Reviewerly/exHarmony huggingface dataset:
BioResources to serve as host for Fundamental Research Symposia archives

The Fundamental Research Committee (FRC), founded in 1956 to organize regular symposia among pulp and paper scientists, has been aiming to widen access to their archival published proceedings. The FRC decided that it would be best to make their published work freely available on the web rather than continuing to offer CD versions for sale. They wanted to work together with an entity having experience with open access publishing. The FRC has selected BioResources as that entity, based on our 13-year record of open access service to the same branch of science and technology. BioResources is honored to take on this role and accordingly will henceforth prominently list the “Fundamental Research Symposia Archives” on our web page with links to the FRC content.
Human face images from multiple perspectives with lighting from multiple directions with no occlusion, glasses and hat

Facial and other human recognition techniques are being used for a growing number of applications, ranging from device security to surveillance video identification to forensics. Data sets are required to test recognitions algorithms. This data set facilitates the evaluation of the impact of multiple factors on algorithm performance. The data set includes images taken under five different lighting levels (which vary in light brightness and temperature), seven different lighting positions and five different subject positions. The data set includes data collected for all combinations of the foregoing three collection variables, for a total of 175 images per subject. In addition, sets of data under three different occlusion conditions (no occlusion, glasses and hat) have been collected. Each data set includes images taken under all lighting level, lighting position and subject position combinations, for a total of 525 images of each subject. The images are all taken in the same location with the same background and camera equipment.
Supervised Policy Update for Deep Reinforcement Learning

We propose a new sample-efficient methodology, called Supervised Policy Update (SPU), for deep reinforcement learning. Starting with data generated by the current policy, SPU formulates and solves a constrained optimization problem in the non-parameterized proximal policy space. Using supervised regression, it then converts the optimal non-parameterized policy to a parameterized policy, from which it draws new samples. The methodology is general in that it applies to both discrete and continuous action spaces, and can handle a wide variety of proximity constraints for the non-parameterized optimization problem. We show how the Natural Policy Gradient and Trust Region Policy Optimization (NPG/TRPO) problems, and the Proximal Policy Optimization (PPO) problem can be addressed by this methodology. The SPU implementation is much simpler than TRPO. In terms of sample efficiency, our extensive experiments show SPU outperforms TRPO in Mujoco simulated robotic tasks and outperforms PPO in Atari video game tasks.
Mineralogical and Geochemical Studies of Oil Shale Deposits in the Cretaceous/Paleogene succession at Quseir Area, Egypt

Cretaceous/Paleogene succession in Quseir area represents one of the most important economic sedimentary rocks, which contain phosphate and oil shale beds. Oil shale samples selected from nine mines around Quseir area were subjected to mineralogical, petrographical and geochemical analyses. As raveled by X-ray diffraction analysis, the oil shale samples are composed of calcite, quartz, dolomite, smectite, kaolinite, gypsum and pyrite. The petrographical investigation of the studied oil shales indicates the dominance of two microfacies: calcareous foraminiferal claystone and Calci-mudstone. The EDX results of oil shale samples show that the pyrite found as framboidal-disseminated particles in smectite. The high ratio of the sulfur and organic carbon contents in the selected mines indicate highly reducing environment. Five mines (El-Nakheil, Abu Tundub, Abu Tundub Bahree, El Beida and Hammadat) are markedly rich in organic content and can be considered as good to excellent source rock.
Personalised Fashion Recommendation using Deep Learning

Clothing we wear reveals our personal style - wealth, occupation, religion, location and socio-identity. Shopper's aesthetic preferences thus influence purchasing decision in a lifestyle marketplace. Given the image of a fashion item, recommending complementary matches is a challenge. This tutorial discusses various techniques for fashion recommendation which in turn enhance conventional data mining approaches like collaborative filtering and matrix factorization. For a few such models and methods, we outline results using real-world data from various online shopping platforms. Recent advances in deep learning are presented for compatibility modeling, learning-to-rank and explainable recommendation.
A capacity-based framework encompassing Belnap–Dunn logic for reasoning about multisource information

