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Author(s):  
Sugondo Hadiyoso ◽  
Inung Wijayanto ◽  
Suci Aulia

Mild cognitive impairment (MCI) was a condition beginning before more serious deterioration, leading to Alzheimer’s dementia (AD). MCI detection was needed to determine the patient's therapeutic management. Analysis of electroencephalogram (EEG) coherence is one of the modalities for MCI detection. Therefore, this study investigated the inter and intra-hemispheric coherence over 16 EEG channels in the frequency range of 1-30 Hz. The simulation results showed that most of the electrode pair coherence in MCI patients have decreased compared to normal elderly subjects. In inter hemisphere coherence, significant differences (p<0.05) were found in the FP1-FP2 electrode pairs. Meanwhile, significant differences (p<0.05) were found in almost all pre-frontal area connectivity of the intra-hemisphere coherence pairs. The electrode pairs were FP2-F4, FP2-T4, FP1-F3, FP1-F7, FP1-C3, FP1-T3, FP1-P3, FP1-T5, FP1-O1, F3-O1, and T3-T5. The decreased coherence in MCI patients showed the disconnection of cortical connections as a result of the death of the neurons. Furthermore, the coherence value can be used as a multimodal feature in normal elderly subjects and MCI. It is hoped that current studies may be considered for early detection of Alzheimer’s in a larger population.


Author(s):  
Amitabh Thapliyal ◽  
Om Prakash Verma ◽  
Amioy Kumar

<p><span>The usage of mobile phones has increased multifold in the recent decades mostly because of its utility in most of the aspects of daily life, such as communications, entertainment, and financial transactions. Feature phones are generally the keyboard based or lower version of touch based mobile phones, mostly targeted for efficient calling and messaging. In comparison to smart phones, feature phones have no provision of a biometrics system for the user access. The literature, have shown very less attempts in designing a biometrics system which could be most suitable to the low-cost feature phones. A biometric system utilizes the features and attributes based on the physiological or behavioral properties of the individual. In this research, we explore the usefulness of keystroke dynamics for feature phones which offers an efficient and versatile biometric framework. In our research, we have suggested an approach to incorporate the user’s typing patterns to enhance the security in the feature phone. We have applied k-nearest neighbors (k-NN) with fuzzy logic and achieved the equal error rate (EER) 1.88% to get the better accuracy. The experiments are performed with 25 users on Samsung On7 Pro C3590. On comparison, our proposed technique is competitive with almost all the other techniques available in the literature.</span></p>


2022 ◽  
Vol 6 (POPL) ◽  
pp. 1-30
Author(s):  
Matthew Kolosick ◽  
Shravan Narayan ◽  
Evan Johnson ◽  
Conrad Watt ◽  
Michael LeMay ◽  
...  

Software sandboxing or software-based fault isolation (SFI) is a lightweight approach to building secure systems out of untrusted components. Mozilla, for example, uses SFI to harden the Firefox browser by sandboxing third-party libraries, and companies like Fastly and Cloudflare use SFI to safely co-locate untrusted tenants on their edge clouds. While there have been significant efforts to optimize and verify SFI enforcement, context switching in SFI systems remains largely unexplored: almost all SFI systems use heavyweight transitions that are not only error-prone but incur significant performance overhead from saving, clearing, and restoring registers when context switching. We identify a set of zero-cost conditions that characterize when sandboxed code has sufficient structured to guarantee security via lightweight zero-cost transitions (simple function calls). We modify the Lucet Wasm compiler and its runtime to use zero-cost transitions, eliminating the undue performance tax on systems that rely on Lucet for sandboxing (e.g., we speed up image and font rendering in Firefox by up to 29.7% and 10% respectively). To remove the Lucet compiler and its correct implementation of the Wasm specification from the trusted computing base, we (1) develop a static binary verifier , VeriZero, which (in seconds) checks that binaries produced by Lucet satisfy our zero-cost conditions, and (2) prove the soundness of VeriZero by developing a logical relation that captures when a compiled Wasm function is semantically well-behaved with respect to our zero-cost conditions. Finally, we show that our model is useful beyond Wasm by describing a new, purpose-built SFI system, SegmentZero32, that uses x86 segmentation and LLVM with mostly off-the-shelf passes to enforce our zero-cost conditions; our prototype performs on-par with the state-of-the-art Native Client SFI system.


