Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Spatio-Temporal Networks CSCi 8701 : Project Report Group 04 :

Growing importance of application domains such as location-based services and evacuation planning highlights the need for efficient modeling of spatio-temporal networks (e.g. roa d networks) that takes into account changes to the network over time. The model should provide the necessary framework for developing efficient algorithms that implement frequent operations posed on such network s. A frequent query that is posed on such networks is to find the shortest route from one place to another or a search for the nearest neighbor. The shortest route would depend on the time dependent properties of the n etwork such as congestion on certain road segments, which would increase the travel time on that segment. T h result of nearest neighbor search could also be time sensitive if it is based on a road network. Modeling such a network poses many challenges. Not only should the model be able to accomodate changes and compute the results consistent with the existing conditions, it should do so a ccurately and simply. In addition, the need to answer frequent queries quickly means fast algorith ms are required for computing the query results. The model should thus provide sufficient support for th e design of correct and efficient algorithms for the frequent computations. Often dynamic networks have been modeled as time expanded networks, whe re the ntire network is replicated for every time instant. The changes in the network, especially the trave l time variations, can be very frequent and for modeling such frequent changes, the time expanded n etworks would require a large number of copies of the original network, thus leading to network sizes that are too memory expensive. For example, traffic sensors on highway networks send measurement data every 30 s econd . A one-year dataset may need over one million copies of the road network, which itself may have a million nodes a nd edges for each time instant. Such large sized networks would also result in computationally expen sive algorithms. The proposed model, a time-aggregated graph, models the changes in a spa tio-temporal network by collecting the node/edge attributes into a set of time series. The model can also acc ount for the changes in the topology of the network. The edges and nodes can disappear from the n etwork during certain instants of time and new nodes and edges can be added. The time-aggregated graph ke eps track of these changes through a time series attached to each node and edge that indicates their presence at various instants of time. Our analysis shows that this model is less memory expensive and leads to algorithms that are computationally more efficient than those for the time expanded networks.
Characterization of the locus responsible for the bacteriocin production in Lactobacillus plantarum C11

Lactobacillus plantarum C11 secretes a small cationic peptide, plantaricin A, that serves as induction signal for bacteriocin production as well as transcription of plnABCD. The plnABCD operon encodes the plantaricin A precursor (PlnA) itself and determinants (PlnBCD) for a signal transducing pathway. By Northern (RNA) and sequencing analyses, four new plantaricin A-induced operons were identified. All were highly activated in concert with plnABCD upon bacteriocin induction. Two of these operons (termed plnEFI and plnJKLR) each encompass a gene pair (plnEF and plnJK, respectively) encoding two small cationic bacteriocin-like peptides with double-glycine-type leaders. The open reading frames (ORFs) encoding the bacteriocin-like peptides are followed by ORFs (plnI and -L, respectively) encoding cationic hydrophobic proteins resembling bacteriocin immunity proteins. On the third operon (termed plnMNOP), a similar bacteriocin-like ORF (plnN) and a putative immunity ORF (either plnM or -P) were identified as well. These findings suggest that two bacteriocins of two-peptide type (mature PlnEF and PlnJK) and a bacteriocin of one-peptide type (mature PlnN) could be responsible for the observed bacteriocin activity. The last operon (termed plnGHSTUV) contains two ORFs (plnGH) apparently encoding an ABC transporter and its accessory protein, respectively, known to be involved in processing and export of peptides with precursor double-glycine-type leaders. Promoter structure was established. A conserved regulatory-like box encompassing two direct repeats was identified in the promoter regions of all five plantaricin A-induced operons. These repeats may serve as regulatory elements for gene expression.
Appearance of Dark Clouds? - An Empirical Analysis of Users' Shadow Sourcing of Cloud Services

Encouraged by recent practical observations of employees' usage of public cloud services for work tasks instead of mandatory internal support sys- tems, this study investigates end users' utilitarian and normative motivators based on the theory of reasoned action. Partial least squares analyses of survey data comprising 71 computer end users at work, employed across various com- panies and industries, show that perceived benefits for job performance, social influences of the entire work environment, and employees' lack of identifica- tion with the organizational norms and values drive insiders to threaten the se- curity of organizational IT assets.
Deformed Matrix Theories with N = 8 and Fivebranes in the PP Wave Background

M(atrix) theory is known to be mass-deformed in the pp-wave background and still retains all 16 dynamical supersymmetries. We consider generalization of such deformations on super Yang-Mills quantum mechanics (SYQM) with less supersymmetry. In particular this includes N = 8 U(N) SYQM with a single adjoint and any number of fundamental hypermultiplets, which is a pp-wave deformation of DLCQ matrix theory of fivebranes. With k ≥ 1 fivebranes, we show that a rich vacuum structure exists, with many continuous family of solutions that preserve all dynamical supersymmetries. The vacuum moduli space contains copies of CP k−1 of various sizes.
Stiffness gradient detection for tissue discrimination based on identification of mass-spring-damper models