Belnap–Dunn four-valued logic is one of the best known logics for handling elementary information items coming from several sources. More recently, a conceptually simple framework, namely a two-tiered propositional logic augmented with classical modal axioms (here called BC logic), was suggested by the second author and colleagues, for the handling of multisource information. It is a fragment of the non-normal modal logic EMN, whose semantics is expressed in terms of two-valued monotonic set functions called Boolean capacities. We show BC logic is more expressive than Belnap–Dunn logic by proposing a consequence-preserving translation of Belnap–Dunn logic in this setting. As special cases, we can recover already studied translations of three-valued logics such as Kleene and Priest logics. Moreover, BC logic is compared with the source-processor logic of Avron, Ben Naim and Konikowska. Our translation bridges the gap between Belnap–Dunn logic, epistemic logic, and theories of uncertainty like possibility theory or belief functions, and paves the way to a unified approach to various methods for handling inconsistency due to several conflicting sources of information.
Is the ‘hate’ in hate speech the ‘hate’ in hate crime? Waldron and Dworkin on political legitimacy

Among the most persuasive arguments against hate speech bans was made by Ronald Dworkin, who warned of the threat to political legitimacy posed by laws that deny those subject to them adequate opportunity for dissent. In his influential defence of hate speech bans, Jeremy Waldron addresses these objections. Dworkin’s concern with political legitimacy is misplaced, he argues, given the provision speech bans make for substituting permissible modes of expression for impermissible ones. I argue that this defence of speech bans misidentifies the ‘hate’ in hate speech with the ‘hate’ in hate crime. In contesting Dworkin, Waldron fails to contend with the necessarily entangled criminalisation of manner and viewpoint entailed in hate speech bans. By failing to grapple with the way in which every linguistic sign is constituted by both manner and viewpoint, Waldron sidesteps the ways in which hate speech bans undermine political legitimacy within liberal democracies.
The Effects of Bank Regulation on Financial Development in the MENA Countries: The Supporting Role of Supervision

This study investigates the impact of bank regulation on financial development in the MENA countries for the period 1995-2014. Restrictions on activity, foreign banks, and capital were used as proxies for bank regulation. Also, bank supervisory power, independence, private monitoring, and moral hazard were used as proxies for bank supervision. Liquid liabilities, private credit, and z-score were chosen as proxies for financial development. They represent, consecutively, size, activity, and stability of the financial sector. A positive and significant impact of bank regulation was observed on all measures of financial development. The most important contribution of the present study is that, it gives evidence of an important supporting role of supervision on bank regulation, to realize its desired impact on financial development. This final result is important for the MENA countries, since data analysis shows that financial sector reform is more concentrated on regulation than supervision. Policy makers in the MENA countries need to focus more, in their financial sector reform, on bank supervision to realize the expected impact of bank regulation on financial development.
Robotic Task Planning Using a Backchaining Theorem Prover for Multiplicative Exponential First-Order Linear Logic

In this paper, we propose an exponential multiplicative fragment of linear logic to encode and solve planning problems efficiently in STRIPS domain, that we call the Linear Planning Logic (LPL). Linear logic is a resource aware logic treating resources as single use assumptions, therefore enabling encoding and reasoning of domains with dynamic state. One of the most important examples of dynamic state domains is robotic task planning, since informational or physical states of a robot include non-monotonic characteristics. Our novel theorem prover is using the backchaining method which is suitable for logic languages like Lolli and Prolog. Additionally, we extend LPL to be able to encode non-atomic conclusions in program formulae. Following the introduction of the language, our theorem prover and its implementation, we present associated algorithmic properties through small but informative examples. Subsequently, we also present a navigation domain using the hexapod robot RHex to show LPL’s operation on a real robotic planning problem. Finally, we provide comparisons of LPL with two existing linear logic theorem provers, llprover and linTAP. We show that LPL outperforms these theorem provers for planning domains.
Testing for constituents: A response from Functional Discourse Grammar

Timothy Osborne has surveyed a very large number of published introductions to grammatical analysis, all of which share the assumption that syntactic argumentation is to be conducted without reference to the meanings, uses and contexts of the example sentences. The purpose of Osborne’s article is to examine how well syntactic tests identify subphrasal strings as constituents. The aim of this discussion note is not to engage directly with this issue but to consider, from the viewpoint of Functional Discourse Grammar (FDG), the validity of the autonomous syntax assumption shared by Osborne and the authors whose work he considers. The note dwells on the hidden presence of functional and interactive notions in a methodology based on syntactic ‘tests’ and it is suggested that the difficulties encountered by that methodology (notably with regard to coordination) can be resolved insightfully by FDG with its four levels of analysis.
Public Key Infrastructure (PKI)

A Public Key Infrastructure is a complex system that includes all the pieces needed to securely issue and manage digital certificates, including certificate revocation checking. There are several commercial providers of PKIs, as well as ways to deploy your own in-house PKI (as with MS AD Certificate Services).
Improving access to e-resources for users at the University of Derby: enhancing discovery systems with Library Plus 2.0

