Miracle-dz/UniFAR-FTUs huggingface dataset:
An advanced 32 kbit/s ADPCM coding to transmit speech and high-speed voiceband data

This paper describes a performance evaluation of an advanced 32 kbit/s ADPCM hardware codec in terms of speech and high-speed voiceband data, V.27 and V.29 at 4.8, 7.2 and 9.6 kbit/s. The results indicated that the advanced 32 kbit/s ADPCM provided an equivalent subjective speech quality to that of the G.721 ADPCM recommended by the CCITT, and was able to maintain the transparency of these high-speed voiceband data at 7.2 kbit/s over at least four and at 9.6 kbit/s over at least two asynchronous tandem links, respectively. Furthermore, the advanced ADPCM can quickly recover a complete synchronous operation in the tandem connections, as burst errors or short-hits damage the digital links.
Scratchpad Memory Assignment in Embedded Multimedia Application

To improve embedded multimedia application performance and reduce power consumption,an efficient method of exploiting scratchpad memory is proposed.Big data array are divided in small tiles and copied to on-chip memory by stages.Data in scratchpad memory should be reused as much as possible to reduce data transfer between off-chip memory and scratchpad memory.Memory access delay can be avoided by proper assignment of memory operand in assemble instructions.Some operand memory constraint conditions can be listed out to minimize pipeline stall.A method of array assignment is proposed in these conditions.
Immutable Mobiles Revisited: A Framework for Evaluating the Function of Ephemeral Texts in Design Arguments

This article makes the argument that material evidence for many of the most valuable contributions that contemporary technical communicators make to their organizations is often found not in the traditional documentation that they produce but, rather, in the more fragmentary and provisional documents they create as daily participants in their work teams. To make this argument, the article presents data from a case study of a technical communicator at a software firm, showing how a reminder note he carried to a meeting helped him achieve an important design change. The article unpacks the concept of immutable mobiles from actor network theory to derive a framework that helps us interpret the multiple functions of this note in helping the technical communicator warrant and win a design argument with software developers.
Hello, Red Fox

Mama Frog gets a big surprise when the guests arrive for Little Frog's birthday party: Red Fox looks green to her! Orange Cat looks blue! What has gone wrong? With the active help of the reader, Little Frog shows Mama Frog how to see the animals in their more familiar colors. Is it magic? No, it's a remarkable function of the human eye. As Little Frog demonstrates, anyone can do it. Small readers will enjoy taking part in the fun of changing the colors of the animals. And they will laugh at the effect they themselves can create at the end of the story when Mama Frog gives Little Frog an embarrassing birthday kiss! Eric Carle believes that learning should be a joyful experience. In this imaginative book he invites young readers to discover complementary colors while enjoying the amusing story of Little Frog and his colorful friends.
Article acquisition in English, German, Norwegian and Swedish

Article omission is a well-documented phenomenon in early child speech. Interestingly, children differ in terms of how extensively they omit articles depending on their age and what language(s) they are exposed to. Different accounts have been proposed to account for this cross-linguistic variation. One of the most widely discussed models is the Nominal Mapping Parameter (NMP), originally proposed in Chierchia (1998), which relates variation in child language to the syntactic and semantic properties of noun phrases across languages (e.g. Chierchia, Guasti and Gualmini 1999, Guasti and Gavarro 2003, Guasti et al. 2004). Other influential accounts of determiner omission have been formulated in prosody-oriented research (e.g. Gerken 1991, 1994, Lleo 1998, 2001, Lleo and Demuth 1999, Roark and Demuth 2000, Demuth et al., in press). So far, no common agreement has been reached.This paper presents a study on article acquisition in English, German, Norwegian and Swedish, where article use is subject to similar syntactic and semantic conditions. Hence, the NMP predicts similar acquisition patterns. In terms of their metrical structure, noun phrases in these languages differ considerably. Accordingly, different acquisition patterns are expected.
PENGARUH DOSIS MIKROORGANISME PROBIOTIK PADA MEDIA PEMELIHARAAN TERHADAP KELANGSUNGAN HIDUP DAN PERTUMBUHAN BENIH MAS KOKI (Carassius auratus) DENGAN PADAT PENEBARAN BERBEDA

