Miracle-dz/UniFAR-FTUs huggingface dataset:
Situating societal challenges in an industrial design classroom

Designing for societal challenges requires not only traditional design competencies but also knowledge from other disciplines such as social science and engineering. In particular, designers should have the ability to take entrepreneurial action, demonstrate design leadership and create responsible designs. Design education has adopted the design studio approach to creating opportunities for design students to learn and practice design skills. However, scholars often criticize it due to its lack of scientifically rigorous. This paper discusses a teaching case in an industrial design class where design students learned to design for a societal challenge through a combination of different educational activities such as following lecture, participating workshops, conducting field research with end users and stakeholders, and giving presentations and receiving feedback from industry experts and academic staff. By combining a mixed-perspective, they got a better understanding of different stakeholders involved, created propositions with all parties in mind and were able to communicate their ideas clearly. In this way, stakeholders were informed, inspired and empowered to collaborate and create the intended innovations. By balancing the rationality and creativity in the design class through offering the theoretical foundations as well as the societal embodiment, this course aimed at equipping future responsible industrial designers with the desired competencies related to entrepreneurial action and design leadership.
An efficient SLM technique based on chaotic biogeography-based optimization algorithm for PAPR reduction in GFDM waveform

ABSTRACT High data rates, extremely low power consumption, and minimal end-to-end latency are considered to be mandatory requirements for 5G wireless networks. Rapid improvements in design and performance of 5G physical layer waveforms have become necessary. The drawback of Orthogonal Frequency Division Multiplexing (OFDM) is high PAPR, that causes signal distortion, which reduces system efficiency. Generalized frequency division multiplexing (GFDM) is a promising non-orthogonal multicarrier transmission scheme, which has recently received a great deal of attention towards future fifth generation (5G) wireless networks. It overcomes the limitations of orthogonal frequency division multiplexing (OFDM), while preserving most of the advantages of it. Selective Level mapping (SLM) is one of the PAPR reduction techniques, that uses the phase shift technology. In this paper, SLM based on Chaotic Biogeography Based Optimization (CBBO) algorithm is proposed to offer an efficient solution to the problem of high PAPR, existing in the GFDM waveforms. Experimental results prove that, the proposed CBBO–SLM technique provides significant improvement in terms of PAPR reduction, as compared to the conventional SLM methods, such as conventional GFDM and OFDM-SLM. The proposed novel scheme is most suitable for QAM and QPSK applications, as it provides good PAPR reduction performance, at lower computational complexity.
Kansei Analysis of Car Front Grill to Design for Thai People

: This study aims to produce the car front grills that are more attractive for local consumers. In our study, the visual impression observed in the front grills of Sport Utility Vehicles (SUVs) have been investigated by using many adjectives and compared the effect of design types on the visual impression between Japanese and Thai consumers. Twenty-one pairs of antonym adjectives such as ‘glossy’ and ‘matte’ were selected, thirteen photo images were prepared, and the Semantic Differential (SD) method was used to quantify the consumers’ visual impression for our experiment. SD data from two nations was analyzed by the Principal Component Analysis (PCA), and it was clear that the visual impression structure for a car front grill was different between Japanese and Thais, in particular, the most important principal components by the PCA were expressed by the term LUXURY and CONTRAST for Japanese, whereas STYLE and LIGHTNESS for Thai people.
WHY CONFLICTS OCCUR IN ROADS AND TUNNELS PROJECTS IN NORWAY

