Search results for: semantic core

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Rui-heng Ray Huang

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This study compares the syntax and semantics of two kinds of passives in Mandarin Chinese: bèi passives and yóu passives. To express a Chinese equivalent for ‘The thief was taken away by the police,’ either bèi or yóu can be used, as in Xiǎotōu bèi/yóu jǐngchá dàizǒu le. It is shown in this study that bèi passives and yóu passives differ semantically and syntactically. The semantic observations are based on the theta theory, dealing with thematic roles. On the other hand, the syntactic analysis draws heavily upon the generative grammar, looking into thematic structures. The findings of this study are as follows. First, the core semantics of bèi passives is centered on the Patient NP in the subject position. This Patient NP is essentially an Affectee, undergoing the outcome or consequence brought up by the action represented by the predicate. This may explain why in the sentence Wǒde huà bèi/*yóu tā niǔqū le ‘My words have been twisted by him/her,’ only bèi is allowed. This is because the subject NP wǒde huà ‘my words’ suffers a negative consequence. Yóu passives, in contrast, place the semantic focus on the post-yóu NP, which is not an Affectee though. Instead, it plays a role which has to take certain responsibility without being affected in a way like an Affectee. For example, in the sentence Zhèbù diànyǐng yóu/*bèi tā dānrèn dǎoyǎn ‘This film is directed by him/her,’ only the use of yóu is possible because the post-yóu NP tā ‘s/he’ refers to someone in charge, who is not an Affectee, nor is the sentence-initial NP zhèbù diànyǐng ‘this film’. When it comes to the second finding, the syntactic structures of bèi passives and yóu passives differ in that the former involve a two-place predicate while the latter a three-place predicate. The passive morpheme bèi in a case like Xiǎotōu bèi jǐngchá dàizǒu le ‘The thief was taken away by the police’ has been argued by some Chinese syntacticians to be a two-place predicate which selects an Experiencer subject and an Event complement. Under this analysis, the initial NP xiǎotōu ‘the thief’ in the above example is a base-generated subject. This study, however, proposes that yóu passives fall into a three-place unergative structure. In the sentence Xiǎotōu yóu jǐngchá dàizǒu le ‘The thief was taken away by the police,’ the initial NP xiǎotōu ‘the thief’ is a topic which serves as a Patient taken by the verb dàizǒu ‘take away.’ The subject of the sentence is assumed to be an Agent, which is in a null form and may find its reference from the discourse or world knowledge. Regarding the post-yóu NP jǐngchá ‘the police,’ its status is dual. On the one hand, it is a Patient introduced by the light verb yóu; on the other, it is an Agent assigned by the verb dàizǒu ‘take away.’ It is concluded that the findings in this study contribute to better understanding of what makes the distinction between the two kinds of Chinese passives.

Keywords: affectee, passive, patient, unergative

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Authors: Natalia M. Nepomniashchikh

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The research focuses on Russian and English linguoculturemes Caucasian mountaineer and Scottish Highlander, the effort of comparative-contrastive analysis was made. In order to reach the aim, the analysis of the vocabulary definitions of the concepts under consideration was taken, which made it possible to build the lexical-semantic fields of both lexical items in Russian and English. This stage of research helped to turn to the linguistic-cultural fields construction. To build these fields, literary pieces containing the concepts under consideration and the items directly related to them were taken from the works about the Caucasus mountains and mountaineers living there by M. Yu. Lermontov and the ones by W. Scott devoted to the Scottish Highlands and their inhabitants. All collected data was systematized in schemes and tables reflecting the differences and intercrossing areas.

Keywords: lexemes, lexical items, lexical-semantic field, linguistic-cultural field, linguoculturemes

