Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinated Multi-Agent Learning

Many real world tasks involve multiple agents acting synchronously in a cooperative setting. Communication policy between multiple agents in most environments is often fixed. In [3], the authors come up with a new DQN [6] architecture to learn a communication policy in addition to the environment policy. In this work we extend the above architecture to a novel grid world environment. We use the above environmental setup to find correlation between the agents’ communication and environment policies. We show through extensive experimentation that architecture is able to learn effective communication policies while acting independently. Further, we analyze these communication policies to see if some patterns emerge.
Integration IMVIP 2019 : Irish Machine Vision and Image Processing 2019 Spatial Coherency in Colourisation

Automatic colourisation is the function of inferring colour information from a grey-scale prior and then combining the colour with the grey-scale to form a colourised version of the image. We identify Spatial Coherence as a particular weakness in methods that use Convolutional Neural Networks for colourisation. Generated colours do not adhere to semantic edges and are not consistent within boundaries where we would expect uniform colour. Spatial Coherence, while often evident to the human eye, does not yet have an objective metric. We show, by segmentation of the combined ab channels of the CIEL*a*b* colour space, that a segmentation based on CNN colourisation is poor. We argue the need for the development of metrics to evaluate a colourisation’s performance on Spatial Coherence.
Development of the Water Quality Index ( WQI ) to Assess Effects of Basin-wide Land-use Alteration on Coastal Marshes of the Laurentian Great Lakes

Development and use of biological indicators to monitor the status and trends of aquatic ecosystems such as streams and rivers (Karr 1981, 1991; Wichert 1995; Wichert and Rapport 1998), lakes (Hughes and Noss 1992) and inland freshwater wetlands (Keddy et al. 1993; Adamus et al. 2001; Weigel 2003) have become routine for many environmental agencies throughout the world (e.g. van Dam et al. 1998; U.S. EPA 2002). The ecological basis for using biological indicators is that the community of plants and animals will refl ect the overall condition or quality of the habitat. Suter (2001) has criticized that the goal of this form of environmental monitoring, which summarizes the overall effects of both natural and human-induced disturbances, is problematic because it does not address the causal relationship between the disturbance and the indicator, or in terms of environmental risk assessment, the measures of effect and the assessment endpoint, respectively. In many cases, the presumed human-induced disturbance is the associated increase in nutrient and sediment loading from conversion of forests in the watershed into agricultural and urban land (e.g. Field et al. 1996; Müller et al. 1998; Dodson and Lillies 2001; Wang et al. 2001). In other cases, however, site-level disturbances such as proximity to roads and highways (Nelson and Booth 2002; Eyles et al. 2003; Ourso CONTENTS
Using P 4 to Enable Scalable Intents in Software Defined Networks

When designing Software Defined Networks (SDNs), there is a risk that the additional abstractions available can result in reduced scalability and performance. One such abstraction, intents, are a way in which network administrators can express policies rather than having to define specific forwarding rules. This provides a benefit to administrators in allowing automatic network reconfiguration and fault tolerance. In this paper, we highlight the performance overheads associated with the intents framework from a popular SDN controller, ONOS. We propose a novel prototype that leverages source-based routing and programmable data planes using P4 in order to reduce the overheads of intent-based forwarding.
Detection of anchors ’ utterances in broadcast news using i-vector-based speaker similarity and temporal information

Accurate speech recognition of anchors’ speech in broadcast news programs is essential for indexing tasks such as topic extraction, summarization, and so on. Consequently, the number of anchors and all speech segments for each anchor are important aspects that must be evaluated correctly. This paper discusses the effectiveness of these two items based on speaker similarity using i-vector. In our proposed approach, first, each input audio source was segmented into four types of sound: speech, noise, silence, and music. Next, a clustering was performed using all speech segments to collect segments from the same speakers. In this clustering, cosine similarity from i-vector was used. However, it was difficult to extract sufficient speaker characteristics from short utterances. To address this problem, we considered the time intervals between successive pairs of speech segments and the existence of background noises, adding to the information obtained from i-vector. Among the detected speaker clusters, anchor clusters were obtained based on the heuristic that the ratio of the number of speech segments from anchors was much higher than that of other speakers. It was experimentally shown that the detection method of anchors’ speech using the proposed approach outperformed the method using conventional k-means clustering.
Petri Nets based Formal Modeling and Verification of Concurrent Systems

