Teaching Art History to Design Students

Art History is often seen as a mandatory core course in the curricula of design programs but it is rarely tailored to the needs and goals of such programs. Instead, the traditional chronological organization of lecture topics, invariably beginning with the “Venus of Willendorf” (c. 25,000 BC) is presented in order to impart to the students a supposed holistic “big picture.” This essay outlines the re-structuring of a two-semester first-year faculty-wide introductory art history course, entitled “History of Art and Design,” in the Faculty of Fine Arts and Design at Izmir University of Economics, Izmir, Turkey. The course was re-configured from a conventional chronologically-presented (time-oriented) lecture series to a thematically presented (topic-oriented) lecture series more relevant to the students of the faculty – architecture, interior architecture, graphic design, industrial design, and fashion design students.

Impact of gate-source/drain channel architecture on the performance of an operational transconductance amplifier (OTA)

In this work, we report on the significance of gate-source/drain extension region (also known as underlap design) optimization in double gate (DG) FETs to improve the performance of an operational transconductance amplifier (OTA). It is demonstrated that high values of intrinsic voltage gain (A(VO_OTA)) > 55 dB and unity gain frequency (f(T_OTA)) similar to 57 GHz in a folded cascode OTA can be achieved with gate-underlap channel design in 60 nm DG MOSFETs. These values correspond to 15 dB improvement in A(VO_OTA) and three fold enhancement in f(T_OTA) over a conventional non-underlap design. OTA performance based on underlap single gate SOI MOSFETs realized in ultra-thin body (UTB) and ultra-thin body BOX (UTBB) technologies is also evaluated. A(VO_OTA) values exhibited by a DG MOSFET-based OTA are 1.3-1.6 times higher as compared to a conventional UTB/UTBB single gate OTA. f(T_OTA) values for DG OTA are 10 GHz higher for UTB OTAs whereas a twofold improvement is observed with respect to UTBB OTAs. The simultaneous improvement in A(VO_OTA) and f(T_OTA) highlights the usefulness of underlap channel architecture in improving gain-bandwidth trade-off in analog circuit design. Underlap channel OTAs demonstrate high degree of tolerance to misalignment/oversize between front and back gates without compromising the performance, thus relaxing crucial process/technology-dependent parameters to achieve 'idealized' DG MOSFETs. Results show that underlap OTAs designed with a spacer-to-straggle (s/sigma) ratio of 3.2 and operated below a bias current (IBIAS) of 80 mu A demonstrate optimum performance. The present work provides new opportunities for realizing future ultra-wide band OTA design with underlap DG MOSFETs.

Simple trapped-ion architecture for high-fidelity Toffoli gates

We discuss a simple architecture for a quantum TOFFOLI gate implemented using three trapped ions. The gate, which, in principle, can be implemented with a single laser-induced operation, is effective under rather general conditions and is strikingly robust (within any experimentally realistic range of values) against dephasing, heating, and random fluctuations of the Hamiltonian parameters. We provide a full characterization of the unitary and noise-affected gate using three-qubit quantum process tomography.

An On Demand Queue Management Architecture for a Programmable Traffic Manager

A queue manager (QM) is a core traffic management (TM) function used to provide per-flow queuing in access andmetro networks; however current designs have limited scalability. An on-demand QM (OD-QM) which is part of a new modular field-programmable gate-array (FPGA)-based TM is presented that dynamically maps active flows to the available physical resources; its scalability is derived from exploiting the observation that there are only a few hundred active flows in a high speed network. Simulations with real traffic show that it is a scalable, cost-effective approach that enhances per-flow queuing performance, thereby allowing per-flow QM without the need for extra external memory at speeds up to 10 Gbps. It utilizes 2.3%–16.3% of a Xilinx XC5VSX50t FPGA and works at 111 MHz.

A Pipeline Interleaved Heterogeneous SIMD Soft Processor Array Architecture for MIMO-OFDM Detection

The most promising way to maintain reliable data transfer across the rapidly fluctuating channels used by next generation multiple-input multiple-output communications schemes is to exploit run-time variable modulation and antenna configurations. This demands that the baseband signal processing architectures employed in the communications terminals must provide low cost and high performance with runtime reconfigurability. We present a softcore-processor based solution to this issue, and show for the first time, that such programmable architectures can enable real-time data operation for cutting-edge standards
such as 802.11n; furthermore, by exploiting deep processing pipelines and interleaved task execution, the cost and performance of these architectures is shown to be on a par with traditional dedicated circuit based solutions. We believe this to be the first such programmable architecture to achieve this, and the combination of implementation efficiency and programmability makes this implementation style the most promising approach for hosting such dynamic architectures.

Fully hardware based WFQ architecture for high-speed QoS packet scheduling

A full hardware implementation of a Weighted Fair Queuing (WFQ) packet scheduler is proposed. The circuit architecture presented has been implemented using Altera Stratix II FPGA technology, utilizing RLDII and QDRII memory components. The circuit can provide fine granularity Quality of Service (QoS) support at a line throughput rate of 12.8Gb/s in its current implementation. The authors suggest that, due to the flexible and scalable modular circuit design approach used, the current circuit architecture can be targeted for a full ASIC implementation to deliver 50 Gb/s throughput. The circuit itself comprises three main components; a WFQ algorithm computation circuit, a tag/time-stamp sort and retrieval circuit, and a high throughput shared buffer. The circuit targets the support of emerging wireline and wireless network nodes that focus on Service Level Agreements (SLA's) and Quality of Experience.

Incremental learning from stream data

Recent years have witnessed an incredibly increasing interest in the topic of incremental learning. Unlike conventional machine learning situations, data flow targeted by incremental learning becomes available continuously over time. Accordingly, it is desirable to be able to abandon the traditional assumption of the availability of representative training data during the training period to develop decision boundaries. Under scenarios of continuous data flow, the challenge is how to transform the vast amount of stream raw data into information and knowledge representation, and accumulate experience over time to support future decision-making process. In this paper, we propose a general adaptive incremental learning framework named ADAIN that is capable of learning from continuous raw data, accumulating experience over time, and using such knowledge to improve future learning and prediction performance. Detailed system level architecture and design strategies are presented in this paper. Simulation results over several real-world data sets are used to validate the effectiveness of this method.