Miracle-dz/UniFAR-FTUs huggingface dataset:
Techno-Spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Members 130-138

Keeping users engaged with mHealth applications is important but difficult to achieve. We describe the development of a smartphone-based application designed to promote health and wellness in church communities, along with mechanisms explicitly designed to maintain engagement. We evaluated religiously tailored techno-spiritual engagement mechanisms, including a prayer posting wall, pastor announcements, an embodied conversational agent for dialogue-based scriptural reflections and health coaching, and tailored push notifications. We conducted a four-week pilot study with 25 participants from two churches, measuring high levels of participant acceptance and satisfaction with all features of the application. Engagement with the app was higher for users considered to be more religious and correlated with the number of notifications received. Our findings demonstrate that our tailored mechanisms can increase engagement with an mHealth app.
A Deep Learning-based Approach to Model Museum Visitors 217-221

Although ubiquitous and fast access to the Internet allows us to admire objects and artworks exhibited worldwide from the comfort of our home, visiting a museum or an exhibition remains an essential experience today. Current technologies can help make that experience even more satisfying. For instance, they can assist the user during the visit, personalizing her experience by suggesting the artworks of her higher interest and providing her with related textual and multimedia content. To this aim, it is necessary to automatically acquire information relating to the active user. In this paper, we show how a deep neural network-based approach can allow us to obtain accurate information for understanding the behavior of the visitor alone or in a group. This information can also be used to identify users similar to the active one to suggest not only personalized itineraries but also possible visiting companions for promoting the museum as a vehicle for social and cultural inclusion.
PENGEMBANGAN MODEL BODY WEIGHT TRAINING UNTUK LATIHAN OTOT PERUT

Kurangnya pengetahuan tentang model/variasi latihan body weight menyebabkan members fitness/pelaku olahraga pada saat melakukan latihan beban terkesan monoton, kurang bervariasi dan membosankan. Tujuan penelitian ini adalah untuk mengembangkan model body weight training untuk latihan otot perut, yang nantinya dapat menjadi panduan untuk latihan otot perut dan diharapkan dapat mempercepat pembentukan otot perut menjadi sixspack. Model-model body weight training lebih menekankan pada spesifikasi bagian otot perut. Penelitian ini merupakan penelitian pengembangan model dengan langkah-langkah penelitiannya sebagai berikut: (1) mengenali potensi dan masalah, (2) pengumpulan data, (3) desain produk, (4) validasi desain, (5) revisi desain, (6) uji coba produk, (7) revisi produk, (8) uji coba pemakaian, (9) revisi produk, dan (10) produk masal. Validasi draf model latihan dilakukan oleh tiga ahli/pakar materi tentang kebugaran fisik. Sampel penelitian dalam uji coba skala kecil berjumlah 5 responden dan uji coba skala besar berjumlah 20 responden. Penelitian dilakukan di Club Arena International Hotel Pandanaran, Hotel Jambuluwuk, dan Hotel Ros In. Teknik analisis data menggunakan data kualitatif dan kuantitatif. Data kualitatif diperoleh dari: (1) hasil wawancara dengan members fitness center, (2) catatan lapangan, dan (3) data saran perbaikan draf model awal dan hasil observasi pada pelaksanaan uji coba dengan skala kecil dan besar. Data kuantitatif diperoleh dari: (1) penilaian skala nilai validasi draf model, (2) penilaian skala nilai observasi pelaksanaan model, dan (3) hasil penilaian kuesioner uji coba skala kecil dan besar dari responden. Hasil yang diperoleh dari data validasi draf model dan observasi pelaksanaan model latihan oleh ahli/pakar 100 % baik sekali. Hasil penilaian kuesioner uji coba skala kecil 80 % baik sekali dan 20 % baik, sedangkan untuk hasil kuesioner uji coba skala besar 60 % baik sekali dan 40 % baik. Berdasarkan hasil tersebut dapat diartikan bahwa model body weight training untuk latihan otot perut layak untuk digunakan.
AI as an Active Writer: Interaction Strategies with Generated Text in Human-AI Collaborative Fiction Writing 56-65

