Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing library data interactively: two demonstrations using R language

Purpose This paper aims to provide two real examples to inspire librarians to use modern techniques for data visualization. Design/methodology/approach Two interactive applications were created for visualizing longitudinal and geographical data collected by libraries. Findings R language has high versatility and flexibility in visualizing various types and hierarchy of data under a prevalent Web framework. The two demonstrations provide workflows from data extractions to visualization products. Originality/value Proper visualization assists librarians and administrators to understand data better and gain more insightful prospects. As a result, more scientific decisions can be made for improving libraries operation.
Student Sensemaking of Learning Analytics Dashboard Interventions in Higher Education

An instrumental case study was conducted at a large, public research university in the mid-Atlantic region of the United States to understand undergraduate use of learning analytics dashboard (LAD) interventions. Eighty-one undergraduate students participated in focus groups. Scenario-based questions, modeled on current and future LAD interventions, were asked to understand student uses, perceptions, and reactions to these interfaces. Results indicate that student sensemaking is tied to data relevance, accuracy, and context. Further, trust in both data, especially predictive data, and in relationships, especially with faculty, are foundational to the sensemaking of LAD data and interventions. A model of student sensemaking of LAD interventions is provided.
Penerapan Feature Selection untuk Prediksi Lama Studi Mahasiswa

Student graduation on time is the problems that often experienced by college institution. A number of factors can be a cause. In this paper proposed feature selection data mining techniques for evaluating the impacts of course subjects over student graduation time. Feature selection techniques that used is Correlation Based, Information Gain Based, and Learner Based. Accuracy of each feature selection methods measured using Naïve Bayes classification algorithm. Experiment result that implementation of feature selection techniques can improve classification accuracy of Naïve Bayes algorithms. Highest accuracy was obtained using Learner Based techniques using Wrapper model. Lowest accuracy was obtained using Information Gain Based techniques.
The influence of knowledge management and professionalization on the use of ERP systems and its effect on the competitive advantages of SMEs

ABSTRACT Although the literature on Enterprise Resource Planning (ERP) systems emphasizes the importance of knowledge management and professionalization in the use of these systems, the factors that mediate these relationships are not sufficiently developed in SMEs. This study proposes the adequate application of knowledge management and professionalization would help to improve the use of ERP systems. The research uses the structural equation approach based on PLS-SEM technique with a sample of 137 Spanish SMEs. The results show that professionalization and knowledge management significantly affect the use of ERP, as well as imply a mediating effect on the competitive advantages of the SMEs. Abbreviations: ERP: Enterprise Resource Planning; SMEs: Small and Medium Enterprises; PLS: Partial Least Squares; SEM: Structural Equation Modelling
Impact of Ninjin’yoeito on frailty and short life in klotho-hypomorphic (kl/kl) mice

With the recent aging of society, the prevention of frailty has become an important issue because people desire both a long and healthy lifespan. Klotho-hypomorphic (kl/kl) mice are known to show phenotypes of premature aging. Ninjin’yoeito (NYT) is a traditional Japanese Kampo medicine used to treat patients with vulnerable constitution, fatigue or physical exhaustion caused by aging and illness. Recent studies have reported the potential efficacy of NYT against frailty. We therefore evaluated the effect of NYT on the gait function, activity, the histopathological status of organs and survival using kl/kl mice as a model of aging-related frailty. Two sets of 28-day-old male kl/kl mice were assigned to the vehicle (non-treated; NT), 3% or 5% NYT dietary groups. One set of groups (NT, n = 18; 3% NYT, n = 11; 5% NYT, n = 11) was subjected to the analysis of free walking, rotarod, and spontaneous activity tests at approximately 58 days old. Thereafter, we measured triceps surae muscles weight and myofiber cross-sectional area (CSA), and quantified its telomere content. In addition, we evaluated bone strength and performed histopathological examinations of organs. Survival was measured in the second set of groups (NT, 3% NYT and 5% NYT group, n = 8 each). In the walking test, several indicators such as gait velocity were improved in the NYT 3% group. Similar results were obtained for the latency to fall in the rotarod test and spontaneous motor activity. Triceps muscle mass, CSA and its telomere content were significantly improved in the NYT 3% group. Bone density, pulmonary alveolus destruction and testicular atrophy were also significantly improved in the NYT 3% group. Survival rate and body weight were both significantly improved in the NYT3% group compared with those in the NT group. Continuous administration of NYT from the early stage of aging improved not only gait performance, but also the survival in the aging-related frailty model. This effect may be associated with the improvements in aging-related organ changes such as muscle atrophy. Intervention with NYT against the progression of frailty may contribute to a longer, healthier life span among the elderly individuals.
VerifyNet: Secure and Verifiable Federated Learning

