Reviewerly/exHarmony huggingface dataset:
Convolutional neural network acoustic model for robust Indonesian speech recognition in noisy environment

Abstract Noise causes the decreasing accuracy of automatic speech recognition (ASR). Several techniques have been developed and proposed to overcome this problem. Using artificial neural network (ANN) as acoustic model is one of the techniques. Convolutional neural network (CNN) is a variant of ANN that has been used for acoustic modeling. Another approach is to do pre-processing to the speech signal or to the extracted acoustic feature from speech signal, such as cepstral mean and variance normalization (CMVN). On this work, CNN acoustic models were trained by using CMVN pre-processed acoustic feature to make a noise-robust speech recognition system. Two group of models were made, each to handle 2 kinds of noise (babble noise and street noise). Those acoustic models were tested with noisy speech at different SNR (signal-to-noise ratio) value. Testing results from CNN acoustic models were compared with the ones from Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) acoustic models. Testing results showed the increasing accuracy scores of acoustic models when models were trained using more variation of training data. CNN acoustic models that were trained using FBANK feature have higher accuracy scores than GMM-HMM models that were built using the same feature.
A Behavior Optimization Method for Unmanned Combat Aerial Vehicles Using Matrix Factorization

One of the fundamental technologies for unmanned combat aerial vehicles and combat simulators is behavior optimization, which finds a behavior that maximizes the probability of winning a battle. With the advent of military science, combat logs became available, allowing machine learning algorithms to be used for the behavior optimization. Due to implicit attributes such as the experience of an operator that are not explicitly presented in log data, existing methods for behavior optimization have limitations in performance improvement. Furthermore, specific behaviors occur with low frequency, resulting in a dataset with imbalanced and empty values. Therefore, we apply a matrix factorization (MF) method, which is one of latent factor models and known for sophisticated imputation of empty values, to the behavior optimization problem of unmanned combat aerial vehicles. A situation-behavior matrix, whose elements are ratings indicating the optimality of behaviors in situations, is defined to implement the MF based method. Experiments for performance comparison were conducted on combat logs, in which the proposed method yielded satisfactory results.
Constant-Round Leakage-Resilient Zero-Knowledge from Collision Resistance

In this paper, we present a constant-round leakage-resilient zero-knowledge argument system for $$\mathcal {NP}$$ under the assumption of the existence of collision-resistant hash function families. That is, using a collision-resistant hash function, we construct a constant-round zero-knowledge argument system that has the following zero-knowledge property: even against any cheating verifier that obtains an arbitrary amount of leakage on the prover’s internal secret state, a simulator can simulate the verifier’s view by obtaining the same amount of leakage on the witness. Previously, leakage-resilient zero-knowledge proofs/arguments for $$\mathcal {NP}$$ were constructed only under a relaxed security definition (Garg et al., in: CRYPTO’11, pp 297–315, 2011) or under the DDH assumption (Pandey, in: TCC’14, pp 146–166, 2014). Our leakage-resilient zero-knowledge argument system satisfies an additional property that it is simultaneously leakage-resilient zero-knowledge, meaning that both zero-knowledge and soundness hold in the presence of leakage.
3CPS

The growing popularity of applications based on 3D rendering, such as visual effects, gaming, augmented and virtual reality, calls for the development of new solutions for the delivery of 3D objects, in particular textures. The format of texture images, which capture the characteristics of materials, has to address two constraints. First, the delivery on the Internet imposes a reduction of the image size. Second, because of memory limitations, the processing by the rendering engine is done in the GPU by extracting small areas of the image only. The format of texture images should thus enable the random-access feature for independent processing of small blocks of the images, called texels, which negatively affects the texture compression performance and, therefore, the network delivery.
High Tempo Work: Design Challenges for Head-worn Displays in Quick Service Restaurants

Quick service restaurants (QSRs) are high tempo work environments that require collaboration and communication between crew. In a number of respects, head-worn displays (HWDs) might seem a promising technology to support QSR crew, but on close inspection they raise challenging issues for design. We conducted fieldwork studies at two large QSRs to understand how work is organised, how existing systems are used, and how information is displayed to and communicated between crew. We observed the crew working both routinely and with improvisation, collaboratively and individually, physically and digitally. From our analysis of the field study, we identify tentative use cases for HWDs, but with these also design tensions-that is, opportunities coupled with challenges that appear difficult to circumvent even with modest design proposals. These tensions would require careful consideration if HWDs were to be deployed in in QSRs, given that HWDs are ubiquitous, potentially private, digital, mobile, and able to collect behavioural data.
Improved of Smart Vacuum Flask with Beverage Identifier and Temperature Indicator