The assurance of required quality properties is one of the major challenge in SelfAdaptive Systems (SAS). Self-adaptive systems have the capability to adapt their dynamic behavior autonomously at runtime due to uncertain changes in the environment. Research in this field is being held since mid-sixties, and over the last decade the importance of self-adaptivity is being increased. In general a self-adaptive system is much difficult to specify and verify, because of its highly complex internal behavior and especially when time constraints are involved. In the proposed research, Colored Petri Net (CPN) formal language will be used to model self-adaptive multi-agent system. CPN is increasingly used to model self-adaptive complex concurrent systems due to its flexible formal specification and formal verification behavior. CPN is visually more expressive than simple Petri Nets enables diverse modeling approaches and provides a richer framework for such a complex formalism. The specification and verification of internal structure of each self-adaptive agent is being expressed through modal μ-calculus (Mμ ). We propose SMACS (Self-adaptive Multi-Agent Concurrent System) framework, that is specifically designed for complex architectures, those contain inter-connected components in a heterogenous way. All agents of SMACS are also known as intelligent agents due to their self-adaptation behavior. The internal structure of SMACS framework is based on MAPE-K feedback loop. Each phase of the feedback loop works as an internal agent known as; Monitor Int-Agent, Analyzer Int-Agent, Planer Int-Agent and Executer Int-Agent. The agents adapt and update their behavior through interaction with the environment by using the decentralized approach. The Liveness, Safeness and Deadlock-freedom properties of self-adaptive agents are being verified through the TAPA model checker. For implementation of SMACS framework, Traffic Monitoring System (TMS) and Smart Computer Lab (SCL) are chosen as case studies. CPN based state space analysis will also be done to verify the behavioral properties of the model. The general objective of the proposed system is to maximize the utility generated over some predetermined time horizon. This research will provide new direction for modeling and verification of concurrent system. The main idea behind this work is to achieve true concurrency of multiple interconnected self-adaptive agents with their dynamic behavior.
Do deep neural networks possess concept space grid cells ?

Place and grid-cells are known to aid navigation in animals and humans. Together 1 with concept cells, they allow humans to form an internal representation of the 2 external world, namely the concept space. We investigate the presence of such a 3 space in deep neural networks by plotting the activation profile of its hidden layer 4 neurons. Although place cell and concept-cell like properties are found, grid-cell 5 like firing patterns are absent thereby indicating a lack of path integration or feature 6 transformation functionality in trained networks. Overall, we present a plausible 7 inadequacy in current deep learning practices that restrict deep networks from 8 performing analogical reasoning and memory retrieval tasks. 9
Naïve Bayes , Decision Tree , and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval

The decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this study is to classify sharia cooperative loan history data using the Naïve Bayes algorithm, Decision Tree and SVM to predict the credibility of future customers. The results showed the accuracy of Naïve Bayes algorithm 77.29%, Decision Tree 89.02% and the highest Support Vector Machine (SVM) 89.86%.
Affine Projection Algorithm Based Decision Fusion for Cooperative Spectrum Sensing In Cognitive Radio Networks

Spectrum sensing is a main function in cognitive radio networks to detect the spectrum holes or unused spectrum. Cooperative spectrum sensing schemes are recently suggested and they provide fast and accurate results. In this paper, we suggested a new adaptive and cooperative spectrum sensing technique based on the affine projection algorithm (APA). In this method, each secondary user (SU) takes a binary decision by its local sensing of the spectrum using energy detector. Local decisions are then forward to the fusion center (FC), where definitive decision is taken on the status of the spectrum using adaptive filters. In our suggested technique, APA updates the weights of the adaptive filter by using the current and the 𝐿 − 1 delayed input signal vectors. Simulation results indicate that the suggested approach provides faster convergence speed and less steady state mean square error than the existing methods that are based on the normalized least mean square (NLMS) or the so-called kernel least mean square (KLMS) algorithm.
Master’s Thesis Educational Attainment, Ethnic groups and Social Mobility: Evidence from 8 African Countries Nijmegen School of Management Master’s in Economics Specialization: International Economics and Development

The paper studied how educational attainment moderates the effect of group characteristics on social mobility by measuring the difference of occupational levels between individuals and their parents. This study focuses on the ethnic groups in African countries since there is high diversity of ethnic groups within countries (Bates, 2000). Previous literatures show that individuals who belong in disadvantaged ethnic groups are less likely to increase social mobility (Bates, 2000; Modood, Loury, & Teles, 2005; Platt, 2005; Wallerstein, 2016). The study is examined the moderating effect on 3 group characteristics i.e. economic, educational and political characteristics. The hypotheses using the data of individuals from 64 ethnic groups in 8 African countries. The results show that educational attainment moderates the negative effect of individuals being in economically, and educationally disadvantaged ethnic groups and helps them increase their social mobility. Moreover, the study also found that educational attainment is important to individuals from advantaged groups to maintain their social class or increase their social mobility. Overall, the study emphasizes the importance of education as a powerful tool to increase social mobility in African countries.
Whoever You Want Me to Be: Personality and Incentives