As an emerging training model with neural networks, federated learning has received widespread attention due to its ability to update parameters without collecting users’ raw data. However, since adversaries can track and derive participants’ privacy from the shared gradients, federated learning is still exposed to various security and privacy threats. In this paper, we consider two major issues in the training process over deep neural networks (DNNs): 1) how to protect user’s privacy (i.e., local gradients) in the training process and 2) how to verify the integrity (or correctness) of the aggregated results returned from the server. To solve the above problems, several approaches focusing on secure or privacy-preserving federated learning have been proposed and applied in diverse scenarios. However, it is still an open problem enabling clients to verify whether the cloud server is operating correctly, while guaranteeing user’s privacy in the training process. In this paper, we propose VerifyNet, the first privacy-preserving and verifiable federated learning framework. In specific, we first propose a double-masking protocol to guarantee the confidentiality of users’ local gradients during the federated learning. Then, the cloud server is required to provide the Proof about the correctness of its aggregated results to each user. We claim that it is impossible that an adversary can deceive users by forging Proof, unless it can solve the NP-hard problem adopted in our model. In addition, VerifyNet is also supportive of users dropping out during the training process. The extensive experiments conducted on real-world data also demonstrate the practical performance of our proposed scheme.
Molecular basis of genetic plasticity to varying environmental conditions on growing rice by dry/direct-sowing and exposure to drought stress: Insights for DSR varietal development

Rice requires plenty of water for its cultivation by transplanting. This poses several challenges to its cultivation due to erratic rainfall resulting in drought, flood, and other abiotic stresses of varying intensity. Dry/direct-sown rice (DSR) has emerged as a water-saving/climate-smart alternative to transplanted rice (TPR). The performance of a rice cultivar on growing by different methods of planting under varying environmental conditions varies considerably. However, the molecular basis of the observed phenotypic plasticity of rice to varying environmental conditions is still elusive. Resilience to various environmental fluctuations is important to ensure sustainable rice production in the present era of global climate change. Our observations on exclusively up-regulated genes in leaf of Nagina 22 (N 22) grown by dry/direct-sowing and subjected to drought stress at panicle initiation stage (compared to that in leaf of IR 64), and another set of genes exclusively down-regulated in leaf of N 22 (compared to that in leaf of IR 64) indicate important roles of leaf in stress resilience. A large number of genes down-regulated exclusively in root of N 22 on dry/direct-sowing subjected to drought stress indicates a major contribution of roots in stress tolerance. The genes for redox-homeostasis, transcription factors, stress signaling, carbohydrate metabolism, and epigenetic modifications play important roles in making N 22 better adapted to DSR conditions. More importantly, the involvement of genes in rendering genetic plasticity to N 22 under changing environmental conditions was confirmed by reversal of the method of planting. To the best of our knowledge, this is the first report on decoding the molecular basis of genetic plasticity of rice grown by two different methods of planting subjected to drought stress at the reproductive stage of plant growth. This might help in DSR varietal development program to enhance water-productivity, conserve natural resources, and minimize the emission of greenhouse gases, thus achieving the objectives of negative-emission agriculture.
Transparent control flow transfer between CPU and Intel FPGAs

As further improvements in computing performance and efficiency become harder to achieve, more attention is being given to heterogeneous computing platforms. These platforms offer the possibility of using dedicated hardware to accelerate software applications. However, for applications to take advantage of these platforms, they need to be rewritten, using a complex and tedious process. The goal of this work is to research transparent mechanisms that would allow the transfer of the control flow between a CPU and an FPGA, which houses an accelerator, particularly in the context of High-Performance Computing (HPC). Such a mechanism can be coupled with transparent software profiling and automatic translation to hardware, which can allow regular software to take advantage of hardware acceleration in a transparent fashion (without any human intervention). In this work, a new mechanism is proposed that uses ptrace, a Linux system call, to take complete control over a software application, and transparently transfer its execution to an accelerator. Implementation is done over Intel’s new Xeon+FPGA hybrid platform, which combines a Xeon processor and an Arria 10 FPGA in the same package while sharing the main system memory. The implemented prototype was tested using two example applications: AES 256 CTR mode encryption, and single-precision floating point matrix multiplication. When compared against a previous approach, the obtained results show that the proposed mechanism introduces an overhead penalty that does not exceed 1.1 ms but with the big advantage of allowing the transparent control flow transfer of any type of function, which has not been possible before.
Predicting Energy Expenditure During Gradient Walking With a Foot Monitoring Device: Model-Based Approach

