Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging Socioeconomic Information and Deep Learning for Residential Load Pattern Prediction

Advanced metering infrastructure systems record a high volume of residential load data, opening up an opportunity for utilities to understand consumer energy consumption behaviors. Existing studies have focused on load profiling and prediction, but neglected the role of socioeconomic characteristics of consumers in their energy consumption behaviors. In this paper, we develop a prediction model using deep neural networks to predict load patterns of consumers based on their socioeconomic information. We analyze load patterns using the K-means clustering method and use an entropy-based feature selection method to select the key socioeconomic characteristics that affect consumers' load patterns. Our prediction method with feature selection achieves a higher prediction accuracy compared with the benchmark schemes, e.g. 80% reduction in the prediction error.
Stable Walking of Humanoid Robots Using Vertical Center of Mass and Foot Motions by an Evolutionary Optimized Central Pattern Generator

This paper proposes a method to produce the stable walking of humanoid robots by incorporating the vertical center of mass (COM) and foot motions, which are generated by the evolutionary optimized central pattern generator (CPG), into the modifiable walking pattern generator (MWPG). The MWPG extends the conventional 3-D linear inverted pendulum model (3-D LIPM) by allowing a zero moment point (ZMP) variation. The disturbance caused by the vertical COM motion is compensated in real time by the sensory feedback in the CPG. In this paper, the vertical foot trajectory of the swinging leg, as well as the vertical COM trajectory of the 3-D LIPM, are generated by the CPG for the effective compensation of the disturbance. Consequently, using the proposed method, the humanoid robot is able to walk with a vertical COM and the foot motions generated by the CPG, while modifying its walking patterns by using the MWPG in real time. The CPG with the sensory feedback is optimized to obtain the desired output signals. The optimization of the CPG is formulated as a constrained optimization problem with equality constraints and is solved by two-phase evolutionary programming (TPEP). The validity of the proposed method is verified through walking experiments for the small-sized humanoid robot, HanSaRam-IX (HSR-IX).
Psychosomatic Pain in Head and Neck Region

Pain can be described as an unpleasant sensory and emotional experience associated with actual or potential tissue damage. The word pain is derived from the Latin word ‘Poena’ which means punishment or penalty after goddess of punishment. This term was originally used to denote suffering particularly if it has resulted from blameworthy act. The word ‘Pschycosomatic’ is originated from the Greek word for mind and body. It does not originate from physical cause. It is related to emotional problem.
Musical Instrument Recognition using Zero Crossing Rate and Short-time Energy

Traditionally, musical instrument recognition is mainly based on frequency domain analysis (sinusoidal analysis, cepstral coefficients) and shape analysis to extract a set of various features. Instruments are usually classified using k-NN classifiers, HMM, Kohonen SOM and Neural Networks. Recognition of musical instruments in multi-instrumental, polyphonic music is a difficult challenge which is yet far from being solved. Successful instrument recognition techniques in solos (monophonic or polyphonic recordings of single instruments) can help to deal with this task. We introduce an instrument recognition process in solo recordings of a set of instruments (flute, guitar and harmonium), which yields a high recognition rate. A large solo database is used in order to encompass the different sound possibilities of each instrument and evaluate the generalization abilities of the classification process. The basic characteristics are computed in 1sec interval and result shows that the estimation of zero crossing rate and short time energy reflects more effectively the difference in musical instruments.
Risk Stratification in Frequent Ventricular Extrasystoles: The Importance of Cardiac Magnetic Resonance

Ventricular tachycardia (VT) has a direct relationship with sudden cardiac death (SCD) and risk stratification is essential for further treatment. In a context of a structural normal heart, idiopathic VT is the principal suspicion. Cardiac magnetic resonance (CMR) is a powerfull tool to evaluate the anatomic substrate of ventricular arrhytmias. Myocarditis is a frequent cause of a arrhytmias, and is properly diagnosis by CMR. The presence of late gadolinium enhacement is relate with the diagnosis and pronostic of myocarditis.
Modeling Continuous System Dynamics in SysML