2022 ◽  
Vol 2 (2) ◽  
pp. 104-111
Author(s):  
Ahmad Fatoni ◽  
Muhamamd Zainuddin

Indonesia is one of the countries with the largest population in the world. Nearly 85% of Indonesia's population  is Muslim. One of the problems faced by the majority of the Indonesian population, especially those who are  Muslim, is the problem of the distribution of inheritance rights. Many Muslims no longer use the inheritance distribution system according to Islamic Shari'a due to the lack of heirs and lack of knowledge about the distribution of inheritance rights according to Islam so that inheritance issues are often a trigger for disputes that lead to flattening family relations. On the other hand, currently the technology that is developing rapidly is Android technology. Almost everyone has an Android-based mobile phone. Android itself is an operating system that runs on smartphones and adjusts specifications from low-end to high-end classes. Almost all vendors are currently developing their products with the Android operating system because the demand is increasing sharply. Based on the problems and conditions above, an expert system application for the distribution of inheritance based on Islamic law based on Android was made with the forward chaining method, which can help solve the problems faced by the community above


Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 207
Author(s):  
Luke Mansard ◽  
Christel Vaché ◽  
Julie Bianchi ◽  
Corinne Baudoin ◽  
Isabelle Perthus ◽  
...  

GSDME, also known as DFNA5, is a gene implicated in autosomal dominant nonsyndromic hearing loss (ADNSHL), affecting, at first, the high frequencies with a subsequent progression over all frequencies. To date, all the GSDME pathogenic variants associated with deafness lead to skipping of exon 8. In two families with apparent ADNSHL, massively parallel sequencing (MPS) integrating a coverage-based method for detection of copy number variations (CNVs) was applied, and it identified the first two causal GSDME structural variants affecting exon 8. The deleterious impact of the c.991-60_1095del variant, which includes the acceptor splice site sequence of exon 8, was confirmed by the study of the proband’s transcripts. The second mutational event is a complex rearrangement that deletes almost all of the exon 8 sequence. This study increases the mutational spectrum of the GSDME gene and highlights the crucial importance of MPS data for the detection of GSDME exon 8 deletions, even though the identification of a causal single-exon CNV by MPS analysis is still challenging.


2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Elena Rojano ◽  
Fernando M. Jabato ◽  
James R. Perkins ◽  
José Córdoba-Caballero ◽  
Federico García-Criado ◽  
...  

Abstract Background Protein function prediction remains a key challenge. Domain composition affects protein function. Here we present DomFun, a Ruby gem that uses associations between protein domains and functions, calculated using multiple indices based on tripartite network analysis. These domain-function associations are combined at the protein level, to generate protein-function predictions. Results We analysed 16 tripartite networks connecting homologous superfamily and FunFam domains from CATH-Gene3D with functional annotations from the three Gene Ontology (GO) sub-ontologies, KEGG, and Reactome. We validated the results using the CAFA 3 benchmark platform for GO annotation, finding that out of the multiple association metrics and domain datasets tested, Simpson index for FunFam domain-function associations combined with Stouffer’s method leads to the best performance in almost all scenarios. We also found that using FunFams led to better performance than superfamilies, and better results were found for GO molecular function compared to GO biological process terms. DomFun performed as well as the highest-performing method in certain CAFA 3 evaluation procedures in terms of $$F_{max}$$ F max and $$S_{min}$$ S min We also implemented our own benchmark procedure, Pathway Prediction Performance (PPP), which can be used to validate function prediction for additional annotations sources, such as KEGG and Reactome. Using PPP, we found similar results to those found with CAFA 3 for GO, moreover we found good performance for the other annotation sources. As with CAFA 3, Simpson index with Stouffer’s method led to the top performance in almost all scenarios. Conclusions DomFun shows competitive performance with other methods evaluated in CAFA 3 when predicting proteins function with GO, although results vary depending on the evaluation procedure. Through our own benchmark procedure, PPP, we have shown it can also make accurate predictions for KEGG and Reactome. It performs best when using FunFams, combining Simpson index derived domain-function associations using Stouffer’s method. The tool has been implemented so that it can be easily adapted to incorporate other protein features, such as domain data from other sources, amino acid k-mers and motifs. The DomFun Ruby gem is available from https://rubygems.org/gems/DomFun. Code maintained at https://github.com/ElenaRojano/DomFun. Validation procedure scripts can be found at https://github.com/ElenaRojano/DomFun_project.