Machine Learning (ML) has become an important part of the creative process for human fiction writers, allowing them to utilize various sources of information and be inspired by strategies and data previously seldom explored. To investigate how human writers collaborate with ML systems in fiction writing, we prototyped a web-based human-AI collaborative writing tool that allows writers to shorten, edit, summarize, and regenerate text produced by AI. To investigate the dynamics of human-AI interaction in fiction co-writing, we used a "finish each other’s story" approach where humans and machines took turns writing collaborative fiction. In results from a preliminary study with 9 users, we found that users took inspiration from unexpected text generated by the machine, that users expected reduced fluency and coherence in the machine text when allowed to edit the output, and that they perceived a mental model of the AI as an active writer in the collaborative process rather than simply as a passive AI writing assistant. This study provides design implications on supporting co-creative writing of humans and machines.
Potential Energy to Improve Link Prediction With Relational Graph Neural Networks

Potential Energy (PE) between 2 bodies with mass, refers to the relative gravitational pull between them. Analogously, in the context of a graph, nodes can thought of as objects where a) the product of the degrees of nodes acts as a proxy for mass, b) the clustering coefficients of common neighbours as a proxy for gravitational acceleration, and c) the inverse of the shortest distance between nodes as a proxy for distance in space, which allows for PE calculation as introduced in prior work. In this work, we are investigating the effects of incorporating PE in Link Prediction (LP) with Relational Graph Convolutional Networks (R-GCN). Specifically, we explore the benefits of including PE calculation as an informative prior to the LP task and in a follow-up experiment as a learnable feature to predict. We performed several experiments and show that considering PE in the LP process has certain advantages and find that the information PE provides was not captured by the embeddings produced by the R-GCN.
Contrastive Visual and Language Translational Embeddings for Visual Relationship Detection

Visual relationship detection aims to understand real-world interactions between object pairs by detecting visual relation triples written in the form of (subject, predicate, object) . Previous work has explored the use of contrastive learning to generate joint visual and language embeddings that aid the detection of both seen and unseen visual relation triples. However, these contrastive approaches often learned the mapping functions implicitly and did not fully consider the underlying structure of visual relation triples, limiting the models’ use cases and their ability to generalize to unseen compositions. This ongoing work aims to construct joint visual and language embedding models that can capture such hierarchical structure between objects and predicates by explicitly imposing structural loss constraints. In this short paper, we propose VLTransE, a novel embedding model that applies translational loss in conjunction with the visual-language contrastive loss to learn transferable embedding spaces for subjects, objects, and predicates. At test time, the model ranks potential visual relationships by aggregating the visual-language consistency score and the translational score. The preliminary results show that the contrastive model trained with the translational loss constraint can capture hierarchical information which aids the prediction of not only visual predicates but also masked-out objects, while achieving comparable predicate prediction results to the model trained without the translational loss.
A quad-band branch line coupler with high frequency ratio

In this paper, a novel quad-band branch line coupler with high ratio (from 6.27 to 14.96) of the largest operating frequency to the smallest operating frequency is presented. To realize quad-band operations, a combination of coupled lines and open stubs is proposed which can make the design flexible. By using analysis of even and odd modes, the equivalent equations for the quad-band operation are obtained. Compared to the existing quad-band branch line coupler, the proposed quad-band coupler has the highest ratio of the largest operating frequency to the smallest operating frequency, which is valuable for wideband and ultra wideband application. For practical applications, a quad-band coupler operating at 0.7, 1.64, 4.09, and 5.03 GHz which can be used for the long term evolution (LTE) and Wi-Fi is designed, fabricated, and measured. The simulated and measured results agree well with the design theory.
Is Explainable AI a Race Against Model Complexity? 192-199

Explaining the behaviour of intelligent systems will get increasingly and perhaps intractably challenging as models grow in size and complexity. We may not be able to expect an explanation for every prediction made by a brain-scale model, nor can we expect explanations to remain objective or apolitical. Our functionalist understanding of these models is of less advantage than we might assume. Models precede explanations, and can be useful even when both model and explanation are incorrect. Explainability may never win the race against complexity, but this is less problematic than it seems.
A Method to Deal With Social Bias and Desirability in Ethical Requirements

[Context] Ethical requirements are a growing area of importance for software. Yet, when dealing with these types of requirements from users, the subject might not always give an accurate representation of their requirements, due to social factors. [Question/problem] Which methods can help mitigate social desirability when dealing with ethical requirements? [Principal ideas/results] This article proposes the usage of factorial survey experiments (FSE) to work around social desirability when working with ethical requirements. FSE works with vignettes, which the RE practitioner presents to the subject, and experimentally varies them to comprehend how the subject reacts to different stimuli. It enables quantitative analysis of requirements and their specifications, adding explainability and transparency to the RE process. [Contribution] This article describes how to use FSE for ethical requirements, and its advantages. We also give an example of application, for which we share preliminary results. Our work opens the discussion for a possible framework using FSE for ethical requirements.
A Shared Aperture Millimeter Wave Antenna Using 3D SIW Technology