Penelitian ini bertujuan untuk mengetahui pengaruh dosis mikroorganisme probiotik dan padat tebar yang tepat pada media pemeliharaan sehingga dapat meningkatkan kelangsungan hidup dan pertumbuhan benih mas koki. Metode yang digunakan dalam penelitian ini adalah metode eksperimental Rancangan Acak Lengkap (RAL) pola faktorial terdiri dari dua faktor. Parameter yang diamati yaitu kelangsungan hidup, pertumbuhan, dan kualitas air. Analisis data tingkat kelangsungan hidup dan pertumbuhan dilakukan dengan menggunakan uji F dengan taraf kepercayaan 95%. Hasil penelitian menunjukkan bahwa penambahan probiotik EM4 pada media pemeliharaan dengan dosis 0,5 ml/L dengan kepadatan 2 ekor/L menghasilkan kelangsungan hidup sebesar 80,56 % sedangkan pertumbuhan bobot dan panjang tertinggi dengan dosis 1 ml/L dengan kepadatan 1 ekor/L sebesar 4,58 gr dan 1,62 cm. Kata kunci : kelangsungan hidup, mas koki, padat penebaran, pertumbuhan, probiotik
Afspoeling van amitrol, atrazion en glyfosaat vanaf een betonklinkerverharding; veldproeven en modelsimulaties

In vier veldproeven op 100 mr betonklinkerbestrating is de afspoeling van amitrol, atrazin en glyfosaat naar het regenwaterriool gemeten. De totaal afgespoelde hoeveelheid is 6 tot 44␟an de dosering. Het grootste deel spoelde af met de eerste millimeters neerslag. Infiltratie naar de ondergrond en de oplosbaarheid van de herbiciden bleken de belangrijkste afspoelingsbepalende processen. Adsorptie van de gebruikte middelen aan het steenoppervlak had nauwelijks invloed op de afspoeling. Door toevoegen van de processen infiltratie en opname van herbicide in de steen aan het model kon de afspoeling beter worden gesimuleerd.
A Traversing and Merging Algorithm of Blobs in Moving Object Detection

In the frame of surveillance video, the colour of both moving objects and background distribute randomly. Consequently, the foreground image obtained by background subtraction or temporal differencing always contains many discrete blobs, which are isolated but actually belong to the same object. These blobs influence the effi ciency of later process such as recognition, classification, and activity analysis. In order to organize the foreground blobs, a trav ersing and merging algorithm of blobs is proposed in this paper. The experimental results show that the proposed algorithm can merge blob effectively.
Analytical Validation of the SDL Metrics Set

Design metrics that quantify the design phase play an important role in reducing system development cost because the problems in early phases of software development seriously affected the quality of the late products. Real-time systems such as telecommunication systems are so large that design quantification is more important in real-time system design. Although many metrics have been proposed, few of them are correctly validated. This paper revises the SDL metrics set proposed in earlier study [9] and perform an analytical validation o the metrics set. Axiomatic approach and dimensional analysis are used for metrics validation and the old metrics are revised ot satisfy the validation criteria.
Genetic algorithms and their applications

This article introduces the genetic algorithm (GA) as an emerging optimization algorithm for signal processing. After a discussion of traditional optimization techniques, it reviews the fundamental operations of a simple GA and discusses procedures to improve its functionality. The properties of the GA that relate to signal processing are summarized, and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.
Analysis of coordinated grasping kinematics and optimization of grasping force of a parallel hybrid hand

