Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.

Novel input-output prediction approach for biomass pyrolysis

Biomass pyrolysis to bio-oil is one of the promising sustainable fuels. In this work, relation between biomass feedstock element characteristic and pyrolysis process outputs was explored. The element characteristics considered in this study include moisture, ash, fix carbon, volatile matter, carbon, hydrogen, nitrogen, oxygen, and sulphur. A semi-batch fixed bed reactor was used for biomass pyrolysis with heating rate of 30 °C/min from room temperature to 600 °C and the reactor was held at 600 °C for 1 h before cooling down. Constant nitrogen flow rate of 5 L/min was provided for anaerobic condition. Rice husk, Sago biomass and Napier grass were used in the study to form different element characteristic of feedstock by altering mixing ratio. Comparison between each element characteristic to total produced bio-oil yield, aqueous phase bio-oil yield, organic phase bio-oil yield, higher heating value of organic phase bio-oil, and organic bio-oil compounds was conducted. The results demonstrate that process performance is associated with feedstock properties, which can be used as a platform to access the process feedstock element acceptance range to estimate the process outputs. Ultimately, this work evaluated the element acceptance range for proposed biomass pyrolysis technology to integrate alternative biomass species feedstock based on element characteristic to enhance the flexibility of feedstock selection.

A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

Az ügyfélszerzési mód hatásának vizsgálata a vevőelégedettségre és a lojalitásra a szervezeti piacon (Analyzing the impact of the customer acquisition mode to the customer satisfaction and loyalty on the corporate market – assessing the effect of recommendation with applying structural equation modelling)

A kutatás célja a marketingeszközök hosszú távú hatásának pontosabb megértése szervezetközi viszonylatban a vevőértékelési modellek egyik nehezen számszerűsíthető tényezője, az ajánlás hatásának vizsgálata által. A hatások elemzésére a strukturális egyenlőségek módszerét (Structural Equation Modelling) alkalmazta a szerző. Rámutatott, hogy az ajánlással szerzett ügyfelek elégedettebbek, lojálisabbak és gyakrabban ajánlják a vállalatot a más módon szerzett ügyfeleknél. Az összefüggések feltárása és bizonyítása különösen az ajánlás kumulatív hatása miatt jelentős. Az eredmények gyakorlati alkalmazásával lehetőség nyílik az ügyfélkör differenciáltabb, értékalapú szegmentációjára, amely pontosabb célcsoport-meghatározást lesz lehetővé, és hosszú távon hozzájárul a vállalat optimális ügyfélportfóliójának kialakításához. ______ The research is aimed at more precise understanding of longterm effects of marketing tools in business to business relations by analysing the impacts of recommendation potential, one of the hardly measurable factors of customer value concept. Structural Equation Modelling is applied for conducting effect analysis. The results show that customers acquired with recommendation are more satisfied, more loyal, and make more recommendation that other customer. These results are more interesting if we take the cumulative effect of recommendation in account. They provide bases for a more differentiated segmentation of customers, which results in a more accurate identification of target groups. In the long-run, the application of the customer-value concept considerably contributes to creating an optimal customer portfolio for companies.

Magyarország hét régiójának új gazdaságföldrajzi modellje – paraméterbecslés (The new economic-geography model of Hungary's seven regions - a parameter estimate)

Az új gazdaságföldrajz – amely napjaink egy igen népszerű közgazdaságtani tudományága – modelljének majdnem minden paramétere előállítható közvetlenül külső adatok segítségével. A helyettesítési rugalmassághoz azonban más módszerre van szükség. Puga [1999] által felvázolt új gazdaságföldrajzi modellt követve, egy regressziós egyenlettel megbecsülhetővé válik a kívánt paraméter, amit Magyarország hét régiójára vonatkozó béregyenlet becsléséből nyertünk. A helyettesítési rugalmasság értéke eltér a szakirodalomhoz képest, aminek magyarázata Magyarország fejlettségi szintjével állhat összefüggésben. ____ The model of the new economic geography - very popular material for economic study these days - allows almost every parameter to be presented directly with the aid of outside data. However, another method is required for substitution flexibility. With the new economic-geography model devised by Puga [1999], a regression equation allows an estimate to be made for the desired parameter, which yielded the wage equation for the six regions of Hungary. The value for substitution flexibility differs from that of the literature, the explanation for which may lie in Hungary's level of development.

