Representation Learning for candlesticks time-series data: A contrastive learning approach

In time series analysis, an important question is to distinguish between highly different samples. This question is even more crucial in the financial market, where time series data usually possess stochastic characteristics and are not easily separated from the human perspective. Representation learning, a prominent area of machine learning research, may potentially solve this challenge. In this thesis, the vector representations of time series samples are learned using the contrastive learning approach, a subfield of representation learning. The Siamese network constructed from BiN-DenseNet architecture is used for training. The data is divided into pairs of positive or negative samples and fed to the Siamese network. The goal is to map a time series sample into a new embedding space such that the cosine similarity of similar samples is high. The dataset used in this work is Bitcoin candlestick data. Since Bitcoin is a new asset class, there are limited investigations on Bitcoin's price vector representation. Therefore, this is an opportunity to explore the properties of this asset's price. After obtaining the vector representations of the data, we can use them for improving downstream tasks such as regression or classification. In this thesis, to evaluate the usefulness of our approach, I designed proxy tasks to compare the performance between pre-trained contrastive learning model and baseline non-pre-trained model. The results show that pretraining increases the model's performance by a slight improvement and also eases the training process

A Study of SVC’s Impact Simulation and Analysis for Distance Protection Relay on Transmission Lines

This paper focuses on analyzing and evaluating impact of a Static Var Compensator (SVC) on the measured impedance at distance protection relay location on power transmission lines. The measured impedance at the relay location when a fault occurs on the line is determined by using voltage and current signals from voltage and current transformers at the relay and the type of fault occurred on the line. The MHO characteristic is applied to analyze impact of SVC on the distance protection relay. Based on the theory, the authors in this paper develop a simulation program on Matlab/Simulink software to analyze impact of SVC on the distance protection relay. In the power system model, it is supposed that the SVC is located at mid-point of the transmission line to study impact of SVC on the distance relay. The simulation results show that SVC will impact on the measured impedance at the relay when the fault occurs after the location of the SVC on the power transmission line

SDN Controller Mechanisms for Flexible and Customized Networking

Software-Defined Networking (SDN) is seen as the most promising networking technology today. The spread of a new technology depends on the acceptance of the engineers implementing the networks. Typically, when engineers start the conceptualization of new network devices that work with a new paradigm, and that should provide expected business values, they must identify and utilize technical enablers for the defined business use cases. This paper tries to summarize essential SDN applications and defines the technical enablers for advanced and efficient SDN networking. To this end, we identify the core technical mechanisms, expecting to provide a useful analysis for the design of new SDN networks

Life Cycle Carbon Dioxide Emissions Assessment in the Design Phase: A Case of a Green Building in Vietnam

Buildings are responsible for about 30% of the total CO2 emissions globally. To reduce this amount of CO2, developing green buildings is one of the best approaches. However, this approach is undeveloped in Vietnam due to lacking methods to evaluate design alternatives to meet the criteria of green buildings. This paper presents a life-cycle CO2 analysis (LCCO2A) as a tool to support the decision-making process in the design phase of a 75-year-lifespan green building in Vietnam. The study conducts LCCO2A for two design alternatives (with different bricks usage and glass types) and points out the reasons for the differences. Comparing the first alternative with the second one, the results show slight variations in the amount of CO2 emissions in the erection and demolition phases (with an increase of 21.81 tons and a reduction of 106.1 tons of CO2eq, respectively), and a significant difference in the operation phase (10,631.52 tons of CO2eq or 58.34% reduction). For the whole life-cycle, the second design scenario, which uses “greener” materials shows a great decrease of 10,715.81 tons of CO2eq or 37.54%. By comparing its results with the findings in the literature, this research proves the environmental dominance of green buildings over other building categories

Customer Co-creation through the Lens of Service-dominant Logic: A literature Review

The proliferation of the service sector in the age of big data highlights the role of customers as co-creators for business value. Customer interactions on digital platforms make a significant contribution to the vast amount of big data. Considering the lack of systematic and comprehensive studies on this research stream, the objective of the paper is to conduct a concept-centric literature review on customer co-creation from the lens of the service-dominant logic and guide future research. The paper systematically synthesizes and categorizes 50 articles by the concept matrix to reveal the interrelationships among them. The result of the paper provides a holistic overview of value, resources, and mechanisms relevant to customer co-creation. Concrete ideas for future research directions are also proposed for enriching the academic literature and promoting practical implications. The paper holds important implications for accelerating customer co-creation for service providers to achieve big-data-driven competitive advantages

A Service-based Model for Customer Intelligence in the Age of Big Data

The dominance of the service sector in today’s economy gives prominence to customer intelligence as a means for enterprises to provide optimal service. In fact, the revolution of big data has generated a vast amount of customer data and reshaped the dimensions of science, management, and engineering within enterprises. The big data era also acknowledges the role of customers as value co-creators. Therefore, the objective of this paper is to propose a service-based customer intelligence model, hereafter called SBCI (Service-based Customer Intelligence) model, to guide the development and application of customer intelligence. Laid the groundwork upon the service science, the model is proposed with three levels: i) the network of service systems level for customer value co-creation, ii) the service system level for the science, management, and engineering dimensions, and iii) the service level for customer intelligence services

Synchronization controller for a 3-RRR parallel manipulator

A 3-RRR parallel manipulator has been well-known as a closed-loop kinematic chain mechanism in which the end-effector generally a moving platform is connected to the base by several independent actuators. Performance of the robot is decided by performances of the component actuators which are independently driven by tracking controllers without acknowledging information from each other. The platform performance is degraded if any actuator could not be driven well. Therefore, this paper aims to develop an advanced synchronization (SYNC) controller for position tracking of a 3-RRR parallel robot using three DC motor-driven actuators. The proposed control scheme consists of three sliding mode controllers (SMC) to drive the actuators and a supervisory controller named PID-neural network controller (PIDNNC) to compensate the synchronization errors due to system nonlinearities, uncertainties and external disturbances. A Lyapunov stability condition is added to the PIDNNC training mechanism to ensure the robust tracking performance of the manipulator. Numerical simulations have been performed under different working conditions to demonstrate the effectiveness of the suggested control approach