Background Many recent commercial devices aim at providing a practical way to measure energy expenditure. However, those devices are limited in accuracy. Objective This study aimed to build a model of energy consumption during walking applicable to a range of sloped surfaces, used in conjunction with a simple, wearable device. Methods We constructed a model of energy consumption during gradient walking by using arguments based in mechanics. We built a foot monitoring system that used pressure sensors on the foot insoles. We did experiments in which participants walked on a treadmill wearing the foot monitoring system, and indirect calorimetry was used for validation. We found the parameters of the model by fitting to the data. Results When walking at 1.5 m/s, we found that the model predicted a calorie consumption rate of 5.54 kcal/min for a woman with average height and weight and 6.89 kcal/min for an average man. With the obtained parameters, the model predicted the data with a root-mean-square deviation of 0.96 kcal/min and median percent error of 12.4%. Conclusions Our model was found to be an accurate predictor of energy consumption when walking on a range of slopes. The model uses few variables; thus, it can be used in conjunction with a convenient wearable device.
Performance Analysis of NLMS Channel Estimation for AMC-COFDM System

In this paper we focus on the adaptive modulation and coding (AMC) techniques, makes use of the channel state information (CSI) to improve the spectral efficiency (SE) in wireless communication systems. To achieve higher data rates and lower bit error rate (BER's) channel coding can be carried out in OFDM, called COFDM. The NLMS channel estimator is used. The simulation analysis presented includes comparisons of SE and throughput vs. SNR for different proposed schemes.
DESIGN OF LEARNING AND TEACHING SPACE FOR PROFESSIONAL GRADUATE DEGREE PROGRAM USING USER EXPERIENCE DESIGN

The professional graduate degree programs including Engineering and Technology Management programs have gained huge popularity all over the world. For most of the programs, the students are the graduates of engineering or similar technical programs with some work experience in the related sphere, and their primary aim is to improve their management skills within the professional & academic network through collective learning platforms. Considering that the students of such programs spend most of their time for their coursework, projects, meetings, and group-studies with their peers, as well as for self-studies, the design of teaching/learning facilities of such professional degree programs is of the utmost importance. This paper presents the re-design of a teaching and learning facility for the students of a Master of Engineering Management (EM) program using the User Experience Design (UXD) approach. UXD is a process of interaction between the user and the design of a product or service, which makes a design more valuable, useful, usable, accessible, desirable, and credible to the user. The primary user group in the form of EM students was identified and the re-design of teaching/learning facilities was developed based on the students’ feedback using the most suitable UXD tools such as persona, survey, guerrilla test, storytelling, A/B test, and card sorting. The responses of students showed that there are not enough spaces at the campus that can be used for the effective collaboration and group studies with their peers in the same program and make them feel comfortable, and that the design of the current regular classrooms is far from meeting the expectations of the students. After careful analysis of the obtained results, the most important attributes of the needed facilities were chosen to design and visualize the new facility in a 3D software program. The final proposed learning and teaching space can serve as a place for students to study, connect, collaborate, innovate and co-create with others.
A semantic event based framework for complex situations modeling and identification in smart environments

Integration of technologies and smart services is an essential need in most pervasive smart automation systems, especially those requiring agile situation management such as a smart home. Ontology reasoning is an efﬁcient technique for identifying the situation of such systems by capturing the context and optimizing connected object lifecycle. It is based on common-sense knowledge for interpreting a huge number of events from different and heterogeneous connected objects. The ontology-driven approach may be used to solve the parallel incoming events using new combination operators in order to achieve high accuracy rates. This paper presents a flexible, modular and hierarchical loosely coupled framework based on open semantic services in order to identify highly complex events to hold the situations with high efficiency. The proposed approach is evaluated on smart domains use cases and compared with other existing methods. Results show interesting ratios of situation identification accuracy with low execution time.
Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review

