Controlled Vocabularies and Information Retrieval: 1918 Pandemic’s Scientific Literature as an Example

The role of controlled vocabularies in information retrieval is broadly recognized as a relevant feature. Besides, there is a standing demand that editors and databases should consider the effective introduction of controlled vocabularies in their procedures to index scientific literature. That is especially important because information retrieval is pointed out as a significant point to drive systematic literature review. Hence, a first question emerges: Are the controlled vocabularies at this moment considered? On the other hand, subject searching in the catalogs is complex mainly due to the dichotomy between keywords from authors versus keywords based on controlled vocabularies. Finally, there is some demand to unify the terminology related to health to make easier the medical history exploitation and research. Considering these features, this paper focuses on controlled vocabularies related to the health field and their role for storing, classifying, and retrieving relevant literature. The objective is knowing which role plays the controlled vocabularies related to the health field to index and retrieve research literature in data bases such as Web of Science (WoS) and Scopus. So, this exploratory research is grounded over two research questions: 1) Which are the terms considered in specific controlled vocabularies of the health field; and 2) How papers are indexed in relevant databases to be easily retrieved, considering keywords vs specific health’ controlled vocabularies? This research takes as fieldwork the controlled vocabularies related to health and the scientific interest for 1918 flu pandemic, also known equivocally as ‘Spanish flu’. This interest has been fostered by the emergence in the early 21st of epidemics of pneumonic diseases caused by virus. Searches about and with controlled vocabularies on WoS and Scopus databases are conducted. First results of this work in progress are surprising. There are different controlled vocabularies for the health field, into which the terms collected and preferred related to ‘1918 pandemic’ are identified. To summarize, ‘Spanish influenza epidemic’ or ‘Spanish flu’ are collected as not preferred terms. The preferred terms are: ‘influenza’ or ‘influenza pandemic, 1918-1919’. Although the controlled vocabularies are clear in their election, most of the literature about ‘1918 pandemic’ is retrievable either by ‘Spanish’ or by ‘1918’ disjunct, and the dominant word to retrieve literature is ‘Spanish’ rather than ‘1918’. This is surprising considering the existence of suitable controlled vocabularies related to health topics, and the modern guidelines of World Health Organization concerning naming of diseases that point out to other preferred terms. A first conclusion is the failure of using controlled vocabularies for a field such as health, and in consequence for WoS and Scopus. This research opens further research questions about which is the role that controlled vocabularies play in the instructions to authors that journals deliver to documents’ authors.

Fast and Robust Long-term Tracking with Effective Searching Model

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Searching for an Effective Marketing in the Food Supplement Industry in Japan

The market for "functional foods" and "foods with functional claims" that are effective in maintaining and improving health, has expanded year by year due to the entry of major food and beverage manufacturers following the introduction of the specified health food system in 1991 in Japan. To bring health claims related products or services to the market, it is necessary to let consumers to learn about these products or services; an effective marketing through advertising are important. This research proposes a framework for an effective advertisement medium for the food supplement industry by using survey data of 2,500 people.

Probabilistic Approach of Dealing with Uncertainties in Distributed Constraint Optimization Problems and Situation Awareness for Multi-agent Systems

In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Multi-Agent Searching Adaptation Using Levy Flight and Inferential Reasoning

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Emotional Association Theory as a Key to Proper Strategy Implementation

Emotional Association (EA) Theory deals with the psychological attachment of the employees to their employer as a focal way of awakening employees’ productivity, innovativeness, and creativity towards achieving a common cause within an organization. The objectives of this paper include: to comprehend the forms of motivation at workstation as provided by the Emotion Association Theory; to improve access to the skills relevant for a good working environment; to raise new skills through knowing the power to influence employees; to improve communication skills as well as researching current leaders and their leadership skills. The paper makes use of descriptive and intervention by examining the effect of motivation on employees. The method makes use of psychological EA theory that analyses the 3E leadership model to impact the ability to adopt the organization’s policy and employee productivity. In this case, the method will assess the workplace culture by assessing personal values and qualities that make master manager in organizations. In addition, the method will apply the theory to support the positive work engagement and its successful implementation to effectively influence employee productivity. The findings of this research showcase the significance motivating employees to increase their productivity as provided by the theory. Nonetheless, it improves sense of belonging among workers in a firm since it is employee-oriented. In addition, it works upon unification of workers within a workplace through mutual respect and empathy which promotes competence and policy implementation. Therefore, emotionally related qualities ignite motivation in workers.