A shared aperture millimeter wave antenna array based on three-dimensional (3D) substrate integrated waveguide (SIW) technology is designed for millimeter wave wireless com- munication applications. Dipole and slot antenna are used as elements and the two proposed antenna arrays work at 28GHz and 75GHz respectively. Both arrays use SIW H-to-E-plan vertical interconnect to form 3D architecture (1). With the development of wireless communication technology, the lower frequency spectrum is be- coming more and more crowded. To solve this problem, millimeter wave wireless communication has been studied for many years, since it has many advantages, such as large capacity of commu- nication, high quality of transmission and high confldentiality In this paper, a shared aperture antenna using 3D SIW technology is proposed. Because of the narrow spacing between the 75GHz element, the 28GHz dipole array is placed in the vertical plane while the 75GHz slot array is placed in the horizontal plane. A 1/8 and a 1/4 power divider are designed to feed the two arrays respectively. SIW H-to-E-plane interconnect is used to form a 3D power divider structure. Rogers RT/Duroid 5880 †r = 2:2 with the thickness of 0.254mm is adopted as substrate material in this design
Fault tolerant control against actuator faults based on enhanced PID controller for a quadrotor

Purpose The purpose of this paper is to present fault tolerant control of a quadrotor based on the enhanced proportional integral derivative (PID) structure in the presence of one or more actuator faults. Design/methodology/approach Mathematical model of the quadrotor is derived by parameter identification of the system for the simulation of the UAV dynamics and flight control in MATLAB/Simulink. An improved PID structure is used to provide the stability of the nonlinear quadcopter system both for attitude and path control of the system. The results of the healty system and the faulty system are given in simulations, together with motor dynamics. Findings In this study, actuator faults are considered to show that a robust controller design handles the loss of effectiveness in motors up to some extent. For the loss of control effectiveness of 20 per cent in first and third motors, psi state follows the reference with steady state error, and it does not go unstable. Motor 1 and Motor 3 respond to given motor fault quickly. When it comes to one actuator fault, steady state errors remain in some states, but the system does not become unstable. Originality/value In this paper, an enhanced PID controller is proposed to keep the quadrotor stable in case of actuator faults. Proposed method demonstrates the effectiveness of the control system against motor faults.
Directe en indirecte werknemersparticipatie in Europa

This study looks at different forms of direct and indirect employee participation in the EU. The research questions are: (1) which forms of direct and indirect employee participation can we distinguish? ; (2) to what extent do forms of direct and indirect employee participation coincide within organisations? ; and (3) to what extent are forms of direct and indirect employee participation associated with (a) workplace wellbeing and (b) the (economic) performance of the organisation? Using the ECS-2013 we analyse data from 24,251 establishments in the 28 EU Member States. Latent class analyses distinguished four types of indirect employee participation and five types of direct employee participation that vary in the extent to which participation is being facilitated. We found little support for the hypothesis that direct employee participation is deployed to replace indirect employee participation: establishments most commonly combine direct and indirect forms of employee participation. Multilevel analyses showed that more extensive forms of direct and indirect employee participation are associated with beneficial outcomes for the organisation (performance) and their employees (workplace wellbeing).
Transformerless Inverter with Charge Pump Circuit Concept for PV Application

This paper introduces a new single phase transformerless photovoltaic (PV) inverter for grid connected PV systems using the concept of a charge pump. It consists of four power switches, two diodes, two capacitors and an LC filter at the output stage. The neutral of the grid is directly connected to the negative terminal of PV panel. This common ground creates a constant Common Mode (CM) voltage and zero leakage current. Meanwhile, the charge pump circuit generates the negative bus voltage for the inverter during the negative power cycle. A unipolar Sinusoidal Pulse Width Modulation (SPWM) technique is applied to the proposed inverter with three level output voltage to reduce the output current ripple and the filter requirements. The main advantages of the proposed inverter are (1) the negative polarity of the PV is directly connected to the grid, so the leakage current eliminated, (2) it has a compact size, (3) peak of output voltage is equal to input dc voltage (unlike Neutral Point Clamped (NPC) inverter, Active NPC (ANPC) and some topologies, which requires two times of the peak ac-voltage magnitude), flexible grounding configuration and high efficiency. The operating principle and analysis of the proposed topology are presented in details. Experimental results of a 500 W prototype are demonstrated to validate the proposed topology and the overall concept. The obtained results clearly verify the performance of the proposed inverter and its practical application for grid connected PV systems.
Performance of 4 /spl times/ 4 sequentially rotated patch antenna array using series feed

