Miracle-dz/UniFAR-FTUs huggingface dataset:
Urban Forms in Planning and Design

This paper on urban form in planning and design is intended to discuss how the old concepts are changing and new meaning of the urban form is emerging in the planning and development of urban centres . The paper is an attempt to elucidate the basic concepts of the urban forms and how they are perceived at different levels of the planning and design exercises. The paper finally concludes with findings and recommendations which can guide the future course of development of new towns and the growth of the urban centres .
Current and future EMI challenges at Intel and how to manage them

Most EMI issues have been resolved using expensive enclosures and gaskets at the system level. In addition, simple components such as decoupling and filtering devices were added to the board to reduce power plane and I/O (input/output) port noise. These were acceptable methodologies in the past when clock frequencies were low (<33 MHz), and cost pressures were less 'overbearing'. However, these approaches are not possible due to increasing frequencies (/spl sim/ GHz) and power (/spl sim/100 W) requirements. The traditional methods are not working since the chassis has limited shielding effectiveness above 1 GHz, and decoupling and filtering devices are ineffective at high frequencies. In addition, with the popularity of the value PC, it is undesirable to add cost to the system. This paper summarizes the historical problems and solutions encountered at Intel, and providing few approaches that have yielded great benefits in terms of solution and cost. In addition, future approaches for effective EMI management at the system, board, and component levels are discussed.
Feng-Shui Knowledge-Based System Untuk Membantu Penentuan Harga Rumah Pada Property Agent

Ilmu feng-shui atau seni tata letak tanah sudah dikenal sejak jaman kuno. Feng-shui banyak dipakai oleh masyarakat Indonesia etnis Tionghoa, dan bahkan etnis lain juga, sebagai pertimbangan dalam membeli rumah. Hal ini dilihat sebagai peluang oleh property agent dalam meng-customize harga rumah mewah yang mereka jual. Belakangan ini banyak property agent yang bekerja sama dengan ahli feng-shui dalam menentukan harga jual rumah mewah sesuai dengan karakteristik calon pembelinya. Sistem ini dibuat untuk membantu para broker rumah pada sebuah property agent guna menganalisa dan meng-customize harga jual rumah berdasarkan ilmu feng-shui. Knowledge-Based Forward Chaining System berbasis Feng-shui yang dikombinasi dengan sebuah fungsi linier dinamis digunakan pada sistem ini guna menghasilkan nilai jual ‘customize’ sebuah rumah mewah. Selain itu sistem dapat pula membantu broker rumah untuk memberikan ‘nasehat’ tentang tipe rumah seperti apa yang cocok pada calon pembelinya. Berdasarkan hasil kuisioner dari calon pengguna, yaitu broker rumah dan pemilik sebuah property agent di surabaya, dengan total nilai kuisioner sebesar 87% dapat disimpulkan bahwa sistem ini telah layak digunakan dan sesuai dengan harapan calon pengguna. Kata Kunci: Feng-shui, Knowledge-Based System, Forward Chaining, Property Agent
EPR AND ITS EFFECTIVENESS IN HIGHER EDUCATION

The recent transformations of higher education system in Indian context, concerns the thinking modern business requirements and sustainable development. Since, many higher educational institutions are employing novel techniques and tools from business sector to meet the requirements of modern management with the aim of mirroring academia to industry. The thought of Re-engineering in education consists of instructional systems with learning experiences as well as governance and support systems. The existing concept of Business Process Re-engineering (BPR) is being practiced as a successful tool in many business organizations with periodical processes evaluation from supplier to customer, and restructuring systems. The Companies use BPR to reduce costs, cycle time and to improve total quality and customer satisfaction. This paper explores the use of adopting BPR into Higher Educational Institutions as a novel approach, to look after functionalities in each process, and named it as Education Process Re-engineering (EPR). And the purpose depends on expectations and focuses on the end user adeptness and gain competitive advantage. Because Career Vision of the student before embarking on higher education may be different from what a student achieves after the course. This paper also showcases the various metrics which are created and evaluated for academic purposes to enhance the quality of teaching –learning pedagogy.
TELL us all about it: establishment of a Technology Enhanced Learning Laboratory

