Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Reinforcement Learning-Based Joint Optimization of Delay and Privacy in Multiple-User MEC Systems

Multi-access Edge Computing (MEC) enables mobile users to run various delay-sensitive applications via offloading computation tasks to MEC servers. However, the location privacy and the usage pattern privacy are disclosed to the untrusted MEC servers. The most related work concerning privacy-preserving offloading schemes in MEC either consider an impractical MEC scenario consisting of a single user or take a large amount of computation and communication cost. In this article, we propose a deep reinforcement learning based joint optimization of delay and privacy preservation during offloading for multiple-user wireless powered MEC systems, preserving users’ both location privacy and usage pattern privacy. The main idea is that, to protect both the two kinds of privacy, we propose to disguise users’ offloading decisions and deliberately offloading redundant tasks along with the actual tasks to the MEC servers. On this basis, we further formalize the task offloading as an optimization problem of computation rate and privacy preservation. Then, we design a deep reinforcement learning based offloading algorithm to solve such an non-convex problem, aiming to obtain the better tradeoff between the computation rate and the privacy preservation. Finally, extensive simulation results demonstrate that our algorithm can maintain a high level of computation rate while protecting users’ usage pattern privacy and location privacy, compared with two learning-based methods and two Baselines.
Learnable Empirical Mode Decomposition based on Mathematical Morphology

Empirical mode decomposition (EMD) is a fully data driven method for multiscale decomposing 4 signals into a set of components known as intrinsic mode functions. EMD is based on lower and 5 upper envelopes of the signal in an iterated decomposition scheme. In this paper, we put forward a 6 simple yet eﬀective method to learn EMD from data by means of morphological operators. We pro-7 pose an end-to-end framework by incorporating morphological EMD operators into deeply learned 8 representations, trained using standard backpropagation principle and gradient descent-based opti-9 mization algorithms. Three generalizations of morphological EMD are proposed: a) by varying the 10 family of structuring functions, b) by varying the pair of morphological operators used to calculate 11 the envelopes, and c) by considering a convex sum of envelopes instead of the mean point used 12 in classical EMD. We discuss in particular the invariances that are induced by the morphological 13 EMD representation. Experimental results on supervised classiﬁcation of hyperspectral images by 14 1D convolutional networks demonstrate the interest of our method. 15
Detecting the Speed Change Intention from EEG Signals: From the Offline and Pseudo-Online Analysis to an Online Closed-Loop Validation

Control of assistive devices by voluntary user intention is an underdeveloped topic in the Brain–Machine Interfaces (BMI) literature. In this work, a preliminary real-time BMI for the speed control of an exoskeleton is presented. First, an offline analysis for the selection of the intention patterns based on the optimum features and electrodes is proposed. This is carried out comparing three different classification models: monotonous walk vs. increasing and decreasing change speed intentions, monotonous walk vs. only increasing intention, and monotonous walk vs. only decreasing intention. The results indicate that, among the features tested, the most suitable parameter to represent these models are the Hjorth statistics in alpha and beta frequency bands. The average offline classification accuracy for the offline cross-validation of the three models obtained is 68 ± 11%. This selection is also tested following a pseudo-online analysis, simulating a real-time detection of the subject’s intentions to change speed. The average results indices of the three models during this pseudoanalysis are of a 42% true positive ratio and a false positive rate per minute of 9. Finally, in order to check the viability of the approach with an exoskeleton, a case of study is presented. During the experimental session, the pros and cons of the implementation of a closed-loop control of speed change for the H3 exoskeleton through EEG analysis are commented.
Adaptable software architecture generation using the nfr approach