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Authors: Yogita Patil-Sen

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Magnetic nanoparticles such as those made of iron oxide have been widely explored as biocatalysts, contrast agents, and drug delivery systems. However, some of the challenges associated with these particles are agglomeration and biocompatibility, which lead to concern of toxicity of the particles, especially for drug delivery applications. Coating the particles with biocompatible materials such as lipids and peptides have shown to improve the mentioned issues. Thus, these core-shell type nanoparticles are emerging as the new class of nanomaterials for targeted drug delivery applications. In this study, various types of core-shell magnetic nanoparticles are prepared and characterized using techniques, such as Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Vibrating Sample Magnetometer (VSM) and Thermogravimetric Analysis (TGA). The heating ability of nanoparticles is tested under oscillating magnetic field. The efficacy of the nanoparticles as drug carrier is also investigated. The loading of an anticancer drug, Doxorubicin at 18 °C is measured up to 48 hours using UV-visible spectrophotometer. The drug release profile is obtained under thermal incubation condition at 37 °C and compared with that under the influence of oscillating field. The results suggest that the core-shell nanoparticles exhibit superparamagnetic behaviour, although, coating reduces the magnetic properties of the particles. Both the uncoated and coated particles show good heating ability, again it is observed that coating decreases the heating behaviour of the particles. However, coated particles show higher drug loading efficiency than the uncoated particles and the drug release is much more controlled under the oscillating magnetic field. Thus, the results strongly indicate the suitability of the prepared core-shell type nanoparticles as drug delivery vehicles and their potential in magnetic hyperthermia applications and for hyperthermia cancer therapy.

Keywords: core-shell, hyperthermia, magnetic nanoparticles, targeted drug delivery

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Authors: R. Rosazley, M. A. Izzati, A. W. Fareezal, M. Z. Shazana, I. Rushdan, M. A. Ainun Zuriyati

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This study focuses on production and characterizations of nanofibrillated cellulose (NFC) from kenaf core. NFC was produced by employing ultrasonic treatments in aqueous solution. Field emission scanning electron microscope (FESEM) and scanning transmission electron microscopy (STEM) were used to study the size and morphology structure. The chemical and characteristics of the cellulose and NFC were studied using Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), X-ray diffraction (XRD) and viscometer. Degrees of polymerization (DP) of cellulose and NFC were obtained via viscosity value. Results showed that 5 to 47 nm diameters of fibrils were measured. Moreover, the thermal stability of the NFC was increased as compared to the cellulose that confirmed by TGA analysis. It was also found that NFC had higher crystallinity and lower viscosity than the cellulose which were measured by XRD and viscometer, respectively. The NFC characteristics have enormous prospect related to bio-nanocomposite.

Keywords: crystallinity, kenaf core, nanofibrillated cellulose, ultrasonic

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Authors: Ayyoub Jamali, Jennie Edlund, Alena Kozlová

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This paper evaluates the monitoring, prevention, and enforcing mechanisms of the core values of international organisations (IOs) in a comparative human rights perspective. The IOs in focus are the European Union, the Council of Europe, the African Union, and the Organization of American States. The paper will take the founding treaties of these IOs and their relevant protocols as a starting point to identify the values and the mechanisms used for their implementation. It will explore the scope of violations, the procedures in place and evaluate what type of response to those breaches seems to work best in terms of achieving its declared objectives. The study will identify and compare the weaknesses and strengths of each mechanism used by the IOs and recognize common challenges and means, thereby drawing inter-organizational comparisons. Consequently, the findings of this paper can be used among the IOs to improve their system and thus enhance their effectiveness.

Keywords: international organizations, core values, human rights, enforcement mechanism, compliance

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Authors: Amira A. A. Abdallah, Amir A. Beltagi

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Background: Core stability training has recently attracted attention for improving muscle balance and optimizing performance in healthy and unhealthy individuals. Purpose: This study investigated the effect of beginner’s core stability exercises on trunk flexors’/extensors’ peak torque ratio and trunk flexors’ and extensors’ peak torques. Methods: Thirty five healthy individuals participated in the study. They were randomly assigned to two groups; experimental “group I, n=20” and control “group II, n=15”. Their mean age, weight and height were 20.7±2.4 vs. 20.3±0.61 years, 66.5±12.1 vs. 68.57±12.2 kg and 166.7±7.8 vs. 164.28 ±7.59 cm. for group I vs. group II. Data were collected using the Biodex Isokinetic system. The participants were tested twice; before and after a 6-week period during which group I performed a core stability training program. Results: The 2x2 Mixed Design ANOVA revealed that there were no significant differences (p>0.025) in the trunk flexors’/extensors’ peak torque ratio between the pre-test and post-test conditions for either group. Moreover, there were no significant differences (p>0.025) in the trunk flexion/extension ratios between both groups at either condition. However, the 2x2 Mixed Design MANOVA revealed significant increases (p<0.025) in the trunk flexors’ and extensors’ peak torques in the post-test condition compared with the pre-test in group I with no significant differences (p>0.025) in group II. Moreover, there was a significant increase (p<0.025) in the trunk flexors’ peak torque only in group I compared with group II in the post-test condition with no significant differences in the other conditions. Interpretation/Conclusion: The improvement in muscle performance indicated by the increase in the trunk flexors’ and extensors’ peak torques in the experimental group recommends including core stability training in the exercise programs that aim to improve muscle performance.