On arterial contractility, energetic requirements of the cardiovascular system, and the formation of arterial sclerosis

The aorta has been viewed as a passive distribution manifold for blood whose elasticity allows it to store blood during cardiac ejection (systole), and release it during relaxation (diastole). This capacitance, or compliance, lowers peak cardiac work input and maintains peripheral sanguine irrigation throughout the cardiac cycle. The compliance of the human and canine circulatory systems have been described either as constant throughout the cycle (Toy et al. 1985) or as some inverse function of pressure (Li et al. 1990, Cappelo et al. 1995). This work shows that a compliance value that is higher during systole than diastole (equivalent to a direct function of pressure) leads to a reduction in the energetic input to the cardiovascular system (CV), even when accounting for the energy required to change compliance. This conclusion is obtained numerically, based on a 3-element lumped-parameter model of the CV, then demonstrated in a physical model built for the purpose. It is then shown, based on the numerical and physical models, on analytical considerations of elastic tubes, and on the analysis of arterial volume as a function of pressure measured in vivo (Armentano et al. 1995), that the mechanical effects of a presupposed arterial contraction are consistent with those of energetically beneficial changes in compliance during the cardiac cycle. Although the amount of energy potentially saved with rhythmically contracting arteries is small (mean 0.55% for the cases studied) the importance of the phenomenon lies in its possible relation to another function of the arterial smooth muscle (ASM): synthesis of wall matrix macromolecules. It is speculated that a reduction in the rate of collagen synthesis by the ASM is implicated in the formation of arteriosclerosis. ^

A non-linear discrete stochastic optimization model for Advanced Access patient appointment scheduling

Access to healthcare is a major problem in which patients are deprived of receiving timely admission to healthcare. Poor access has resulted in significant but avoidable healthcare cost, poor quality of healthcare, and deterioration in the general public health. Advanced Access is a simple and direct approach to appointment scheduling in which the majority of a clinic's appointments slots are kept open in order to provide access for immediate or same day healthcare needs and therefore, alleviate the problem of poor access the healthcare. This research formulates a non-linear discrete stochastic mathematical model of the Advanced Access appointment scheduling policy. The model objective is to maximize the expected profit of the clinic subject to constraints on minimum access to healthcare provided. Patient behavior is characterized with probabilities for no-show, balking, and related patient choices. Structural properties of the model are analyzed to determine whether Advanced Access patient scheduling is feasible. To solve the complex combinatorial optimization problem, a heuristic that combines greedy construction algorithm and neighborhood improvement search was developed. The model and the heuristic were used to evaluate the Advanced Access patient appointment policy compared to existing policies. Trade-off between profit and access to healthcare are established, and parameter analysis of input parameters was performed. The trade-off curve is a characteristic curve and was observed to be concave. This implies that there exists an access level at which at which the clinic can be operated at optimal profit that can be realized. The results also show that, in many scenarios by switching from existing scheduling policy to Advanced Access policy clinics can improve access without any decrease in profit. Further, the success of Advanced Access policy in providing improved access and/or profit depends on the expected value of demand, variation in demand, and the ratio of demand for same day and advanced appointments. The contributions of the dissertation are a model of Advanced Access patient scheduling, a heuristic to solve the model, and the use of the model to understand the scheduling policy trade-offs which healthcare clinic managers must make. ^

Reduced-parameter model of head-related transfer functions for synthesized spatial audio

Digital systems can generate left and right audio channels that create the effect of virtual sound source placement (spatialization) by processing an audio signal through pairs of Head-Related Transfer Functions (HRTFs) or, equivalently, Head-Related Impulse Responses (HRIRs). The spatialization effect is better when individually-measured HRTFs or HRIRs are used than when generic ones (e.g., from a mannequin) are used. However, the measurement process is not available to the majority of users. There is ongoing interest to find mechanisms to customize HRTFs or HRIRs to a specific user, in order to achieve an improved spatialization effect for that subject. Unfortunately, the current models used for HRTFs and HRIRs contain over a hundred parameters and none of those parameters can be easily related to the characteristics of the subject. This dissertation proposes an alternative model for the representation of HRTFs, which contains at most 30 parameters, all of which have a defined functional significance. It also presents methods to obtain the value of parameters in the model to make it approximately equivalent to an individually-measured HRTF. This conversion is achieved by the systematic deconstruction of HRIR sequences through an augmented version of the Hankel Total Least Squares (HTLS) decomposition approach. An average 95% match (fit) was observed between the original HRIRs and those re-constructed from the Damped and Delayed Sinusoids (DDSs) found by the decomposition process, for ipsilateral source locations. The dissertation also introduces and evaluates an HRIR customization procedure, based on a multilinear model implemented through a 3-mode tensor, for mapping of anatomical data from the subjects to the HRIR sequences at different sound source locations. This model uses the Higher-Order Singular Value Decomposition (HOSVD) method to represent the HRIRs and is capable of generating customized HRIRs from easily attainable anatomical measurements of a new intended user of the system. Listening tests were performed to compare the spatialization performance of customized, generic and individually-measured HRIRs when they are used for synthesized spatial audio. Statistical analysis of the results confirms that the type of HRIRs used for spatialization is a significant factor in the spatialization success, with the customized HRIRs yielding better results than generic HRIRs.