In this paper, we present a formal approach to modeling continuous system dynamics in SysML using differential algebraic equations (DAE’s). To support model-based design, the Object Management Group has recently developed the Systems Modeling Language (OMG SysML™). The language is well-suited for modeling many different aspects of largescale, multidisciplinary engineering projects. It allows systems designers to capture information concerning system requirements, tests, structures, functions, and behaviors. However, SysML lacks explicit support for modeling continuous system dynamics using DAE’s. Such models are important for representing system behavior resulting from energy or signal exchange between system components. We introduce support for modeling system dynamics in the form of a language mapping between SysML and Modelica, an equation-based, object-oriented behavioral simulation language. The bidirectional mapping provides support for creating system dynamics models in SysML that can exist alongside other SysML information models, but that can also be transformed into executable simulations by a Modelica solver. To illustrate the approach, we provide an example SysML model of a hydraulic pump.
ExActa An Apple a Day

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/apha.12850 This article is protected by copyright. All rights reserved. Received Date : 16-Jan-2017 Revised Date : 30-Nov-2016 Accepted Date : 16-Jan-2017 Article type : Editorial
Effects of Long-Duration Administration of 1% Isoflurane on Resting Cerebral Blood Flow and Default Mode Network in Macaque Monkeys

Isoflurane is an inhalational anesthetic that is widely used in medical procedures or biomedical research. The duration of anesthesia administration varies from minutes to hours. It is known that isoflurane has dose-dependent effects on brain functionality and physiology, and long-duration anesthesia administration could cause neurocognitive decline in animals and humans. However, the duration effect of isoflurane on the brain physiology and functionality still remains poorly understood. In the present study, cerebral blood flow (CBF) and functional connectivity of adult rhesus monkeys (maintained with 1% isoflurane for 4 h) were examined by using magnetic resonance imaging. The results demonstrate that long-duration isoflurane exposure could result in CBF reduction in most brain areas and functional connectivity decrease in the dominant default-mode network. This study reveals the anesthetic duration effects in the central nervous system of anesthetized subjects and suggests that such duration effects should be considered in examining the brain function of anesthetized animals or humans with contemporary neuroimaging approaches.
COGNITIVE-ENHANCING PROPERTIES OF MORINDA LUCIDA (RUBIACEAE) AND PELTOPHORUM PTEROCARPUM (FABACEAE) IN SCOPOLAMINE-INDUCED AMNESIC MICE.

Background: Cognitive disorders associated with aging have been successfully managed by African traditional medical practitioners using various plants. This study evaluated the cognitive enhancing potentials of Morinda lucida (L) Rubiaceae and Peltophorum pterocarpum (DC) ex. K Heyne in scopolamine induced amnesic animals. Materials and Methods: The anti-amnesic activity of the ethyl acetate extracts of Morinda lucida and Peltophorum pterocarpum at doses of 4 mg/kg, 6 mg/kg and 8 mg/kg were assessed in scopolamine induced amnesic mice using Morris water maze test model. Effect of the extracts on the histology of the hippocampus was also evaluated. Results: The ethyl acetate extract of Morinda lucida and Peltophorum pterocarpum ameliorated scopolamine induced memory deficit in the animals under study. There was no effect of the extract on the histology of the hippocampus. However, there was an increase in the density of cells in the hippocampus of treated group as compared to the untreated. Conclusion: Morinda lucida and Peltophorum pterocarpum showed considerable enhancement of cognition in scopolamine induced amnesic mice.
Determination of best Regime for Administration of Atropine Eye Drops for Cycloplegia

Methods: This cross-sectional study was conducted in Pediatric Clinic, Mayo Hospital Lahore, Pakistan in the duration of 3 months to assess the best regime for administration of 1% atropine eye drops for cycloplegia and to see the effect of cycloplegia on different types of refractive error. Non probability purposive sampling was done and 30 patients of age between 0 to 12 years were assessed using a self designed performa. Patients who required cycloplegic refraction were examined after installation of atropine 1 drop for 1 day and 3 drops for 3 days by auto refactometer and retinoscopy. Results were compared to find out the difference in refractive error and the effect of cycloplegia on myopes and hyperopes.
Implementation of Fuzzy Logic Systems into Diagnosing Acute and Degenerative Meniscal Tears