Conflicts within the Norwegian construction industry have reached unacceptable levels. The grievance of these disputes, whether it is the number of conflicts or the expense involved in these conflicts, is under discussion. This article examines the reasons for these conflicts in a comprehensive and inclusive manner. Twenty-five respondents with expertise and understanding of most conflicts in the Norwegian construction industry were interviewed. Results from a questionnaire sent to 1799 contractors have also been included in this study. Sixteen reasons for disputes were identified out of which four comprised the root causes. Tender specification and contract understanding came in first followed by “final settlement-payment related”, corroborating previous findings. The third and fourth root causes of conflicts were “low priced contracts” and “changes in projects” respectively. Our findings point to design deficiencies and defective contract plans as significant causes of conflicts, confirming the view of construction experts. The third root cause of conflicts might explicate some aspects of the first and second major causes of disputes. It is also important to mention that though this is the general view, one can also see how every group involved in this study interpret major causes of conflicts. Our findings also point to “communication between clients and contractor”, “carried out quantities” and “client restriction to time extension” as among the chief causes of conflicts, confirming the view of construction experts. Client understanding of contractors’ anxiety and quest for sound contracting process are aspects that Norwegian clients are currently engaging in, for the sake of conflict reduction and prevention in future construction projects.
Participation in Targeted Poverty Alleviation and Enterprise Innovation Investment: Analysis of the Mediating Effect Test Model Based on Financing Constraints

In China, enterprises participating in targeted poverty alleviation can be provided with a strategic resource to enhance their ultimate value creation ability and directly win reputation and obtain sustainable competitive advantages, thus enhancing their innovation ability. In this study, the influence and mechanism of the participation in targeted poverty alleviation on enterprise innovation investment are empirically examined based on financing constraints with the data of nonfinancial listed companies in Shanghai and Shenzhen from 2012 to 2019 as the object. The research suggests that enterprises taking the initiative to participate in targeted poverty alleviation can first have increased innovation investment and especially enhanced exploratory innovation ability. Second, enterprises’ participation in targeted poverty alleviation can reduce financing constraints of enterprises’ innovation, improve their resource allocation efficiency, and stimulate their innovation vitality primarily through the influence of resource, reputation, and information. This study enriches the theoretical research on the economic consequences of targeted poverty alleviation and provides a reference for guiding enterprises in practice to fulfill social responsibilities to promote enterprises’ innovation vigor and boost their high-quality development.
Charging-Related State Prediction for Electric Vehicles Using the Deep Learning Model

Electric vehicles (EVs) are becoming the potential contender for the conventional gasoline vehicles in view of the environment-friendly and energy-efficient characteristics. The prediction of EV charging-related states (defined in this study as home charge, outside charge, home stop, outside stop, low-battery travel, and high-battery travel) could help to identify the future charging demand (power consumption) of EV individuals. Specifically, it could guide the operation and management of charging facilities and also provide tailored charger availability information based on users’ real-time locations. This study aims to predict charging-related states of individual EVs using a deep learning approach. We first propose a tangible approach to convert EV trajectory data into state sequences and then develop a bidirectional gated recurrent unit model with attention mechanism (Bi-GRU-Attention) to forecast EV states. A sensitivity analysis is conducted to tune and/or calibrate parameters in the model based on plug-in hybrid EV trajectories dataset collected in Shanghai, China. Experiment results show that (i) the proposed method could achieve an average accuracy of 77.15% with a 1-hour prediction length and it outperforms the baseline models for all tested prediction lengths; (ii) it is also revealed that the prediction accuracy varies dramatically with different states and time periods. Among all states, the proposed model has a higher prediction accuracy on “home stop” (89.0%). As for time periods, the EV states around 08:00 am and 04:00 pm are hard to predict, and a comparatively low prediction accuracy (close to 60%) is obtained; and (iii) the stability and robustness analysis implies that the proposed model is stable and insensitive to SOC noise or season.
Dermatoglyphic and acoustic analysis of singing voices: a multiple case preliminary report