Physical model parameter optimisation for calibrated emulation of the Dallas Rangemaster Treble Booster guitar pedal

In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.

Produção de CDR a partir de resíduos industriais: caso de estudo da Recivalongo

A produção de combustível derivado de resíduos (CDR) resultou de uma decisão política que permitiu a instalação em Portugal de um significativo conjunto de processos, cuja avaliação técnico-económica e ambiental pode já ser feita. Este trabalho faz uma avaliação técnica e ambiental da linha de produção de CDR da Recivalongo. A avaliação técnica consistiu na análise dos caudais de material que entraram na linha de produção, na quantidade de CDR produzido, contabilizando também os gastos de recursos da linha (energia e materiais auxiliares). A avaliação da qualidade de CDR produzido a partir do ensaio laboratorial representou também uma parte muito significativa do trabalho produzido. A avaliação ambiental foi efetuada com base na metodologia da Avaliação de Ciclo de Vida (ACV). Os resultados obtidos permitiram concluir que o processo da Recivalongo transforma 69% do material de entrada, recuperando 2% em metais ferrosos e rejeitando para aterro a restante fração de 29%. As análises efetuadas ao CDR mostraram que apresenta um PCI compreendido entre 17 e 20 MJ/kg; o teor em cloro está compreendido entre 0,2 e 0,8% Conclui-se que neste processo o parâmetro mais difícil de controlar é o teor em cloro no CDR, pois existe uma grande diversidade de resíduos com grandes quantidades de cloro na sua constituição e que por muitas vezes são difíceis de identificar e/ou separar na primeira fase do tratamento dos resíduos. Da análise ciclo de vida efetuada à produção de CDR pode-se afirmar que esta operação de gestão de resíduos apresenta uma mais-valia quando comparada com a deposição dos resíduos em aterro, não sendo a diferença entre destinos tão significativa quanto o esperado. Desta avaliação pode concluir-se que a instalação operou muito abaixo da sua capacidade, sendo esta considerada uma das melhores linhas de produção de CDR a nível nacional.

PHC Production Management System Based on RFID

At present, in large precast concrete enterprises, the management over precast concrete component has been chaotic. Most enterprises take labor-intensive manual input method, which is time consuming and laborious, and error-prone. Some other slightly better enterprises choose to manage through bar-code or printing serial number manually. However, on one hand, this is also labor-intensive, on the other hand, this method is limited by external environment, making the serial number blur or even lost, and also causes a big problem on production traceability and quality accountability. Therefore, to realize the enterprise’s own rapid development and cater to the needs of the time, to achieve the automated production management has been a big problem for a modern enterprise. In order to solve the problem, inefficiency in production and traceability of the products, this thesis try to introduce RFID technology into the production of PHC tubular pile. By designing a production management system of precast concrete components, the enterprise will achieve the control of the entire production process, and realize the informatization of enterprise production management. RFID technology has been widely used in many fields like entrance control, charge management, logistics and so on. RFID technology will adopt passive RFID tag, which is waterproof, shockproof, anti-interference, so it’s suitable for the actual working environment. The tag will be bound to the precast component steel cage (the structure of the PHC tubular pile before the concrete placement), which means each PHC tubular pile will have a unique ID number. Then according to the production procedure, the precast component will be performed with a series of actions, put the steel cage into the mold, mold clamping, pouring concrete (feed), stretching, centrifugalizing, maintenance, mold removing, welding splice. In every session of the procedure, the information of the precast components can be read through a RFID reader. Using a portable smart device connected to the database, the user can check, inquire and management the production information conveniently. Also, the system can trace the production parameter and the person in charge, realize the traceability of the information. This system can overcome the disadvantages in precast components manufacturers, like inefficiency, error-prone, time consuming, labor intensity, low information relevance and so on. This system can help to improve the production management efficiency, and can produce a good economic and social benefits, so, this system has a certain practical value.