2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Ruizhong Du ◽  
Jingze Wang ◽  
Shuang Li

Internet of Things (IoT) device identification is a key step in the management of IoT devices. The devices connected to the network must be controlled by the manager. For this purpose, many schemes are proposed to identify IoT devices, especially the schemes working on the gateway. However, almost all researchers do not pay close attention to the cost. Thus, considering the gateway’s limited storage and computational resources, a new lightweight IoT device identification scheme is proposed. First, the DFI (deep/dynamic flow inspection) technology is utilized to efficiently extract flow-related statistical features based on in-depth studies. Then, combined with symmetric uncertainty and correlation coefficient, we proposed a novel filter feature selection method based on NSGA-III to select effective features for IoT device identification. We evaluate our proposed method by using a real smart home IoT data set and three different ML algorithms. The experimental results showed that our proposed method is lightweight and the feature selection algorithm is also effective, only using 6 features can achieve 99.5% accuracy with a 3-minute time interval.


2022 ◽  
Vol 7 (4) ◽  
pp. 638-641
Author(s):  
I D Chaurasia ◽  
Yogita Chaurasia

To analyse the demographics and presenting features of patients presenting with optic neuritis and papillitis. Clinical profiles of 40 patients presenting with optic neuritis and papillitis at a tertiary care center were collected retrospectively and prospectively. Detailed medical and ophthalmic history was taken especially about mode, duration and course of the disease, drug intake, alcoholism, smoking, pregnancy, lactation, convulsions, pyrexia, history suggestive of TB, syphilis, neurological deficit. A comprehensive ophthalmological and neurological evaluation was done for each patient along with radiological work up. Patients were prospectively followed up for an average of three months. Females in the reproductive age group constituted largest number of the patients (61.8%) in the present series. Maximum patients (70%) were between 20-50 years of age. Vision was found to be affected in all the patients at presentation and most of them presented with vision CF or HM (35.4% and 29.25% respectively) while 4 patients had complete loss of vision. Two third (66.7%) of patients reported eye pain at presentation. Abnormal pupillary reaction was found in most patients with the most common being RAPD on swinging flash light which was seen in 85.4%. Equal percentage (39.5%) of patients presented with Blurred Hyperemic (BH) disc and ophthalmoscopically normal appearing disc. Onset and progression of disease was found to be rapid in most cases ranging from few hours to days. Visual recovery post treatment was found to be good with most eyes achieving vision 6/24 or better. Optic neuritis has varied clinical presentations. Most of our patients were young to middle aged females. The most common presenting features were decrease in vision ranging from slight to profound, eye pain and abnormal pupillary reaction. Morphological abnormalities in appearance of optic disc were also found in two third of cases.Rapid progression was noted in almost all cases. Most of the cases achieved a good outcome at the end of follow up period.


2022 ◽  
Vol 12 (01) ◽  
pp. 77-98
Author(s):  
Carme Ferré-Pavia ◽  
◽  
Mariona Codina ◽  

This article aims to analyze the strategies used by political parties on Instagram posts during the election campaign of November 10, 2019, in terms of their content and media resources, in a politainment environment. A total of 655 publications were analyzed, coming from state and autonomous Catalan parties, through content analysis with quantitative and interpretative focus. From a comparative point of view, a gap is found between new and old political parties in the use of Instagram, and it is evident that the use of per- sonalization varies between formations. In the case of Catalan parties, the campaign is mixed with the effects of the situation of their former leaders. With some exceptions, the programmatic proposals during the campaign are blurred in almost all cases. It is concluded that, on Instagram, the electoral narrative is constructed as a narrative of staged self-referential actions, with the context of the political events in the Catalan case.


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