Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method and Exoskeletons for Whole-Arm Gravity Compensation

We present a new method for providing gravity compensation to a human or robot arm. This method allows the arm to be supported in any orientation, and also allows for the support of a load held in the hand. We accomplish this with a pantograph, whereby one portion of the linkage duplicates the arm’s geometry, and another portion of the linkage contains a scaled copy of the arm. Forces applied to the scaled copy are transferred back to the original arm. We implement these concepts with two exoskeletons: the Panto-Arm Exo, a low-profile exoskeleton that supports the arm’s weight, and the Panto-Tool Exo that supports a mass held in the hand. We present two linkages used for pantographs, and analyze how different linkage dimensions and their positioning relative to the body affect the forces providing gravity compensation. We also measured the effect of the Panto-Arm exoskeleton on fourteen subjects’ arm muscles during static holding tasks and a task in which subjects drew horizontal and vertical lines on a whiteboard. Even though the Panto-Arm Exo linkage geometry and forces were not optimized, it reduced the Mid Deltoid by 33-43% and the Biceps Brachii by up to 52% in several arm postures.
On a Temporal Logic of Prefixes and Infixes

A classic result by Stockmeyer [16] gives a non-elementary lower bound to the emptiness problem for star-free generalized regular expressions. This result is intimately connected to the satisﬁability problem for interval temporal logic, notably for formulas that make use of the so-called chop operator. Such an operator can indeed be interpreted as the inverse of the concatenation operation on regular languages, and this correspondence enables reductions between non-emptiness of star-free generalized regular expressions and satisﬁability of formulas of the interval temporal logic of the chop operator under the homogeneity assumption [5]. In this paper, we study the complexity of the satisﬁability problem for a suitable weakening of the chop interval temporal logic, that can be equivalently viewed as a fragment of Halpern and Shoham interval logic featuring the operators B , for “begins”, corresponding to the preﬁx relation on pairs of intervals, and D , for “during”, corresponding to the inﬁx relation. The homogeneous models of the considered logic naturally correspond to languages deﬁned by restricted forms of regular expressions, that use union, complementation, and the inverses of the preﬁx and inﬁx relations.
High Enhancement Strain Sensor Based on Vernier Effect Using 2-Fiber Loop Mirrors

In this letter, a strain sensor with high sensitivity enhancement using a special case of Vernier effect is presented. The sensor configuration is composed of two-fiber loop mirrors in a cascaded configuration with opposite strain responses when individually characterized. Thus, the enhanced Vernier effect is explored, which is the most sensitive of three possible cases Vernier effect. Here, the Vernier response depends on the difference between the sensitivities of each Hi-Bi optical fiber. In addition to this, the fundamental and the first harmonic were also explored. The results obtained are a strain sensitivity of (13.3 ± 0.3) pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> for the carrier, (80.0 ± 0.3) pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> or the Vernier envelope of the fundamental case and (120 ± 1) pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> for the Vernier envelope of the first harmonic. The first harmonic could achieve a magnification factor of 8. Considering that the optical interrogation system allows a minimum resolution of 0.02 nm, the minimum measurement step achievable is <inline-formula> <tex-math notation="LaTeX">$0.2~\mu \varepsilon $ </tex-math></inline-formula>. This work proves the possibility of applying the concept of enhanced Vernier effect to fiber loop mirrors, obtaining higher sensitivity than a standard fiber loop mirror alone. Besides, the sensitivity can be increased through the usage of harmonics of the Vernier effect. Moreover, the use of large interferometers allows a better discretization of the envelope, which implies a greater ease of analysis.
Reconciling Resource-Based View and Competency-Based View of Start-Up Formation in Universities

Given the industrial and economic importance of start-up formation in universities, researchers have adopted a variety of theoretical approaches, including embeddedness theory, ecosystem theory, resource-based view (RBV), and competency-based view (CBV). Despite the benefits of diversity, elucidating the conceptual coherence among different theories is urgent to advance our understanding of academic entrepreneurship. Although both embeddedness and ecosystem theory stress the environmental importance of students’ start-ups, the RBV and CBV studies have emphasized the different dimensions of the ecosystem components without considering coherence and interactions between them. The goal of this research is to reconcile the RBV and CBV by not only comparing their relative strengths but also elucidating their reciprocal interactions in an analytical framework. Based on a national survey data of 136 universities in South Korea, this research first investigates the positive impact of the RBV variables on the venture creation, such as university technological assets, incubator administration, and venture funds, and the CBV variables, including entrepreneurship education programs and student clubs. Second, by comparing the relative influence, this research shows that the effects of the CBV variables on start-up formation are stronger than that of the RBV variables. Third, the analyses of interaction effect show that the incubator administration strengthens the positive impact of education programs on the start-up formation, while the venture funds substitute the effect of education programs on academic entrepreneurship.
Obstructive Sleep Apnea and Chronic Lung Disease

Idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are typical chronic lung diseases that progress slowly in the elderly. Recent years have seen the development of new anti-fibrotic agents and ongoing development of inhalers, and there have been improvements in the control of both diseases. However, the mortality and clinical outcomes of IPF and COPD remain of concern, and the burden of illness and economic cost to patients and society remain high [1,2]. IPF is characterized primarily by the restriction of pulmonary function due to fibrosis of the interstitial area, while COPD is characterized by the obstruction of pulmonary function due to an emphysematous change in alveolar and bronchiolar inflammation. However, the two diseases have several commonalities. Systemic inflammation Obstructive Sleep Apnea and Chronic Lung Disease
Modular Kinematic Modelling of Articulated Buses

Development of compact and easy to use mathematical models of articulated vehicles for the motion planning, control, and localization purposes becomes more and more important in the era of intelligent transportation systems, especially when there exists a need of reliable predictions of motion for multi-body (semi-)automated freight and public transportation vehicles of various kinematic structures. We propose a modular algorithmic approach to kinematic modelling of nonholonomic (multi-)articulated buses, including the N-trailer vehicles as a special case, comprising a car-like prime-mover passively interconnected with arbitrary number of segments (wagons/trailers) equipped with fixed or steerable wheels, and with various locus of a driving axle in a kinematic chain. Kinematic models are valid under an assumption of a pure rolling of all the vehicle wheels (no skid/slip motion), which is practically justified for the low-speed maneuvering conditions. The proposed approach leads to compact nonlinear models which, thanks to their modular construction, preserve clear geometrical interpretation of velocity couplings between the vehicle segments. Derivations of kinematic models for popular structures of articulated and bi-articulated urban buses are presented for various driving-axle locus and steering capabilities. Experimental model validation, conducted with a full-scale wagon-driven articulated bus, illustrates utility of the approach.
The finite element model and analyses of a three-phase 12/8 pole Switched Reluctance Motor

The paper presents simulation model, realized by the finite element method of a three-phase 12/8 switched reluctance motor (SRM) in the software simulator Infolytica MotorSolve. The highly non-linear characteristics of this type of motor complicate the analytical methods for the analysis. For this reason, the numerical method (FEA) is used to obtain accurate characteristics of the basic parameters of the motor. The physical dimensions of the machine are used to obtain the model. On the basis of the FEA model, the characteristics of a phase inductance, a torque and a flux-linkage are obtained, which are the main characteristics of SRM, and have a significant impact on the operation of the motor. The obtained simulation results for the different characteristics of the SRM are determined at different positions of the rotor and excitation currents of the phase windings.
Can Information Security, Privacy and Satisfaction Influence The E-Commerce Consumer Trust?

E-commerce must face the risk of cybercrimes such as phishing and cracking that can cause complaints and reports from consumers who suffer losses due to insecurity of their information and privacy. The purpose of this study is to investigate the effect of information security and privacy on the level of customer satisfaction and trust in e-commerce. Data were collected using questionnaires distributed to 100 Bukalapak users as e-commerce users. In addition to using the PLS-SEM method to explain the relationship between constructs, this study also employs the Importance and Performance Matrix Analysis (IPMA) method to find out how important and how much influence the indicator variable has on latent variables. The result of this study shows that consumer trust can be achieved by consumer satisfaction and privacy. On the other hand, consumer satisfaction is influenced by information security and privacy. This research is expected to contribute insights to e-commerce players, especially Bukalapak, to focus on improving the privacy of their consumers. Future research can apply the same model to e-commerce players other than Bukalapak.
A Novel Double Co-Transformation for a Simple and Memory Efficient Logarithmic Number System

To date, co-transformation architecture is typically used in resolving the singularity issue in the logarithmic number system (LNS). The co-transformation was first introduced by Coleman, by using a rule of sign(r1) ≠ sign(r2) which translate the singularity into an argument that can be stored in two identical look-up tables (LUTs) with size of 2k. Recently, a portable 32-bit chipset preferred a small LUT, hitherto a co-transformation architecture is rearranged. This paper presents a novel double co-transformation, by means of first-order co-transformation architecture that covers −0.5 < r < 0 region is extended to r > −1 to replace the triumvirate F, D and E tables occupy by the interpolator. The accuracy settings at the co-transformation is compromised with the worst case error of 0.5 ulp. The outcome revealed a double co-transformation with Lagrange interpolator shows a decline in the total bit by 13% compared to European Logarithmic Microprocessor (ELM). With a simple architecture, the proposed double co-transformation is a promise for a fast LNS system.
Opinion Mining Model System For Indonesian Non Profit Organization Using Multinomial Naive Bayes Algorithm