Abstract Vacuum flask has been an essential part of the everyday life of a working person. Nowadays, vacuum flask is not the only function as a liquid carrier but also has been equipped with technology to diversify its function from the essential function. This paper proposes to create a smart vacuum flask that able to classify the beverage type and indicate the temperature range of the beverage. This is attempted to address the user difficulty in remembering the type and temperature of the beverage inside the vacuum flask. This project is built using Arduino as the microcontroller, while LM35 is used to read the temperature sensor. A simple concept of tomography using LDRs and LEDs is used to determine the beverage type. The flask is tested to test nine scenarios: 1) cold and clear beverage; 2) warm and clear beverage; 3) hot and clear beverage; 4) cold and juice beverage; 5) warm and juice beverage; 6) hot and juice beverage; 7) cold and milk beverage; 8) warm and milk beverage; 9) hot and milk beverage. The result obtained indicates that the prototype able to classify all nine scenarios correctly.
Entrepreneurship Development Interventions as a Pragmatic Approach to Political and Economic Restructuring in Nigeria

This study discusses the imperative of entrepreneurship development interventions as pragmatic responses to political and economic restructuring in Nigeria. The qualitative research method, which entails a systematic collection of information extracted from government documents and scholarly articles, was adopted. The extracted information was critically reviewed and synthesized using content analysis. The chapter found that political and economic structures in Nigeria are largely ineffective and require urgent restructuring. For political restructuring, there is a need for constitutional amendments, while for economic restructuring, the establishment of industrial clusters to reinvigorate entrepreneurship development interventions is imperative. The study concludes with policy implications and suggestions for further research.
Optimal Tuning of PID Control on Single Machine Infinite Bus Using Ant Colony Optimization

Sudden changes in the load on the electric power system will cause a dynamic disturbance. This interference causes the generator stability to be disrupted because the generator does not respond to the interference quickly. This causes oscillations in the generator in the form of frequency oscillations and rotor angles. One additional control equipment that can improve the stability of a generator is the Power System Stabilizer (PID). When there is a disturbance oscillation on the generator, the PID provides an additional signal to the excitation equipment to provide additional attenuation to the generator. The use of PID is needed to coordinate the determination of the right parameters to achieve good performance control for the system. In the application, the determination of PID parameters still uses the trial & error method, this method is very difficult to get the right parameters. To solve this problem, here the author uses one of the computational techniques (soft computing) artificial intelligence, namely the Ant Colony Optimization (ACO) algorithm to optimize the tuning of the PID parameters. From the simulation results, the optimal PID parameters obtained are P (Proportional) of 53.4899, I (Integral) of 14.6551, and D (Derivative) of 10.5383. With optimal tuning, the SMIB frequency response is perfect compared to the system without PID trial error control and control, this is indicated by the system response that has improved, where the controller is able to provide stability so that the overshoot oscillation can be muted, and the settling time performance is faster for the system goes to steady-state condition. By tuning the right PID parameters, Overshoot that occurs in this system can be muted that is equal to -0.0002609 up to 0.0001954.
Teaching based on models and transformations under the active learning approach

Abstract Requirements engineering is a fundamental part of the software development cycle and, therefore, must be present in the curricula of systems engineering programs. In this document, a set of training situations based on active learning principles is presented to facilitate the teaching of requirements engineering. In the application of the methodology, the subjects of the software engineering line of the systems engineering program of the “Universidad Francisco de Paula Santander, Ocaña, Colombia” were used, guiding the process for teaching requirements engineering in agile environments with a view from the model driven engineering and its implementation in a virtual environment as a complement to the face-to-face classes. The strategy allowed participants to be organized in teams to improve requirements engineering learning. An activity guide based on scenarios with real problems was used, which allowed to strengthen the relationship between theory and practice of the subject to generate models and transform them into the search for solutions to problem domain under study.
The QQUIC Transport Protocol: Quantum-Assisted UDP Internet Connections

Quantum key distribution, initialized in 1984, is a commercialized secure communication method that enables two parties to produce a shared random secret key using quantum mechanics. We propose a QQUIC (Quantum-assisted Quick UDP Internet Connections) transport protocol, which modifies the well-known QUIC transport protocol by employing quantum key distribution instead of the original classical algorithms in the key exchange stage. Due to the provable security of quantum key distribution, the security of the QQUIC key does not depend on computational assumptions. It is possible that, surprisingly, QQUIC can reduce network latency in some circumstances even compared with QUIC. To achieve this, the attached quantum connections are used as the dedicated lines for key generation.
Creative Expression with Immersive 3D Interactions

