nils-herrmann/clean_scirepeval huggingface dataset:
Prediction of Optimum Combination of Eudragit RS/Eudragit RL/Ethyl Cellulose Polymeric Free Films Based on Experimental Design for Using as a Coating System for Sustained Release Theophylline Pellets.
Venue: Advanced pharmaceutical bulletin

The physicochemical properties of free films made from different mixtures of sustained release polymers were investigated, and an optimum formulation coating on drug containing pellets, based on the study of free film was evaluated.  In order to determine the effect of different variables on the permeability and swelling of films and procedure optimization, the experimental design was fulfilled based on the statistical method of a 3(3) full factorial design, and according to this method 27 formulations were prepared. The films were prepared using casting solvent evaporation method. Water vapor permeability, the swelling and permeability of free films in both acidic and buffer media, were carried out. Then, the pellets containing theophylline were coated with the optimum formulation.  The results of this study demonstrated that an increase in the free film thickness and Eurdragit RS ratio in films lowered the water vapor transmission (WVT) the swelling and the permeability of all formulations, while an increase in the quantity of ethylcellulose, up to a specific ratio (approximately 40% decreased the permeability and swelling. The most optimum free film formulation was made up of 60% Eudragit RS and 40% ethylcellulose.  Pellets coated with a 10% coating level of ethylcellulose and Eudragit RS (4:6) showed suitable release properties and could serve as a favorable sustained release system for theophylline.
The Dark Side of Defence: Masculinities and Violence in the Military

Militaries are institutions of violence. This chapter considers the dark side of military violence: violence within the military. While many criminological studies have attended to the violence and crime of, and within, environments of war, the study of the source of that violence, the military institution, has been neglected. This chapter draws upon the criminological literature of the dark side of organisations to argue violence within the military: hazing, brutalisation, and sexual assault of, and between service personnel, are a structured element of militarism. This is predominantly male violence and crime. By drawing upon critical gender studies and critical theory, the phenomenon of male violence within the military is considered along three key themes: the scission of civil and military, the production of violent subjectivities through military training, and the fraternal character of military masculinities and military organisation.
Effect of dietary inclusion of palm kernel meal on feed intake, growth and body composition of Nile Tilapia, Oreochromis niloticus reared in concrete tanks in Togo

An experiment was conducted to determine the effect of inclusion of palm kernel meal on feed intake, growth and body composition of Nile tilapia Oreochromis niloticus reared in concrete tanks. Fingerlings of fish with an average initial weight 5.18 0.06 g were fed five isonitrogenous diets (R0, R1, R2, R3 and R4) containing respectively 0% 10% 20% 30% and 40% of palm kernel meal. These diets were compared with a commercial fish feed (Raanan) all about 32% After 8 weeks of experiment the final body weight varied between 25.75 g and 38.18 g according to the tested treatments. The best growth rate and food conversion ratio were obtained by feed containing 30% and 40% of palm kernel meal, with respective specific growth rate (SGR) of 3.35%/d and 3.08%/d and food conversion ratio (FCR) of 1.67 and 2.00 against a SGR of 3.58%/d and a FCR of 1.53 obtained with commercial food (RC) This successful test which allowed determining the optimal dietary inclusion of palm kernel meal at 30% in Tilapia on growing feed will be pursued by nutritional improvement tests of this ingredient in order to have a performed feed for Tilapia rearing in Togo.
Impact assessment of climate change and human activities on net runoff in the Yellow River Basin from 1951 to 2012

Runoff in the Yellow River Basin (YRB) has changed constantly during the past six decades. This study investigates the features of variations in runoff increment in the YRB and evaluates the impact of climate change and human activities on the mean annual net runoff. Residual analysis based on double mass curves (RA DMC) was performed to quantitatively assess the separate contributions of climate change and human activities to the changes in net runoff. There was a significant downward trend in annual net runoff for each of the Yellow River sub basins. For the basin as a whole, net runoff decreased at a rate of 0.721 x 10 9 m 3 yr 1 with the upper, middle, and lower sub basins separately accounting for 28.4% 40.5% and 31.1% of the decrease. Human activities were responsible for more than 90% of the change in runoff in each separate sub basin between 1960 and 2012. For the entire YRB, 91.7% of the change in net runoff from baseline was attributed to human activities. This indicates that human activities have become the dominant factor in net runoff changes in the Yellow River Basin. Among the upper, middle, and lower reaches, the effect of human activities was greatest in the lower reaches.
Toward an Efficient Website Fingerprinting Defense
Venue: ESORICS