The Library at the University of Derby recently collaborated with EBSCO Information Services to co-create unique search interfaces and introduce a series of innovations aimed at improving the user experience. These innovations included a range of clearer icons linking through to full-text journal articles and abstract-only resources subscribed to by the Library, apps linking to additional online resource content and a fresh interface design and style. Billed as Library Plus 2.0, the project aimed to significantly improve the accessibility and visibility of the Library’s online resources, while providing an enhanced user experience shaped through consultation and engagement. This article looks at the impact of the Library Plus 2.0 changes and identifies improvements for future implementation. The work contributes towards the Library’s digital strategies and the continual enhancement of our core systems. The author presented this work at the University of Derby’s 13th Annual Learning &amp; Teaching Conference in July 2018.
Depth Extraction from a Single Image and Its Application

In this chapter, a method for the generation of depth map was presented.To generate the depth map from an image, the proposed approach involves application of a sequence of blurring and deblurring operations on a point to determine the depth of the point.The proposed method makes no assumptions with regard to the properties of the scene in resolving depth ambiguity in complex images.Since applications involving depth map manipulation can be achieved by obtaining all-infocus images through a deblurring operation and then blurring the obtained images, we have presented methods to derive all-in-focus images from our depth maps.Furthermore, 2D to 3D conversion can also be achieved from the estimated depth map.Some demonstrations show the performance and applications of the estimated depth map in this chapter.
Kernel Embedded Nonlinear Observational Mappings in the Variational Mapping Particle Filter

Recently, some studies have suggested methods to combine variational probabilistic inference with Monte Carlo sampling. One promising approach is via local optimal transport. In this approach, a gradient steepest descent method based on local optimal transport principles is formulated to deterministically transform point samples from an intermediate density to a posterior density. The local mappings that transform the intermediate densities are embedded in a reproducing kernel Hilbert space (RKHS). This variational mapping method requires the evaluation of the log-posterior density gradient and therefore the adjoint of the observational operator. In this work, we evaluate nonlinear observational mappings in the variational mapping method using two approximations that avoid the adjoint, an ensemble based approximation in which the gradient is approximated by the sample cross-covariances between the state and observational spaces the so-called ensemble space and an RKHS approximation in which the observational mapping is embedded in an RKHS and the gradient is derived there. The approximations are evaluated for highly nonlinear observational operators and in a low-dimensional chaotic dynamical system. The RKHS approximation is shown to be highly successful and superior to the ensemble approximation for non-Gaussian posterior densities.
Detection of Aedes aegypti larvae using single shot multibox detector with transfer learning

The flavivirus epidemiology has reached an alarming rate which haunts the world population including Malaysia. In fact, World Health Organization has proposed and practised many methods of vector control through environmental management, chemical and biological orientations but still cannot fully overcome the problem. This paper proposed a detection of Aedes Aegypti larvae in water storage tank using Single Shot Multibox Detector with transfer learning. The objective of the study was to acquire the training and the performance metrics of the detection. The detection was done using SSD with Inception_V2 through transfer learning. The experimental results revealed that the probability detection scored more than 80% accuracies and there was no false alarm. These results demonstrate the effectiveness of the model approach.
Analysis of the influence of multimedia network hybrid teaching method on college students learning ability in physical education

When using the existing methods to analyse college students' physical learning ability, there is no clear pertinence, students' interest is low, and physical learning ability cannot be effectively improved. A multimedia network hybrid teaching method based on multiple linear regression analysis is proposed. The factors that promote the hybrid teaching of multimedia network are analysed, and the multiple regression analysis model of mixed teaching method is obtained. The model is used to analyse the influence of multimedia network hybrid teaching method on college students' learning ability. The simulation results show that the satisfaction of the method is higher than 80%, which is much higher than the existing method; the student learning ability index is between 90 and 100, which is twice the existing method. It proves that the method of this paper has certain practicability and can effectively improve the physical learning ability of college students.
A Survey on Anomaly Detection and Diagnosis Problem in the Space System Operation

Spacecraft telemetry data is transferred from satellite to ground control station.The data contains not only information about health status of the satellite but also contains response messages to telecommand (telecommand data is send to spacecraft from ground control station) data.Telemetry data can indicate data error, communication link failure, sensor error, equipment and electronic devices failure.Safety and reliability are provided by telemetry and telecommand data.The most important subjects are safety and reliability for space mission.Therefore, telemetry data should be analyzed and take measures against to attack or unexpected situation.Various intelligent anomaly detection methods are proposed in the literature.Supervised/unsupervised (machine learning) anomaly detection approaches and data mining technology are the most used methods.This paper is a literature review for anomaly detection approaches in space system operation.Anomaly detection techniques have been investigated in the literature, but studies on space domain is quite limited.It is considered to contribute to literature in terms of that.
BYOD with Security