Submit Manuscript | http://medcraveonline.com significant amount of false positive results [5,6] A detailed ,focused history and comprehensive physical examination still considered the cornerstones of the diagnosis of meniscal injuries. Conversely, the outputs of the physical examination are usually quite ambiguous / equivocal [7-9] regarding complex even simpler patterns of knee soft tissue injuries, arousing the necessity of a complete different perspective to tackle the problem. That can be achieved inserting into the equation the “fuzzy logic systems “realm of cybernetics. We believe it is possible to create dynamic, non linear systems of algorithmic diagnosis, that could evolve and be reprogrammed in correspondence to the inputs and the feedback of the experts in the field of sports medicine and more importantly, to reach and perhaps surpass in accuracy the MRI diagnostic modality, hence providing a useful tool to the armamentarium of the clinician [10,11].
OPTIMAL CAMERA NETWORK DESIGN FOR 3D MODELING OF CULTURAL HERITAGE

Abstract. Digital cultural heritage documentation in 3D is subject to research and practical applications nowadays. Image-based modeling is a technique to create 3D models, which starts with the basic task of designing the camera network. This task is – however – quite crucial in practical applications because it needs a thorough planning and a certain level of expertise and experience. Bearing in mind todays computational (mobile) power we think that the optimal camera network should be designed in the field, and, therefore, making the preprocessing and planning dispensable. The optimal camera network is designed when certain accuracy demands are fulfilled with a reasonable effort, namely keeping the number of camera shots at a minimum. In this study, we report on the development of an automatic method to design the optimum camera network for a given object of interest, focusing currently on buildings and statues. Starting from a rough point cloud derived from a video stream of object images, the initial configuration of the camera network assuming a high-resolution state-of-the-art non-metric camera is designed. To improve the image coverage and accuracy, we use a mathematical penalty method of optimization with constraints. From the experimental test, we found that, after optimization, the maximum coverage is attained beside a significant improvement of positional accuracy. Currently, we are working on a guiding system, to ensure, that the operator actually takes the desired images. Further next steps will include a reliable and detailed modeling of the object applying sophisticated dense matching techniques.
Proceedings of the forty-fifth annual ACM symposium on Theory of computing

The results in this volume were presented at the 45th Annual ACM Symposium on Theory of Computing (STOC 2013), which was held in Palo Alto, CA, June 2-4, 2013, and sponsored by the ACM Special Interest Group on Algorithms and Computation Theory (SIGACT). At the suggestion of SIGACT Past Chair Lance Fortnow, we experimented with a two-tiered program committee for the first time in STOC's 45-year history. Specifically, the program was constructed by a nine-person Executive Committee (EC) and a 62-person Program Committee (PC). Members of the PC were allowed to submit, but members of the EC were not. It was an interesting and highly controversial experiment that I blogged about at Michael Mitzenmacher's invitation (http://mybiasedcoin.blogspot.com/2013/02/discussing-stoc-2013-pc-with-joan.html). I will post a longer report on the experiment on my web page in June 2013. We received 373 submissions, 13 of which were withdrawn before accept/reject decisions were made. Of the remaining 360 submissions, 100 were accepted, for an acceptance rate of 27.8%; after accept/reject decisions were announced, one of the accepted submissions was withdrawn. One pair of accepted submissions was presented in a joint talk, for a total of 98 talks and 99 proceedings contributions. Submissions were not formally and officially refereed, and many of the proceedings contributions are preliminary reports on ongoing research; it is expected that most of the results in the proceedings will ultimately be published in final form in refereed journals. From the many excellent candidates, we selected "Low Rank Approximation and Regression in Input Sparsity Time," by Kenneth L. Clarkson and David P. Woodruff, and "Approximation Resistance from Pairwise Independent Subgroups," by Siu On Chan, as co-winners of the Best- Paper Award and "Maintaining Shortest Paths Under Deletions in Weighted Directed Graphs," by Aaron Bernstein, and "Approximation Resistance from Pairwise Independent Subgroups," by Siu on Chan, as co-winners of the Danny Lewin Best-Student-Paper Award. In addition to the basic conference program, STOC 2013 included the Knuth-Prize lecture by Gary Miller on June 3 and three workshops on June 1: "New (Theoretical) Challenges in Machine Learning," "Information Complexity and Applications," and "Online Matching and Ad Serving: Theory and Practice. " The June 1 program also included an invited talk by Prabhakar Raghavan and a panel session on grant-proposal writing. A poster session was held in the evening of June 2.
Outcomes of a Mobile Phone Intervention for Heart Failure in a Minority County Hospital Population.

