Generalized Features Research Articles

A Deep Convolutional Neural Network Based Classification Of Multi-Class Motor Imagery With Improved Generalization.

Motor imagery (MI) based brain-computer interface (BCI) plays a crucial role in various scenarios ranging from post-traumatic rehabilitation to control prosthetics. Computer-aided interpretation of MI has augmented prior mentioned scenarios since decades but failed to address interpersonal variability. Such variability further escalates in case of multi-class MI, which is currently a common practice. The failures due to interpersonal variability can be attributed to handcrafted features as they failed to extract more generalized features. The proposed approach employs convolution neural network (CNN) based model with both filtering (through axis shuffling) and feature extraction to avail end-to-end training. Axis shuffling is performed adopted in initial blocks of the model for 1D preprocessing and reduce the parameters required. Such practice has avoided the overfitting which resulted in an improved generalized model. Publicly available BCI Competition-IV 2a dataset is considered to evaluate the proposed model. The proposed model has demonstrated the capability to identify subject-specific frequency band with an average and highest accuracy of 70.5% and S3.6% respectively. Proposed CNN model can classify in real time without relying on accelerated computing device like GPU.

Psychological features of the relationship the parameters of moral and legal reliability and adaptive capabilities of business entities

The article is devoted to consideration of the problem of development of personal reliability of entrepreneurs. Application methods: "Personality questionnaire reliability moral and legal personality" (Strizhov); Expert assessment of the employee's personality (Bovin); "Multi personality questionnaire Adaptability” "(Maklakov, Chermyanin) allowed to investigate specific features of adaptive capacity studied with different levels of moral and legal reliability, given the socio-psychological and some physiological characteristics that reflect generalized features neuropsychiatric and social development. Empirically proved that the psychological factor of personal safety business is a moral and meaningful determination of behavior of the individual.

A Novel Generalized Approach for Real-Time Tool Condition Monitoring

In high-speed cutting processes, late replacement of defective tools may lead to machine breakdowns and badly affect the product quality, which subsequently lead to scrap parts and high process costs. Accurate tool condition detection is essential to achieve high level of competitiveness via increasing process productivity and standardizing the quality of the produced parts. Therefore, tool condition monitoring (TCM) systems have been widely emphasized as an important principle to achieve these industrial demands. Several studies for TCM were carried out to capture tool failure using complex conventional and artificial intelligence (AI) techniques. However, these studies suffer from the absence of standardization and generalization. Hence, this paper presents a robust and reliable processing technique for the cutting process signals to extract generalized features in time and frequency domains. The proposed technique masks the effects of the cutting conditions on the extracted features and accentuates the tool condition effect. Characterization and statistical analysis of the processed features were performed to examine their sensitivity to the tool condition. The results revealed the processing technique capability to separate the features extracted from the spindle motor current signals into two mutually exclusive clusters according to their tool condition. The statistical analysis results were employed to optimize the tool condition detection approach using linear discrimination analysis (LDA) model. The results indicate the capability of the processing technique to minimize the system learning effort and to detect tool wear above the threshold level with accuracy above 90%.

Approach to Clustering with Variance-Based XCS

This paper presents an approach to clustering that extends the variance-based Learning Classifier System (XCS-VR). In real world problems, the ability to combine similar rules is crucial in the knowledge discovery and data mining field. Conventionally, XCS-VR is able to acquire generalized rules, but it cannot further acquire more generalized rules from these rules. The proposed approach (called XCS-VRc) accomplishes this by integrating similar generalized rules. To validate the proposed approach, we designed a bench-mark problem to examine whether XCS-VRc can cluster both the generalized and more generalized features in the input data. The proposed XCS-VRc proved to be more efficient than XCS and the conventional XCS-VR.

Bird detection and species classification with time‐lapse images around a wind farm: Dataset construction and evaluation

AbstractCollisions of birds, especially endangered species, with wind turbines is a major environmental concern. Automatic bird monitoring can be of aid in resolving the issue, particularly in environmental risk assessments and real‐time collision avoidance. For automatic recognition of birds in images, a clean, detailed, and realistic dataset to learn features and classifiers is crucial for any machine‐learning‐based method. Here, we constructed a bird image dataset that is derived from the actual environment of a wind farm and that is useful for examining realistic challenges in bird recognition in practice. It consists of high‐resolution images covering a wide monitoring area around a turbine. The birds captured in these images are at relatively low resolution and are hierarchically labeled by experts for fine‐grained species classification. We conducted evaluations of state‐of‐the‐art image recognition methods by using this dataset. The evaluations revealed that a deep‐learning‐based method and a simpler traditional learning method were almost equally successful at detection, while the former captures more generalized features. The most promising results were provided by the deep‐learning‐based method in classification. The best methods in our experiments recorded a 0.98 true positive rate for bird detection at a false positive rate of 0.05 and a 0.85 true positive rate for species classification at a false positive rate of 0.1.

