory to cheaper memory technologies via kernel or hypervisor techniques. The key challenge, however, is to develop a datacenter-scale solution that is robust in dealing with diverse workloads and large performance variance of different offload devices such as compressed memory, SSD, and NVM. This paper presents TMO, Meta’s transparent memory offloading solution for heterogeneous datacenter environments. TMO introduces a new Linux kernel mechanism that directly measures in realtime the lost work due to resource shortage across CPU, memory, and I/O. Guided by this information and without any prior application knowledge, TMO automatically adjusts how much memory to offload to heterogeneous devices (e.g., compressed memory or SSD) according to the device’s performance characteristics and the application’s sensitivity to memory-access slowdown. TMO holistically identifies offloading opportunities from not only the application containers but also the sidecar containers that provide infrastructure-level functions. To maximize memory savings, TMO targets both anonymous memory and file cache, and balances the swap-in rate of anonymous memory and the reload rate of file pages that were recently evicted from the file cache. TMO has been running in production for more than a year, and has saved between 20-32% of the total memory across millions of servers in our large datacenter fleet. We have successfully upstreamed TMO into the Linux kernel.
How is Computational Thinking Defined in Elementary Science?

Computational thinking (CT) is a foundational skill of computer science that all elementary students should have equitable access to for learning and engaging in throughout their day. For the integration of CT into science instruction to be successful, teachers need to be able to communicate clearly what CT is and how it is defined through precise language. The intention of this poster is to explore the meaning of CT at the elementary level through a critical review of literature, analysis of standards, value-mapping across multiple stakeholders, analysis of written responses from elementary teachers on a CT survey, and deep discussions of a Design-Based Implementation Research Team (DBIR). The data collected and analyzed from these sources was combined to develop a definition of CT that would support implementation of CT for elementary teachers.
Tree traversal synthesis using domain-specific symbolic compilation

Efficient computation on tree data structures is important in compilers, numeric computations, and web browser layout engines. Efficiency is achieved by statically scheduling the computation into a small number of tree traversals and by performing the traversals in parallel when possible. Manual design of such traversals leads to bugs, as observed in web browsers. Automatic schedulers avoid these bugs but they currently cannot explore a space of legal traversals, which prevents exploring the trade-offs between parallelism and minimizing the number of traversals. We describe Hecate, a synthesizer of tree traversals that can produce both serial and parallel traversals. A key feature is that the synthesizer is extensible by the programmer who can define a template for new kinds of traversals. Hecate is constructed as a solver-aided domain-specific language, meaning that the synthesizer is generated automatically by translating the tree traversal DSL to an SMT solver that synthesizes the traversals. We improve on the general-purpose solver-aided architecture with a scheduling-specific symbolic evaluation that maintains the engineering advantages solver-aided design but generates efficient ILP encoding that is much more efficient to solve than SMT constraints. On the set of Grafter problems, Hecate synthesizes traversals that trade off traversal fusion to exploit parallelism. Additionally, Hecate allows defining a tree data structure with an arbitrary number of children. Together, parallelism and data structure improvements accelerate the computation 2× on a tree rendering problem. Finally, Hecate’s domain-specific symbolic compilation accelerates synthesis 3× compared to the general-purpose compilation to an SMT solver; when scheduling a CSS engine traversal, this ILP-based synthesis executes orders of magnitude faster.
Unplugged Parallelism for First-Year CS Majors

We use "unplugged" activities to introduce parallel concepts in a first-year seminar for Computer Science majors. Student teams explore parallel approaches to computational tasks. Pre- and post-activity surveys, and a reflection paper, measure the impact of these activities on students' views about parallel programming. Our goal is to encourage parallel thinking about programming tasks before sequential approaches become ingrained. Computer Science curricula have traditionally focused on sequential approaches to programming, which were well matched to earlier computer systems. However, current systems almost all use multiprocessor CPUs, and are frequently used in clusters or networks of multiple computers. Recent curricular guidelines from organizations such as ACM and ABET recommend exposure to parallel computing concepts.
Design and Use of a Visualization for Teaching Integer Coercion

The C language is used to develop software that implements fundamental mechanisms used by higher level software to protect data. Yet C continues to be difficult for students to understand and use securely, and integer errors continue to create vulnerabilities. In fact, \em Integer Overflow or Wraparound is listed at position 11 in the 2020 CWE Top 25 Most Dangerous Software Weaknesses. This paper presents the Expression Evaluation (EE) visualization tool that helps students understand the type conversions that take place implicitly within a C program. This tool depicts step-wise the coercions that take place within the compilation of an expression with mixed integer type operands. This enables students to create unlimited examples to test their understanding. We present the results of our evaluation of EE in both a lower-level class and an upper-level class. We also present the results of an expanded evaluation of a complementary integer security education tool Integer Representation (IR) in these same classes. This represents evaluation of IR across a wider student audience; prior evaluations of the IR tool were within classes focused on low-level programming and security. Our evaluation results showed that students in an upper-level course improved their understanding in both IR and EE more significantly than students in a lower-level course. As shown by the data collected from both classes, our tools were easy to use and very effective.