BACKGROUND Chronic heart failure (HF) causes significant morbidity, mortality, and cost. Managing HF requires considerable self-management skills and self-efficacy. Little information exists about feasibility and potential impact of a mobile monitoring intervention to improve self-efficacy and quality of life (QoL) among minority patients with HF. MATERIALS AND METHODS We developed a mobile phone-assisted case management program and tested its impact on outcomes in minority patients with HF in a 2:1 randomized controlled trial. We evaluated self-care efficacy, knowledge, behavior, and QoL at baseline and 3 months. RESULTS We enrolled 61 participants: intervention 42, usual care 19; mean age ± SD: 55 ± 10 years; 64% male; 75% white Hispanic, 25% African American; and 56% high school education or less. Comparison of the two groups with respect to changes from baseline to 3 months showed significant differences for Self-Efficacy for Managing Chronic Disease (2.09 ± 2.32, p-value = 0.005); health distress scale (-1.1 ± 1.5, p-value = 0.017); and QoL (Role Physical, 23.6 ± 44.5, p-value = 0.042, and General Health, 11.1 ± 14.2, p-value = 0.012). CONCLUSIONS A mobile phone-based disease management program may help improve self-care efficacy and QoL in a minority population and offers a modality to help reduce ethnic disparity.
Real-time multi-face detection on FPGA for video surveillance applications

In the field of face recognition and in the establishment of a face database, face detection is a crucial step. In current security and surveillance systems, most of the face detection proposed now is focused on software algorithms to improve the detection rate and decrease false alarms. However, these more complex algorithms require more computation time, which hinders real-time applications. In this paper, we propose a real-time multi-face detection system based on hardware design to enhance processing time. The proposed hardware architecture is implemented on an Altera DE2-70 field-programmable gate array development board to test the feasibility of our hardware design. To implement, our system requires 15,223 logic elements. The proposed system can operate in real-time at a frame rate of 30 fps, and detects up to five faces simultaneously. Our experimental results show that the proposed face detection architecture provides a reliable real-time system operating at low cost and providing a high detection rate.
Playing in Traffic : pervasive gaming for commuters

The influx of cycle commuters and the resulting paradigm shift in traffic composition is causing friction between road users. This paper proposes the use of an experimental alternate reality game (ARG) that is also a role-playing game (RPG) layered on top of the commuting experience. This experimental social game, Playing in Traffic, is played with a global positioning system (GPS) capable smart phone, such as an iPhone, and is aimed at the expanding community of casual gamers. The game is designed to encourage more positive behaviour while in traffic by introducing game rewards mechanisms, such as the collection of achievements, and provides a positive feedback loop to augment commuter behaviour. Playing in Traffic is an exploratory suggestion that looks at the role of pervasive gaming in addressing the larger issues of urban planning, traffic congestion and the challenges around active commuting.
A Survey on Autonomous Learning of College English Listening