This paper presents a case study of the design and development of the Technology Enhanced Learning Laboratory (TELL), a physical, multi-purpose, “sandpit” space at the University of Southern Queensland (USQ). As USQ is a regional, predominantly distance learning, multi-campus institution with students studying off-campus in both national and international locations, the TELL aligns with the University Vision to improve learning and increase access through innovative pedagogy and the creative use of technology. The TELL also supports the flexible learning priorities identified in the Learning and Teaching Operational Plan 2007-2012. The Lab is quite different from existing physical learning spaces, such as lecture theatres and ICT training rooms. It embraces the ‘next generation learning spaces’ concept by adopting an open plan, studio-style room, with flexible, configurable technologies and fittings. The research and development intent of the TELL suggests that it should not be used for regular timetabled classes as the aim is to make it available for trial-based activity through an electronic booking system. Preliminary evaluation data indicate that the successful uptake of the TELL will be influenced by institutional buy-in, ease of use, sustainable support structures (including ICT and pedagogical), and evidence of pedagogical enhancement. Because of the newness of this project, a structured, ongoing evaluation process is in the design stage and will soon be rolled out.
Mechanisms of Third-order Harmonic in TC-SAW Resonators Using a Nonlinear FEM Model

The nonlinearity generation mechanisms in temperature compensated SAW (TC-SAW) devices arouse great interest recently. Accurate nonlinearity-simulation methods are needed eagerly to predict and further help suppress devices' nonlinearity. This paper develops the propagation theory of finite amplitude waves in nonlinear mediums. The low-frequency variable coupling terms become higher-order nonlinear physical fields' source to derive the third-order harmonic (H3) wave equation. Several important nonlinear origins are taken into full consideration including geometry and material nonlinearity. Based on the nonlinear theory, a nonlinear FEM model is set to directly calculate H3 in TC-SAW resonators without material scale factors, and the bulk mode nonlinear origin is considered with the finite thickness of the piezoelectric substrate. The model explains the periodic bulk wave characteristics of H3 are mainly caused by the nonlinear elastic effect. The amplitude of H3 increases with the thickness of metal and cover layers. Moreover, a new TC-SAW structure with small bumps above the cover layer is designed to suppress H3 response by about 12 dBm.
A Measure of Energy Density to Quantify Progress in Pb-free Piezoelectric Material Development

The negative environmental impact of Pb has led to an increased demand for Pb-free electronics. This is particularly important in ultrasonic transducers where Pb-based piezoelectric materials, primarily ceramic PZT, are the dominant choice. Naturally for Pb-free materials to become a viable option, the performance must match that of the current standard. However, present comparison methods and figures of merit for piezoelectric materials are based on specific use cases which can lead to disparate results. In the work described here, a new measure is developed for the performance of a piezoelectric material, based on its energy density. This was achieved by developing a generalized electromechanical coupling factor derived from first principles and defined at zero frequency. It encompasses all conversion mechanisms allowed by symmetry and so avoids any resonance/geometry effects which obscure the pure material response. Comparison between Pb-free materials using this new coupling factor are made within the context of PZT and high performance piezocrystal and were validated using finite element analysis. Whilst no Pb-free materials currently match the level of PZT/single crystal by this method, it is shown that the new figure of merit is independent of geometry and other spatial effects and thus allows a fully unbiased comparison between materials. Hence it defines a universal measure against which Pb-free material development may be traced.
MAEF-Net: Multi-Attention Efficient Feature Fusion Network for Deep Learning Segmentation

Segmentation of cardiac chambers and quantification of clinical functional parameters in dynamic echocardiography are the key to clinical diagnosis of heart disease. It is challenging and tedious for clinicians to identify end-diastolic frames (EDFs) and end-systolic frames (ESFs) in echocardiogram cine loops and to manually segment the left ventricle (LV). In this work, we presented a new multi-attention efficient feature fusion network (MAEF-Net) for automatic identification of EDFs and ESFs in echocardiogram videos and for automatic segmentation of the LV. Multi-attention mechanism was incorporated to guide the network to capture the characteristics of heart beat more efficiently, even in low-quality videos. At the same time, the deep supervision mechanism and spatial pyramid feature fusion were used to enhance the ability of feature extraction and gradient flow information was used to accurately segment the region of interest. MAEF-Net was trained and tested using the large public EchoNet-Dynamic data set. The Dice similarity coefficient of LV segmentation reached (93.10 ± 2.22)%. The key frame positioning error was (2.80 ± 0.22) frames. By using the information across multiple cardiac cycles, our model is more repeatable and robust with clinical interpretability. The proposed MAEF-Net may be used as a new method for automatic segmentation of the LV and identification of EDFs and ESFs.
3D confocal photoacoustic dermoscopy using a multifunctional sono-opto probe

In spite of acoustic or optical zoom lenses have been developed in photoacoustic dermoscopy (PAD) to promote human skin imaging capability, an acoustic and optical synchronous zoom lens-based confocal PAD (CPAD) system hasn't been acquired yet reviously, for all we know. Here, we exploited a 3D-CPAD equipped with a multifunction sono-opto probe to facilitate the acquisition of high resolution 3D imaging of human skins with uneven surface or multilayer structures in depth direction. The integration of an sono-opto probe of an electrowetting-based zoom lens can be used to adjust of the acoustic or optical confocal length. With the sono-opto probe, the 3D-CPAD achieved a confocal focus-shifting range with a high spatial resolution, substantially shortening the synchronous varifocal time of acoustic and optical zoom lenses. Performance tests and 3D imaging of human skin have been carried out to prove that the sono-opto probe has very good prospects for studying the physio-pathology of clinical skin diseases, and promoting the development of in vivo rapid-noninvasive PAD 3D imaging.
Providing Knee Movement Assistance using Android and IOT