What can employers learn from personality tests when applicants have incentives to misrepresent themselves? Using a within‐subject, laboratory experiment, we compare personality measures with and without incentives for misrepresentation. Incentivized personality measures are weakly to moderately correlated with non‐incentivized measures in all treatments. When test‐takers are given a job ad indicating that an extrovert (introvert) is desired, extroversion measures are positively (negatively) correlated with IQ. Among other characteristics, only locus of control appears related to faking on personality measures. Our findings highlight the identification challenges in measuring personality and the potential for correlations between incentivized personality measures and other traits.
SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval

With the explosive growth of video data in real applications, near-duplicate video retrieval (NDVR) has become indispensable and challenging, especially for short videos. However, all existing NDVR datasets are introduced for long videos. Furthermore, most of them are small-scale and lack of diversity due to the high cost of collecting and labeling near-duplicate videos. In this paper, we introduce a large-scale short video dataset, called SVD, for the NDVR task. SVD contains over 500,000 short videos and over 30,000 labeled videos of near-duplicates. We use multiple video mining techniques to construct positive/negative pairs. Furthermore, we design temporal and spatial transformations to mimic user-attack behavior in real applications for constructing more difficult variants of SVD. Experiments show that existing state-of-the-art NDVR methods, including real-value based and hashing based methods, fail to achieve satisfactory performance on this challenging dataset. The release of SVD dataset will foster research and system engineering in the NDVR area. The SVD dataset is available at https://svdbase.github. io.
Stress Concentration Factors ( SCFs ) in Circular Hollow Section CHS-toH-shaped Section Welded T-Joints under Axial Compression

The aim of this paper is to investigate the effects of non-dimensional geometric parameters on stress concentration factors (SCFs) of circular hollow section CHS brace-to-H-shaped section T-connections under axial compression. This type of welded joints is used increasingly in steel construction. However, its fatigue design is not covered by codes, and its fatigue strength has not been given the deserved attention by researchers. This research, however, bridges the gab on SCFs in this type of welded connections when being loaded in axial compression. here, parametric study based on the numerical analysis was performed to evaluate the effect of CHS brace diameter to H-shaped chord flange width ratio (β), H-shaped chord flange width to thickness ratio (2γ) and CHS brace thickness to H-shaped chord flange thickness ratio (τ) on SCFs in the brace and the chord of the connection. Based on practical considerations, the validity range of these parameters was 0.3 ≤ β ≤ 0.7, 16 ≤ 2γ ≤ 30 and 0.2 ≤ τ ≤ 0.1. Three-dimensional finite element (FE) study using commercial software ABAQUS was performed to study the hot spot stress distribution and hence SCFs in this type of welded joints. To begin with, the results of FEM were verified against available experimental data and good agreement was achieved. Afterwards, 48 joints were modeled in Abaqus to study the effect of geometrical parameter on SCFs in brace and chord. Based on the results of this extensive study, the effect of geometrical parameters was revealed. The paper, thus, shows that whilst β increases, SCFs in the brace and chord increases. Moreover, increasing the parameter 2γ results in an increase in SCFs in the two members. However, the change in τ has no significant effect on the SCFs in the brace or the chord. Values of SCFs are found to be between 2 and 7.
An Assessment of the Effects of Commercial Exploitation on the Pancake Tortoise , Malacochersus tornieri , in Tanzania

Ansrnacr. Pancake tortoises, flattened, rock-crevice dwelling testudinids of East Africa's SomaliaMasai floristic region, have been supplied to the commercial wildlife trade by exports from Tanzania since 1981. Collection and trade is concentrated between Arusha and Dodoma in north-central Tanzania. Compared to exploited habitats, unexploited habitats are characterized by significantly greater numbers of tortoises encountered per unit of search time, a larger proportion of multiple tortoise occupancies per crevice, and a higher proportion of adults. Isolation of suitable habitats coupled with this species' limited dispersal abilities and low recruitment rates make recovery of depleted populations unlikely. Commercial collecting is conducted through a well-organized, multitier system with minimal economic return for the actual collectors or local middlemen. No significant threats to survival of pancake tortoises other than commercial collecting were identified. We therefore recommend the severe curtailment of trade in pancake tortoises by Tanzania and recipient countries as the best method to halt further depletion.
SEMI-FLEXIBLE PROTEIN-LIGAND DOCKING USING A CONTROLLED GENETIC ALGORITHM