It is important to obtain optimal grasping performance of a parallel hybrid hand in order to reduce the grasping impact force and power loss, to avoid the damage of object or human body during grasping operation or rescue missions. In this article, the coordinated grasping kinematics of the multi-fingers and the optimization of grasping force for a parallel hybrid hand are studied and analyzed systematically. First, the coordinated grasping condition is analyzed, and the formulae are derived for solving the displacement, the velocity, and the acceleration of the contact points between the object and the multi-fingertips of the parallel hybrid hand. Second, the formulae are derived for solving the contact forces at the contact points. Third, the frictional constraints between the multi-fingers and the object are analyzed during stable grasping, and the formulae are derived for solving the optimum contact forces. Finally, an analytic numerical example is given, the analytic solutions of the coordinated grasping kinematics and optimum contact forces are solved and verified by simulation solutions.
A meta-analysis of the relationship between body mass index and risk of rheumatoid arthritis

The present meta-analysis aimed to evaluate the relationship between body mass index (BMI) and rheumatoid arthritis (RA). A systematic search of the Cochrane, Pubmed, and Embase databases was conducted to identify relevant studies published before September 2017 using terms related to BMI and RA. Fixed or random-effect models were used to estimate the pooled relative risk (RR) with 95 % confidence interval (CI). Subgroup analyses by sex were performed to investigate the association between BMI and RA in male and female subgroups. A total of 14 eligible studies containing 353,948 patients were included in the analysis. The pooled results suggested that the odds ratios (ORs) of RA were 1.08 (95 % CI: 1.00~1.15) for overweight, and 1.32 (95 % CI: 1.11~1.54) for obesity, respectively, suggesting that a higher BMI increases the risk of RA compared to normal weight. Further subgroup analyses showed a positive association between BMI and RA risk but only in females, with a RR of 1.11 (95 % CI: 1.00~1.22) for overweight and 1.40 (95 % CI: 1.24~1.57) for obesity. In conclusion, an increased BMI may lead to a higher risk for RA development. Furthermore, the positive association between BMI and RA risk may be stronger in female populations than in males. However, additional analyses are needed.
Cell type–dependent bimodal p53 activation engenders a dynamic mechanism of chemoresistance

A new chemoresistance mechanism via bimodal p53 activation is attributed to differential output of a four-component control module. Studies of drug resistance mostly characterize genetic mutation, and we know much less about phenotypic mechanisms of drug resistance, especially at a quantitative level. p53 is an important mediator of cellular response to chemotherapy, but even p53 wild-type cells vary in drug sensitivity for unclear reasons. Here, we elucidated a new resistance mechanism to a DNA-damaging chemotherapeutic through bimodal modulation of p53 activation dynamics. By combining single-cell imaging with computational modeling, we characterized a four-component regulatory module, which generates bimodal p53 dynamics through coupled feed-forward and feedback, and found that the inhibitory strength between ATM and Mdm2 determined the differential modular output between drug-sensitive and drug-resistant cancer cell lines. We further showed that the combinatorial inhibition of Mdm2 and Wip1 was an effective strategy to alter p53 dynamics in resistant cancer cells and sensitize their apoptotic response. Our results point to p53 pulsing as a potentially druggable mechanism that mediates chemoresistance.
An Advance on Gender Classification by Information Preserving Features

One of the most challenging issues in Speaker's Gender Classification (SGC) is feature extraction. Since, it degrades the classification accuracy due to information loss during features extraction using speech signals. In previous researches, Perceptual Linear Prediction (PLP) coefficients were extracted by using Blackman windowing method along with the other features of speech signal to improve the classification accuracy. However, still some information was lost at those window edges which degrade the recognition accuracy and also more efficient features were required to improve the classification performance. Hence in this paper, SGC is improved by extracting the PLP coefficients based on novel windowing technique. In this technique, initially type-1 features such as spectral and prosodic features of speech signal are extracted. In addition, Information Preserving Perceptual Linear Prediction (IPPLP) coefficients are also extracted using Slepian windowing method. Moreover, the frequency-dependent transmission characteristics of the outer ear are compensated based on the analysis of time-varying Equal Loudness Contour (ELC) curves and Peak-to-Loudness Ratio (PLR). After that, the extracted IPPLP features are fused with type-1 features and classified by using different combinations of classifiers like Gaussian Mixture Model (GMM), Support Vector Machine (SVM) and GMM supervectors-based SVM at score level fusion scheme. According to the final classification result, the type of speaker's gender is recognized. Finally, the experimental results show the significant improvements on classification accuracy by using proposed classification technique. With the proposed speaker's gender classification technique, the classification accuracy values are obtained 38.55%, 62.65% and 69.88% in GMM, SVM and GMM-SVM classification, respectively.
Statistical Shape Model Generation Using K-means Clustering