Virtual and augmented realities (VR/AR) allow artists to create 3D content in a three-dimensional space — both display and inputs are 3D. Getting rid of 2D proxies such as screens and graphic tablets removes a significant barrier from 3D creation and allows artists to create more intuitively, and potentially more efficiently. However, creating in VR/AR introduces new control, precision, and ergonomic challenges. Designing interactive tools for 3D creation is therefore non-trivial. A deep understanding of human factors, user preferences, as well as biases stemming from users' experience with 2D tools is essential to develop effective creative tools for VR/AR. My research combines exploratory user studies and technical advancements to build novel tools for creating 3D content in immersive spaces. I present two computer graphics applications which utilize 3D interactions to improve existing creative workflows and devise novel ones for visual creative expression in three-dimensions. The first studies concept sketching, while the second explores animation of dynamic physical phenomena. I then describe my ongoing work and planned future work on other creative applications.
Design and Implementation Network Administrators Account Management System Based on Authentication, Authorization, and Accounting Based on TACACS and LDAP

Abstract Authentication is required for to authenticate user administrators for accessing network devices. In large-scale network devices management, firstly administrators need centralized user management to modify their account for logging network devices. Secondly, they must have log monitoring data who modified their account. The goal of this research is to develop and implement Authorization, Authentication, Accounting (AAA) system and making Log Monitoring System (LMS). Objectives of this research are implementing a system that can centralize and manage network administrators account. Design and topology of the network use simple star network. Software design uses Rapid Application Development (RAD) method. Research began with analyzing the research problem, next step is creating a system design, then build the system. After the system has been built, a demo is done whether the system is running well. If the system has not functioning as desired yet, refine the system. If already functioning as desired, a testing is done. If there are no obstacles during testing, the system is ready to be implemented by users who will use the system. The result shown that system is able to centralized authentication and authorization using Terminal Access Controller Access-Control System (TACACS), and processing accounting data into information in graphical form using ELK Stack. The result of the research is developing monitor user login and log review. The test result shown that system can manage network administrators account according to the Authentication, Authorization, Accounting (AAA) principle.
Configuration Lattices for Planar Contact Manipulation Under Uncertainty

This work addresses the challenge of a robot using real-time feedback from contact sensors to reliably manipulate a movable object on a cluttered tabletop. We formulate this task as a partially observable Markov decision process (POMDP) in the joint space of robot configurations and object poses. This formulation enables the robot to explicitly reason about uncertainty and all major types of kinematic constraints: reachability, joint limits, and collision. We solve the POMDP using DESPOT, a state-of-the-art online POMDP solver, by leveraging two key ideas for computational efficiency. First, we lazily construct a discrete lattice in the robot’s configuration space. Second, we guide the search with heuristics derived from an unconstrained relaxation of the problem. We empirically show that our approach outperforms several baselines on a simulated seven degree-of-freedom manipulator.
The Research and Practice of a General Data Management Tool on Multivariate Marine Geology Data

In this paper a general data management tool based on Oracle database and Spring MVC framework is designed and developed, which takes advantage of oracle's high-performance nested query and combines the recursive data of relational database with the front-end tree structure. The general data management tool allows customizing data directories and data structures as needed, thus the storage and query of multivariate data can be realized. We have accumulated a large amount of various data in the field of marine geology and the data management tool has been applied in the platform of marine geological information management.
&lt;b&gt;Trends and Topics of Research and Development Related to the Sophistication of Signalling and Telecommunication Systems&lt;/b&gt;

Following recent developments in information and communication technology (ICT), various research and development projects are ongoing around the world to propose new train control technology for safer and more stable transportation services. In particular, 5th generation mobile communication network systems (5G) which will be partially available in 2019 are expected to be used for critical roles in various safety related systems in the future, such as for automatic driving systems for road vehicles and train control systems. This paper outlines recent trends in basic studies for utilizing various communication network techniques including content centric network techniques and 5G systems to sophisticate signalling systems and train control systems. This paper also introduces a future plan for the challenges of the developing autonomous train operation and control system to realize safer, more stable and low-cost train operation services.
Regulating Workers in Federated Learning by Yardstick Competition