Adaptability is emerging as an important non-functional requirement (NFR) for software systems. Briefly stated, adaptability is the ability of software systems to withstand changes in their environment. In general, a software system will be adaptable provided its software architecture is itself adaptable in the first place. However, there are very few systematic methods to develop adaptable architectures and almost all of them fail to provide traceability to adaptability requirements and lack ability to represent NFRs, their decompositions, and design artifacts. This thesis uses the NFR Approach to generate adaptable architectures that not only provides a mechanism to trace architectures to requirements but also provides a rich ontology to represent various software artifacts. The thesis first explores the nature of adaptability itself, defines adaptability in a manner consistent with most of the current definitions of adaptability, and explores the constituents of a software architecture such as components, connections, patterns, constraints, styles and rationales. Next, the thesis identifies adaptable constituents of architecture and, to aid in this effort, the Adaptable Software Architecture Framework (ASAF) is proposed that helps in identifying and cataloging adaptable architectural constituents and subsequently searching the catalogs for the most appropriate constituents for a given problem. One of the premises used in this thesis is that using adaptable constituents helps generate adaptable architectures. The ASAF is based on the well-known NFR Framework that helps deal with NFRs at different software development phases including the architecture development phase. Using ASAF, the adaptable architectural constituents are identified and then stored in a knowledge base for later reuse; when required, a search through the knowledge base is made for the most appropriate constituents satisfying the particular requirements and an architecture is developed using these constituents. All these steps together comprise the NFR Approach as applied to adaptable architecture generation. The ASAF also helps in developing a framework for architecture adaptability metrics, called the Process-Oriented Metrics for Software Architecture Adaptability (POMSAA), which generates architectural adaptability metrics in an intuitive manner. POMSAA has been applied to two commercial systems developed at Anritsu Company. In order to validate ASAF, a prototype implementation called the Adaptable Software Architecture Assistant (ASAA) is developed that helps in the semi-automatic generation of adaptable architectures. ASAF and ASAA are used in three different software systems. The results of the application of ASAF and ASAA and the feedback from the industry experts are encouraging and give hope to systematic and semi-automatic generation of adaptable architectures.
Comparison Between 2D and 3D Mapping For Indoor Environments

This paper describes two ways of mapping. The first way is using sonar and the results of it are 2D maps and the second way is using kinect sensor and the results of it are 3D maps. This work involved manually navigation that is operating by using mobile robot with sonar or kinect sensor for mapping. The aim of this paper is to make comparison between the results of mapping by using kinect sensors with results mapping by using sonar. Pioneer 3-dx robot is used in this projects that it contain sonar sensors and the programs that are used for this robot are the Advanced Robotics Interface for Applications (ARIA) that program with C++ package ( Visual C++.Net ), and ARNetworking software is used for setup Wireless TCP/IP Ethernet-to-Serial connection between robot and PC. The programs that are used for kinect sensor are OpenNI/NITE to make it work with pc and also we used Skanect software for building 3d map for environment.
Investigation of Rapid-Prototyping Methods for 3D Printed Power Electronic Module Development

The recent research in wide-bandgap (WBG) power electronic semiconductors has produced a wide variety of device and combinational topologies, such as HFETS, MOSHFETS, and the Cascode Pair. Each variation needs to be tested with certain package criteria (e.g. high voltage SiC devices up to 15kV, high current GaN devices up to 300A, or unprecedented high frequencies). Having a common package is costly and cannot provide an investigation of optimized performance. Hence, use of a rapid prototyping method to print power electronic packages and modules is needed. Also, the continual move to higher frequencies will require greater integration of packaging into the end application, as is presently done with point-of-load converters. The future modules will take on more functional integration, including more mechanical features, which further supports use of printed fabrication technologies. It is not reasonable to assume that a complete module can be directly printed, though most would be; some assembly is requir.
Applied electrokinetics for tissue engineering applications

Tissue engineering could provide an alternative source of transplant tissue regardless of donor supply and with reduced risk of immune rejection. Engineered tissue requires three critical components for successful development: the cells, growth factors, and the scaffold on which they will initially grow. The scaffold acts as a temporary extracellular matrix (ECM) allowing cell attachment and acclimation to the environment prior to synthesis and construction of the cell's native ECM. Prior to cell seeding, the scaffold must be characterized to determine whether or not the pore geometry is conducive to cell implantation. Electrochemical impedance spectroscopy (EIS) provides a unique and effective tool for scaffold evaluation upon fabrication as well as following modification and cell seeding. Chitosan scaffolds were tested with EIS showing good comparative values to more common and proven characterization methods. In addition to characterization, modification may be necessary to improve the cell scaffold interaction. Previous attempts to modify chitosan scaffolds with microparticles during the fabrication have shown that these approaches compromise scaffold integrity; however, particles cannot be effectively forced into the scaffold without damaging it. In light of this difficult modification, electrophoretic particle treatment was implemented. Transport of iron oxide microparticles at low voltage was proven an effective modification method and might be capable of modifying a seeded scaffold.
The efficacy and safety of cariprazine in the early and late stage of schizophrenia: a post hoc analysis of three randomized, placebo-controlled trials