Phenotypic analysis of 303 multiplex families with common epilepsies.

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and inter-relationships of the common epilepsy syndromes.

Dual many-to-one-encoder-based transfer learning for cross-dataset human action recognition

The emergence of large-scale human action datasets poses a challenge to efficient action labeling. Hand labeling large-scale datasets is tedious and time consuming; thus a more efficient labeling method would be beneficial. One possible solution is to make use of the knowledge of a known dataset to aid the labeling of a new dataset. To this end, we propose a new transfer learning method for cross-dataset human action recognition. Our method aims at learning generalized feature representation for effective cross-dataset classification. We propose a novel dual many-to-one encoder architecture to extract generalized features by mapping raw features from source and target datasets to the same feature space. Benefiting from the favorable property of the proposed many-to-one encoder, cross-dataset action data are encouraged to possess identical encoded features if the actions share the same class labels. Experiments on pairs of benchmark human action datasets achieved state-of-the-art accuracy, proving the efficacy of the proposed method.

Authorship Identification using Generalized Features and Analysis of Computational Method

Authorship Identification is being used for forensics analysis and humanities to identify the author of anonymous text used for communication. Authorship Identification can be achieved by selecting the textual features or writing style. Textual features are the important elements for Authorship Identification .It is therefore important to analyze them and identify the most promising features. This paper tries to identify and analyze promising generalized features and computational methods for authorship Identification. The performed experiments in the authorship identification task shows that, the support vector machine classifier used as computational method can achieve better results with identified generalized feature set.

The role of focal versus generalized epilepsy classification and EEG features on antiepileptic drug choice

The role of focal versus generalized epilepsy classification and EEG features on antiepileptic drug choice

"Gentlemen-type rules" and "back room deals" in public participation: natural resource management and a fractured state in North Carolina

This paper examines the political ecology of a participatory environmental management setting. It argues the failure of participatory forums to meet their goals reveals more generalized features of the state, namely its fractured quality and inconsistent actions. Thus, rather than premise questions of how participatory forums might be more effective, researchers should first consider what cleavages and inconsistencies in the state that participatory forums reveal. How do the various actors involved negotiate these cleavages and inconsistencies? The paper explores disputes surrounding the Cape Hatteras National Seashore, North Carolina, USA. The argument centers on whether or not off-road vehicles might access the Seashore. Parties to the dispute have lobbied elected representatives, participated in a public forum, enacted litigation, and carried out campaigns of public admonishment. While using one part of the state to counteract the actions of another, supporters of off-road vehicles proffer a moral assessment which contrasts "gentlemen-type rules" with "backroom deals". The paper argues this rhetoric acts as a kind of cultural script that people use to corral heterogeneous state institutions into a single discursive framework that premises the kind of face-to-face relations where they are more likely to achieve their goals.Keywords: conservation; state formation; environmentality; environmental governance

A NEW GENERALIZED PAUCITUBERCULATAN MARSUPIAL FROM THE OLIGOCENE OF BOLIVIA AND THE ORIGIN OF ‘SHREW‐LIKE’ OPOSSUMS

Abstract: Insights into the origin of ‘shrew‐like’ oposssums of South America are gained thanks to a new fossil from the Oligocene Salla Beds in Bolivia. The specimen described here consists of a partial rostrum, palate and postcanine teeth, and shows several generalized features (cranial and dental) in the context of the Paucituberculata. On this basis we recognize Evolestes hadrommatos gen. et sp. nov. In order to evaluate the affinities of the new taxon, we performed a phylogenetic analysis including representatives of the Caenolestidae, Pichipilus and allies (not regarded here as caenolestids), Palaeothentidae, and Abderitidae, with three outgroups. Evolestes is the basalmost ‘caenolestoid’, and provides clues to the morphological changes involved in the origin of caenolestids.