A new 4 /spl times/ 4 sequentially rotated patch antenna array using an out-of-line series feed network is presented. The use of a series feed is shown to increase input impedance bandwidth and axial ratio bandwidth compared with a corporate feed when used in this sequentially rotated array. Performance is confirmed by full-wave simulation and experimental measurement, demonstrating a voltage standing wave ratio 2:1 bandwidth of 14.7% and a 3 dB axial ratio bandwidth of 12.4%.
A Novel Structure to Realize Memory Cell Fluctuation Under Voltage Control in Ising Chip

New computing architecture utilizing the noise of integrated circuit to realize indeterminate computing has been proposed previously to solve combinatorial optimization problems. But the solution accuracy of realizing indeterminate computing with circuit's noise performed significantly worse than that with external random number. Because large scale of time is spent to introduce randomness in reading memory cells by row, which reduces the effective computing time. This paper presents a novel structure to introduce probabilistic behavior with just one read operation. It improves the rate of effective computing time and can get close solution accuracy to the scheme using external random number but with less cost. Introduction Most combinatorial optimization problems belong to NP-hard class problems [1]. Generally, finding the global optimum solution to them in conventional computer needs exponential time. CMOS implementation of Ising computing has been proposed previously to solve this problem with its own convergence property [2]. It maps the problem to the coefficients of Ising model firstly and then activates the ground-state search by interaction between spins. Finally the solution is acquired through observing the ground state [3]. The purpose of Ising computer is to find a spin configuration that minimizes the energy of the system [4], which corresponds to the ground state [5]. But the energy profile of the Ising model has peaks and troughs as shown in Fig. 1. The energy goes down along the energy profile by interaction between spins but will fall into a local optimum and be stuck at these points in many cases [6]. Then the system needs to change to other states randomly to prevent being stuck at local optimum. 425 Advances in Computer Science Research (ACRS), volume 54 International Conference on Computer Networks and Communication Technology (CNCT2016)
Enhancing Self-Organizing Maps with numerical criteria: a case study in SCADA networks

Self-Organizing Maps (SOM) can provide a visualization for multi-dimensional data with two dimensional mappings. By applying unsupervised learning techniques to SOM representations, we can further enhance visual inspection for change detection. In order to obtain a more accurate measurement for the changes of self-organizing maps beyond simple visual inspection, we introduce the Gaussian Mixture Model (GMM) and Kullback-Leibler Divergence (KLD) on top of SOM trained maps. The main contribution in this dissertation focuses on adding numerical methods to SOM algorithms, with anomaly detection as example domain. Through extensive tracedbased simulations, it is observed that our techniques can uncover anomalies with an accuracy of 100% at an anomaly mixture-rate as low as 12% from the CTU-13 dataset. Tuning of the KLD threshold further reduces the mixture-rate to 7%, significantly augmenting visual inspection to assist in detecting low-rate anomalies. Suitable hierarchical and distributed SOM-based approaches are also explored, along with other approaches in the literature. Hierarchies in SOM can show the correlations among the neural cells on the self-organizing maps. In order to obtain a higher accuracy for anomaly detection, a new dimension of labels is suggested to be added in the second layer of SOM training. Also for more general distributed SOMbased algorithms, we investigate the use of principal component analysis (PCA) for
A survey on experimental and numerical studies of convection heat transfer of nanofluids inside closed conduits

Application of nanofluids in heat transfer enhancement is prospective. They are solid/liquid suspensions of higher thermal conductivity and viscosity compared to common working fluids. A number of studies have been performed on the effect of nanofluids in heat transfer to determine the enhancement of properties in addition to rearrangement of flow passage configurations. The principal objective of this study is to elaborate this research based on natural, forced, and the mixed heat transfer characteristics of nanofluids exclusively via convection for single- and two-phase mixture models. In this study, the convection heat transfer to nanofluids has been reviewed in various closed conduits both numerically and experimentally.
Galactic Anomalies and Particle Dark Matter

This is a brief review of aspects of galactic astrophysics and astronomy which have a possible bearing on particle dark matter. It is still quite normal for particle physicists to try to solve “well known anomalies“ that are apparently seen in observations of galaxies (missing satellites, cusp vs. core, etc.) whereas a lot of these anomalies have actually been resolved many years ago. We will try to briefly review the field and discuss many of the areas in question.