This work describes the design and implementation of a controlled genetic algorithm for a molecular docking process between protein-ligand complexes. This algorithm was designed to keep a range of values for a selection pressure, and genotypic and phenotypic diversity, and aimed to prevent premature convergence or being trapped in a local minimum energy. During the evolution process, these parameters are checked in each generation and when one of them is go out from the allowed interval, a controlled correction is applied to the population by replacement a number of individuals in a random mode. The best one is never replaced with this strategy. The controlled correction can be applied in a finite number of times to allow that this algorithm stops when the diversity is too small. Additionally, this designed genetic algorithm allows a refinement in the search of the best protein-ligand complex. This algorithm is divided into three zones, where each one develops a specific number of energy computations and a particular step for the angle rotation of the rotatable bonds present in the ligand. Transition from one zone to other needs a specific conversion operation of the values inside the chromosome. Finally, for the validation of this algorithm, 10 simulations were performed for two complexes: 1AI5 and 2TMN, and the obtained values showed an average RMSD value lower than 2. 5Å.
DISTRIBUTION AND POPULATION STATUS OF HIMALAYAN MONAL PHEASANT ( LOPHOPHORUSIMPEJANUS ) IN SALKHALA GAME RESERVE , NEELUM VALLEY AZAD JAMMU AND KASHMIR ( PAKISTAN )

Present study was carried out to determine distribution and population status of Himalayan Monal pheasant (Lophophorus impejanus) in Salkhala Game Reserve. This game reserve is an Endemic Bird Area in the Neelum valley within Western Himalayas, situated along ceasefire line between Pakistan and India. For data collection, study area was divided into three localities with eleven sub-localities. Systematic surveys were conducted in each sub-locality from March to September 2014, early in the morning (5:00-9:00am) and half an hour before evening. Distribution was determined by direct and indirect evidences including sighting, ground scratching, feathers, fecal material, foot prints, information collected from hunters, locals and wildlife staff. Populationof the bird was estimated by line transect method, laid down in the habitat of Himalayan Monal. The results indicated that this pheasant is distributed in all localities of the study area, preferring high altitude mountains with different aspects and slopes between 1900 mand 2600 m above sea level (asl). Overall population density of Himalayan Monal in the study area was 5.63 birds/km2. The highest density (6.81 birds/km2) was recorded in locality Khikhre-dohre, followed by locality Tehar-chhamman (5.33 birds/km2) and Chitta-pani (4.76 birds/km2). The sub-locality Dohre had highest population density (8.15 birds/km2) among eleven sub-localities.
Face Detector Video Audio Features LabelsVoice Activity Detection AlexNet Adam Optimization LSTM Model Training Prediction PredictionsFace Detector Video Features AlexNet

This paper presents a supervised learning method for automatic visual detection of the active speaker in multiparty interactions. The presented detectors are built using a multimodal multiparty interaction dataset previously recorded with the purpose to explore patterns in the focus of visual attention of humans. Three different conditions are included: two humans involved in taskbased interaction with a robot; the same two humans involved in task-based interaction where the robot is replaced by a third human, and a free three-party human interaction. The paper also presents an evaluation of the active speaker detection method in a speaker dependent experiment showing that the method achieves good accuracy rates in a fairly unconstrained scenario using only image data as input. The main goal of the presented method is to provide real-time detection of the active speaker within a broader framework implemented on a robot and used to generate natural focus of visual attention behavior during multiparty human-robot interactions.
Positron annihilation spectroscopy investigation of vacancy defects in neutron-irradiated 3 CSiC

Positron annihilation spectroscopy characterization results for neutron-irradiated 3C-SiC are described here, with a specific focus on explaining the size and character of vacancy clusters as a complement to the current understanding of the neutron irradiation response of 3C-SiC. Positron annihilation lifetime spectroscopy was used to capture the irradiation temperature and dose dependence of vacancy defects in 3C-SiC following neutron irradiation from 0.01 to 31 dpa in the temperature range from 380 to 790°C. The neutral and negatively charged vacancy clusters were identified and quantified. The results suggest that the vacancy defects that were measured by positron annihilation spectroscopy technique contribute very little to the transient swelling of SiC. In addition, coincidence Doppler broadening measurement was used to investigate the chemical identity surrounding the positron trapping sites. It was found that silicon vacancy–related defects dominate in the studied materials and the production of the antisite defect CSi may result in an increase in the probability of positron annihilation with silicon core electrons.