Miracle-dz/UniFAR-FTUs huggingface dataset:
Organizing tactics based optimization theory

This paper proposed a new general framework for intelligent optimization based on organizing tactics rather than probability rules. Compared with the existing intelligent optimization algorithms, like Particle Swarm Optimization, this framework has several significant advantages. First, the “intelligence” does not depend on the probability rules of the operators, but their organizing tactics. Thus there are no probability equations that need to be updated, and involved control parameters are fewer, so it is easier to use in practice. Second, synergistic coexistence and automatic balance of the exploration and the exploitation are achieved in the running. Third, population diversity has been kept during the running. Fourth, most useless and ineffective repetitious operations are avoided, and thus the needed consumption of storage space and running time are lessened largely.
Can a reconfigurable architecture beat ASIC as a CNN accelerator?

To exploit the high accuracy, inherent redundancy, and embarrassingly parallel nature of Convolutional Neural Networks (CNN), for intelligent embedded systems, many dedicated CNN accelerators have been presented. These accelerators are optimized to employ compression, tiling, and layer merging for a specific data flow/parallelism pattern. However, the dimension of a CNN differ widely from one application to another (and also from one layer to another). Therefore, the optimal parallelism and data flow pattern also differs significantly in different CNN layers. An efficient accelerator should have flexibility to not only efficiently support different data flow patterns but also to interleave and cascade them. To achieve this ability requires configuration overheads. This paper analyzes whether the reconfiguration overheads for interleaving and cascading multiple data flow and parallelism patterns are justified. To answer this question, we first design a reconfigurable CNN accelerator, called ReCon. ReCon is the compared with state-of-the-art accelerators. Post-layout synthesis results reveal that ReCon provides up to 2.2X higher throughput and up to 2.3X better energy efficiency at the cost of 26–35% additional area.
Whiskers: Exploring the Use of Ultrasonic Haptic Cues on the Face

Haptic cues are a valuable feedback mechanism for smart glasses. Prior work has shown how they can support navigation, deliver notifications and cue targets. However, a focus on actuation technologies such as mechanical tactors or fans has restricted the scope of research to a small number of cues presented at fixed locations. To move beyond this limitation, we explore perception of in-air ultrasonic haptic cues on the face. We present two studies examining the fundamental properties of localization, duration and movement perception on three facial sites suitable for use with glasses: the cheek, the center of the forehead, and above the eyebrow. The center of the forehead led to optimal performance with a localization error of 3.77mm and accurate duration (80%) and movement perception (87%). We apply these findings in a study delivering eight different ultrasonic notifications and report mean recognition rates of up to 92.4% (peak: 98.6%). We close with design recommendations for ultrasonic haptic cues on the face.
Understanding Users' Capability to Transfer Information between Mixed and Virtual Reality: Position Estimation across Modalities and Perspectives

Mixed Reality systems combine physical and digital worlds, with great potential for the future of HCI. It is possible to design systems that support flexible degrees of virtuality by combining complementary technologies. In order for such systems to succeed, users must be able to create unified mental models out of heterogeneous representations. In this paper, we present two studies focusing on the users' accuracy on heterogeneous systems using Spatial Augmented Reality (SAR) and immersive Virtual Reality (VR) displays, and combining viewpoints (egocentric and exocentric). The results show robust estimation capabilities across conditions and viewpoints.
Diagnostic Accuracy of Whole-Brain Computed Tomographic Perfusion Imaging in Small-Volume Infarctions

PurposeThe aims of this study were to determine the diagnostic accuracy of whole-brain computed tomographic perfusion (WB-CTP) in small ischemic brain infarctions and to identify factors influencing the detection rate. Materials and MethodsOut of a retrospective cohort of 1380 subjects who underwent initial WB-CTP because of suspected stroke, we selected all patients with a supratentorial magnetic resonance imaging-confirmed ischemic infarction with a volume of 8 mL or less. Infratentorial lesions were excluded. The study was designed as a case-control study with a ratio of cases to controls with no infarction in follow-up magnetic resonance imaging of 1:3. Two blinded readers independently evaluated 4 different computed tomographic perfusion parameter data sets per subject with respect to the presence and localization of a perfusion deficit. ResultsA total of 113 subjects met the inclusion criteria for the patient group. Overall, WB-CTP reached a sensitivity of 43.4% and a specificity of 92.9%. Among these, cortical infarctions were detected in 31 (69%) of 49 cases, whereas subcortical infarctions were detected only in 18 (28%) of 64 cases (P < 0.05). Mean final infarction diameter (17.3 mm) and volume (1.9 mL) of infarctions detected on CTP were significantly larger than those of infarctions not detected (12.4 mm and 0.8 mL, respectively; P < 0.001). Time from symptom onset did not differ significantly between infarctions that were detected or those that were not (204 vs 189 minutes; P = 0.75). ConclusionsThe detection rate of WB-CTP in small infarctions highly depends on infarction localization and final size, whereas time from symptom onset does not seem to influence diagnostic accuracy.
Jetto: Using Lateral Force Feedback for Smartwatch Interactions