Abstract Background The aim of the post hoc analysis was to better understand the efficacy and safety of cariprazine in patients with schizophrenia for less than 5 years (early stage) and for more than 15 years (late stage). Methods Data from three phase II/III randomized, double-blind, placebo-controlled trials with similar design in patients with acute exacerbation of schizophrenia were pooled and patients with early and late stage of schizophrenia were determined. A mixed-effects model for repeated measures approach was applied and least square (LS) mean changes from baseline to week 6 on the Positive and Negative Syndrome Scale (PANSS) total and factor scores were reported. Descriptive statistics were used for safety analyses including treatment emergent adverse events (TEAEs) and discontinuation rates. Results Overall, 460 patients were identified as being in the early and 414 in the late stage of schizophrenia. The pooled analysis evaluating mean change from baseline to week 6 in the PANSS total score indicated statistically significant difference between cariprazine and placebo in favor of cariprazine in both the early (LS mean difference [LSMD] −7.5 P < .001) and late stage (LSMD −6.7, P < .01) subpopulation. Early stage patients experienced similar amount of TEAEs (CAR 67.3%, PBO 54.1%) as patients in the late stage (CAR 69.6%, PBO 65.6%). Conclusion In conclusion, cariprazine, a potent D3-D2 partial agonist has been found to be safe and effective in the treatment of early and late stage schizophrenia.
Livelihood Challenges and Mitigation Strategies Adopted During COVID-19 Lockdown Period

Over the past century, apart from COVID-19, human civilization has seen five other significant pandemics such as the H1N1 outbreak in 2009, Ebola outbreak in West Africa in 2014, and subsequent outbreak in Congo in 2019, Zika outbreak in 2016, etc. However, of all these outbreaks, perhaps the COVID-19 pandemic is unparalleled due to the global proportions that it has assumed. The severity of the epidemic can be seen in terms of the number of lives lost and the multi-dimensional impact that COVID-19 has had upon the economies of nations and lives of people. Beyond the physical sphere of human life, COVID-19 has also impacted human life's social, mental, and economic aspects. This study was conducted to understand the livelihood challenges faced by the residents of 5 villages in Mulshi taluka during the lockdown period. In-depth interviews were conducted with three respondents from each village (15 respondents). The study drew upon the insights given by key opinion leaders in the towns such as Sarpanch and elected members of the gram panchayat, ASHA workers, ration shop owners etc. Identify the livelihood challenges faced by the people during the lockdown imposed due to COVID-19. Describe the strategies adopted by the people to overcome the challenges to livelihood faced by the people. The residents of the village's studies faced various challenges related to agriculture such as lack of manpower to harvest produce, lack of transportation facilities to transport produce to markets, lack of storage facilities to store agricultural produce etc, loss of employment faced by daily wage laborers due to non-operational status of small businesses during the lockdown period and challenges due to reverse migration.
Development of a Cost-Effective IoT-Based Weather Monitoring System

This work explores the development and deployment of a cost-effective IoT platform to monitor and archival weather data, namely temperature, humidity, atmospheric pressure, and dust particles in a residential area, using open-source technologies. The IoT device sends the data to a remote virtual private server (VPS) over the Internet. A server application runs 24x7 to collect the data and logs it into a database. The necessary steps to set up a VPS server, secure it and install the IoT server application implementing the message queuing telemetry transport protocol are also described. The complete system is verified by real-time implementation using IoT devices, namely NodeMCU ESP 8266 and Raspberry Pi Zero W, along with suitable sensors. The work demonstrates the proof-of-concept feasibility of developing and deploying a scalable weather station from scratch using open-source technologies for faster time to market and the privacy and safety concerns with the end product.
Double-ended Synchronous Reluctance Motor Drive with Extended Constant Power Speed Ratio and Increased Power Factor

Abstract This article proposes a double-ended synchronous reluctance machine drive to increase the constant power speed ratio and the power factor of a synchronous reluctance machine. The proposed double-ended synchronous reluctance machine drive is formed by two inverters, one connected to an energy source and the other one connected to a floating capacitor bank for reactive power compensation. Two control strategies are presented: the unity power factor control can keep the power factor unity seen from the energy source side inverter under all operating conditions; the optimum inverter utilization control can increase torque output ability and the constant power speed ratio while increasing the power factor. Detailed modeling and simulation of the proposed double-ended synchronous reluctance machine drive are presented. Compared to the traditional single-inverter synchronous reluctance machine drive, the proposed drive is able to reduce the conversion ratio of the front-end DC/DC converter and the rating of each switching device. In addition, three-level voltage output of the proposed drive is also capable to reduce total harmonic distortion. In conclusion, the proposed drive is very attractive for applications for which a high power factor or reactive power regulation is required or when a high constant power speed ratio is desired.
Food Waste Management: Does Information Technology Matter in Food Waste?