Website Fingerprinting attacks enable a passive eavesdropper to recover the user's otherwise anonymized web browsing activity by matching the observed traffic with prerecorded web traffic templates. The defenses that have been proposed to counter these attacks are impractical for deployment in real world systems due to their high cost in terms of added delay and bandwidth overhead. Further, these defenses have been designed to counter attacks that, despite their high success rates, have been criticized for assuming unrealistic attack conditions in the evaluation setting. In this paper, we propose a novel, lightweight defense based on Adaptive Padding that provides a sufficient level of security against website fingerprinting, particularly in realistic evaluation conditions. In a closed world setting, this defense reduces the accuracy of the state of the art attack from 91 to 20 while introducing zero latency overhead and less than 60 bandwidth overhead. In an open world, the attack precision is just 1 and drops further as the number of sites grows.
Low profile scalable phased array antenna at Ku band for mobile satellite communications
Venue: 2016 IEEE International Symposium on Phased Array Systems and Technology (PAST)

This paper discusses the design of an 8x8 phased array antenna tile for Ku band mobile satellite communications. The array has low profile, high gain, and wide angle scanning properties. The design steps and electromagnetic analysis of a dual polarized radiating antenna element and an 8x8 array tile comprised of these radiating elements are presented. The array structure makes it possible for satellite communication (SATCOM) terminals with compact sizes, because the whole front end might be on the same multilayer printed circuit board (PCB) With a compact geometry and 25% bandwidth, the array promises an excellent performance for satellite communication applications. The radiation characteristics and other array parameters are evaluated with respect to the application requirements.
IRobot: Teaching the Basics of Artificial Intelligence in High Schools
Venue: AAAI

Profound knowledge about Artificial Intelligence (AI) will become increasingly important for careers in science and engineering. Therefore an innovative educational project teaching fundamental concepts of AI at high school level will be presented in this paper. We developed an AI course covering major topics (problem solving, search, planning, graphs, data structures, automata, agent systems, machine learning) which comprises both theoretical and hands on components. A pilot project was conducted and empirically evaluated. Results of the evaluation show that the participating pupils have become familiar with those concepts and the various topics addressed. Results and lessons learned from this project form the basis for further projects in different schools which intend to integrate AI in future secondary science education.
Towards a Prescriptive Theory of Dynamic Capabilities: Connecting Strategic Choice, Learning, and Competition

The field of strategy has mounted an enormous effort to understand, define, predict, and measure how organizational capabilities shape competitive advantage. While the notion that capabilities influence strategy dates back to the work of Andrews (1971) attempts to formalize a "capabilities based" approach to strategy only began to take shape in the past twenty years. In particular, the publication of Teece and Pisano (1994) Teece, Pisano, and Shuen (1997) and Eisenhart and Martin (2000) works on "dynamic capabilities" triggered a flood of debate and discussion on the topic. Unfortunately, the literature on dynamic capabilities has become mired in endless debates about definitions and has engaged in an elusive search for properties that make organizations adaptable. This paper argues that the research program on dynamic capabilities needs to be reset around the fundamental strategic problem facing firms: how to identify and select capabilities that lead to competitive advantage. To this end, the paper develops a framework that attempts to connect firms' capability search strategies with their strategies in product markets. It frames firms' capability search strategies as choices among different types of capability enhancing investments. The key distinguishing feature of capabilities in this framework is their degree of fungibility: capabilities span a continuum ranging from highly general purpose (e.g. quality management) to highly market specific (e.g. knowing how to manufacture an airplane wing) To illustrate the potential of the framework to shed new light on traditional strategy questions, the paper applies the framework to explore some unexplained features of Penrosian diversification strategies. The paper concludes by suggesting a research agenda for dynamic capabilities.
Unsupervised Learning of Audio Segment Representations using Sequence to sequence Recurrent Neural Networks