Keywords: core stability, isokinetic, trunk muscles, muscle balance

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Authors: Umar Saeed

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Peptidyl-prolyl cis/trans isomerases Par14 and Par17 in humans play crucial roles in diverse cellular processes, including protein folding, chromatin remodeling, DNA binding, ribosome biogenesis, and cell cycle progression. However, the effects of Par14 and Par17 on viral replication have been explored to a limited extent. We first time discovered their influential roles in promoting Hepatitis B Virus replication. In this study, we observed that in the presence of HBx, either Par14 or Par17 could upregulate HBV replication. However, in the absence of HBx, neither Par14 nor Par17 had any effect on replication. Their mechanism of action involves binding to specific motifs within HBc and HBx proteins. Notably, they target the conserved 133Arg-Pro134 (RP) motif of HBc and the 19RP20-28RP29 motifs of HBx. This interaction is fundamental for the stability of HBx, core particles, and HBc. Par14 and Par17 exhibit versatility by binding both outside and inside core particles, thereby facilitating core particle assembly through their participation in HBc dimer-dimer interactions. NAGE and immunoblotting analyses unveiled the binding of Par14/Par17 to core particles. Co-immunoprecipitation experiments further demonstrated the interaction of Par14/Par17 with core particle assembly-defective and dimer-positive HBc-Y132A. It's essential to emphasize that R133 is the key residue in the HBc RP motif that governs their interaction with Par14/Par17. Chromatin immunoprecipitation conducted on HBV-infected cells elucidated the participation of residues S19 and E46/D74 in Par14 and S44 and E71/D99 in Par17 in the recruitment of 133RP134 motif-containing HBc into cccDNA. Depleting PIN4 in liver cell lines results in a significant reduction in cccDNA levels, pgRNA, sgRNAs, HBc, core particle assembly, and HBV DNA synthesis. Notably, parvulin inhibitors like juglone and PiB have proven to be effective in substantially reducing HBV replication. These inhibitors weaken the interaction between HBV core particles and Par14/Par17, underscoring the dynamic nature of this interaction. It's also worth noting that specific Par14/Par17 inhibitors hold promise as potential therapeutic options for chronic hepatitis B.

Keywords: Par14Par17, HBx, HBc, cccDNA, HBV

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Authors: Thomas Ousterhout

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The purpose of this study was to investigate if incorporating meaningful pictures of gestures and facial expressions in short sentences of text could supplement the text with enough semantic information to produce and N400 effect when probe words incongruent to the picture were subsequently presented. Event-related potentials (ERPs) were recorded from a 14-channel commercial grade EEG headset while subjects performed congruent/incongruent reaction time discrimination tasks. Since pictures of meaningful gestures have been shown to be semantically processed in the brain in a similar manner as words are, it is believed that pictures will add supplementary information to text just as the inclusion of their equivalent synonymous word would. The hypothesis is that when subjects read the text/picture mixed sentences, they will process the images and words just like in face-to-face communication and therefore probe words incongruent to the image will produce an N400.

Keywords: EEG, ERP, N400, semantics, congruency, facilitation, Emotiv

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Authors: Sadeq Al Yaari, Fayza Alhammadi, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Saleh Al Yami

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Background: There has been a debate in the literature over the years as to whether or not MossTalk Words program fits Arab Broca’s aphasics (BAs) due to that language differences and also the fact that the technique has not yet been used for aphasics with semantic dementia (SD aphasics). Aims: To oversimplify the above mentioned debate slightly for purposes of exposition, the purpose of the present study is to investigate the “usability” of this program as well as pictures and community as therapeutic techniques for both Arab BAs and SD aphasics. Method: The subjects of this study are two Saudi aphasics (53 and 57 years old, respectively). The former suffers from Broca’s aphasia due to a stroke, while the latter suffers from semantic dementia. Both aphasics can speak English and have used the Moss Talk Words program in addition to intensive picture-naming therapeutic sessions for two years. They were tested by one of the researchers four times (a time per six months). The families of the two subjects, in addition to their relatives and friends, played a major part in all therapeutic sessions. Conclusion: Results show that in averages across the entire therapeutic sessions, MossTalk Words program was clearly found more effective in modeling BAs’ pronunciation than that of SD aphasic. Furthermore, picture-naming intensive exercises in addition to the positive role of the community members played a major role in the progress of the two subjects’ performance.