A Bacterial Foraging Optimization Algorithm Applied to the Synthesis of Polyacrylamide Hydrogels

The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Researching International PhD Algerian Students’ Communication Challenges in Speaking When Discussing and Interacting with Their British Peers: A Researcher’s Interpretive Perspective through the Use of Semi-Structured Interview

This paper addresses the issue of the speaking challenges that the Algerian PhD students experience during their studies abroad, particularly in UK territory; more specifically, this study describes how these students may deal with such challenges and whether the cultural differences is one core reason in such dilemma or not. To this end, an understanding and interpretation of what actually encompasses both linguistic interference and cultural differences are required. Throughout the paper there is an attempt to explain the theoretical basis of the interpretive research and to theoretically discuss the pivotal use of the interview, as a data collection tool, in interpretive research. Thus, the central issue of this study is to frame the theoretical perspective of the interpretive research through the discussion of PhD Algerian’s communication and interaction challenges in the EFL context. This study is a corner stone for other research studies to further investigate the issue related to communication challenges because no specific findings will be pointed out in this research.

Information Literacy among Faculty and Students of Medical Colleges of Haryana, Punjab and Chandigarh

With the availability of diverse printed, electronic literature and web sites on medical and health related information, it is impossible for the medical professional to get the information he seeks in the shortest possible time. For all these problems information literacy is the only solution. Thus, information literacy is recognized as an important aspect of medical education. In the present study, an attempt has been made to know the information literacy skills of the faculty and students at medical colleges of Haryana, Punjab and Chandigarh. The scope of the study was confined to the 12 selected medical colleges of three States (Haryana, Punjab, and Chandigarh). The findings of the study were based on the data collected through 1018 questionnaires filled by the respondents of the medical colleges. It was found that Online Medical Websites (such as WebMD, eMedicine and Mayo Clinic etc.) were frequently used by 63.43% of the respondents of Chandigarh which is slightly more than Haryana (61%) and Punjab (55.65%). As well, 30.86% of the respondents of Chandigarh, 27.41% of Haryana and 27.05% of Punjab were familiar with the controlled vocabulary tool; 25.14% respondents of Chandigarh, 23.80% of Punjab, 23.17% of Haryana were familiar with the Boolean operators; 33.05% of the respondents of Punjab, 28.19% of Haryana and 25.14% of Chandigarh were familiar with the use and importance of the keywords while searching an electronic database; and 51.43% of the respondents of Chandigarh, 44.52% of Punjab and 36.29% of Haryana were able to make effective use of the retrieved information. For accessing information in electronic format, 47.74% of the respondents rated their skills high, while the majority of respondents (76.13%) were unfamiliar with the basic search technique i.e. Boolean operator used for searching information in an online database. On the basis of the findings, it was suggested that a comprehensive training program based on medical professionals information needs should be organized frequently. Furthermore, it was also suggested that information literacy may be included as a subject in the health science curriculum so as to make the medical professionals information literate and independent lifelong learners.

A Development of Creative Instruction Model through Digital Media

This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

The Two Layers of Food Safety and GMOs in the Hungarian Agricultural Law

The study presents the complexity of food safety dividing it into two layers. Beyond the basic layer of requirements, there is a more demanding higher level linked with quality and purity aspects. It would be important to give special prominence to both layers, given that massive illnesses are caused by foods even though officially licensed. Then the study discusses an exciting safety challenge stemming from the risks of genetically modified organisms (GMOs). Furthermore, it features legal case examples that illustrate how certain liability questions are solved or not yet decided in connection with the production of genetically modified crops. In addition, a special kind of land grabbing, more precisely land grabbing from non-GMO farming systems can also be noticed as well as a new phenomenon eroding food sovereignty. Coexistence, the state where organic, conventional, and GM farming systems are standing alongside each other is an unsuitable experiment that cannot be successful, because of biophysical reasons (such as cross-pollination). Agricultural and environmental lawyers both try to find the optimal solution. Agri-environmental measures are introduced as a special subfield of law maintaining also food safety. The important steps of agri-environmental legislation are aiming at the protection of natural values, the environmental media and strengthening food safety as well, practically the quality of agricultural products intended for human consumption. The major findings of the study focus on searching for the appropriate approach capable of solving the security and safety problems of food production. The most interesting concepts of the Hungarian national and EU food law legislation are analyzed in more detail with descriptive, analytic and comparative methods.

Interactive, Topic-Oriented Search Support by a Centroid-Based Text Categorisation

Centroid terms are single words that semantically and topically characterise text documents and so may serve as their very compact representation in automatic text processing. In the present paper, centroids are used to measure the relevance of text documents with respect to a given search query. Thus, a new graphbased paradigm for searching texts in large corpora is proposed and evaluated against keyword-based methods. The first, promising experimental results demonstrate the usefulness of the centroid-based search procedure. It is shown that especially the routing of search queries in interactive and decentralised search systems can be greatly improved by applying this approach. A detailed discussion on further fields of its application completes this contribution.