Discrimination of tumorous and healthy tissue is a critical task in minimally invasive surgery because mechanic palpation techniques used in open surgery cannot be applied. The surgeons rely on alternative sensor data such as images (camera) or displacements (force sensor). In order to take advantage of these sensor data beyond the pure visual inspection a detailed soft tissue model as well as an reliable parameter identification algorithm are required. In this contribution, a tissue model based on mass-spring-damper elements is selected due to its excellent approximation performance. As this model is high dimensional, a parametric model order reduction technique is applied in order to obtain a model which can be used for real-time parameter identification. It is shown that the parameter identification algorithm using the reduced order model offers accurate results, even in the presence of measurement noise.
Using Confusion Reject to Improve (User and) System (Cross) Learning of Gesture Commands

This paper presents a new method to help users defining personalized gesture commands (on pen-based devices) that maximize recognition performance from the classifier. The use of gesture commands give rise to a cross-learning situation where the user has to learn and memorize the command gestures and the classifier has to learn and recognize drawn gestures. The classification task associated with the use of customized gesture commands is complex because the classifier only has very few samples per class to start learning from. We thus need an evolving recognition system that can start from scratch or very few data samples and that will learn incrementally to achieve good performance after some using time. Our objective is to make the user aware of the recognizer difficulties during the definition of commands, by detecting confusion among gesture classes, in order to help him define a gesture set that yield good recognition performance from the beginning. To detect confusing classes we apply confusion reject principles to our evolving recognizer, which is based on a first order fuzzy inference system. A realistic experiment has been made on 55 persons to validate our confusion detection technique, and it shows that our method leads to a significant improvement of the classifier recognition performance.
Finite-time observer for a class of time-varying nonlinear systems

The problem of global finite-time convergent observer design for a class of nonlinear systems with time-varying coefficients is investigated in this paper. To solve this problem, a new time-varying finite-time convergent observer is first designed for the nominal system without nonlinearities. Using a recursive argument, an explicitly homogeneous Lyapunov function is constructed to prove the finite-time convergence of the error dynamic system. Then, using the homogeneous domination approach, we scale the finite-time observer with an appropriate choice of gain to obtain a global finite-time convergent observer for the nonlinear system.
Multilocus Sequence Analysis for the Assessment of Phylogenetic Diversity and Biogeography in Hyphomonas Bacteria from Diverse Marine Environments

Hyphomonas, a genus of budding, prosthecate bacteria, are primarily found in the marine environment. Seven type strains, and 35 strains from our collections of Hyphomonas, isolated from the Pacific Ocean, Atlantic Ocean, Arctic Ocean, South China Sea and the Baltic Sea, were investigated in this study using multilocus sequence analysis (MLSA). The phylogenetic structure of these bacteria was evaluated using the 16S rRNA gene, and five housekeeping genes (leuA, clpA, pyrH, gatA and rpoD) as well as their concatenated sequences. Our results showed that each housekeeping gene and the concatenated gene sequence all yield a higher taxonomic resolution than the 16S rRNA gene. The 42 strains assorted into 12 groups. Each group represents an independent species, which was confirmed by virtual DNA-DNA hybridization (DDH) estimated from draft genome sequences. Hyphomonas MLSA interspecies and intraspecies boundaries ranged from 93.3% to 96.3%, similarity calculated using a combined DDH and MLSA approach. Furthermore, six novel species (groups I, II, III, IV, V and XII) of the genus Hyphomonas exist, based on sequence similarities of the MLSA and DDH values. Additionally, we propose that the leuA gene (93.0% sequence similarity across our dataset) alone could be used as a fast and practical means for identifying species within Hyphomonas. Finally, Hyphomonas' geographic distribution shows that strains from the same area tend to cluster together as discrete species. This study provides a framework for the discrimination and phylogenetic analysis of the genus Hyphomonas for the first time, and will contribute to a more thorough understanding of the biological and ecological roles of this genus.
Segmental Muscle Vibration Improves Walking in Chronic Stroke Patients With Foot Drop: A Randomized Controlled Trial