Keywords: moss talk words, program, technique, Broca’s aphasia, semantic dementia, subjects, picture, community

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Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

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Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Chin-Hsien Yeh, Shao-Wen Chen, Wen-Shu Huang, Chun-Fu Huang, Jong-Rong Wang, Jung-Hua Yang, Yuh-Ming Ferng, Chunkuan Shih

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In this research, a Fukushima-like conditions is simulated with TRACE and RELAP5. Fukushima Daiichi Nuclear Power Plant (NPP) occurred the disaster which caused by the earthquake and tsunami. This disaster caused extended loss of all AC power (ELAP). Hence, loss of ultimate heat sink (LUHS) happened finally. In order to handle Fukushima-like conditions, Taiwan Atomic Energy Council (AEC) commanded that Taiwan Power Company should propose strategies to ensure the nuclear power plant safety. One of the diverse and flexible coping strategies (FLEX) is a different water injection strategy. It can execute core injection at 20 Kg/cm2 without depressurization. In this study, TRACE and RELAP5 were used to simulate Maanshan nuclear power plant, which is a three loops PWR in Taiwan, under Fukushima-like conditions and make sure the success criteria of FLEX. Reducing core cooling ability is due to failure of emergency core cooling system (ECCS) in extended loss of all AC power situation. The core water level continues to decline because of the seal leakage, and then FLEX is used to save the core water level and make fuel rods covered by water. The result shows that this mitigation strategy can cool the reactor pressure vessel (RPV) as soon as possible under Fukushima-like conditions, and keep the core water level higher than Top of Active Fuel (TAF). The FLEX can ensure the peak cladding temperature (PCT) below than the criteria 1088.7 K. Finally, the FLEX can provide protection for nuclear power plant and make plant safety.

Keywords: TRACE, RELAP5/MOD3.3, ELAP, FLEX

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Authors: F. Arslan, S.D. Guven, A. Özcan, H. Vatansev, Ö. Taşgin

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Weight, hypertension and dyslipidemia control and increased physical activity are required for the treatment of metabolic syndrome (METS). The purpose of this study was to investigate the effect of core exercise, reflexology and intake chrome picolinate on METS. This study comprised a twelve-week randomized controlled trial. A total of 25 university workers with metabolic risk factors participated in this study voluntarily. They were randomly divided into three groups: Those undertaking a core exercise program (n=7), reflexology intervention group (n=8) and intake chrome group (n=10). The subjects took part in a core exercise program for one hour per day, three days a week and a reflexology interfered for thirty minutes per day, one days a week and chrome group took chrome picolinate every day in week for twelve weeks. The components of metabolic syndrome were analyzed before and after the completion of all the intervention. There were significant differences at pre-prandial blood glucose in the core exercise group and at systolic blood pressure in chrome group after the twelve week interventions (p < 0.005). While High Density Lipoprotein (HDL) excluding the components of METS decreased after the interventions on the all groups; levels of HDL and the other components of METS decreased in reflexology group. There was a clear response to the twelve-week interventions in terms of METS control. Besides, the reflexology intervention should not be applied to individuals with low HDL levels and core exercise and intake chrome picolinate suggested to improve the components of METS.