Fiber-reinforced polymer composites have excellent mechanical properties and outstanding development potential and are cost-effective. They have increasingly been used in numerous advanced and engineering applications as materials for wind turbine blades, helicopter rotors, high-pressure pipelines, and medical equipment. Understanding and assessing structural failure promptly in the whole lifecycle of a composite is essential to mitigating safety concerns and reducing maintenance costs. Various nondestructive testing and evaluation (NDT&E) technologies based on different evaluation principles have been established to inspect defects under different conditions. This paper reviews the established types of NDT&E techniques: acoustic emission, ultrasonic testing, eddy current testing, infrared thermography, terahertz testing, digital image correlation, shearography, and X-ray computed tomography, which is divided into three categories based on the operation frequency and data processing means of the output signal that is directly under analysis. We listed four types of defects/damage that are currently of great interest, namely, voids and porosity, fiber waviness and wrinkling, delamination and debonding, as well as impact damage. To identify a suitable method for different defects/damage, we performed characterization and evaluation by using these NDT&E techniques for typical defects/damage. Then, the cost, inspection speed, benefits and limitations, etc. were compared and discussed. Finally, a brief overview of the development of the technologies and their applications in the field of composite fabrication was discussed.
SHARED LEARNING DATA ALLOWING BLENDING OF A VARIETY OF TOOLS AND A CENTRAL POINT OF DATA COLLECTION

We will present the preliminary results of an investigation on the use of a variety of learning tools loosely integrated by the Next Generation Digital Learning Environment (NGDLE) of the Up2U EU-funded project. Students perform individual and group activities, both formal and informal ones, within a project of fixed duration, to accomplish a common task established by a teacher or chosen by the learners on their own initiative. Learning-related data are fed to a central store by a popular LMS, by a collaborative platform supporting project-oriented and artifact-oriented learning and by more specialized tools able to track a set of less structured activities. Data are then processed in various ways to analyse meaningful correlations between activities mediated by different tools and are finally compared to information acquired in more traditional ways about some skill levels, before and after the project execution. The investigation puts a special focus on actions related to the set-up and the coordination of a project group and on the activity aimed at finding educational resources on the web. The tools in the NGDLE use the xAPI protocol to send statements of user actions. A common Learning Record Store (LRS) is provided by the NGDLE itself. Processing of analytics data is performed both with native functions of the LRS and with external tools being fed with exported data.
A 0.34-THz Wideband Wide-Angle 2-D Steering Phased Array in 0.13- $\mu$ m SiGe BiCMOS

In this paper, a 0.34-THz <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> phased array integrated circuit is presented, which demonstrates a new approach for implementing phased arrays in the millimeter-wave (mm-wave)/terahertz (THz) spectrum. The circuit structure consists of four unit standing wave oscillators. In each cell, fundamental frequency (<inline-formula> <tex-math notation="LaTeX">$f_{0}$ </tex-math></inline-formula>) and odd harmonics are systematically cancelled, while the desired fourth harmonics (<inline-formula> <tex-math notation="LaTeX">$4f_{0}$ </tex-math></inline-formula>) are combined and radiated by on-chip patch antennas. A phase-shifter-less mechanism is employed based on combining standing and traveling waves to create the required phase shift between the sources for beam steering. The transistors provide negative resistance to the circuit and generate the desired fourth harmonics through nonlinearity. Simultaneously, transistors are employed as active variable capacitors for varactor-less frequency tuning. The implemented phased array is capable of independent wideband frequency tuning and 2-D wide-angle beam steering. The circuit is fabricated in a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text {m}$ </tex-math></inline-formula> SiGe BiCMOS process and is measured to have 52-GHz/15.1% frequency tuning range from 318 to 370 GHz and 128°/53° 2-D beam-steering angle. The chip consumes 310–640 mW power from a 1.5-V supply with −6.8-dBm maximum radiated power and minimum −93.1-dBc/Hz phase noise at 10-MHz offset. To the best of our knowledge, this paper has the largest bandwidth among fully integrated THz radiator/phased arrays as well as the widest angle beam steering among fully integrated THz phased arrays.
Modal Analysis of Lenses Used in Automotive Lighting Industry and Obtaining MAC Matrix

In this study, 4 different pieces of automotive rear lamp lenses which are made of Polymethylmethacrylate (PMMA) and have different geometries have been inspected. Free-free natural frequencies and mode shapes of lenses have been estimated by the help of ANSYS WB® Finite Element Analysis (FEA) software. Meanwhile, by the help of Experimental Modal Analysis (EMA) methods; natural frequencies, damping ratios and mode shapes of the lenses have been determined. Finally, mode shapes calculated by FE and measured by EMA were compared and Modal Assurance Criteria matrix (MAC) was determined. After experimental modal tests, FRF’s were calculated by DEWESoft® X3 software then natural frequencies, damping ratios and mode shapes were calculated by the use of ME’scope® VESVT-570 Visual Modal software. In addition, MAC was calculated by the help of MEScope® software. The main reason for the use of such experimental methods was to understand if the assumptions made before theoretical analysis were satisfied in reality or not.