Instagram is one of the popular social media being used to publish information and gain awareness of Nonprofit organization (NPOs). In the process of sounding through social media, the engagement formed in the comment section also needs to be monitored to help NPOs assess the effectiveness of using Instagram as a tool to introduce their program. Moreover, to built engagement with their audience and extract knowledge of the potential donor and volunteer. Unfortunately, this knowledge is still difficult to obtain. One of the challenges in this field is how to find relationship between content features and NPO audience engagement. The purpose of this research is to study, analyze and design a model of Indonesian NPOs opinion mining from Instagram dataset, specifically for NPOs that concern with Indonesian child welfare. The proposed model also designed to obtain 10 categories to represent audience opinion, which are gratitude, appreciation, encouragement wishes, empathy, suggesting, sharing, need more information, behavioral intention, engagement, agreement, and disagreement. The proposed model adopts Binarized Multinomial Naϊve Bayes algorithm for categorizing caption’s aspects and Normal Multinomial Naϊve Bayes for categorizing comment’s aspect. From the captions and comments collected from four major Indonesian NPOs with children welfare programs for six months, 70% were used as training data and 30% were used as testing data. Based on the testing result, the proposed model proved successfully categorize the opinion, with average precision value 96.67% and recall 96.4% for categorizing caption aspects, and average precision value 83.3% and recall 80.3% for categorizing comment aspects.
Low Complexity Quantization in High Efficiency Video Coding

The rate-distortion optimized quantization (RDOQ) provides an excellent trade-off between rate and distortion in High Efficiency Video Coding (HEVC), leading to inspiring improvement in terms of rate-distortion performance. However, its heavy use imposes high complexity on the encoder in real-world video compression applications. In this paper, we provide a comprehensive review on low complexity quantization techniques in HEVC, including both fast RDOQ and all-zero block detection. In particular, the fast RDOQ relies on rate and distortion models for rate-distortion cost estimation, such that the most appropriate quantized coefficient is selected in a low complexity way. All-zero block detection infers the all-zero block by skipping transform and quantization, in an effort to further reduce the complexity. The relationship between the two techniques is also discussed, and moreover, we also envision the future design of low complexity quantization in the upcoming Versatile Video Coding (VVC) standard.
Multi-Running State Health Assessment of Wind Turbines Drive System Based on BiLSTM and GMM

With the continuous elevation of demand for large-scale wind turbines and operation & maintenance cost an increasing interest has been rapidly generated on CM (Condition Monitoring) system. The main components of wind turbines are the focus on all CM as they overall lead to high repair costs and equipment downtime. Thus, it is difficult to make comprehensive assessment in the assessment. In the present study, intelligent machine learning algorithms are adopted to mine SCADA (Supervisory Control and Data Acquisition) system data of WTs (wind turbines). Besides, based on bidirectional long short-term memory (BiLSTM) neural networks and gaussian mixture model (GMM) algorithm, this study developed a multi-running state health assessment model for the drive system of wind turbines. First, the state-identification model is built with health data to overcome the effect of the time-varying characteristics of running environment and alterations of running condition during the assessment. Then, in each state, the BiLSTM algorithm is adopted to extract the residual set of valid state variables, and the GMM algorithm is employed to accurately fit the distribution of residual set. The multi-running state benchmark model based on BiLSTM and GMM is built. Subsequently, the drive system of wind turbines health degree is calculated by health index. Lastly, based on multiple driving system faults data of a wind turbine, the feasibility and validity of the model are verified.
COST TRENDS OF MBR SYSTEMS FOR MUNICIPAL WASTEWATER TREATMENT

Cost estimates were developed for full-scale (1 and 5 MGD) MBR facilities designed to treat municipal wastewater. These estimates included both capital and operational / maintenance (O&M) costs related to the headworks, MBR process (biological process and membrane system), chlorine disinfection and effluent storage. The costs associated with the membrane systems were developed from budgetary cost quotes provided by suppliers which have recently introduced newly developed MBR products into the U.S. market. Each of these products offer unique design features aimed towards the reduction of capital and/or operation costs. All other costs associated with the MBR facilities were developed from previous conceptual designs performed by the project team and updated using current standard engineering cost indices. Total estimated capital plus annual costs ($/1000 gal treated) for the newly developed MBR systems (1-MGD capacity) ranged from $2.02-$2.58. The range in costs directly reflects the range in membrane system and membrane replacement costs provided by the participating MBR suppliers. Evaluation of cost estimates for 1 and 5 MGD capacity MBR facilities revealed an average economy of scale of 16.5% for the non-membrane components (i.e. headworks, process basins, buildings etc.) of the MBR facility and 23.6% for the membrane system only. Comparison of the current MBR cost estimates to historical costs estimates (adjusted for inflation) suggest that a steady decrease has occurred in the membrane system cost of MBRs between 2000-2006. However, an opposite trend was observed over the same time period for costs associated with the non-membrane components of the MBR facility. The drop in membrane system costs are attributed to advancements in manufacturing and increased competition in the market place while the increased costs of facility components are attributed to the increased cost of concrete and other raw materials used for plant construction. Results from this analysis shows these opposing trends have resulted in the overall total cost of MBR facilities to be fairly level (i.e. < 10% increase) between 2000 and 2006.
Are innovative managers emotionally intelligent