Keywords: blood pressure, body mass index, exercise, METS, pre-prandial blood glucose

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Authors: Ikediobi Lottanna Samuel

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Days are gone when perpetrators of core international crimes hide under the cloak of sovereignty to go with impunity. The principle of international criminal responsibility is a reality. This move to end impunity for violation of human rights has led to the creation of international and hybrid tribunals, a permanent international criminal court, and increased prosecution of human rights violations in domestic courts. This article examines the attempts by the international community to bring perpetrators of heinous crimes to book. The work reveals the inadequacy of the current international mechanism for prosecuting core international crimes in order to end the culture of impunity and entrench the culture of accountability. It also identifies that ad hoc international criminal tribunals and the international criminal court face similar challenges ranging from lack of cooperation by nation states, non-existence of hierarchy of crimes, lack of effective enforcement mechanism, limited prosecutorial capacity and agenda, difficulty in apprehending suspects, difficulty in blending different legal tradition, absence of a coherent sentencing guideline, distant location of courts, selective indictment, etc. These challenges adversely affect the functioning of these courts. It is suggested that a more helpful way to end impunity would be to have a more robust and synergistic relationship between national, regional, and international approaches to prosecuting core international crimes.

Keywords: prosecution, criminal, international, tribunal, justice, ad hoc

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Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

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Authors: Hyungmo Kim, Hwang Bae, Seok-Kyu Chang, Dong Won Lee, Yung Joo Ko, Sun Rock Choi, Hae Seob Choi, Hyeon Seok Woo, Dong-Jin Euh, Hyeong-Yeon Lee

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Flow mixing characteristics in the wire-wrapped 37-pin rod bundle were measured by using a wire-mesh sensing system for a sodium-cooled fast reactor (SFR). The subchannel flow mixing in SFR core subchannels was an essential characteristic for verification of a core thermal design and safety analysis. A dedicated test facility including the wire-mesh sensor system and tracing liquid injection system was developed, and the conductivity fields at the end of 37-pin rod bundle were visualized in several different flow conditions. These experimental results represented the reasonable agreements with the results of CFD, and the uncertainty of the mixing experiments has been conducted to evaluate the experimental results.

Keywords: core thermal design, flow mixing, a wire-mesh sensor, a wire-wrap effect

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Authors: Haluk Eren, Mucahit Karaduman

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This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, three-dimensional, smart city, scholarly search, semantic

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: Arpan Bera, Rini Ganguly, Raja Chakraborty, Amlan J. Pal

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To deal with the increasing demands for the high-density non-volatile memory devices, we need nano-sites with efficient and stable charge storage capabilities. We prepared nanocrystals (NCs) of inorganic perovskite, CsPbCl₃ coated with Cs₄PbCl₆, by colloidal synthesis. Due to the type-I band alignment at the junction, this core-shell composite is expected to behave as a charge trapping site. Using Scanning Tunneling Spectroscopy (STS), we investigated voltage-controlled resistive switching in this heterostructure by tracking the change in its current-voltage (I-V) characteristics. By applying voltage pulse of appropriate magnitude on the NCs through this non-invasive method, different resistive states of this system were systematically accessed. For suitable pulse-magnitude, the response jumped to a branch with enhanced current indicating a high-resistance state (HRS) to low-resistance state (LRS) switching in the core-shell NCs. We could reverse this process by using a pulse of opposite polarity. These two distinct resistive states can be considered as two logic states, 0 and 1, which are accessible by varying voltage magnitude and polarity. STS being a local probe in space enabled us to capture this switching at individual NC site. Hence, we claim a bright prospect of these core-shell NCs made of inorganic halide perovskites in future high density memory application.

Keywords: Core-shell perovskite, CsPbCl₃-Cs₄PbCl₆, resistive switching, Scanning Tunneling Spectroscopy

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Mahbobeh Bozhmehrani, Afshin Farah Bakhsh

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Nanoparticles with PbS core of 12 nm and shell of approximately 3 nm were synthesized at PbS:ZnS ratios of 1.01:0.1 using Merca Ptopropionic Acid as stabilizing agent. PbS/ZnS nanoparticles present a dramatically increase of Photoluminescence intensity, confirming the confinement of the PbS core by increasing the Quantum Yield from 0.63 to 0.92 by the addition of the ZnS shell. In this case, the synthesis by microwave method allows obtaining nanoparticles with enhanced optical characteristics than those of nanoparticles synthesized by colloidal method.