Purpose: to identify genetically enhanced physical skills (speed, strength, endurance and motor coordination), provided by the dermatoglyphic method and to analyze the preliminary correlation between dermatoglyphic and acoustic data of lyrical and pop singers. Methods: the study was approved by the Ethics and Research Committee. Four male singers were evaluated (two lyrical and two pop singers), 31-53 years old. Data collection and analysis procedures comprised (1) Survey -Self-Perception of Vocal Characteristics in Singers (vocal habits, voice performance and phenotypic characteristics); (2) Dermatoglyphic Profile (fingerprint image digitalization: predominance of digital drawings (Arch, Loop and Whorl); scores of deltas (D10); the Total Ridge Count (TRC); digital formula and dermatoglyphic profile (aerobic, anaerobic and mix)); (3) Acoustic Analysis (the Expression Evaluator script application to the audio recordings: f0, intensity, spectral slope and long-term average spectrum – LTAS values); and (4) Integrated (Statistical) Analysis; cluster analysis. Results: correlations were found between dermatoglyphic variables (Arch, Loop, Whorl, D10, TRC) and acoustic parameters (f0 (median); intensity (asymmetry); spectral slope (mean); and LTAS (SD)). The dermatoglyphic profile did not segregate singing styles. Conclusion: the dermatoglyphic profiles showed a preliminary correlation with the acoustic vocal measures, especially f0 and LTAS measures.
Standardization, Distance, Host Galaxy Extinction of Type Ia Supernova and Hubble Diagram from the Flux Ratio Method

In this paper we generalize the flux ratio method Bailey et al. (2009) to the case of two luminosity indicators and search the optimal luminosity-flux ratio relations on a set of spectra whose phases are around not only the date of bright light but also other time. With these relations, a new method is proposed to constrain the host galaxy extinction of SN Ia and its distance. It is first applied to the low redshift supernovas and then to the high redshift ones. The results of the low redshift supernovas indicate that the flux ratio method can indeed give well constraint on the host galaxy extinction parameter E(B-V), but weaker constraints on R_{V}. The high redshift supernova spectra are processed by the same method as the low redshift ones besides some differences due to their high redshift. Among 16 high redshift supernovas, 15 are fitted very well except 03D1gt. Based on these distances, Hubble diagram is drew and the contents of the Universe are analyzed. It supports an acceleration behavior in the late Universe. Therefore, the flux ratio method can give constraints on the host galaxy extinction and supernova distance independently. We believe, through further studies, it may provide a precise tool to probe the acceleration of the Universe than before.
An SiC-Driven Modular Step-Up Converter With Soft-Switched Module Having 1:1 Turns Ratio Multiphase Transformer for Wind Systems

In this paper, a new step-up dc–dc converter module that consists of three resonant submodules interconnecting with 1:1 turns ratio three-phase transformer and coupled current-fed voltage doubler modules is presented for medium voltage dc converter design in wind energy application. By utilizing step-up resonant circuits with three-phase transformer and combining it with a “multistring” inverter, the proposed circuit structure completely utilizes all the switching circuits to transfer power to the output. In addition, the proposed topology is able to achieve high voltage gain without using large turns ratio high frequency step-up transformers. Zero voltage switching turn-on and near zero current switching (ZCS) turn-off are maintained for all the switches. A modular 1.5 MW, 1 kV (dc-link), 20 kV (output) converter system is presented to validate the performance of the proposed circuit. Experimental results on a laboratory-scale 2.8 kW, 0.3 kV (dc-link), 6 kV (output), prototype are provided to highlight the merits of this work. Silicon Carbide (SiC) MOSFETs and SiC Schottky diodes are utilized in both designs. Results confirm that a peak efficiency of 97.6% is achieved in the prototype.
Low Loss 16-Channel Photodetector Array Receiving Module With Fine Tuning Ability

A 16-channel photodetector array receiving module with good performance as low loss, fine tuning and high reliability is manufactured in our laboratory. The whole module was consisted with a silica arrayed waveguide grating chip (AWG), a thermo-optical type variable optical attenuator (VOA), a photodetectors (PDs) array with direct-current (DC) bias circuit, all components were integrated via 3D package method. In the article, the structure parameters of Y branch and edge couplers were optimized for lower loss. In order to realize excellent tuning ability, Titanium was selected as heating material for precisely tuning and its electric attenuation range could reach at a level more than 20 dB. Periodically segmented waveguide coupler designed in passive chips could minimize coupling loss less than 0.4 dB/coupling. The high-performance receiving module could effectively improve detection quality and significantly enlarge capacity in communication system.
New Driving Structure to Increase Pixel Charging Ratio for UHD TFT-LCDs With High Frame Rate