Aging in living beings is a natural process and with aging one encounters challenges with walking or standing for long hours. Obsolete solutions like walking sticks do not provide satisfactory and effective solutions permanently neither can they be integrated with smart features to help in physical ailments. This paper aims to provide a knee brace made up of aluminium along with the device built using lead screw mechanism attached to the legs for the movement of the legs. This is made possible using 12V High Torque DC Geared Motor with 30 RPM and 21 Kg /Cm Rated torque. Lead Screw Mechanism uses the power generated by the motor to facilitate movement. Arduino Uno with the microchip ATmega328P controls the motor. The Bluetooth module (HC-05) helps in connecting the microcontroller to the Walk-Easy mobile app created. The Walk-Easy app allows the user to sit or stand using either buttons provided or through voice command. The Mobile App is integrated for user convenience, through which the movement is assisted as desired by the user. The main goal here is to realise a device to overcome these problems and provide effective solution to the knee related problem
Hartley Stochastic Computing For Convolutional Neural Networks

Energy consumption and the latency of convolutional neural networks (CNNs) are two important factors that limit their applications specifically for embedded devices. Fourier-based frequency domain (FD) convolution is a promising low-cost alter-native to conventional implementations in the spatial domain (SD) for CNNs. FD convolution performs its operation with point-wise multiplications. However, in CNNs, the overhead for the Fourier-based FD-convolution surpasses its computational saving for small filter sizes. In this work, we propose to implement convolutional layers in the FD using the Hartley transformation (HT) instead of the Fourier transformation. We show that the HT can reduce the convolution delay and energy consumption even for small filters. With the HT of parameters, we replace convolution with point-wise multiplications. HT lets us compress input feature maps, in all convolutional layer, before convolving them with filters. To optimize the hardware implementation of our method, we utilize stochastic computing (SC) to perform the point-wise multiplications in the FD. In this regard, we re-formalize the HT to better match with SC. We show that, compared to conventional Fourier-based convolution, Hartley SC-based convolution can achieve 1.33x speedup, and 1.23x energy saving on a Virtex 7 FPGA when we implement AlexNet over CIFAR-10.
Can Agents 'Report Their Types'? An Experiment that Changed the Course Allocation Mechanism at Wharton

This paper reports on an experimental test of a new market design that is attractive in theory but makes the common and potentially unrealistic assumption that “agents report their type”; that is, that market participants can perfectly report their preferences to the mechanism. Concerns about preference reporting led to a novel experimental design that brought real market participants’ real preferences into the lab, as opposed to endowing experimental subjects with artificial preferences as is typical in market design. The experiment found that market participants were able to report their preferences “accurately enough” to realize efficiency and fairness benefits of the mechanism even while preference reporting mistakes meaningfully harmed mechanism performance. The experimental results persuaded the Wharton School to adopt the new mechanism and helped guide its practical implementation.
Quarrelsome committees in US defense acquisition: the KC-X case

When the US Air Force set out to acquire a new aerial tanker (the KC-X), two highly suitable alternatives were offered. What could have been a short and simple source selection turned into a prolonged embarrassment. The original selection of 100 leased KC-767s was made in May 2003. But the KC-46 is expected to be operational in 2017 – more than a decade later. Our primary purpose here is to narrate and explain key events in the KC-X program. We search for useful paradigms, based in part on the US Government being better viewed as a quarrelsome committee than a monopsonist. In addition, we consider what this case might tell us about the US defense acquisition system.
Leveraging Model-Driven Technologies for JSON Artefacts: The Shipyard Case Study

With JSON's increasing adoption, the need for structural constraints and validation capabilities led to JSON Schema, a dedicated meta-language to specify languages which are in turn used to validate JSON documents. Currently, the standardisation process of JSON Schema and the implementation of adequate tool support (e.g., validators and editors) are work in progress. However, the periodic issuing of newer JSON Schema drafts makes tool development challenging. Nevertheless, many JSON Schemas as language definitions exist, but JSON documents are still mostly edited in basic text-based editors. To tackle this challenge, we investigate in this paper how Model-Driven Engineering (MDE) methods for language engineering can help in this area. Instead of re-inventing the wheel of building up particular technologies directly for JSON, we study how the existing MDE infrastructures may be utilized for JSON. In particular, we present a bridge between the JSONware and Modelware technical spaces to exchange languages and documents. Based on this bridge, our approach supports language engineers, domain experts, and tool providers in editing, validating, and generating tool support with enhanced capabilities for JSON schemas and their documents. We evaluate our approach with Shipyard, a JSON Schema-based language for the workflow specification for Keptn, an open-source tool for DevOps automation of cloud-native applications. The results of the case study show that proper editors and language evolution support from MDE can be reused and, at the same time, the surface syntax of JSON is maintained.
Research on Auditory Tension Classification Algorithm Based on Interval Statistics