Interacting with media and games is a challenging user experience on smartwatches due to their small screens. We propose using lateral force feedback to enhance these experiences. When virtual objects on the smartwatch display visually collide or push the edge of the screen, we add haptic feedback so that the user also feels the impact. This addition creates the illusion of a virtual object that is physically hitting or pushing the smartwatch, from within the device itself. Using this approach, we extend virtual space and scenes into a 2D physical space. To create realistic lateral force feedback, we first examined the minimum change in force magnitude that is detectable by users in different directions and weight levels, finding an average JND of 49% across all tested conditions, with no significant effect of weight and force direction. We then developed a proof-of-concept hardware prototype called Jetto and demonstrated its unique capabilities through a set of impact-enhanced videos and games. Our preliminary user evaluations indicated the concept was welcomed and is regarded as a worthwhile addition to smartwatch output and media experiences.
Combined modified P&O algorithm with improved direct power control method applied to single-stage three-phase grid-connected PV system

In the recent years, with development of power electronics and semiconductor technologies, grid-connected photovoltaic systems have gained a high significance. This systems can be classified to single-stage and two-stage power conversion systems. In the single-stage systems, the DC/DC converter is removed and efficiency is improved as well as cost reduction of the system. However, both of maximum power point tracking and DC/AC conversion must be implemented by inverter in this systems. Therefore, applying the appropriate control method for inverter is so important. Consequently, firstly, this paper proposes a modified MPP tracking algorithm based on the power perturbation instead of voltage or current perturbation to speed up the dynamic response of the proposed control system. In addition, considering several benefits of sliding mode control in control of non-linear systems, an improved direct power control method based on sliding mode control is also proposed to be used to control the injected active and reactive powers to the grid. Since power control is the main goal of grid connected PV systems, removing any internal control loops or interface variables, the proposed control system shows fast dynamic response with satisfied steady state performance.
Regulation of photoperiodic flowering by Arabidopsis photoreceptors

Photoperiodism is a day-length-dependent seasonal change of physiological or developmental activities that is widely found in plants and animals. Photoperiodic flowering in plants is regulated by photosensory receptors including the red/far-red light-receptor phytochromes and the blue/UV-A light-receptor cryptochromes. However, the molecular mechanisms underlying the specific roles of individual photoreceptors have remained poorly understood. Here, we report a study of the day-length-dependent response of cryptochrome 2 (cry2) and phytochrome A (phyA) and their role as day-length sensors in Arabidopsis. The protein abundance of cry2 and phyA showed a diurnal rhythm in plants grown in short-day but not in plants grown in long-day. The short-day-specific diurnal rhythm of cry2 is determined primarily by blue light-dependent cry2 turnover. Consistent with a proposition that cry2 and phyA are the major day-length sensors in Arabidopsis, we show that phyA mediates far-red light promotion of flowering with modes of action similar to that of cry2. Based on these results and a finding that the photoperiodic responsiveness of plants depends on light quality, a model is proposed to explain how individual phytochromes and cryptochromes work together to confer photoperiodic responsiveness in Arabidopsis.
Keys in the Clouds: Auditable Multi-device Access to Cryptographic Credentials

Personal cryptographic keys are the foundation of many secure services, but storing these keys securely is a challenge, especially if they are used from multiple devices. Storing keys in a centralized location, like an Internet-accessible server, raises serious security concerns (e.g. server compromise). Hardware-based Trusted Execution Environments (TEEs) are a well-known solution for protecting sensitive data in untrusted environments, and are now becoming available on commodity server platforms. Although the idea of protecting keys using a server-side TEE is straight-forward, in this paper we validate this approach and show that it enables new desirable functionality. We describe the design, implementation, and evaluation of a TEE-based Cloud Key Store (CKS), an online service for securely generating, storing, and using personal cryptographic keys. Using remote attestation, users receive strong assurance about the behaviour of the CKS, and can authenticate themselves using passwords while avoiding typical risks of password-based authentication like password theft or phishing. In addition, this design allows users to i) define policy-based access controls for keys; ii) delegate keys to other CKS users for a specified time and/or a limited number of uses; and iii) audit all key usages via a secure audit log. We have implemented a proof of concept CKS using Intel SGX and integrated this into GnuPG on Linux and OpenKeychain on Android. Our CKS implementation performs approximately 6,000 signature operations per second on a single desktop PC. The latency is in the same order of magnitude as using locally-stored keys, and 20x faster than smart cards.
Twelve tips for enhancing student engagement