Background. Studies have described the effects of segmental muscle vibration (SMV) on brain plasticity and corticomotor excitability. Information on the treatment-induced effects of SMV in stroke patients is, however, still limited. Objectives. To assess whether the application of SMV to ankle dorsiflexor muscles of chronic stroke patients can improve walking. Methods. Forty-four patients were randomly assigned to either an experimental group (EG) or a control group (CG) and underwent 12 sessions over 4 weeks of general physical therapy. Patients in the EG also received SMV at 120 Hz over the peroneus longus and tibialis anterior for 30 minutes at the end of each session. All the participants underwent pretreatment and posttreatment gait analysis assessments. Time—distance, kinematic, and surface electromyography (EMG) data were used as outcome measures. Results. A moderate improvement in mean gait speed, normal-side swing velocity, bilateral stride length, and normal-side toe-off percentage was observed only in the EG. A significant increase in bilateral ankle dorsiflexion angle at heel contact was associated with increased maximum ankle dorsiflexion and plantarflexion degrees during the swing phase on the paretic side after treatment in EG. Surface EMG during the swing phase revealed a significant increase in the activation of the tibialis anterior muscle on the paretic side in the posttreatment assessment in the EG. Conclusions. SMV added to general physical therapy may improve gait performance in patients with foot drop secondary to chronic stroke. The authors hypothesize that this may be due to the mechanical vibration stimulation, probably as a consequence of effective brain reorganization.
Model Analysis of Talents' Abilities and Qualities for Information-Based Entrepreneurship

In such an age of information, the talents competent for information-based entrepreneurship not only constitute the core competitiveness of newly-established enterprises, but also are of crucial importance to the success in entrepreneurship. In a bid to form a scientific and quantitative system for the selection, cultivation, use and keeping of talents for information-based entrepreneurship, this paper summarizes the abilities and qualities essential for such talents, makes a comprehensive analysis over the talents' roles in work, and eventually proposes a model concerning the talents' abilities and qualities for information-based entrepreneurship on the basis of the previous researches.
DVoDP/sup 2/P: distributed P2P assisted multicast VoD architecture

For a high scalable VoD system, the distributed server architecture (DVoD) with more than one server-node is a cost-effective design solution. However, such a design is highly vulnerable to workload variations because the service capacity is limited. In this paper, we propose a new and efficient VoD architecture that combines DVoD with a P2P system. The DVoD's server-nodes is able to offer a minimum required quality of service (QoS) and the P2P system is able to provide the mechanism to increase the system service capacity according to client demands. Our P2P system is able to synchronize a group of clients in order to replace server-nodes in the delivery process. We compared the new VoD architecture with DVoD architecture based on classic multicast and P2P delivery policies (patching and chaining). The experimental results showed that our design is better than previous solutions, providing higher scalability
Parallel hybrid Price-Genetic algorithm for Global Optimization.

A hybrid algoritm to find the absolute extreme point of a multimodal scalar function of many variables is presented. The algorithm is well suited to be implemeted in parallel over a distributed computer environment. The algorithm is suitable when the objective function is expensive to compute, the computation can be affected by noise and/or partial derivatives cannot be calculated. The method used is a genetic modification of a previous algorithm based on the Price’s method. The genetic part of the algorithm is very effective to escape from local attractors of the algorithm and assures convergence in probability to the global optimum. The parallel implementation of the algorithm is based on a domain decomposition approach, fully exploiting available information over global behaviour of the function, reducing to a small amount the computer charge due to need for syncronization. The algorithm has been tested for optimizing several multimodal test function. Key-words:Global Optimization, Controlled Random Search, Genetic Algorithms, Parallel Computation.
Comparison of adjuvant and adjuvant-free murine experimental asthma models

Introduction The most widely used protocol for the induction of experimental allergic airway inflammation in mice involves sensitization by intraperitoneal (i.p.) injections of the antigen ovalbumin (OVA) used in conjunction with the adjuvant aluminium hydroxide (alum). Although adjuvants are frequently used, there are questions regarding the necessity of alum for murine asthma studies due to the non‐physiological nature of this chemical.
A classifier-free codebook-based image classification of vehicle logos

Logo identification and classification have received considerable attention from both the machine learning and computer vision communities. Vehicle logo recognition (VLR) is used to recognise accurately the manufacturer of a vehicle by using its iconic logo. A VLR system in addition to license plate recognition aims to increase the confidence of vehicle monitoring systems in private environments such as car parks in companies, shopping malls, and institutions. VLR is a challenging process due to the presence of extensive background, clutter, different degree of illumination, varying sizes of vehicles in motion, and change of weather conditions such as fog, sunny and rainy which are present in the two-dimensional images. On the other hand, the bag-of-features (BoF) approach initiated to be used as a black box providing reliable and repeatable measurements from images for a wide range of applications such as visual object recognition. The advantages of such a BoF approach are its simplicity and state-of-the-art performance in recent VLR tasks. Most of the VLR in the literature has focused on less than twenty distinctive iconic logos of the vehicles. In this paper, we propose a novel VLR system as an alternative method to the BoF approach in which the extracted patch-based descriptors of a test image is voted against a locally merged codebooks of logos to predict the class label without the need for mapping the extracted descriptors into a fixed-length feature vector and then feeding it to a standard classifier. The proposed VLR system using SIFT descriptors is compared with the traditional BoF approach that employs a standard classifier: nearest neighbour and support vector machines. The system is evaluated on 25 distinctive vehicle classes with 20 images per class. Testing results show that our method promotes codebooks that deliver a robust classification performance of 98.6% which drastically reduces the time needed by the traditional BoF approach.
Collapse of primordial clouds — I

