Volunteered geographic information (VGI) platforms often suffer from redundant submissions, as contributors tend to create new reports rather than update existing ones—partly due to the effort required to locate and examine relevant prior entries. This study introduces Tell2Find, a large language model (LLM)-powered agent designed to support report retrieval and reuse during mobile crowdsourcing tasks. We conducted a study comparing Tell2Find with a traditional filter-based tool and a hybrid version combining both. Users with access to Tell2Find were more likely to examine existing reports before acting, resulting in more updates to prior reports and lower redundancy. Qualitatively, participants highlighted Tell2Find’s advantages in reducing the effort of matching reports, improving convenience in mobile contexts, and encouraging engagement with prior data due to more relevant suggestions. However, we also observed friction points: user trust around the system’s opaque matching logic and uncertainty about input phrasing occasionally led to disengagement with Tell2Find.

The popularity of task-oriented chatbots is constantly growing, but smooth conversational progress with them remains profoundly challenging. In recent years, researchers have argued that chatbot systems should include guidance for users on how to converse with them. Nevertheless, empirical evidence about what to place in such guidance, and when to deliver it, has been lacking. Using a mixed-methods approach that integrates results from a between-subjects experiment and a reflection session, this paper compares the effectiveness of eight combinations of two guidance types (example-based and rule-based) at four guidance timings (service-onboarding, task-intro, after-failure, and upon-request), as measured by users’ task performance, improvement on subsequent tasks, and subjective experience. It establishes that each guidance type and timing has particular strengths and weaknesses, thus that each type/timing combination has a unique impact on performance metrics, learning outcomes, and user experience. On that basis, it presents guidance-design recommendations for future task-oriented chatbots.

A new computation-efficient parallel prefix algorithm for message-passing multicomputers is presented. The algorithm uses only half-duplex communications. It provides the flexibility of choosing parameter values for either fewer computation time steps or fewer communication time steps to achieve the minimal running time based on the ratio of the time required by a communication step to the time required by a computation step. Thus, under certain conditions, the new algorithm can run faster than previous ones for the same multicomputer model.

Prefix computation is used in various areas and is considered as a primitive operation. Parallel prefix circuits are parallel prefix algorithms on the combinational circuit model. The depth of a prefix circuit is a measure of its processing time; smaller depth implies faster computation. The size of a prefix circuit is the number of operation nodes in it. Smaller size implies less power consumption, less VLSI area, and less cost. A prefix circuit with n inputs is depth-size optimal if its depth plus size equals 2 n − 2. A circuit with a smaller fan-out is in general faster and occupies less VLSI area. To be of practical use, the depth and fan-out of a prefix circuit should be small. In this paper, a family of depth-size optimal, parallel prefix circuits with fan-out 2 is presented. This family of prefix circuits is easier to construct and more amenable to automatic synthesis than two other families of the same type, although the three families have the same minimum depth among all depth-size optimal prefix circuits with fan-out 2. The balanced structure of the new family is also a merit.

Given n values /spl nu/(0), /spl nu/(1), ..., /spl nu/(n-1) and an associative binary operation, denoted by o, the prefix problem is to compute the n prefixes /spl nu/(0) o /spl nu/(1) o...0 /spl nu/(i), 0/spl les/i/spl les/n-1. We are interested in prefix computation on message-passing fully connected multicomputers, in which each processor can only send or receive a message to or from any other processor in a communication step, in as few communication steps as possible. An algorithm is presented to solve the prefix problem on a system of n processors in no more than [1.44 log/sub 2/ n]+1 communication steps. Then, to explore the possibility of obtaining a faster algorithm, a class of algorithms is presented, It is shown that the algorithm in this class requiring the fewest communication steps is equivalent to the first algorithm presented. An algorithm using p

A parallel algorithm is presented for generation of long sorted runs as the first phase of sorting a large file. It can generate runs of length about 2mp + 2 on a unidirectional linear array of p processors each with a heap of size m. Internal computations can be completely overlapped with I/O, and almost only disk read time is required. Experiments with the algorithm and its variations have been conducted. The results show that all the versions can generate longer runs than a previous algorithm run on a bidirectional linear array.

A balanced parallel algorithm to sort a sequence of items on a linear array of processors is presented. The length of the sequence may be small to arbitrarily large. For a short sequence, the output of the sorted sequence begins at the step following the last input of the whole sequence. For an arbitrarily long sequence, the time complexity is optimal under realistic hardware conditions. A variation of the algorithm is also introduced. Both algorithms require far less local memory than that required by a different approach of balanced computation. Any number of balanced processors can be connected to deliver more computing power without increasing the memory size of each processor.>

A low-delay code-excited linear prediction (LD-CELP) speech coder which is expected to be standardized in 1992 as a CCITT G Series Recommendation for universal applications of speech coding at 16 kb/s is presented. The coder achieves a one-way coding delay of less than 2 ms by making both the LPC predictor and the excitation gain backward-adaptive and by using a small excitation vector size of five samples. The official CCITT laboratory tests revealed that the speech quality of this 16 kb/s LD-CELP coder is either equivalent to or better than that of the CCITT G.721 standard 32-kb/s ADPCM coder for almost all conditions tested. A description of the LD-CELP algorithm, its implementation on the DSP32C for CCITT testing, and performance results from these tests are presented.>

On sequential machines, most internal sorting algorithms can sort no more than m items using a memory of size m. However, sorting with a heap can produce sorted sequences, called runs, of length about twice the heap size. A second advantage of sorting with a heap is that data I/O and the heap restructuring can be performed concurrently to reduce the sorting time. The third advantage is that it can even sort an arbitrarily large file in one pass if the file satisfies a certain ordering condition. The authors present an algorithm running on a linear array to obtain the above advantages. Specifically, the algorithm can produce runs of length about 2(m+2)p on a linear array of p PEs each with a heap of size m, and can overlap I/O with internal operations. In addition, it can completely sort an arbitrarily large file in one pass providing no item in the file has (m+2)p larger items before it. The algorithm can be modified to perform (mp+2p)-way merges. The authors have also estimated the optimal heap size in each PE for the minimum sorting time.>

The authors describe the algorithm modifications they have made in order to make the LD-CELP (low-delay code-excited linear prediction) algorithm suitable for 16 bit fixed-point implementation. They replaced T.P Barnwell's recursive windowing method (1981) by a novel hybrid which is partially recursive and partially nonrecursive. This method avoided the dynamic range problem and the double-precision arithmetic that would otherwise have been required. A fourth-order LPC filter was cascaded at the output of the original 50th-order LPC filter. This filter effectively reduced the spectral dynamic range of the output of the 50th-order LPC filter, therefore alleviating the ill-conditioning problem of the 50th-order LPC analysis. Although the algorithm of J. LeRoux and C. Gueguen (1979) was believed to be better suited for fixed-point arithmetic than Durbin's recursion (see L.R. Rabiner and R.W. Schafer, 1978), this was not necessarily true for the two-stage cascaded LPC filter used. Fixed-point simulation showed that the speech quality of the modified fixed-point LD-CELP algorithm was essentially the same as that of the original floating-point LD-CELP algorithm.>