Statistical shape models (SSMs) is a robust and efficient method in medical image segmentation. In this paper, a novel landmark corresponding method based on k-means clustering and demons registration is proposed to train a 3-D statistical shape model with higher quality. The k-means clustering method is performed on the original geometric surface to obtain a simplified surface as standard set of landmarks to find correspondent landmarks on each mapped spherical surface obtained from demon registration in the training set. Twenty cases of left lung and right lung regions in thoracic MDCT images are used in the experiment to build two SSMs. Performance evaluation results show that SSMs generated by the proposed method achieve better generalization ability and specificity while maintaining the same compactness and accuracy of segmentation as those reported by state-of-the-art methods.
CCE: A Combined SRAM and Non Volatile Cache for Endurance of Next Generation Multilevel Non Volatile Memories in Embedded Systems

In this paper we present Combined Cache for Endurance (CCE), a scheme to enable the use of next generation high density multilevel non volatile memories in embedded systems. These memories are attractive as they can reduce the static power consumption dramatically and a single memory can be potentially used avoiding having both flash and SRAM or DRAM in a system. However, a common drawback of the new multilevel non volatile memories is that they support a limited number of write operations and thus its endurance needs to be improved to make them a viable alternative for the main memory of embedded systems. The proposed CCE relies on the fact that most writes are concentrated on a few addresses. Therefore, a small SRAM cache can be used to store positions that are frequently written. However, this would not preserve the non volatile nature of the memory. To do so, in the proposed CCE, the cache cell has an SRAM part and a non volatile part. At power up the contents of the non volatile part are copied to the SRAM and the other way around at power down. As many embedded systems execute predictable workloads, this cache is statically set to cover the most frequently written addresses. The evaluation shows that CCE can increase the endurance of the memory by several orders of magnitude. At the same time the overheads required to implement the cache are small relative to the main memory. Therefore, CCE can be an interesting option to improve the endurance of next generation high density multilevel non volatile memories.
Resource Allocation for System Throughput Maximization Based on Mobile Edge Computing

Mobile edge computing (MEC) provides cloud computing capabilities at the edge of the mobile network, emphasizing proximity to mobile users to reduce network operation and service delays, improving user experience. In this paper, we study the problem of low utilization spectrum resources for MEC in 5G heterogeneous networks. We first explore the problem of computing offloading in multi-channel environment. Then an optimization problem is proposed to maximum the overall throughput of the offloading system, where the power control and interference are taken into consideration. We transform the original optimization problem into a convex optimization problem, and use the Lagrangian dual algorithm to establish the KKT condition. By continuous iterative operation, the user's transmit power is optimally achieved. Simulation results show that our proposed scheme not only guarantees the communication quality, but also improves the system throughput and spectrum utilization.
What Your DRAM Power Models Are Not Telling You: Lessons from a Detailed Experimental Study

Main memory (DRAM) consumes as much as half of the total system power in a computer today, due to the increasing demand for memory capacity and bandwidth. There is a growing need to understand and analyze DRAM power consumption, which can be used to research new DRAM architectures and systems that consume less power. A major obstacle against such research is the lack of detailed and accurate information on the power consumption behavior of modern DRAM devices. Researchers have long relied on DRAM power models that are predominantly based off of a set of standardized current measurements provided by DRAM vendors, called IDD values. Unfortunately, we find that state-of-the-art DRAM power models are often highly inaccurate when compared with the real power consumed by DRAM. This is because existing DRAM power models (1) are based off of the worst-case power consumption of devices, as vendor specifications list the current consumed by the most power-hungry device sold; (2) do not capture variations in DRAM power consumption due to different data value patterns; and (3) do not account for any variation across different devices or within a device.
Free BDD based CAD of Compact Memristor Crossbars for in-Memory Computing

