Analysis and improvement of a construction permit approval process: A teaching case for developing business process development capabilities, targeting developing nations

With the increasing competitiveness in global markets, many developing nations are striving to constantly improve their services in search for the next competitive edge. As a result, the demand and need for Business Process Management (BPM) in these regions is seeing a rapid rise. Yet there exists a lack of professional expertise and knowledge to cater to that need. Therefore, the development of well-structured BPM training/ education programs has become an urgent requirement for these industries. Furthermore, the lack of textbooks or other self-educating material, that go beyond the basics of BPM, further ratifies the need for case based teaching and related cases that enable the next generation of professionals in these countries. Teaching cases create an authentic learning environment where complexities and challenges of the ‘real world’ can be presented in a narrative, enabling students to evolve crucial skills such as problem analysis, problem solving, creativity within constraints as well as the application of appropriate tools (BPMN) and techniques (including best practices and benchmarking) within richer and real scenarios. The aim of this paper is to provide a comprehensive teaching case demonstrating the means to tackle any developing nation’s legacy government process undermined by inefficiency and ineffectiveness. The paper also includes thorough teaching notes The article is presented in three main parts: (i) Introduction - that provides a brief background setting the context of this paper, (ii) The Teaching Case, and (iii) Teaching notes.

Learning through writing: Reconceptualising the research supervision process

This paper seeks to re-conceptualize the research supervision relationship. The literature has tended to view doctoral study in four ways: (i) as an exercise in self-management; (ii) as a research experience; (iii) as training for research, or; (iv) as an instance of student-centred learning. Although each of these approaches has their merits, they also suffer from conceptual weaknesses. This paper seeks to harness the merits — and minimize the disadvantages — by re-conceptualizing doctoral research as a ‘writing journey’. The paper utilizes the insights of new rhetoric in linguistic theory to defend a writing-centered conception of supervised research and offers some practical strategies on how it might be put into effect.

Validation-Based Sparse Gaussian Process Classifier Design

Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

A Novel, Balanced, and Energy-Efficient Training Method for Receive Antenna Selection

In receive antenna selection (AS), only signals from a subset of the antennas are processed at any time by the limited number of radio frequency (RF) chains available at the receiver. Hence, the transmitter needs to send pilots multiple times to enable the receiver to estimate the channel state of all the antennas and select the best subset. Conventionally, the sensitivity of coherent reception to channel estimation errors has been tackled by boosting the energy allocated to all pilots to ensure accurate channel estimates for all antennas. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS that transmits one extra pilot symbol that generates accurate channel estimates for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. We derive closed-form expressions for the proposed scheme's symbol error probability for MPSK and MQAM, and optimize the energy allocated to pilot and data symbols. Through an insightful asymptotic analysis, we show that the optimal solution achieves full diversity and is better than the conventional method.

Whose ETSIP? National and local ownership of Namibia's education and training sector improvement programme

Tämä työ tarkastelee kansallista ja paikallista omistajuutta Namibian opetussektorin kehittämisohjelmassa. Opetussektorin kehittämisohjelma ETSIP on 15-vuotinen sektoriohjelma vuosille 2005-2015 ja sen tavoitteena on edesauttaa Namibian kehittymistä tietoyhteiskunnaksi. Tutkimuksen tarkoituksena on selvittää miten kansallinen ja paikallinen omistajuus on toteutunut ETSIP prosessin aikana. Erityisesti pyritään selvittämään paikallistason opetussektorin virkamiesten näkemyksiä ETSIP prosessista, heidän roolistaan siinä ja siitä millaisia vaikuttamisen ja hallinnan mahdollisuuksia heillä on ollut prosessin aikana. Tutkimuksen lähtökohta on laadullinen ja lähestymistapa konstruktionistinen: tutkimus tarkastelee todellisuutta ihmisten kokemusten, näkemysten ja toiminnan kautta. Tutkimusaineisto koostuu haastatteluista, epävirallisista keskusteluista, lehtiartikkeleista ja ETSIP dokumenteista. Tutkimus osoittaa että kansallinen omistajuus on epämääräinen käsite sillä kansallisia toimijoita ja näkemyksiä on useita. Tutkimus vahvistaa Castel-Brancon huomion siitä, että omistajuutta on tarkasteltava kontekstissaan: muuttuvana ja kilpailtuna. ETSIPin rinnalle ollaan valmistelemassa uutta strategista ohjelmaa opetusministeriölle mikä saattaa muuttaa omistajuutta ETSIPiin. ETSIP dokumenttien omistajuusretoriikka myötäilee kansainvälisiä sitoumuksia avun vaikuttavuuden parantamiseksi mutta niistä puuttuu syvällisempi analyysi siitä, miten kansallinen ja paikallinen omistajuus toteutuisi käytännössä. Avunantajien näkemys omistajuudesta on suppea: omistajuus nähdään lähinnä sitoutumisena ennalta määrättyyn politiikkaohjelmaan. Haastatteluaineistosta nousee esiin Whitfieldin ja Frazerin jaottelu suppeista ja laajoista omistajuuskäsityksistä. Sitoutumista ETSIP ohjelmaan pidetään tärkeänä mutta riittämättömänä määritteenä omistajuudelle. Paikallisella tasolla sitoutuminen ETSIP ohjelman periaatteisiin ja tavoitteisiin on toteutunut melko hyvin mutta jos omistajuutta tarkastellaan laajemmin vaikutusvallan ja hallinnan käsitteiden kautta voidaan todeta että omistajuus on ollut heikkoa. Paikallisella tasolla ei ole ollut juurikaan vaikutusvaltaa ETSIP ohjelman sisältöön eikä mahdollisuutta hallita ohjelman toteutusta ja päättää siitä mitä hankkeita ohjelman kautta rahoitetaan. Tujanin demokraattisen omistajuuden käsite kuvaa tarvetta muuttaa ja laajentaa omistajuusajattelua huomioiden paikallisen tason paremmin. Tämä tutkimus viittaa siihen että omistajuuden toteutuminen paikallisella tasolla edellyttäisi institutionaalisen kulttuurin muutosta ja institutionaalisen legitimiteetin vahvistamista. Omistajuuden mahdollistamiseksi paikallisella tasolla tarvittaisiin poliittista johtajuutta, luottamusta, vastuullisuuden kulttuurin kehittämistä, tehokkaampaa tiedonjakoa, laajaa osallistumista, vuoropuhelua ja yhteistyötä. Ennen kaikkea tarvittaisiin paikallisen tason vaikutusvaltaa päätöksenteossa ja kontrollia resurssien käytöstä. Tälle muutokselle on selvä tarve ja tilaus.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