With the increasing competition, it is imperative for organizations to bring about managerial innovation and focus on managerial effectiveness. Studies indicate that only 27% of success at work is contributed by an employee's Intelligence Quotient, the rest of it being contributed by Emotional Intelligence. This paper attempts to study the role of Emotional Intelligence in Managerial Innovation and Effectiveness. The results of the study indicate a positive correlation between Emotional Intelligence and Managerial Innovation and Managerial Effectiveness implying thereby that Emotional Intelligence should be an integral part of an organization's recruitment and developmental process.
Big Data Series Analytics in the Context of Environmental Crowd Sensing

The new mobile crowd sensing (MCS) paradigm leads to the generation of a large amount of data originated from different sources. The inhomogeneous nature of produced data turns the process of data analytics and knowledge extraction extremely challenging and complicated. More specifically, mining such data needs special care and processing. In this paper, we focus on the analysis, processing, and exploration of such data. We advocate this process should benefit from the diverse data sources in the MCS context, including user’s annotation and various ambient data collected through sensors.
Responses of date palm (Phoenix dactylifera L.) callus to biotic and abiotic stresses

The in vitro responses of date palm (Phoenix dactylifera L.) callus of Hillawi cv. to Aspergillus niger culture filtrates (ACF) (10 and 20%) and sodium chloride (68.45; 137 and 205.34 mM) treatments were investigated at proliferation stage. Results indicated that both ACF and NaCl treatments at high concentrations led to an adverse effect on callus growth. Fresh and dry weights were significantly decreased, in contrast with control treatment (untreated callus). Growth reduction was accompanied with an increase of browning intensity. A stimulatory effect on callus growth was observed at low concentration of NaCl (68.45 mM). The exposed callus generally tends to accumulate a significant amount of free proline as well as hydrogen peroxide. This accumulation increased significantly with the increase of ACF and NaCl concentrations, whereas the opposite trend was seen in the activity of Catalase. Additionally, RAPD-PCR technique utilized to define any DNA rearrangements that may have been induced by ACF and NaCl treatments. Results of RAPD analysis detected DNA polymorphism usingOPA01-OPA03 primers which revealed appearance and disappearance of fragments compared to control profile. Thus suggesting genetic rearrangements which could be the cause of the observed morphological and biochemical variations in date palm callus exposed to biotic and abiotic stresses.
Compliance Control and Analysis for Equivalent Hydraulic Legs

In this article, the compliant behavior of an equivalent hydraulic leg is achieved by combining active compliance control of hydraulic cylinder with a passive spring at its end effector. Firstly, a position-based active compliance control is proposed based on impedance control to reduce the contact impact. Secondly, the stability of proposed compliance controller and the range of impedances (Z-width) of compliance control are analyzed, and the design procedure of proposed compliance controller is given out. Finally, experimental results show that the contact impacts could be well handled by the proposed control method. This research provides an insight for the compliance control of hydraulic legged robots.
Gradient Boosted Tree Based Feature Selection and Parkinson’s Disease Classification

Parkinson’s Disease (PD) is one of the most common neurodegenerative disorder with increasing prevalence in the world. Many studies have been conducted to detect or diagnose PD. Recently, voice signal based PD detection has been conducted rapidly. However, the performance of the detection still not excellent, hence the need for excellent detection still an open issue in PD detection. In this study, PD detection based on voice signal was conducted using public dataset. Since the dataset consist of many features, the proposed method combines feature selection mechanism and classification based on Gradient Boosted Tree (GBT) algorithm. Feature selection was conducted by using feature weighting from GBT. The experimental results show that the proposed method outperforms prior research with the accuracy about 0.92 with the minimum number of features. This result proves that GBT able to perform feature selection and good classifier. This concludes that the proposed method is promising as PD detection based on voice signal analysis.
Robust Finite-Time H∞ Filtering for Uncertain Switched Systems With State Constraints and Multiple Time Delays

In this paper, robust finite-time $H_\infty $ filtering for uncertain switched systems with state constraints and multiple time delays is investigated. In this studied plant, there are nonlinear functions and exogenous disturbances. First, a filter is described for the switched systems. A closed-loop system is earned to acquire filtering error. Secondly, piecewise Lyapunov function is designed to gain sufficient stability conditions for the closed-loop system. Not only finite-time boundedness (FTB) but also input-output finite-time stability (IO-FTS) is studied. The attempt is the first time to research. In the end, an example is shown to demonstrate the availability of this method suggested in this study.