Representing audio segments expressed with variablelength acoustic feature sequences as fixed length feature vectors is usually needed in many speech applications, including speaker identification, audio emotion classification and spoken term detection (STD) In this paper, we apply and extend sequence to sequence learning framework to learn representations for audio segments without any supervision. The model we used is called Sequence to sequence Autoencoder (SA) which consists of two RNNs equipped with Long Short Term Memory (LSTM) units: the first RNN acts as an encoder that maps the input sequence into a vector representation of fixed dimensionality, and the second RNN acts as a decoder that maps the representation back to the input sequence. The two RNNs are then jointly trained by minimizing the reconstruction error. We further propose Denoising Sequence to sequence Autoencoder (DSA) that improves the learned representations. The vector representations learned by SA and DSA are shown to be very helpful for query by example STD. The experimental results have shown that the proposed models achieved better retrieval performance than using audio segment representation designed heuristically and the classical Dynamic Time Warping (DTW) approach.
Attempted Serial Neonaticides: Case Report and a Brief Review of the Literature
Venue: Journal of forensic sciences

Neonaticide is an infant murder occurring on the day of birth. The case reports found in the literature are often focused on the mother as the agent in the context of pregnancy denial, dissociative symptoms, or psychosis. However, this report describes a rare case of attempted serial neonaticides, in which the acts were committed by a nurse at the nursery of a referral hospital in Brazil. The authors describe a forensic psychiatric evaluation for criminal responsibility and correlate the information from this particular case with relevant forensic themes, namely neonaticide, Munchausen by proxy syndrome, and serial healthcare killers.
Question answering system for factoid based question
Venue: 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)

Objective of question answering system (QA) is to generate concise answer of arbitrary question asked in natural language. This kind of information retrieval is required with growth of digital information. Analysis of natural language is complex task. Previously QAS were developed for specific domain and have limited efficiency. Present QAS Target on types of question commonly asked by users, characteristics of data source and correct answer generated. Our aim is to build web scale QA system. Early QA system are based on rewriting various kind of rules and pattern generation methods for finding answer paragraph and for answer extraction. Most of QA system before answer extraction do question classification for predicting entity type of answer of question. In this paper we deals with open domain factoid based question. Li and Roth (2002) classify questions into 6 coarse classes and 50 fine classes but it deals with limited classes of question. But we have classified question into 5 categories only and use the advance search engine technology and growth of web for QA system.
Measuring customer experience in situ: The link between appraisals, emotions and overall assessments

Customer experience is frequently researched using one off recall studies, missing the opportunity to assess the momentary fluctuations associated with consumption in real time. To address this gap, this study investigates how specific experience appraisals of an event affect emotions at different points in time, as well as determining how these appraisals contribute to overall satisfaction, recommendation, and repeat visitation. Fifty one event goers report their experiences on four occasions (three during and one post event) Results show appraisals of having fun predict feelings of joy at each of the three sampling periods, whereas appraisals of sensory experience predict feelings of inspiration. Overall, sensory appraisals at Time 2 and appraisals of fun at Time 3 are associated with higher ratings of recommendation and repeat visitation. This research extends the understanding of customer experience by demonstrating the differential role of appraisals and emotions in real time and the flow on effects to post experience assessments.
Recent developments in identifying and quantifying emotions during food consumption.
Venue: Journal of the science of food and agriculture

Emotions and the consumption of food and beverages are inextricably intertwined. As the fields of sensory and consumer science seek to better conceptualize the consumer experience, interest in emotion measurement is growing. Emotions can provide key information to differentiate between products and predict consumer choice as well as give more detail about product perception. There are several emotion measurement instruments, including physiological methods and facial recognition, self reported verbal emotion measurement and self reported visual emotion measurement. This review discusses the purpose of measuring emotions, what is the definition of an emotion, what different instruments are available, and touches upon some promising research to deepen the connection between food and emotions.
A Multiagent Competitive Gaming Platform to Address Societal Challenges
Venue: MIS Q.