&lt;p class="IndexTerms"&gt;The concern of companies to keep sensitive data protected from improper access and information leaking has grown a lot. The constant cases of industrial espionage and information leakage regarding companies are an evidence of the need to apply strict information security policies, improve data protection and allow an auditing track. With the evolution of technology, the usage of personal mobile devices increased in organizations (BYOD - Bring Your Own Device), which allows the employees to use their own mobile devices at work. This paper addresses the current challenges faced by IT companies and teams in protecting access to this kind of information, and what strategies are used to mitigate, to track leaks, and reduce the misuse of documents in the organization. Considering the scenario evaluated, a framework with good Information Security practices based on the ISO 27002:2005 and the practical controls of the Center of Internet Security (CIS) is proposed, associating good practices with the needs of BYOD’s culture. The framework suggested in this paper reinforces the necessity for a standardization of the rules of information security in the process of adoption of BYOD’s culture, following the life cycle of the user with his personal mobile device in the company.&lt;/p&gt;&lt;p class="IndexTerms"&gt; &lt;/p&gt;&lt;p class="IndexTerms"&gt; &lt;/p&gt;
The Role of the User's Browsing and Query History for Improving MPC-generated Query Suggestions

In this paper we use the user&rsquo;s recent web browsing history in order to provide better query suggestions in an information retrieval system. We have built a Chrome browser plugin that collects each web page visited by a user and submits it to our query suggestion server for indexing, thus building a personal history profile for each user. We then analyze if future queries submitted by a user to the search engine can be predicted from web pages visited by that user in the past (i.e. his recent browsing history) or from queries submitted by that user in the past (i.e. his recent query history). The contribution of this paper is a method of using this personal history profile for reordering the query suggestions offered by Google when the user searches information on Google, moving query suggestions more relevant to the user&rsquo;s information need to the front positions in the Google provided query suggestions list. We have collected browsing history log data for over 4 months from several users who installed our Chrome plugin on their local computers and then we performed an offline evaluation test that shows that our personalized query suggestion system improves the MRR (i.e. Mean Reciprocal Rank) score of Google query suggestions by approximately 0.04 (i.e. improves Google&rsquo;s MRR score by 12 percents).
PERSEPSI SISWA SEKOLAH MENENGAH ATAS TENTANG PENGGUNAAN SMARTPHONE SEBAGAI MEDIA PEMBELAJARAN BAHASA INGGRIS

In her previous-related study the researcher discussed about the digital learning model aiming at educating Indonesian students and English language teaching and learning practitioners in increasing the listening and speaking skills in English (Wahyuni, 2017). Meanwhile in this research, the researcher focused on the students’ perception on the use of smartphone as an English learning media especially for Indonesian Secondary High School (SMA) students. This is the type of concurrent mix (combination) research whose qualitative method is more highly used than its quantitative method. Data collecting techniques in this research are survey study with Likert-scaled questionnaire, direct observation, and interview. The survey result then classified and ranked statistically to know the frequency level of the smartphone use in learning English as well as to encounter students’ perception on it.To present more comprehensive data and information, the research result then quantitatively illustrated in an appropriate chart or diagram, and qualitatively described in narrative form. The implication about the use of smart phone is presented as well to give more insightful view for the students or teachers about how to maximize the advantages of smart phone media in learning English.
Robust Encryption, Extended

Robustness is a notion often tacitly assumed while working with encrypted data. Roughly speaking, it states that a ciphertext cannot be decrypted under different keys. Initially formalized in a public-key context, it has been further extended to key-encapsulation mechanisms, and more recently to pseudorandom functions, message-authentication codes and authenticated encryption. In this work, we motivate the importance of establishing similar guarantees for functional encryption schemes, even under adversarially generated keys. Our main security notion is intended to capture the scenario where a ciphertext obtained under a master key (corresponding to Authority 1) is decrypted by functional keys issued under a different master key (Authority 2). Furthermore, we show there exist simple functional encryption schemes where robustness under adversarial key-generation is not achieved. As a secondary and independent result, we formalize robustness for digital signatures – a signature should not verify under multiple keys – and point out that certain signature schemes are not robust when the keys are adversarially generated. We present simple, generic transforms that turn a scheme into a robust one, while maintaining the original scheme's security. For the case of public-key functional encryption, we look into ciphertext anonymity and provide a transform achieving it.