Abstract Student engagement refers to a broad range of activities where students participate in management, education, research, and community activities within their institutions. It is a mutually beneficial collaborative approach between students and their institutions. This article provides practical advice for the implementation or further development of student engagement at medical, dental, and veterinary schools. The tips provided are based on the experiences of a group of universities recently recognized for best practice in student engagement, and are supported by evidence from the literature. The tips cover overarching themes which include the creation of an institutional culture and formal framework for student engagement, and maximize communication routes between students with peers and faculty. Tips are for specific areas of active student engagement, covering curriculum design and development, peer teaching, governance processes, research activities, peer support programs, and interaction with the local community.
Everything We Do, Everything We Press: Data-Driven Remote Performance Management in a Mobile Workplace

This paper examines how data-driven performance monitoring technologies affect the work of telecommunications field engineers. As a mobile workforce, this occupational group rely on an array of smartphone applications to plan, manage and report on their jobs, and to liaise remotely with managers and colleagues. These technologies intend to help field engineers be more productive and have greater control over their work; however they also gather data related to the quantity and effectiveness of their labor. We conducted a qualitative study examining engineers' experiences of these systems. Our findings suggest they simultaneously enhance worker autonomy, support co-ordination with and monitoring of colleagues, but promote anxieties around productivity and the interpretation of data by management. We discuss the implications of data-driven performance management technologies on worker agency, and examine the consequences of such systems in an era of quantified workplaces.
Synthesis of highly nanoporous YBO3 architecture via a co-precipitation approach and tunable luminescent properties.

We present a simple co-precipitation method to prepare highly nanoporous YBO(3) architecture using NaBO(3) · 4H(2)O as a boric source and 600°C as the annealing temperature. The reaction was carried out under an aqueous condition without any organic solvent, surfactant, or catalysts. The prepared samples were characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The photoluminescence of doped-nanoporous YBO(3):Eu(3+) was further investigated. It is expected that highly nanoporous YBO(3) architecture can be an ideal candidate for applications in catalysis, adsorption, and optoelectronic devices.
The influence of organizational structure on software quality

Often software systems are developed by organizations consisting of many teams of individuals working together. Brooks states in the Mythical Man Month book that product quality is strongly affected by organization structure. Unfortunately there has been little empirical evidence to date to substantiate this assertion. In this paper we present a metric scheme to quantify organizational complexity, in relation to the product development process to identify if the metrics impact failure-proneness. In our case study, the organizational metrics when applied to data from Windows Vista were statistically significant predictors of failure-proneness. The precision and recall measures for identifying failure-prone binaries, using the organizational metrics, was significantly higher than using traditional metrics like churn, complexity, coverage, dependencies, and pre-release bug measures that have been used to date to predict failure-proneness. Our results provide empirical evidence that the organizational metrics are related to, and are effective predictors of failure-proneness.
Interferon γ improves the vaccination potential of oncolytic parvovirus H-1PV for the treatment of peritoneal carcinomatosis in pancreatic cancer

Oncolytic viruses with their capacity to specifically replicate in and kill tumor cells emerged as a novel class of cancer therapeutics. Rat oncolytic parvovirus (H-1PV) was used to treat different types of cancer in preclinical settings and was lately successfully combined with standard gemcitabine chemotherapy in treating pancreatic ductal adenocarcinoma (PDAC) in rats. Our previous work showed that the immune system and particularly the release of interferon-gamma (IFNγ) seem to mediate the anticancer effect of H-1PV in that model. Therefore, we reasoned that the therapeutic properties of H-1PV can be boosted with IFNγ for the treatment of late incurable stages of PDAC like peritoneal carcinomatosis. Rats bearing established orthotopic pancreatic carcinomas with peritoneal metastases were treated with a single intratumoral (i.t.) or intraperitoneal (i.p.) injection of 5x108 plaque forming units of H-1PV with or without concomitant IFNγ application. Intratumoral injection proved to be more effective than the intraperitoneal route in controlling the growth of both the primary pancreatic tumors and peritoneal carcinomatosis, accompanied by migration of virus from primary to metastatic deposits. Concomitant i.p. treatment of H-1PV with recIFNγ resulted in improved therapeutic effect yielding an extended animal survival, compared with i.p. treatment with H-1PV alone. IFNγ application enhanced the H-1PV-induced peritoneal macrophage and splenocyte responses against tumor cells while causing a significant reduction in the titers of H1-PV-neutralising antibodies in ascitic fluid. Thus, IFNγ co-application together with H-1PV might be considered as a novel therapeutic option to improve the survival of PDAC patients with peritoneal carcinomatosis.
A Data Preprocessing Technique for Gesture Recognition Based on Extended-Kalman-Filter