Autonomous learning of Colleges English Listening (ALCEL) has been carried out in many college and universities for nearly ten years in China. However, the effect of ALCEL is not as good as expected. In order to probe problems of ALCEL, questionnaire on ALCEL was conducted in six local universities of Hubei province. It focused on the quantities of seats in Autonomous learning (AL) rooms, the condition of the hardware and software for ALCEL, the guidance from teachers of Colleges English Listening, and students’ attitudes towards ALCEL. 180 Questionnaires were distributed to students at six local universities of Hubei province, and 175 returned Questionnaires were valid ones. Data from the survey showed that there were problems in the existing ALCEL, which need solving urgently. And on the basis of discussion, solutions were offered to overcome these problems in the end. Keywords—Autonomous learning; Autonomous learning of Colleges English Listening; problems; solutions
A Fast Low-Cost Shortest Path Tree Algorithm

Low-Cost Shortest Path Tree is a commonly-used multicast tree type, which can minimize the end-to-end delay and at the same time reduce the bandwidth requirement if possible. Based on the low-cost shortest path tree algorithm DDSP (destination-driven shortest path) and through improving on the search procedure, a Fast Low-cost Shortest Path Tree (FLSPT) algorithm is presented in this paper. The Shortest Path Tree constructed by the FLSPT algorithm is the same as that constructed by the DDSP algorithm, but its computation complexity is lower than that of the DDSP algorithm. The simulation results with random network models show that FLSPT algorithm is
On routing structure for the hybrid field programmable architecture

In this paper, we investigate the routing architecture for an FPGA with hybrid clusters comprising both look-up tables (LUTs) and PLA-like blocks. We discuss the CAD flow that is used to place and route a number of MCNC benchmark circuits. Our experimental results show the optimized values for cluster-level parameters as well as the best cluster size in terms of area and performance.
Redundanzreduktion bei komprimierten Audiosignalen

Using only psychoacoustic effects for data compression of audio signals leaves redundant components in the compressed audio signal due to remaining correlations. Prediction-based methods will be presented that allow using these redundancies for further datacompression. For such an extension of the standardized algorithm a parameter optimization by measurements with different audio signals is performed. An implementation of this new method confirms the measurement results.
cdma2000 mobile radio access for IMT 2000

This article presents key design characteristics of the cdma2000 RTT in terms of the proposed forward and reverse link structure. cdma2000 demonstrates that it can fully support IMT-2000 requirements and additional future services while providing backward compatibility to existing TIA/EIA-95-A/B cdmaOne networks. Major differences between the cdma2000 and WCDMA RTT proposals, in the areas of chip rate selection, pilot structure, base station synchronization, and frame length are highlighted in this article. Based on theoretical analyses, computer simulation results, and several years of experience with CDMA networks, it is concluded that cdma2000 provides several competitive and economical advantages to operators and end users.
Moringa oleifera from Cambodia Ameliorates Oxidative Stress, Hyperglycemia, and Kidney Dysfunction in Type 2 Diabetic Mice.

Abstract Recent reports have shown the antidiabetic effect of Moringa oleifera from various parts of the world. However, M. oleifera from Cambodia has never determined. Therefore, the aim of this study was to assess the antidiabetic effect of M. oleifera extract from Cambodia. The leaf ethanolic extract contained flavonoids (31.90 mg/mL), polyphenols (53.03 mg/mL), lycopene (0.042 mg/mL), and s-carotene (0.170 mg/mL), and possessed 2,2-diphenyl-1-picrylhydrazyl, hydrogen peroxide, and hydroxyl radical scavenging activities of 92.40, 99.25, and 83.57 TE/μM at 1 mg/mL, respectively. Db/db mice were orally administered the leaf extract (150 mg/kg/day) for 5 weeks. M. oleifera treatment significantly ameliorated the altered fasting plasma glucose (from 483 to 312 mg/dL), triglyceride (from 42.12 to 23.00 mg/dL), and low-density lipoprotein cholesterol (from 107.21 to 64.25 mg/dL) compared to control group, and increased the insulin levels from 946 ± 92 to 1678 ± 268 pg/mL. The histopathological damage and exp.