Oscillatory exchange bias and training effects in nanocrystalline Pr0.5Ca0.5MnO3

We report on exchange bias effects in 10 nm particles of Pr0.5Ca0.5MnO3 which appear as a result of competing interactions between the ferromagnetic (FM)/anti-ferromagnetic (AFM) phases. The fascinating new observation is the demonstration of the temperature dependence of oscillatory exchange bias (OEB) and is tunable as a function of cooling field strength below the SG phase, may be attributable to the presence of charge/spin density wave (CDW/SDW) in the AFM core of PCMO10. The pronounced training effect is noticed at 5 K from the variation of the EB field as a function of number of field cycles (n) upon the field cooling (FC) process. For n > 1, power-law behavior describes the experimental data well; however, the breakdown of spin configuration model is noticed at n >= 1. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.3696033]

Energy-efficient training for antenna selection in time-varying channels

Training for receive antenna selection (AS) differs from that for conventional multiple antenna systems because of the limited hardware usage inherent in AS. We analyze and optimize the performance of a novel energy-efficient training method tailored for receive AS. In it, the transmitter sends not only pilots that enable the selection process, but also an extra pilot that leads to accurate channel estimates for the selected antenna that actually receives data. For time-varying channels, we propose a novel antenna selection rule and prove that it minimizes the symbol error probability (SEP). We also derive closed-form expressions for the SEP of MPSK, and show that the considered training method is significantly more energy-efficient than the conventional AS training method.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Interdisciplinary experience in the Teacher Training College of Vitoria-Gasteiz: teaching profession module

[EN] The higher education regulation process in Europe, known as the Bologna Process, has involved many changes, mainly in relation to methodology and assessment. The paper given below relates to implementing the new EU study plans into the Teacher Training College of Vitoria-Gasteiz; it is the first interdisciplinary paper written involving teaching staff and related to the Teaching Profession module, the first contained in the structure of the new plans. The coordination of teaching staff is one of the main lines of work in the Bologna Process, which is also essential to develop the right skills and maximise the role of students as an active learning component. The use of active, interdisciplinary methodologies has opened up a new dimension in universities, requiring the elimination of the once componential, individual structure, making us look for new areas of exchange that make it possible for students' training to be developed jointly.

Freshwater prawn fry production and delivery process: key to sustainable aquaculture development for Bangladesh

This study was conducted to identify a functioning fingerlings production and delivery system for a sustainable aquaculture development. Data were collected from 234 respondents randomly sampled from a population of 600 fish farmers. Results indicated that farmer-to-farmer was the major source of fingerlings production and distribution system. Although this source accessed disadvantaged groups like the rural based, resource poor, less educated and women, it lacked knowledge on how to produce good quality fingerlings. These results suggest that a decentralized and privatized fingerlings production and delivery system should be promoted. For this system to operate effectively the aquaculture department should first identify potential zones for aquaculture growth and profit motivated fingerlings producers and distributors. Furthermore, the institutional mechanism through which farmer-to-farmer will operate should be identified and strengthened through short and long term training programmes. The government should support the system by providing guidelines for good quality fingerlings management; maintain brood stock parents and technical training in Bangladesh.