The demise of Moore’s law, breakdown of Dennard Scaling, dark silicon phenomenon, process variation, leakage currents and quantum tunneling are some of the hurdles faced in the further advancement of computing systems today. As a result, there is a renewed interest in alternate computing paradigms using emerging nanoelectronic devices. This work uses free binary decision diagrams (FBDDs) for computer-aided design (CAD) of compact memristive crossbars for sneak-path based in-memory computing. The absence of a fixed variable ordering makes FBDDs more compact than their ordered counterpart called reduced ordered binary decision diagrams (ROBDDs). Our design has used the size of the circuit-representation of Boolean functions for selecting different variable orderings along different paths which results in compact FBDDs. We have demonstrated our approach by designing compact crossbars for a four-bit multiplier and other RevLib benchmarks. Our synthesis process yields a 50.1% reduction in area over the previous FBDD-based synthesis for the fourth-output-bit of the multiplier. Overall, our approach has reduced the multiplier area by 20.1%.
Reimagining participatory design

We recently edited a special issue of the ACM ToCHI journal on Re-Imagining Participatory Design (Bannon et al. 2018a) and as a result of this process, and the earlier work leading up to it, we have had many interesting discussions concerning Participatory Design (PD) and where it stands today. We refer the reader to the ToCHI special issue for details of the various contributions, but present here some further discussion of the themes that emerged as we ourselves discussed this topic of reimagining PD. The history of the field, and the ongoing debates about the general concept of “participation,” have been discussed elsewhere (Simonsen and Robertson 2012, Vines et al. 2013, etc.). We have also been inspired by material in the CoDesign journal special issue on “Unfolding Participation over Time in the Design of IT” (Saad-Sulonen et al. 2018) and the 2017 special issue of the CSCW Journal on “Infrastructuring and Collaborative Design” (Pipek et al. 2017). These projects and others collectively suggest a willingness in the PD community to step back, take stock, and reflect on PD as an approach to design and research. Why is there a need for this now? What is it about PD today that has become somehow problematic, in that so many take this reflexive turn? Does PD no longer work? has it lost its coherence? has it been co-opted and corrupted? In this article we seek to account for the questioning within PD of its purpose at the present moment and to make a constructive contribution to the debate by offering some thoughts on ways to move forward.
Fast Estimations of Failure Probability Over Long Time Spans

Shrinking of device dimensions has undoubtedly enabled the very large scale integration of transistors on electronic chips. However, it has also brought to surface time-zero and time-dependent variation phenomena that degrade system’s performance and threaten functional operation. Hence, the need to capture and describe these mechanisms, as well as effectively model their impact is crucial. To this extent, we follow existing models and propose a complete framework that evaluates failure probability of electronic components. To assess our framework, a case-study of packet-switched Network on Chip (NoC) routers is presented, studying the failure probability of its SRAM buffers.
Optimized Variable Size Windowing Based Speaker Verification

In recent years the variances of speech features of speaker verification system were measured by computing covariance matrix parameterized through its eigenvalues and vectors by keeping fixed sliding window size. The computed eigenvectors were weighted with its corresponding magnitude and normalized. Then, the features were extracted and fused using different fusion techniques for recognizing the speaker. However, this approach was not suitable for all types of datasets and some significant feature information may be lost during extraction based on fixed window size. Hence in this article, the variable size sliding window is applied for Speaker Verification system. Initially, the speech signal is considered as input and the FMPM features are extracted using FDLP, MHEC and PNCC including MFCC based on the variable size of a sliding window. Here, the sliding window size is optimized by Modified Grey Wolf Optimization (MGWO) algorithm which is also used for selecting the classifier parameters and most optimal features adaptively. The most optimal features are selected from the extracted FMPM and classified by using GMM classification. Thus, the proposed approach allows continuous adaptation of SV using variable window size and classifier parameters. Finally, the considerable improvements in Speaker Verification are observed through experimental results.