Construction of Classifiers by Iterative Compositions of Features with Partial Knowledge

We consider the classification problem to construct a classifier c :{0,1}n |-> {0,1} from a given set of examples (training set), which (approximately) realizes the hidden oracle y :{0,1}n |-> (0,1) describing the phenomenon under consideration. For this problem, a number of approaches are already known in computational learning theory; e.g., decision trees, support vector machines (SVM), and iteratively composed features (ICF). The last one, ICF, was proposed in our previous work (Haraguchi et al., (2004)). A feature, composed of a nonempty subset S of other features (including the original data attributes), is a Boolean function fS : {0,1}S |-> {0,1} and is constructed according to the proposed rule. The ICF algorithm iterates generation and selection processes of features, and finally adopts one of the generated features as the classifier, where the generation process may be considered as embodying the idea of boosting, since new features are generated from the available features. In this paper, we generalize a feature to an extended Boolean function fS :{0,1,*}S |-> {0,1,*} to allow partial knowledge, where * denotes the state of uncertainty. We then propose the algorithm ICF* to generate such generalized features. The selection process of ICF* is also different from that of ICF, in that features are selected so as to cover the entire training set. Our computational experiments indicate that ICF* is better than ICF in terms of both classification performance and computation time. Also, it is competitive with other representative learning algorithms such as decision trees and SVM.

Unsupervised and supervised exploitation of semantic domains in lexical disambiguation

Domains are common areas of human discussion, such as economics, politics, law, science, etc., which are at the basis of lexical coherence. This paper explores the dual role of domains in word sense disambiguation (WSD). On one hand, domain information provides generalized features at the paradigmatic level that are useful to discriminate among word senses. On the other hand, domain distinctions constitute a useful level of coarse grained sense distinctions, which lends itself to more accurate disambiguation with lower amounts of knowledge. In this paper we extend and ground the modeling of domains and the exploitation of WordNet Domains, an extension of WordNet in which each synset is labeled with domain information. We propose a novel unsupervised probabilistic method for the critical step of estimating domain relevance for contexts, and suggest utilizing it within unsupervised domain driven disambiguation for word senses, as well as within a traditional supervised approach. The paper presents empirical assessments of the potential utilization of domains in WSD at a wide range of comparative settings, supervised and unsupervised. Following the dual role of domains we report experiments that evaluate both the extent to which domain information provides effective features for WSD, as well as the accuracy obtained by WSD at domain-level sense granularity. Furthermore, we demonstrate the potential for either avoiding or minimizing manual annotation thanks to the generalized level of information provided by domains.

A reevaluation of Proneotherium repenningi from the Miocene Astoria Formation of Oregon and its position as a basal odobenid (Pinnipedia: Mammalia)

ABSTRACT New crania, dentitions, and postcrania of the fossil pinniped, Proneotherium repenningi are described from the early to middle Miocene-age Astoria Formation of Lincoln County, Oregon. This sample includes specimens of four adult individuals; all probably males. The skull of Proneotherium repenningi shares many generalized features with basal pinnipeds (e.g., species of Enaliarctos) including its overall elongation, low profile, low sagittal crest, well developed lambdoidal crests, slender zygomatic arches, small orbits, slightly arched palate, dental formulae, and distinct embrasure pit. Proneotherium, however, differs from species of Enaliarctos in possession of a continuous and horizontal crest connecting the mastoid and paroccipital processes and in having a less secodont dentition. The molariform premolar dentition of Proneotherium is noteworthy and can be interpreted as representing the initial stage in a morphologic series that extends through Neotherium to Imagotaria. This morphologic series reflects a functional change from a shearing dentition to more of a piercing dentition and from a dentition capable of processing food (i.e., chewing) to a dentition that serves primarily to seize and hold prey. The hindlimb anatomy of Proneotherium provides important information concerning the evolution of aquatic adaptations and clearly shows that many pinniped innovations (short and broad femur, long and slender tibia, and elongated metatarsals I and V [relative to metatarsal III]) evolved very early. Evaluation of available specimens of Proneotherium supports recognition of a single species, Proneotherium repenningi. A cladistic analysis utilizing 24 cranial, dental and postcranial characters supports monophyly of the genus Proneotherium and suggests a close sister group relationship with another basal walrus, Prototaria. The parsimony analysis also confirms the monophyly of the Odobenidae, which is here defined as the clade containing the most recent common ancestor of Proneotherium and Odobenus and all of its descendants including Prototaria, Neotherium, Imagotaria, the dusignathines, and the odobenines.

Focal cortical-subcortical calcifications (FCSCs) and epilepsy in the Indian subcontinent.