We present studies of the collapse of purely baryonic Population III objects with masses ranging from 10 to 106M⊙. A spherical Lagrangian hydrodynamic code has been written to study the formation and evolution of primordial clouds, from the beginning of the recombination era (zrec ∼ 1500) until the redshift when the collapse occurs. All the relevant processes are included in the calculations, as well as the expansion of the Universe. As initial condition we take different values for the Hubble constant and for the baryonic density parameter (considering however a purely baryonic Universe), as well as different density perturbation spectra, in order to see their influence on the behaviour of the evolution of the Population III objects. We find, for example, that the first mass that collapses is 8.5 × 104 M⊙ for h = 1, Ω = 0.1 and δi = δρ/ρ = (M/M0)−1/3(1 + zrec)−1, with the mass-scale M 0 = 1015M⊙. For M0 = 4 × 1017 M⊙ we obtain 4.4 × 104 M⊙ for the first mass that collapses. The cooling–heating and photon drag processes have a key role in the collapse of the clouds and in their thermal history. Our results show, for example, that when we disregard the Compton cooling–heating, the collapse of the objects with masses >8.5 × 104 M⊙ occurs earlier. On the other hand, when we disregard the photon drag process, the collapse occurs at a higher redshift.
Enhanced frequency hopping for reliable interconnection of low power smart home devices

The interconnection of smart home devices plays a key role in future smart grid energy systems. It is reasonable to apply wireless technologies for smart home networks, as they can be easily retrofitted in existing homes. Due to multipath propagation in indoor environments, wireless technologies have to cope with frequency selective fading. Thus, this paper presents an enhanced frequency hopping mechanism for reliable interconnection of low power smart home devices. The evaluations are based on the Bluetooth Low Energy standard. Different options are compared by evaluating the indoor coverage range, the energy consumption, and the latency.
A new automatic registration method for InSAR image based on multi-step strategy

Interferometric Synthetic Aperture Radar (InSAR) technology has been widely used in various applications. The registration of SAR (Synthetic Aperture Radar) images is the first step in interferometric processing therefore accurate registration is essential for the successful creation and interpretation of interferometric products. However, with the growing number of SAR satellite launch and the amount of data acquisition, the degree of automation of image registration have become increasingly demanding. In this paper, we propose an automatic registration approach based on multi-step matching strategy. In the first step, key points are detected and matched using modified scale invariant feature transform (SIFT) operator which modified by us reducing the influence of speckles. In this step, owing to the existing of speckle and the defect of matching strategy of SIFT operator, the expected level of matching accuracy is about 2 to 3 pixels. In the second step, correlation matching (CM) is used to exclude the matched points with low correlation. In the third step, the probability relaxation (PR) algorithm based on global matching is used to induce consistency constraint and ensure reliability of the matching result. Finally, corresponding transformation function is determined through the relationship established by matched point pairs. In order to verify the applicability of proposed methodology, two SAR images acquired over mountainous regions are used in our experiment. The experiment results show that subpixel registration accuracy and good efficiency have been achieved, which demonstrates the correctness and feasibility of proposed method.
Osteosarcoma of the patella: A case report

Abstract We present a rare case of osteosarcoma involving the patella. A 30-year-old Japanese woman first consulted our out-patient clinic with a 2-year history of knee pain. Radiographs showed an enlargement of the patella with irregular distribution of both osteolytic and sclerotic lesions. Computed tomography and magnetic resonance imaging demonstrated soft tissue extension at the anterior part of the patella. Incisional biopsy showed abundant osteoid formation by spindle-shaped malignant cells, and the histological diagnosis was conventional osteosarcoma. The patient underwent preoperative chemotherapy, but there was no response. Furthermore, she developed a pathological fracture during chemotherapy. She underwent above-the-knee amputation with postoperative chemotherapy. She developed multiple metastases in the thoracic vertebrae 20 months after the surgery. At the most recent examination, she remains alive with multiple spinal metastases without paralysis 4 years after the surgery.
Ima: the intelligent machine architecture

Approved: Date: ACKNOWLEDGEMENTS I thank Dr. K. Kawamura for believing in my ideas enough to let me lead his robotics lab into the new area of architecture-driven software design. I thank my committee for their comments, reviews and suggestions that contributed to this effort. I thank my wonderful wife, Ruth, for putting up with me during this very long journey. Finally, I thank God for the ability and the inspiration to develop new contributions to the area of robotics. He has continually guided me back to the idea of robots and I pray that this work will contribute in some small way to the development of service robots that relieve pain and suffering, aid those in need of assistance, or provide companionship to those who are alone.