Casa Basalto is an affordable luxury sustainable hotel located in Pachuca in the state of Hidalgo, Mexico. The hotel hosts Dolina, a traditional Mexican cuisine restaurant that follows the hotel’s green practices. With this case study, students are introduced to an example of green practices in the hospitality industry, and to some models of technology acceptance and the importance of information technology based systems (ITBS). General information about the infrastructure of the hotel and restaurant is provided to familiarize students with the core business concepts of the establishment featured in the case study. In addition, the administrative bodies are explained, and the food waste issue is introduced. The main source of waste for this property is food (approximately 60% of their total waste production). The board of directors is very concerned about this issue; they are worried about the congruence of their brand with sustainability and the possible hidden costs related to sustainability. The general manager of the property has been asked to find a solution to this problem. Introduction of an ITBS called Leanpath is proposed to prevent and manage food waste, but the board of directors is not convinced. They hire a student as a consultant to further research this issue and propose solutions by making a presentation to the board and submitting a brief summary of their findings to the stakeholders’ assembly.
Outdoor Performance and Stability Assessment of Dye-Sensitized Solar Cells (DSSCs)

In this era the requirement for energy is enhancing, therefore, many energy resources are developed among them the emerging third-generation dye-sensitized solar cell is one of the environment-friendly solar cell-based technology. Generally, dye-sensitized solar cells consist of a nanomaterial-based photoanode, dye molecules as an absorber, electrolyte, and counter electrode. In the case of indoor application, this solar cell works easily so this is the characteristics of a dye-sensitized solar cell. Moreover, the outdoor performance of DSSC degrades on exposure to sunlight. Exposure to sunlight increases the temperature of the internal component of DSSC and consequently degradation in device performance. Long-term stability is obtained by the choice of such material where degradation takes place slowly and plastic covers are also coated over DSSC to prevent degradation. The solar response of DSSC towards dye was also mentioned, the higher the percentage of EQE higher the efficiency of the device. In this chapter, the authors discuss the introduction of a solar cell, the working principle of DSSC, and the available research background for outdoor performance and long-term stability with a solar response of device i.e. EQE or IPCE.
Municipal Shared Services and Consolidation : A Public Solutions Handbook

Series Editor's Introduction Marc Holzer Introduction Alexander C. Henderson Part 1: Introduction and Theoretical Considerations 1. Municipal Size, Resources, and Efficiency: Theoretical Bases for Shared Services and Consolidation Mildred E. Warner 2. The Costs of Services Cooperation: A Review of the Literature Christopher V. Hawkins and Jered B. Carr 3. Communities and Culture Sydney Cresswell and Anthony Cresswell Part 2: Municipal Shared Services and Consolidation in Practice 4. Service-Level Consolidation and Sharing Arrangements Michael R. Hattery 5. Lessons Learned from the Nonprofit-Government Relationship for the Municipal Government Manager Lauren Miltenberger 6. Managing Interlocal Contracts and Shared Service Relationships Eric S. Zeemering 7. Do Shared Services Achieve Results? The Performance of Interlocal Agreements Daniel E. Bromberg 8. Toward Interlocal Collaboration: Lessons from a Failed Attempt to Create a Fire Authority William D. Hatley, Richard C. Elling, and Jered B. Carr 9. Mapping the Shared Services Landscape Ricardo S. Morse and Charles R. Abernathy 10. Alternative Service Delivery Arrangements: Creativity and Innovation in Local Government Suzanne Leland and Reid Wodicka Index About the Editor and Contributors
The Contribution of Nasal Murmur to the Perception of Nasal Consonant

Identification of perceptual cues can be very helpful in almost all areas of speech signal processing. Recently, a new methodology called the 3-Dimensional-Deep Search and a visualized intelligible time-frequency computer-based model AI-gram is invented for research on the perceptual cues. Based on this technique, the acoustic cues for stop conso- nants (1), fricative consonants (2) and nasal consonants (3) are successfully found. However, it has limitations on studying the contribution of nasal murmur to the recognition of nasal consonants due to the following reasons: Firstly, it only al- lows the investigating of individual recognition effects along the time, frequency and amplitude axes. The effects of fre- quency and amplitude in a combinatorial way cannot be studied. Secondly, the initial value for the high-pass filter in the filter experiment HL07 (4) is set to be 697 Hz, but the nasal murmur region lies around 250 Hz. The perceptual contribu- tion of nasal murmur to the nasal consonants cannot be assessed. To solve these problems, a new experiment is designed by analyzing experiment data and comparing them with the stimuli under different SNRs via AI-gram. It is revealed that when the primary cue of nasal consonant is clear, which is usually under high SNRs, filtering out nasal murmur does not affect its correct perception. However, when the primary cue is weak usually under low SNRs, nasal murmur has strong complementary effects on the primary cue, and can greatly suppress confusions. This conclusion can be used for noise- robust speech recognition.