This paper proposes a classification model based on interval statistics and a classification algorithm of auditory tension for complex networks. Firstly, a model of interval statistical method for feature extraction of music and speech is introduced. Then, I understand the relationship and calculation method between interval consonance and auditory tension, and propose a classification model of auditory tension based on interval statistical method. Finally, this classification model is used to classify and simulate unused music and speech.
An automatically thyroid nodules feature extraction and description network for ultrasound images

Thyroid nodules are mainly detected and diagnosed using ultrasound (US) images. However, interpreting and summarizing the content of thyroid US images is a time-consuming task event for experienced radiologist. Thus, an intelligent method that can complete the mapping from visual information to concise text description is very necessary. A deep learning network structure for thyroid nodules features description in US images is proposed. This network consists of 2 parts: 1. the visual features extraction part; 2. the language description generation part. The proposed framework can automatically extract the features of the thyroid nodules and generate feature description reports based on the input ultrasound image and its segmentation results. A description accuracy of 95% is achieved using clinical US images.
A Model of Human-Robot Trust

This work explores the theoretical foundations of trust which provide the framework for the development of our model of human-robot team trust. The pragmatic purpose for this model is to provide a greater understanding of the factors that facilitate the development of human operator trust in robotic teammates. We predicate the model’s structure with our findings from a quantitative meta-analysis that we have completed. Our approach categorizes the dimensions influencing trust in human-robot interaction. To date, we have explored human, robot and environmental-based factors. Our road map for model development and refinement is here outlined.
The Best, The Requested, and The Default Non-Binary LDPC Decoding Algorithm

This paper presents a different vision of the Non-Binary LDPC decoding algorithm. So far, state-of-the-art decoders are mainly focused on the reduction of the check node processing complexity, with a potential side effect on the size of the messages that are exchanged in the iterative decoder. However, it is possible to take a different approach and consider the reduction of the message size as the main objective. The paper presents "the Best, the Requested and the Default" algorithm that shrinks dramatically the communication load between the variable nodes and check nodes.
Cortical Bone Ultrasonic Imaging Based on Accurate Delay Times

This work proposed a dynamic aperture delay-and-sum method based on velocity reconstruction (DA-DAS-VR) to implement accurate cortical bone ultrasonic imaging. Two identical linear array probes were placed parallelly on the upper and lower sides of the imaging region. The ultrasonic signals were captured with full-matrix mode. After extraction of first arrival time from the ultrasonic data, the travel-time inversion was utilized to reconstruct the velocity distribution in advance. Then, combined with the estimated velocity distribution, Fast Marching method was employed to calculate the accurate delay times of all focused points. Finally, the dynamic aperture delay-and-sum imaging method (DA-DAS) was applied to reconstruct the cortical bone. The experimental results show that the mean relative errors of the estimated sound velocity in the region-of-interest (ROI) are all below 10%.
A Precise Model of TSV Parasitic Capacitance Considering Temperature for 3D IC

As the technology of three dimension integrated circuit (3D IC) develop quickly, through silicon via (TSV) plays a basic and important role.In consideration of real working environment, factors as temperature and working voltage are studied by TCAD simulator. And the contribution of physical sizes and the concentration of doping in the course are analyzed. A new analysis model of capacitance for TSV is given, which is with an error less than 4% with the measurement data. In the range of 25 to 125 degree centigrade with different physical sizes of TSV, this model of TSV's parasitic capacitance shows a better accuracy and takes less time than the former one. The neglect of temperature in course of design will lead to a big problem in real chip, an accurate mode considering temperature is important both in design and SI analysis.
Simulation and Fabrication of a Low-Cost RFID Reader

RFID (Radio-Frequency Identification) systems have their importance renewed due to the surge of the Internet-of-Things scenario. This article describes the design and fabrication of a low-cost RFID Reader. This research comprises the fabrication of a printed antenna of the reader, as well as generating the waveform used in the transmission as a proof of concept. The antenna is designed on ANSYS HFSS and then printed on a FR-4 substrate using microstrip lines. The waveform is designed as a set of sinusoids and then generated on Labview. The setup is validated as a proof of concept using an indoor scenario, with passive RFID printed tags placed 50 cm from the reader. The received waveforms present an adequate signal level.