Gesture recognition derived from skeletal data plays an important role in our TaiChi rehabilitation training and evaluation system. This paper investigates an extended-Kalman-filter-based preprocessing method to fix those incomplete and inconsistent kinematic sensory data. To evaluate the performance of preprocessing, several representative classifiers such as support-vector-machine (SVM), decision tree, and K-nearest neighbor (KNN) are also employed and investigated in gesture recognition. The addressed work is critically assessed using two open-access Kinect-oriented data sets and one Tai-Chi kinematic data set as benchmark. The experimental results show that the addressed preprocessing technique can improve the gesture recognition rate, and that among the classifiers addressed in this work, SVM has superior performance than others.
Tinnitus Treatment with Oxytocin: A Pilot Study

Introduction Tinnitus is the perception of sound in the absence of an external stimulus. It is a frequent condition for which there is as yet no pharmacological treatment approved. Auditory and non-auditory pathways are involved in tinnitus’ pathophysiology. Oxytocin is a neurohormone and eventual neurotransmitter that plays a complex role in social cognition and behavior. Objective To evaluate the potential of oxytocin as a tinnitus treatment. Study design Two studies were performed. Study 1 was a long-term open pilot study, while study 2 investigated short-term effects with a double-blinded placebo-controlled cross-over study. Setting Ambulatory ENT care. Subjects and method In study 1, 15 patients were investigated over a 10-week period in an open pilot study. In study 2, 16 patients were included in a placebo-controlled crossover trial to investigate short-term effects following a single dose. Results For the long-term study (study 1), analysis of variance revealed a significant decrease in tinnitus sensation, both for the Tinnitus Handicap Inventory and Clinical Global Impression (CGI). Also, the short-term effects in study 2 revealed a significant reduction of tinnitus because of the oxytocin nasal spray as measured with the Visual Analog Scale and the CGI Scale. Conclusion These preliminary studies demonstrated that oxytocin may represent a helpful tool for treating tinnitus and further larger controlled studies are warranted.
Algorithmic Challenges in Web Search Engines

In this paper, we describe six algorithmic problems that arise in web search engines and that are not or only partially solved: (1) Uniformly sampling of web pages; (2) modeling the web graph; (3) finding duplicate hosts; (4) finding top gainers and losers in data streams; (5) finding large dense bipartite graphs; and (6) understanding how eigenvectors partition the web.
Split Converter-Fed SRM Drive for Flexible Charging in EV/HEV Applications

Electric vehicles (EVs) and hybrid EVs are the way forward for green transportation and for establishing low-carbon economy. This paper presents a split converter-fed four-phase switched reluctance motor (SRM) drive to realize flexible integrated charging functions (dc and ac sources). The machine is featured with a central-tapped winding node, eight stator slots, and six rotor poles (8/6). In the driving mode, the developed topology has the same characteristics as the traditional asymmetric bridge topology but better fault tolerance. The proposed system supports battery energy balance and on-board dc and ac charging. When connecting with an ac power grid, the proposed topology has a merit of the multilevel converter; the charging current control can be achieved by the improved hysteresis control. The energy flow between the two batteries is balanced by the hysteresis control based on their state-of-charge conditions. Simulation results in MATLAB/Simulink and experiments on a 150-W prototype SRM validate the effectiveness of the proposed technologies, which may provide a solution to EV charging issues associated with significant infrastructure requirements.
A Model Driven based Aspect Oriented Model Weaving Framework for Distributed System

MDA and AOP techniques are used in combination with each other in software design. In MDA, one can use AOP's aspect-oriented concept to create a model so as to separate the concerns. The aspects in AOP can be used as models in MDA to be transformed, checked, queried and maintained. The model-driven based aspect-oriented model weaving framework (MAMW) is a form of model transformation, which separates concerns and improves the abstract level by modeling the crosscutting in aspect-orientation to aspect model. The woven model Mw can be mapped to xKL language and interpreted, at the same time it can be used as metamodel to create object model Mwo, and then the object model Mwo can be interpreted to executable objects by an interpreter, finally the executable objects are used to provide external services through socket port. MAMW improved the abstract level of model transformation, and it supports the newest model transformation criterion QVT. It eliminates the variety of model transformation technique to some extent and at the same time it is simple, well regulated and executable.
Developing a multi agent system model in GAIA for court case management system as a case study and providing an extension to GAIA

MAS Methodologies have evolved in the past decade with a growth curve that has segregated them into specific arena of their own expertise. Each methodology is applicable for a selected group of projects. These methodologies include Prometheus, MaSE, Tropos, Gaia and many more. Each comes with its own strengths and weaknesses. In this paper, the authors are trying to provide an extension to the Gaia methodology which is outstanding in early requirements analysis and design. The only limitation comes when we need to share goals between agents. The goals are also not identified which poses problems in mapping them to Roles and Agents. As an extension to Gaia, the authors have modified the model of Gaia by introducing Goal Model by deriving goals from the organization and sub-organization and fitting them before mapping them onto the roles. The authors have taken the “Legal Semantic Web” as a case study.