This paper proposes a new driving structure of the thin-film transistor liquid crystal display (TFT-LCD) that can yield a high image quality with a reduction in the number of source driver ICs for use in narrow-bezel notebook displays with ultra-high definition (UHD) and a high frame rate. The proposed driving structure improves the pixel charging ratio by reducing the RC loadings of TFTs of de-multiplexers on data lines and extending the available row-line time for pixel charging. A new gate driver circuit that generates two output waveforms in a single stage is presented to reduce the cost and occupied layout area of gate driver ICs, enabling the realization of high-resolution displays with a narrow bezel. To verify the feasibility of the proposed driving structure, a 12.3-inch panel with UHD (3840 × 2160) and a frame rate of 120 Hz is fabricated. Experimental results demonstrate that the proposed driving structure yields a measured pixel charging ratio of more than 97.09% for a heavy loading pattern with a gray level of 255. Following an accelerated lifetime test, the measured waveforms of the proposed gate driver circuit are stable without any malfunction, demonstrating its high reliability. Therefore, the proposed driving structure and the gate driver circuit are highly suitable for use in UHD TFT-LCD notebook applications.
Recent Research Progress of Ionic Liquid Dissolving Silks for Biomedicine and Tissue Engineering Applications

Ionic liquids (ILs) show a bright application prospect in the field of biomedicine and energy materials due to their unique recyclable, modifiability, structure of cation and anion adjustability, as well as excellent physical and chemical properties. Dissolving silk fibroin (SF), from different species silkworm cocoons, with ILs is considered an effective new way to obtain biomaterials with highly enhanced/tailored properties, which can significantly overcome the shortcomings of traditional preparation methods, such as the cumbersome, time-consuming and the organic toxicity caused by manufacture. In this paper, the basic structure and properties of SF and the preparation methods of traditional regenerated SF solution are first introduced. Then, the dissolving mechanism and main influencing factors of ILs for SF are expounded, and the fabrication methods, material structure and properties of SF blending with natural biological protein, inorganic matter, synthetic polymer, carbon nanotube and graphene oxide in the ILs solution system are introduced. Additionally, our work summarizes the biomedicine and tissue engineering applications of silk-based materials dissolved through various ILs. Finally, according to the deficiency of ILs for dissolving SF at a high melting point and expensive cost, their further study and future development trend are prospected.
A Multi-Analysis of Children and Adolescents’ Video Gaming Addiction with the AHP and TOPSIS Methods

The video game market has become increasingly popular among children and adolescents in recent decades. In this research, we investigated the Video Game Addiction Scale (VGAS) for Chinese children and adolescents. We aimed to examine children and adolescents’ prioritization on the VGAS criteria and comparative analysis of the trend of video game addiction among them. A cross-sectional paper questionnaire study was conducted on 1400 Chinese students from grade 3 (9 years old) to grade 12 (18 years old). The respondents had to complete the socio-demographic information and the VGAS test. The VGAS characteristic was prepared in 18 criteria, which was the combination of the Video Game Addiction Test (VAT), Gaming Addiction Scale (GAS), and Revised Chinese Internet Addiction (CIAS-R). Eventually, the VGAS criteria prioritization was ranked methodologically through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for each grade separately. Additionally, the Analytic Hierarchy Process (AHP) weighting technique was utilized to analyze the video game addiction of each grade under the four alternatives, individually. The results indicate that 3rd-grade students with some levels of addiction were the youngest who felt their life would not be fun without video games. Students in 5th grade with some levels of addiction were the youngest students who disclosed that their willingness to play video games is for forgetting their problems or feeling down. Moreover, they played video games more than before, thus, they did not sleep enough. Pupils of grade 6 reported that they played video games more than last semester. In their opinion, it is fair to play video games this much and does not need to reduce playing hours. Not getting enough sleep because of playing video games was seen in 7th graders as their first preference. 10th-grade students were the first to neglect to do their important responsibilities for playing video games. None of the 7th and 12th graders were somehow safe from video game addiction. In conclusion, playing video games can negatively affect studying, sleeplessness, getting far from society, and skipping important responsibilities for school students. Furthermore, the symptoms of video game addiction had seen at younger ages. These data provided insights for decision-makers to target effective measures to prevent children and adolescents’ video game addiction.
Graphene Oxide Loaded on TiO2-Nanotube-Modified Ti Regulates the Behavior of Human Gingival Fibroblasts