A focal cortical-subcortical calcification (FCSC) is a common finding on computed tomography (CT) in individuals with focal or generalized seizures in the Indian subcontinent. We sought to determine the relation of FCSCs to epilepsy by comparing the lobe of seizure origin by electroclinical and CT evaluations and to study the nature and severity of epilepsy associated with FCSCs. The relation of these FCSCs to epilepsy/seizures was studied in 40 patients, seen for the first time to the neurology outpatient department of a tertiary care hospital. An attempt was made to classify seizures and determine their lobe of origin based on clinical-electroencephalographic (EEG) criteria of the International League Against Epilepsy (ILAE). The clinical lobe of origin was compared with the location of the FCSC on CT scan. In addition, records of the CT unit of the same hospital were reviewed retrospecitvely, to identify cases with an FCSC and their referral diagnoses. Thirty-one (77.5%) patients with FCSCs were considered to have localization-related epilepsy (frontal lobe epilepsy, 20; temporal lobe epilepsy, three; parietal lobe epilepsy, one; occipital lobe epilepsy, three; and definitely localization related but having ambiguous localization features, four) based on ictal semiology and EEG studies. Other ILAE categories in the cohort included epilepsy without unequivocal focal or generalized features (four patients; 10%), isolated seizures (one patient; 2.5%), juvenile absence epilepsy (one patient; 2.5%), and insufficient data to classify epilepsy (three patients; 7.5%). Radiologic sites for FCSCs included frontal (20; 50%), temporal (six; 15%), parietal (seven; 17.5%), and occipital (seven; 17.5%). Electroclinical and radiologic data were congruent in localizing and lateralizing seizures in 22 (55%) patients. The FCSC was truly incidental in one patient with juvenile absence epilepsy. Discordance between the clinical and radiologic localizations was noted in five (12.5%) instances. Magnetic resonance imaging (MRI) did not reveal additional lesions corresponding to lobes of origin as determined by electroclinical analysis. Discordance was surmised to be a result of seizure spread from a silent region to symptomatic cortex. In 12 (30%) patients, electroclinical and radiologic congruence could not be ascertained because ictal descriptions were either inadequate or ambiguous, and EEG findings were noncontributory. Review of 4,452 CT scans of brain performed in the CT unit revealed 29 (0.65%) cases with FCSCs in individuals with nonseizure disorders, that could be labeled as incidental. An FCSC is an important radiologic finding in localization-related epilepsy in the Indian subcontinent. The severity of epilepsy ranges from asymptomatic cases to daily seizures.

Benign familial neonatal convulsions: abnormal intrauterine movements, provocation by feeding and ICTAL EEG

An infant with benign familial neonatal convulsions had abnormal movements during the last 2 months of pregnancy suggestive of intrauterine seizures. His postnatal seizures, one of which was captured by electroencephalography, had both partial and generalized features. Most seizures appeared to be provoked by feeding.

American Trypanosomosis:In Situand Generalized Features of Parasitism and Inflammation Kinetics in a Murine Model

Monteón, V. M., Furuzawa-Carballeda, J., Alejandre-Aguilar, R., Aranda-Fraustro, A., Rosales-Encina, J. L., and Reyes, P. A. 1996. American trypanosomiasis:In situand generalized features of parasitism and inflammation kinetics in a murine model.Experimental Parasitology83, 267–274. Mimicking the natural conditions of mammalian infection, metacyclic trypomastigote forms of a Mexican isolate (Ninoa) ofTrypanosoma cruziwere inoculated into mice in order to study inflammation kinetics and parasite clearance at the inoculation site, parasite tropism to different organs, and local inflammatory cell infiltrates. Polymorphonuclear cells were detected at the inoculation site as early as 1 hr after inoculation. Peak cell infiltrate was observed at 24 hr; at 96 hr polymorphonuclear cells had disappeared. Mononuclear cell infiltrates began at 24 hr, peaking at Day 15, and then stared disappearing by Day 30. Antigens and parasites were detected by conventional techniques up to 15 min and thereafter became undetectable. Amplification of the hypervariable region of kinetoplast minicircle DNA by polymerase chain reaction was positive from 24 hr to Day 15, and the reaction became negative on Day 30. Myositis was observed in skeletal muscle from Days 7 to 180, it progressed from slight to severe, with an inflammation process which included macrophages, plasmatic cells, and a few eosinophils, the phenotype of the infiltrating cells included LyT2+and LyT1+on Day 30, and both cell populations decreased in parallel on Day 180. Antigen and parasite nests were present from Days 15 to 180; in muscle the earliest time at which minicircle DNA was detected was Day 7 and it was present until Day 180. Myocarditis was also observed; it developed from slight to severe in between Days 7 and 30, then gradually decreased, and cleared up. Mononuclear cell infiltrates in the myocardium were present from Days 7 to 180. Antigen and parasite nests were detected at Days 15 and 30 and disappeared at Day 180, although minicircle DNA was detected until the last day of observation. Both skeletal and heart muscles showed inflammatory reaction foci containingT. cruziantigen. There was twice the number of foci in heart as in skeletal muscle. This ratio was maintained by Day 30; later skeletal muscle showed persistent inflammation which was practically cleared up in the heart. Parasites or antigen were not detected by Day 180 in both skeletal and cardiac muscle; however, minicircle DNA was amplified, indicating that an small proportion of parasites evaded immune response. According to these data, Mexican Ninoa Strain has a classification as biodeme 3.