Behavioral Mapping and Post-Occupancy Evaluation of Meeting-Point Design in an International Airport

The meeting behavior is a pervasive kind of interaction, which often occurs between the passenger and the shuttle. However, the meeting point set up at the Taoyuan International Airport is too far from the entry-exit, often causing passengers to stop searching near the entry-exit. When the number of people waiting for the rush hour increases, it often results in chaos in the waiting area. This study tried to find out what is the key factor to promote the rapid finding of each other between the passengers and the pick-ups. Then we implemented several design proposals to improve the meeting behavior of passengers and pick-ups based on behavior mapping and post-occupancy evaluation to enhance their meeting efficiency in unfamiliar environments. The research base is the reception hall of the second terminal of Taoyuan International Airport. Behavioral observation and mapping are implemented on the entry of inbound passengers into the welcome space, including the crowd distribution of the people who rely on the separation wall in the waiting area, the behavior of meeting and the interaction between the inbound passengers and the pick-ups. Then we redesign the space planning and signage design based on post-occupancy evaluation to verify the effectiveness of space plan and signage design. This study found that passengers ignore existing meeting-point designs which are placed on distant pillars at both ends. The position of the screen affects the area where the receiver is stranded, causing the pick-ups to block the passenger's moving line. The pick-ups prefer to wait where it is easy to watch incoming passengers and where it is closest to the mode of transport they take when leaving. Large visitors tend to gather next to landmarks, and smaller groups have a wide waiting area in the lobby. The location of the meeting point chosen by the pick-ups is related to the view of the incoming passenger. Finally, this study proposes an improved design of the meeting point, setting the traffic information in it, so that most passengers can see the traffic information when they enter the country. At the same time, we also redesigned the pick-ups desk to improve the efficiency of passenger meeting.

CookIT: A Web Portal for the Preservation and Dissemination of Traditional Italian Recipes

Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Searching for Forensic Evidence in a Compromised Virtual Web Server against SQL Injection Attacks and PHP Web Shell

SQL injection is one of the most common types of attacks and has a very critical impact on web servers. In the worst case, an attacker can perform post-exploitation after a successful SQL injection attack. In the case of forensics web servers, web server analysis is closely related to log file analysis. But sometimes large file sizes and different log types make it difficult for investigators to look for traces of attackers on the server. The purpose of this paper is to help investigator take appropriate steps to investigate when the web server gets attacked. We use attack scenarios using SQL injection attacks including PHP backdoor injection as post-exploitation. We perform post-mortem analysis of web server logs based on Hypertext Transfer Protocol (HTTP) POST and HTTP GET method approaches that are characteristic of SQL injection attacks. In addition, we also propose structured analysis method between the web server application log file, database application, and other additional logs that exist on the webserver. This method makes the investigator more structured to analyze the log file so as to produce evidence of attack with acceptable time. There is also the possibility that other attack techniques can be detected with this method. On the other side, it can help web administrators to prepare their systems for the forensic readiness.

Dynamic Measurement System Modeling with Machine Learning Algorithms

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Evidence Based Practice for Oral Care in Children

As far as is known, general nursing care practices do not include specific evidence-based practices related to oral care in children. This study aimed to evaluate the evidence based nursing practice for oral care in children. This article is planned as a review article by searching the literature in this field. According to all age groups and the oral care in various specific situations located evidence in the literature were examined. It has been determined that the methods and frequency used in oral care practices performed by nurses in clinics differ from one hospital to another. In addition, it is seen that different solutions are used in basic oral care, oral care practices to prevent ventilator-associated pneumonia and evidence-based practice in mucositis management in children. As a result, a standard should be established in oral care practices for children and education for children is recommended.

Weighted-Distance Sliding Windows and Cooccurrence Graphs for Supporting Entity-Relationship Discovery in Unstructured Text

The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

An Alternative and Complementary Medicine Method in Vulnerable Pediatric Cancer Patients: Yoga

Pediatric cancer patients experience multiple distressing, challenges, physical symptom such as fatigue, pain, sleep disturbance, and balance impairment that continue years after treatment completion. In recent years, yoga is often used in children with cancer to cope with these symptoms. Yoga practice is defined as a unique physical activity that combines physical practice, breath work and mindfulness/meditation. Yoga is an increasingly popular mind-body practice also characterized as a mindfulness mode of exercise. This study aimed to evaluate the impact of yoga intervention of children with cancer. This article planned searching the literature in this field. It has been determined that individualized yoga is feasible and provides benefits for inpatient children, improves health-related quality of life, physical activity levels, physical fitness. After yoga program, children anxiety score decreases significantly. Additionally, individualized yoga is feasible for inpatient children receiving intensive chemotherapy. As a result, yoga is an alternative and complementary medicine that can be safely used in children with cancer.

3D-Vehicle Associated Research Fields for Smart City via Semantic Search Approach

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.