Surface topography, protein adsorption, and the loading of coating materials can affect soft tissue sealing. Graphene oxide (GO) is a promising candidate for improving material surface functionalization to facilitate soft tissue integration between cells and biomaterials. In this study, TiO2 nanotubes (TNTs) were prepared by the anodization of Ti, and TNT-graphene oxide composites (TNT-GO) were prepared by subsequent electroplating. The aim of this study was to investigate the effect of TNTs and TNT-GO surface modifications on the behavior of human gingival fibroblasts (HGFs). Commercially pure Ti and TNTs were used as the control group, and the TNT-GO surface was used as the experimental group. Scanning electron microscopy, X-ray photoelectron spectroscopy, and X-ray diffraction were used to perform sample characterization. Cell adhesion, cell proliferation, cell immunofluorescence staining, a wound-healing assay, real-time reverse-transcriptase polymerase chain reaction (RT-PCR), and Western blotting showed that the proliferation, adhesion, migration, and adhesion-related relative gene expression of HGFs on TNT-GO were significantly enhanced compared to the control groups, which may be mediated by the activation of integrin β1 and the MAPK-Erk1/2 pathway. Our findings suggest that the biological reactivity of HGFs can be enhanced by the TNT-GO surface, thereby improving the soft tissue sealing ability.
A Power-Aware Real-Time System for Multi-Video Treatment on FPGA with Dynamic Partial Reconfiguration and Voltage Scaling

As the energy consumption is an evaluating factor for System-On-Chip (SOC) design, this paper presents a power-aware architecture for a real-time multi-video system on FPGA. This architecture aims to optimize power consumption for a multi-video system on ARM-based architectures. The proposed architecture uses dynamic reconfiguration and voltage scaling to create a power-aware system for real-time multi-video processing with minimal power dissipation. Dynamic partial reconfiguration was used to optimize the utilization of resources and reduce dynamic power consumption. Voltage scaling was also used to optimize dynamic power consumption, by configuring the blocks to use the minimum necessary voltage for normal operating conditions. The proposed architecture focused on the Zynq platform. The results showed power savings of up to 70% concerning performance and real-time constraints.
A Twitter Corpus for Named Entity Recognition in Turkish

This paper introduces a new Turkish Twitter Named Entity Recognition dataset. The dataset, which consists of 5000 tweets from a year-long period, was labeled by multiple annotators with a high agreement score. The dataset is also diverse in terms of the named entity types as it contains not only person, organization, and location but also time, money, product, and tv-show categories. Our initial experiments with pretrained language models (like BertTurk) over this dataset returned F1 scores of around 80%. We share this dataset publicly.
Universal Dependencies for Punjabi

We introduce the first Universal Dependencies treebank for Punjabi (written in the Gurmukhi script) and discuss corpus design and linguistic phenomena encountered in annotation. The treebank covers a variety of genres and has been annotated for POS tags, dependency relations, and graph-based Enhanced Dependencies. We aim to expand the diversity of coverage of Indo-Aryan languages in UD.