Classification of epilepsies and epileptic syndromes in a child neurology unit

We attempted to classify, according to the 1989 International Classification of Epilepsies and Epileptic Syndromes, 1076 patients examined during a 4-year period (1 January 1988 to 31 December 1991) in the Child Neurology Unit. We aimed to determine the proportion of the clearly defined epileptic syndromes or the non-specific categories of the International Classification of Epilepsies and Epileptic Syndromes, to estimate the relative incidence of different categories and to review the criteria for defining epileptic syndromes. The proportion in categories as defined by the International Classification of Epilepsies and Epileptic Syndromes in our patients was as follows. Localization-related epilepsies and syndromes: idiopathic 3.15%, symptomatic 17%, cryptogenic 9.20%. Generalized epilepsies and syndromes: idiopathic 20.35%, cryptogenic or symptomatic 14.68%, symptomatic 11.5%. Epilepsies and syndromes undetermined whether focal or generalized: with both generalized and focal seizures 7.8%, without unequivocal focal or generalized features 1.68%. Special syndromes: situation-related seizures: febrile convulsions 12.83%, isolated seizures or isolated status epilepticus 1.02%, seizures due to an acute toxic or metabolic event 1.20%. The presence of non-specific categories in the International Classification of Epilepsies and Epileptic Syndromes enables the categorization of all patients but it gives the false impression of diagnostic precision to what are essentially uncertain cases.

A generalized method for 3D object location from single 2D images

A method is presented to solve for the three-dimensional (3D) object position and orientation from single two-dimensional (2D) images based on a systematic hierarchy of features: primitive features, generalized features, and compound structures. A virtual viewpoint analysis shows that a feature-centered coordinate system allows us to drastically reduce the mathematical complexity of the inverse projection problem for higher order curves. At the heart of the matchings are the matching functions for primitive features, which are: point-to-point correspondence, line-to-line correspondence, and ellipse-to-ellipse correspondence. Parametric matching by generalized features is used to solve for viewpoints at any stage of matching. The generalized features can be viewed as the generalization of features used by previous researchers. The matching method goes “top-down” and then “bottom- up”, if necessary. Models of the objects are analyzed first. In the top-down process, search starts from the most complex features to the least complex features. In the bottom-up process, the least complex generalized features are used to solve for initial viewpoints. The viewpoints are further refined by matching the compound structures which are obtained by merging the consistent generalized features. The contributions include: (1) solving the problem of ellipse-to-ellipse correspondence, thus extending the class of recognizable objects; (2) the generalized features can assume various configurations, thus enabling the system to detect a multitude of features; (3) parametric matching instead of point-point matching makes the algorithm robust; (4) the top-down-bottom-up strategy combines efficiency with robustness.

Selective predation by carp (Cyprinus carpio L.) on benthic molluscs in Skadar Lake, Yugoslavia

Analysis of predation by carp (Cyprinus carpio L.) on mollusc species in Skadar Lake, Yugoslavia, indicated both generalized and specific features of a predator‐prey interaction. Vertical distribution of molluscs in sediments seemed unrelated to predation rates by carp. Although size selective predation may occur, electivity indices appeared most related to shell shape and thickness. Of the three most abundant species, electivity was high for Valvata piscinalis but low for Pyrgula annulata and Dreissencia polymorpha. Valvata has a more readily crushed shell, a higher proportion of occupied shells and a greater percentage of organic content than Pyrgula. Although a potentially preferred prey item, Dreissencia probably escaped intensive predation by being attached to larger objects. Carp appeared to utilize a sequence of tactile and gustatory cues in the prey selection process.