Keywords: Pbs/Zns, quantum dots, colloidal method, microwave

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Iyd Eqqab Maree, Habil Jurgen Bast

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Vibration control of machines and structures incorporating viscoelastic materials in suitable arrangement is an important aspect of investigation. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. Multilayered cantilever sandwich beam like structures can be used in aircrafts and other applications such as robot arms for effective vibration control. These members may experience parametric instability when subjected to time dependant forces. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. The purpose of the present work is to investigate the dynamic stability of a three layered symmetric sandwich beam (Drone Aircraft wings ) subjected to an end periodic axial force . Equations of motion are derived using finite element method (MATLAB software). It is observed that with increase in core thickness parameter fundamental buckling load increases. The fundamental resonant frequency and second mode frequency parameter also increase with increase in core thickness parameter. Fundamental loss factor and second mode loss factor also increase with increase in core thickness parameter. Increase in core thickness parameter enhances the stability of the beam. With increase in core loss factor also the stability of the beam enhances. There is a very good agreement of the experimental results with the theoretical findings.

Keywords: steel cantilever beam, viscoelastic material core, loss factor, transition region, MATLAB R2011a

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Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

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Authors: Antonio Piga

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The issue of European cultural identity has become a prominent topic of discussion among political actors in the wake of the unsuccessful referenda held in France and the Netherlands in May and June 2006. The „period of reflection‟ announced by the European Council at the conclusion of June 2006 has provided an opportunity for the implementation of several initiatives and programmes designed to „bridge the gap‟ between the EU institutions and its citizens. Specific programmes were designed with the objective of enhancing the European Commission‟s external communication of its activities. Subsequently, further plans for democracy, debate, and dialogue were devised with the objective of fostering open and extensive discourse between EU institutions and citizens. Further documentation on communication policy emphasised the necessity of developing linguistic techniques to re-engage disenchanted or uninformed citizens with the European project. It was observed that the European Union is perceived as a „faceless‟ entity, which is attributed to the absence of a distinct public identity vis-à-vis its institutions. This contribution presents an analysis of a collection of informative publications regarding the European Union, entitled “Europe on the Move”. This collection of booklets provides comprehensive information about the European Union, including its historical origins, core values, and historical development, as well as its achievements, strategic objectives, policies, and operational procedures. The theoretical framework adopted for the longitudinal linguistic analysis of EU discourse is that of Systemic Functional Linguistics (SFL). In more detail, this study considers two basic systems of relations between clauses: firstly, the degree of interdependency (or taxis) and secondly, the logico-semantic relation of expansion. The former refers to the structural markers of grammatical relations between clauses within sentences, namely paratactic, hypotactic and embedded relations. The latter pertains to various logicosemantic relationships existing between the primary and secondary members of the clause nexus. These relationships include how the secondary clause expands the primary clause, which may be achieved by (a) elaborating it, (b) extending it or (c) enhancing it. This study examines the impact of the European Commission‟s post-referendum communication methods on the portrayal of Europe, its role in facilitating the EU institutional process, and its articulation of a specific EU identity linked to distinct values. The research reveals that the language employed by the EU is evidently grounded in an explanatory logic, elucidating the rationale behind their institutionalised acts. Nevertheless, the minimal use of hypotaxis in the post-referendum booklets, coupled with the inconsistent yet increasing ratio of parataxis to hypotaxis, may suggest a potential shift towards a logic of appearance, characterised by a predominant reliance on coordination and additive, and elaborative logico-semantic relations.

Keywords: systemic functional linguistics, logic of appearance, explanatory logic, interdependency, logico-semantic relation

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Authors: G. K. Pandey, D. Ramadasu, I. Banerjee, V. Vinod, G. Padmakumar, V. Prakash, K. K. Rajan

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Detailed thermal hydraulic investigations are very essential for safe and reliable functioning of liquid metal cooled fast breeder reactors. These investigations are further more important for components with complex profile, since there is no direct correlation available in literature to evaluate the hydraulic characteristics of such components directly. In those cases available correlations for similar profile or geometries may lead to significant uncertainty in the outcome. Hence experimental approach can be adopted to evaluate these hydraulic characteristics more precisely for better prediction in reactor core components. Prototype Fast Breeder Reactor (PFBR), a sodium cooled pool type reactor is under advanced stage of construction at Kalpakkam, India. Several components of this reactor core require hydraulic investigation before its usage in the reactor. These hydraulic investigations on full scale models, carried out by experimental approaches using water as simulant fluid are discussed in the paper.

Keywords: fast breeder reactor, cavitation, pressure drop, reactor components

Procedia PDF Downloads 463