Due to the large size of the training data, distributed learning approaches such as federated learning have gained attention recently. However, the convergence rate of distributed learning suffers from heterogeneous worker performance. In this paper, we consider an incentive mechanism for workers to mitigate the delays in completion of each batch. To motivate the workers to perform at their best by assigning higher computational resources to the learning task, we use a yardstick of average desired delay to complete each mini-batch calculation. The rewards are determined by how much each worker deviates from this yardstick. We analytically obtain the optimum equilibrium strategy of the workers as well as the optimal reward function of the model owner that achieves the average desired delay while minimizing the cost of operation. Our numerical results indicate that by adjusting budget parameters, the model owner should judiciously decide on the number of workers due to trade off between the diversity provided by the number of workers and the latency of completing the training.
A Quantum secure sharing protocol for Cloud data based on proxy re-encryption

Abstract A quantum scheme for cloud data sharing based on proxy re-encryption is proposed. The user Alice stores the cipher-text of her data on cloud data center. When Alice wants to share her data with another user Bob, Alice is called the delegator and Bob is called the delegatee. The cloud service provider (called the proxy) can convert the delegator’s cipher-text into the delegatee’s cipher-text without decrypting the former, so that the delegatee can get the plain-text of Alice’s data with his private key. The proxy cannot obtain the plain-text of the user’s data stored on cloud data center. Delegator in the protocol should have the ability of producing Bell states, performing Bell basis and Z-basis measurements, and storing qubits. The quantum requirements for the delegatee are reduced. The delegatee needs to have the ability of reflecting and performing Z-basis measurement. One secret at a time (one-time one-pad) is theoretically implemented, especially when the same data is shared multiple times. The anti-selection plain-text attack security and the anti-selective cipher-text attack security are realized. Fine-granularity secret data sharing is achieved flexibly.
Robust 3D Detection in Traffic Scenario with Tracking-Based Coupling System

Autonomous driving is conducted in complex scenarios, which requires to detect 3D objects in real time scenarios as well as accurately track these 3D objects in order to get such information as location, size, trajectory, velocity. MOT (Multi-Object Tracking) performance is heavily dependent on object detection. Once object detection gives false alarms or missing alarms, the multi-object tracking would be automatically influenced. In this paper, we propose a coupling system which combines 3D object detection and multi-object tracking into one framework. We use the tracked objects as a reference in 3D object detection, in order to locate objects, reduce false or missing alarms in a single frame, and weaken the impact of false and missing alarms on the tracking quality. Our method is evaluated on kitti dataset and is proved effective.
User Experience Study on Touchscreen Technology: A Case Study on Automated Payment Machines

The advancement of technology has introduced the use of an Automated Payment Machine (APM) to offer convenience in paying bills, sending funds, purchasing prepaid cards, and other cash transactions. However, the use of this kind of technology is new to the users which makes it crucial to identify whether the current design fits them or not. In line with this, a usability study has shown that users have encountered design issues while using the system. This paper reports on the usability assessment of an APM which investigates the effects of design factors such as method of data input, button color, button placement, and UI standardization. The experiment results provide substantial insights into the usability design issues of the APM. Such results were assessed by measuring the efficiency, effectiveness, and satisfaction followed by computing for their corresponding Single Usability Metric (SUM) for benchmarking. Hence, from the usability results of the redesigned UI, an improvement on the sigma level has been observed.
Research on multi cloud dynamic secure storage technology

The arrival of the era of big data poses a higher challenge to the secure storage of data. The growing data needs a large number of storage media to store. In order to solve the security problem of data storage, this paper proposes a method of slicing data blocks, encrypting them separately, and finally storing them on multiple clouds. In order to further improve the reliability of data storage, this paper proposes a multi cloud dynamic storage scheduling strategy and local storage optional configuration scheme. At the same time, this paper uses micro service architecture and decentralization strategy to ensure the availability of services. In order to solve the problem of data storage efficiency, the data De duplication strategy is proposed in the multi cloud backup system, and the idea of reference counting and reference reachability is used in the multi cloud storage system. This paper introduces the prototype implementation of multi cloud dynamic storage system, and finally tests and analyzes the system. The experimental results show that the scheme is feasible and can achieve the expected design goals.
Shape Sensing using the ShArc Technique

ShArc is a new, geometric technique for real-time measurement of complex curves. These sensors have a flexible strip that can be dynamically formed into different shapes in a plane. Unlike traditional bend sensors which provide only a single measure of angle, inexpensive ShArc sensors provide detailed information about their precise shape. They can be thought of as "digital calipers for curves". The exhibit includes an explanation of the operating principle and the basic construction. Demonstrations of the sensors in action allow attendees to appreciate how these devices can be applied to understanding human pose and the potential for shape as an expressive input mechanism.