The shift toward sustainable electricity systems is one of the grand challenges of the 21st century. Decentralized production from renewable sources, electric mobility, and related advances are at odds with traditional power systems where central, large scale generation of electricity follows inelastic consumer demand. Information systems innovations can enable new forms of dynamic electricity trading that leverage real time consumption information and that use price signals to incentivize sustainable consumption behaviors. However, the best designs for these innovations, and the societal implications of different design choices, are largely unclear. We are addressing these challenges through the Power Trading Agent Competition (Power TAC) a competitive gaming platform on which numerous research groups now jointly devise, benchmark, and improve IS based solutions to the sustainable electricity challenge. Based on the Power TAC community's results, we give preliminary empirical evidence for the efficacy of competitive gaming platforms, and for the community's contributions toward resolving the sustainable electricity challenge.
Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics
Venue: MIS Q.

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex sociotechnical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating these problems requires research methods that scale beyond the traditional areas of inquiry of information systems (IS) individuals, organizations, and markets and that deliver solutions in addition to insights. We describe an approach to address these challenges through competitive benchmarking (CB) a novel research method that helps interdisciplinary research communities tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS based solutions.
Training feedforward neural networks using multi verse optimizer for binary classification problems
Venue: Applied Intelligence

This paper employs the recently proposed nature inspired algorithm called Multi Verse Optimizer (MVO) for training the Multi layer Perceptron (MLP) neural network. The new training approach is benchmarked and evaluated using nine different bio medical datasets selected from the UCI machine learning repository. The results are compared to five classical and recent evolutionary metaheuristic algorithms: Genetic Algorithm (GA) Particle Swarm Optimization (PSO) Differential Evolution (DE) FireFly (FF) Algorithm and Cuckoo Search (CS) In addition, the results are compared with two well regarded conventional gradient based training methods: the conventional Back Propagation (BP) and the Levenberg Marquardt (LM) algorithms. The comparative study demonstrates that MVO is very competitive and outperforms other training algorithms in the majority of datasets in terms of improved local optima avoidance and convergence speed.
Optimization of Test Case Generation using Genetic Algorithm (GA)
Venue: ArXiv

provides means pertaining to assuring software performance. The total aim of software industry is actually to make a certain start associated with high quality software for the end user. However, associated with software testing has quite a few underlying concerns, which are very important and need to pay attention on these issues. These issues are effectively generating, prioritization of test cases, etc. These issues can be overcome by paying attention and focus. Solitary of the greatest Problems in the software testing area is usually how to acquire a great proper set associated with cases to confirm software. Some other strategies and also methodologies are proposed pertaining to shipping care of most of these issues. Genetic Algorithm (GA) belongs to evolutionary algorithms. Evolutionary algorithms have a significant role in the automatic test generation and many researchers are focusing on it. In this study explored software testing related issues by using the GA approach. In addition to right after applying some analysis, better solution produced, that is feasible and reliable. The particular research presents the implementation of GAs because of its generation of optimized test cases. Along these lines, this paper gives proficient system for the optimization of test case generation using genetic algorithm.
Generating test case for algebraic specification based on Tabu search and genetic algorithm
Venue: Cluster Computing

To improve the effectiveness of generating test case for algebraic specification, an approach for generating test cases based on tabu search and genetic algorithm (Tabu GA) is presented. A prototype tool CASCATT (Common Algebraic Specification based Class, Component and Web service Automatic Testing Tool) is implemented based on Tabu GA, which tests Class, Component and Web Service based on algebraic specification described by CASOCC WS (Common Algebraic Specification of Components, Classes and Web service) language. The experiments results show the testing method is better effective, comparing with the existed random method in algebraic testing tool CASCAT (Common AS based Component Automatic Testing) which generated test case from random data rewriting technology.
Software Test Case Reduction using Genetic Algorithm A Modified Approach

Software test cases play an important role in Software Testing. A lot of test cases are developed while designing test cases that are of no use or redundant in nature. These types of test cases increase the effort and cost involved in testing and results in decrease of software testing efficiency. In this paper, a Genetic Algorithm based methodology has been proposed which can significantly reduce the test suite and leads to optimization of the efficiency of software testing. The testing efficiency can be increased by identifying the most critical paths. The proposed Genetic Algorithm based approach select the software path clusters that are weighted in accordance with the criticality of the path. Proposed algorithm has been evaluated by applying simple Genetic Algorithm and Fitness Scaling on a case study. GA with Fitness scaling helps in improving the efficiency of software testing by effectively reducing software test cases.