An investigation of environmental conditions experienced during the life of high-value wood components and products

Australian forest industries have a long history of export trade of a wide range of products from woodchips (for paper manufacturing), sandalwood (essential oils, carving and incense) to high value musical instruments, flooring and outdoor furniture. For the high value group, fluctuating environmental conditions brought on by changes in temperature and relative humidity, can lead to performance problems due to consequential swelling, shrinkage and/or distortion of the wood elements. A survey determined the types of value-added products exported, including species and dimensions packaging used and export markets. Data loggers were installed with shipments to monitor temperature and relative humidity conditions. These data were converted to timber equilibrium moisture content values to provide an indication of the environment that the wood elements would be acclimatising to. The results of the initial survey indicated that primary high value wood export products included guitars, flooring, decking and outdoor furniture. The destination markets were mainly located in the northern hemisphere, particularly the United States of America, China, Hong Kong, Europe (including the United Kingdom), Japan, Korea and the Middle East. Other regions importing Australian-made wooden articles were south-east Asia, New Zealand and South Africa. Different timber species have differing rates of swelling and shrinkage, so the types of timber were also recorded during the survey. Results from this work determined that the major species were ash-type eucalypts from south-eastern Australia (commonly referred to in the market as Tasmanian oak), jarrah from Western Australia, spotted gum, hoop pine, white cypress, black butt, brush box and Sydney blue gum from Queensland and New South Wales. The environmental conditions data indicated that microclimates in shipping containers can fluctuate extensively during shipping. Conditions at the time of manufacturing were usually between 10 and 12% equilibrium moisture content, however conditions during shipping could range from 5 (very dry) to 20% (very humid). The packaging systems incorporated were reported to be efficient at protecting the wooden articles from damage during transit. The research highlighted the potential risk for wood components to ‘move’ in response to periods of drier or more humid conditions than those at the time of manufacturing, and the importance of engineering a packaging system that can account for the environmental conditions experienced in shipping containers. Examples of potential dimensional changes in wooden components were calculated based on published unit shrinkage data for key species and the climatic data returned from the logging equipment. The information highlighted the importance of good design to account for possible timber movement during shipping. A timber movement calculator was developed to allow designers to input component species, dimensions, site of manufacture and destination, to see validate their product design.

Privacy in data publishing for tailored recommendation scenarios

Personal information is increasingly gathered and used for providing services tailored to user preferences, but the datasets used to provide such functionality can represent serious privacy threats if not appropriately protected. Work in privacy-preserving data publishing targeted privacy guarantees that protect against record re-identification, by making records indistinguishable, or sensitive attribute value disclosure, by introducing diversity or noise in the sensitive values. However, most approaches fail in the high-dimensional case, and the ones that don’t introduce a utility cost incompatible with tailored recommendation scenarios. This paper aims at a sensible trade-off between privacy and the benefits of tailored recommendations, in the context of privacy-preserving data publishing. We empirically demonstrate that significant privacy improvements can be achieved at a utility cost compatible with tailored recommendation scenarios, using a simple partition-based sanitization method.

Recomendr-entity recommendation based on ad-hoc dimensions

The growing availability and popularity of opinion rich resources on the online web resources, such as review sites and personal blogs, has made it convenient to find out about the opinions and experiences of layman people. But, simultaneously, this huge eruption of data has made it difficult to reach to a conclusion. In this thesis, I develop a novel recommendation system, Recomendr that can help users digest all the reviews about an entity and compare candidate entities based on ad-hoc dimensions specified by keywords. It expects keyword specified ad-hoc dimensions/features as input from the user and based on those features; it compares the selected range of entities using reviews provided on the related User Generated Contents (UGC) e.g. online reviews. It then rates the textual stream of data using a scoring function and returns the decision based on an aggregate opinion to the user. Evaluation of Recomendr using a data set in the laptop domain shows that it can effectively recommend the best laptop as per user-specified dimensions such as price. Recomendr is a general system that can potentially work for any entities on which online reviews or opinionated text is available.